diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ARPESView.fig b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ARPESView.fig new file mode 100644 index 0000000..74081b5 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ARPESView.fig differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ARPESView.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ARPESView.m new file mode 100644 index 0000000..0b7b89b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ARPESView.m @@ -0,0 +1,1635 @@ +function varargout = ARPESView(varargin) +% ARPESVIEW M-file for ARPESView.fig +% ARPESVIEW, by itself, creates a new ARPESVIEW or raises the existing +% singleton*. +% H = ARPESVIEW returns the handle to a new ARPESVIEW or the handle to +% the existing singleton*. +% ARPESVIEW('CALLBACK',hObject,eventData,handles,...) calls the local +% function named CALLBACK in ARPESVIEW.M with the given input arguments. +% ARPESVIEW('Property','Value',...) creates a new ARPESVIEW or raises the +% existing singleton*. Starting from the left, property value pairs are +% applied to the GUI before EasyLineSetup_OpeningFunction gets called. An +% unrecognized property name or invalid value makes property application +% stop. All inputs are passed to ARPESView_OpeningFcn via varargin. +% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one +% instance to run (singleton)". +% See also: GUIDE, GUIDATA, GUIHANDLES +% Edit the above text to modify the response to help ARPESView +% Last Modified by GUIDE v2.5 03-Mar-2021 15:31:22 +% Begin initialization code - DO NOT EDIT +gui_Singleton = 1; +gui_State = struct('gui_Name', mfilename, ... + 'gui_Singleton', gui_Singleton, ... + 'gui_OpeningFcn', @ARPESView_OpeningFcn, ... + 'gui_OutputFcn', @ARPESView_OutputFcn, ... + 'gui_LayoutFcn', [] , ... + 'gui_Callback', []); +if nargin && ischar(varargin{1}) + gui_State.gui_Callback = str2func(varargin{1}); +end +if nargout + [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); +else + gui_mainfcn(gui_State, varargin{:}); +end +% End initialization code - DO NOT EDIT + +% --- Executes just before ARPESView is made visible. +function ARPESView_OpeningFcn(hObject,~,handles,varargin) +% This function has no output args, see OutputFcn. +% hObject handle to figure +% varargin command line arguments to ARPESView (see VARARGIN) +clear global; global IniDir RunFile CubePos EWin valPre hGUI +% choose default command line output for ARPESView +handles.output = hObject; +% update handles structure +guidata(hObject, handles); +% initial directory +IniDir='X:\'; +% run file and pushbutton visibility +if exist('C:\ARPES Tools','dir')==7 + RunFile='C:\temp\LastRun.h5'; +else + set(handles.pushbuttonRunFile,'Visible','Off'); +end +% openGL rendering necessary for R2013a or some graphics drivers +try opengl software; end +% data cube +axis(handles.axesCube,[-1 1 -1 1 -1 1]); +set(gca,'layer','top','box','on','Projection','Orthographic','TickLength',[0 0],'XTick',[],'YTick',[],'ZTick',[]); +axis square tight; view(-86,6); +set(gca,'PlotBoxAspectRatio',[5 1 1]); +try set(gca,'boxstyle','full'); end % R2017b +CubePos=get(handles.axesCube,'Position'); +% initial viewMode value +%viewMode=1; +% initial iso-energy window +EWin=[-0.1 0]; valPre=0; %set(handles.editEnergy,'String',sprintf('%g+-%g',[mean(EWin) diff(EWin)/2])); +% Setup panels +% - LockSetup +global feat_Lock featIni setTo_Lock setToIni % dEWin_Lock dEWinIni dESm_Lock dESmIni +% dEWinIni=[]; dEWin_Lock=dEWinIni; dESmIni=[]; dESm_Lock=dESmIni; +featIni='Edge'; feat_Lock=featIni; setToIni=0.0; setTo_Lock=setToIni; +% - NormSetup +global scCoeffIni scCoeff +scCoeffIni=0.75; scCoeff=scCoeffIni; +% - ImgProcSetup initializes in itself because the image processing is activated by selecting XTra which calls ImgProcSetup +% - ViewSetup +global FracView FracViewIni gamma gammaIni render renderIni %XRange YRange +FracViewIni=[1e-2 1-1e-4]; FracView=FracViewIni; +gammaIni=1; gamma=gammaIni; +renderIni='Flat'; render=renderIni; +% XRange=[]; YRange=[]; +% % - NaviSetup +% % global hvNorm_Navi hvNormIni kxNorm_Navi kxNormIni thtANorm_Navi thtANormIni thtMNorm_Navi thtMNormIni surfNx +% % hvNormIni=0; hvNorm_Navi=hvNormIni; kxNormIni=0; kxNorm_Navi=kxNormIni; thtANormIni=0; thtANorm_Navi=thtANormIni; +% % thtMNormIni=0; thtMNorm_Navi=thtMNormIni; surfNx=0; +% global surfNx surfNx=[]; +% % position of the Kz-transform fields +% PosHvKz=get(handles.radiobuttonHvKz,'Position'); PosTextVo=get(handles.textVo,'Position'); PosEditVo=get(handles.editVo,'Position'); +% PosSurfNy=get(handles.editSurfNy,'Position'); shift=PosHvKz(2)-PosSurfNy(2); +% set(handles.radiobuttonHvKz,'Position',[PosHvKz(1) PosHvKz(2)-shift PosHvKz(3:4)]); +% set(handles.textVo,'Position',[PosTextVo(1) PosTextVo(2)-shift PosTextVo(3:4)]); +% set(handles.editVo,'Position',[PosEditVo(1) PosEditVo(2)-shift PosEditVo(3:4)]); +% % initial state of menus +% global valMenuLockPre; valMenuLockPre=1; +% GUI handle +hGUI=gcf; + +% --- Outputs from this function are returned to the command line. +function varargout = ARPESView_OutputFcn(~,~,handles) +% varargout cell array for returning output args (see VARARGOUT); +% hObject handle to figure +% Get default command line output from handles structure +varargout{1} = handles.output; + +% --- Executes on button press in pushbuttonDirFile +function pushbuttonDirFile_Callback(~,~,handles) +% Hint: get(hObject,'Value') returns toggle state of togglebutton2 +global FullName IniDir DataFull DataXC FullList +% loading filename +[filename,pathname]=uigetfile({'*.h5;*.sp2'},'Data File',IniDir); +if isequal(filename,0) || isequal(path,0); return; end % return if Cancel pressed +IniDir=pathname; FullName=[pathname filename]; +% reset data and load file +DataFull=[]; DataXC=[]; LoadFile(handles,FullName); +% file list +% - trim filename to show in menu +lenMax=37; if length(FullName)>lenMax TrimName=['...' FullName(max(1,end-(lenMax-4)):end)]; else TrimName=FullName; end +% - full- and trimmed-name lists +TrimList=get(handles.menuFileList,'String'); +if isempty(TrimList); FullList={FullName}; TrimList={TrimName}; +else + FullList=[{FullName};FullList]; TrimList=[{TrimName};TrimList]; +end +% remove previous identical filenames +for iList=2:size(FullList,1) +% [num2str(iList) ' ' FullList{iList} ' ' FullName ' ' num2str(strcmp(FullList{iList},FullName))] + if strcmp(FullList{iList},FullName)==1; FullList(iList,:)=[]; TrimList(iList,:)=[]; break; end +end +% - max number of last files +maxList=5; FullList=FullList(1:min(end,maxList)); TrimList=TrimList(1:min(end,maxList)); +% - set menu +set(handles.menuFileList,'String',TrimList,'Value',1); + +% --- Executes on selection change in menuFileList. +function menuFileList_Callback(hObject,~,handles) +% Hints: contents = cellstr(get(hObject,'String')) returns menuFileList contents as cell array +% contents{get(hObject,'Value')} returns selected item from menuFileList +global DataFull DataXC FullList FullName +n=get(hObject,'Value'); FullName=FullList(n); FullName=FullName{1}; +% reset data and load file +DataFull=[]; DataXC=[]; LoadFile(handles,FullName); + +% --- Executes on button press in pushbuttonRunFile +function pushbuttonRunFile_Callback(~,~,handles) +% hObject handle to menuFileList (see GCBO) +global RunFile FullName DataFull DataXC +% check if exists +if exist(RunFile,'file')~=2 + msgbox('Run File Inavailable','modal'); return; +end +FullName=RunFile; +% reset data and load file +DataFull=[]; DataXC=[]; LoadFile(handles,FullName); + +% --- Executes on selection change in radiobuttonEqImages. +function radiobuttonEqImages_Callback(~,~,handles) +% hObject handle to radiobuttonEqImages (see GCBO) +global FullName +if isempty(FullName); return; else; LoadFile(handles,FullName); end + +% --- Function to load data file +function LoadFile(handles,FullName) +% LoadFile loads data file with the full name FullName +global Energy Angle ScanFull Scan SWin DataFull DataXC Data Note RawTable HV thtM tltM aDef ScanType ACorr ECorr ... + dEWinIni dESmIni EAlign dESm_Lock dEWin_Lock feat_Lock ERange ARange AutoAWin AKx Kx KxRange ... + AutoKxWin AKxRange AKxWin IDiv ISubtr CubePos setTo_Lock alpha % RangeIni RangeNorm +% clear arrays +Kx=[]; IDiv=[]; ISubtr=[]; ScanType=[]; +disp('- cleared Kx IDiv ISubtr ScanType') +% clear Scan field +set(handles.editScan,'String','') +% enable summation +set(handles.radiobuttonEqImages,'Enable','On') +% load file if new filename +if isempty(DataFull) + try + h=waitbar(0.5,'Reading In','Windowstyle','Modal'); + [Angle,Energy,ScanFull,DataFull,ep,Note,RawTable]=ReadARPES(FullName); + close(h); + catch + msgbox('Data Input Error','modal'); return; + end +end +Data=DataFull; Scan=ScanFull; +% equivalent scans +if ~isempty(Scan)&&~all(diff(Scan)) + if get(handles.radiobuttonEqImages,'Value')==1 +% - cross-correlated summation + if isempty(DataXC) + h=waitbar(0.5,'Reducing Equivalent Scans','Windowstyle','Modal'); + maxLagE=0.2; DataXC=SumScanXC(Energy,Data,maxLagE); + close(h) + end + Data=DataXC; Scan=[]; + else +% - artificial Scan of the image numbers + Scan=1:1:length(ScanFull); ScanType='Number'; + end +else + set(handles.radiobuttonEqImages,'Enable','Off') +end +% scan name +if isempty(ScanType) +PosColon=strfind(Note,':'); + if ~isempty(PosColon) + PosEqual=strfind(Note,'='); PosEqual=PosEqual(PosEqual1 + if isequal(ScanType,'Number'); thtM=mean(thtM); else thtM=[]; end + end +end +% tltM +tltM=[]; +try + pos1=strfind(Note,'Tilt = '); pos2=strfind(Note,'Azimuth'); eval(['tltM=' Note(pos1+9:pos2-2) ';']); + if length(tltM)>1; tltM=[]; end +end +% aDef (added at the upgrade to PHOIBOS225) +aDef=[]; +try + pos1=strfind(Note,'ADef = '); pos2=strfind(Note,'Gain'); pos3=strfind(Note,'dt'); % 'Gain' in new files and 'dt' in older files + eval(['aDef=' Note(pos1+9:min(pos2,pos3)-2) ';']); + if length(aDef)>1; aDef=[]; end +end +% % adding up tltM and aDef if scalars, otherwise empty +% tltM=tltM+aDef; +% % adding scalar tltM and aDef to Scan +% if isequal(ScanType,'Tilt') +% Scan=Scan+tltMAdd+aDefAdd; +% end +% alpha +alpha=20; try + pos1=strfind(Note,'alpha'); pos2=strfind(Note,'Grating'); eval(['alpha=' Note(pos1+9:pos2-2) ';']); +end +% select compatible modes and show Scan range +if isempty(Scan)||length(Scan)<2 + if get(handles.menuViewMode,'Value')>2; set(handles.menuViewMode,'Value',1); end + set(handles.menuViewMode,'String',{'Image';'Angle-Int Img'}) + SWin=[0 0.5]; +else + set(handles.menuViewMode,'String',{'Image';'Angle-Int Img';'Image Series';'Iso-E';'Iso-Angle/Kx'}) + SWin=[Scan(1) Scan(end)]; +end +% select curvature and warping correction modes +pos=strfind(Note,'Corr'); +if isequal(lower(Note(pos+10:pos+13)),'true') + set(handles.radiobuttonCurvatureCorr,'Value',0,'Visible','Off') + set(handles.radiobuttonWarpingCorr,'Value',0,'Visible','Off') +else +% set(handles.radiobuttonCurvatureCorr,'Value',1,'Visible','On') +% set(handles.radiobuttonWarpingCorr,'Value',1,'Visible','On') + set(handles.radiobuttonCurvatureCorr,'Visible','On') + set(handles.radiobuttonWarpingCorr,'Visible','On') + % disable curvature correction if HV unknown (edited in raw table) + if any(isnan(HV)); set(handles.radiobuttonWarpingCorr,'Value',0,'Visible','Off'); end +end +% curvature and warping correction +% - check if the data already corrected +if contains(FullName,'_Export') && ... +(get(handles.radiobuttonCurvatureCorr,'Value')==1||get(handles.radiobuttonWarpingCorr,'Value')==1) + waitfor(warndlg('Data may be already corrected','')); +end +% - curvature corrected energy: 2D array +if get(handles.radiobuttonCurvatureCorr,'Value')==1 + ECorr=CurveCorr(Angle,Energy,ep); +else ECorr=repmat(Energy,1,length(Angle)); +end +% - warping corrected angles: 2D array for images and angle scans/ 3D for hv scans +if get(handles.radiobuttonWarpingCorr,'Value')==1 + ACorr=WarpCorr(Angle,Energy,HV); +else + ACorr=repmat(Angle,length(Energy),1); + if length(HV)>1; ACorr=repmat(ACorr,[1 1 length(HV)]); end +end +% % - - correcting average Angle +% Angle=mean(ACorr,3); Angle=mean(Angle,1); +% angle range and auto window +ARange=[min(min(ACorr(:,1,:))) max(max(ACorr(:,end,:)))]; +aMin=max(max(ACorr(:,1,:))); aMax=min(min(ACorr(:,end,:))); AutoAWin=[0.95*aMin+0.05*aMax 0.05*aMin+0.95*aMax]; +AKx=ACorr; AKxRange=ARange; AKxWin=AutoAWin; +% aligned energy and its range +% In the case the aligment fails, should it be left here or better disactivate the menu? Left here, consistently with Angle->Kx and Norm/Subtr +% set(handles.menuLock,'Value',1) +if get(handles.menuLock,'Value')>1 + h=waitbar(0.5,'Aligning EF','Windowstyle','Modal'); % waitbar +% - alignment + eWin=field2num(handles.editLockEF,0); if length(eWin)>1; eWin=linspace(eWin(1),eWin(2),size(Data,3)); end + EAlign=AlignEF(Data,ECorr,eWin,dEWin_Lock,dESm_Lock,feat_Lock); EAlign=EAlign+setTo_Lock; +% if ~isempty(Fail); uiwait(msgbox(['Warning: Failed to Lock EF in ' num2str(length(Fail)) ' images'],'modal')); end + close(h) % close waitbar +else +EAlign=repmat(ECorr,[1 1 max(1,length(Scan))]); +end +% - update energy range +ERange=[min(min(EAlign(:,1,:))) max(max(EAlign(:,end,:)))]; +% ERange=[min(ECorr(1,:)) max(ECorr(end,:))]; +% Kx-transform and auto Kx range if selected +if get(handles.radiobuttonAKx,'Value')==1 + surfNx=str2num(get(handles.editSurfNx,'String')); Kx=Kxx(HV,EAlign,thtM,ACorr,surfNx,alpha); +% - Kx range and auto window + KxRange=[min(min(Kx(:,1,:))) max(max(Kx(:,end,:)))]; + aMin=max(max(Kx(:,1,:))); aMax=min(min(Kx(:,end,:))); AutoKxWin=[0.95*aMin+0.05*aMax 0.05*aMin+0.95*aMax]; + AKx=Kx; AKxRange=KxRange; AKxWin=AutoKxWin; +end +% draw data cube +axes(handles.axesCube); cla +% - 2D case +if isempty(Scan)||length(Scan)<2 + axis([0 1 -0.5 0.5 ERange]); + set(gca,'Position',[1.01*CubePos(1) CubePos(2) 0.8*CubePos(3:4)],'PlotBoxAspectRatio',[0.5 1 1]); +% - 3D case +else + axis([Scan([1 end]) -0.5 0.5 ERange]); % axis square tight; + set(gca,'Position',CubePos,'PlotBoxAspectRatio',[5 1 1]) +end +% ranges and auto windows +% - Angle/Kx +if get(handles.radiobuttonAKx,'Value')==0 + set(handles.textAKx,'String',[sprintf('%0.1f',ARange(1)) 'max(Scan); return; end +if length(SWin)==1; set(handles.editScan,'String',sprintf('%g',SWin)); else set(handles.editScan,'String',sprintf('%g:%g',SWin)); end +% re-draw cube +DrawCubeSlice(handles) +% re-draw the existing view window +try Pos=get(hFig,'Position'); createNewFig=0; ProcessView(handles); set(hFig,'Position',Pos); end + +% --- Executes on edit of editAKx. +function editAKx_Callback(hObject,~,handles) +global AutoAWin AutoKxWin AKxWin % hFig createNewFig +% read in +%AKxWin=sort( sscanf( get(hObject,'String'),'%g:%g') ); +AKxWin=sort(field2num(hObject)); +% check validity and substitute by automatic range if invalid +if isempty(AKxWin) + if get(handles.radiobuttonAKx,'Value')==0; set(hObject,'String',sprintf('%g:%g',AutoAWin)); + else set(hObject,'String',sprintf('%g:%g',AutoKxWin)); end +end +% display +set(hObject,'String',sprintf('%g:%g',AKxWin)) +% re-draw cube +DrawCubeSlice(handles) +% % re-draw the existing view window +% try Pos=get(hFig,'Position'); createNewFig=0; ProcessView(handles); set(hFig,'Position',Pos); end +% --- Executes on button press in pushbuttonAKxMinus. +function pushbuttonAKxMinus_Callback(~,~,handles) +global AKxRange AKxWin hFig createNewFig +% read in Angle/Kx +AKxWin=sort(field2num(handles.editAKx)); +% calculate and write new Angle/Kx +AKxWin=AKxWin-diff(AKxWin); +if AKxWin(1)AKxRange(2); return; end +set(handles.editAKx,'String',sprintf('%g:%g',AKxWin)) +% re-draw cube +DrawCubeSlice(handles) +% re-draw the existing view window +try Pos=get(hFig,'Position'); createNewFig=0; ProcessView(handles); set(hFig,'Position',Pos); end + +% --- Executes on selection change in radiobuttonAKx. +function radiobuttonAKx_Callback(hObject,~,handles) +global HV ECorr ACorr ARange AutoAWin thtM Kx KxRange AutoKxWin AKx AKxRange AKxWin alpha +if get(hObject,'Value')==0 + set([handles.textSurfNx handles.editSurfNx handles.pushbuttonFindSurfNx],'Visible','Off'); +else + set([handles.textSurfNx handles.editSurfNx handles.pushbuttonFindSurfNx],'Visible','On'); +end +if isempty(HV); return; end % return if no data +% change between angle and Kx modes +if get(hObject,'Value')==0 +% - display angle range + AKx=ACorr; AKxRange=ARange; AKxWin=AutoAWin; + set(handles.textAKx,'String',[sprintf('%0.1f',ARange(1)) 'ERange(2); EWin=[]; msgbox('Check energy-window ranges','modal'); return; end +EWin=[eSlice-dE eSlice+dE]; +% re-draw cube +DrawCubeSlice(handles) +% % re-draw the existing view window +% try Pos=get(hFig,'Position'); createNewFig=0; ProcessView(handles); set(hFig,'Position',Pos); end +% --- Executes on button press in pushbuttonEMinus. +% Note: Replacement of malfunctioning Slider +function pushbuttonEMinus_Callback(~,~,handles) +global ERange EWin hFig createNewFig +% read in energy window +eStr=get(handles.editEnergy,'String'); pmPos=strfind(deblank(eStr),'+-'); +eSlice=str2num(eStr(1:pmPos-1)); dE=str2num(eStr(pmPos+2:end)); +% calculate and write new energy window +eSlice=eSlice-dE; +if eSlice-dEERange(2); return; end % leave the previous window if above the range +EWin=[eSlice-dE eSlice+dE]; +set(handles.editEnergy,'String',[num2str(eSlice) '+-' num2str(dE)]) +% re-draw cube +DrawCubeSlice(handles) +% re-draw the existing view window +try Pos=get(hFig,'Position'); createNewFig=0; ProcessView(handles); set(hFig,'Position',Pos); end + +% --- Executes on selection change in menuLock. +function menuLock_Callback(hObject,~, handles) +% Hints: contents = cellstr(get(hObject,'String')) returns menuLock contents as cell array +% contents{get(hObject,'Value')} returns selected item from menuLock +global hGUI Data HV thtM ACorr ECorr EAlign ERange Kx KxRange AutoKxWin AKxRange AKxWin ... + dEWin_Lock dEWinIni dESm_Lock dESmIni feat_Lock featIni setTo_Lock setToIni IDiv ISubtr CubePos Scan alpha +% % return if no change in selection +% if get(hObject,'Value')==valMenuLockPre; return; else valMenuLockPre=get(hObject,'Value'); end +% reset +IDiv=[]; ISubtr=[]; disp('- cleared IDiv ISubtr') +if get(hObject,'Value')==1 + EAlign=repmat(ECorr,[1 1 max(1,length(Scan))]); +else +% set initial parameters if 'Auto' + if get(hObject,'Value')==2 + dEWin_Lock=dEWinIni; dESm_Lock=dESmIni; feat_Lock=featIni; setTo_Lock=setToIni; +% draw the popup window and wait for initial parameters if 'XTra' + else +% position of the popup window + PosGUI=get(hGUI,'Position'); PosPanel=get(handles.PanelProcessing,'Position'); PosButton=get(hObject,'Position'); + xPos_Lock=PosGUI(1)+PosPanel(1)+PosButton(1)+PosButton(3); yPos_Lock=PosGUI(2)+PosPanel(2)+PosButton(2); +% popup window + h=LockSetup; + Pos=get(h,'Position'); Pos=[xPos_Lock yPos_Lock-Pos(4)-30 Pos(3) Pos(4)]; + set(h,'Position',Pos,'WindowStyle','modal'); uiwait(h); + end +% aligned energy and energy range + h=waitbar(0.5,'Aligning EF','WindowStyle','Modal'); % open waitbar +% - alignment + eWin=field2num(handles.editLockEF,0); if length(eWin)>1; eWin=linspace(eWin(1),eWin(2),size(Data,3)); end + EAlign=AlignEF(Data,ECorr,eWin,dEWin_Lock,dESm_Lock,feat_Lock); EAlign=EAlign+setTo_Lock; +% if ~isempty(Fail); uiwait(msgbox(['Warning: Failed to Lock EF in ' num2str(length(Fail)) ' images'],'modal')); end + close(h) % close waitbar +end +% update energy range + ERange=[min(min(EAlign(:,1,:))) max(max(EAlign(:,end,:)))]; + set(handles.textEnergy,'String',[sprintf('%0.1f',ERange(1)) '1; eWin=linspace(eWin(1),eWin(2),size(Data,3)); end +EAlign=AlignEF(Data,ECorr,eWin,dEWin_Lock,dESm_Lock,feat_Lock); EAlign=EAlign+setTo_Lock; +% if ~isempty(Fail); uiwait(msgbox(['Warning: Failed to Lock EF in ' num2str(length(Fail)) ' images'],'modal')); end +close(h) % close waitbar +% update energy range +ERange=[min(min(EAlign(:,1,:))) max(max(EAlign(:,end,:)))]; +set(handles.textEnergy,'String',[sprintf('%0.1f',ERange(1)) '1 +% h=waitbar(0.5,'Aligning EF','Windowstyle','Modal'); % waitbar +% % - parameters and alignment +% % eWin=str2num(get(handles.editLockEF,'String')); +% eWin=field2num(handles.editLockEF); +% [EAlign,dECorr,Fail]=AlignEF(Data,ECorr,eWin,dEWin_Lock,dESm_Lock,feat_Lock); EAlign=EAlign+setTo_Lock; +% % if ~isempty(Fail); uiwait(msgbox(['Warning: Failed to Lock EF in ' num2str(length(Fail)) ' images'],'modal')); end +% close(h) % close waitbar +% else +% EAlign=repmat(ECorr,[1 1 max(1,length(Scan))]); +% end +% end +% % update energy range +% ERange=[min(min(EAlign(:,1,:))) max(max(EAlign(:,end,:)))]; +set(handles.textEnergy,'String',[sprintf('%0.1f',ERange(1)) '1 + if isempty(IDiv) + h=waitbar(0.5,'Forming Normalization Array','Windowstyle','Modal'); + if isempty(RangeNorm); IntEWin=[0.9*ERange(1)+0.1*ERange(2) 0.1*ERange(1)+0.9*ERange(2)]; + else IntEWin=RangeNorm; end + IDiv=Slice(ACorr,EAlign,Data3,'isoE',IntEWin); + close(h) + if isempty(IDiv) msgbox('Error: Inconsistent normalization energy window','modal'); return; end + IDiv=Gaco2(IDiv,5,0); % HWHM adjusted to suppress uneven sensitivity of the CCD channels + IDiv=repmat(IDiv,1,1,size(Data3,1)); IDiv=permute(IDiv,[3 2 1]); + end + Data3=Data3./IDiv; +% subtract angle-integrated spectrum and clip negative values into global output Data3 + if scCoeff~=0 + if isempty(ISubtr) + h=waitbar(0.5,'Forming Subtraction Array','Windowstyle','Modal'); + ISubtr=Slice(ACorr,EAlign,Data3,'isoK',AutoAWin); + close(h) + ISubtr=repmat(ISubtr,1,1,size(Data3,2)); ISubtr=permute(ISubtr,[1 3 2]); + end + Data3=Data3-scCoeff*ISubtr; + if clipNormNeg==1; Data3(Data3<0)=0; end + end +end +% processing and image modes into global output X,Y,Z +switch viewMode +% +% *** image *** (summation of images from 3D data ignores their energy shifts; in principle, should use remapping) +case 1 + if size(AKx,3)>1; X=mean(AKx(:,:,nS1:nPeriod:nS2),3); else X=AKx; end + Y=mean(EAlign(:,:,nS1:nPeriod:nS2),3); + Z=mean(Data3(:,:,nS1:nPeriod:nS2),3); +% +case 2 +% *** angle integrated image *** +% [Y,X]=IntAngle(mean(Data3(:,:,nS1:nS2),3),Angle,mean(EAlign(:,:,nS1:nS2),3),AKxWin); + if ismatrix(AKx); MeanAKx=AKx; else MeanAKx=mean(AKx(:,:,nS1:nPeriod:nS2),3); end + [Y,X]=Slice(MeanAKx,mean(EAlign(:,:,nS1:nPeriod:nS2),3),mean(Data3(:,:,nS1:nPeriod:nS2),3),'isoK',AKxWin); + Z=[]; +% +% **** series of images mode **** +case 3 +% plot images in the selected Scan range + if size(AKx,3)>1; A=AKx(:,:,nS1:nPeriod:nS2); else A=AKx; end +% if size(EAlign,3)>1; EAlignV=EAlign(:,:,nS1:nPeriod:nS2); else EAlignV=EAlign; end + modeMap=get(handles.menuColormap,'Value'); modeMapC=get(handles.menuColormap,'String'); colorScheme=[char(modeMapC(modeMap)) '(256)']; % color scheme + nRows=3; nCols=3; ViewSeries(A,EAlign(:,:,nS1:nPeriod:nS2),Scan(nS1:nPeriod:nS2),Data3(:,:,nS1:nPeriod:nS2),nRows,nCols,colorScheme,FracView(1),FracView(2)) + X=[]; Y=[]; Z=[]; +% +% *** iso-E mode *** +case 4 +% - slice formation waitbar + h=waitbar(0.5,'Forming Data Slice','Windowstyle','Modal'); +% - slice within EWin + if size(ACorr,3)>1; A=ACorr(:,:,nS1:nPeriod:nS2); else A=ACorr; end + try [ISliceE,ASliceE]=Slice(A,EAlign(:,:,nS1:nPeriod:nS2),Data3(:,:,nS1:nPeriod:nS2),'isoE',EWin); catch; beep; close(h); return; end +% try [ISliceE,ASliceE]=Slice(ACorr,EAlign(:,:,nS1:nPeriod:nS2),Data3(:,:,nS1:nPeriod:nS2),'isoE',EWin); catch; beep; close(h); return; end +% - close waitbar + close(h) +% scan normalization + normScanMode=get(handles.menuNormScans,'Value'); + switch normScanMode +% - no normalization + case 1 + ISliceN=ISliceE; + otherwise +% - integral intensity of scans over 90% of angular range + nA=size(ISliceE,2); n1=round(0.05*nA); n2=round(0.95*nA); + ISliceN=ISliceE(:,n1:n2); ISliceN=sum(ISliceN,2)/(n2-n1+1); +% - 2-order smoothing of integral intensity if normalization set to 'Smooth' + if normScanMode==3; P=polyfit(Scan(nS1:nPeriod:nS2)',ISliceN,2); ISliceN=polyval(P,Scan(nS1:nPeriod:nS2)'); end +% - normalization + ISliceN=ISliceE./repmat(ISliceN,1,nA); +% % - bilinear over 90% of angular range +% [~,Coeffs]=Flat(AngleN,Scan,ISliceN); +% [AngleM,ScanM]=meshgrid(Angle,Scan); +% ISliceN=ISliceE./(Coeffs(1)*AngleM+Coeffs(2)*ScanM+Coeffs(3)); + end +% Kx-conversion + if switchAKx==0 + AKxSliceE=ASliceE; + else + if isequal(ScanType,'Tilt')||isequal(ScanType,'ADef'); AKxSliceE=Kxx(HV,mean(EWin),thtM,ASliceE,surfNx,alpha); end + if isequal(ScanType,'hv'); AKxSliceE=Kxx(HV(nS1:nPeriod:nS2),mean(EWin),thtM,ASliceE,surfNx,alpha); end + end +% - image output + X=AKxSliceE; Y=Scan(nS1:nPeriod:nS2)'; Z=ISliceN; +% K-space transformation if Kx activated + if switchAKx==1 + surfNy=field2num(handles.editSurfNy); +% - Tilt scan + if isequal(ScanType,'Tilt') + Ky=Kyy(HV,mean(EWin),ASliceE,thtM,Scan(nS1:nPeriod:nS2)-surfNy,surfNx,alpha); Y=Ky; + end +% - ADef scan + if isequal(ScanType,'ADef') +% Ky=Kyy(HV,mean(EWin),ASliceE,thtM,Scan(nS1:nPeriod:nS2)+tltM-surfNy,surfNx,alpha); + ADefM=repmat((Scan(nS1:nPeriod:nS2))',1,size(ASliceE,2)); + Ky=0.5124*sqrt(HV-ePhi+mean(EWin)).*sind(tltM+ADefM-surfNy).*cosd(ASliceE+thtMPhys)+2*pi*HV*sind(alpha+thtMPhys).*sind(tltM)/12400; + Y=Ky; + end +% - hv scan + if isequal(ScanType,'hv') + if get(handles.radiobuttonHvKz,'Value')==1 + Vo=field2num(handles.editVo,-10); + Kz=Kzz(HV(nS1:nPeriod:nS2),mean(EWin),thtM,ASliceE,tltM+aDef-surfNy,Vo,surfNx,alpha); Y=Kz; + end + end + end +% +% *** Iso-Angle/Kx mode *** +case 5 +% angle integration + h=waitbar(0.5,'Angle Integrating','Windowstyle','Modal'); % waitbar +% [ISliceA,ESliceA]=IntAngle(Data3,Angle,EAlign,AWin); + if size(AKx,3)>1; A=AKx(:,:,nS1:nPeriod:nS2); else A=AKx; end + try [ISliceA,ESliceA]=Slice(A,EAlign(:,:,nS1:nPeriod:nS2),Data3(:,:,nS1:nPeriod:nS2),'isoK',AKxWin); catch; beep; close(h); return; end + close(h) % close waitbar + % scan normalization + normScanMode=get(handles.menuNormScans,'Value'); + ISliceZ=ISliceA'; + switch normScanMode +% - no normalization + case {2,3} +% - integral intensity of scans over 80% of energy range + nE=size(ISliceZ,2); n1=round(0.1*nE); n2=round(0.9*nE); + ISliceN=ISliceZ(:,n1:n2); ISliceN=sum(ISliceN,2)/(n2-n1+1); +% - 2-order smoothing of integral intensity if normalization set to 'Smooth' + if normScanMode==3; P=polyfit(Scan',ISliceN,2); ISliceN=polyval(P,Scan'); end +% - normalization + ISliceZ=ISliceZ./repmat(ISliceN,1,nE); + end +% image data +% X=ESliceA'; Y=Scan'; Z=ISliceZ; + X=ESliceA'; Y=Scan(nS1:nPeriod:nS2)'; Z=ISliceZ; +% interpolation to uniform energy grid if active energy alignment + if get(handles.menuLock,'Value')>1 + XGrid=linspace(min(X(:,1)),max(X(:,end)),size(X,2)); % energy grid column vector + for iScan=1:length(Y) + Z(iScan,:)=interp1(X(iScan,:),Z(iScan,:),XGrid); % interpolation to the same energy grid + end + X=XGrid; + end +% K-space transformations if Kx activated + if get(handles.radiobuttonAKx,'Value')==1 +% surfNx=str2num(get(handles.editSurfNx,'String')); +% surfNx=field2num(handles.editSurfNx); thtMPhys=thtM+surfNx; +% surfNy=str2num(get(handles.editSurfNy,'String')); + surfNy=field2num(handles.editSurfNy); + kx=mean(AKxWin); +% - Tilt scan + if isequal(ScanType,'Tilt') + Eb=X; TltM=repmat(Y,1,size(X,2))-surfNy; + ThtA=asind((kx+2*pi*HV*cosd(alpha+thtMPhys)/12400)./(0.5124*sqrt(HV-ePhi+Eb)))-thtMPhys; + Ky=0.5124*sqrt(HV-ePhi+Eb).*sind(TltM).*cosd(ThtA+thtMPhys)+2*pi*HV*sind(alpha+thtMPhys).*sind(TltM)/12400; + Y=Ky; + end +% - ADef scan + if isequal(ScanType,'ADef') + Eb=X; ADefM=repmat(Y,1,size(X,2))-surfNy; + ThtA=asind((kx+2*pi*HV*cosd(alpha+thtMPhys)/12400)./(0.5124*sqrt(HV-ePhi+Eb)))-thtMPhys; + Ky=0.5124*sqrt(HV-ePhi+Eb).*sind(tltM+ADefM).*cosd(ThtA+thtMPhys)+2*pi*HV*sind(alpha+thtMPhys).*sind(tltM)/12400; + Y=Ky; + end + % - hv scan + if isequal(ScanType,'hv') + if get(handles.radiobuttonHvKz,'Value')==1 +% Vo=str2num(get(handles.editVo,'String')); + Vo=field2num(handles.editVo,-10); + Eb=X; HV2=repmat(Y,1,size(X,2)); + ThtA=asind((kx+2*pi*HV2*cosd(alpha+thtMPhys)/12400)./(0.5124*sqrt(HV2-ePhi+Eb)))-thtMPhys; + Kxy_2=(HV2-ePhi+Eb).*(sind(ThtA+thtMPhys).^2+(sind(tltM+aDef-surfNy).*cosd(ThtA+thtMPhys)).^2); + Kz=0.5124*sqrt(HV2+Eb+Vo-Kxy_2)+2*pi*HV2*sind(alpha+thtMPhys)/12400; + Y=Kz; + end + end + end +end +% image filter +if viewMode~=2 + if get(handles.menuImgProcMode,'Value')==2 + dx=mean(mean(diff(X'))); dy=mean(mean(diff(Y))); +% - Gaussian pre-smoothing + hwPtsX=0.5*presmdX/dx; hwPtsY=0.5*presmdY/dy; + Z=Gaco2(Z,hwPtsX,hwPtsY,2*hwPtsX,2*hwPtsY); +% - image structure + switch structMode + case 2 % curvature along X + if sharp==0; Z=-1*(DifC(Z',2))'; else; Z=-DiffFlt2(Z','1D',sharp)'; end + case 3 % curvature along Y + if sharp==0; Z=-1*DifC(Z,2); else; Z=-DiffFlt2(Z,'1D',sharp); end + case 4 % curvature along XY + if sharp==0; Z=-1*(DifC(Z,2)+(dy/dx)^2*(DifC(Z',2))'); else; Z=-DiffFlt2(Z,'2D',sharp,dx/dy); end + end +% - Gaussian post-smoothing + hwPtsX=0.5*postsmdX/dx; hwPtsY=0.5*postsmdY/dy; + Z=Gaco2(Z,hwPtsX,hwPtsY); + % - clipping negative values + if clipImgProcNeg==1; Z(Z<0)=0; end + end +end +% enable export +set(handles.menuExport,'Enable','On') +% % *** end 3D block *** +% end +% +% *** plot *** +Pos=strfind(FullName,'\'); if isempty(Pos); Pos=strfind(FullName,'/'); end % parsing universal between Windows and Mac/Linux +FileName=FullName(Pos(end)+1:end); Opts.FileName=FileName; Opts.Scan=Scan; Opts.ScanType=ScanType; +PlotAll(X,Y,Z,Opts,handles) + +% --- Plot and set callbacks function +function PlotAll(X,Y,Z,Opts,handles) +global switchAKx FracView render XRange YRange hFig createNewFig gamma ZView + % presmdX presmdY structMode sharp postsmdX postsmdY clipImgProcNeg ScanType hIm hXDC hYDC +viewMode=get(handles.menuViewMode,'Value'); +% reject image series +if viewMode==3; return; end +% color scheme +modeMap=get(handles.menuColormap,'Value'); modeMapC=get(handles.menuColormap,'String'); colorScheme=[char(modeMapC(modeMap)) '(256)']; +% scan type +ScanType=Opts.ScanType; +% deactivate slope readout +% set(handles.menuReadout,'Value',1,'Enable','Off'); +% set previous or create new figure +if createNewFig==0 +% try delete(hFig); end +% - set previous figure as current + figure(hFig) +% clf(hFig) +% - retrieve previous image axes handle and set it active + UserData=get(hFig,'UserData'); hIm=UserData.hIm; axes(hIm) +else +% - new figure with callbacks + hFig=figure('WindowButtonDownFcn',{@window_Zoom,handles},'WindowButtonUpFcn',{@window_H,handles}); % default normalized units +end +% linear plot +if isempty(Z) + plot(X,Y); axis tight; set(gca,'TickDir','Out') +% image plots +else +% set image limits +% - render 1D-X,Y to 2D-X,Y + if size(X,1)==1; XX=repmat(X,size(Y,1),1); else XX=X; end + if size(Y,2)==1; YY=repmat(Y,1,size(X,2)); else YY=Y; end +% - set NaN outside the limits + if ~isempty(XRange); Z(XXXRange(2))=NaN; end + if ~isempty(YRange); Z(YYYRange(2))=NaN; end +% set contrast + % RawZ=Z; + ZView=SetContrast(Z,FracView(1),FracView(2),gamma); +% if get(handles.menuNorm,'Value')==1; Z=Z*scale; end +% different image modes + switch viewMode +% - image + case 1 + ImData(X,Y,ZView,render); axis tight; colorbar; eval(['colormap ''' colorScheme '''']) +% - iso-E + case 4 + ImData(X,Y,ZView,render); axis tight; colorbar; eval(['colormap ''' colorScheme '''']) +% - Iso-E(Angle) + if isequal(ScanType,'Tilt')||isequal(ScanType,'ADef') + axis tight equal %set(gca,'YDir','Reverse'); + set(handles.menuReadout,'Enable','On'); + end +% - angle-integrated scan + case 5 + ImData(X,Y,ZView,render); axis tight; colorbar; eval(['colormap ''' colorScheme '''']) + end +end +% update image axes handle +hIm=gca; +% limitsOpts.Scan +if ~isempty(XRange); xlim(XRange); end +if ~isempty(YRange); ylim(YRange); end +% title and axes information +if switchAKx==0; titleAKx=', Angle='; else titleAKx=', Kx='; end +switch viewMode + case 1 + if isempty(Opts.Scan); titleStr=Opts.FileName; + else titleStr=[Opts.FileName ', Scan=' get(handles.editScan,'string')]; + end + if switchAKx==0; xlabel('Angle (deg)'); else xlabel('K_{x} (1/A)'); end + if min(Y)>100; ylabel('E_{k} (eV)'); else ylabel('E_{B} (eV)'); end + case 2 + if isempty(Opts.Scan); titleStr=[Opts.FileName titleAKx get(handles.editAKx,'string')]; + else titleStr=[Opts.FileName ', Scan=' get(handles.editScan,'string') titleAKx get(handles.editAKx,'string')]; + end + if min(X)>100; xlabel('E_{k} (eV)'); else xlabel('E_{B} (eV)'); end + ylabel('Intensity'); + case 4 + titleStr=[Opts.FileName ', E=' get(handles.editEnergy,'string')]; + if switchAKx==0; xlabel('Angle (deg)'); else xlabel('K_{x} (1/A)'); end + switch(ScanType) + case 'Number'; ylabel('Image Number'); + case 'hv'; if get(handles.radiobuttonHvKz,'Value')==0; ylabel('hv (eV)'); else ylabel('K_{z} (1/A)'); end + case {'Theta','Azimuth'}; ylabel([ScanType ' (deg)']) + case {'Tilt','ADef'}; if switchAKx==0; ylabel([ScanType ' (deg)']); else ylabel('K_{y} (1/A)'); end + case {'X','Z'}; ylabel([ScanType ' (mm)']) + end + case 5 + titleStr=[Opts.FileName titleAKx get(handles.editAKx,'string')]; + if min(X)>100; xlabel('E_{k} (eV)'); else xlabel('E_{B} (eV)'); end + switch(ScanType) + case 'Number'; ylabel('Image Number'); + case 'hv'; if get(handles.radiobuttonHvKz,'Value')==0; ylabel('hv (eV)'); else ylabel('K_{z} (1/A)'); end + case {'Theta','Azimuth'}; ylabel([ScanType ' (deg)']) + case {'Tilt','ADef'}; if switchAKx==0; ylabel([ScanType ' (deg)']); else ylabel('K_{y} (1/A)'); end + case {'X','Z'}; ylabel([ScanType ' (mm)']) + end +end +if get(handles.menuNorm,'value')>1; titleStr=[titleStr ', Subtr']; end +if isequal(get(handles.menuNormScans,'enable'),'on') && get(handles.menuNormScans,'value')~=1 + titleStr=[titleStr ', NormScans']; +end +title(titleStr,'Interpreter','none','fontweight','normal'); +% white background +set(hFig,'color','w') +% user data for Zoom +UserData.viewMode=viewMode; UserData.Opts=Opts; UserData.X=X; UserData.Y=Y; UserData.Z=Z; UserData.hIm=hIm; +set(hFig,'UserData',UserData) +% +% *** add XDC/YDC panels *** +if viewMode~=2 && viewMode~=3 && get(handles.radiobuttonXYDC,'Value')==1 +% switch off the Zoom callback on WindowButtonDownFcn + set(hFig,'WindowButtonDownFcn',[]); +% switch off resizing (resizing corrupts positioning of the panels) + set(hFig,'resize','off') +% extend figure for the XYDC panels + PosFig=get(hFig,'Position'); sizeFig=max(PosFig([3 4])); set(hFig,'Position',[PosFig(1) PosFig(2)+PosFig(4)-sizeFig sizeFig sizeFig]) +% prepare the figure + axis square; colorbar('off'); hIm=gca; +% remove old and draw new panels + set(hIm,'position',[0.1 0.1 0.5 0.5]); +% XLim=get(hIm,'XLim'); YLim=get(hIm,'YLim'); +% hPlot=plot(hOver,XLim,YLim); set(hPlot,'visible','off') + try delete(UserData.hXDC); end; hXDC=axes('position',[0.1 0.7 0.5 0.25],'box','on','XTick',[],'YTick',[]); + try delete(UserData.hYDC); end; hYDC=axes('position',[0.7 0.1 0.25 0.5],'box','on','XTick',[],'YTick',[]); +% X/Y edit fields +hY=uicontrol('Callback',@PlotXYDC,'Style','edit','fontsize',11,'units','normalized','position',[0.65 0.8 0.16 0.04], ... + 'string',['-0.1' '+-' sprintf('%0.1f',0.1)]); +uicontrol('Style','text','string','Y=','units','normalized','position',[0.61 0.795 0.04 0.04],'BackgroundColor','w','fontsize',11); +hX=uicontrol('Callback',@PlotXYDC,'Style','edit','fontsize',11,'units','normalized','position',[0.76 0.625 0.16 0.04], ... + 'string',['0.0' '+-' sprintf('%0.1f',0.1)]); +uicontrol('Style','text','string','X=','units','normalized','position',[0.72 0.62 0.04 0.04],'BackgroundColor','w','fontsize',11); +% set callback on cursor motion +set(hFig,'WindowButtonDownFcn',@Ginput_XYDC); +% set(hFig,'WindowButtonMotionFcn',@window_XYDC,'BusyAction','Cancel'); +% add user data + %UserData.RawZ=RawZ; + UserData.hIm=hIm; UserData.hYDC=hYDC; UserData.hXDC=hXDC; UserData.hX=hX; UserData.hY=hY; + set(hFig,'UserData',UserData) %UserData.hOver=hOver; +% plot the ROI-cross and XYDCs +PlotXYDC +end + +% --- Executes on button press in radiobuttonXYDC. +function radiobuttonXYDC_Callback(hObject, ~, handles) +% hObject handle to radiobuttonXYDC (see GCBO) +if get(hObject,'Value')==0 + set(handles.menuExport,'String',{'Data';'Raw Image';'View Image'}) +else + set(handles.menuExport,'String',{'Data';'Raw Image';'View Image';'XDC';'YDC'}) +end + +% graphical input of ROI for XYDCs +function Ginput_XYDC(~,~,~) +global hFig +% retrieve user data from the current figure +UserData=get(hFig,'UserData'); hIm=UserData.hIm; +try hX=UserData.hX; hY=UserData.hY; catch; return; end % return if the previous figure without edit fields +% remove previous lines +try delete([hLine1 hLine2 hLine3 hLine4]); end +%delete(hIm) deleting image makes the function reactive +% plot(hIm,[0 1],[0 1]) +% current point +XY=get(hIm,'CurrentPoint'); x=XY(1,1); y=XY(1,2); +% XY=get(hOver,'CurrentPoint'); x=XY(1,1); y=XY(1,2); +% return if outside the image +XLim=get(hIm,'XLim'); YLim=get(hIm,'YLim'); +if xXLim(2) || yYLim(2); return; end +% X- and Y-fields +xStr=get(hX,'String'); pmPos=strfind(deblank(xStr),'+-'); dX=str2num(xStr(pmPos+2:end)); set(hX,'String',[sprintf('%0.2f+-%0.2f',[x dX])]); +yStr=get(hY,'String'); pmPos=strfind(deblank(yStr),'+-'); dY=str2num(yStr(pmPos+2:end)); set(hY,'String',[sprintf('%0.2f+-%0.2f',[y dY])]); +% plot the ROI-cross and XYDCs +PlotXYDC + +% plot the ROI-cross and XYDCs +function PlotXYDC(~,~,~) +global hLine1 hLine2 hLine3 hLine4 hFig XPts XDC YPts YDC +% remove previous lines +try delete([hLine1 hLine2 hLine3 hLine4]); end +% retrieve user data from the current figure +UserData=get(hFig,'UserData'); X=UserData.X; Y=UserData.Y; Z=UserData.Z; +hIm=UserData.hIm; hXDC=UserData.hXDC; hYDC=UserData.hYDC; hX=UserData.hX; hY=UserData.hY; %hOver=UserData.hOver; +% x- and y-windows +xStr=get(hX,'String'); pmPos=strfind(deblank(xStr),'+-'); x=str2num(xStr(1:pmPos-1)); dX=abs(str2num(xStr(pmPos+2:end))); +if isempty(x*dX); msgbox('Check format X+-dX','modal'); return; end +yStr=get(hY,'String'); pmPos=strfind(deblank(yStr),'+-'); y=str2num(yStr(1:pmPos-1)); dY=abs(str2num(yStr(pmPos+2:end))); +if isempty(y*dY); msgbox('Check format Y+-dY','modal'); return; end +% return if outside the image +XLim=get(hIm,'XLim'); YLim=get(hIm,'YLim'); +if x+dXXLim(2) || y+dYYLim(2); return; end +% cross +hLine1=line(hIm,[XLim(1) x-dX x-dX],[y-dY y-dY YLim(1)],'color','g'); +hLine2=line(hIm,[x+dX x+dX XLim(2)],[YLim(1) y-dY y-dY ],'color','g'); +hLine3=line(hIm,[x+dX x+dX XLim(2)],[YLim(2) y+dY y+dY ],'color','g'); +hLine4=line(hIm,[XLim(1) x-dX x-dX],[y+dY y+dY YLim(2)],'color','g'); +% XDC panel +[XPts,XDC]=Cut(X,Y,Z,'mdc',[y-dY y+dY]); +if isempty(XDC); cla(hXDC) +else plot(hXDC,XPts,XDC,'linewidth',1); set(hXDC,'xlim',XLim,'xtickmode','auto'); +end +% YDC panel +[YPts,YDC]=Cut(X,Y,Z,'edc',[x-dX x+dX]); +if isempty(YDC); cla(hYDC) +else plot(hYDC,YDC,YPts,'linewidth',1); set(hYDC,'ylim',YLim,'ytickmode','auto') +end + +% --- Zoom and XY/slope readout function +function window_Zoom(~,~,handles) +global CurrentXY PSave ha hc hl hFig hGUI createNewFig +% return if GUI +if isequal(gcf,hGUI); return; end +% clear previous line +try delete([ha hc hl]); end +% retrieve user data from the figure +hFig=gcf; +UserData=get(hFig,'UserData'); +viewMode=UserData.viewMode; Opts=UserData.Opts; X=UserData.X; Y=UserData.Y; Z=UserData.Z; +% reject image series +if viewMode==3; return; end +% keep the plot figure handle which gets spoiled by rbbox +hhFig=hFig; +% previous limits +XLim0=get(gca,'XLim'); YLim0=get(gca,'YLim'); +% rbbox and its borders +p1=get(gca,'CurrentPoint'); p1x=p1(1,1); p1y=p1(1,2); rbbox; p2=get(gca,'CurrentPoint'); p2x=p2(1,1); p2y=p2(1,2); +% XY-coordinates if point click +if (p2x-p1x)==0 && (p2y-p1y)==0 +% return if the coordinates outside the plot + if p1xXLim0(2)||p1yYLim0(2); return; end +% readout set to XY + if get(handles.menuReadout,'Value')==1 +% hc=line(p1x-[-1 1 0 0 0]*diff(XLim0)/20,p1y-[0 0 0 1-1]*diff(YLim0)/20); set(hc,'color','g','linewidth',1.5) % draw cross + hold on; hc=plot(p1x,p1y,'+g','markersize',20); hold off + ha=annotation('textbox', [0.65, 0.02, 0.35, 0.05],'String',['X=' sprintf('%0.3f',p1x) '; Y=' sprintf('%0.3f',p1y)],'EdgeColor','W','FontSize',11); + CurrentXY=[p1x p1y]; +% pause(1); delete(hc) + return +% readout set to Slope + else + if isempty(PSave) + PSave=[p1x p1y]; + hold on; hc=plot(p1x,p1y,'*g','markersize',10); hold off + else hl=line([PSave(1) p1x],[PSave(2) p1y]); set(hl,'color','g','linewidth',1.5); + Fit=polyfit([PSave(1) p1x],[PSave(2) p1y],1); slope=atand(Fit(1)); + ha=annotation('textbox', [0.7, 0.02, 0.3, 0.05],'String',['Slope=' sprintf('%0.3f',slope)],'EdgeColor','W','FontSize',11); +% pause(1); delete(hl) + PSave=[]; + end + end +end +% restore the plot figure handle +hFig=hhFig; +% process current point +XLim=sort([p1x p2x]); YLim=sort([p1y p2y]); +XLim=[max(XLim(1),XLim0(1)) min(XLim(2),XLim0(2))]; +YLim=[max(YLim(1),YLim0(1)) min(YLim(2),YLim0(2))]; +% return if rbbox is too small +% if diff(XLim)*diff(YLim)==0; return; end +if diff(XLim)<0.01*diff(XLim0) || diff(YLim)<0.01*diff(YLim0); return; end +% % return if not the last plotted figure +% if ~isequal(gcf,hhFig); +% hMsg=msgbox('Zooming Active Only in the Last Plot','modal'); pause(2); close(hMsg); return; +% end +% trimming of images to re-colorscale +ZZ=Z; +switch viewMode +case 1 + ZZ(XXLim(2))=NaN; ZZ(YYLim(2))=NaN; +case 2 + ZZ=[]; +case {4,5} + if size(Y,2)==1; YY=repmat(Y,1,size(X,2)); else YY=Y; end % 1D vector of angles vs 2D array of k + ZZ(XXLim(2))=NaN; ZZ(YYYLim(2))=NaN; +% case 5 +% [XX,YY]=meshgrid(X,Y); +% ZZ(XXLim(2))=NaN; ZZ(YYYLim(2))=NaN; +end +% draw zoomed figure +% close(gcf) % replace previous figure +createNewFig=0; PlotAll(X,Y,ZZ,Opts,handles); set(gca,'XLim',XLim,'YLim',YLim) + +% --- Function to set global handle of the active figure for readout +function window_H(~,~,handles) +global hFig hGUI +% return if GUI +if isequal(gcf,hGUI); return; end +hFig=gcf; +% set XDC/YDC of the figure +hAllAxes=findobj(hFig,'Type','axes'); +if length(hAllAxes)==1; set(handles.radiobuttonXYDC,'Value',0); else set(handles.radiobuttonXYDC,'Value',1); end +% enable slope readout +A=daspect; +if isequal(A(1),A(2)); set(handles.menuReadout,'Enable','On'); +else set(handles.menuReadout,'Value',1,'Enable','Off'); end + +% --- Executes on selection change in menuColormap. +function menuColormap_Callback(~,~,handles) +% % colorscheme +% global colorScheme +% modeMap=get(hObject,'Value'); modeMapC=get(hObject,'String'); colorScheme=[char(modeMapC(modeMap)) '(256)']; +% % ['set(gca,''colormap'', ' colorScheme '(256))']; eval(['set(gca,''colormap'', ' colorScheme '(256))']) % does not work +% re-draw image +global createNewFig +createNewFig=0; ProcessView(handles); + +% --- Executes on selection change in menuReadout. +function menuReadout_Callback(hObject,~,~) +global PSave +if get(hObject,'Value')==2; PSave=[]; end + +% --- Executes on button press in CloseFigs. +function CloseFigs_Callback(~,~,~) +% hObject handle to CloseFigs (see GCBO) +% handles of all figures +global hGUI +hPlots=findobj('Type','figure'); +% remove the GUI handle +hPlots=hPlots(hPlots~=hGUI); +% close all plots +close(hPlots) + +% --- Executes on button press in pushbuttonExport. +function pushbuttonExport_Callback(~,~,handles) +% hObject handle to pushbuttonExport (see GCBO) +global Scan Data3 Note EAlign FullName AKx X Y Z ZView XPts XDC YPts YDC +global ExpX ExpY ExpZ % share output data +% DataX=Data; ECorrX=ECorr; EAlignX=EAlign; ACorrX=ACorr; +% check data and activated corrections +if isempty(Data3); errordlg('No Data','','modal'); return; end +if contains(FullName,'_Exp'); waitfor(warndlg('Data file seems already exported','')); end +% filename to export +Dots=strfind(FullName,'.'); dot=Dots(end); +[filename,pathname]=uiputfile('*.h5','Export As',[FullName(1:dot-1) '_Exp.h5']); +if filename~=0; filename=[pathname filename]; +else errordlg('Invalid Filename','','modal'); return +end +% select export mode +switch get(handles.menuExport,'Value') +% - current data generated by ProcessView (incl. energy alignment and normalization/subtraction) + case 1; ExpX=AKx; ExpY=EAlign; ExpZ=Data3; +% - current image or plot (empty Z) generated by ProcessView (+ scan normalizaton and image filtering) + case 2; ExpX=X; ExpY=Y; ExpZ=Z; +% - current image generated by PlotAll (+ contrast enhancement and X/Y ranges) + case 3; ExpX=X; ExpY=Y; ExpZ=ZView; +% - current XDC + case 4; ExpX=XPts; ExpY=XDC; ExpZ=[]; +% - current YDC + case 5; ExpX=YPts; ExpY=YDC; ExpZ=[]; +end +% remapping +% - linear plots +if isempty(ExpZ) +% - interpolate if non-equidistant + if any(diff(diff(ExpX))~=0) + LinX=linspace(ExpX(1),ExpX(end),length(ExpX)); + ExpY=interp1(ExpX,ExpY,LinX,'pchip'); ExpX=LinX; + end +% - data or images +else +% - remapping (3D data processed sequentally through the images) + h=waitbar(0.5,'Remapping Data','Windowstyle','Modal'); + [ExpX,ExpY,ExpZ]=Remap(ExpX,ExpY,ExpZ); + close(h) +end +% % conversion to int32 (normalized to use the full resolution of int32) +% ExpZ=int32(double(intmax('int32'))*ExpZ/max(max(max(ExpZ))) ); +% IGOR's scales +xaxis = [ExpX(1) mean(diff(ExpX))]; +if get(handles.menuExport,'Value')>=4; scale = [0 0; xaxis]; +else + yaxis = [ExpY(1) mean(diff(ExpY))]; + if get(handles.menuExport,'Value')>=2; scale = [0 0; xaxis; yaxis]; + else +% if repeated scans (such as hi-stat scans) the original Scan is ScanFull of the repeated parameters and Scan is their sequential numbers + scan = [Scan(1) mean(diff(Scan))]; + scale = [0 0; xaxis; yaxis; scan]; + ExpZ = permute(ExpZ, [3 1 2]); + end +end +% open writing waitbar +h=waitbar(0.5,'Saving Data','Windowstyle','Modal'); +% delete the file to overwrite which otherwise causes error in h5create +if exist(filename,'file'); delete(filename); end +% ExpY to ExpZ substitution for linear plots +if isempty(ExpZ); ExpZ=ExpY; end +% writing +h5create(filename, '/Matrix', size(ExpZ)); +h5write(filename, '/Matrix', ExpZ); +h5writeatt(filename, '/Matrix', 'IGORWaveNote', Note,'TextEncoding', 'system'); +h5writeatt(filename, '/Matrix', 'IGORWaveScaling', fliplr(scale)'); +% close waitbar +close(h) + +% % --- Executes on button press in pushbuttonExport. +% function pushbuttonExport_Callback(~,~,handles) +% % hObject handle to pushbuttonExport (see GCBO) +% global ScanFull Scan Data3 Note EAlign FullName AKx hFig ExpX ExpY ExpZ +% % DataX=Data; ECorrX=ECorr; EAlignX=EAlign; ACorrX=ACorr; +% % check data and activated corrections +% if isempty(Data3); errordlg('No Data','','modal'); return; end +% if contains(FullName,'_Export'); waitfor(warndlg('Data file seems already exported','')); end +% % filename to export +% Dots=strfind(FullName,'.'); dot=Dots(end); +% [filename,pathname]=uiputfile('*.h5','Export As',[FullName(1:dot-1) '_Export.h5']); +% if filename~=0; filename=[pathname filename]; +% else errordlg('Invalid Filename','','modal'); return; +% end +% % select export of the current image +% if get(handles.menuExport,'Value')==2 +% get(hFig,'UserData',UserData); +% ExpX=UserData.X; ExpY=UserData.Y; ExpZ=UserData.Z; +% % select export of the whole data +% else +% ExpX=AKx; ExpY=EAlign; ExpZ=Data3; +% end +% % open waitbar +% h=waitbar(0.5,'Remapping Data','Windowstyle','Modal'); +% % remapping (3D data processed sequentally through the images) +% [ExpX,ExpY,ExpZ]=Remap(ExpX,ExpY,ExpZ); +% % % conversion to int32 (normalization to use the full resolution of int32) +% % ExpZ=int32(double(intmax('int32'))*ExpZ/max(max(max(ExpZ))) ); +% % arrays in the IGOR-compatible format +% % repeated Data (any acquisition with ones(XXX)) are saved as a sequence of numbered frames and can no more be summed up with correlation; +% % all normal scans are OK because Scan is saved +% xaxis = [ExpX(1) mean(diff(ExpX))]; +% yaxis = [ExpY(1) mean(diff(ExpY))]; +% if isempty(Scan) +% scale = [0 0; xaxis; yaxis;]; +% else +% ExpZ = permute(ExpZ, [3 1 2]); +% % if repeated scans (such as hi-stat scans) the original Scan is ScanFull of the repeated parameters and Scan is their sequential numbers +% % scan = [Scan(1) mean(diff(Scan))]; +% scan = [ScanFull(1) mean(diff(ScanFull))]; +% scale = [0 0; xaxis; yaxis; scan]; +% end +% close(h); h=waitbar(0.5,'Saving Data','Windowstyle','Modal'); +% % delete the file to overwrite which otherwise causes error in h5create +% if exist(filename,'file'); delete(filename); end +% % write into HDF5 file +% h5create(filename, '/Matrix', size(ExpZ)); +% h5write(filename, '/Matrix', ExpZ); +% h5writeatt(filename, '/Matrix', 'IGORWaveNote', Note); +% h5writeatt(filename, '/Matrix', 'IGORWaveScaling', fliplr(scale)'); +% % close waitbar +% close(h); + +% --- Executes during object deletion, before destroying properties. +function figure1_DeleteFcn(~,~,~) +% handles of all figures +hPlots=findobj('Type','figure'); +% close all figures including the GUI +close(hPlots) + +% 07.01.2021 +% X,Y,Z from ProcessView are written by PlotAll to UserData of each plot; after zooming, PlotAll updates Z where all values outside the X/Y range are set to NaN +% RawZ excluded; contrast-enhanced ImZ deglobalized (it looks like previously zoom applied to already contrast-enhanced data) +% Global Z is set only in ProcessView diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/CompileMe.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/CompileMe.m new file mode 100644 index 0000000..0eaac2f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/CompileMe.m @@ -0,0 +1 @@ +mcc -a CurveFit.dat -a WarpFit.dat -e ARPESView.m \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ImgProcSetup.fig b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ImgProcSetup.fig new file mode 100644 index 0000000..97597a0 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ImgProcSetup.fig differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ImgProcSetup.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ImgProcSetup.m new file mode 100644 index 0000000..787ee8a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ImgProcSetup.m @@ -0,0 +1,108 @@ +function varargout = ImgProcSetup(varargin) +% IMGPROCSETUP MATLAB code for ImgProcSetup.fig +% IMGPROCSETUP, by itself, creates a new IMGPROCSETUP or raises the existing +% singleton*. +% H = IMGPROCSETUP returns the handle to a new IMGPROCSETUP or the handle to +% the existing singleton*. +% IMGPROCSETUP('CALLBACK',hObject,eventData,handles,...) calls the local +% function named CALLBACK in IMGPROCSETUP.M with the given input arguments. +% IMGPROCSETUP('Property','Value',...) creates a new IMGPROCSETUP or raises the +% existing singleton*. Starting from the left, property value pairs are +% applied to the GUI before ImgProcSetup_OpeningFcn gets called. An +% unrecognized property name or invalid value makes property application +% stop. All inputs are passed to ImgProcSetup_OpeningFcn via varargin. +% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one +% instance to run (singleton)". +% Last Modified by GUIDE v2.5 04-Nov-2020 16:11:59 +% Begin initialization code - DO NOT EDIT +gui_Singleton = 1; +gui_State = struct('gui_Name', mfilename, ... + 'gui_Singleton', gui_Singleton, ... + 'gui_OpeningFcn', @ImgProcSetup_OpeningFcn, ... + 'gui_OutputFcn', @ImgProcSetup_OutputFcn, ... + 'gui_LayoutFcn', [] , ... + 'gui_Callback', []); +if nargin && ischar(varargin{1}) + gui_State.gui_Callback = str2func(varargin{1}); +end +if nargout + [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); +else + gui_mainfcn(gui_State, varargin{:}); +end +% End initialization code - DO NOT EDIT + +% --- Executes just before ImgProcSetup is made visible. +function ImgProcSetup_OpeningFcn(hObject,~,handles,varargin) +% This function has no output args, see OutputFcn. +% hObject handle to figure +% varargin command line arguments to ImgProcSetup (see VARARGIN) +% Choose default command line output for ImgProcSetup +handles.output = hObject; +% Update handles structure +guidata(hObject, handles); +% figure properties +% set(gcf,'WindowStyle','modal') +% global parameters and their initialization +global presmdX presmdY structMode sharp sharpIni postsmdX postsmdY clipImgProcNeg +if isempty(presmdX); presmdX=0; end; set(handles.editPresmdX,'String',sprintf('%g',presmdX)); +if isempty(presmdY); presmdY=0; end; set(handles.editPresmdY,'String',sprintf('%g',presmdY)); +if isempty(structMode); structMode=1; end; set(handles.menuStructMode,'Value',structMode) +if structMode==1; set([handles.textSharp handles.editSharp],'Visible','Off'); else set([handles.textSharp handles.editSharp],'Visible','On'); end +sharpIni=0; if isempty(sharp); sharp=sharpIni; end; set(handles.editSharp,'String',sprintf('%g',sharp)); +if isempty(postsmdX); postsmdX=0; end; set(handles.editPostsmdX,'String',sprintf('%g',postsmdX)); +if isempty(postsmdY); postsmdY=0; end; set(handles.editPostsmdY,'String',sprintf('%g',postsmdY)); +if isempty(clipImgProcNeg); clipImgProcNeg=1; end; set(handles.radiobuttonClipImgProcNeg,'Value',clipImgProcNeg); +%if modeView==1; set(handles.menuStructMode,'String',{'None';'Curvature' ; '-d2I/dE2>0'}); else; set(handles.menuStructMode,'String',{'None';'Curvature'}); end +% % - figure position +% global xPos_View yPos_View +% Pos=get(gcf,'position'); offsetFigHeader=29; +% set(gcf,'position',[xPos_View yPos_View-Pos(4)-offsetFigHeader Pos(3) Pos(4)]); + +% --- Outputs from this function are returned to the command line. +function varargout = ImgProcSetup_OutputFcn(~,~,handles) +% varargout cell array for returning output args (see VARARGOUT); +% hObject handle to figure +% Get default command line output from handles structure +varargout{1} = handles.output; + +% --- Executes on button press in editPresmdX. +function editPresmdX_Callback(hObject,~,~) +global presmdX; presmdX=field2num(hObject,0); +% --- Executes on button press in editPresmdY. +function editPresmdY_Callback(hObject,~,~) +global presmdY; presmdY=field2num(hObject,0); + +% --- Executes on selection change in menuStructMode. +function menuStructMode_Callback(hObject,~,handles) +global structMode; structMode=get(hObject,'Value'); +if structMode==1; set([handles.textSharp handles.editSharp],'Visible','Off'); else set([handles.textSharp handles.editSharp],'Visible','On'); end + +function editSharp_Callback(hObject, ~,~) +global sharp sharpIni; sharp=field2num(hObject,sharpIni); + +% --- Executes on button press in editPostsmdX. +function editPostsmdX_Callback(hObject,~,~) +global postsmdX; postsmdX=field2num(hObject,0); +% --- Executes on button press in editPresmdY. +function editPostsmdY_Callback(hObject,~,~) +global postsmdY; postsmdY=field2num(hObject,0); + +% --- Executes on button press in radiobuttonClipImgProcNeg. +function radiobuttonClipImgProcNeg_Callback(hObject,~,~) +global clipImgProcNeg; clipImgProcNeg=get(hObject,'value'); + +% Hints: get(hObject,'String') returns contents of editSharp as text +% str2double(get(hObject,'String')) returns contents of editSharp as a double + +% % --- Executes on button press in editXRange. +% function editXRange_Callback(hObject,~,~) +% global XRange +% XRange=field2num(hObject); if length(XRange)~=2; XRange=[]; set(hObject,'String','Full'); end +% +% % --- Executes on button press in editYRange. +% function editYRange_Callback(hObject,~,~) +% global YRange +% YRange=field2num(hObject); if length(YRange)~=2; YRange=[]; set(hObject,'String','Full'); end + +% Hint: get(hObject,'Value') returns toggle state of radiobuttonClipImgProcNeg diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/LockSetup.fig b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/LockSetup.fig new file mode 100644 index 0000000..5d76510 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/LockSetup.fig differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/LockSetup.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/LockSetup.m new file mode 100644 index 0000000..a2c81fc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/LockSetup.m @@ -0,0 +1,86 @@ +function varargout = LockSetup(varargin) +% LOCKSETUP MATLAB code for LockSetup.fig +% LOCKSETUP, by itself, creates a new LOCKSETUP or raises the existing +% singleton*. +% H = LOCKSETUP returns the handle to a new LOCKSETUP or the handle to +% the existing singleton*. +% LOCKSETUP('CALLBACK',hObject,eventData,handles,...) calls the local +% function named CALLBACK in LOCKSETUP.M with the given input arguments. +% LOCKSETUP('Property','Value',...) creates a new LOCKSETUP or raises the +% existing singleton*. Starting from the left, property value pairs are +% applied to the GUI before LockSetup_OpeningFcn gets called. An +% unrecognized property name or invalid value makes property application +% stop. All inputs are passed to LockSetup_OpeningFcn via varargin. +% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one +% instance to run (singleton)". +% Last Modified by GUIDE v2.5 26-Apr-2020 14:27:52 +% Begin initialization code - DO NOT EDIT +gui_Singleton = 1; +gui_State = struct('gui_Name', mfilename, ... + 'gui_Singleton', gui_Singleton, ... + 'gui_OpeningFcn', @LockSetup_OpeningFcn, ... + 'gui_OutputFcn', @LockSetup_OutputFcn, ... + 'gui_LayoutFcn', [] , ... + 'gui_Callback', []); +if nargin && ischar(varargin{1}) + gui_State.gui_Callback = str2func(varargin{1}); +end +if nargout + [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); +else + gui_mainfcn(gui_State, varargin{:}); +end +% End initialization code - DO NOT EDIT + +% --- Executes just before LockSetup is made visible. +function LockSetup_OpeningFcn(hObject,~,handles,varargin) +% This function has no output args, see OutputFcn. +% hObject handle to figure +% varargin command line arguments to LockSetup (see VARARGIN) +% Choose default command line output for LockSetup +handles.output = hObject; +% Update handles structure +guidata(hObject, handles); +% figure properties +% set(gcf,'WindowStyle','modal') +% global parameters +% - initial values +global feat_Lock setTo_Lock dESm_Lock dEWin_Lock +if isequal(feat_Lock,'Peak'); set(handles.popupmenuFeat,'Value',2); else set(handles.popupmenuFeat,'Value',1); end +set(handles.editSetTo,'String',num2str(setTo_Lock)); +if isempty(dESm_Lock); set(handles.editSmooth,'String','Auto'); else; set(handles.editSmooth,'String',num2str(dESm_Lock)); end +if isempty(dEWin_Lock); set(handles.editSearch,'String','Auto'); else; set(handles.editSearch,'String',num2str(dEWin_Lock)); end +% % - figure position +% global xPos_Lock yPos_Lock +% Pos=get(gcf,'position'); offsetFigHeader=29; +% set(gcf,'position',[xPos_Lock yPos_Lock-Pos(4)-offsetFigHeader Pos(3) Pos(4)]); + +% --- Outputs from this function are returned to the command line. +function varargout = LockSetup_OutputFcn(~,~,handles) +% varargout cell array for returning output args (see VARARGOUT); +% hObject handle to figure +% Get default command line output from handles structure +varargout{1} = handles.output; + +% --- Executes on selection change in popupmenuFeat. +function popupmenuFeat_Callback(hObject,~,~) +global feat_Lock +val=get(hObject,'Value'); if val==2; feat_Lock='Peak'; end + +% --- Executes on button press in editSetTo. +function editSetTo_Callback(hObject,~,~) +global setTo_Lock +setTo_Lock=str2num(get(hObject,'String')); +if isempty(setTo_Lock); set(hObject,'String','0.0'); end + +% --- Executes on button press in editSmooth. +function editSmooth_Callback(hObject,~,~) +global dESm_Lock +dESm_Lock=str2num(get(hObject,'String')); +if isempty(dESm_Lock); set(hObject,'String','Auto'); end + +% --- Executes on button press in editSearch. +function editSearch_Callback(hObject,~,~) +global dEWin_Lock +dEWin_Lock=str2num(get(hObject,'String')); +if isempty(dEWin_Lock); set(hObject,'String','Auto'); end diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NaviSetup.fig b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NaviSetup.fig new file mode 100644 index 0000000..c3fe185 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NaviSetup.fig differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NaviSetup.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NaviSetup.m new file mode 100644 index 0000000..492411d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NaviSetup.m @@ -0,0 +1,113 @@ +function varargout = NaviSetup(varargin) +% Ver. 21Aug2022 +% NAVISETUP MATLAB code for NaviSetup.fig +% NAVISETUP, by itself, creates a new NAVISETUP or raises the existing +% singleton*. +% H = NAVISETUP returns the handle to a new NAVISETUP or the handle to +% the existing singleton*. +% NAVISETUP('CALLBACK',hObject,eventData,handles,...) calls the local +% function named CALLBACK in NAVISETUP.M with the given input arguments. +% NAVISETUP('Property','Value',...) creates a new NAVISETUP or raises the +% existing singleton*. Starting from the left, property value pairs are +% applied to the GUI before NaviSetup_OpeningFcn gets called. An +% unrecognized property name or invalid value makes property application +% stop. All inputs are passed to NaviSetup_OpeningFcn via varargin. +% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one +% instance to run (singleton)". +% Last Modified by GUIDE v2.5 21-May-2020 19:44:12 +% Begin initialization code - DO NOT EDIT +gui_Singleton = 1; +gui_State = struct('gui_Name', mfilename, ... + 'gui_Singleton', gui_Singleton, ... + 'gui_OpeningFcn', @NaviSetup_OpeningFcn, ... + 'gui_OutputFcn', @NaviSetup_OutputFcn, ... + 'gui_LayoutFcn', [] , ... + 'gui_Callback', []); +if nargin && ischar(varargin{1}) + gui_State.gui_Callback = str2func(varargin{1}); +end +if nargout + [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); +else + gui_mainfcn(gui_State, varargin{:}); +end +% End initialization code - DO NOT EDIT + +% --- Executes just before NaviSetup is made visible. +function NaviSetup_OpeningFcn(hObject,~,handles,varargin) +% This function has no output args, see OutputFcn. +% hObject handle to figure +% varargin command line arguments to NaviSetup (see VARARGIN) +% Choose default command line output for NaviSetup +handles.output = hObject; +% Update handles structure +guidata(hObject, handles); +% figure properties +% set(gcf,'WindowStyle','modal') +% global parameters +global surfNx_Navi hv_N eB_N kx_N thtM thtM_N thtA_N alpha +set(handles.editHv,'String',sprintf('%0.3f',hv_N)); +thtM_N=thtM; set(handles.editThtM,'String',sprintf('%0.3f',thtM_N)); +set(handles.editEB,'String',sprintf('%0.3f',eB_N)); +kx_N=0; % kx_N=[]; +set(handles.editKx,'String',sprintf('%0.3f',kx_N)); +set(handles.editThtA,'String',sprintf('%0.3f',thtA_N)); +surfNx_Navi=SurfNormX(hv_N,eB_N,kx_N,thtM_N,thtA_N,alpha); +set(handles.textSurfNormX,'String',['surfNx = ' sprintf('%0.3f',surfNx_Navi)]); +% % - figure position +% global xPos_Navi yPos_Navi +% if ~isempty(xPos_Navi*yPos_Navi) +% Pos=get(gcf,'position'); offsetFigHeader=29; set(gcf,'position',[xPos_Navi yPos_Navi-Pos(4)-offsetFigHeader Pos(3) Pos(4)]); +% end + +% --- Outputs from this function are returned to the command line. +function varargout = NaviSetup_OutputFcn(~,~,handles) +% varargout cell array for returning output args (see VARARGOUT); +% hObject handle to figure +% Get default command line output from handles structure +varargout{1} = handles.output; + +function editHv_Callback(hObject,~,handles) +global hv_N eB_N kx_N thtM_N thtA_N surfNx_Navi alpha +hv_N=field2num(hObject); +if length(hv_N)==1 + surfNx_Navi=SurfNormX(hv_N,eB_N,kx_N,thtM_N,thtA_N,alpha); + set(handles.textSurfNormX,'String',['surfNx = ' sprintf('%0.3f',surfNx_Navi)]); +end +%set(hObject,'String',num2str(hv_N)) + +function editThtM_Callback(hObject,~,handles) +global hv_N eB_N kx_N thtM_N thtA_N surfNx_Navi alpha +thtM_N=field2num(hObject); +if length(thtM_N)==1 + surfNx_Navi=SurfNormX(hv_N,eB_N,kx_N,thtM_N,thtA_N,alpha); + set(handles.textSurfNormX,'String',['surfNx = ' sprintf('%0.3f',surfNx_Navi)]); +end +%set(hObject,'String',num2str(thtM_N)) + +function editKx_Callback(hObject,~,handles) +global hv_N eB_N kx_N thtM_N thtA_N surfNx_Navi alpha +kx_N=field2num(hObject); +if length(kx_N)==1 + surfNx_Navi=SurfNormX(hv_N,eB_N,kx_N,thtM_N,thtA_N,alpha); + set(handles.textSurfNormX,'String',['surfNx = ' sprintf('%0.3f',surfNx_Navi)]); +end +%set(hObject,'String',num2str(kx_N)) + +function editThtA_Callback(hObject,~,handles) +global hv_N eB_N kx_N thtM_N thtA_N surfNx_Navi alpha +thtA_N=field2num(hObject); +if length(thtA_N)==1 + surfNx_Navi=SurfNormX(hv_N,eB_N,kx_N,thtM_N,thtA_N,alpha); + set(handles.textSurfNormX,'String',['surfNx = ' sprintf('%0.3f',surfNx_Navi)]); +end +%set(hObject,'String',num2str(thtA_N)) + +function editEB_Callback(hObject,~,handles) +global hv_N eB_N kx_N thtM_N thtA_N surfNx_Navi alpha +eB_N=field2num(hObject); +if length(eB_N)==1 + surfNx_Navi=SurfNormX(hv_N,eB_N,kx_N,thtM_N,thtA_N,alpha); + set(handles.textSurfNormX,'String',['surfNx= ' sprintf('%0.3f',surfNx_Navi)]); +end +%set(hObject,'String',num2str(eB_N)) diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NormSetup.fig b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NormSetup.fig new file mode 100644 index 0000000..2b54ea4 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NormSetup.fig differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NormSetup.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NormSetup.m new file mode 100644 index 0000000..0799f3b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/NormSetup.m @@ -0,0 +1,87 @@ +function varargout = NormSetup(varargin) +% NORMSETUP MATLAB code for NormSetup.fig +% NORMSETUP, by itself, creates a new NORMSETUP or raises the existing +% singleton*. +% H = NORMSETUP returns the handle to a new NORMSETUP or the handle to +% the existing singleton*. +% NORMSETUP('CALLBACK',hObject,eventData,handles,...) calls the local +% function named CALLBACK in NORMSETUP.M with the given input arguments. +% NORMSETUP('Property','Value',...) creates a new NORMSETUP or raises the +% existing singleton*. Starting from the left, property value pairs are +% applied to the GUI before NormSetup_OpeningFcn gets called. An +% unrecognized property name or invalid value makes property application +% stop. All inputs are passed to NormSetup_OpeningFcn via varargin. +% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one +% instance to run (singleton)". +% Last Modified by GUIDE v2.5 04-Nov-2020 16:28:10 +% Begin initialization code - DO NOT EDIT +gui_Singleton = 1; +gui_State = struct('gui_Name', mfilename, ... + 'gui_Singleton', gui_Singleton, ... + 'gui_OpeningFcn', @NormSetup_OpeningFcn, ... + 'gui_OutputFcn', @NormSetup_OutputFcn, ... + 'gui_LayoutFcn', [] , ... + 'gui_Callback', []); +if nargin && ischar(varargin{1}) + gui_State.gui_Callback = str2func(varargin{1}); +end +if nargout + [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); +else + gui_mainfcn(gui_State, varargin{:}); +end +% End initialization code - DO NOT EDIT + +% --- Executes just before NormSetup is made visible. +function NormSetup_OpeningFcn(hObject,~,handles,varargin) +% This function has no output args, see OutputFcn. +% hObject handle to figure +% varargin command line arguments to NormSetup (see VARARGIN) +% Choose default command line output for NormSetup +handles.output = hObject; +% Update handles structure +guidata(hObject, handles); +% figure properties +% set(gcf,'WindowStyle','modal') +% global parameters +% - initial values +global RangeNorm scCoeff scCoeffIni clipNormNeg +% if isempty(RangeNorm)||isempty(str2num(RangeNorm)); set(handles.editRange,'String','Full'); else set(handles.editRange,'String',sprintf('%g:%g',RangeNorm)); end +if isempty(RangeNorm); set(handles.editRange,'String','Full'); else set(handles.editRange,'String',sprintf('%g:%g',RangeNorm)); end +if isempty(scCoeff); scCoeff=scCoeffIni; end; set(handles.editSubtr,'String',num2str(scCoeff)) +if isempty(clipNormNeg); clipNormNeg=1; end; set(handles.radiobuttonClipNormNeg,'Value',clipNormNeg) +% % - figure position +% global xPos_Norm yPos_Norm +% Pos=get(gcf,'position'); offsetFigHeader=29; +% set(gcf,'position',[xPos_Norm yPos_Norm-Pos(4)-offsetFigHeader Pos(3) Pos(4)]); + +% --- Outputs from this function are returned to the command line. +function varargout = NormSetup_OutputFcn(~,~,handles) +% varargout cell array for returning output args (see VARARGOUT); +% hObject handle to figure +% Get default command line output from handles structure +varargout{1} = handles.output; + +% --- Executes on button press in editRange. +function editRange_Callback(hObject,~,~) +% hObject handle to editRange (see GCBO) +% clear normalization array +global RangeNorm IDiv ISubtr +IDiv=[]; ISubtr=[]; disp('- cleared IDiv ISubtr') +% energy range +% RangeStr=get(hObject,'String'); RangeStr=strrep(RangeStr,':',' '); Range=sort(str2num(RangeStr)); +% if length(Range)==2; RangeNorm=Range; else RangeNorm=RangeIni; end +RangeNorm=field2num(hObject); if length(RangeNorm)~=2; RangeNorm=[]; set(hObject,'String','Full'); end +% set(hObject,'String',[num2str(RangeNorm(1)) ':' num2str(RangeNorm(2))]); + +% --- Executes on button press in editSubtr. +function editSubtr_Callback(~,~,handles) +% hObject handle to editSubtr (see GCBO) +global scCoeff scCoeffIni +% Scaling coefficient to subtract angle-integrated spectrum +scCoeff=field2num(handles.editSubtr,scCoeffIni); +% set(handles.editSubtr,'String',num2str(scCoeffIni)); + +% --- Executes on button press in radiobuttonClipNormNeg. +function radiobuttonClipNormNeg_Callback(hObject,~,~) +global clipNormNeg; clipNormNeg=get(hObject,'value'); \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/RawTableDisplay.fig b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/RawTableDisplay.fig new file mode 100644 index 0000000..ecf1c81 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/RawTableDisplay.fig differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/RawTableDisplay.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/RawTableDisplay.m new file mode 100644 index 0000000..89766ad --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/RawTableDisplay.m @@ -0,0 +1,44 @@ +function varargout = RawTableDisplay(varargin) +% Created by X. Wang, 02-Feb-2021 + +% Begin initialization code - DO NOT EDIT +gui_Singleton = 1; +gui_State = struct('gui_Name', mfilename, ... + 'gui_Singleton', gui_Singleton, ... + 'gui_OpeningFcn', @RawTableDisplay_OpeningFcn, ... + 'gui_OutputFcn', @RawTableDisplay_OutputFcn, ... + 'gui_LayoutFcn', [] , ... + 'gui_Callback', []); +if nargin && ischar(varargin{1}) + gui_State.gui_Callback = str2func(varargin{1}); +end +if nargout + [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); +else + gui_mainfcn(gui_State, varargin{:}); +end +% End initialization code - DO NOT EDIT + +% --- Executes just before RawTableDisplay is made visible. +function RawTableDisplay_OpeningFcn(hObject,~, handles, varargin) +% This function has no output args, see OutputFcn. +% varargin command line arguments to RawTableDisplay (see VARARGIN) +% Set table properties +emptyRow = TableColumns.emptyRow(); numberColumns = TableColumns.Activate - 1; set(handles.tableRaw, 'Data', emptyRow(1:numberColumns)); +coledit = true(1, numberColumns); set(handles.tableRaw, 'ColumnEditable', coledit); +colname = TableColumns.columnNames(); set(handles.tableRaw, 'ColumnName', colname(1:numberColumns)); +colformat = TableColumns.columnFormats(); set(handles.tableRaw, 'ColumnFormat', colformat(1:numberColumns)); +colwidth = TableColumns.columnWidth(); colwidth{TableColumns.File} = 0; colwidth{TableColumns.Comment} = 0; +colwidth{TableColumns.Sweeps} = 50; colwidth{TableColumns.Y} = 'auto'; set(handles.tableRaw, 'ColumnWidth', colwidth); +% Find main GUI from input argument +rawData = varargin{1}; +set(handles.tableRaw, 'Data', rawData); +handles.output = hObject; +% Update handles structure +guidata(hObject, handles); uiwait(hObject); + +% --- Outputs from this function are returned to the command line. +function varargout = RawTableDisplay_OutputFcn(~,~,~) +% varargout cell array for returning output args (see VARARGOUT); +% Get default command line output from handles structure +%varargout{1} = handles.output; diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/TableColumns.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/TableColumns.m new file mode 100644 index 0000000..3a319ac --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/TableColumns.m @@ -0,0 +1,72 @@ +% X. Wang, 02-Feb-2021 +classdef TableColumns < uint32 + enumeration + % File + File(1) + Comment(2) + % Beamline + hv(3) + Polarization(4) + Slit(5) + % Analyzer + Mode(6) + Epass(7) + EbEk(8) + Energy(9) + dt(10) + Sweeps(11) + % Manipulator + Theta(12) + Tilt(13) + Azimuth(14) + X(15) + Y(16) + Z(17) + % Control + Activate(18) + Action(19) + Time(20) + end + methods(Static) + function v = numberColumns() + v = 20; + end + function v = vectorizableColumns() + v = [hv, Theat, Tilt, Azimuth, X, Z]; + end + function v = emptyRow() + v = {'' '' ... % File + '' '' [] ... % Beamline + '' [] '' '' '' [] ... % Analyzer + '' '' '' '' '' ''... % Manipulator + false 'Select' '' % Control + }; + end + function v = columnNames() + v = {'File', 'Comment', ... + 'hv', 'Pol', 'Slit', ... + 'Mode', 'Epass', 'Eb/k', 'Energy', 'dt(s)', 'Sweeps', ... + 'Theta', ... + 'Tilt', ... + 'Azim', ... + 'X', ... + 'Y', ... + 'Z', ... + 'Activate', 'Action', 'T(min)'}; + end + function v = columnFormats() + v = {'char', 'char', ... + 'char', {'LH','LV','C+','C-'}, 'char',... + {'WAM','MAM','LAD'}, 'char', {'Eb','Ek'}, 'char', 'char', 'char', ... + 'char', 'char', 'char', 'char', 'char', 'char' ... + 'logical', {'Select','Clear','Copy','Paste','Edit Raw', 'Load Raw'}, 'char'}; + end + function v = columnWidth() + v = {122 122 ... + 80 40 40 ... + 45 40 40 80 30 0 ... + 70 70 70 70 0 70 ... + 50 70 70}; + end + end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ViewSetup.fig b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ViewSetup.fig new file mode 100644 index 0000000..fd17365 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ViewSetup.fig differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ViewSetup.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ViewSetup.m new file mode 100644 index 0000000..c4bbf43 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/ViewSetup.m @@ -0,0 +1,90 @@ +function varargout = ViewSetup(varargin) +% VIEWSETUP MATLAB code for ViewSetup.fig +% VIEWSETUP, by itself, creates a new VIEWSETUP or raises the existing +% singleton*. +% H = VIEWSETUP returns the handle to a new VIEWSETUP or the handle to +% the existing singleton*. +% VIEWSETUP('CALLBACK',hObject,eventData,handles,...) calls the local +% function named CALLBACK in VIEWSETUP.M with the given input arguments. +% VIEWSETUP('Property','Value',...) creates a new VIEWSETUP or raises the +% existing singleton*. Starting from the left, property value pairs are +% applied to the GUI before ViewSetup_OpeningFcn gets called. An +% unrecognized property name or invalid value makes property application +% stop. All inputs are passed to ViewSetup_OpeningFcn via varargin. +% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one +% instance to run (singleton)". +% Last Modified by GUIDE v2.5 05-Nov-2020 12:36:57 +% Begin initialization code - DO NOT EDIT +gui_Singleton = 1; +gui_State = struct('gui_Name', mfilename, ... + 'gui_Singleton', gui_Singleton, ... + 'gui_OpeningFcn', @ViewSetup_OpeningFcn, ... + 'gui_OutputFcn', @ViewSetup_OutputFcn, ... + 'gui_LayoutFcn', [] , ... + 'gui_Callback', []); +if nargin && ischar(varargin{1}) + gui_State.gui_Callback = str2func(varargin{1}); +end +if nargout + [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); +else + gui_mainfcn(gui_State, varargin{:}); +end +% End initialization code - DO NOT EDIT + +% --- Executes just before ViewSetup is made visible. +function ViewSetup_OpeningFcn(hObject,~,handles,varargin) +% This function has no output args, see OutputFcn. +% hObject handle to figure +% varargin command line arguments to ViewSetup (see VARARGIN) +% Choose default command line output for ViewSetup +handles.output = hObject; +% Update handles structure +guidata(hObject, handles); +% figure properties +% set(gcf,'WindowStyle','modal') +% global parameters +% - initial values +global FracView FracViewIni XRange YRange viewMode gamma gammaIni render renderIni +if viewMode==2; set([handles.editFracView handles.editGamma handles.popupmenuRender],'Enable','Off'); +else set([handles.editFracView handles.editGamma handles.popupmenuRender],'Enable','On'); end +if isempty(FracView); FracView=FracViewIni; end; set(handles.editFracView,'String',sprintf('%g:%g',FracView)); +if isempty(XRange); set(handles.editXRange,'String','Full'); else; set(handles.editXRange,'String',sprintf('%g:%g',XRange)); end +if isempty(YRange); set(handles.editYRange,'String','Full'); else; set(handles.editYRange,'String',sprintf('%g:%g',YRange)); end +gammaIni=1; if isempty(gamma); gamma=gammaIni; end; set(handles.editGamma,'String',gamma); +renderIni='Flat'; if isempty(render); render=renderIni; end; if isequal(render,'Flat'); set(handles.popupmenuRender,'value',1); else set(handles.popupmenuRender,'value',2); end +% % - figure position +% global xPos_View yPos_View +% Pos=get(gcf,'position'); offsetFigHeader=29; +% set(gcf,'position',[xPos_View yPos_View-Pos(4)-offsetFigHeader Pos(3) Pos(4)]); + +% --- Outputs from this function are returned to the command line. +function varargout = ViewSetup_OutputFcn(~,~,handles) +% varargout cell array for returning output args (see VARARGOUT); +% hObject handle to figure +% Get default command line output from handles structure +varargout{1} = handles.output; + +% --- Executes on button press in editFracView. +function editFracView_Callback(hObject,~,~) +global FracView FracViewIni +FracView=field2num(hObject); if length(FracView)~=2; FracView=FracViewIni; set(hObject,'String',sprintf('%g:%g',FracView)); end + +% --- Executes on button press in editXRange. +function editXRange_Callback(hObject,~,~) +global XRange +XRange=field2num(hObject); if length(XRange)~=2; XRange=[]; set(hObject,'String','Full'); end + +% --- Executes on button press in editYRange. +function editYRange_Callback(hObject,~,~) +global YRange +YRange=field2num(hObject); if length(YRange)~=2; YRange=[]; set(hObject,'String','Full'); end + +function editGamma_Callback(hObject,~,~) +global gamma +gamma=field2num(hObject,1); set(hObject,'String',num2str(gamma)) + +% --- Executes on selection change in popupmenuRender. +function popupmenuRender_Callback(hObject,~,~) +global render +val=get(hObject,'Value'); if val==1; render='Flat'; else render='Interp'; end diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/field2num.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/field2num.m new file mode 100644 index 0000000..ecbe028 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ARPESView/field2num.m @@ -0,0 +1,16 @@ +function Num = field2num(Field,DefaultNum) +% Num = field2num(Field [,DefaultNum]) reads numerical input in Field (scalar or +% a two-element vector separated by colon) into Num relayed in the field. If input +% is invalid and DefaultNum specified, Num and the field are set to DefaultNum. + +% if ~isequal(Field,'hObject'); eval('Field=[''handles.'' Field];'); end % does not work +Str=get(Field,'String'); if ~isempty(findstr(Str,' ')); Str='XXX'; end; Str=strrep(Str,':',' '); +% Num=sort(str2num(Str)); +Num=str2num(Str); +if nargin>1 + if isempty(Num)||length(Num)>2; Num=DefaultNum; + if length(DefaultNum)==1; set(Field,'String',sprintf('%g',DefaultNum)) + else set(Field,'String',sprintf('%g:%g',DefaultNum)) + end + end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/AlignEF.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/AlignEF.m new file mode 100644 index 0000000..6126915 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/AlignEF.m @@ -0,0 +1,81 @@ +function [EAlign,EF,Fail]=AlignEF(Data,ECorr,eWin,dEWin,dESmooth,feat) +% [EAlign,EF,Fail]=AlignEF(Data,ECorr [,eWin] [,dEWin] [,dESmooth] [,feat]) aligns the energy scale relative +% to EF or peak . The inputs are 2D or 3D data array Data, corresponding 1D-column % vector or +% (curvature corrected) 2D-matrix of energies ECorr, (optional scalar/vector of the length size(Data,3) or +% empty value) approximate EF position eWin, (optional or empty value) width of the EF support dEWin, +% (optional or empty value) Gaussian pre-smoothing energy width dESmooth, and (optional or empty +% value) feat = 'Peak' (case-insensitive) defines the feature to align as a peak instead of the default Fermi +% edge. If eWin,dEWin and dESmooth are skipped or empty values, they take reasonable automatic +% values. The output EF is the determined EF positions in the input energy scale. Fail returns the indices +% of the scans where the alignment failed and EF was set to eWin. +% - Ver. 7 Mar 2020 (added vectorization of eWin) +disp('- EF alignment') + +% parameters +% - dimensions +nE=size(Data,1); nA=size(Data,2); nS=size(Data,3); +% - energy matrix +if size(ECorr,2)==1; rep=1; ECorr=repmat(ECorr,1,nA); else rep=0; end +% - energy interval and step +eMin=max(ECorr(1,:)); eMax=min(ECorr(end,:)); eInterval=eMax-eMin; dE=eInterval/(size(ECorr,1)-1); +% - failed alignment indices +Fail=[]; +% automatic parameters +if nargin<6; feat='Edge'; end +if nargin<5; dESmooth=[]; end; if isempty(dESmooth); dESmooth=0.01*eInterval; end +if nargin<4; dEWin=[]; end; if isempty(dEWin); dEWin=0.1*eInterval; end +if nargin<3; eWin=[]; end; if isempty(eWin); eWin=eMin+0.7*eInterval; dEWin=0.1*eInterval; end +if isscalar(eWin); eWin=eWin*ones(1,size(Data,3)); end +if length(eWin)~=size(Data,3); disp('- AlignEF: Incompatible eWin length'); return; end + +% angle integration (can be replaced by evalc(IntAngle(...), where evalc suppresses text output) +% - reference grid +EInt=(eMin:dE:eMax)'; +% - cycle over angles in triads for speed +AngleInt=zeros(length(EInt),nS); +for iS=1:nS + if nA>1 + for iA=round(0.05*nA)+1:3:round(0.95*nA)-1 +% - interpolation on the reference grid + ACorr=interp1(ECorr(:,iA),sum(Data(:,iA-1:iA+1,iS),2),EInt); +% - angle integration + AngleInt(:,iS)=AngleInt(:,iS)+ACorr; + end + else + AngleInt(:,iS)=Data(:,1,nS); + end +end + +% processing +% - logarithmic derivative if edge not peak +if ~isequal(lower(feat),'peak') + D=AngleInt(3:length(EInt),:)-AngleInt(1:length(EInt)-2,:); D=[D(1,:);D;D(end,:)]; + D=D./AngleInt; +else D=-1*AngleInt; end +% - smoothing (after the derivation to suppress the spikes) +hwPts=dESmooth/dE; hsPts=3*hwPts; DS=Gaco1(D,hwPts,hsPts); + +% alignment at EF +% - cycle through scans +EAlign=zeros(nE,nA,nS); EF=zeros(1,nS); +for iS=1:nS + % - alignment region + DS1=DS(EInt>=eWin(iS)-dEWin/2&EInt<=eWin(iS)+dEWin/2,iS); + ERef=EInt(EInt>=eWin(iS)-dEWin/2&EInt<=eWin(iS)+dEWin/2); +% - locating the minimum + L=DS1(1:end-2); C=DS1(2:end-1); R=DS1(3:end); IMinima=1+find(C12; mode=3; end; if aRange>18; mode=2; end; if aRange>24; mode=1; end; + +% load curvature correction +CurveFit=load(CurveFit); +% select the mode +ind=find(CurveFit(:,1)==mode); +if isempty(ind); disp('- Error: Angular mode not curvature calibrated'); ECorr=[]; return +else CurveFit=CurveFit(ind,2:end); +end +% interpolate fitting coefficients +if size(CurveFit,1)==1 + curveFit=CurveFit(2:end); +else + Ep=[0;CurveFit(:,1);realmax]; + CurveFit=[CurveFit(1,2:end);CurveFit(:,2:end);CurveFit(end,2:end)]; + curveFit=interp1q(Ep',CurveFit,ep); +end +% append zero constant term +curveFit=[curveFit 0]; + +% angle-dependent energy correction +ECorr=polyval(curveFit,Angle)*ep; +% corrected energy matrix +ECorr=repmat(Energy,1,nA)-repmat(ECorr,length(Energy),1); \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/CurveFit.dat b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/CurveFit.dat new file mode 100644 index 0000000..a9c4b01 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/CurveFit.dat @@ -0,0 +1,59 @@ +% WAM data: Derived from the data taken on 10.07.2013 with Ag 3d doublet, +% only the high-energy peak, Ek~350eV, range +/-14deg, Uconv=-0.1*Ep + 1.0000000e+00 3.0000000e+01 5.7549797e-08 2.1158619e-07 -3.3674509e-05 -8.4042108e-05 + 1.0000000e+00 3.5000000e+01 1.0505235e-07 7.1089350e-07 -5.1345310e-05 -1.5238416e-04 + 1.0000000e+00 4.0000000e+01 9.2186459e-08 6.4460407e-07 -4.5949043e-05 -1.3554235e-04 + 1.0000000e+00 5.0000000e+01 7.0686093e-08 5.2940559e-07 -3.9347857e-05 -1.1235947e-04 + 1.0000000e+00 6.0000000e+01 5.6283692e-08 4.5041152e-07 -3.3508238e-05 -9.4024728e-05 + 1.0000000e+00 7.0000000e+01 4.6072350e-08 3.8347197e-07 -3.0571355e-05 -8.1005505e-05 + 1.0000000e+00 8.0000000e+01 2.9146535e-08 2.2734112e-07 -2.4364012e-05 -5.0864007e-05 + 1.0000000e+00 9.0000000e+01 2.5496097e-08 1.9852660e-07 -2.4291307e-05 -4.4976466e-05 + 1.0000000e+00 1.0000000e+02 3.1989259e-08 2.4854284e-07 -2.8141413e-05 -5.4139857e-05 + 1.0000000e+00 1.1000000e+02 2.7389427e-08 2.5019251e-07 -2.6970258e-05 -5.4302099e-05 + 1.0000000e+00 1.2000000e+02 2.2344655e-08 2.3894543e-07 -2.5521078e-05 -5.1900527e-05 + 1.0000000e+00 1.3000000e+02 2.0850462e-08 2.2253980e-07 -2.4625183e-05 -4.9655316e-05 + 1.0000000e+00 1.5000000e+02 1.8535201e-08 2.1325583e-07 -2.3211084e-05 -4.6419003e-05 + 1.0000000e+00 1.7000000e+02 1.7530471e-08 1.9432319e-07 -2.2085372e-05 -4.2948120e-05 + 1.0000000e+00 1.9000000e+02 1.7808490e-08 1.9211485e-07 -2.1718196e-05 -4.1936317e-05 + 1.0000000e+00 2.1000000e+02 1.6743817e-08 1.7716850e-07 -2.1202846e-05 -3.9064115e-05 + 1.0000000e+00 2.3000000e+02 1.5972928e-08 1.6835411e-07 -2.0703645e-05 -3.7292074e-05 + +% MAM data: Derived from the data taken on 06.02.2014 with Au 4f doublet, +% only the high-energy peak, Ek=600eV, range +/-10deg, Uconv=-0.1*Ep + 2.0000000e+00 5.0000000e+01 -5.1437913e-08 -1.2542236e-08 -1.7764284e-05 -3.7514664e-05 + 2.0000000e+00 6.0000000e+01 -1.8041414e-08 -2.4458453e-08 -2.3996694e-05 -4.1370343e-05 + 2.0000000e+00 7.0000000e+01 2.9236181e-08 1.2566237e-07 -2.9297142e-05 -5.2360323e-05 + 2.0000000e+00 8.0000000e+01 1.2752606e-08 7.8533778e-08 -2.7479533e-05 -4.9415261e-05 + 2.0000000e+00 9.0000000e+01 7.5112234e-09 2.0679238e-08 -2.5652457e-05 -4.2271472e-05 + 2.0000000e+00 1.0000000e+02 -1.4011202e-08 2.8402782e-09 -2.2424522e-05 -3.9853476e-05 + 2.0000000e+00 1.1000000e+02 4.0507111e-09 5.9354326e-08 -2.4315809e-05 -4.3545690e-05 + 2.0000000e+00 1.2000000e+02 1.5488383e-08 8.7218602e-08 -2.5835792e-05 -4.4856094e-05 + 2.0000000e+00 1.3000000e+02 4.8677328e-09 1.4383923e-07 -2.3652203e-05 -4.6226302e-05 + 2.0000000e+00 1.5000000e+02 -5.7244407e-08 -5.8666841e-08 -1.7606347e-05 -3.4487768e-05 + 2.0000000e+00 1.7000000e+02 -4.1382132e-08 -2.8961874e-08 -1.9501614e-05 -3.6009241e-05 + 2.0000000e+00 1.9000000e+02 -2.2639470e-08 3.7623335e-09 -2.1696643e-05 -3.8397051e-05 + 2.0000000e+00 2.1000000e+02 -1.2801735e-08 -2.3204288e-08 -2.2944474e-05 -3.6757262e-05 + 2.0000000e+00 2.4000000e+02 -1.1737097e-08 -5.1748812e-09 -2.2853740e-05 -3.6909846e-05 + 2.0000000e+00 2.8000000e+02 -7.8257657e-09 1.2411199e-08 -2.3460122e-05 -3.7130127e-05 + 2.0000000e+00 3.2000000e+02 2.7760873e-09 2.3242272e-08 -2.4619223e-05 -3.7341181e-05 + 2.0000000e+00 3.6000000e+02 -1.5466724e-08 -1.2627854e-08 -2.2548439e-05 -3.4346397e-05 + 2.0000000e+00 4.0000000e+02 -1.8199853e-08 -1.9653684e-08 -2.2350511e-05 -3.3019789e-05 + +% LAD data: Derived from the data taken on 10.07.2013 with As 3d doublet, +% average of two peaks, Ek~450eV, range +/-7deg, Uconv=-0.1*Ep + 3.0000000e+00 2.0000000e+01 -5.6590710e-07 3.7657977e-07 -4.5918343e-05 -1.5095901e-04 + 3.0000000e+00 2.5000000e+01 -4.7487888e-08 8.0426266e-07 -5.3329296e-05 -1.0409184e-04 + 3.0000000e+00 3.0000000e+01 4.6092656e-08 5.1490354e-07 -5.7203510e-05 -9.6523178e-05 + 3.0000000e+00 4.0000000e+01 -3.9284756e-08 5.1742300e-07 -5.2464655e-05 -5.7580797e-05 + 3.0000000e+00 5.0000000e+01 -9.4676429e-08 3.5994451e-07 -5.5091213e-05 -4.8691923e-05 + 3.0000000e+00 6.0000000e+01 -1.7565702e-09 3.6889550e-07 -5.9880389e-05 -4.8252266e-05 + 3.0000000e+00 7.0000000e+01 -2.0084433e-08 4.1847882e-07 -5.8378467e-05 -4.8201603e-05 + 3.0000000e+00 8.0000000e+01 -8.1540589e-09 3.3351325e-07 -5.7895254e-05 -4.5131684e-05 + 3.0000000e+00 1.0000000e+02 6.1610583e-10 4.3373624e-07 -5.9036927e-05 -4.7745530e-05 + 3.0000000e+00 1.2000000e+02 -6.0724832e-09 3.4058051e-07 -5.8828172e-05 -4.3386438e-05 + 3.0000000e+00 1.4000000e+02 2.5038671e-08 2.7496880e-07 -6.0021915e-05 -3.9312189e-05 + 3.0000000e+00 1.6000000e+02 2.1618208e-09 2.6940645e-07 -5.9964532e-05 -3.9010305e-05 + 3.0000000e+00 1.8000000e+02 9.8608825e-09 2.5477795e-07 -6.0625964e-05 -3.6786976e-05 + 3.0000000e+00 2.2000000e+02 3.6290369e-08 2.3779143e-07 -6.1622441e-05 -3.2874057e-05 + 3.0000000e+00 2.6000000e+02 3.4024333e-08 2.3038477e-07 -6.0573206e-05 -3.1100064e-05 + 3.0000000e+00 2.6000000e+02 3.4024333e-08 2.3038477e-07 -6.0573206e-05 -3.1100064e-05 \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/CurveFit_Uc=0.dat b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/CurveFit_Uc=0.dat new file mode 100644 index 0000000..39a86cc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/CurveFit_Uc=0.dat @@ -0,0 +1,35 @@ +% WAM data: Derived from the data taken on 10.07.2013 with Ag3d doublet, +% only the high-energy peak, Ek~350eV, range +/-14deg, Uconv=0 + 1.0000000e+00 3.0000000e+01 2.1306546e-08 1.4768044e-07 -2.8795764e-05 -8.5032310e-05 +% 1.0000000e+00 3.0000000e+01 1.0393199e-07 3.3741764e-07 -3.8090737e-05 -9.8030810e-05 + 1.0000000e+00 3.5000000e+01 1.0631018e-07 7.5754682e-07 -5.1340744e-05 -1.5328049e-04 + 1.0000000e+00 4.0000000e+01 1.0080948e-07 6.8498696e-07 -4.7175019e-05 -1.3615200e-04 + 1.0000000e+00 5.0000000e+01 7.9379740e-08 5.8225266e-07 -4.1056249e-05 -1.1444108e-04 + 1.0000000e+00 6.0000000e+01 6.4803800e-08 4.9031506e-07 -3.5221582e-05 -9.4853610e-05 + 1.0000000e+00 7.0000000e+01 5.2840298e-08 4.0994889e-07 -3.2070365e-05 -8.0827960e-05 + 1.0000000e+00 8.0000000e+01 3.4672706e-08 2.4991694e-07 -2.5523078e-05 -5.1622928e-05 + 1.0000000e+00 9.0000000e+01 2.8673121e-08 2.1401474e-07 -2.5286271e-05 -4.5141067e-05 + 1.0000000e+00 1.0000000e+02 2.7832710e-08 2.0968809e-07 -2.5140436e-05 -4.3153996e-05 + 1.0000000e+00 1.1000000e+02 3.0312848e-08 2.7422049e-07 -2.8034394e-05 -5.4651777e-05 + 1.0000000e+00 1.2000000e+02 2.7064196e-08 2.6192190e-07 -2.6748270e-05 -5.2730280e-05 + 1.0000000e+00 1.3000000e+02 2.3602394e-08 2.4425979e-07 -2.5610484e-05 -5.0146420e-05 + 1.0000000e+00 1.5000000e+02 2.1596039e-08 2.3548527e-07 -2.4195916e-05 -4.7598225e-05 + 1.0000000e+00 1.7000000e+02 2.2027151e-08 2.2445147e-07 -2.3256239e-05 -4.4669348e-05 + 1.0000000e+00 1.9000000e+02 2.1021630e-08 2.0826566e-07 -2.2647293e-05 -4.1608327e-05 + 1.0000000e+00 2.1000000e+02 1.9713603e-08 1.9696854e-07 -2.2082909e-05 -3.9933074e-05 + 1.0000000e+00 2.3000000e+02 1.6458739e-08 1.6959803e-07 -2.0449888e-05 -3.4962645e-05 +% LAD data: Derived from the data taken on 08.09.2011 with Bi4f doublet, +% only the high-energy peak, Ek~335eV, range +/-8deg, Uconv=0. + 2.0000000e+00 2.0000000e+01 -3.8292981e-07 -6.8686463e-07 -2.0384950e-05 -4.4744837e-05 + 2.0000000e+00 3.0000000e+01 -9.1341088e-08 -3.3673794e-07 -3.8264046e-05 -3.3915924e-05 + 2.0000000e+00 4.0000000e+01 -1.9917581e-08 7.3363282e-08 -4.2197301e-05 -3.1728725e-05 + 2.0000000e+00 5.0000000e+01 2.7592216e-08 -1.3185723e-07 -4.5099978e-05 -2.6869346e-05 + 2.0000000e+00 6.0000000e+01 -4.6319220e-08 -8.6985546e-08 -4.2574396e-05 -2.9587033e-05 + 2.0000000e+00 7.0000000e+01 6.3612583e-08 1.3971578e-07 -4.7547438e-05 -3.1673379e-05 + 2.0000000e+00 8.0000000e+01 7.1098497e-08 7.5987040e-08 -4.7584179e-05 -3.1804050e-05 + 2.0000000e+00 1.0000000e+02 3.7604619e-08 -9.4977276e-08 -4.7238403e-05 -2.3134884e-05 + 2.0000000e+00 1.2500000e+02 -2.9897730e-08 -9.9245647e-08 -4.5563467e-05 -2.1980214e-05 + 2.0000000e+00 1.5000000e+02 5.9584031e-08 1.8400067e-07 -4.9629554e-05 -2.9789333e-05 + 2.0000000e+00 2.0000000e+02 6.7021293e-08 -6.2406963e-08 -4.9811175e-05 -2.2856145e-05 + 2.0000000e+00 2.5000000e+02 4.3345596e-09 -6.4595199e-08 -4.7740393e-05 -2.3217752e-05 + 2.0000000e+00 3.0000000e+02 3.1404303e-08 6.1270702e-08 -4.8883771e-05 -2.6030532e-05 \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Cut.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Cut.m new file mode 100644 index 0000000..b6eaa37 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Cut.m @@ -0,0 +1,74 @@ +function [XCut,DCut]=Cut(ACorr,ECorr,Data,xMode,Win) +% [XCut,DCut]=Cut(ACorr,ECorr,Data,xMode,Win) calculates 1D array DCut of intensity as +% a function of 1D array XCut(raw vector of angles/momenta) for xMode='mdc', or XCut +% (column vector of energies in Energy dimension) for xMode='edc'. The input 2D array +% Data of intensity is defined on the 1D (row) or 2D array ACorr of [warping corrected] +% angles/momenta and the 1D (column) or 2D array ECorr of curvature corrected [aligned] +% energies. DCut is integrated within the Win window [win1 win2] in energies (xMode='mdc') +% or angles/momenta (xMode='edc'). XCut is calculated in the middle of Win. +% Ver. 01.01.2021 + +% Revisions to Ver. 29.12.2017: Grossly reworked to correct the dimensions and linear/subscript indexing of the arrays meeting in the interpolation + +disp('- Data cut formation') + +% check inputs +% - supported modes +xMode=lower(xMode); +if ~isequal(xMode,'mdc') && ~isequal(xMode,'edc') + XCut=[]; DCut=[]; disp('Error: Only ''mdc'' and ''edc'' modes supported'); return; +end +% - integration window and its check +Win=sort(Win); +Win(1)=Win(1)+1e-10*diff(Win); Win(2)=Win(2)-1e-10*diff(Win); % to avoid the edge effects in the code +if isequal(xMode,'mdc') Range=[max(ECorr(1,:)) min(ECorr(end,:))]; +else Range=[max(ACorr(:,1)) min(ACorr(:,end))]; end +if Win(1)Range(2) + XCut=[]; DCut=[]; disp('Error: Inconsistent integration window'); return; +end + +% shaping the arrays +% - remove NaNs spoiling the cumulative sum +Data(isnan(Data))=0; +% - expanding ACorr and ECorr if 1D arrays +if size(ACorr,1)==1; ACorr=repmat(ACorr,size(Data,1),1); end +if size(ECorr,2)==1; ECorr=repmat(ECorr,1,size(Data,2)); end +% - array permutation to reduce the 'edc' mode to 'mdc' +if isequal(xMode,'edc') + ACorr=ACorr'; ECorr=ECorr'; Data=Data'; + T=ACorr; ACorr=ECorr; ECorr=T; clear T; +end +% - shifted energy arrays for locating the window +ECorr1=ECorr(1:end-1,:); ECorr2=ECorr(2:end,:); + +% parameters +de=mean(mean(diff(ECorr,1))); + +% array of intensity values DCut +% cumulative array +ISum=cumsum(Data(1:end,:),1)-0.5*Data(1:end,:)-0.5*Data(1,:); +% - point 1 +% - - subscripts and linear indices of the grid point below Win(1) +[I,J]=find(ECorr1<=Win(1)&ECorr2>Win(1)); Lin1=sub2ind(size(ECorr),I,J); +% - - linear indices of the grid point above Win(1) +Lin2=sub2ind(size(ECorr),I+1,J); +% - - interpolation of the linear matrices defined by linear indices +I1=ISum(Lin1)+(ISum(Lin2)-ISum(Lin1)).*(Win(1)-ECorr(Lin1))/de; +% - point 2 +[I,J]=find(ECorr1<=Win(2)&ECorr2>Win(2)); Lin1=sub2ind(size(ECorr),I,J); +Lin2=sub2ind(size(ECorr),I+1,J); +I2=ISum(Lin1)+(ISum(Lin2)-ISum(Lin1)).*(Win(2)-ECorr(Lin1))/de; +% integral value +DCut=I2-I1; +% normalization +DCut=DCut*de/(eps+diff(Win)); + +% array of coordinate values XCut interpolated in the middle of Win +% - this block runs ~25% of the integration block runtime +midE=mean(Win); +[I,J]=find(ECorr1<=midE&ECorr2>midE); +Lin1=sub2ind(size(ECorr),I,J); Lin2=sub2ind(size(ECorr),I+1,J); +XCut=ACorr(Lin1)+(ACorr(Lin2)-ACorr(Lin1)).*(midE-ECorr(Lin1))/de; + +% transpose if the MDC mode +if isequal(xMode,'mdc'); DCut=DCut'; XCut=XCut'; end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/DiffFlt2.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/DiffFlt2.m new file mode 100644 index 0000000..fcf2e17 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/DiffFlt2.m @@ -0,0 +1,29 @@ +function AA=DiffFlt2(A,scheme,sharp,dX2dY) +% AA=DiffFlt2(A,scheme,sharp [,dX2dY]) applies a curvature filter to sharpen the structure in the 2D array A. +% Inputs: +% scheme='1D' or '2D' selects 1D derivation along columns or 2D derivaton +% sharp from 0 to 1 tunes the sharpening essentially from smooth f'' to singular 1/f' +% dX2dY (if scheme='2D') is the step-width ratio between rows and columns +% Algorithm: Zhang et al, "A precise method for visualizing dispersive features in image plots," Revi. Sci. Instr. 82 (2011) 043712 + +% check input +if ~isequal(scheme,'1D')&&~isequal(scheme,'2D'); disp('Input error in CurvFlt2: scheme must be ''1D'' or ''2D'); AA=[]; return; end +if sharp<0||sharp>1; disp('Input error in CurvFlt2: sharp must be between 0 and 1'); AA=[]; return; end + +% sharpening constant +c=1/(sharp+eps)-1; + +% 1D derivation scheme +if isequal(scheme,'1D') +% - normalize the derivative + A1Sq=DifC(A,1).^2; A1Sq=A1Sq./mean(A1Sq(~isnan(A1Sq))); +% - calculate curvature + AA=DifC(A,2)./(c+A1Sq).^(3/2); +% 2D derivation scheme (neglecting cross-derivatives in the exact curvature) +else +% - normalize the partial derivatives along X and Y + A1XSq=DifC(A',1).^2; A1XSq=A1XSq./mean(A1XSq(~isnan(A1XSq))); + A1YSq=DifC(A,1).^2; A1YSq=A1YSq./mean(A1YSq(~isnan(A1YSq))); +% - calculate curvature + AA=(DifC(A',2)./(c+A1XSq).^(3/2))'+dX2dY^2*DifC(A,2)./(c+A1YSq).^(3/2); +end diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/014_FS.h5 b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/014_FS.h5 new file mode 100644 index 0000000..dcbff32 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/014_FS.h5 differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/BlindDeconvReport.mlx b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/BlindDeconvReport.mlx new file mode 100644 index 0000000..25f7303 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/BlindDeconvReport.mlx differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/BlindDeconvReport.pdf b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/BlindDeconvReport.pdf new file mode 100644 index 0000000..0afda8f Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/BlindDeconvReport.pdf differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive.mlx b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive.mlx new file mode 100644 index 0000000..135f427 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive.mlx differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive.pdf b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive.pdf new file mode 100644 index 0000000..7fffaee Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive.pdf differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive_WarpCurvCorr.mlx b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive_WarpCurvCorr.mlx new file mode 100644 index 0000000..87a7c32 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive_WarpCurvCorr.mlx differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive_WarpCurvCorr.pdf b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive_WarpCurvCorr.pdf new file mode 100644 index 0000000..35207ad Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Examples/ExamplesLive_WarpCurvCorr.pdf differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Gaco2.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Gaco2.m new file mode 100644 index 0000000..42b9aa2 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Gaco2.m @@ -0,0 +1,54 @@ +function AA=Gaco2(A,hwX,hwY,hsX,hsY) +% AA=Gaco2(A,hwX,hwY [,hsX] [,hsY]) convolves vector or matrix A with Gaussian of half-width/ +% half-support along the rows hwX/hsX (in inter-point distances > 0) and along the columns hwY/hsY. +% If empty or skipped, the default hsX=3*hwX and hsY=3*hwY. Setting hwX or hwY to zero disables +% convolution along the corresponding direction. The input A is padded by the end values. +% Gaco2 is equivalent to Gaco1 except that it convolves along both dimensions. +% Ver. 23.12.2020 + +% Update to Ver. 17.06.2017: 2D convolution changed to two 1D convolutions to keep the dimensionality at ~50% increase of runtime + +% default supports +if nargin<4||isempty(hsX); hsX=3*hwX; end; hsX=round(hsX); +if nargin<5||isempty(hsY); hsY=3*hwY; end; hsY=round(hsY); + +% convolution along rows +if hwX~=0 +% - normalized kernel + KX=-1*hsX:hsX; KX=exp(-1*(sqrt(log(2))*KX/(hwX)).^2); KX=KX/sum(KX); +% - padding + A=padarray(A,[0 hsX],'replicate','both'); +% - convolution + A=conv2(1,KX,A,'valid'); +end + +% convolution along columns +if hwY~=0 +% - normalized kernel + KY=(-1*hsY:hsY)'; KY=exp(-1*(sqrt(log(2))*KY/(hwY)).^2); KY=KY/sum(KY); +% - padding + A=padarray(A,[hsY 0],'replicate','both'); +% - convolution + A=conv2(KY,1,A,'valid'); +end + +% output +AA=A; + +% % Ver. 2017 (malfunctioning: changing dimensionality) +% % normalized convolution kernels +% % - along rows +% if hwX==0; hsX=0; KX=1; else +% KX=(-1*hsX:hsX)'; KX=exp(-1*(sqrt(log(2))*KX/(hwX)).^2); +% KX=KX/sum(KX); +% end +% % - along columns +% if hwY==0; hsY=0; KY=1; else +% KY=-1*hsY:hsY; KY=exp(-1*(sqrt(log(2))*KY/(hwY)).^2); KY=KY/sum(KY); +% end +% +% % padding A +% A=padarray(A,[hsY hsX],'replicate','both'); +% +% % convolution +% AA=conv2(KY,KX,A,'valid'); \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ImData.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ImData.m new file mode 100644 index 0000000..95cb89f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ImData.m @@ -0,0 +1,44 @@ +function h=ImData(X,Y,Z,style) +% [h=] ImData(X,Y,Z[,style]) plots image of Z(X,Y) using the style 'flat' (default) +% or 'interp' style. X and Y are vectors or 2D arrays, Z is 2D array. +% h (optional) can be used for further handling of the image (rotation, etc) + +% default style +if nargin==3; style='flat'; end + +% squeeze input arrays to 2D +% X=squeeze(X); Y=squeeze(X); Z=squeeze(Z); + +% X and Y matrices +% [X,Y]=meshgrid(X,Y); end +if size(X,1)==1||size(X,2)==1 + if size(X,1)>size(X,2); X=X'; end + X=repmat(X,size(Z,1),1); +end +if size(Y,1)==1||size(Y,2)==1 + if size(Y,1)1&&size(ECorr,3)==1; ECorr=repmat(ECorr,1,1,nS); end +% - reference energy grid +if nA==1&&nS==1; EInt=ECorr; +else eMin=max(max(ECorr(1,:,:))); eMax=min(min(ECorr(end,:,:))); EInt=linspace(eMin,eMax,nE)'; +end +% data within the angular interval/normalization +if size(ACorr,1)==1 +% - 1D-ACorr + Data=Data(:,Interval(1)<=ACorr&ACorr<=Interval(2),:); + nA=size(Data,2); Data=Data/nA; +else +% - 2D-ACorr + Out=find(Interval(1)>ACorr|ACorr>Interval(2)); Data(Out)=0; + Supp=ones(size(Data)); Supp(Out)=0; + Weight=sum(Supp,2); Weight=repmat(Weight,1,nA); + Data=Data.*Supp./Weight; +end + +% cycle over scans +DataInt=zeros(nE,nS); +for iS=1:nS +% cycle over angles in triads for speed + IntScan=zeros(size(EInt)); + for iA=2:3:nA-1 +% interpolation on the reference grid + if nS>1 + DCorr=interp1(ECorr(:,iA,iS),sum(Data(:,iA-1:iA+1,iS),2),EInt); + else + if nA>1 + DCorr=interp1(ECorr(:,iA),sum(Data(:,iA-1:iA+1),2),EInt); + else DCorr=interp1(ECorr,sum(Data(:,iA-1:iA+1),2),EInt); + end + end +% angle integration + IntScan=IntScan+DCorr; + end +% check +% figure; plot(EInt,DD,EInt,DDS); +% output and normalization + DataInt(:,iS)=IntScan; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/KNavi/CompileMe.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/KNavi/CompileMe.m new file mode 100644 index 0000000..9c6f20c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/KNavi/CompileMe.m @@ -0,0 +1 @@ +mcc -e KNavi.m \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/KNavi/KNavi.fig b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/KNavi/KNavi.fig new file mode 100644 index 0000000..9949e53 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/KNavi/KNavi.fig differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/KNavi/KNavi.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/KNavi/KNavi.m new file mode 100644 index 0000000..63bbd45 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/KNavi/KNavi.m @@ -0,0 +1,211 @@ +function varargout = KNavi(varargin) +% KNAVI MATLAB code for KNavi.fig +% KNAVI, by itself, creates a new KNAVI or raises the existing +% singleton*. +% H = KNAVI returns the handle to a new KNAVI or the handle to +% the existing singleton*. +% KNAVI('CALLBACK',hObject,eventData,handles,...) calls the local +% function named CALLBACK in KNAVI.M with the given input arguments. +% KNAVI('Property','Value',...) creates a new KNAVI or raises the +% existing singleton*. Starting from the left, property value pairs are +% applied to the GUI before KNavi_OpeningFcn gets called. An +% unrecognized property name or invalid value makes property application +% stop. All inputs are passed to KNavi_OpeningFcn via varargin. +% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one +% instance to run (singleton)". +% See also: GUIDE, GUIDATA, GUIHANDLES +% Edit the above text to modify the response to help KNavi +% Last Modified by GUIDE v2.5 11-Aug-2022 19:48:25 +% Begin initialization code - DO NOT EDIT +gui_Singleton = 1; +gui_State = struct('gui_Name', mfilename, ... + 'gui_Singleton', gui_Singleton, ... + 'gui_OpeningFcn', @KNavi_OpeningFcn, ... + 'gui_OutputFcn', @KNavi_OutputFcn, ... + 'gui_LayoutFcn', [] , ... + 'gui_Callback', []); +if nargin && ischar(varargin{1}) + gui_State.gui_Callback = str2func(varargin{1}); +end +if nargout + [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); +else + gui_mainfcn(gui_State, varargin{:}); +end +% End initialization code - DO NOT EDIT + +% --- Executes just before KNavi is made visible. +function KNavi_OpeningFcn(hObject,~,handles,varargin) +% This function has no output args, see OutputFcn. +% hObject handle to figure +% eventdata reserved - to be defined in a future version of MATLAB +% handles structure with handles and user data (see GUIDATA) +% varargin command line arguments to KNavi (see VARARGIN) +% Choose default command line output for KNavi +handles.output = hObject; +% Update handles structure +guidata(hObject, handles); +% parameters +clear global +global ePhi alpha eB +ePhi=4.5; alpha=9; eB=0; % surfNx calculated for arbitrary eB, and all other calculations assume eB=0 +% image the scheme +% - read in image +IS=imread('Scheme.png'); +% - match the axis size to image +Origin=get(handles.axes1,'Position'); Origin=Origin(1:2); +WH=size(IS); WH=WH(1:2); +set(handles.axes1,'Position',[Origin WH]); +% - plot image +image(IS,'Parent',handles.axes1); axis image off + +% UIWAIT makes KNavi wait for user response (see UIRESUME) +% uiwait(handles.figure1); + +% --- Outputs from this function are returned to the command line. +function varargout = KNavi_OutputFcn(~,~,handles) +% Get default command line output from handles structure +varargout{1} = handles.output; + +% ---------------- Nominal X-ray incidence ---------------- +% --- Executes on selection change in popupmenuAlpha. +function popupmenuAlpha_Callback(hObject,~,handles) +% hObject handle to popupmenuAlpha (see GCBO) +global alpha +if get(hObject,'Value')==1; alpha=9; else alpha=20; end +% update all outputs if the parameters available +try pushbuttonOrgCalc_Callback(handles.pushbuttonOrgCalc,[],handles); end +try pushbuttonKxCalc_Callback(handles.pushbuttonKxCalc,[],handles); end +try pushbuttonKyCalc_Callback(handles.pushbuttonKyCalc,[],handles); end +try pushbuttonKzCalc_Callback(handles.pushbuttonKzCalc,[],handles); end + +% ---------------- Origin section ---------------- + +% --- Executes on button press in pushbuttonOrgCalc. +function pushbuttonOrgCalc_Callback(~,~,handles) +global ePhi alpha +% initial parameters +set(handles.textOrgSurfNormX,'String','') +% read in the parameters +hv=str2num(get(handles.editOrgHv,'String')); if hv1))>1; disp('Error in Kyy: Only one of hv/tilt/defection can be vectorized'); return; end +if size(ThtA,1)==1&&size(ThtA,2)~=1; ThtA=repmat(ThtA,nE,1); end % form 2D array of ThtA unless scalar or 3D +if size(Eb,2)==1&&size(Eb,1)~=1; Eb=repmat(Eb,1,nA); end % form 2D array of Eb unless scalar or 3D +thtMPhys=thtM+surfNormX; +nS=max([length(HV) length(TltM) length(TltE)]); % scan is either HV or TltM or TltE + +% conversion of iso-E 2D-arrays to 3D-arrays (immune to scalars) +% if isscalar(Eb); HV=permute(HV,[3,2,1]); TltM=permute(TltM,[3,2,1]); sq=1; else sq=0; end +if isscalar(Eb); ThtA=permute(ThtA,[3,2,1]); sq=1; else sq=0; end + +% % hv-independent data (scalar HV) including single image +% Ky=[]; +% if isscalar(HV) +% % - cycle through tilt (non-scalar TltM) +% for iS=1:nS +% KyF=Ky1(HV,Eb(:,:,min(iS,size(Eb,3))),ThtA,TltM(iS)); +% Ky=cat(3,Ky,KyF); +% end +% % hv-dependent data (non-scalar HV) +% else +% % - cycle through HV +% for iS=1:nS +% KyF=Ky1(HV(iS),Eb(:,:,min(iS,size(Eb,3))),ThtA(:,:,min(iS,size(ThtA,3))),TltM); +% Ky=cat(3,Ky,KyF); +% end +% end + +% Ky conversion +Ky=[]; for iS=1:nS + KyF=Ky1(HV(min(nH,iS)),squeeze(Eb(:,:,min(iS,size(Eb,3)))),squeeze(ThtA(:,:,min(iS,size(ThtA,3)))),TltM(min(nT,iS)),TltE(min(nD,iS))); +% Note: by default all Matlab scalars and arrays have infinite number of singleton dimensions + Ky=cat(3,Ky,KyF); +end +% back conversion of iso-E 3D-arrays to 2D-arrays as required for ImData +if sq==1; Ky=(squeeze(Ky))'; end + +% single 2D-image conversion +function Ky1 = Ky1(hv,Eb,ThtA,tltM,tltE) +% Ky1 = Ky1(hv,Eb,ThtAF,tltM) calculates Ky for single Eb/ThtA image with scalar hv, tltM and tltE +global alpha ePhi thtMPhys nA nE +% forming 2D arrays if vectors +if size(Eb,2)==1&&size(Eb,1)~=1; Eb=repmat(Eb,1,nA); end +if size(ThtA,1)==1&&size(ThtA,2)~=1; ThtA=repmat(ThtA,nE,1); end +% Ky calculation +Ky1=0.5124*sqrt(hv-ePhi+Eb)*sind(tltM+tltE).*cosd(ThtA+thtMPhys)+2*pi*hv*sind(alpha+thtMPhys).*sind(tltM)/12400; \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Kzz.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Kzz.m new file mode 100644 index 0000000..976f0ac --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Kzz.m @@ -0,0 +1,61 @@ +function Kz = Kzz(HV,Eb,thtM,ThtA,TltM,v000,surfNormX,incAlpha) +% Kz = Kzz(HV,Eb,thtM,ThtA,TltM,v000,surfNormX,incAlpha) calculates kz along the surface normal +% Inputs: +% HV (scalar or vector) - photon energies +% Eb (Eb<0; scalar/column vector/2D/3D array) - binding energies +% ThtA (scalar/row vector/2D/3D array) - analyzer scale angles +% TltM (scalar/row vector) - manipulator tilt relative to the surface normal + deflection angle +% ThtA and TltM (scalar/column vector/2D/3D array) - angles along the x- and y-axis +% v000 >0 - inner potential relative to EF +% thtM - the manipulator primary rotation +% surfNormX - surface normal primary angle returned by SurfNormX.m +% incAlpha - nominal X-ray incidence angle. If omitted, 20deg is implied +% Ver. 02.12.2022 + +% parameters +global alpha ePhi thtMPhys v0001 nA nE +if nargin<8; alpha=20; else alpha=incAlpha; end % nominal incidence angle +ePhi=4.5; % workfunction +nH=length(HV); nT=length(TltM); +if length(find([nH nT]>1))>1; disp('Error in Kyy: Only one of hv/tilt/defection can be vectorized'); return; end +thtMPhys=thtM+surfNormX; +v0001=v000; +nA=size(ThtA,2); nE=size(Eb,1); nH=length(HV); nT=length(TltM); +nS=max(nH,size(TltM,3)); % number of scans in HV or in tilt encoded in TltM +if size(ThtA,1)==1&&size(ThtA,2)~=1; ThtA=repmat(ThtA,nE,1); end % form 2D array of ThtA unless scalar or 3D +if size(Eb,2)==1&&size(Eb,1)~=1; Eb=repmat(Eb,1,nA); end % form 2D array of Eb unless scalar or 3D + +% conversion of iso-E/iso-K 2D-arrays from Slice to 3D-arrays (immune to scalars) +if isscalar(Eb); ThtA=permute(ThtA,[3,2,1]); TltM=permute(TltM,[3,2,1]); sq=1; else sq=0; end +if isscalar(ThtA); Eb=permute(Eb,[1,3,2]); TltM=permute(TltM,[1,3,2]); sq=2; end + +% % extension of Eb to 3D (if not extended by AlignEF) +% if nS>1 && size(Eb,3)==1; Eb=repmat(Eb,1,1,nS); end +% % extension of ThtA,TltM to 3D +% if nS>1 && size(ThtA,3)==1; ThtA=repmat(ThtA,1,1,nS); end +% if nS>1 && size(TltM,3)==1; TltM=repmat(TltM,1,1,nS); end + +% Kz conversion +Kz=[]; for iS=1:nS + KzF=Kz1(HV(min(nH,iS)),squeeze(Eb(:,:,min(iS,size(Eb,3)))),squeeze(ThtA(:,:,min(iS,size(ThtA,3)))),TltM(min(nT,iS))); +% Note: by default all Matlab scalars and arrays have infinite number of singleton dimensions + Kz=cat(3,Kz,KzF); +end + +% back conversion of iso-E/iso-K 3D-arrays to 2D-arrays as required for ImData +if sq==1; Kz=(squeeze(Kz))'; end +if sq==2; Kz=squeeze(Kz); end + +% single 2D-image conversion +function Kz1 = Kz1(hv,Eb,ThtA,tltM) +% Kz1 = Kz1(hv,Eb,ThtA,tltM) calculates Kz for single Eb/ThtA image with scalar hv +global alpha ePhi thtMPhys v0001 nA nE +% forming 2D arrays if vectors +if size(Eb,2)==1&&size(Eb,1)~=1; Eb=repmat(Eb,1,nA); end +if size(ThtA,1)==1&&size(ThtA,2)~=1; ThtA=repmat(ThtA,nE,1); end +% final-state Kz +Kx1_2=(hv-ePhi+Eb).*sind(ThtA+thtMPhys).^2; +Ky1_2=(hv-ePhi+Eb).*(sind(tltM).*cosd(ThtA+thtMPhys)).^2; +Kz1=0.5124*sqrt(hv+Eb+v0001-(Kx1_2+Ky1_2)); +% photon momentum corrected initial-state Kz +Kz1=Kz1+2*pi*hv*sind(alpha+thtMPhys)/12400; \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsCompiled/ARPESView.exe b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsCompiled/ARPESView.exe new file mode 100644 index 0000000..e7a1383 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsCompiled/ARPESView.exe differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsCompiled/KNavi.exe b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsCompiled/KNavi.exe new file mode 100644 index 0000000..eccd583 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsCompiled/KNavi.exe differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsCompiled/ResBeamline.exe b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsCompiled/ResBeamline.exe new file mode 100644 index 0000000..e96a2cd Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsCompiled/ResBeamline.exe differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsUserGuide.doc b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsUserGuide.doc new file mode 100644 index 0000000..9885c54 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/MAToolsUserGuide.doc differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ReadARPES.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ReadARPES.m new file mode 100644 index 0000000..22a72b6 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ReadARPES.m @@ -0,0 +1,43 @@ +function [Angle,Energy,Scan,Data,ep,Note,RawTable]=ReadARPES(file) +% [Angle,Energy,Scan,Data,ep,Note]=ReadARPES(file) reads in HDF5 and SP2 files +% to return Angle (row), Energy (column), Scan (empty for 2D arrays and row +% for 3D arrays, Data (2- or 3-dim array), ep (pass energy) and Note (info) +% Ver. 17.08.2022 + +disp(['- Reading in ' file]) + +RawTable = []; +if strcmp(file(end-1:end),'h5') +% read in HDF5 + [Data,Axes,Note]=ReaderHDF5(file); + try; RawTable = load(file, 'SmartTable', '-mat').SmartTable.rawData; end + Angle=Axes{1}; + Energy=(Axes{2})'; + if size(Axes,1)==3; Scan=Axes{3}; else Scan=[]; end + if ndims(Data)==3; Data=double(permute(Data,[2 1 3])); else Data=double(Data'); end +% pos=strfind(Note,'Epass'); ep=str2double(Note(pos+9:pos+12)); +else +% read in SP2 + [data,NoteCell]=ReaderSP2(file); + Data=data.image; Data=double(Data'); + Angle=linspace(data.arange(1),data.arange(2),size(Data,2)); + Energy=(linspace(data.erange(1),data.erange(2),size(Data,1)))'; + Scan=[]; +% ep=str2double(NoteCell{10}(22:27)); +% convert Note from cell to string + Note = ''; for i=1:size(NoteCell) + Note = sprintf('%s\n%s', Note, NoteCell{i}); + end +end +% ep evaluation +pos=strfind(Note,'Ep ='); +% - sp2 or sp2/hdf5 converted file +if ~isempty(pos) + hash=strfind(Note(pos:end),'#'); + ep=str2double(Note(pos+20:pos+hash(1)-2)); +else +% - hdf5 file + pos1=strfind(Note,'Epass ='); + pos2=strfind(Note,'Ek/Eb ='); + ep=str2double(Note(pos1+9:pos2-1)); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Remap.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Remap.m new file mode 100644 index 0000000..1cd6849 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Remap.m @@ -0,0 +1,43 @@ +function [XR,YR,DataR]=Remap(XM,YM,Data) +% [XR,YR,DataR]=Remap(XM,YM,Data) remaps the data array Data defined on the raw +% vector/2D/3D array XM of x-coordinates (usually the corrected angles ACorr) and +% column vector/2D/3D array YM of y-coordinates (usually aligned energies EAlign) +% onto DataR defined on the rectangular grid formed by the equidistant vectors XR and YR +% Ver. 8 Jan 2021 + +disp('- Re-mapping') + +% check if XM and YM are already equidistant vectors +if ndims(XM)==1&&ndims(YM)==1 + if all([diff(diff(XM))==0 diff(diff(XM))]==0) + disp('- No remapping of the output data because the input coordinates are already equidistant vectors'); + XR=XM; YR=YM; DataR=Data; return + end +end + +% parameters +nA=size(XM,2); nA3=size(XM,3); +nE=size(YM,1); nE3=size(YM,3); +nS=size(Data,3); + +% extending 1D arrays to 2D +if size(XM,1)==1; XM=repmat(XM,nE,1); end +if size(YM,2)==1; YM=repmat(YM,1,nA); end +% output grid +XR=linspace(min(min(min(XM))),max(max(max(XM))),nA); +YR=linspace(min(min(min(YM))),max(max(max(YM))),nE); +[XRM,YRM]=meshgrid(XR,YR); +% NaN-wrapping against the edge triangulation errors +XM=[2*XM(1,:,:)-XM(2,:,:); XM; 2*XM(end,:,:)-XM(end-1,:,:)]; XM=[2*XM(:,1,:)-XM(:,2,:) XM 2*XM(:,end,:)-XM(:,end-1,:)]; +YM=[2*YM(1,:,:)-YM(2,:,:); YM; 2*YM(end,:,:)-YM(end-1,:,:)]; YM=[2*YM(:,1,:)-YM(:,2,:) YM 2*YM(:,end,:)-YM(:,end-1,:)]; +Data=[NaN*Data(1,:,:); Data; NaN*Data(end,:,:)]; Data=[NaN*Data(:,1,:) Data NaN*Data(:,end,:)]; + +% re-mapping +DataR=zeros(nE,nA,nS); +for iS=1:nS + iA=min(nA3,iS); X=XM(:,:,iA); X=X(:); + iE=min(nE3,iS); Y=YM(:,:,iE); Y=Y(:); + DL=Data(:,:,iS); DL=DL(:); + % DataR(:,:,iS)=griddata(X,Y,D,AngleM,EnergyM); + F=TriScatteredInterp(X,Y,DL); DataR(:,:,iS)=F(XRM,YRM); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ResBeamline/CompileMe.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ResBeamline/CompileMe.m new file mode 100644 index 0000000..e330b41 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ResBeamline/CompileMe.m @@ -0,0 +1 @@ +mcc -e ResBeamline.m \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ResBeamline/ResBeamline.fig b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ResBeamline/ResBeamline.fig new file mode 100644 index 0000000..d7c47a1 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ResBeamline/ResBeamline.fig differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ResBeamline/ResBeamline.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ResBeamline/ResBeamline.m new file mode 100644 index 0000000..cda11aa --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ResBeamline/ResBeamline.m @@ -0,0 +1,242 @@ +function varargout = ResBeamline(varargin) +%RESBEAMLINE M-file for ResBeamline.fig +% RESBEAMLINE, by itself, creates a new RESBEAMLINE or raises the existing +% singleton*. +% H = RESBEAMLINE returns the handle to a new RESBEAMLINE or the handle to +% the existing singleton*. +% RESBEAMLINE('Property','Value',...) creates a new RESBEAMLINE using the +% given property value pairs. Unrecognized properties are passed via +% varargin to ResBeamline_OpeningFcn. This calling syntax produces a +% warning when there is an existing singleton*. +% RESBEAMLINE('CALLBACK') and RESBEAMLINE('CALLBACK',hObject,...) call the +% local function named CALLBACK in RESBEAMLINE.M with the given input +% arguments. +% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one +% instance to run (singleton)". +% See also: GUIDE, GUIDATA, GUIHANDLES + +% Edit the above text to modify the response to help ResBeamline +% Last Modified by GUIDE v2.5 14-Feb-2023 18:06:32 +% Begin initialization code - DO NOT EDIT +gui_Singleton = 1; +gui_State = struct('gui_Name', mfilename, ... + 'gui_Singleton', gui_Singleton, ... + 'gui_OpeningFcn', @ResBeamline_OpeningFcn, ... + 'gui_OutputFcn', @ResBeamline_OutputFcn, ... + 'gui_LayoutFcn', [], ... + 'gui_Callback', []); +if nargin && ischar(varargin{1}) + gui_State.gui_Callback = str2func(varargin{1}); +end +if nargout + [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); +else + gui_mainfcn(gui_State, varargin{:}); +end +% End initialization code - DO NOT EDIT + +% --- Executes just before ResBeamline is made visible. +function ResBeamline_OpeningFcn(hObject,~, handles, varargin) +% This function has no output args, see OutputFcn. +% hObject handle to figure +% Choose default command line output for ResBeamline +handles.output = hObject; +% beamline parameters +handles.sigmaSizeV_ID=0.014; % rms vertical source size +handles.sigmaDivV_ID=0.014E-3; % rms vertical divergence of the coherent core +handles.fCM=17750; % distance between the source and CM +handles.graLength=90; % grating optical surface length +handles.fFM=9510; % dispersion length +handles.Gratings=get(handles.popupmenuGrating,'String'); % available gratings +handles.Cff=[2.15 3 2.55]; % default Cff values +handles.Orders=get(handles.popupmenuOrder,'String'); % available orders +handles.sigmaSE_PM=1e-6*0.252; % rms slope error PM = 0.052 arcsec +handles.sigmaSE_Gr=1e-6*[0.07*4.848137 0.35 0.079]; % rms slope error of the grating +% handles.Cff=Res(:,1); handles.SigmaV=Res(:,2:end)/4; +% Update handles structure +guidata(hObject, handles); +% UIWAIT makes ResBeamline wait for user response (see UIRESUME) +% uiwait(handles.figure1); + +% --- Outputs from this function are returned to the command line. +function varargout = ResBeamline_OutputFcn(~,~, handles) +% varargout cell array for returning output args (see VARARGOUT); +% hObject handle to figure +% Get default command line output from handles structure +varargout{1} = handles.output; + +% % --- Executes on button press in pushbuttonUpdate. +% function pushbuttonUpdate_Callback(hObject, eventdata, handles) +% % hObject handle to pushbuttonUpdate (see GCBO) +% set([handles.editSlitWidth handles.editResolution],'BackgroundColor','w') +% % retrieve the actual parameters +% [hEnergy,hGratingNo,hOrd,hCff,hSlitWidth]=mcaopen('X03MA-PGM:energy','X03MA-PGM-GRCH:GRATING',... +% 'X03MA-PGM:difforder0','X03MA-PGM:cff','X03MA-OP-SL:TRY_AP'); +% [energy,gratingNo,ord,cff,slitWidth]=mcaget(hEnergy,hGratingNo,hOrd,hCff,hSlitWidth); +% mcaexit() +% % display the actual parameters +% set(handles.editEnergy,'String',num2str(energy)); +% % gratingNo=2-gratingNo; % reverse grating order from EPICS +% set(handles.popupmenuGrating,'Value',gratingNo+1); +% set(handles.popupmenuOrder,'Value',ord+1); +% set(handles.editCff,'String',num2str(cff)); +% set(handles.editSlitWidth,'String',num2str(slitWidth)); slitWidth=slitWidth/1000; +% % try to calculate the resolution parameters +% [resLimit,resCoeff]=resParams(handles); if isempty(resLimit*resCoeff) return; end +% % slit limited resolution +% resSlit=slitWidth*energy^2/(resCoeff*1240*1e-6); +% % total resolution +% resTotal=sqrt(resSlit^2+resLimit^2); +% % display resolution +% set(handles.editResolution,'String',num2str(1000*resTotal)) + +% Cff solver +function alphabeta=cffSolver(cff,N,k,lambda) +% alphabeta=cffSolver(cff,N,k,lambda) finds the incident and exit angles +% [alpha beta](rad) from the cff value, groove density N(l/mm), +% diffraction order k and wavelength lambda(mm) +a=1-(1/cff)^2; b=-2*N*k*lambda; c=(1/cff)^2+(N*k*lambda)^2-1; +if cff==1 + disp('cffSolver => error: invalid cff=1'); beta=NaN; +else + X=[-1*b-sqrt(b^2-4*a*c) -1*b+sqrt(b^2-4*a*c)]/(2*a); + Beta=asin(X); + [~,ind]=min( abs( imag(Beta) ) ); beta=Beta(ind); % selecting the real value +end +% alpha +alpha=asin(N*k*lambda-sin(beta)); +% output +alphabeta=[alpha beta]; + +function editEnergy_Callback(hObject,~, handles) +% hObject handle to editEnergy (see GCBO) +% Hints: get(hObject,'String') returns contents of editEnergy as text +% str2double(get(hObject,'String')) returns contents of editEnergy as a double +set([handles.editSlitWidth handles.editResolution],'String','') +% get energy value +energy=str2num(get(hObject,'String')); +if ~isempty(energy) && (energy<160 || energy>1800); set(hObject,'String',''); return; end +% try to calculate the resolution parameters +resParams(handles); + +% --- Executes on selection change in popupmenuGrating. +function popupmenuGrating_Callback(hObject,~, handles) +% hObject handle to popupmenuGrating (see GCBO) +% Hints: contents = get(hObject,'String') returns popupmenuGrating contents as cell array +% contents{get(hObject,'Value')} returns selected item from popupmenuGrating +set([handles.editSlitWidth handles.editResolution],'String','') +% default Cff +gratingNo=get(hObject,'Value'); cff=handles.Cff(gratingNo); set(handles.editCff,'String',num2str(cff)) +% try to calculate the resolution parameters +resParams(handles); + +% --- Executes on selection change in popupmenuOrder. +function popupmenuOrder_Callback(~,~, handles) +% hObject handle to popupmenuOrder (see GCBO) +% Hints: contents = get(hObject,'String') returns popupmenuOrder contents as cell array +% contents{get(hObject,'Value')} returns selected item from popupmenuOrder +set([handles.editSlitWidth handles.editResolution],'String','') +% try to calculate the resolution parameters +resParams(handles); + +function editCff_Callback(hObject,~, handles) +% hObject handle to editCff (see GCBO) +% Hints: get(hObject,'String') returns contents of editCff as text +% str2double(get(hObject,'String')) returns contents of editCff as a double +set([handles.editSlitWidth handles.editResolution],'String','') +% get Cff value +cff=str2num(get(hObject,'String')); +if isempty(cff) || cff<1 || cff>10; set(hObject,'String',''); return; end +% try to calculate the resolution parameters +resParams(handles); + +function editSlitWidth_Callback(hObject,~,handles) +% hObject handle to editSlitWidth (see GCBO) +% Hints: get(hObject,'String') returns contents of editSlitWidth as text +% str2double(get(hObject,'String')) returns contents of editSlitWidth as a double +set(handles.editResolution,'String','') +slitWidth=str2num(get(hObject,'String'))/1000; +if isempty(slitWidth); set([hObject handles.editResolution],'String',''); return; end +energy=str2num(get(handles.editEnergy,'String')); +% try to calculate the resolution parameters +[resLimit,resCoeff]=resParams(handles); if isempty(resLimit*resCoeff) return; end +% slit limited resolution +resSlit=slitWidth*energy^2/(resCoeff*1240*1e-6); +% total resolution +resTotal=sqrt(resSlit^2+resLimit^2); +% display resolution +set(handles.editResolution,'String',num2str(round(1e6*resTotal)/1000)) + +function editResolution_Callback(hObject,~,handles) +% hObject handle to editResolution (see GCBO) +% Hints: get(hObject,'String') returns contents of editResolution as text +% str2double(get(hObject,'String')) returns contents of editResolution as a double +set(handles.editSlitWidth,'String','') +res=str2num(get(hObject,'String'))/1000; +if isempty(res); set([hObject handles.editSlitWidth],'String',''); return; end +energy=str2num(get(handles.editEnergy,'String')); +% try to calculate the resolution parameters +[resLimit,resCoeff]=resParams(handles); if isempty(resLimit*resCoeff) return; end +% check the resolution limit +if resmax(max(max(ECorr))) || Win(2)min(min(ECorr(end,:,:))) + XSlice=[]; DSlice=[]; disp('Error in Slice: Inconsistent integration window'); return; +end + +% remove NaNs spoiling the cumulative sum +Data(isnan(Data))=0; + +% expanding angle and energy arrays +% - 1D arrays +if size(ACorr,1)==1; ACorr=repmat(ACorr,size(Data,1),1); end +if size(ECorr,2)==1; ECorr=repmat(ECorr,1,size(Data,2)); end +% - 2D arrays +if size(ACorr,3)==1; ACorr=repmat(ACorr,[1 1 size(Data,3)]); end +if size(ECorr,3)==1; ECorr=repmat(ECorr,[1 1 size(Data,3)]); end + +% shifted angle and energy arrays +ACorr1=ACorr(1:end-1,:,:); ECorr1=ECorr(1:end-1,:,:); ECorr2=ECorr(2:end,:,:); + +% parameters +nA=size(Data,2); nS=size(Data,3); de=mean(mean(mean(diff(ECorr,1,1)))); + +% cumulative arrays +if isequal(xMode,'isoe') + if isempty(ISumE); ISumE=cumsum(Data(1:end-1,:,:),1)-0.5*Data(1:end-1,:,:); end + ISum=ISumE; +else + if isempty(ISumK); ISumK=cumsum(Data(1:end-1,:,:),1)-0.5*Data(1:end-1,:,:); end + ISum=ISumK; +end + +% slice values +% point 1 +Lin1=find(ECorr1<=Win(1)&ECorr2>Win(1)); +% - subscript indices of the next point in energy +[I,J,K]=ind2sub(size(ECorr1),Lin1); Lin2=sub2ind(size(ECorr1),I+1,J,K); +% - interpolation of the linear matrices defined by linear indices +I1=ISum(Lin1)+(ISum(Lin2)-ISum(Lin1)).*(Win(1)-ECorr1(Lin1))/de; +% point 2 +Lin1=find(ECorr1<=Win(2)&ECorr2>Win(2)); +[I,J,K]=ind2sub(size(ECorr1),Lin1); Lin2=sub2ind(size(ECorr1),I+1,J,K); +I2=ISum(Lin1)+(ISum(Lin2)-ISum(Lin1)).*(Win(2)-ECorr1(Lin1))/de; +% integral value +% size(ISum) +% size(I2) +% size(I1) +DSlice=I2-I1; +% normalization +DSlice=DSlice*de/diff(Win); +% reshape back to array +DSlice=(reshape(DSlice,nA,nS))'; + +% XSlice values interpolated in the middle of Win +% - this block runs ~25% of the integration block runtime + midE=mean(Win); + Lin1=find(ECorr1<=midE&ECorr2>midE); + [I,J,K]=ind2sub(size(ECorr1),Lin1); Lin2=sub2ind(size(ECorr1),I+1,J,K); + XSlice=ACorr1(Lin1)+(ACorr1(Lin2)-ACorr1(Lin1)).*(midE-ECorr1(Lin1))/de; +% - reshape back to array + XSlice=(reshape(XSlice,nA,nS))'; + +% permutate back if the 'IsoK' mode +if isequal(xMode,'isok') + XSlice=XSlice'; DSlice=DSlice'; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/SubtrBkg.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/SubtrBkg.m new file mode 100644 index 0000000..15cfef2 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/SubtrBkg.m @@ -0,0 +1,42 @@ +function A=SubtrBkg(ACorr,EAlign,Data,EWinNorm,scCoeff,clipNeg) +% A=SubtrBkg(ACorr,EAlign,Data [,EWinNorm] [,scCoeff] [,clipNeg]) subtracts angle-integrated spectral weight from +% the 2D/3D data array Data. Before the subtraction, the data is normalized to the spectral intensity integrated within +% the energy window EWinNorm (default 90% of the EAlign range). scCoeff scales the subtracted angle-integrated +% intensity (default 0.7) and clipNeg indicates whether the negative values are set to zero (default 1) or not (0). +% Ver. 11.07.2022 + +% default arguments + if nargin<6||isempty(clipNeg); clipNeg=1; end + if nargin<5||isempty(scCoeff); scCoeff=0.7; end + if nargin<4||isempty(EWinNorm); EWinNorm=[]; end + + % validity check +if ~isnumeric(scCoeff)||~isequal(size(scCoeff),[1 1]); disp ('Error in SubtrBkg: scCoeff should be scalar'); A=[]; return; end +if ~isequal(clipNeg,0)&&~isequal(clipNeg,1); disp ('Error in SubtrBkg: clipNeg should be 0 or 1'); A=[]; return; end +if ~isempty(EWinNorm)&&~isequal(size(EWinNorm),[1 2])&&~isequal(size(EWinNorm),[2 1]); disp('Error in SubtrBkg: EWinNorm should be a two-element vector'); A=[]; return; end + +% normalization energy window +ERange=[min(min(EAlign(:,1,:))) max(max(EAlign(:,end,:)))]; +if isempty(EWinNorm) + EWinNorm=[0.9*ERange(1)+0.1*ERange(2) 0.1*ERange(1)+0.9*ERange(2)]; +else + if min(EWinNorm)ERange(2) disp('Error in SubtrBkg: Inconsistent normalization energy window'); A=[]; return; end +end +% normalizing data +disp('- Normalizing data') +IDiv=Slice(ACorr,EAlign,Data,'isoE',EWinNorm); +IDiv=Gaco2(IDiv,5,0); % HWHM adjusted to suppress uneven sensitivity of the CCD channels +IDiv=repmat(IDiv,1,1,size(Data,1)); IDiv=permute(IDiv,[3 2 1]); +Data=Data./IDiv; + + % angle-integration window +aMin=max(max(ACorr(:,1,:))); aMax=min(min(ACorr(:,end,:))); +AWin=[0.95*aMin+0.05*aMax 0.05*aMin+0.95*aMax]; +% subtract angle-integrated spectrum and clip negative values +if scCoeff~=0 + disp('- Subtracting angle-integrated background') + ISubtr=Slice(ACorr,EAlign,Data,'isoK',AWin); + ISubtr=repmat(ISubtr,1,1,size(Data,2)); ISubtr=permute(ISubtr,[1 3 2]); + A=Data-scCoeff*ISubtr; + if clipNeg==1; A(A<0)=0; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/SumScanXC.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/SumScanXC.m new file mode 100644 index 0000000..9251439 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/SumScanXC.m @@ -0,0 +1,65 @@ +function [DataXC,OffsE]=SumScanXC(Energy,Data,maxLagE,Win) +% [DataXC,OffsE] = SumScanXC(Energy,Data,maxLagE[,WinE]) summs up the separate scan frames from 3D +% array Data with energy offsets calculated by cross-correlation within the lag interval % +-maxLagE. +% The cross-correlation energy window is Win (default 80% of Energy) and angular window is fixed to +% default 90%. The returned offsets OffsE are discrete on energy grid without interpolation. +% Note: The cross-correlation algorithm subtracts linear background fixed at the end points of the +% energy window. For better accuracy choose the window ends at valleys between the spectral peaks +% and not far above EF. +% Ver. 17.06.2017 +disp('- Correlating scans') +% check input +if size(Data,3)<2; DataXC=Data; OffsE=0; return; end +% parameters +nE=length(Energy); dE=mean(diff(Energy)); nA=size(Data,2); nS=size(Data,3); +maxLag=round(maxLagE/dE); Lag=-1*maxLag:maxLag; +% XC-window +% - default window of 80% in energy and 90% in angle +EWin=(1+round(0.1*nE)):round(0.9*nE); +AWin=(1+round(0.05*nA)):round(0.95*nA); nAWin=length(AWin); +% - energy window +if nargin>3; + Win=sort(Win); + EWin=round([max(1,interp1(Energy,1:nE,Win(1))):min(nE,interp1(Energy,1:nE,Win(2)))]); +end +nEWin=length(EWin); + +% data window +DWin=Data(EWin(1):EWin(end),AWin(1):AWin(end),:); +X=repmat(1:nAWin,nEWin,1); Y=repmat((1:nEWin)',1,nAWin); +% figure; surf(X,Y,DWin(:,:,1),'edgecolor','none'); +% suppress the window edge effects by 1D linear fit of the edge values +% - window edge values averaged over 3 end points +D1=sum(DWin(1:3,:,:),1)/3; D2=sum(DWin(end-2:end,:,:),1)/3; +for iS=1:nS + D1S=D1(1,:,iS); D2S=D2(1,:,iS); + Bkg=repmat(D1S,nEWin,1)+repmat((D2S-D1S)./(Y(end,:)-Y(1,:)),nEWin,1).*Y; +% figure; surf(X,Y,Bkg,'edgecolor','none'); + DWin(:,:,iS)=DWin(:,:,iS)-Bkg; +% figure; surf(X,Y,DWin(:,:,iS),'edgecolor','none'); +end + +% padded reference +Ref=DWin(:,:,1); RPad=[zeros(maxLag,nAWin);Ref;zeros(maxLag,nAWin)]; +% cycle over scans +OffsE=0; DataXC=Data(:,:,1)/nS; +for iS=2:nS +% - cycle over lags + XC=[]; for lag=Lag + DPad=[zeros(maxLag+lag,nAWin);DWin(:,:,iS);zeros(maxLag-lag,nAWin)]; + xc=sum(sum(RPad.*DPad)); +%/(size(Ref,1)-abs(lag)); % Note: Unbiased correlation may fail for flat-topped functions like y=x^2 (see TestXC.m) + XC=[XC xc]; + end +% figure; plot(dE*Lag,XC); +% - offset at maximal correlation + [~,indMax]=max(XC); offs=Lag(indMax); offsE=offs*dE; OffsE=[OffsE; offsE]; + disp(['Scan = ' num2str(iS) ': Offset = ' num2str(offsE)]) +% - appending/truncation of the correlated images +% Note: negative arguments of ones(n,m) return empty array +Data(:,:,iS)=[NaN*ones(offs,nA); ... + Data(max(1,1-offs):min(nE,nE-offs),:,iS); ... + NaN*ones(-1*offs,nA)]; +% - summation normalized by nS + DataXC=DataXC+Data(:,:,iS)/nS; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/CurvatureFlt2.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/CurvatureFlt2.m new file mode 100644 index 0000000..0f08270 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/CurvatureFlt2.m @@ -0,0 +1,62 @@ +% ------------------------------------------------------------------------- +% FUNCTION CALL: Img = CurvatureFlt2(Img [,order] [,CX] [,CY]) +% ------------------------------------------------------------------------- +% DESCRIPTION: +% This function computes the 1D or the 2D curvature as presented in [1] +% of the image. +% ------------------------------------------------------------------------- +% INPUT: +% Img inpute image +% order dim parameter [String]: '1D', '2D' (1D or 2D curvature method) +% CX weighting parameter x direction (in 2D: exact parameter defined in [1]) +% CY weighting parameter y direction (in 2D: exact parameter defined in [1]) +% [1] P. P. Zhang, "A precise method for visualizing dispersive features +% in image plots," Review of Scientific Instruments, vol. 82, +% no. 4, 2011. +% ------------------------------------------------------------------------- +% OUTPUT: +% Img filtered image (image is normalized to value range between (0,1)) +% ------------------------------------------------------------------------- +function [img] = CurvatureFlt2(img,varargin) + if(isempty(varargin)) + img = curvature2D(img, 1,1); + else + switch varargin{1} + case '1D' + img = curvature1D(img,varargin{2},varargin{3}); + case '2D' + img = curvature2D(img,varargin{2},varargin{3}); + end + end +end +function AA = curvature2D(A,CX,CY) +%compute 1st,2nd derivative along x,y + + AX = DifC(A',1)'; + AXX = DifC(A',2)'; + AY = (DifC(A,1)); + AYY = (DifC(A,2)); + AXY = (DifC(AX,1)); + +%compute curvature + + AA = subplus(-(... + ((1+CX*AX.^2).*CY.*AYY) -... + (2*CX*CY*(AX.*AY.*AXY)) +... + ((1+CY*AY.^2)*CX.*AXX)) ./... + (... + (1 + CX*AX.^2 +CY*AY.^2).^(1.5))); + AA = mat2gray(AA); +end + +function AA = curvature1D(A,hw,vw) + AX = DifC(A',1)'; + AXX = DifC(A',2)'; + AY = (DifC(A,1)); + AYY = (DifC(A,2)); + + AA = hw*AXX./(1+AX.^2).^(3/2) + vw*AYY./(1+AY.^2).^(3/2); + AA = subplus(-AA); + + AA = mat2gray(AA); +end diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/GaussFlt2.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/GaussFlt2.m new file mode 100644 index 0000000..c58a872 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/GaussFlt2.m @@ -0,0 +1,40 @@ +% ------------------------------------------------------------------------- +% FUNCTION CALL: GaussFlt2(Img,hwX,hwY,hsX,hsY) +% ------------------------------------------------------------------------- +% DESCRIPTION: +% The image is convolved with a gaussian kernel. The gaussian kernel is a +% kernel with [hsX,hsY] size and incorporates the horicontal, vertical +% half widths. The kernel is normalized. +% ------------------------------------------------------------------------- +% HINT: +% For medianfilter use the MATLAB function medfilt2 (help medfilt2) +% ------------------------------------------------------------------------- +% INPUT: +% Img 2D intensity image +% hwX horizontal half width +% hwY vertical half width +% hsX horizontal kernel length +% hsY vertical kernel length +% ------------------------------------------------------------------------- +% OUTPUT: +% Img image convolved with gaussian kernel +% ------------------------------------------------------------------------- +function Img = GaussFlt2(Img,hwX,hwY,hsX,hsY) + sigx = hwX/(2*sqrt(2*log(2))); + sigy = hwY/(2*sqrt(2*log(2))); + cov = [sigx, 0; 0 sigy]; + kernel = getGauss(hsX,hsY,cov); + Img = imfilter(Img,kernel); +end + +function gauss = getGauss(hsX, hsY, cov) + halfx = (hsX-1)/2; + halfy = (hsY-1)/2; + [x,y] = meshgrid(-halfx:halfx,-halfy:halfy); + A = inv(cov); + a1 = A(1,1)*x + A(1,2)*y; + a2 = A(2,1)*x + A(2,2)*y; + gauss = exp(-0.5*(x.*a1 + y.*a2)); + gauss = gauss./sum(gauss(:)); +end + diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/LaplaceFlt2.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/LaplaceFlt2.m new file mode 100644 index 0000000..b0c84cd --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/LaplaceFlt2.m @@ -0,0 +1,159 @@ +% ------------------------------------------------------------------------- +% FUNCTION CALL: LaplaceFlt2(Img [,y2xRatio] [,order]) +% ------------------------------------------------------------------------- +% DESCRIPTION: +% For laplacian computation a 2nd and 4th order scheme is used, for details +% please see (https://en.wikipedia.org/wiki/Finite_difference_coefficient). +% The 2nd order scheme needs a x_(i-1) and x_(i+1) for computation of the +% 2nd derivative at x_i. While the 4th order scheme needs x_(i-2),..., +% x_(i+2) values for x_i computation. For boundary pixels padding is +% therefore needed. Padding is done by mirroring boundary pixels. +% ------------------------------------------------------------------------- +% EXAMPLE USE: +% img = imread('cameraman.tif'); +% img = Laplacian2(img,1,'4th'); +% imshow(img) +% ------------------------------------------------------------------------- +% INPUT: +% Img --- image (NxM array) +% y2xRatio --- weigthing ratio between y and x laplacian +% order --- laplacian order [String]; '2nd','4th' +% ------------------------------------------------------------------------- +% OUTPUT: +% Img --- output image (NxM array), image is normalized between +% (0,1) +% ------------------------------------------------------------------------- + +function [img] = LaplaceFlt2(img, varargin) + if(isempty(varargin)) + img = laplacian2nd(img,1); + elseif(length(varargin)==2) + y2x = varargin{1}; + + switch varargin{2} + case '2nd' + img = laplacian2nd(img, y2x); + + case '4th' + img = laplacian4th(img, y2x); + end + end + +end + +function [img] = laplacian2nd(img, y2x) + a = 1; + b = -2; + + %resize array + + [nsz, msz] = size(img); + AA = zeros(nsz+2,msz+2); + AA(2:end-1,2:end-1) = img; + AA(1,2:end-1) = (img(1,:)); + AA(end,2:end-1) = (img(end,:)); + AA(:,1) = (AA(:,2)); + AA(:,end) = (AA(:,end-1)); + + img = AA; + + % horizontal + + Am = b*img(2:end-1,2:end-1); + Al = a*img(2:end-1,1:end-2); + Ar = a*img(2:end-1,3:end); + + Ah = subplus(-(Am + Al + Ar)); + % vertical + + Am = b*img(2:end-1,2:end-1); + Al = a*img(1:end-2,2:end-1); + Ar = a*img(3:end,2:end-1); + + Av = subplus(-(Am + Al + Ar)); + +% % diag-1 +% +% Am = b*img(2:end-1,2:end-1); +% Al = a*img(1:end-2,1:end-2); +% Ar = a*img(3:end,3:end); +% +% Ad = dw1*subplus(-(Am + Al + Ar)/2); +% +% +% % diag-2 +% +% Am = b*img(2:end-1,2:end-1); +% Al = a*img(3:end,1:end-2); +% Ar = a*img(1:end-2,3:end); +% +% Add = dw2*subplus(-(Am + Al + Ar)/2); + + Av = y2x*mat2gray(Av); + Ah = mat2gray(Ah); +% Add = mat2gray(Add); +% Ad = mat2gray(Ad); +% img = max(max(Av,Ah),max(Add,Ad)); + img = max(Av,Ah); +end + +function [img] = laplacian4th(A,y2x) + %coeff 4th order + + a = -1/12; + b = 4/3; + c = -5/2; + + %enlarge array + [nsz, msz] = size(A); + AA = zeros(nsz+4,msz+4); + AA(3:end-2,3:end-2) = A; + AA(1:2,3:end-2) = repmat(A(1,:),[2 1]); + AA(end-1:end,3:end-2) = repmat(A(end,:),[2 1]); + AA(:,1:2) = repmat(AA(:,3),[1 2]); + AA(:,end-1:end) = repmat(AA(:,end-2),[1 2]); + + A = AA; + % horizontal + Am = c*A(3:end-2,3:end-2); + All = a*A(3:end-2,1:end-4); + Al = b*A(3:end-2,2:end-3); + Arr = a*A(3:end-2,5:end); + Ar = b*A(3:end-2,4:end-1); + + Axx = subplus(-(All + Al + Am + Ar + Arr)); + + % vertical + Am = c*A(3:end-2,3:end-2); + All = a*A(1:end-4,3:end-2); + Al = b*A(2:end-3,3:end-2); + Arr = a*A(5:end,3:end-2); + Ar = b*A(4:end-1,3:end-2); + + Ayy = subplus(-(All + Al + Am + Ar + Arr)); + +% % diag-1 +% Am = c*A(3:end-2,3:end-2); +% All = a*A(1:end-4,1:end-4); +% Al = b*A(2:end-3,2:end-3); +% Arr = a*A(5:end,5:end); +% Ar = b*A(4:end-1,4:end-1); +% +% Aud = dw1 * subplus(-(All + Al + Am + Ar + Arr)/2); +% +% % diag-2 +% Am = c*A(3:end-2,3:end-2); +% All = a*A(5:end,1:end-4); +% Al = b*A(4:end-1,2:end-3); +% Arr = a*A(1:end-4,5:end); +% Ar = b*A(2:end-3,4:end-1); +% +% Abu = dw2 * subplus(-(All + Al + Am + Ar + Arr)/2); + + Axx = mat2gray(Axx); + Ayy = y2x*mat2gray(Ayy); +% Aud = mat2gray(Aud); +% Abu = mat2gray(Abu); +% img = max(max(Axx,Ayy),max(Aud,Abu)); + img = max(Axx,Ayy); +end diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/SkewCorr.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/SkewCorr.m new file mode 100644 index 0000000..597ad83 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Supplementary/SkewCorr.m @@ -0,0 +1,46 @@ +function DataCorr=SkewCorr(Angle,Energy,Data,AngleC,EnergyC,DataC,eLoc,feat) +% SkewCorr.m removes skewing of Data in energy scale as function of angle, which may result from +% certain irreproducibility of the analyzer slit setting. The algorithm uses 2-order polynomial fit +% of the Fermi edge or spectral peak in the calibration data, averaged within 20 angular bins, and +% AlignEF.m with default energy window and pre-smoothing parameters. +% Inputs: Angle (1D-row), Energy (1D-column) and Data (2D or 3D) are the input data arrays; +% AngleC (1D-row), EnergyC (1D-column) and DataC (2D) are the calibration data arrays; optional eLoc +% (default eLoc=0) specifies approximate energy of the calibration spectral structure, and optional +% feat = 'EF' or 'Peak' (case-insensitive, default 'EF') the type of this structure. +% Outputs: DataCorr as a function of the same Angle and Energy + +% calibration data and parameters +%[AngleC,EnergyC,~,DataC,~,~]=ReadARPES(CalibFile); % the previous version +nA=size(DataC,2); nBin=20; +if nargin<7; eLoc=[]; end; if isempty(eLoc); eLoc=0; end +if nargin<8; feat=[]; end; if isempty(feat); feat='EF'; end; + +% alignment and fit of the calibration data +% - global EF alignment to help reliability of the local alignment +[EnergyC,~,Fail]=AlignEF(DataC,EnergyC,eLoc,[],[],feat); +if ~isempty(Fail); DataCorr=[]; disp('Global EF alignment error'); return; end +% - local EF alignment +width=floor(nA/nBin); +n1=round((nA-nBin*width)/2); +A=[]; EF=[]; +for j=n1:width:n1+width*(nBin-1); + [~,ef,Fail]=AlignEF(DataC(:,j:j+width),EnergyC,0,[],[],feat); + if isempty(Fail); + A=[A (AngleC(floor(j+width/2))+AngleC(ceil(j+width/2)))/2]; EF=[EF ef]; + end +end +% - polynomial fit +P=polyfit(A,EF,2); +% figure; plot(A,EF,'b',AngleC,polyval(P,AngleC),'r') +% - removal of constant offset +P(end)=0; + +% input data alignment +% - interpolation matrices +AngleM=repmat(Angle,size(Data,1),1); +EnergyCorr=repmat(Energy,1,size(Data,2))+repmat(polyval(P,Angle),size(Data,1),1); +% - cycle through scans +DataCorr=Data; for iScan=1:size(Data,3) +% - interpolating the corrected data + DataCorr(:,:,iScan)=interp2(Angle,Energy,Data(:,:,iScan),AngleM,EnergyCorr,'pchip'); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/SurfNormX.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/SurfNormX.m new file mode 100644 index 0000000..7e85cbc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/SurfNormX.m @@ -0,0 +1,21 @@ +function surfNormX = SurfNormX(hv,eB,kx,thtM,thtA,incAlpha) +% surfNormX = SurfNormX(hv,eB,kx,thtM,thtA,incAlpha) calculates the surface normal +% angle in the measurement plane. Inputs: +% hv - photon energy; +% eB and kx - binding energy (eB<0) and known k// of some reference feature; +% thtN and thtA - corresponding angle of the sample rotation and angle on +% the analyser scale. +% incAlpha - nominal X-ray incidence angle, for the present geometry equal to 9deg. If omitted, old geometry with 20deg implied. +% Ver. 08.11.2022 + +% parameters +if nargin<6; alpha=20; else alpha=incAlpha; end % nominal incidence angle +ePhi=4.5; % workfunction +% inputs check +if isempty(hv*eB*kx*thtM*thtA); surfNormX=[]; return; end +% physical reference THT +[thtMPhys,~,exitFlag]=fsolve(@(x) 0.5124*sqrt(hv-ePhi+eB)*sind(thtA+x)-... + 2*pi*hv*cosd(alpha+x)/12400-kx,0,optimset('Display','off','TolFun',1e-10)); +if exitFlag~=1||imag(thtMPhys)~=0; thtMPhys=[]; msgbox('Error: Failed to find the surface normal'); end +% surface normal +surfNormX=thtMPhys-thtM; \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/UnDisperse.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/UnDisperse.m new file mode 100644 index 0000000..8a2094c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/UnDisperse.m @@ -0,0 +1,58 @@ +function [AA,ClipIm]=UnDisperse(A,hwSm,threshD2,threshD1) +% [AA,ClipIm]=UnDisperse(A,hwSm,threshD2,threshD1) clips from the ARPES image A the band-dispersion regions and +% evaluates the spectrum AA which is angle-integrated and normalized by the number of points outside these regions. +% The dispersion regions are identified by the condition -d2I/dE2>threshD2 (between the peak inflexion points) or, +% if the fourth parameter provided, by |d2I/dE2|>threshD2 and |dI/dE|>threshD1 (larger peak base width). Before +% the derivation, the image A is Gaussian pre-smoothed in the energy direction with hwSm, and the resulting +% spectrum AA post-smoothed with hwSm/2. If the -d2I/dE2>threshD2 condition is used, the corresponding peak +% width underestimate can be compensted by an increase of hwSm (which simultaneously reduces noise). +% Example: [AA,ClipIm]=UnDisperse(Z,0.5/dE,0.04); ImData(X,Y,SetContrast(ClipIm,0.001,0.999)); plot(AA) + +% parameters +histMax=0.999; Mask=ones(size(A)); +% pre-smoothing +SmA=Gaco2(A,0,hwSm); + +% peak identification from second derivative only +if nargin<4 +% - derivatives in the Y-direction + DA2=-1*DifC(SmA,2); DA2(DA2<0)=0; DA2(isnan(DA2))=0; +% - normalization to histogrammic maximum + DA2=DA2/max(max(DA2)); limDA2=stretchlim(DA2,[0 histMax]); DA2=DA2/limDA2(2); +% - clipping mask + Mask(DA2>threshD2)=0; + +% peak identification from second and first derivatives +else +% - derivatives in the Y-direction + DA1=abs(DifC(SmA,1)); DA1(isnan(DA1))=0; + DA2=-1*DifC(SmA,2); DA2(DA2<0)=0; DA2(isnan(DA2))=0; % peak width within -d2I/dY2 maximum +% DA2=abs(DifC(SmA,2)); DA2(isnan(DA2))=0; % peak width between -d2I/dY2 minima +% - normalization to histogrammic maximum + DA1=DA1/max(max(DA1)); limDA1=stretchlim(DA1,[0 histMax]); DA1=DA1/limDA1(2); + DA2=DA2/max(max(DA2)); limDA2=stretchlim(DA2,[0 histMax]); DA2=DA2/limDA2(2); +% - clipping mask + Mask(DA2>threshD2|DA1>threshD1)=0; +end + +% angle-integrated unstructure +% - input data with the clipped dispersion regions +ClipIm=A; ClipIm(Mask==0)=NaN; +% - nput data with zeros in the clipped regions +A(Mask==0)=0; +% - angle-integrated data normalized by number of points outside the clipped regions +nA=size(A,2); nE=size(A,1); AA=IntAngle(A,1:nA,(1:nE)',[1+0.05*(nA-1) 1+0.95*(nA-1)]); +% [~,AA]=Cut(1:nA,(1:nE)',A,'edc',[1+0.05*(nA-1) 1+0.95*(nA-1)]); % for some reasons does not work +MSum=IntAngle(Mask,1:nA,(1:nE)',[1+0.05*(nA-1) 1+0.95*(nA-1)]); +AA=AA./MSum; +% post-smoothing +AA=Gaco2(AA,0,hwSm/2); + +% SmoZ=Gaco2(ExpZ,0,0.1/dE); +% figure; ImData(ExpX,ExpY,SmoZ); colormap hot; colorbar +% Di2Z=-DifC(SmoZ,2); +% Diff1=DifC(SmoZ,1); +% Cl2Z=Di2Z; Cl2Z(abs(Di2Z)>max(max(abs(Di2Z)))/40|abs(Diff1)>max(max(abs(Diff1)))/10)=NaN; +% figure; ImData(ExpX,ExpY,Cl2Z); colormap hot; colorbar; +% Cl2Z=Di2Z; Cl2Z(abs(Di2Z)>max(max(abs(Di2Z)))/20|abs(Diff1)>max(max(abs(Diff1)))/10)=NaN; +% figure; ImData(ExpX,ExpY,Cl2Z); colormap hot; colorbar; \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/DifC.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/DifC.m new file mode 100644 index 0000000..956c398 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/DifC.m @@ -0,0 +1,22 @@ +function D=DifC(X,n) +% D = DifC(X,n) calculates the central differencies for the vector X of +% the n=1 or 2 order. The result is end-padded to keep the length of X. +% If A is matrix, the differences are calculated along the columns. + +% consistency check +if n~=1 && n~=2; disp('DifC: Error, only n=1 or 2 are supported'); return; end + +% transpose the row vector input +if size(X,1)==1; X=X'; tra=1; else tra=0; end + +% central differences +if n==1 + D=( X(3:end,:)-X(1:end-2,:) )/2; +else + D=X(3:end,:)+X(1:end-2,:)-2*X(2:end-1,:); +end +% padding +D=[D(1,:); D; D(end,:)]; + +% back transpose when the row vector input +if tra==1; D=D'; end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ExLoc.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ExLoc.m new file mode 100644 index 0000000..0ddc6a3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ExLoc.m @@ -0,0 +1,25 @@ +function [XMIN, XMAX] = ExLoc(X,Y) +% [XMIN, XMAX] = ExLoc(X,Y) finds all local extrema and interpolates their position +% inputs/outputs: +% X,Y - vectors of x- and y-values +% XMIN, XMAX - interpolated x-values of the local minima and maxima + +% size check and reshape to rows +nx=length(X); ny=length(Y); if (nx-ny)~=0 error('Mismatch of input vectors'); end +X=reshape(X,[1 nx]); Y=reshape(Y,[1 ny]); + +% - locating the extrema +L=Y(1:size(Y,2)-2); C=Y(2:size(Y,2)-1); R=Y(3:size(Y,2)); +IMIN=1+find(CL&C>R); + +% - interpolating +XMIN=[]; +for imin=IMIN + [x dummy]=XYMax( [Y(imin-1) Y(imin) Y(imin+1)] ); + XMIN=[XMIN X(imin-1)+x*(X(imin)-X(imin-1))]; +end +XMAX=[]; +for imax=IMAX + [x dummy]=XYMax( [Y(imax-1) Y(imax) Y(imax+1)] ); + XMAX=[XMAX X(imax-1)+x*(X(imax)-X(imax-1))]; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ExtremeXY.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ExtremeXY.m new file mode 100644 index 0000000..778ad2c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ExtremeXY.m @@ -0,0 +1,38 @@ +function [XMin,YMin,XMax,YMax] = ExtremeXY(X,Y) +% [XMin,YMin,XMax,YMax] = ExtremeXY(X,Y) finds and interpolates all local extremes +% Inputs/outputs: +% X,Y - vectors (rows or columns) of x- and y-values +% XMin,YMin,XMax,YMax - interpolated x- and y-values of the local minima and maxima +% Note: X shall not necessarily be equidistant, but plaid and not repeating values + +% locating indices of the extremes +L=Y(1:end-2); C=Y(2:end-1); R=Y(3:end); +IMin=1+find(CL&C>R); + +% offsets to pre-condition the polynom fit +xOffset=mean(X); yOffset=mean(Y); +X=X-xOffset; Y=Y-yOffset; + +% interpolating minima and offset backcorrection +XMin=[]; YMin=[]; +if ~isempty(IMin) + for iMin=IMin + X(iMin-1:iMin+1); Y(iMin-1:iMin+1); + Fit=polyfit(X(iMin-1:iMin+1),Y(iMin-1:iMin+1),2); + xMin=-0.5*Fit(2)/Fit(1); XMin=[XMin xMin]; + yMin=polyval(Fit,xMin); YMin=[YMin yMin]; + end; + XMin=XMin+xOffset; YMin=YMin+yOffset; +end + +% interpolating maxima and offset backcorrection +XMax=[]; YMax=[]; +if ~isempty(IMax) + for iMax=IMax + Fit=polyfit(X(iMax-1:iMax+1),Y(iMax-1:iMax+1),2); + xMax=-0.5*Fit(2)/Fit(1); XMax=[XMax xMax]; + yMax=polyval(Fit,xMax); YMax=[YMax yMax]; + end; + XMax=XMax+xOffset; YMax=YMax+yOffset; +end + \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/Flat.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/Flat.m new file mode 100644 index 0000000..412cca5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/Flat.m @@ -0,0 +1,14 @@ +function [AFlat,Coeffs]=Flat(Angle,Scan,Slice) +% AFlat=Flat(Angle,Scan,Slice) returns a bilinear fit of Slice + +% flatten the arrays +SliceF=Slice(:); +[AngleM,ScanM]=meshgrid(Angle,Scan); AngleF=AngleM(:); ScanF=ScanM(:); +OnesF=ones(size(SliceF)); +% fitting +Coeffs=[AngleF ScanF OnesF]\SliceF; +% fitting plane +AFlat=Coeffs(1)*AngleM+Coeffs(2)*ScanM+Coeffs(3); +% figure; imagesc(Angle,Scan,Slice); set(gca,'TickDir','Out'); axis equal tight; +% figure; imagesc(Angle,Scan,FitM); set(gca,'TickDir','Out'); axis equal tight; + diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/Gaco1.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/Gaco1.m new file mode 100644 index 0000000..34b6084 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/Gaco1.m @@ -0,0 +1,27 @@ +function AA=Gaco1(A,hw,hs) +% AA=Gaco1(A,hw [,hs]) convolutes vector or matrix A with Gaussian of +% half-width hw and half-support hs(in inter-point distances). If skipped, +% the default hs=3*hw. The ends are padded symmetrically. If A is matrix, +% the convolution proceeds along the columns. + +% transpose the row vector input +if size(A,1)==1; A=A'; tra=1; else tra=0; end + +% default support +if nargin<3; hs=3*hw; end; hs=ceil(hs); + +% convolution kernel +% - formation +K=(-1*hs:1:hs)'; K=exp(-1*(sqrt(log(2))*K/(hw+eps)).^2); +% - normalization +K=K/sum(K); + +% padding A +% ALow=flipud(A(2:hs+1,:)); AHi=flipud(A(end-hs:end-1,:)); A=[ALow;A;AHi]; +A=padarray(A,[hs 0],'replicate','both'); + +% convolution +AA=conv2(K,1,A,'valid'); + +% back transpose when the row vector input +if tra==1; AA=AA'; end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/IniConfig.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/IniConfig.m new file mode 100644 index 0000000..10cf868 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/IniConfig.m @@ -0,0 +1,1244 @@ +classdef IniConfig < handle + %IniConfig - The class for working with configurations of settings and INI-files. + % This class allows you to create configurations of settings, and to manage them. + % The structure of the storage settings is similar to the structure of + % the storage the settings in the INI-file format. + % The class allows you to import settings from the INI-file and to export + % the settings in INI-file. + % Can be used for reading/writing data in the INI-file and managing + % settings of application. + % + % + % Config Syntax: + % + % ; some comments + % + % [Section1] ; allowed the comment to section + % ; comment on the section + % key1 = value_1 ; allowed a comment to an individual parameter + % key2 = value_2 + % + % [Section2] + % key1 = value_1.1, value_1.2 ; array data + % key2 = value_2 + % ... + % + % Note: + % * There may be spaces in the names of sections and keys + % * Keys should not be repeated in the section (will read the last) + % * Sections should not be repeated in the config (will read the last) + % --------------------------------------------------------------------- + % + % Support data types: + % * numeric scalars and vectors + % * logical scalars and vectors + % * strings + % + % --------------------------------------------------------------------- + % + % Using: + % ini = IniConfig(); % Constructor (an instance of class) + % + % Public Properties: + % Enter this command to get the properties: + % >> properties IniConfig + % + % Public Methods: + % Enter this command to get the methods: + % >> methods IniConfig + % + % Enter this command to get more info of method: + % >> help IniConfig/methodname + % + % --------------------------------------------------------------------- + % + % Example: + % ini = IniConfig(); + % ini.ReadFile('example.ini') + % sections = ini.GetSections() + % [keys, count_keys] = ini.GetKeys(sections{1}) + % values = ini.GetValues(sections{1}, keys, cell(count_keys, 1)) + % new_values = cell(count_keys, 1); + % new_values(:) = {rand()}; + % ini.SetValues(sections{1}, keys, new_values) + % ini.WriteFile('example1.ini') + % + % + % Example: + % ini = IniConfig(); + % ini.AddSection('Some Section 1') + % ini.AddKey('Some Section 1', 'some_key1', 'hello!') + % ini.AddKey('Some Section 1', 'some_key2', [10, 20]) + % ini.AddKey('Some Section 1', 'some_key3', true) + % ini.AddSection('Some Section 2') + % ini.AddKey('Some Section 2', 'some_key1') + % ini.WriteFile('example2.ini') + % + % + % Example: + % ini = IniConfig(); + % ini.AddSection('Some Section 1') + % ini.AddKey('Some Section 1', 'some_key1', 'hello!') + % ini.AddKey('Some Section 1', 'some_key2', [10, 20]) + % ini.AddKey('Some Section 1', 'some_key3', [false, true]) + % ini.WriteFile('example31.ini') + % ini.RemoveKey('Some Section 1', 'some_key1') + % ini.RenameKey('Some Section 1', 'some_key2', 'renamed_some_key2') + % ini.RenameSection('Some Section 1', 'Renamed Section 1') + % ini.WriteFile('example32.ini') + % + % + % --------------------------------------------------------------------- + % Note: + % This implementation does not use cycles, and works fairly quickly, + % even on large files. + % Parsing the files by using regular expressions + % All comments are saved when set values + % + % This class was tested on the win32 platform only but it should + % also work on Unix/Linux platforms. + % + % + % --------------------------------------------------------------------- + % Author: Iroln + % Version: 0.6.2 + % First release: 25.07.09 + % Last revision: 11.08.09 + % Copyright: (c) 2009 Evgeny Pr aka Iroln. All rights reserved. + % + % Bug reports, questions, etc. can be sent to the e-mail given above. + % --------------------------------------------------------------------- + + + properties (GetAccess = 'public', SetAccess = 'private') + comment_style = ';' + count_sections = 0 + full_count_keys = 0 + end + + properties (GetAccess = 'private', SetAccess = 'private') + file_name = '' + config_data_array = {} + indexes_of_sections = [] + indexes_of_empty_str = [] + + count_strings = 0 + count_empty_strings = 0 + + is_created_configuration = false + end + + + methods + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Public Methods + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %------------------------------------------------------------------ + function obj = IniConfig() + %IniConfig - Constructor + % To Create empty default configuration. + % Using: + % ini_obj = IniConfig() + % + + obj.CreateIni(); + end + + %------------------------------------------------------------------ + function status = ReadStream(obj, data_stream, comment_style) + obj.comment_style = ValidateCommentStyle(comment_style); + file_data = data_stream; + obj.count_strings = size(file_data, 1); + + % Parse data + obj.config_data_array = IniFileParser(file_data, obj.comment_style); + obj.UpdateSectionsInfo() + obj.UpdateEmptyStringsInfo() + obj.UpdateCountKeysInfo() + + obj.is_created_configuration = true; + end + + %------------------------------------------------------------------ + function status = ReadFile(obj, filename, comment_style) + %ReadFile - to read in the object the config data from a INI file + % Using: + % status = ReadFile(filename, comment_style) + % status - 1 (true): Success + % status - 0 (false): Failed + % + + if (nargin < 2) + error('Not enough input arguments.') + elseif (nargin == 3) + obj.comment_style = ValidateCommentStyle(comment_style); + end + + if ~ischar(filename) + error('Requires string input.') + else + % Get data from file + fid = fopen(filename, 'r'); + + if (fid ~= -1) + file_data = textscan(fid, ... + '%s', ... + 'delimiter', '\n', ... + 'endOfLine', '\r\n'); + + fclose(fid); + status = true; + else + status = false; + return; + end + + obj.file_name = filename; + file_data = file_data{1}; + obj.count_strings = size(file_data, 1); + + % Parse data + obj.config_data_array = IniFileParser(file_data, obj.comment_style); + + obj.UpdateSectionsInfo() + obj.UpdateEmptyStringsInfo() + obj.UpdateCountKeysInfo() + + obj.is_created_configuration = true; + end + end + + %------------------------------------------------------------------ + function status = IsSection(obj, section_name) + %IsSection - determine whether there is a section + % Using: + % status = IsSection(section_name) + % status - 1 (true): section is found + % status - 0 (false): section is not found + % + + if (obj.is_created_configuration) + if (nargin < 2) + error('Not enough input arguments.') + end + + section_name = obj.ValidateSectionName(section_name); + sect_num = obj.NameToNumSection(section_name); + + if ~isempty(sect_num) + status = ~obj.IsUniqueSectionName(section_name); + else + status = false; + end + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function status = IsKey(obj, section_name, key_name) + %IsSection - determine whether there is a key in a given section + % Using: + % status = IsKey(section_name, key_name) + % status - 1 (true): key is found + % status - 0 (false): key is not found + % + + if (obj.is_created_configuration) + if (nargin < 3) + error('Not enough input arguments.') + end + + section_name = obj.ValidateSectionName(section_name); + key_name = obj.ValidateKeyName(key_name); + sect_num = obj.NameToNumSection(section_name); + + if (~isempty(sect_num) && ~isempty(key_name)) + status = ~obj.IsUniqueKeyName(section_name, key_name); + else + status = false; + end + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function [names_sect, count_sect] = GetSections(obj) + %GetSections - get names of all sections + % Using: + % [names_sect, count_sect] = GetSections() + % + % Output: + % names_sect - cell array with the names of sections + % count_sect - number of sections in configuration + % + + if (obj.is_created_configuration) + names_sect = obj.config_data_array(obj.indexes_of_sections, 1); + count_sect = obj.count_sections; + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function [keys_names, count_keys] = GetKeys(obj, section_name) + %GetKeys - get names of all keys from given section + % Using: + % [keys_names, count_keys] = GetKeys(section_name) + % + % Output: + % keys_names - cell array with the names of keys + % count_keys - number of keys in given section + % + + if (obj.is_created_configuration) + if (nargin < 2) + error('Not enough input arguments.') + end + + section_name = obj.ValidateSectionName(section_name); + + [keys_indexes, count_keys] = obj.GetKeysIndexes(section_name); + + if isempty(keys_indexes) + keys_names = {}; + count_keys = 0; + return; + end + + keys_names = obj.config_data_array(keys_indexes, 1); + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function [values, count_read] = GetValues(obj, section_name, keys_names, default_values, param_name, param_val) + %GetValues - get values of keys from given section + % Using: + % [values, count_read] = GetValues(section_name, ... + % keys_names, ... + % default_values, ... + % param_name, ... + % param_val) + % Output: + % values - cell array with the values + % count_read - number of successfully get values + % + % Input: + % section_name - name of given section + % keys_names - names of given keys + % default_values - default values + % + % Optional Input Parameters: + % param_name - must be 'AlwaysReturnCell' + % param_val - must be 0 or 1 + % + + if (obj.is_created_configuration) + if (nargin < 4) + error('Not enough input arguments.') + elseif (nargin == 4) + is_get_values_always_in_cell = true; + + elseif (nargin == 5) + error('Not enough input arguments.') + + elseif (nargin == 6) + if ischar(param_name) + if strcmpi('AlwaysReturnCell', param_name) + if (param_val == 0 || param_val == 1) + is_get_values_always_in_cell = logical(param_val); + else + error('Value must be 0 or 1.') + end + else + error('Invalid param name: "%s". Must be "AlwaysReturnCell"', param_name) + end + else + error('The method GetValue expects a string "AlwaysReturnCell".') + end + end + + section_name = obj.ValidateSectionName(section_name); + + [keys_names, default_values] = ... + ValidateInputsForGetAndSetValues(section_name, ... + keys_names, default_values); + + count_keys = numel(keys_names); + values = cell(count_keys, 1); + count_read = 0; + + keys_indexes = obj.GetKeysIndexes(section_name); + + if isempty(keys_indexes) + values = default_values; + + if (length(values) == 1 && ~is_get_values_always_in_cell) + values = values{1}; + end + + return; + end + + keys_names = strtrim(keys_names); + keys = obj.config_data_array(keys_indexes, 1); + vals = obj.config_data_array(keys_indexes, 2); + + % Get the names of keys, which are not in the INI file + % in a given section and specifying this key Defaults + [not_found_keys, not_found_indexes] = setdiff(keys_names, keys); + values(not_found_indexes) = default_values(not_found_indexes); + + % Getting the names of keys, which is in the INI file in a + % given section + [found_keys, found_indexes, found_data_indexes] = intersect(keys_names, keys); + values(found_indexes) = vals(found_data_indexes); + count_read = length(found_indexes); + + %DEBUG: found_indexes = sort(found_indexes); + values(found_indexes) = ParserValues(values(found_indexes)); + + if (length(values) == 1 && ~is_get_values_always_in_cell) + values = values{1}; + end + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function count_write = SetValues(obj, section_name, keys_names, values) + %SetValues - set values for given keys from given section + % Using: + % count_write = SetValues(section_name, keys_names, values) + % + % Output: + % count_write - number of successfully set values + % + % Input: + % section_name - name of given section (must be string) + % keys_names - names of given keys (must be cell array of strings or string) + % values - values of keys (must be cell array or one value) + % + % Note: + % Number of elements in the second and third input argument must be equal + % + + if (obj.is_created_configuration) + if (nargin < 4) + error('Not enough input arguments.') + end + + section_name = obj.ValidateSectionName(section_name); + + [keys_names, values] = ... + ValidateInputsForGetAndSetValues(section_name, ... + keys_names, values); + + count_keys = numel(keys_names); + count_write = 0; + keys_indexes = obj.GetKeysIndexes(section_name); + + if isempty(keys_indexes) + return; + end + + [valid_keys, count_valid_keys] = obj.GetKeys(section_name); + + if (count_keys > count_valid_keys) + values = values(1:count_valid_keys); + end + + keys_names = strtrim(keys_names); + keys = obj.config_data_array(keys_indexes, 1); + + % If the key is not unique within the section, it will be + % processed by the key, which is located the last + [keys_names, m] = unique(keys_names); + values = values(m); + + [not_found_keys, not_found_indexes] = setdiff(keys_names, keys); + keys_names(not_found_indexes) = []; + values(not_found_indexes) = []; + + [found_keys, found_indexes, found_data_indexes] = intersect(keys_names, keys); + values(sort(found_indexes)) = values(found_indexes); + + % Get string value indices + str_indexes = cellfun(@(x) ischar(x), values); + + % Get numeric value indices + num_indexes = cellfun(@(x) isnumeric(x), values); + + % Get logical value indices + log_indexes = cellfun(@(x) islogical(x), values); + + values(num_indexes | log_indexes) = cellfun(@(x) mat2str(x), ... + values(num_indexes | log_indexes), 'UniformOutput', 0); + + values(~str_indexes & ~num_indexes & ~log_indexes) = []; + values(str_indexes) = strtrim(values(str_indexes)); + + values(num_indexes | log_indexes) = ... + CorrectNumArrayStrings(values(num_indexes | log_indexes)); + + if isempty(values) + values = {''}; + end + + obj.config_data_array(keys_indexes(found_data_indexes), 2) = values; + count_write = length(values); + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function CreateIni(obj) + %CreateIni - create new empty INI configuration + % Using: + % CreateIni() + % + + obj.config_data_array = cell(2,3); + obj.config_data_array(:,:) = {''}; + + obj.UpdateCountStrings(); + obj.UpdateSectionsInfo() + obj.UpdateEmptyStringsInfo() + + obj.file_name = ''; + obj.is_created_configuration = true; + end + + %------------------------------------------------------------------ + function status = AddSection(obj, section_name) + %AddSection - add section to end configuration + % Using: + % status = AddSection(section_name) + % status - 1 (true): Success + % status - 0 (false): Failed + % + + if (obj.is_created_configuration) + if (nargin < 2) + error('Not enough input arguments.') + end + + section_name = obj.ValidateSectionName(section_name); + status = obj.InsertSection(obj.count_sections+1, section_name); + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function status = InsertSection(obj, pos, section_name) + %InsertSection - insert section to given position + % Using: + % status = InsertSection(pos, section_name) + % status - 1 (true): Success + % status - 0 (false): Failed + % + + if (obj.is_created_configuration) + if (nargin < 3) + error('Not enough input arguments.') + else + if (~isnumeric(pos) && ~isscalar(pos)) + error('Position must be a scalar positive integer') + end + + if (pos < 1) + error('Position must be a positive integer') + elseif (pos > obj.count_sections+1) + pos = obj.count_sections+1; + end + end + + section_name = obj.ValidateSectionName(section_name); + + if ~isempty(section_name) + is_unique_sect = obj.IsUniqueSectionName(section_name); + if ~is_unique_sect + status = false; + return; + end + + if (pos <= obj.count_sections && obj.count_sections > 0) + sect_ind = obj.indexes_of_sections(pos); + + elseif (pos == 1 && obj.count_sections == 0) + sect_ind = 1; + obj.config_data_array = {}; + + elseif (pos == obj.count_sections+1) + %FIXME: + sect_ind = obj.count_strings+1; + end + + new_data = cell(2,3); + new_data(1,:) = {section_name, '', ''}; + new_data(2,:) = {''}; + + obj.config_data_array = insertcell(obj.config_data_array, ... + sect_ind, new_data); + + obj.UpdateCountStrings(); + obj.UpdateSectionsInfo(); + obj.UpdateEmptyStringsInfo(); + + status = true; + else + status = false; + end + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function status = RemoveSection(obj, section_name) + %RemoveSection - remove given section + % Using: + % status = RemoveSection(section_name) + % status - 1 (true): Success + % status - 0 (false): Failed + % + + if (obj.is_created_configuration) + if (nargin < 2) + error('Not enough input arguments.') + end + + section_name = obj.ValidateSectionName(section_name); + sect_num = obj.NameToNumSection(section_name); + + if ~isempty(sect_num) + + if (sect_num < obj.count_sections) + first_ind = obj.indexes_of_sections(sect_num); + last_ind = obj.indexes_of_sections(sect_num+1)-1; + + elseif (sect_num == obj.count_sections) + first_ind = obj.indexes_of_sections(sect_num); + last_ind = obj.count_strings; + end + + obj.config_data_array(first_ind:last_ind,:) = []; + + obj.UpdateCountStrings(); + obj.UpdateSectionsInfo(); + obj.UpdateEmptyStringsInfo(); + obj.UpdateCountKeysInfo(); + + status = true; + else + status = false; + end + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function status = RenameSection(obj, section_name, new_section_name) + %RenameSection - rename given section + % Using: + % status = RenameSection(section_name, new_section_name) + % status - 1 (true): Success + % status - 0 (false): Failed + % + + if (obj.is_created_configuration) + if (nargin < 3) + error('Not enough input arguments.') + end + + section_name = obj.ValidateSectionName(section_name); + new_section_name = obj.ValidateSectionName(new_section_name); + sect_num = obj.NameToNumSection(section_name); + + if (~isempty(new_section_name) && ~isempty(sect_num)) + sect_ind = obj.indexes_of_sections(sect_num); + + obj.config_data_array(sect_ind, 1) = {new_section_name}; + status = true; + else + status = false; + end + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function [status, write_value] = AddKey(obj, section_name, key_name, value) + %AddKey - add key in a end given section + % Using: + % [status, write_value] = AddKey(section_name, key_name, value) + % + % Output: + % status - 1 (true): Success, status - 0 (false): Failed + % write_value - 1 (true): Success, status - 0 (false): Failed + % + + if (obj.is_created_configuration) + if (nargin < 3) + error('Not enough input arguments.') + elseif (nargin == 3) + value = ''; + end + + section_name = obj.ValidateSectionName(section_name); + [keys_indexes, count_keys] = obj.GetKeysIndexes(section_name); + + [status, write_value] = obj.InsertKey(section_name, count_keys+1, key_name, value); + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function [status, write_value] = InsertKey(obj, section_name, key_pos, key_name, value) + %InsertKey - insert key into the specified position in a given section + % Using: + % [status, write_value] = InsertKey(section_name, key_pos, key_name, value) + % + % Output: + % status - 1 (true): Success, status - 0 (false): Failed + % write_value - 1 (true): Success, status - 0 (false): Failed + % + + if (obj.is_created_configuration) + if (nargin < 4) + error('Not enough input arguments.') + elseif (nargin == 4) + value = ''; + elseif (nargin == 5) + if isempty(value) + value = ''; + end + end + + if (~isnumeric(key_pos) && ~isscalar(key_pos)) + error('Index must be a scalar positive integer') + else + if (key_pos < 1) + error('Index must be a positive integer') + end + end + + write_value = 0; + section_name = obj.ValidateSectionName(section_name); + key_name = obj.ValidateKeyName(key_name); + sect_num = obj.NameToNumSection(section_name); + + if (~isempty(sect_num) && ~isempty(key_name)) + is_unique_key = obj.IsUniqueKeyName(section_name, key_name); + if ~is_unique_key + status = false; + return; + end + + [keys_indexes, count_keys] = obj.GetKeysIndexes(section_name); + if (count_keys > 0) + if (key_pos <= count_keys) + insert_index = keys_indexes(key_pos); + elseif (key_pos > count_keys) + insert_index = keys_indexes(end)+1; + end + else + insert_index = obj.indexes_of_sections(sect_num) + 1; + end + + new_data = {key_name, '', ''}; + + obj.config_data_array = insertcell(obj.config_data_array, ... + insert_index, new_data); + + obj.UpdateCountStrings(); + obj.UpdateSectionsInfo(); + obj.UpdateEmptyStringsInfo(); + obj.UpdateCountKeysInfo(); + + if ~isempty(value) + write_value = obj.SetValues(section_name, key_name, value); + end + + status = true; + else + status = false; + end + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function status = RenameKey(obj, section_name, key_name, new_key_name) + %RenameKey - rename the key in a given section + % Using: + % status = RenameKey(section_name, key_name, new_key_name) + % status - 1 (true): Success + % status - 0 (false): Failed + % + + if (obj.is_created_configuration) + if (nargin < 4) + error('Not enough input arguments.') + end + + section_name = obj.ValidateSectionName(section_name); + key_name = obj.ValidateKeyName(key_name); + new_key_name = obj.ValidateKeyName(new_key_name); + sect_num = obj.NameToNumSection(section_name); + [keys, count_keys] = obj.GetKeys(section_name); + + if (~isempty(sect_num) && ~isempty(key_name) && ~isempty(new_key_name) && count_keys > 0) + is_unique_key = obj.IsUniqueKeyName(section_name, key_name); + if is_unique_key + status = false; + return; + end + + tf = find(strcmp(key_name, keys), 1, 'last'); + keys_indexes = obj.GetKeysIndexes(section_name); + + key_index = keys_indexes(tf); + obj.config_data_array{key_index, 1} = new_key_name; + + status = true; + else + status = false; + end + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function status = RemoveKey(obj, section_name, key_name) + %RemoveKey - remove the key from a given section + % Using: + % status = RemoveKey(section_name, key_name) + % status - 1 (true): Success + % status - 0 (false): Failed + % + + if (obj.is_created_configuration) + if (nargin < 3) + error('Not enough input arguments.') + end + + section_name = obj.ValidateSectionName(section_name); + key_name = obj.ValidateKeyName(key_name); + sect_num = obj.NameToNumSection(section_name); + [keys, count_keys] = obj.GetKeys(section_name); + + if (~isempty(sect_num) && ~isempty(key_name) && count_keys > 0) + is_unique_key = obj.IsUniqueKeyName(section_name, key_name); + if is_unique_key + status = false; + return; + end + + tf = find(strcmp(key_name, keys), 1, 'last'); + keys_indexes = obj.GetKeysIndexes(section_name); + + key_index = keys_indexes(tf); + obj.config_data_array(key_index, :) = []; + + obj.UpdateCountStrings(); + obj.UpdateSectionsInfo(); + obj.UpdateEmptyStringsInfo(); + obj.UpdateCountKeysInfo(); + + status = true; + else + status = false; + end + else + error('Configuration is not created or not loaded.') + end + end + + %------------------------------------------------------------------ + function status = WriteFile(obj, filename) + %WriteFile - write to the configuration INI file on disk + % Using: + % status = WriteFile(filename) + % status - 1 (true): Success + % status - 0 (false): Failed + % + + if (obj.is_created_configuration) + if (nargin < 1) + error('Not enough input arguments.') + else + if ~ischar(filename) + error('Requires string input.') + else + fid = fopen(filename, 'w'); + + if (fid ~= -1) + count_str = obj.count_strings; + indexes_of_sect = obj.indexes_of_sections; + config_data = obj.config_data_array; + + for k = 1:count_str + if isempty(config_data{k,1}) + if isempty(config_data{k,3}) + fprintf(fid, '\n'); + else + comment_str = config_data{k,3}; + fprintf(fid, '%s\n', comment_str); + end + + elseif ~isempty(indexes_of_sect(indexes_of_sect == k)) + if isempty(config_data{k,3}) + section_str = config_data{k,1}; + + fprintf(fid, '%s\n', section_str); + else + section_str = config_data{k,1}; + comment_str = config_data{k,3}; + + fprintf(fid, '%s %s\n', ... + section_str, comment_str); + end + + elseif ~isempty(config_data{k,1}) && ... + isempty(indexes_of_sect(indexes_of_sect == k)) + if isempty(config_data{k,3}) + key_str = config_data{k,1}; + val_str = config_data{k,2}; + + fprintf(fid, '%s = %s\n', ... + key_str, val_str); + + else + key_str = config_data{k,1}; + val_str = config_data{k,2}; + comment_str = config_data{k,3}; + + fprintf(fid, '%s = %s %s\n', ... + key_str, val_str, comment_str); + end + end + end + + fclose(fid); + status = true; + else + status = false; + return; + end + end + end + else + error('Configuration is not created or not loaded.') + end + end + + end % public methods + + + methods (Access = 'private') + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Private Methods + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %------------------------------------------------------------------ + function num = NameToNumSection(obj, name) + %NameToNumSection - get number of section + + sections = obj.GetSections(); + indexes = find(strcmp(name, sections)); + + if ~isempty(indexes) + % If the section is not unique, then choose the latest + num = indexes(end); + else + num = []; + end + end + + %------------------------------------------------------------------ + function [keys_indexes, count_keys] = GetKeysIndexes(obj, section_name) + %GetKeysIndexes - get keys indices from given section + + sect_num = obj.NameToNumSection(section_name); + + if isempty(sect_num) + keys_indexes = []; + count_keys = 0; + return; + + elseif (sect_num == obj.count_sections) + keys_indexes = ... + obj.indexes_of_sections(sect_num)+1:obj.count_strings; + else + keys_indexes = ... + obj.indexes_of_sections(sect_num)+1:obj.indexes_of_sections(sect_num+1)-1; + end + + indexes_of_empty = obj.indexes_of_empty_str; + [i_str, empty_indexes] = intersect(keys_indexes, indexes_of_empty); + + keys_indexes(empty_indexes) = []; + keys_indexes = keys_indexes(:); + count_keys = length(keys_indexes); + end + + %------------------------------------------------------------------ + function UpdateSectionsInfo(obj) + %UpdateSectionsInfo + + keys_data = obj.config_data_array(:,1); + sect_indexes_cell = regexp(keys_data, '^\[.*\]$'); + obj.indexes_of_sections = find(cellfun(@(x) ~isempty(x), sect_indexes_cell)); + obj.count_sections = length(obj.indexes_of_sections); + end + + %------------------------------------------------------------------ + function UpdateCountKeysInfo(obj) + %UpdateCountKeys + + obj.full_count_keys = obj.count_strings - obj.count_sections - obj.count_empty_strings; + end + + %------------------------------------------------------------------ + function UpdateEmptyStringsInfo(obj) + %UpdateEmptyStringsInfo + + keys_data = obj.config_data_array(:,1); + indexes_of_empty_cell = strcmp('', keys_data); + obj.indexes_of_empty_str = find(indexes_of_empty_cell); + obj.count_empty_strings = length(obj.indexes_of_empty_str); + end + + %------------------------------------------------------------------ + function UpdateCountStrings(obj) + %UpdateCountStrings + + obj.count_strings = size(obj.config_data_array, 1); + end + + %------------------------------------------------------------------ + function status = IsUniqueKeyName(obj, section_name, key_name) + %IsUniqueKeyName - check whether the name of the key unique + + keys = obj.GetKeys(section_name); + status = ~any(strcmp(key_name, keys)); + end + + %------------------------------------------------------------------ + function status = IsUniqueSectionName(obj, section_name) + %IsUniqueKeyName - check whether the name of the section a unique + + sections = obj.GetSections(); + status = ~any(strcmp(section_name, sections)); + end + + %------------------------------------------------------------------ + function section_name = ValidateSectionName(obj, section_name) + %ValidateSectionName - check the name of the section + + if (~ischar(section_name) || size(section_name, 1) > 1) + error('Requires string input for name of section.') + else + section_name = strtrim(section_name); + + if isempty(section_name) + section_name = []; + else + sect_indexes_cell = regexp(section_name, '^\[.*\]$', 'once'); + indexes_cell_comment = regexp(section_name, obj.comment_style, 'once'); + + if ~isempty(indexes_cell_comment) + section_name = []; + return; + end + + if isempty(sect_indexes_cell) + section_name = ['[', section_name, ']']; + end + end + end + end + + %------------------------------------------------------------------ + function key_name = ValidateKeyName(obj, key_name) + %ValidateKeyName - check the name of the key + + if (~ischar(key_name) || size(key_name, 1) > 1) + error('Requires string input for key name.') + else + key_name = strtrim(key_name); + indexes_cell = regexp(key_name, '^\[.*\]$', 'once'); + indexes_cell_comment = regexp(key_name, obj.comment_style, 'once'); + + if isempty(key_name) || ~isempty(indexes_cell) || ~isempty(indexes_cell_comment) + key_name = []; + end + end + end + + end % private methods + +end % classdef IniConfig +%-------------------------------------------------------------------------- + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Tools Functions +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +%========================================================================== +function config_data = IniFileParser(file_data, comment_style) + %IniFileParser - parser data from the INI file + + % Select the comment in a separate array + pat = sprintf('^[^%s]+', comment_style); + comment_data = regexprep(file_data, pat, ''); + + % Deleting comments + pat = sprintf('%s.*+$', comment_style); + file_data = regexprep(file_data, pat, ''); + + % Select the key value in a separate array + values_data = regexprep(file_data, '^.[^=]*.', ''); + + % Select the names of the sections and keys in a separate array + keys_data = regexprep(file_data, '=.*$', ''); + + config_data = cell(size(file_data, 1), 3); + config_data(:,1) = keys_data; + config_data(:,2) = values_data; + config_data(:,3) = comment_data; + + config_data = strtrim(config_data); +end +%-------------------------------------------------------------------------- + +%========================================================================== +function values = ParserValues(values) + %ParserValues - classify the data types and convert them + + start_idx = regexp(values, '^[\-\d\s\,\.\:truefalse]+$'); + number_indexes = cellfun(@(x) ~isempty(x), start_idx); + + num_values_strs = values(number_indexes); + num_values = cellfun(@(x) str2num(x), num_values_strs, 'UniformOutput', 0); + + empty_num_indexes = cellfun(@(x) isempty(x), num_values); + num_values(empty_num_indexes) = num_values_strs(empty_num_indexes); + values(number_indexes) = num_values; + + empty_indexes = cellfun(@(x) isempty(x), values); + values(empty_indexes) = {[]}; +end +%-------------------------------------------------------------------------- + +%========================================================================== +function values = CorrectNumArrayStrings(values) + %CorrectNumStrings + + values = regexprep(values, '^\[', ''); + values = regexprep(values, '\]$', ''); + values = regexprep(values, '\s', ', '); +end +%-------------------------------------------------------------------------- + +%========================================================================== +function comment_style = ValidateCommentStyle(comment_style) + %ValidateCommentStyle + + if ~ischar(comment_style) + error('Requires char input for comment style.') + else + if (length(comment_style) ~= 1) + error('The style comments should contain the single character') + end + end +end +%-------------------------------------------------------------------------- + +%========================================================================== +function [keys, values] = ValidateInputsForGetAndSetValues(section, keys, values) + %ValidateInputsForGetAndSetValues + + if ~ischar(section) + error('First input argument must be a string.') + end + + if ~ischar(keys) && ~iscellstr(keys) + error('Second input argument must be a string or cell array of strings_indexes.') + else + if ischar(keys) + keys = {keys}; + end + end + + if ~iscell(values) + values = {values}; + end + + if (numel(keys) ~= numel(values)) + error('Number of elements in the second and third input argument must be equal') + end + + keys = keys(:); + values = values(:); +end +%-------------------------------------------------------------------------- + +%========================================================================== +function B = insertcell(C, index, data) + %insertcell - insert a new cell or several cells in a two-dimensional + % array of cells on the index + + M = index; + N = 1; + + if ~iscell(data) + data = {data}; + end + + [m, n] = size(C); + [md, nd] = size(data); + + mm = m + md; + nt = nd + N - n - 1; + + if (nt > 0) + nn = n + nt; + else + nn = n; + end + + B = cell(mm, nn); + B(M:M+md-1, N:N+nd-1) = data; + + ia = 1:M-1; + ib = M+md:mm; + j = 1:n; + + ibb = [ia, ib]; + if (m > 2) + t = 0; + else + t = 1; + end + icc = [ia, M:length(C)-t]; + B(ibb, j) = C(icc, j); +end +%-------------------------------------------------------------------------- + diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/LinFit.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/LinFit.m new file mode 100644 index 0000000..dafa761 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/LinFit.m @@ -0,0 +1,16 @@ +function Fit=LinFit(X,Y,Z,FString) +% linear fit of Z(X,Y) with the functions of X and Y specified in FString +% (space separated). The constant term is represented by leading 1. +% Example: Fit=LinFit(X,Y,Z,'1 X.^2 X.*Y Y.^2') + +% replacing the constant term +if isequal(FString(1),'1'); FString=['ones(size(X))' FString(2:end)]; end + +% flattening +X=X(:); Y=Y(:); Z=Z(:); +if length(Y)~=length(X) || length(Z)~=length(X) + Fit=[]; disp('LinFit error: Incompatible input arrays'); return +end + +% - fitting +eval(['Fit=[' FString ']\Z;']); Fit=Fit'; \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/LinVal.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/LinVal.m new file mode 100644 index 0000000..0d2ac00 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/LinVal.m @@ -0,0 +1,25 @@ +function Z=LinVal(FString,Coeffs,X,Y) +% Z=LinVal(FString,Coeffs,X,Y) returns values of the linear combination of +% the functions of X and Y defined in FString (space separated) with +% the coefficients defined in Coeffs. +% Example: Z=LinVal('1 X.^2 X.Y Y.^2',Coeffs,X,Y) + +% squeeze multiple spaces from FString +while ~isempty(strfind(FString,' ')) + FString=strrep(FString,' ',' '); +end + +% consistency check +if length(strfind(FString,' '))~=length(Coeffs)-1 + Z=[]; disp('LinVal error: FString misfits with Coeffs'); return +end + +% formation of the linear combination string +FString=['Coeffs(1)*' FString]; % leading term +for iCoeff=2:length(Coeffs) + iSep=strfind(FString,' '); iSep=iSep(1); + FString=[FString(1:iSep-1) '+Coeffs(' num2str(iCoeff) ')*' FString(iSep+1:end)]; +end + +% values +eval(['Z=' FString ';']); \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/MaxLoc2.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/MaxLoc2.m new file mode 100644 index 0000000..41608bc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/MaxLoc2.m @@ -0,0 +1,26 @@ +function [xMax,yMax,zMax]=MaxLoc2(X,Y,Z) +% [xMax,yMax,zMax]=MaxLoc2(X,Y,Z) finds the global maximum of Z(X,Y) and +% quadratically interpolates its coordinates and value + +% locate the global maximum +ZMax=max(max(Z)); [iMax,jMax]=find(Z==ZMax); +X=X(jMax-1:jMax+1); Y=Y(iMax-1:iMax+1); Z=Z(iMax-1:iMax+1,jMax-1:jMax+1); +% test +% figure; ImData(X,Y,Z); + +% quadratic fit of the global maximum +% - flatten the arrays +[XM,YM]=meshgrid(X,Y); XF=XM(:); YF=YM(:); +ZF=Z(:); +OnesF=ones(size(ZF)); +% - fit coeffs +A=[XF.^2 YF.^2 XF.*YF XF YF OnesF]\ZF; +% - fit surface +ZFit=A(1)*XM.^2+A(2)*YM.^2+A(3)*XM.*YM+A(4)*XM+A(5)*YM+A(6); +% - output test +% figure; ImData(X,Y,ZFit); + +% - coordinates and value of the global maximum +xMax=(2*A(2).*A(4)-A(3).*A(5))/(A(3).^2-4*A(1).*A(2)); +yMax=(-2*A(1)*xMax-A(4))/A(3); +zMax=A(1)*xMax.^2+A(2)*yMax.^2+A(3)*xMax.*yMax+A(4)*xMax+A(5)*yMax+A(6); \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/PolyAlignEF.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/PolyAlignEF.m new file mode 100644 index 0000000..08337a5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/PolyAlignEF.m @@ -0,0 +1,35 @@ +function DataCorr=PolyAlignEF(Angle,Energy,Data,CalibFile) +% PolyCorrEF.m aligns Data in energy scale relative to EF varying as function of angle. The +% algorithm uses 3-order polynomial fit of the Fermi edge, averaged within 20 angular bins. +% Inputs: Angle (1D-row), Energy (1D-column) and Data (2D or 3D) are the input array; CalibFile +% is the EF calibration file. Outputs: DataCorr as a function of the same Angle and Energy + +% calibration data and parameters +[AngleC,EnergyC,~,DataC,~,~]=ReadARPES(CalibFile); +nA=size(DataC,2); nBin=20; +% - global EF alignment to help reliability of the local alignment +[EnergyC,~,Fail]=AlignEF(DataC,EnergyC,0); +if ~isempty(Fail); DataCorr=[]; disp('Global EF alignment error'); return; end +% - local EF alignment +width=floor(nA/nBin); +n1=round((nA-nBin*width)/2); +A=[]; EF=[]; +for j=n1:width:n1+width*(nBin-1); + [~,ef,Fail]=AlignEF(DataC(:,j:j+width),EnergyC,0); + if isempty(Fail); + A=[A (AngleC(floor(j+width/2))+AngleC(ceil(j+width/2)))/2]; EF=[EF ef]; + end +end +% - polynomial fit +P=polyfit(A,EF,3); +% figure; plot(A,EF,'b',AngleC,polyval(P,AngleC),'r') + +% input data alignment +% - interpolation matrices +AngleM=repmat(Angle,size(Data,1),1); +EnergyCorr=repmat(Energy,1,size(Data,2))+repmat(polyval(P,Angle),size(Data,1),1); +% - cycle through scans +DataCorr=Data; for iScan=1:size(Data,3) +% - interpolating the corrected data + DataCorr(:,:,iScan)=interp2(Angle,Energy,Data(:,:,iScan),AngleM,EnergyCorr,'pchip'); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReadSumXC.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReadSumXC.m new file mode 100644 index 0000000..b1cd3f2 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReadSumXC.m @@ -0,0 +1,16 @@ +function [Angle,Energy,Scan,DataXC,ep,Note]=ReadSumXC(Files) +% ReadSumXC reads and adds separate sp2- or hdf5-files with x-correlation. +% The files are assumed to have the same size and energy scale. +% The input parameter Files is a cell array like {'A','B','C'}. + +% load files +DataXC=[]; +for iFile=1:size(Files,2) + try [Angle,Energy,Scan,Data,ep,Note]=ReadARPES(Files{iFile}); + catch msgbox(['Input Error in ' Files{iFile}],'modal'); return; end + DataXC=cat(3,DataXC,Data); +end + +% reduction +disp('- X-correlating data') +maxLagE=0.25; [Energy,DataXC]=SumScanXC(Energy,DataXC,maxLagE); diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReaderHDF5.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReaderHDF5.m new file mode 100644 index 0000000..cd96998 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReaderHDF5.m @@ -0,0 +1,19 @@ +function [data, axes, note] = ReaderHDF5(fname) + % Read HDF5 file saved by SmartGUI + % data is the possible multidimensional matrix. + % axes is a cell object. Each row holds the scale array for + % corresponding dimension. + axes = {}; + % data dimensions are reversed + data = h5read(fname, '/Matrix'); + data = permute(data, ndims(data):-1:1); + % notes + note = h5readatt(fname, '/Matrix', 'IGORWaveNote'); + % scale information for each dimension + scale = h5readatt(fname, '/Matrix', 'IGORWaveScaling'); + [~, ncols] = size(scale); + for n=2:ncols + axis = scale(2,n)+[0:size(data,n-1)-1]*scale(1, n); + axes = vertcat(axes, axis); + end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReaderSP2.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReaderSP2.m new file mode 100644 index 0000000..4e448db --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReaderSP2.m @@ -0,0 +1,45 @@ +function [data,comments,transform] = ReaderSP2(filename) + data = struct('image',[], ... + 'raw', [], ... % raw image without correction + 'erange',[], ... % in the format of [EkinStart, EkinEnd] + 'arange',[], ... % in the format of [aStart, aEnd] + 'edelta',[], ... % in the format of [EkinStart, EkinDelta] + 'adelta',[] ... % in the format of [aStart, aDelta] + ); + d = readsp2(filename); + if (isempty(d.image)) + return + end + data.image = d.image; + data.raw = d.raw; + comments = d.comment; + + % Parse ERange and aRange + ini = IniConfig(); + ini.ReadStream(comments,'#'); + + value = ini.GetValues('Transform','ERange',''); + erange = value{1}; + delta = (erange(2)-erange(1))/(size(data.image,2)-1); + data.erange = erange; + data.edelta = [erange(1) delta]; + + value = ini.GetValues('Transform','aRange',''); + arange = value{1}; + delta = (arange(2)-arange(1))/(size(data.image,1)-1); + data.arange = arange; + data.adelta = [arange(1) delta]; + + % Parse Transform section + transform = []; + keys = {'lensmode', 'Ek', 'Ep', 'WF', 'ERange', 'aRange', 'De1', 'aInner', ... + 'eShift', 'Da1', 'Da3', 'Da5', 'Da7', 'pixel_size', 'magnification', ... + 'offset', 'interpolation_mode', 'intensity_scaling', 'aUnit', ... + 'eGrid', 'aGrid', 'source'}; + for key=keys + keyname = key{1}; + value = ini.GetValues('Transform', keyname, ''); + value = value{1}; + transform.(keyname) = value; + end +end diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReaderSP2_Matlab.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReaderSP2_Matlab.m new file mode 100644 index 0000000..d81a7e4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/ReaderSP2_Matlab.m @@ -0,0 +1,65 @@ +function [data,comments] = ReaderSP2(filename) + % Read SP2 files. + % It read the image as well as the scale information. + + data = struct('image',[], ... + 'erange',[], ... % in the format of [EkinStart, EkinEnd] + 'arange',[], ... % in the format of [aStart, aEnd] + 'edelta',[], ... % in the format of [EkinStart, EkinDelta] + 'adelta',[] ... % in the format of [aStart, aDelta] + ); + + + % Read image data + % This is much slower than read with textscan +% try +% data.image = imread(filename); +% lastwarn(''); +% catch ME +% disp(ME.message) +% return +% end + + % Valid SP2 file? + file = fopen(filename); + line = fgetl(file); + if ~strcmp(line, 'P2') + fclose(file); + return + end + + % Read comments + comments = {}; + line = fgetl(file); + while ischar(line) + if line(1)~='#', break; end + comments = vertcat(comments,regexprep(line, '^#(.*)', '$1')); + line = fgetl(file); + end + + % Read dimension information + dims = sscanf(line, '%d %d %d'); + % Read data + raw = textscan(file, '%d'); + data.image = double(reshape(raw{1}, dims(1), dims(2))'); + % Close file + fclose(file); + + % Parse ERange and aRange + ini = IniConfig(); + ini.ReadStream(comments,'#'); + + value = ini.GetValues('Transform','ERange',''); + range = value{1}; + delta = (range(2)-range(1))/(size(data.image,2)-1); + data.erange = range; + data.edelta = [range(1) delta]; + + value = ini.GetValues('Transform','aRange',''); + range = value{1}; + delta = (range(2)-range(1))/(size(data.image,1)-1); + data.arange = range; + data.adelta = [range(1) delta]; + +end + diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/VGaco.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/VGaco.m new file mode 100644 index 0000000..98a5a06 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/VGaco.m @@ -0,0 +1,48 @@ +function AA=VGaco(A,HW,hs,PadMethod) +% AA=VGaco(A,HW [,hs] [,PadMethod]) convolutes A (vector) with Gaussian +% having varying half-width HW (vector or scalar, in inter-point distances) +% and fixed half-support hs (scalar, in inter-point distances). If skipped +% or empty, the default hs=3*hw. Reduction of the end effects is controlled +% by PadMethod (optional): default symmetric padding if skipped or 'symm', +% or padding by hs-wide arrays linearly extrapolated from the HW-wide end +% intervals if 'extrap' + +% default support +if nargin<3; hs=[]; end +if isempty(hs); hs=3*HW; end + +% check the PadMethod arguments +if nargin==4 && ~strcmp(PadMethod,'extrap') && ~strcmp(PadMethod,'symm') + error('''symm'' (default) and ''extrap'' padding methods are supported'); +end + +% parameters +na=length(A); AA=A; A=reshape(A,[1 na]); +HW=HW/sqrt(log(2))+eps; if length(HW)==1; HW=HW*ones(1,na); end +hs=ceil(hs); + +% convolution with padding by linear extrapolation +if nargin==4 && strcmp(PadMethod,'extrap') +% - linear fit within HW + rangeL=1:1+ceil(HW(1)); PL=polyfit(rangeL,A(rangeL),1); AL=polyval(PL,1-hs:0); + rangeR=na-ceil(HW(end)):na; PR=polyfit(rangeR,A(rangeR:na),1); AR=polyval(PR,na+1:na+hs); +% - appending + if size(A,1)size(PTS,2); pts=PTS; else pts=PTS'; end + +c=pts(1); +ab=[-1 0.5; 2 -0.5]*(pts(2:3)-c*ones(2,1)); +x=-ab(2)/(2*ab(1)); +y=ab(1)*x^2+ab(2)*x+c; + + diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/dispname.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/dispname.m new file mode 100644 index 0000000..62e3c07 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/dispname.m @@ -0,0 +1,8 @@ +function dispname(varargin) +% dispname(x [,...]) displays variables in coma-separated argument list with names +for i=1:nargin + disp([inputname(i) '= ' num2str(varargin{i})]) +end +% function dispname(name) +% % dispname(X) -- Display scalar variable(s) in argument list with name(s) +% disp([inputname(1) '= ' num2str(name)]) \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/readsp2.mexw64 b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/readsp2.mexw64 new file mode 100644 index 0000000..140477a Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/readsp2.mexw64 differ diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/smoothn.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/smoothn.m new file mode 100644 index 0000000..140fc47 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/Utils/smoothn.m @@ -0,0 +1,482 @@ +function [z,s,exitflag,Wtot] = smoothn(varargin) + +%SMOOTHN Robust spline smoothing for 1-D to N-D data. +% SMOOTHN provides a fast, automatized and robust discretized smoothing +% spline for data of any dimension. +% +% Z = SMOOTHN(Y) automatically smoothes the uniformly-sampled array Y. Y +% can be any N-D noisy array (time series, images, 3D data,...). Non +% finite data (NaN or Inf) are treated as missing values. +% +% Z = SMOOTHN(Y,S) smoothes the array Y using the smoothing parameter S. +% S must be a real positive scalar. The larger S is, the smoother the +% output will be. If the smoothing parameter S is omitted (see previous +% option) or empty (i.e. S = []), it is automatically determined using +% the generalized cross-validation (GCV) method. +% +% Z = SMOOTHN(Y,W) or Z = SMOOTHN(Y,W,S) specifies a weighting array W of +% real positive values, that must have the same size as Y. Note that a +% nil weight corresponds to a missing value. +% +% Robust smoothing +% ---------------- +% Z = SMOOTHN(...,'robust') carries out a robust smoothing that minimizes +% the influence of outlying data. +% +% [Z,S] = SMOOTHN(...) also returns the calculated value for S so that +% you can fine-tune the smoothing subsequently if needed. +% +% An iteration process is used in the presence of weighted and/or missing +% values. Z = SMOOTHN(...,OPTION_NAME,OPTION_VALUE) smoothes with the +% termination parameters specified by OPTION_NAME and OPTION_VALUE. They +% can contain the following criteria: +% ----------------- +% TolZ: Termination tolerance on Z (default = 1e-3) +% TolZ must be in ]0,1[ +% MaxIter: Maximum number of iterations allowed (default = 100) +% Initial: Initial value for the iterative process (default = +% original data) +% ----------------- +% Syntax: [Z,...] = SMOOTHN(...,'MaxIter',500,'TolZ',1e-4,'Initial',Z0); +% +% [Z,S,EXITFLAG] = SMOOTHN(...) returns a boolean value EXITFLAG that +% describes the exit condition of SMOOTHN: +% 1 SMOOTHN converged. +% 0 Maximum number of iterations was reached. +% +% Class Support +% ------------- +% Input array can be numeric or logical. The returned array is of class +% double. +% +% Notes +% ----- +% The N-D (inverse) discrete cosine transform functions DCTN and IDCTN are required. +% +% To be made +% ---------- +% Estimate the confidence bands (see Wahba 1983, Nychka 1988). +% +% Reference +% --------- +% Garcia D, Robust smoothing of gridded data in one and higher dimensions +% with missing values. Computational Statistics & Data Analysis, 2010. +% PDF download +% +% Examples: +% -------- +% % 1-D example +% x = linspace(0,100,2^8); +% y = cos(x/10)+(x/50).^2 + randn(size(x))/10; +% y([70 75 80]) = [5.5 5 6]; +% z = smoothn(y); % Regular smoothing +% zr = smoothn(y,'robust'); % Robust smoothing +% subplot(121), plot(x,y,'r.',x,z,'k','LineWidth',2) +% axis square, title('Regular smoothing') +% subplot(122), plot(x,y,'r.',x,zr,'k','LineWidth',2) +% axis square, title('Robust smoothing') +% +% % 2-D example +% xp = 0:.02:1; +% [x,y] = meshgrid(xp); +% f = exp(x+y) + sin((x-2*y)*3); +% fn = f + randn(size(f))*0.5; +% fs = smoothn(fn); +% subplot(121), surf(xp,xp,fn), zlim([0 8]), axis square +% subplot(122), surf(xp,xp,fs), zlim([0 8]), axis square +% +% % 2-D example with missing data +% n = 256; +% y0 = peaks(n); +% y = y0 + rand(size(y0))*2; +% I = randperm(n^2); +% y(I(1:n^2*0.5)) = NaN; % lose 1/2 of data +% y(40:90,140:190) = NaN; % create a hole +% z = smoothn(y); % smooth data +% subplot(2,2,1:2), imagesc(y), axis equal off +% title('Noisy corrupt data') +% subplot(223), imagesc(z), axis equal off +% title('Recovered data ...') +% subplot(224), imagesc(y0), axis equal off +% title('... compared with original data') +% +% % 3-D example +% [x,y,z] = meshgrid(-2:.2:2); +% xslice = [-0.8,1]; yslice = 2; zslice = [-2,0]; +% vn = x.*exp(-x.^2-y.^2-z.^2) + randn(size(x))*0.06; +% subplot(121), slice(x,y,z,vn,xslice,yslice,zslice,'cubic') +% title('Noisy data') +% v = smoothn(vn); +% subplot(122), slice(x,y,z,v,xslice,yslice,zslice,'cubic') +% title('Smoothed data') +% +% % Cardioid +% t = linspace(0,2*pi,1000); +% x = 2*cos(t).*(1-cos(t)) + randn(size(t))*0.1; +% y = 2*sin(t).*(1-cos(t)) + randn(size(t))*0.1; +% z = smoothn(complex(x,y)); +% plot(x,y,'r.',real(z),imag(z),'k','linewidth',2) +% axis equal tight +% +% % Cellular vortical flow +% [x,y] = meshgrid(linspace(0,1,24)); +% Vx = cos(2*pi*x+pi/2).*cos(2*pi*y); +% Vy = sin(2*pi*x+pi/2).*sin(2*pi*y); +% Vx = Vx + sqrt(0.05)*randn(24,24); % adding Gaussian noise +% Vy = Vy + sqrt(0.05)*randn(24,24); % adding Gaussian noise +% I = randperm(numel(Vx)); +% Vx(I(1:30)) = (rand(30,1)-0.5)*5; % adding outliers +% Vy(I(1:30)) = (rand(30,1)-0.5)*5; % adding outliers +% Vx(I(31:60)) = NaN; % missing values +% Vy(I(31:60)) = NaN; % missing values +% Vs = smoothn(complex(Vx,Vy),'robust'); % automatic smoothing +% subplot(121), quiver(x,y,Vx,Vy,2.5), axis square +% title('Noisy velocity field') +% subplot(122), quiver(x,y,real(Vs),imag(Vs)), axis square +% title('Smoothed velocity field') +% +% See also SMOOTH, SMOOTH3, DCTN, IDCTN. +% +% -- Damien Garcia -- 2009/03, revised 2010/11 +% Visit my website for more details about SMOOTHN + +% Check input arguments +error(nargchk(1,12,nargin)); + +%% Test & prepare the variables +%--- +k = 0; +while k=0') +end +%--- +% "Maximal number of iterations" criterion +I = find(strcmpi(varargin,'MaxIter'),1); +if isempty(I) + MaxIter = 100; % default value for MaxIter +else + try + MaxIter = varargin{I+1}; + catch ME + error('MATLAB:smoothn:IncorrectMaxIter',... + 'MaxIter must be an integer >=1') + end + if ~isnumeric(MaxIter) || ~isscalar(MaxIter) ||... + MaxIter<1 || MaxIter~=round(MaxIter) + error('MATLAB:smoothn:IncorrectMaxIter',... + 'MaxIter must be an integer >=1') + end +end +%--- +% "Tolerance on smoothed output" criterion +I = find(strcmpi(varargin,'TolZ'),1); +if isempty(I) + TolZ = 1e-3; % default value for TolZ +else + try + TolZ = varargin{I+1}; + catch ME + error('MATLAB:smoothn:IncorrectTolZ',... + 'TolZ must be in ]0,1[') + end + if ~isnumeric(TolZ) || ~isscalar(TolZ) || TolZ<=0 || TolZ>=1 + error('MATLAB:smoothn:IncorrectTolZ',... + 'TolZ must be in ]0,1[') + end +end +%--- +% "Initial Guess" criterion +I = find(strcmpi(varargin,'Initial'),1); +if isempty(I) + isinitial = false; % default value for TolZ +else + isinitial = true; + try + z0 = varargin{I+1}; + catch ME + error('MATLAB:smoothn:IncorrectInitialGuess',... + 'Z0 must be a valid initial guess for Z') + end + if ~isnumeric(z0) || ~isequal(size(z0),sizy) + error('MATLAB:smoothn:IncorrectTolZ',... + 'Z0 must be a valid initial guess for Z') + end +end +%--- +% "Weighting function" criterion +I = find(strcmpi(varargin,'Weights'),1); +if isempty(I) + weightstr = 'bisquare'; % default weighting function +else + try + weightstr = lower(varargin{I+1}); + catch ME + error('MATLAB:smoothn:IncorrectWeights',... + 'A valid weighting function must be chosen') + end + if ~ischar(weightstr) + error('MATLAB:smoothn:IncorrectWeights',... + 'A valid weighting function must be chosen') + end +end +%--- +% Weights. Zero weights are assigned to not finite values (Inf or NaN), +% (Inf/NaN values = missing data). +IsFinite = isfinite(y); +nof = nnz(IsFinite); % number of finite elements +W = W.*IsFinite; +if any(W<0) + error('MATLAB:smoothn:NegativeWeights',... + 'Weights must all be >=0') +else + W = W/max(W(:)); +end +%--- +% Weighted or missing data? +isweighted = any(W(:)<1); +%--- +% Robust smoothing? +isrobust = any(strcmpi(varargin,'robust')); +%--- +% Automatic smoothing? +isauto = isempty(s); +%--- +% DCTN and IDCTN are required +test4DCTNandIDCTN + +%% Creation of the Lambda tensor +%--- +% Lambda contains the eingenvalues of the difference matrix used in this +% penalized least squares process. +d = ndims(y); +Lambda = zeros(sizy); +for i = 1:d + siz0 = ones(1,d); + siz0(i) = sizy(i); + Lambda = bsxfun(@plus,Lambda,... + cos(pi*(reshape(1:sizy(i),siz0)-1)/sizy(i))); +end +Lambda = -2*(d-Lambda); +if ~isauto, Gamma = 1./(1+s*Lambda.^2); end + +%% Upper and lower bound for the smoothness parameter +% The average leverage (h) is by definition in [0 1]. Weak smoothing occurs +% if h is close to 1, while over-smoothing appears when h is near 0. Upper +% and lower bounds for h are given to avoid under- or over-smoothing. See +% equation relating h to the smoothness parameter (Equation #12 in the +% referenced CSDA paper). +N = sum(sizy~=1); % tensor rank of the y-array +hMin = 1e-6; hMax = 0.99; +sMinBnd = (((1+sqrt(1+8*hMax.^(2/N)))/4./hMax.^(2/N)).^2-1)/16; +sMaxBnd = (((1+sqrt(1+8*hMin.^(2/N)))/4./hMin.^(2/N)).^2-1)/16; + +%% Initialize before iterating +%--- +Wtot = W; +%--- Initial conditions for z +if isweighted + %--- With weighted/missing data + % An initial guess is provided to ensure faster convergence. For that + % purpose, a nearest neighbor interpolation followed by a coarse + % smoothing are performed. + %--- + if isinitial % an initial guess (z0) has been provided + z = z0; + else + z = InitialGuess(y,IsFinite); + end +else + z = zeros(sizy); +end +%--- +z0 = z; +y(~IsFinite) = 0; % arbitrary values for missing y-data +%--- +tol = 1; +RobustIterativeProcess = true; +RobustStep = 1; +nit = 0; +%--- Error on p. Smoothness parameter s = 10^p +errp = 0.1; +opt = optimset('TolX',errp); +%--- Relaxation factor RF: to speedup convergence +RF = 1 + 0.75*isweighted; + +%% Main iterative process +%--- +while RobustIterativeProcess + %--- "amount" of weights (see the function GCVscore) + aow = sum(Wtot(:))/noe; % 0 < aow <= 1 + %--- + while tol>TolZ && nit tol=0 (no iteration) + tol = isweighted*norm(z0(:)-z(:))/norm(z(:)); + + z0 = z; % re-initialization + end + exitflag = nit0.9 % aow = 1 means that all of the data are equally weighted + % very much faster: does not require any inverse DCT + RSS = norm(DCTy(:).*(Gamma(:)-1))^2; + else + % take account of the weights to calculate RSS: + yhat = idctn(Gamma.*DCTy); + RSS = norm(sqrt(Wtot(IsFinite)).*(y(IsFinite)-yhat(IsFinite)))^2; + end + %--- + TrH = sum(Gamma(:)); + GCVscore = RSS/nof/(1-TrH/noe)^2; +end + +end + +%% Robust weights +function W = RobustWeights(r,I,h,wstr) + % weights for robust smoothing. + MAD = median(abs(r(I)-median(r(I)))); % median absolute deviation + u = abs(r/(1.4826*MAD)/sqrt(1-h)); % studentized residuals + if strcmp(wstr,'cauchy') + c = 2.385; W = 1./(1+(u/c).^2); % Cauchy weights + elseif strcmp(wstr,'talworth') + c = 2.795; W = uhere.']) + elseif ~exist('idctn','file') + error('MATLAB:smoothn:MissingFunction',... + ['DCTN and IDCTN are required. Download IDCTN here.']) + end +end + +%% Initial Guess with weighted/missing data +function z = InitialGuess(y,I) + %-- nearest neighbor interpolation (in case of missing values) + if any(~I(:)) + if license('test','image_toolbox') + [z,L] = bwdist(I); + z = y; + z(~I) = y(L(~I)); + else + % If BWDIST does not exist, NaN values are all replaced with the + % same scalar. The initial guess is not optimal and a warning + % message thus appears. + z = y; + z(~I) = mean(y(I)); + warning('MATLAB:smoothn:InitialGuess',... + ['BWDIST (Image Processing Toolbox) does not exist. ',... + 'The initial guess may not be optimal; additional',... + ' iterations can thus be required to ensure complete',... + ' convergence. Increase ''MaxIter'' criterion if necessary.']) + end + else + z = y; + end + %-- coarse fast smoothing using one-tenth of the DCT coefficients + siz = size(z); + z = dctn(z); + for k = 1:ndims(z) + z(ceil(siz(k)/10)+1:end,:) = 0; + z = reshape(z,circshift(siz,[0 1-k])); + z = shiftdim(z,1); + end + z = idctn(z); +end diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ViewSeries.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ViewSeries.m new file mode 100644 index 0000000..6cc11f5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/ViewSeries.m @@ -0,0 +1,43 @@ +function ViewSeries(ACorr,EAlign,Scan,Data,nRows,nCols,colorScheme,minFrac,maxFrac) +% View series of downsampled images. The inputs are ACorr (2D or 3D array of [warping +% corrected] angles), EAlign (2D or 3D matrix of curvature corrected/aligned to EF energies), +% Scan (row), Data (3D data array Data), nRows and nCols as number of rows and columns +% of the frames in which the images are shown, and their colorScheme from the standard +% Matlab colormaps including 'jet', 'hot' and 'gray'. minFrac and maxFrac are contrast enhancement +% parameters used by SetContrast.m inside. + +% downsampling parameters +[nR,nC,~]=size(EAlign); nR=nRows*floor(nR/nRows); nC=nCols*floor(nC/nCols); + +% contrast parameters +if nargin<8; minFrac=1e-2; maxFrac=1-1e-4; end + +% frame loop +for ipage=1:ceil(size(Data,3)/nRows/nCols) + figure; orient tall + for iframe=1:nRows*nCols + n=(ipage-1)*nRows*nCols+iframe; if n>size(Scan,2); break; end +% frames + if ndims(ACorr)<3; ACorrFrame=ACorr; else ACorrFrame=squeeze(ACorr(:,:,n)); end + if ndims(EAlign)<3; EAlignFrame=EAlign; else EAlignFrame=squeeze(EAlign(:,:,n)); end + DataFrame=squeeze(Data(:,:,n)); +% downsampling +% - angles + ACorrFrame1=0; for iF=1:nCols; ACorrFrame1=ACorrFrame1+ACorrFrame(:,iF:nCols:nC)/nCols; end + ACorrFrame=0; for iF=1:nRows; ACorrFrame=ACorrFrame+ACorrFrame1(iF:nRows:nR,:)/nRows; end +% - energies + EAlignFrame1=0; for iF=1:nCols; EAlignFrame1=EAlignFrame1+EAlignFrame(:,iF:nCols:nC)/nCols; end + EAlignFrame=0; for iF=1:nRows; EAlignFrame=EAlignFrame+EAlignFrame1(iF:nRows:nR,:)/nRows; end +% - data + DataFrame1=0; for iF=2:nCols; DataFrame1=DataFrame1+DataFrame(:,iF:nCols:nC)/nCols; end + DataFrame=0; for iF=2:nRows; DataFrame=DataFrame+DataFrame1(iF:nRows:nR,:)/nRows; end +% contrast enhancement + DataFrame=SetContrast(DataFrame,minFrac,maxFrac); +% plot + subplot(nRows,nCols,iframe); +% h=pcolor(ACorrFrame,EAlignFrame,DataFrame); set(h,'EdgeColor','None','FaceColor','Interp'); + ImData(ACorrFrame,EAlignFrame,DataFrame); + colormap('jet'); if nargin>6; eval(['colormap ''' colorScheme '''']); end + title(['Scan=' num2str(Scan(n))],'Interpreter','none','fontweight','normal'); + end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/WarpCorr.m b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/WarpCorr.m new file mode 100644 index 0000000..e06d659 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/WarpCorr.m @@ -0,0 +1,72 @@ +function ACorr=WarpCorr(Angle,Energy,HV,ep,warpFitFile) +% ACorr=WarpCorr(Angle,Energy [,HV] [,ep] [,warpFitFile]) returns matrix ACorr of warping corrected angles +% for the vector of angles Angle, vector of (kinetic or binding) energies Energy and pass energy ep. +% If HV is omitted or empty, Energy is in kinetic energies; if a scalar or raw vector of photon energies, +% Energy is in binding energies. If ep is omitted or empty, it is set to the default value based on the +% input energy range. If the file of the warping fit coefficients warpFitFile is omitted or empty, it is +% set to the default file WarpFit.dat. +% Note1: WarpCorr assumes the raw size of the data array as returned by ReadARPES without trimming +% Note2: WarpCorr applies to the data acquired in the snapshot mode but not in the scanning mode. +% Note3: WarpCorr keeps between the calls the correction matrices if the Angle, Energy and ep +% inputs are the same + +disp('- Warping correction') + +persistent iniChk WarpFit A1 A2 A3 A4 A5 A6 A7 A8 A9 + +% parameters +ePhi=4.5; +if nargin<3; HV=[]; end +if nargin<4; ep=[]; end +if nargin<5; warpFitFile='WarpFit.dat'; end; +% mode WAM/MAM/LAD/MAD = 1/2/3/4 +aRange=Angle(end)-Angle(1); +mode=4; if aRange>12; mode=3; end; if aRange>18; mode=2; end; if aRange>24; mode=1; end; +% transformation to kinetic energy scale +if isempty(HV) +% - check against binding energy input + if min(Energy)<4.5; disp('Warning: Binding energy scale requires photon energy input'); end +% - kinetic energy input + KEnergy=Energy; +else + if min(Energy)<4.5 +% - binding energy input + KEnergy=repmat(HV,length(Energy),1)+repmat(Energy,1,length(HV))-ePhi; + else +% - kinetic energy input + KEnergy=Energy; + end +end +% default pass energy +eRange=Energy(end)-Energy(1); +if isempty(ep); ep=eRange/(2*0.066); end +% initialization if the first call or input energy or retarding ratio range changed +if isempty(iniChk)||norm(iniChk-[aRange eRange ep])>1e-3 +% - load warping coefficients + WarpFit=load(warpFitFile); + ind=find(WarpFit(:,1)==mode); + if isempty(ind); disp('- Error: Angular mode not in WarpFit.dat'); ACorr=[]; return + else WarpFit=WarpFit(ind,2:end); + end +% - polynomial matrices + [AM,EScM]=meshgrid(Angle,(Energy-mean(Energy))/ep); + A1=AM; A2=AM.^2; A3=AM.^3; A4=AM.*EScM; A5=AM.^2.*EScM; + A6=AM.^3.*EScM; A7=AM.*EScM.^2; A8=AM.^2.*EScM.^2; A9=AM.^3.*EScM.^2; +% - initialization check + iniChk=[aRange eRange ep]; +end + +% array of corrected angles +ACorr=zeros(size(KEnergy,1),length(Angle),size(KEnergy,2)); +% - cycle over hv frames +for iS=1:size(KEnergy,2) +% - rr +rr=mean(KEnergy(:,iS))/ep; +% - interpolating the coefficients +Fit=interp1(WarpFit(:,1),WarpFit(:,2:end),rr,'pchip','extrap'); +% - correction +ACorr(:,:,iS)=Fit(1)*A1+Fit(2)*A2+Fit(3)*A3+Fit(4)*A4+Fit(5)*A5+... + Fit(6)*A6+Fit(7)*A7+Fit(8)*A8+Fit(9)*A9; +% - check corrected image +% ImData(ACorr,KEnergy,Data,'interp'); set(gca,'YDir','normal','TickDir','Out'); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/WarpFit.dat b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/WarpFit.dat new file mode 100644 index 0000000..a30c547 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MATools_IceLine_VNS/WarpFit.dat @@ -0,0 +1,47 @@ +% Calibration data is taken with slit array, hv=1keV, Uconv=0.1*Ep. +% WAM (mode=1) and LAD (mode=3) data taken on 26.02.2013, Ek=350eV for WAM and 600eV for LAD; +% for WAM the Ep=40eV is missing; the WAM angular scale zero slightly drifted with Ep. +% MAM (mode=2)data taken on 30.01.2014, Ek=600eV. + 1.0000000e+00 1.1666667e+01 7.8486451e-01 2.6252806e-03 3.5512691e-04 -7.4497438e-01 -2.4580483e-02 -3.7022362e-03 -1.3631077e-01 1.4317764e-01 6.5564314e-02 + 1.0000000e+00 1.0000000e+01 9.4499244e-01 1.7689033e-03 -3.8234004e-04 1.3925957e-02 -1.6661738e-02 8.9034796e-04 -1.6619161e+00 6.0289210e-02 3.5817790e-02 + 1.0000000e+00 7.0000000e+00 9.3235873e-01 1.8190070e-03 -2.7861773e-04 7.3757226e-02 -1.8692558e-02 6.4249864e-04 7.5243953e-02 4.9788753e-02 2.0103766e-02 + 1.0000000e+00 5.8333333e+00 9.3524064e-01 1.8917568e-03 -2.7576215e-04 6.5569738e-02 -2.2072579e-02 9.0871021e-04 -2.2796855e-01 5.3575007e-02 2.4874189e-02 + 1.0000000e+00 5.0000000e+00 9.3567974e-01 1.8840452e-03 -2.5814245e-04 9.9078822e-02 -2.1204896e-02 5.9724247e-04 3.6117336e-01 7.9235749e-02 2.1807709e-02 + 1.0000000e+00 4.3750000e+00 9.3423311e-01 1.7632761e-03 -1.9652570e-04 1.1406955e-01 -1.9603072e-02 2.6210206e-04 1.9102179e+00 1.1841798e-01 7.4437550e-03 + 1.0000000e+00 3.5000000e+00 9.2752366e-01 1.6677888e-03 -1.1378830e-04 9.8774920e-02 -1.9596768e-02 -2.6333242e-04 2.3756781e+00 1.1412266e-01 7.7495397e-03 + 1.0000000e+00 2.6923077e+00 9.2060166e-01 1.8213639e-03 -1.1955421e-04 1.3194298e-01 -2.2950809e-02 -1.3957909e-04 2.8245694e+00 1.4470518e-01 2.2700228e-03 + 1.0000000e+00 2.1875000e+00 9.2935241e-01 1.8769675e-03 -9.3625226e-05 1.3575745e-01 -2.5524283e-02 -6.0465036e-04 2.7982317e+00 1.5847581e-01 6.6328318e-03 + 1.0000000e+00 1.8421053e+00 9.3656931e-01 1.7687522e-03 -6.2474978e-05 1.5743513e-01 -2.8426630e-02 -1.3498163e-03 2.4628121e+00 1.7628626e-01 1.6234894e-02 + 1.0000000e+00 1.5909091e+00 9.2938240e-01 1.6957461e-03 -3.9240799e-05 1.2509238e-01 -2.8341617e-02 -9.8517958e-04 2.6782854e+00 1.6688236e-01 1.4041178e-02 + 2.0000000e+00 1.2000000e+01 7.6340370e-01 2.8311455e-03 8.7784755e-04 -1.0528934e+00 -1.9788828e-02 6.9303195e-03 -3.7868593e+00 7.6877506e-01 1.7424718e-01 + 2.0000000e+00 1.0000000e+01 8.2478673e-01 3.8048564e-03 5.5116463e-04 -6.0337470e-01 -5.3664259e-02 1.6127571e-03 4.8760283e-02 4.4770815e-01 8.5291411e-02 + 2.0000000e+00 8.5714286e+00 1.0132165e+00 4.8351660e-04 -9.6574036e-04 3.0291150e-01 -5.2268240e-02 -3.5668126e-04 2.3490278e+00 2.8591823e-01 2.0497625e-02 + 2.0000000e+00 7.5000000e+00 9.5708136e-01 1.5895249e-03 -5.3801601e-04 2.5578373e-01 -5.3235553e-02 -7.5476739e-05 2.4991774e+00 1.9286898e-01 1.4686713e-02 + 2.0000000e+00 6.6666667e+00 9.2782840e-01 1.2318005e-03 -3.8288588e-04 1.5718071e-01 -4.9498322e-02 8.7663337e-04 3.0540761e+00 1.4544714e-01 -2.9375903e-03 + 2.0000000e+00 6.0000000e+00 8.9758672e-01 1.1934265e-03 -2.2681473e-04 6.4393674e-02 -4.9833857e-02 2.1689127e-03 2.0134532e+00 1.3894570e-01 1.9039625e-02 + 2.0000000e+00 5.0000000e+00 9.6315181e-01 2.1745774e-03 -9.6708540e-04 6.1694709e-01 -3.5742960e-02 1.8491167e-03 4.3117049e+00 -5.2714209e-02 -2.9614572e-02 + 2.0000000e+00 4.2857143e+00 8.8061723e-01 1.1420589e-03 -2.4107998e-04 3.5522605e-02 -4.2134093e-02 1.2462684e-03 -2.3505993e-01 -2.9622535e-02 7.6506177e-02 + 2.0000000e+00 3.7500000e+00 8.3604179e-01 1.4563854e-03 3.4238938e-04 -2.2020728e-01 -4.7625697e-02 2.6158676e-03 1.2073054e+00 1.8789753e-01 3.9003591e-02 + 2.0000000e+00 3.3333333e+00 8.5472996e-01 2.2077427e-03 2.1913633e-04 -8.3935875e-02 -4.7708154e-02 1.3911611e-03 2.1482459e+00 1.8466381e-01 2.1355393e-02 + 2.0000000e+00 3.0000000e+00 8.8033923e-01 2.7350849e-03 5.2930675e-05 7.4992070e-02 -4.5016908e-02 8.6731942e-04 2.7334027e+00 1.6623259e-01 1.1169896e-02 + 2.0000000e+00 2.6086957e+00 8.6080389e-01 2.9582837e-03 2.6876811e-04 -4.8866475e-02 -4.4468867e-02 3.0794569e-04 2.4451004e+00 1.5987892e-01 2.1482036e-02 + 2.0000000e+00 2.3076923e+00 8.6939260e-01 3.0808461e-03 2.9024917e-04 -5.7687620e-02 -4.4296704e-02 -3.1359215e-04 1.2520497e+00 2.4316067e-01 5.3319916e-02 + 2.0000000e+00 2.0689655e+00 8.8114430e-01 3.1895318e-03 2.5917070e-04 -3.6177198e-02 -4.4957985e-02 -9.3637200e-04 8.9044034e-01 2.8432750e-01 6.5562841e-02 + 2.0000000e+00 1.8750000e+00 8.8190357e-01 3.3104458e-03 2.5970035e-04 -6.6930388e-02 -4.4925623e-02 -1.2009718e-03 6.4660172e-01 3.1089539e-01 7.3783136e-02 + 2.0000000e+00 1.7142857e+00 8.5755429e-01 3.2986432e-03 4.9007648e-04 -1.3617042e-01 -4.3987221e-02 -1.4989395e-03 5.2155899e-01 3.1316903e-01 7.7923608e-02 + 3.0000000e+00 3.0000000e+01 9.3131022e-01 8.2597450e-03 5.1081804e-04 -1.3402651e-01 -7.2246367e-02 -5.5988897e-03 1.5374868e+00 3.4599698e-01 4.9330743e-02 + 3.0000000e+00 2.4000000e+01 9.2467526e-01 6.3341991e-03 1.7753699e-04 -4.3261422e-01 -5.5131881e-02 -1.9958705e-03 2.8918526e+00 2.1531420e-01 1.6078639e-02 + 3.0000000e+00 2.0000000e+01 9.3393229e-01 3.3488154e-03 -1.1152565e-04 -5.5244530e-02 -3.8968289e-02 -9.5867096e-04 1.2268025e+00 8.4294093e-02 3.5574940e-02 + 3.0000000e+00 1.7142857e+01 9.5059772e-01 3.8272919e-03 -5.5642471e-04 2.8256611e-01 -3.3916381e-02 2.9679522e-04 1.5630599e+00 5.0493715e-02 9.0972340e-03 + 3.0000000e+00 1.5000000e+01 9.3402812e-01 4.3175605e-03 -1.0838535e-04 -6.6806770e-02 -4.4191578e-02 -1.1142718e-03 1.4536725e+00 9.4831758e-02 4.1854807e-02 + 3.0000000e+00 1.2000000e+01 9.3498016e-01 4.0473169e-03 -8.4715514e-05 -7.7367878e-02 -4.5312966e-02 -1.5645238e-03 1.9968548e+00 1.4511322e-01 4.1655025e-02 + 3.0000000e+00 1.0000000e+01 9.3092485e-01 3.1875552e-03 -6.5883380e-05 -2.5108918e-02 -3.4356190e-02 -7.5332491e-05 1.9673302e+00 8.5808907e-02 3.7330198e-02 + 3.0000000e+00 7.5000000e+00 9.2899302e-01 3.0826568e-03 -1.5707219e-05 -6.2741266e-03 -3.3001991e-02 1.7303876e-04 2.2077348e+00 6.5493832e-02 3.7567881e-02 + 3.0000000e+00 6.0000000e+00 9.2387684e-01 2.7580768e-03 8.5993606e-05 2.3771552e-03 -3.1345898e-02 4.5503776e-04 2.0704301e+00 3.7166065e-02 3.3210115e-02 + 3.0000000e+00 5.0000000e+00 9.2170936e-01 2.9736780e-03 8.2170413e-05 4.1645762e-03 -2.6929763e-02 1.3352710e-04 2.6869195e+00 5.1833013e-02 2.0828516e-02 + 3.0000000e+00 4.2857143e+00 9.2617785e-01 2.8454061e-03 7.3152173e-05 1.0271635e-01 -2.7756657e-02 1.6176086e-04 2.7132439e+00 1.7374439e-02 1.3080123e-02 + 3.0000000e+00 3.5294118e+00 9.2064153e-01 2.9982272e-03 7.8310905e-05 2.1679619e-03 -2.4080499e-02 4.9988504e-04 2.7449118e+00 4.2088094e-02 1.6814754e-02 + 3.0000000e+00 3.0000000e+00 9.2029058e-01 2.8926509e-03 7.4431320e-05 1.1011673e-02 -2.2522534e-02 5.4270980e-04 2.8238914e+00 6.2191053e-02 2.1547114e-02 + 3.0000000e+00 2.4000000e+00 9.2055433e-01 3.0481727e-03 1.0739890e-04 4.7432488e-02 -2.2275385e-02 5.4720232e-04 2.8764483e+00 4.2127172e-02 1.7435568e-02 + 3.0000000e+00 2.0000000e+00 9.2212435e-01 3.0485849e-03 5.0553969e-05 3.0420616e-02 -2.1232073e-02 5.7598728e-04 2.6726310e+00 5.5332318e-02 2.2860502e-02 + 3.0000000e+00 1.7142857e+00 9.2326920e-01 3.0488348e-03 4.5036335e-05 3.4798953e-02 -1.9970755e-02 3.2405038e-04 2.7769612e+00 6.0283280e-02 2.0726711e-02 \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/0_ReadMeImages/IMFP_UI_Snapshot.png b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/0_ReadMeImages/IMFP_UI_Snapshot.png new file mode 100644 index 0000000..4fcdecd Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/0_ReadMeImages/IMFP_UI_Snapshot.png differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/0_ReadMeImages/PES_UI_Snapshot.png b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/0_ReadMeImages/PES_UI_Snapshot.png new file mode 100644 index 0000000..869b1d5 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/0_ReadMeImages/PES_UI_Snapshot.png differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Apps/IMFP_UI.mlapp b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Apps/IMFP_UI.mlapp new file mode 100644 index 0000000..d1af2dc Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Apps/IMFP_UI.mlapp differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Apps/PES_UI.mlapp b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Apps/PES_UI.mlapp new file mode 100644 index 0000000..a466056 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Apps/PES_UI.mlapp differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/IMFP_CALC.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/IMFP_CALC.m new file mode 100644 index 0000000..dad1ee3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/IMFP_CALC.m @@ -0,0 +1,86 @@ +function imfp = IMFP_CALC(formalism, ke_dat, args) +% imfp = IMFP_CALC(formalism, ke_dat, args) +% Function that calculates the electron inelastic mean free path (IMFP). +% The TPP2M, S1, S2 and Universal formalisms are available. The user can +% define a scalar or vector of kinetic energies for the input. +% If the args is a string of an element / material, it will look it up +% the relevant materials parameters in the Material Properties Database +% (MPD) ('MPD_PCC.mat'). Otherwise, the args can be manually inserted as +% defined below. +% +% IN: +% - formalism: string for imfp calculator formalism. Default:"TPP2M" ["TPP2M","S1","S2","Universal"] +% - ke_dat: N×1 column vector of the input electron kinetic energy (for PES; KE = BE - PHI) [eV] +% - args: string or vector of scalars defining the arguments of the chosen formalism; +% (1) string of element / material whose parameters are found in materials database; e.g. "Si", "SiO2", "Al2O3"... +% (2) vector with manual entry of material parameters: +% -> TPP2M: 4x1 [density(g/cc),atomicweight(amu),egap(eV),valency(valence electrons per atom)] +% -> S1: 4x1 [density(g/cc),atomicweight(amu),egap(eV),Z(atomic mass number or average for compounds)] +% -> S2: 1x1 [Z(atomic mass number or average for compounds)] +% -> Universal: no args, material independent. +% +% OUT: +% - imfp: N×1 column vector of the electron IMFP values [Angstroms] +% +% SEE REFERENCES: +% [1] Tanuma, S., Powell, C. J., & Penn, D. R. (1987). +% Proposed formula for electron inelastic mean free paths based on +% calculations for 31 materials. Surface Science Letters, 192(1), +% L849–L857. https://doi.org/10.1016/0167-2584(87)90829-2 +% [2] Shinotsuka H, Tanuma S, Powell CJ, Penn DR. Calculations of +% electron inelastic mean free paths. XII. Data for 42 inorganic +% compounds over the 50 eV to 200 keV range with the full Penn +% algorithm. Surf Interface Anal. 2018;51(4):427-457. +% doi:10.1002/sia.6598 +% [3] M. P. Seah, "An accurate and simple universal curve for the +% energy-dependent electron inelastic mean free path,†+% Surf. Interface Anal., vol. 44, no. 4, pp. 497–503, 2012, +% doi: 10.1002/sia.4816. + +%% Default parameters +% - Default formalism +if nargin < 3; args = []; end +if nargin < 1; formalism = "TPP2M"; end +if isempty(formalism); formalism = "TPP2M"; end +if isempty(args); args = []; end +% - Validity check on the inputs +if ischar(formalism); formalism = string(formalism); end +if ischar(args); args = string(args); end + +%% - 1 - Determination of the IMFP +% If the kinetic energy is negative, assume it is zero +ke_dat(ke_dat<0) = 0; +% -- TPP2M formalism +if strcmpi(formalism, "TPP2M") || strcmpi(formalism, "TPP-2M") + if isstring(args) + material = args; + imfp = eimfp_tpp2m_mpd(ke_dat, material); + else + rho = args(1); Nv=args(4); M = args(2); Egap = args(3); + imfp = eimfp_tpp2m(ke_dat, rho, Nv, M, Egap); + end +% -- S1 formalism +elseif strcmpi(formalism, "S1") + if isstring(args) + material = args; + imfp = eimfp_S1_mpd(ke_dat, material); + else + rho = args(1); Z=args(4); M = args(2); Egap = args(3); + imfp = eimfp_S1(ke_dat, rho, M, Egap, Z); + end +% -- S2 formalism +elseif strcmpi(formalism, "S2") + if isstring(args) + material = args; + imfp = eimfp_S2_avg_mpd(ke_dat, material); + else + Z=args(1); + imfp = eimfp_S2_avg(ke_dat, Z); + end +% -- Universal formalism +elseif strcmpi(formalism, "Universal") + imfp = eimfp_universal(ke_dat); +end +%% Ensuring the imfp is a column vector +if size(imfp, 2) >1; imfp = imfp'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/003_Li_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/003_Li_eIMFP.txt new file mode 100644 index 0000000..c45fccb --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/003_Li_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Li + +SOURCE: + Tanuma, Powell and Penn + Unpublished data + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 6.94100 + +DENSITY: 0.5340 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.59 + 54.9 4.85 + 59.8 5.10 + 64.6 5.35 + 69.5 5.59 + 74.4 5.82 + 79.3 6.05 + 84.1 6.28 + 89.0 6.50 + 93.9 6.73 + 98.8 6.95 + 103.6 7.17 + 108.5 7.39 + 113.4 7.60 + 118.3 7.82 + 123.1 8.03 + 128.0 8.24 + 132.9 8.46 + 137.8 8.67 + 142.6 8.88 + 147.5 9.09 + 152.4 9.29 + 157.3 9.50 + 162.1 9.71 + 167.0 9.91 + 171.9 10.12 + 176.8 10.32 + 181.6 10.52 + 186.5 10.72 + 191.4 10.92 + 196.3 11.12 + 201.1 11.32 + 206.0 11.52 + 210.9 11.72 + 215.8 11.92 + 220.6 12.12 + 225.5 12.31 + 230.4 12.51 + 235.3 12.70 + 240.1 12.90 + 245.0 13.09 + 249.9 13.29 + 254.8 13.48 + 259.6 13.67 + 264.5 13.86 + 269.4 14.06 + 274.3 14.25 + 279.1 14.44 + 284.0 14.63 + 288.9 14.82 + 293.8 15.01 + 298.6 15.20 + 303.5 15.38 + 308.4 15.57 + 313.3 15.76 + 318.1 15.95 + 323.0 16.13 + 327.9 16.32 + 332.8 16.51 + 337.6 16.69 + 342.5 16.88 + 347.4 17.06 + 352.3 17.25 + 357.1 17.43 + 362.0 17.61 + 366.9 17.80 + 371.8 17.98 + 376.6 18.16 + 381.5 18.35 + 386.4 18.53 + 391.3 18.71 + 396.1 18.89 + 401.0 19.07 + 405.9 19.25 + 410.8 19.43 + 415.6 19.61 + 420.5 19.79 + 425.4 19.97 + 430.3 20.15 + 435.1 20.33 + 440.0 20.51 + 444.9 20.69 + 449.8 20.87 + 454.6 21.04 + 459.5 21.22 + 464.4 21.40 + 469.3 21.58 + 474.1 21.75 + 479.0 21.93 + 483.9 22.11 + 488.8 22.28 + 493.6 22.46 + 498.5 22.63 + 503.4 22.81 + 508.3 22.98 + 513.1 23.16 + 518.0 23.33 + 522.9 23.51 + 527.8 23.68 + 532.6 23.86 + 537.5 24.03 + 542.4 24.20 + 547.3 24.38 + 552.1 24.55 + 557.0 24.72 + 561.9 24.90 + 566.8 25.07 + 571.6 25.24 + 576.5 25.41 + 581.4 25.59 + 586.3 25.76 + 591.1 25.93 + 596.0 26.10 + 600.9 26.27 + 605.8 26.44 + 610.6 26.61 + 615.5 26.78 + 620.4 26.95 + 625.3 27.13 + 630.1 27.30 + 635.0 27.47 + 639.9 27.63 + 644.8 27.80 + 649.6 27.97 + 654.5 28.14 + 659.4 28.31 + 664.3 28.48 + 669.1 28.65 + 674.0 28.82 + 678.9 28.99 + 683.8 29.15 + 688.6 29.32 + 693.5 29.49 + 698.4 29.66 + 703.3 29.83 + 708.1 29.99 + 713.0 30.16 + 717.9 30.33 + 722.8 30.49 + 727.6 30.66 + 732.5 30.83 + 737.4 30.99 + 742.3 31.16 + 747.1 31.33 + 752.0 31.49 + 756.9 31.66 + 761.8 31.82 + 766.6 31.99 + 771.5 32.15 + 776.4 32.32 + 781.3 32.49 + 786.1 32.65 + 791.0 32.82 + 795.9 32.98 + 800.8 33.14 + 805.6 33.31 + 810.5 33.47 + 815.4 33.64 + 820.3 33.80 + 825.1 33.97 + 830.0 34.13 + 834.9 34.29 + 839.8 34.46 + 844.6 34.62 + 849.5 34.78 + 854.4 34.95 + 859.3 35.11 + 864.1 35.27 + 869.0 35.44 + 873.9 35.60 + 878.8 35.76 + 883.6 35.92 + 888.5 36.09 + 893.4 36.25 + 898.3 36.41 + 903.1 36.57 + 908.0 36.73 + 912.9 36.90 + 917.8 37.06 + 922.6 37.22 + 927.5 37.38 + 932.4 37.54 + 937.3 37.70 + 942.1 37.86 + 947.0 38.02 + 951.9 38.19 + 956.8 38.35 + 961.6 38.51 + 966.5 38.67 + 971.4 38.83 + 976.3 38.99 + 981.1 39.15 + 986.0 39.31 + 990.9 39.47 + 995.8 39.63 + 1000.6 39.79 + 1005.5 39.95 + 1010.4 40.11 + 1015.3 40.27 + 1020.1 40.43 + 1025.0 40.59 + 1029.9 40.74 + 1034.8 40.90 + 1039.6 41.06 + 1044.5 41.22 + 1049.4 41.38 + 1054.3 41.54 + 1059.1 41.70 + 1064.0 41.86 + 1068.9 42.01 + 1073.8 42.17 + 1078.6 42.33 + 1083.5 42.49 + 1088.4 42.65 + 1093.3 42.81 + 1098.1 42.96 + 1103.0 43.12 + 1107.9 43.28 + 1112.8 43.44 + 1117.6 43.59 + 1122.5 43.75 + 1127.4 43.91 + 1132.3 44.07 + 1137.1 44.22 + 1142.0 44.38 + 1146.9 44.54 + 1151.8 44.69 + 1156.6 44.85 + 1161.5 45.01 + 1166.4 45.16 + 1171.3 45.32 + 1176.1 45.48 + 1181.0 45.63 + 1185.9 45.79 + 1190.8 45.95 + 1195.6 46.10 + 1200.5 46.26 + 1205.4 46.41 + 1210.3 46.57 + 1215.1 46.73 + 1220.0 46.88 + 1224.9 47.04 + 1229.8 47.19 + 1234.6 47.35 + 1239.5 47.50 + 1244.4 47.66 + 1249.3 47.81 + 1254.1 47.97 + 1259.0 48.12 + 1263.9 48.28 + 1268.8 48.43 + 1273.6 48.59 + 1278.5 48.74 + 1283.4 48.90 + 1288.3 49.05 + 1293.1 49.21 + 1298.0 49.36 + 1302.9 49.52 + 1307.8 49.67 + 1312.6 49.82 + 1317.5 49.98 + 1322.4 50.13 + 1327.3 50.29 + 1332.1 50.44 + 1337.0 50.59 + 1341.9 50.75 + 1346.8 50.90 + 1351.6 51.06 + 1356.5 51.21 + 1361.4 51.36 + 1366.3 51.52 + 1371.1 51.67 + 1376.0 51.82 + 1380.9 51.98 + 1385.8 52.13 + 1390.6 52.28 + 1395.5 52.44 + 1400.4 52.59 + 1405.3 52.74 + 1410.1 52.89 + 1415.0 53.05 + 1419.9 53.20 + 1424.8 53.35 + 1429.6 53.51 + 1434.5 53.66 + 1439.4 53.81 + 1444.3 53.96 + 1449.1 54.11 + 1454.0 54.27 + 1458.9 54.42 + 1463.8 54.57 + 1468.6 54.72 + 1473.5 54.88 + 1478.4 55.03 + 1483.3 55.18 + 1488.1 55.33 + 1493.0 55.48 + 1497.9 55.63 + 1502.8 55.79 + 1507.6 55.94 + 1512.5 56.09 + 1517.4 56.24 + 1522.3 56.39 + 1527.1 56.54 + 1532.0 56.69 + 1536.9 56.85 + 1541.8 57.00 + 1546.6 57.15 + 1551.5 57.30 + 1556.4 57.45 + 1561.3 57.60 + 1566.1 57.75 + 1571.0 57.90 + 1575.9 58.05 + 1580.8 58.20 + 1585.6 58.35 + 1590.5 58.50 + 1595.4 58.65 + 1600.3 58.81 + 1605.1 58.96 + 1610.0 59.11 + 1614.9 59.26 + 1619.8 59.41 + 1624.6 59.56 + 1629.5 59.71 + 1634.4 59.86 + 1639.3 60.01 + 1644.1 60.16 + 1649.0 60.31 + 1653.9 60.46 + 1658.8 60.61 + 1663.6 60.76 + 1668.5 60.90 + 1673.4 61.05 + 1678.3 61.20 + 1683.1 61.35 + 1688.0 61.50 + 1692.9 61.65 + 1697.8 61.80 + 1702.6 61.95 + 1707.5 62.10 + 1712.4 62.25 + 1717.3 62.40 + 1722.1 62.55 + 1727.0 62.70 + 1731.9 62.84 + 1736.8 62.99 + 1741.6 63.14 + 1746.5 63.29 + 1751.4 63.44 + 1756.3 63.59 + 1761.1 63.74 + 1766.0 63.89 + 1770.9 64.03 + 1775.8 64.18 + 1780.6 64.33 + 1785.5 64.48 + 1790.4 64.63 + 1795.3 64.78 + 1800.1 64.92 + 1805.0 65.07 + 1809.9 65.22 + 1814.8 65.37 + 1819.6 65.52 + 1824.5 65.66 + 1829.4 65.81 + 1834.3 65.96 + 1839.1 66.11 + 1844.0 66.26 + 1848.9 66.40 + 1853.8 66.55 + 1858.6 66.70 + 1863.5 66.85 + 1868.4 66.99 + 1873.3 67.14 + 1878.1 67.29 + 1883.0 67.44 + 1887.9 67.58 + 1892.8 67.73 + 1897.6 67.88 + 1902.5 68.03 + 1907.4 68.17 + 1912.3 68.32 + 1917.1 68.47 + 1922.0 68.61 + 1926.9 68.76 + 1931.8 68.91 + 1936.6 69.05 + 1941.5 69.20 + 1946.4 69.35 + 1951.3 69.49 + 1956.1 69.64 + 1961.0 69.79 + 1965.9 69.93 + 1970.8 70.08 + 1975.6 70.23 + 1980.5 70.37 + 1985.4 70.52 + 1990.3 70.67 + 1995.1 70.81 + 2000.0 70.96 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/004_Be_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/004_Be_eIMFP.txt new file mode 100644 index 0000000..ff1bd16 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/004_Be_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Be + +SOURCE: + Tanuma, Powell and Penn + Unpublished data + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 9.01218 + +DENSITY: 1.8500 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 3.53 + 54.9 3.56 + 59.8 3.60 + 64.6 3.66 + 69.5 3.73 + 74.4 3.81 + 79.3 3.89 + 84.1 3.97 + 89.0 4.06 + 93.9 4.15 + 98.8 4.24 + 103.6 4.33 + 108.5 4.43 + 113.4 4.52 + 118.3 4.62 + 123.1 4.71 + 128.0 4.81 + 132.9 4.91 + 137.8 5.00 + 142.6 5.10 + 147.5 5.20 + 152.4 5.29 + 157.3 5.39 + 162.1 5.49 + 167.0 5.58 + 171.9 5.68 + 176.8 5.78 + 181.6 5.87 + 186.5 5.97 + 191.4 6.07 + 196.3 6.16 + 201.1 6.26 + 206.0 6.35 + 210.9 6.45 + 215.8 6.54 + 220.6 6.64 + 225.5 6.73 + 230.4 6.83 + 235.3 6.92 + 240.1 7.01 + 245.0 7.11 + 249.9 7.20 + 254.8 7.29 + 259.6 7.39 + 264.5 7.48 + 269.4 7.57 + 274.3 7.66 + 279.1 7.76 + 284.0 7.85 + 288.9 7.94 + 293.8 8.03 + 298.6 8.12 + 303.5 8.21 + 308.4 8.31 + 313.3 8.40 + 318.1 8.49 + 323.0 8.58 + 327.9 8.67 + 332.8 8.76 + 337.6 8.85 + 342.5 8.94 + 347.4 9.03 + 352.3 9.12 + 357.1 9.20 + 362.0 9.29 + 366.9 9.38 + 371.8 9.47 + 376.6 9.56 + 381.5 9.65 + 386.4 9.74 + 391.3 9.82 + 396.1 9.91 + 401.0 10.00 + 405.9 10.09 + 410.8 10.17 + 415.6 10.26 + 420.5 10.35 + 425.4 10.44 + 430.3 10.52 + 435.1 10.61 + 440.0 10.70 + 444.9 10.78 + 449.8 10.87 + 454.6 10.95 + 459.5 11.04 + 464.4 11.13 + 469.3 11.21 + 474.1 11.30 + 479.0 11.38 + 483.9 11.47 + 488.8 11.55 + 493.6 11.64 + 498.5 11.72 + 503.4 11.81 + 508.3 11.89 + 513.1 11.98 + 518.0 12.06 + 522.9 12.15 + 527.8 12.23 + 532.6 12.31 + 537.5 12.40 + 542.4 12.48 + 547.3 12.57 + 552.1 12.65 + 557.0 12.73 + 561.9 12.82 + 566.8 12.90 + 571.6 12.98 + 576.5 13.07 + 581.4 13.15 + 586.3 13.23 + 591.1 13.31 + 596.0 13.40 + 600.9 13.48 + 605.8 13.56 + 610.6 13.64 + 615.5 13.73 + 620.4 13.81 + 625.3 13.89 + 630.1 13.97 + 635.0 14.06 + 639.9 14.14 + 644.8 14.22 + 649.6 14.30 + 654.5 14.38 + 659.4 14.46 + 664.3 14.54 + 669.1 14.63 + 674.0 14.71 + 678.9 14.79 + 683.8 14.87 + 688.6 14.95 + 693.5 15.03 + 698.4 15.11 + 703.3 15.19 + 708.1 15.27 + 713.0 15.35 + 717.9 15.43 + 722.8 15.51 + 727.6 15.59 + 732.5 15.67 + 737.4 15.75 + 742.3 15.83 + 747.1 15.91 + 752.0 15.99 + 756.9 16.07 + 761.8 16.15 + 766.6 16.23 + 771.5 16.31 + 776.4 16.39 + 781.3 16.47 + 786.1 16.55 + 791.0 16.63 + 795.9 16.71 + 800.8 16.79 + 805.6 16.87 + 810.5 16.95 + 815.4 17.03 + 820.3 17.10 + 825.1 17.18 + 830.0 17.26 + 834.9 17.34 + 839.8 17.42 + 844.6 17.50 + 849.5 17.58 + 854.4 17.65 + 859.3 17.73 + 864.1 17.81 + 869.0 17.89 + 873.9 17.97 + 878.8 18.05 + 883.6 18.12 + 888.5 18.20 + 893.4 18.28 + 898.3 18.36 + 903.1 18.43 + 908.0 18.51 + 912.9 18.59 + 917.8 18.67 + 922.6 18.74 + 927.5 18.82 + 932.4 18.90 + 937.3 18.98 + 942.1 19.05 + 947.0 19.13 + 951.9 19.21 + 956.8 19.28 + 961.6 19.36 + 966.5 19.44 + 971.4 19.52 + 976.3 19.59 + 981.1 19.67 + 986.0 19.75 + 990.9 19.82 + 995.8 19.90 + 1000.6 19.98 + 1005.5 20.05 + 1010.4 20.13 + 1015.3 20.21 + 1020.1 20.28 + 1025.0 20.36 + 1029.9 20.43 + 1034.8 20.51 + 1039.6 20.59 + 1044.5 20.66 + 1049.4 20.74 + 1054.3 20.81 + 1059.1 20.89 + 1064.0 20.97 + 1068.9 21.04 + 1073.8 21.12 + 1078.6 21.19 + 1083.5 21.27 + 1088.4 21.34 + 1093.3 21.42 + 1098.1 21.50 + 1103.0 21.57 + 1107.9 21.65 + 1112.8 21.72 + 1117.6 21.80 + 1122.5 21.87 + 1127.4 21.95 + 1132.3 22.02 + 1137.1 22.10 + 1142.0 22.17 + 1146.9 22.25 + 1151.8 22.32 + 1156.6 22.40 + 1161.5 22.47 + 1166.4 22.55 + 1171.3 22.62 + 1176.1 22.70 + 1181.0 22.77 + 1185.9 22.85 + 1190.8 22.92 + 1195.6 23.00 + 1200.5 23.07 + 1205.4 23.14 + 1210.3 23.22 + 1215.1 23.29 + 1220.0 23.37 + 1224.9 23.44 + 1229.8 23.52 + 1234.6 23.59 + 1239.5 23.66 + 1244.4 23.74 + 1249.3 23.81 + 1254.1 23.89 + 1259.0 23.96 + 1263.9 24.03 + 1268.8 24.11 + 1273.6 24.18 + 1278.5 24.26 + 1283.4 24.33 + 1288.3 24.40 + 1293.1 24.48 + 1298.0 24.55 + 1302.9 24.63 + 1307.8 24.70 + 1312.6 24.77 + 1317.5 24.85 + 1322.4 24.92 + 1327.3 24.99 + 1332.1 25.07 + 1337.0 25.14 + 1341.9 25.21 + 1346.8 25.29 + 1351.6 25.36 + 1356.5 25.43 + 1361.4 25.51 + 1366.3 25.58 + 1371.1 25.65 + 1376.0 25.73 + 1380.9 25.80 + 1385.8 25.87 + 1390.6 25.94 + 1395.5 26.02 + 1400.4 26.09 + 1405.3 26.16 + 1410.1 26.24 + 1415.0 26.31 + 1419.9 26.38 + 1424.8 26.45 + 1429.6 26.53 + 1434.5 26.60 + 1439.4 26.67 + 1444.3 26.74 + 1449.1 26.82 + 1454.0 26.89 + 1458.9 26.96 + 1463.8 27.03 + 1468.6 27.11 + 1473.5 27.18 + 1478.4 27.25 + 1483.3 27.32 + 1488.1 27.40 + 1493.0 27.47 + 1497.9 27.54 + 1502.8 27.61 + 1507.6 27.68 + 1512.5 27.76 + 1517.4 27.83 + 1522.3 27.90 + 1527.1 27.97 + 1532.0 28.04 + 1536.9 28.12 + 1541.8 28.19 + 1546.6 28.26 + 1551.5 28.33 + 1556.4 28.40 + 1561.3 28.48 + 1566.1 28.55 + 1571.0 28.62 + 1575.9 28.69 + 1580.8 28.76 + 1585.6 28.83 + 1590.5 28.91 + 1595.4 28.98 + 1600.3 29.05 + 1605.1 29.12 + 1610.0 29.19 + 1614.9 29.26 + 1619.8 29.33 + 1624.6 29.41 + 1629.5 29.48 + 1634.4 29.55 + 1639.3 29.62 + 1644.1 29.69 + 1649.0 29.76 + 1653.9 29.83 + 1658.8 29.90 + 1663.6 29.98 + 1668.5 30.05 + 1673.4 30.12 + 1678.3 30.19 + 1683.1 30.26 + 1688.0 30.33 + 1692.9 30.40 + 1697.8 30.47 + 1702.6 30.54 + 1707.5 30.61 + 1712.4 30.69 + 1717.3 30.76 + 1722.1 30.83 + 1727.0 30.90 + 1731.9 30.97 + 1736.8 31.04 + 1741.6 31.11 + 1746.5 31.18 + 1751.4 31.25 + 1756.3 31.32 + 1761.1 31.39 + 1766.0 31.46 + 1770.9 31.53 + 1775.8 31.60 + 1780.6 31.67 + 1785.5 31.74 + 1790.4 31.81 + 1795.3 31.88 + 1800.1 31.96 + 1805.0 32.03 + 1809.9 32.10 + 1814.8 32.17 + 1819.6 32.24 + 1824.5 32.31 + 1829.4 32.38 + 1834.3 32.45 + 1839.1 32.52 + 1844.0 32.59 + 1848.9 32.66 + 1853.8 32.73 + 1858.6 32.80 + 1863.5 32.87 + 1868.4 32.94 + 1873.3 33.01 + 1878.1 33.08 + 1883.0 33.15 + 1887.9 33.22 + 1892.8 33.29 + 1897.6 33.36 + 1902.5 33.43 + 1907.4 33.50 + 1912.3 33.57 + 1917.1 33.64 + 1922.0 33.71 + 1926.9 33.77 + 1931.8 33.84 + 1936.6 33.91 + 1941.5 33.98 + 1946.4 34.05 + 1951.3 34.12 + 1956.1 34.19 + 1961.0 34.26 + 1965.9 34.33 + 1970.8 34.40 + 1975.6 34.47 + 1980.5 34.54 + 1985.4 34.61 + 1990.3 34.68 + 1995.1 34.75 + 2000.0 34.82 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/005_B_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/005_B_eIMFP.txt new file mode 100644 index 0000000..72c4627 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/005_B_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + B + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 10.81100 + +DENSITY: 2.3400 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.36 + 54.9 5.50 + 59.8 5.59 + 64.6 5.66 + 69.5 5.72 + 74.4 5.78 + 79.3 5.84 + 84.1 5.91 + 89.0 5.99 + 93.9 6.07 + 98.8 6.15 + 103.6 6.23 + 108.5 6.32 + 113.4 6.41 + 118.3 6.51 + 123.1 6.60 + 128.0 6.70 + 132.9 6.80 + 137.8 6.90 + 142.6 7.00 + 147.5 7.11 + 152.4 7.21 + 157.3 7.32 + 162.1 7.42 + 167.0 7.53 + 171.9 7.64 + 176.8 7.74 + 181.6 7.85 + 186.5 7.96 + 191.4 8.07 + 196.3 8.18 + 201.1 8.28 + 206.0 8.39 + 210.9 8.50 + 215.8 8.61 + 220.6 8.72 + 225.5 8.83 + 230.4 8.94 + 235.3 9.05 + 240.1 9.16 + 245.0 9.26 + 249.9 9.37 + 254.8 9.48 + 259.6 9.59 + 264.5 9.70 + 269.4 9.81 + 274.3 9.92 + 279.1 10.03 + 284.0 10.13 + 288.9 10.24 + 293.8 10.35 + 298.6 10.46 + 303.5 10.57 + 308.4 10.67 + 313.3 10.78 + 318.1 10.89 + 323.0 11.00 + 327.9 11.10 + 332.8 11.21 + 337.6 11.32 + 342.5 11.42 + 347.4 11.53 + 352.3 11.64 + 357.1 11.74 + 362.0 11.85 + 366.9 11.95 + 371.8 12.06 + 376.6 12.17 + 381.5 12.27 + 386.4 12.38 + 391.3 12.48 + 396.1 12.59 + 401.0 12.69 + 405.9 12.80 + 410.8 12.90 + 415.6 13.01 + 420.5 13.11 + 425.4 13.22 + 430.3 13.32 + 435.1 13.42 + 440.0 13.53 + 444.9 13.63 + 449.8 13.74 + 454.6 13.84 + 459.5 13.94 + 464.4 14.05 + 469.3 14.15 + 474.1 14.25 + 479.0 14.36 + 483.9 14.46 + 488.8 14.56 + 493.6 14.66 + 498.5 14.77 + 503.4 14.87 + 508.3 14.97 + 513.1 15.07 + 518.0 15.17 + 522.9 15.28 + 527.8 15.38 + 532.6 15.48 + 537.5 15.58 + 542.4 15.68 + 547.3 15.78 + 552.1 15.88 + 557.0 15.99 + 561.9 16.09 + 566.8 16.19 + 571.6 16.29 + 576.5 16.39 + 581.4 16.49 + 586.3 16.59 + 591.1 16.69 + 596.0 16.79 + 600.9 16.89 + 605.8 16.99 + 610.6 17.09 + 615.5 17.19 + 620.4 17.29 + 625.3 17.39 + 630.1 17.49 + 635.0 17.59 + 639.9 17.69 + 644.8 17.78 + 649.6 17.88 + 654.5 17.98 + 659.4 18.08 + 664.3 18.18 + 669.1 18.28 + 674.0 18.38 + 678.9 18.48 + 683.8 18.57 + 688.6 18.67 + 693.5 18.77 + 698.4 18.87 + 703.3 18.97 + 708.1 19.06 + 713.0 19.16 + 717.9 19.26 + 722.8 19.36 + 727.6 19.45 + 732.5 19.55 + 737.4 19.65 + 742.3 19.75 + 747.1 19.84 + 752.0 19.94 + 756.9 20.04 + 761.8 20.13 + 766.6 20.23 + 771.5 20.33 + 776.4 20.42 + 781.3 20.52 + 786.1 20.62 + 791.0 20.71 + 795.9 20.81 + 800.8 20.91 + 805.6 21.00 + 810.5 21.10 + 815.4 21.19 + 820.3 21.29 + 825.1 21.38 + 830.0 21.48 + 834.9 21.58 + 839.8 21.67 + 844.6 21.77 + 849.5 21.86 + 854.4 21.96 + 859.3 22.05 + 864.1 22.15 + 869.0 22.24 + 873.9 22.34 + 878.8 22.43 + 883.6 22.53 + 888.5 22.62 + 893.4 22.72 + 898.3 22.81 + 903.1 22.91 + 908.0 23.00 + 912.9 23.10 + 917.8 23.19 + 922.6 23.28 + 927.5 23.38 + 932.4 23.47 + 937.3 23.57 + 942.1 23.66 + 947.0 23.75 + 951.9 23.85 + 956.8 23.94 + 961.6 24.04 + 966.5 24.13 + 971.4 24.22 + 976.3 24.32 + 981.1 24.41 + 986.0 24.50 + 990.9 24.60 + 995.8 24.69 + 1000.6 24.78 + 1005.5 24.88 + 1010.4 24.97 + 1015.3 25.06 + 1020.1 25.16 + 1025.0 25.25 + 1029.9 25.34 + 1034.8 25.43 + 1039.6 25.53 + 1044.5 25.62 + 1049.4 25.71 + 1054.3 25.81 + 1059.1 25.90 + 1064.0 25.99 + 1068.9 26.08 + 1073.8 26.18 + 1078.6 26.27 + 1083.5 26.36 + 1088.4 26.45 + 1093.3 26.54 + 1098.1 26.64 + 1103.0 26.73 + 1107.9 26.82 + 1112.8 26.91 + 1117.6 27.00 + 1122.5 27.09 + 1127.4 27.19 + 1132.3 27.28 + 1137.1 27.37 + 1142.0 27.46 + 1146.9 27.55 + 1151.8 27.64 + 1156.6 27.74 + 1161.5 27.83 + 1166.4 27.92 + 1171.3 28.01 + 1176.1 28.10 + 1181.0 28.19 + 1185.9 28.28 + 1190.8 28.37 + 1195.6 28.46 + 1200.5 28.56 + 1205.4 28.65 + 1210.3 28.74 + 1215.1 28.83 + 1220.0 28.92 + 1224.9 29.01 + 1229.8 29.10 + 1234.6 29.19 + 1239.5 29.28 + 1244.4 29.37 + 1249.3 29.46 + 1254.1 29.55 + 1259.0 29.64 + 1263.9 29.73 + 1268.8 29.82 + 1273.6 29.91 + 1278.5 30.00 + 1283.4 30.09 + 1288.3 30.18 + 1293.1 30.27 + 1298.0 30.36 + 1302.9 30.45 + 1307.8 30.54 + 1312.6 30.63 + 1317.5 30.72 + 1322.4 30.81 + 1327.3 30.90 + 1332.1 30.99 + 1337.0 31.08 + 1341.9 31.17 + 1346.8 31.26 + 1351.6 31.35 + 1356.5 31.44 + 1361.4 31.53 + 1366.3 31.62 + 1371.1 31.71 + 1376.0 31.79 + 1380.9 31.88 + 1385.8 31.97 + 1390.6 32.06 + 1395.5 32.15 + 1400.4 32.24 + 1405.3 32.33 + 1410.1 32.42 + 1415.0 32.51 + 1419.9 32.60 + 1424.8 32.68 + 1429.6 32.77 + 1434.5 32.86 + 1439.4 32.95 + 1444.3 33.04 + 1449.1 33.13 + 1454.0 33.22 + 1458.9 33.30 + 1463.8 33.39 + 1468.6 33.48 + 1473.5 33.57 + 1478.4 33.66 + 1483.3 33.75 + 1488.1 33.83 + 1493.0 33.92 + 1497.9 34.01 + 1502.8 34.10 + 1507.6 34.19 + 1512.5 34.27 + 1517.4 34.36 + 1522.3 34.45 + 1527.1 34.54 + 1532.0 34.63 + 1536.9 34.71 + 1541.8 34.80 + 1546.6 34.89 + 1551.5 34.98 + 1556.4 35.06 + 1561.3 35.15 + 1566.1 35.24 + 1571.0 35.33 + 1575.9 35.41 + 1580.8 35.50 + 1585.6 35.59 + 1590.5 35.68 + 1595.4 35.76 + 1600.3 35.85 + 1605.1 35.94 + 1610.0 36.03 + 1614.9 36.11 + 1619.8 36.20 + 1624.6 36.29 + 1629.5 36.37 + 1634.4 36.46 + 1639.3 36.55 + 1644.1 36.64 + 1649.0 36.72 + 1653.9 36.81 + 1658.8 36.90 + 1663.6 36.98 + 1668.5 37.07 + 1673.4 37.16 + 1678.3 37.24 + 1683.1 37.33 + 1688.0 37.42 + 1692.9 37.50 + 1697.8 37.59 + 1702.6 37.68 + 1707.5 37.76 + 1712.4 37.85 + 1717.3 37.94 + 1722.1 38.02 + 1727.0 38.11 + 1731.9 38.20 + 1736.8 38.28 + 1741.6 38.37 + 1746.5 38.45 + 1751.4 38.54 + 1756.3 38.63 + 1761.1 38.71 + 1766.0 38.80 + 1770.9 38.89 + 1775.8 38.97 + 1780.6 39.06 + 1785.5 39.14 + 1790.4 39.23 + 1795.3 39.32 + 1800.1 39.40 + 1805.0 39.49 + 1809.9 39.57 + 1814.8 39.66 + 1819.6 39.74 + 1824.5 39.83 + 1829.4 39.92 + 1834.3 40.00 + 1839.1 40.09 + 1844.0 40.17 + 1848.9 40.26 + 1853.8 40.34 + 1858.6 40.43 + 1863.5 40.52 + 1868.4 40.60 + 1873.3 40.69 + 1878.1 40.77 + 1883.0 40.86 + 1887.9 40.94 + 1892.8 41.03 + 1897.6 41.11 + 1902.5 41.20 + 1907.4 41.28 + 1912.3 41.37 + 1917.1 41.45 + 1922.0 41.54 + 1926.9 41.62 + 1931.8 41.71 + 1936.6 41.79 + 1941.5 41.88 + 1946.4 41.96 + 1951.3 42.05 + 1956.1 42.13 + 1961.0 42.22 + 1965.9 42.30 + 1970.8 42.39 + 1975.6 42.47 + 1980.5 42.56 + 1985.4 42.64 + 1990.3 42.73 + 1995.1 42.81 + 2000.0 42.90 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/006_C_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/006_C_eIMFP.txt new file mode 100644 index 0000000..d9e661f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/006_C_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + C + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 12.01070 + +DENSITY: 1.8000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.80 + 54.9 5.75 + 59.8 5.74 + 64.6 5.76 + 69.5 5.80 + 74.4 5.85 + 79.3 5.92 + 84.1 6.00 + 89.0 6.09 + 93.9 6.18 + 98.8 6.28 + 103.6 6.38 + 108.5 6.49 + 113.4 6.60 + 118.3 6.71 + 123.1 6.82 + 128.0 6.94 + 132.9 7.06 + 137.8 7.18 + 142.6 7.30 + 147.5 7.42 + 152.4 7.54 + 157.3 7.66 + 162.1 7.78 + 167.0 7.90 + 171.9 8.02 + 176.8 8.15 + 181.6 8.27 + 186.5 8.39 + 191.4 8.51 + 196.3 8.64 + 201.1 8.76 + 206.0 8.88 + 210.9 9.00 + 215.8 9.13 + 220.6 9.25 + 225.5 9.37 + 230.4 9.49 + 235.3 9.62 + 240.1 9.74 + 245.0 9.86 + 249.9 9.98 + 254.8 10.10 + 259.6 10.22 + 264.5 10.35 + 269.4 10.47 + 274.3 10.59 + 279.1 10.71 + 284.0 10.83 + 288.9 10.95 + 293.8 11.07 + 298.6 11.19 + 303.5 11.31 + 308.4 11.43 + 313.3 11.55 + 318.1 11.66 + 323.0 11.78 + 327.9 11.90 + 332.8 12.02 + 337.6 12.14 + 342.5 12.26 + 347.4 12.37 + 352.3 12.49 + 357.1 12.61 + 362.0 12.73 + 366.9 12.84 + 371.8 12.96 + 376.6 13.08 + 381.5 13.19 + 386.4 13.31 + 391.3 13.42 + 396.1 13.54 + 401.0 13.66 + 405.9 13.77 + 410.8 13.89 + 415.6 14.00 + 420.5 14.12 + 425.4 14.23 + 430.3 14.35 + 435.1 14.46 + 440.0 14.58 + 444.9 14.69 + 449.8 14.80 + 454.6 14.92 + 459.5 15.03 + 464.4 15.14 + 469.3 15.26 + 474.1 15.37 + 479.0 15.48 + 483.9 15.60 + 488.8 15.71 + 493.6 15.82 + 498.5 15.93 + 503.4 16.05 + 508.3 16.16 + 513.1 16.27 + 518.0 16.38 + 522.9 16.49 + 527.8 16.61 + 532.6 16.72 + 537.5 16.83 + 542.4 16.94 + 547.3 17.05 + 552.1 17.16 + 557.0 17.27 + 561.9 17.38 + 566.8 17.49 + 571.6 17.60 + 576.5 17.71 + 581.4 17.82 + 586.3 17.93 + 591.1 18.04 + 596.0 18.15 + 600.9 18.26 + 605.8 18.37 + 610.6 18.48 + 615.5 18.59 + 620.4 18.70 + 625.3 18.81 + 630.1 18.92 + 635.0 19.02 + 639.9 19.13 + 644.8 19.24 + 649.6 19.35 + 654.5 19.46 + 659.4 19.57 + 664.3 19.67 + 669.1 19.78 + 674.0 19.89 + 678.9 20.00 + 683.8 20.10 + 688.6 20.21 + 693.5 20.32 + 698.4 20.43 + 703.3 20.53 + 708.1 20.64 + 713.0 20.75 + 717.9 20.85 + 722.8 20.96 + 727.6 21.07 + 732.5 21.17 + 737.4 21.28 + 742.3 21.39 + 747.1 21.49 + 752.0 21.60 + 756.9 21.70 + 761.8 21.81 + 766.6 21.92 + 771.5 22.02 + 776.4 22.13 + 781.3 22.23 + 786.1 22.34 + 791.0 22.44 + 795.9 22.55 + 800.8 22.65 + 805.6 22.76 + 810.5 22.86 + 815.4 22.97 + 820.3 23.07 + 825.1 23.18 + 830.0 23.28 + 834.9 23.39 + 839.8 23.49 + 844.6 23.59 + 849.5 23.70 + 854.4 23.80 + 859.3 23.91 + 864.1 24.01 + 869.0 24.11 + 873.9 24.22 + 878.8 24.32 + 883.6 24.42 + 888.5 24.53 + 893.4 24.63 + 898.3 24.73 + 903.1 24.84 + 908.0 24.94 + 912.9 25.04 + 917.8 25.15 + 922.6 25.25 + 927.5 25.35 + 932.4 25.46 + 937.3 25.56 + 942.1 25.66 + 947.0 25.76 + 951.9 25.87 + 956.8 25.97 + 961.6 26.07 + 966.5 26.17 + 971.4 26.27 + 976.3 26.38 + 981.1 26.48 + 986.0 26.58 + 990.9 26.68 + 995.8 26.78 + 1000.6 26.89 + 1005.5 26.99 + 1010.4 27.09 + 1015.3 27.19 + 1020.1 27.29 + 1025.0 27.39 + 1029.9 27.49 + 1034.8 27.59 + 1039.6 27.70 + 1044.5 27.80 + 1049.4 27.90 + 1054.3 28.00 + 1059.1 28.10 + 1064.0 28.20 + 1068.9 28.30 + 1073.8 28.40 + 1078.6 28.50 + 1083.5 28.60 + 1088.4 28.70 + 1093.3 28.80 + 1098.1 28.90 + 1103.0 29.00 + 1107.9 29.10 + 1112.8 29.20 + 1117.6 29.30 + 1122.5 29.40 + 1127.4 29.50 + 1132.3 29.60 + 1137.1 29.70 + 1142.0 29.80 + 1146.9 29.90 + 1151.8 30.00 + 1156.6 30.10 + 1161.5 30.20 + 1166.4 30.30 + 1171.3 30.40 + 1176.1 30.50 + 1181.0 30.60 + 1185.9 30.70 + 1190.8 30.80 + 1195.6 30.90 + 1200.5 31.00 + 1205.4 31.10 + 1210.3 31.19 + 1215.1 31.29 + 1220.0 31.39 + 1224.9 31.49 + 1229.8 31.59 + 1234.6 31.69 + 1239.5 31.79 + 1244.4 31.88 + 1249.3 31.98 + 1254.1 32.08 + 1259.0 32.18 + 1263.9 32.28 + 1268.8 32.38 + 1273.6 32.47 + 1278.5 32.57 + 1283.4 32.67 + 1288.3 32.77 + 1293.1 32.87 + 1298.0 32.96 + 1302.9 33.06 + 1307.8 33.16 + 1312.6 33.26 + 1317.5 33.36 + 1322.4 33.45 + 1327.3 33.55 + 1332.1 33.65 + 1337.0 33.75 + 1341.9 33.84 + 1346.8 33.94 + 1351.6 34.04 + 1356.5 34.14 + 1361.4 34.23 + 1366.3 34.33 + 1371.1 34.43 + 1376.0 34.52 + 1380.9 34.62 + 1385.8 34.72 + 1390.6 34.82 + 1395.5 34.91 + 1400.4 35.01 + 1405.3 35.11 + 1410.1 35.20 + 1415.0 35.30 + 1419.9 35.40 + 1424.8 35.49 + 1429.6 35.59 + 1434.5 35.69 + 1439.4 35.78 + 1444.3 35.88 + 1449.1 35.98 + 1454.0 36.07 + 1458.9 36.17 + 1463.8 36.26 + 1468.6 36.36 + 1473.5 36.46 + 1478.4 36.55 + 1483.3 36.65 + 1488.1 36.74 + 1493.0 36.84 + 1497.9 36.94 + 1502.8 37.03 + 1507.6 37.13 + 1512.5 37.22 + 1517.4 37.32 + 1522.3 37.42 + 1527.1 37.51 + 1532.0 37.61 + 1536.9 37.70 + 1541.8 37.80 + 1546.6 37.89 + 1551.5 37.99 + 1556.4 38.08 + 1561.3 38.18 + 1566.1 38.28 + 1571.0 38.37 + 1575.9 38.47 + 1580.8 38.56 + 1585.6 38.66 + 1590.5 38.75 + 1595.4 38.85 + 1600.3 38.94 + 1605.1 39.04 + 1610.0 39.13 + 1614.9 39.23 + 1619.8 39.32 + 1624.6 39.42 + 1629.5 39.51 + 1634.4 39.61 + 1639.3 39.70 + 1644.1 39.79 + 1649.0 39.89 + 1653.9 39.98 + 1658.8 40.08 + 1663.6 40.17 + 1668.5 40.27 + 1673.4 40.36 + 1678.3 40.46 + 1683.1 40.55 + 1688.0 40.65 + 1692.9 40.74 + 1697.8 40.83 + 1702.6 40.93 + 1707.5 41.02 + 1712.4 41.12 + 1717.3 41.21 + 1722.1 41.30 + 1727.0 41.40 + 1731.9 41.49 + 1736.8 41.59 + 1741.6 41.68 + 1746.5 41.77 + 1751.4 41.87 + 1756.3 41.96 + 1761.1 42.06 + 1766.0 42.15 + 1770.9 42.24 + 1775.8 42.34 + 1780.6 42.43 + 1785.5 42.52 + 1790.4 42.62 + 1795.3 42.71 + 1800.1 42.80 + 1805.0 42.90 + 1809.9 42.99 + 1814.8 43.08 + 1819.6 43.18 + 1824.5 43.27 + 1829.4 43.36 + 1834.3 43.46 + 1839.1 43.55 + 1844.0 43.64 + 1848.9 43.74 + 1853.8 43.83 + 1858.6 43.92 + 1863.5 44.02 + 1868.4 44.11 + 1873.3 44.20 + 1878.1 44.29 + 1883.0 44.39 + 1887.9 44.48 + 1892.8 44.57 + 1897.6 44.67 + 1902.5 44.76 + 1907.4 44.85 + 1912.3 44.94 + 1917.1 45.04 + 1922.0 45.13 + 1926.9 45.22 + 1931.8 45.31 + 1936.6 45.41 + 1941.5 45.50 + 1946.4 45.59 + 1951.3 45.68 + 1956.1 45.78 + 1961.0 45.87 + 1965.9 45.96 + 1970.8 46.05 + 1975.6 46.15 + 1980.5 46.24 + 1985.4 46.33 + 1990.3 46.42 + 1995.1 46.51 + 2000.0 46.61 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/011_Na_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/011_Na_eIMFP.txt new file mode 100644 index 0000000..e08bf03 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/011_Na_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Na + +SOURCE: + Tanuma, Powell and Penn + Unpublished data + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 22.98977 + +DENSITY: 0.9700 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.95 + 54.9 5.27 + 59.8 5.56 + 64.6 5.83 + 69.5 6.09 + 74.4 6.34 + 79.3 6.58 + 84.1 6.81 + 89.0 7.05 + 93.9 7.27 + 98.8 7.50 + 103.6 7.72 + 108.5 7.94 + 113.4 8.16 + 118.3 8.37 + 123.1 8.59 + 128.0 8.80 + 132.9 9.01 + 137.8 9.22 + 142.6 9.43 + 147.5 9.64 + 152.4 9.85 + 157.3 10.05 + 162.1 10.26 + 167.0 10.46 + 171.9 10.66 + 176.8 10.87 + 181.6 11.07 + 186.5 11.27 + 191.4 11.47 + 196.3 11.67 + 201.1 11.87 + 206.0 12.06 + 210.9 12.26 + 215.8 12.46 + 220.6 12.65 + 225.5 12.85 + 230.4 13.04 + 235.3 13.24 + 240.1 13.43 + 245.0 13.63 + 249.9 13.82 + 254.8 14.01 + 259.6 14.20 + 264.5 14.39 + 269.4 14.58 + 274.3 14.77 + 279.1 14.96 + 284.0 15.15 + 288.9 15.34 + 293.8 15.53 + 298.6 15.72 + 303.5 15.90 + 308.4 16.09 + 313.3 16.28 + 318.1 16.46 + 323.0 16.65 + 327.9 16.83 + 332.8 17.02 + 337.6 17.20 + 342.5 17.39 + 347.4 17.57 + 352.3 17.75 + 357.1 17.94 + 362.0 18.12 + 366.9 18.30 + 371.8 18.48 + 376.6 18.66 + 381.5 18.85 + 386.4 19.03 + 391.3 19.21 + 396.1 19.39 + 401.0 19.57 + 405.9 19.75 + 410.8 19.93 + 415.6 20.11 + 420.5 20.28 + 425.4 20.46 + 430.3 20.64 + 435.1 20.82 + 440.0 21.00 + 444.9 21.17 + 449.8 21.35 + 454.6 21.53 + 459.5 21.70 + 464.4 21.88 + 469.3 22.05 + 474.1 22.23 + 479.0 22.41 + 483.9 22.58 + 488.8 22.76 + 493.6 22.93 + 498.5 23.10 + 503.4 23.28 + 508.3 23.45 + 513.1 23.63 + 518.0 23.80 + 522.9 23.97 + 527.8 24.15 + 532.6 24.32 + 537.5 24.49 + 542.4 24.66 + 547.3 24.84 + 552.1 25.01 + 557.0 25.18 + 561.9 25.35 + 566.8 25.52 + 571.6 25.69 + 576.5 25.86 + 581.4 26.03 + 586.3 26.20 + 591.1 26.37 + 596.0 26.54 + 600.9 26.71 + 605.8 26.88 + 610.6 27.05 + 615.5 27.22 + 620.4 27.39 + 625.3 27.56 + 630.1 27.73 + 635.0 27.90 + 639.9 28.06 + 644.8 28.23 + 649.6 28.40 + 654.5 28.57 + 659.4 28.74 + 664.3 28.90 + 669.1 29.07 + 674.0 29.24 + 678.9 29.40 + 683.8 29.57 + 688.6 29.74 + 693.5 29.90 + 698.4 30.07 + 703.3 30.24 + 708.1 30.40 + 713.0 30.57 + 717.9 30.73 + 722.8 30.90 + 727.6 31.06 + 732.5 31.23 + 737.4 31.39 + 742.3 31.56 + 747.1 31.72 + 752.0 31.89 + 756.9 32.05 + 761.8 32.22 + 766.6 32.38 + 771.5 32.54 + 776.4 32.71 + 781.3 32.87 + 786.1 33.03 + 791.0 33.20 + 795.9 33.36 + 800.8 33.52 + 805.6 33.69 + 810.5 33.85 + 815.4 34.01 + 820.3 34.17 + 825.1 34.34 + 830.0 34.50 + 834.9 34.66 + 839.8 34.82 + 844.6 34.99 + 849.5 35.15 + 854.4 35.31 + 859.3 35.47 + 864.1 35.63 + 869.0 35.79 + 873.9 35.95 + 878.8 36.11 + 883.6 36.27 + 888.5 36.44 + 893.4 36.60 + 898.3 36.76 + 903.1 36.92 + 908.0 37.08 + 912.9 37.24 + 917.8 37.40 + 922.6 37.56 + 927.5 37.72 + 932.4 37.88 + 937.3 38.04 + 942.1 38.20 + 947.0 38.35 + 951.9 38.51 + 956.8 38.67 + 961.6 38.83 + 966.5 38.99 + 971.4 39.15 + 976.3 39.31 + 981.1 39.47 + 986.0 39.62 + 990.9 39.78 + 995.8 39.94 + 1000.6 40.10 + 1005.5 40.26 + 1010.4 40.41 + 1015.3 40.57 + 1020.1 40.73 + 1025.0 40.89 + 1029.9 41.05 + 1034.8 41.20 + 1039.6 41.36 + 1044.5 41.52 + 1049.4 41.67 + 1054.3 41.83 + 1059.1 41.99 + 1064.0 42.14 + 1068.9 42.30 + 1073.8 42.46 + 1078.6 42.61 + 1083.5 42.77 + 1088.4 42.93 + 1093.3 43.08 + 1098.1 43.24 + 1103.0 43.39 + 1107.9 43.55 + 1112.8 43.71 + 1117.6 43.86 + 1122.5 44.02 + 1127.4 44.17 + 1132.3 44.33 + 1137.1 44.48 + 1142.0 44.64 + 1146.9 44.79 + 1151.8 44.95 + 1156.6 45.10 + 1161.5 45.26 + 1166.4 45.41 + 1171.3 45.57 + 1176.1 45.72 + 1181.0 45.88 + 1185.9 46.03 + 1190.8 46.19 + 1195.6 46.34 + 1200.5 46.49 + 1205.4 46.65 + 1210.3 46.80 + 1215.1 46.96 + 1220.0 47.11 + 1224.9 47.26 + 1229.8 47.42 + 1234.6 47.57 + 1239.5 47.73 + 1244.4 47.88 + 1249.3 48.03 + 1254.1 48.19 + 1259.0 48.34 + 1263.9 48.49 + 1268.8 48.64 + 1273.6 48.80 + 1278.5 48.95 + 1283.4 49.10 + 1288.3 49.26 + 1293.1 49.41 + 1298.0 49.56 + 1302.9 49.71 + 1307.8 49.87 + 1312.6 50.02 + 1317.5 50.17 + 1322.4 50.32 + 1327.3 50.47 + 1332.1 50.63 + 1337.0 50.78 + 1341.9 50.93 + 1346.8 51.08 + 1351.6 51.23 + 1356.5 51.39 + 1361.4 51.54 + 1366.3 51.69 + 1371.1 51.84 + 1376.0 51.99 + 1380.9 52.14 + 1385.8 52.29 + 1390.6 52.45 + 1395.5 52.60 + 1400.4 52.75 + 1405.3 52.90 + 1410.1 53.05 + 1415.0 53.20 + 1419.9 53.35 + 1424.8 53.50 + 1429.6 53.65 + 1434.5 53.80 + 1439.4 53.95 + 1444.3 54.10 + 1449.1 54.25 + 1454.0 54.40 + 1458.9 54.55 + 1463.8 54.70 + 1468.6 54.85 + 1473.5 55.00 + 1478.4 55.15 + 1483.3 55.30 + 1488.1 55.45 + 1493.0 55.60 + 1497.9 55.75 + 1502.8 55.90 + 1507.6 56.05 + 1512.5 56.20 + 1517.4 56.35 + 1522.3 56.50 + 1527.1 56.65 + 1532.0 56.80 + 1536.9 56.95 + 1541.8 57.10 + 1546.6 57.25 + 1551.5 57.40 + 1556.4 57.54 + 1561.3 57.69 + 1566.1 57.84 + 1571.0 57.99 + 1575.9 58.14 + 1580.8 58.29 + 1585.6 58.44 + 1590.5 58.59 + 1595.4 58.73 + 1600.3 58.88 + 1605.1 59.03 + 1610.0 59.18 + 1614.9 59.33 + 1619.8 59.48 + 1624.6 59.62 + 1629.5 59.77 + 1634.4 59.92 + 1639.3 60.07 + 1644.1 60.21 + 1649.0 60.36 + 1653.9 60.51 + 1658.8 60.66 + 1663.6 60.81 + 1668.5 60.95 + 1673.4 61.10 + 1678.3 61.25 + 1683.1 61.40 + 1688.0 61.54 + 1692.9 61.69 + 1697.8 61.84 + 1702.6 61.98 + 1707.5 62.13 + 1712.4 62.28 + 1717.3 62.43 + 1722.1 62.57 + 1727.0 62.72 + 1731.9 62.87 + 1736.8 63.01 + 1741.6 63.16 + 1746.5 63.31 + 1751.4 63.45 + 1756.3 63.60 + 1761.1 63.75 + 1766.0 63.89 + 1770.9 64.04 + 1775.8 64.19 + 1780.6 64.33 + 1785.5 64.48 + 1790.4 64.62 + 1795.3 64.77 + 1800.1 64.92 + 1805.0 65.06 + 1809.9 65.21 + 1814.8 65.35 + 1819.6 65.50 + 1824.5 65.65 + 1829.4 65.79 + 1834.3 65.94 + 1839.1 66.08 + 1844.0 66.23 + 1848.9 66.37 + 1853.8 66.52 + 1858.6 66.67 + 1863.5 66.81 + 1868.4 66.96 + 1873.3 67.10 + 1878.1 67.25 + 1883.0 67.39 + 1887.9 67.54 + 1892.8 67.68 + 1897.6 67.83 + 1902.5 67.97 + 1907.4 68.12 + 1912.3 68.26 + 1917.1 68.41 + 1922.0 68.55 + 1926.9 68.70 + 1931.8 68.84 + 1936.6 68.99 + 1941.5 69.13 + 1946.4 69.28 + 1951.3 69.42 + 1956.1 69.57 + 1961.0 69.71 + 1965.9 69.85 + 1970.8 70.00 + 1975.6 70.14 + 1980.5 70.29 + 1985.4 70.43 + 1990.3 70.58 + 1995.1 70.72 + 2000.0 70.86 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/012_Mg_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/012_Mg_eIMFP.txt new file mode 100644 index 0000000..4b9b4d0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/012_Mg_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Mg + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 24.30500 + +DENSITY: 1.7400 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 3.89 + 54.9 4.09 + 59.8 4.27 + 64.6 4.43 + 69.5 4.58 + 74.4 4.72 + 79.3 4.86 + 84.1 5.00 + 89.0 5.14 + 93.9 5.27 + 98.8 5.41 + 103.6 5.54 + 108.5 5.67 + 113.4 5.81 + 118.3 5.94 + 123.1 6.07 + 128.0 6.20 + 132.9 6.33 + 137.8 6.46 + 142.6 6.59 + 147.5 6.72 + 152.4 6.84 + 157.3 6.97 + 162.1 7.10 + 167.0 7.23 + 171.9 7.35 + 176.8 7.48 + 181.6 7.61 + 186.5 7.73 + 191.4 7.86 + 196.3 7.98 + 201.1 8.11 + 206.0 8.23 + 210.9 8.36 + 215.8 8.48 + 220.6 8.60 + 225.5 8.73 + 230.4 8.85 + 235.3 8.97 + 240.1 9.09 + 245.0 9.21 + 249.9 9.34 + 254.8 9.46 + 259.6 9.58 + 264.5 9.70 + 269.4 9.82 + 274.3 9.94 + 279.1 10.06 + 284.0 10.18 + 288.9 10.30 + 293.8 10.42 + 298.6 10.54 + 303.5 10.65 + 308.4 10.77 + 313.3 10.89 + 318.1 11.01 + 323.0 11.12 + 327.9 11.24 + 332.8 11.36 + 337.6 11.48 + 342.5 11.59 + 347.4 11.71 + 352.3 11.82 + 357.1 11.94 + 362.0 12.06 + 366.9 12.17 + 371.8 12.29 + 376.6 12.40 + 381.5 12.52 + 386.4 12.63 + 391.3 12.74 + 396.1 12.86 + 401.0 12.97 + 405.9 13.09 + 410.8 13.20 + 415.6 13.31 + 420.5 13.43 + 425.4 13.54 + 430.3 13.65 + 435.1 13.76 + 440.0 13.88 + 444.9 13.99 + 449.8 14.10 + 454.6 14.21 + 459.5 14.32 + 464.4 14.43 + 469.3 14.55 + 474.1 14.66 + 479.0 14.77 + 483.9 14.88 + 488.8 14.99 + 493.6 15.10 + 498.5 15.21 + 503.4 15.32 + 508.3 15.43 + 513.1 15.54 + 518.0 15.65 + 522.9 15.76 + 527.8 15.87 + 532.6 15.98 + 537.5 16.09 + 542.4 16.20 + 547.3 16.30 + 552.1 16.41 + 557.0 16.52 + 561.9 16.63 + 566.8 16.74 + 571.6 16.85 + 576.5 16.95 + 581.4 17.06 + 586.3 17.17 + 591.1 17.28 + 596.0 17.39 + 600.9 17.49 + 605.8 17.60 + 610.6 17.71 + 615.5 17.81 + 620.4 17.92 + 625.3 18.03 + 630.1 18.13 + 635.0 18.24 + 639.9 18.35 + 644.8 18.45 + 649.6 18.56 + 654.5 18.66 + 659.4 18.77 + 664.3 18.88 + 669.1 18.98 + 674.0 19.09 + 678.9 19.19 + 683.8 19.30 + 688.6 19.40 + 693.5 19.51 + 698.4 19.61 + 703.3 19.72 + 708.1 19.82 + 713.0 19.93 + 717.9 20.03 + 722.8 20.14 + 727.6 20.24 + 732.5 20.34 + 737.4 20.45 + 742.3 20.55 + 747.1 20.66 + 752.0 20.76 + 756.9 20.86 + 761.8 20.97 + 766.6 21.07 + 771.5 21.18 + 776.4 21.28 + 781.3 21.38 + 786.1 21.48 + 791.0 21.59 + 795.9 21.69 + 800.8 21.79 + 805.6 21.90 + 810.5 22.00 + 815.4 22.10 + 820.3 22.20 + 825.1 22.31 + 830.0 22.41 + 834.9 22.51 + 839.8 22.61 + 844.6 22.72 + 849.5 22.82 + 854.4 22.92 + 859.3 23.02 + 864.1 23.12 + 869.0 23.22 + 873.9 23.33 + 878.8 23.43 + 883.6 23.53 + 888.5 23.63 + 893.4 23.73 + 898.3 23.83 + 903.1 23.93 + 908.0 24.03 + 912.9 24.14 + 917.8 24.24 + 922.6 24.34 + 927.5 24.44 + 932.4 24.54 + 937.3 24.64 + 942.1 24.74 + 947.0 24.84 + 951.9 24.94 + 956.8 25.04 + 961.6 25.14 + 966.5 25.24 + 971.4 25.34 + 976.3 25.44 + 981.1 25.54 + 986.0 25.64 + 990.9 25.74 + 995.8 25.84 + 1000.6 25.94 + 1005.5 26.04 + 1010.4 26.14 + 1015.3 26.24 + 1020.1 26.34 + 1025.0 26.44 + 1029.9 26.54 + 1034.8 26.63 + 1039.6 26.73 + 1044.5 26.83 + 1049.4 26.93 + 1054.3 27.03 + 1059.1 27.13 + 1064.0 27.23 + 1068.9 27.33 + 1073.8 27.43 + 1078.6 27.52 + 1083.5 27.62 + 1088.4 27.72 + 1093.3 27.82 + 1098.1 27.92 + 1103.0 28.02 + 1107.9 28.11 + 1112.8 28.21 + 1117.6 28.31 + 1122.5 28.41 + 1127.4 28.51 + 1132.3 28.60 + 1137.1 28.70 + 1142.0 28.80 + 1146.9 28.90 + 1151.8 28.99 + 1156.6 29.09 + 1161.5 29.19 + 1166.4 29.29 + 1171.3 29.38 + 1176.1 29.48 + 1181.0 29.58 + 1185.9 29.68 + 1190.8 29.77 + 1195.6 29.87 + 1200.5 29.97 + 1205.4 30.06 + 1210.3 30.16 + 1215.1 30.26 + 1220.0 30.35 + 1224.9 30.45 + 1229.8 30.55 + 1234.6 30.64 + 1239.5 30.74 + 1244.4 30.84 + 1249.3 30.93 + 1254.1 31.03 + 1259.0 31.13 + 1263.9 31.22 + 1268.8 31.32 + 1273.6 31.41 + 1278.5 31.51 + 1283.4 31.61 + 1288.3 31.70 + 1293.1 31.80 + 1298.0 31.89 + 1302.9 31.99 + 1307.8 32.09 + 1312.6 32.18 + 1317.5 32.28 + 1322.4 32.37 + 1327.3 32.47 + 1332.1 32.57 + 1337.0 32.66 + 1341.9 32.76 + 1346.8 32.85 + 1351.6 32.95 + 1356.5 33.04 + 1361.4 33.14 + 1366.3 33.23 + 1371.1 33.33 + 1376.0 33.42 + 1380.9 33.52 + 1385.8 33.61 + 1390.6 33.71 + 1395.5 33.80 + 1400.4 33.90 + 1405.3 33.99 + 1410.1 34.09 + 1415.0 34.18 + 1419.9 34.28 + 1424.8 34.37 + 1429.6 34.47 + 1434.5 34.56 + 1439.4 34.66 + 1444.3 34.75 + 1449.1 34.84 + 1454.0 34.94 + 1458.9 35.03 + 1463.8 35.13 + 1468.6 35.22 + 1473.5 35.32 + 1478.4 35.41 + 1483.3 35.50 + 1488.1 35.60 + 1493.0 35.69 + 1497.9 35.79 + 1502.8 35.88 + 1507.6 35.97 + 1512.5 36.07 + 1517.4 36.16 + 1522.3 36.26 + 1527.1 36.35 + 1532.0 36.44 + 1536.9 36.54 + 1541.8 36.63 + 1546.6 36.72 + 1551.5 36.82 + 1556.4 36.91 + 1561.3 37.00 + 1566.1 37.10 + 1571.0 37.19 + 1575.9 37.29 + 1580.8 37.38 + 1585.6 37.47 + 1590.5 37.56 + 1595.4 37.66 + 1600.3 37.75 + 1605.1 37.84 + 1610.0 37.94 + 1614.9 38.03 + 1619.8 38.12 + 1624.6 38.22 + 1629.5 38.31 + 1634.4 38.40 + 1639.3 38.49 + 1644.1 38.59 + 1649.0 38.68 + 1653.9 38.77 + 1658.8 38.87 + 1663.6 38.96 + 1668.5 39.05 + 1673.4 39.14 + 1678.3 39.24 + 1683.1 39.33 + 1688.0 39.42 + 1692.9 39.51 + 1697.8 39.61 + 1702.6 39.70 + 1707.5 39.79 + 1712.4 39.88 + 1717.3 39.98 + 1722.1 40.07 + 1727.0 40.16 + 1731.9 40.25 + 1736.8 40.34 + 1741.6 40.44 + 1746.5 40.53 + 1751.4 40.62 + 1756.3 40.71 + 1761.1 40.80 + 1766.0 40.90 + 1770.9 40.99 + 1775.8 41.08 + 1780.6 41.17 + 1785.5 41.26 + 1790.4 41.35 + 1795.3 41.45 + 1800.1 41.54 + 1805.0 41.63 + 1809.9 41.72 + 1814.8 41.81 + 1819.6 41.90 + 1824.5 42.00 + 1829.4 42.09 + 1834.3 42.18 + 1839.1 42.27 + 1844.0 42.36 + 1848.9 42.45 + 1853.8 42.54 + 1858.6 42.63 + 1863.5 42.73 + 1868.4 42.82 + 1873.3 42.91 + 1878.1 43.00 + 1883.0 43.09 + 1887.9 43.18 + 1892.8 43.27 + 1897.6 43.36 + 1902.5 43.45 + 1907.4 43.55 + 1912.3 43.64 + 1917.1 43.73 + 1922.0 43.82 + 1926.9 43.91 + 1931.8 44.00 + 1936.6 44.09 + 1941.5 44.18 + 1946.4 44.27 + 1951.3 44.36 + 1956.1 44.45 + 1961.0 44.54 + 1965.9 44.63 + 1970.8 44.72 + 1975.6 44.81 + 1980.5 44.90 + 1985.4 45.00 + 1990.3 45.09 + 1995.1 45.18 + 2000.0 45.27 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/013_Al_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/013_Al_1_eIMFP.txt new file mode 100644 index 0000000..ebab039 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/013_Al_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Al + +SOURCE: + Ashley + J. Electron Spectrosc. 50 (1990) 323; J. C. Ashley, Private communication + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 26.98154 + +DENSITY: 2.7000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 40.0 4.77 + 64.9 4.93 + 89.8 5.27 + 114.7 5.69 + 139.6 6.14 + 164.5 6.60 + 189.4 7.07 + 214.3 7.55 + 239.2 8.03 + 264.1 8.50 + 289.0 8.98 + 313.9 9.45 + 338.8 9.92 + 363.7 10.38 + 388.6 10.85 + 413.5 11.31 + 438.4 11.77 + 463.3 12.23 + 488.2 12.68 + 513.1 13.13 + 538.0 13.58 + 562.9 14.03 + 587.8 14.47 + 612.7 14.91 + 637.6 15.35 + 662.5 15.79 + 687.4 16.22 + 712.3 16.65 + 737.2 17.08 + 762.1 17.51 + 787.0 17.94 + 811.9 18.36 + 836.8 18.78 + 861.7 19.20 + 886.6 19.62 + 911.5 20.04 + 936.4 20.45 + 961.3 20.87 + 986.2 21.28 + 1011.1 21.69 + 1036.0 22.10 + 1060.9 22.51 + 1085.8 22.91 + 1110.7 23.32 + 1135.6 23.72 + 1160.5 24.12 + 1185.4 24.52 + 1210.3 24.92 + 1235.2 25.32 + 1260.1 25.71 + 1285.0 26.11 + 1309.9 26.50 + 1334.8 26.90 + 1359.7 27.29 + 1384.6 27.68 + 1409.5 28.07 + 1434.4 28.45 + 1459.3 28.84 + 1484.2 29.23 + 1509.1 29.61 + 1534.0 30.00 + 1558.9 30.38 + 1583.8 30.76 + 1608.7 31.14 + 1633.6 31.52 + 1658.5 31.90 + 1683.4 32.28 + 1708.3 32.66 + 1733.2 33.03 + 1758.1 33.41 + 1783.0 33.78 + 1807.9 34.16 + 1832.8 34.53 + 1857.7 34.90 + 1882.6 35.27 + 1907.5 35.64 + 1932.4 36.01 + 1957.3 36.38 + 1982.2 36.75 + 2007.1 37.11 + 2032.0 37.48 + 2056.9 37.85 + 2081.8 38.21 + 2106.7 38.57 + 2131.6 38.94 + 2156.5 39.30 + 2181.4 39.66 + 2206.3 40.02 + 2231.2 40.38 + 2256.1 40.74 + 2281.0 41.10 + 2305.9 41.46 + 2330.8 41.82 + 2355.7 42.18 + 2380.6 42.53 + 2405.5 42.89 + 2430.4 43.24 + 2455.3 43.60 + 2480.2 43.95 + 2505.1 44.31 + 2530.0 44.66 + 2554.9 45.01 + 2579.8 45.36 + 2604.7 45.72 + 2629.6 46.07 + 2654.5 46.42 + 2679.4 46.77 + 2704.3 47.11 + 2729.2 47.46 + 2754.1 47.81 + 2779.0 48.16 + 2803.9 48.50 + 2828.8 48.85 + 2853.7 49.20 + 2878.6 49.54 + 2903.5 49.89 + 2928.4 50.23 + 2953.3 50.57 + 2978.2 50.92 + 3003.1 51.26 + 3028.0 51.60 + 3052.9 51.94 + 3077.8 52.28 + 3102.7 52.62 + 3127.6 52.96 + 3152.5 53.30 + 3177.4 53.64 + 3202.3 53.98 + 3227.2 54.32 + 3252.1 54.66 + 3277.0 55.00 + 3301.9 55.33 + 3326.8 55.67 + 3351.7 56.01 + 3376.6 56.34 + 3401.5 56.68 + 3426.4 57.01 + 3451.3 57.35 + 3476.2 57.68 + 3501.1 58.01 + 3526.0 58.35 + 3550.9 58.68 + 3575.8 59.01 + 3600.7 59.34 + 3625.6 59.68 + 3650.5 60.01 + 3675.4 60.34 + 3700.3 60.67 + 3725.2 61.00 + 3750.1 61.33 + 3775.0 61.66 + 3799.9 61.99 + 3824.8 62.31 + 3849.7 62.64 + 3874.6 62.97 + 3899.5 63.30 + 3924.4 63.62 + 3949.3 63.95 + 3974.2 64.28 + 3999.1 64.60 + 4024.0 64.93 + 4048.9 65.25 + 4073.8 65.58 + 4098.7 65.90 + 4123.6 66.23 + 4148.5 66.55 + 4173.4 66.88 + 4198.3 67.20 + 4223.2 67.52 + 4248.1 67.84 + 4273.0 68.17 + 4297.9 68.49 + 4322.8 68.81 + 4347.7 69.13 + 4372.6 69.45 + 4397.5 69.77 + 4422.4 70.09 + 4447.3 70.41 + 4472.2 70.73 + 4497.1 71.05 + 4522.0 71.37 + 4546.9 71.69 + 4571.8 72.01 + 4596.7 72.33 + 4621.6 72.64 + 4646.5 72.96 + 4671.4 73.28 + 4696.3 73.59 + 4721.2 73.91 + 4746.1 74.23 + 4771.0 74.54 + 4795.9 74.86 + 4820.8 75.17 + 4845.7 75.49 + 4870.6 75.81 + 4895.5 76.12 + 4920.4 76.43 + 4945.3 76.75 + 4970.2 77.06 + 4995.1 77.38 + 5020.0 77.69 + 5044.9 78.00 + 5069.8 78.31 + 5094.7 78.63 + 5119.6 78.94 + 5144.5 79.25 + 5169.4 79.56 + 5194.3 79.87 + 5219.2 80.18 + 5244.1 80.50 + 5269.0 80.81 + 5293.9 81.12 + 5318.8 81.43 + 5343.7 81.74 + 5368.6 82.05 + 5393.5 82.35 + 5418.4 82.66 + 5443.3 82.97 + 5468.2 83.28 + 5493.1 83.59 + 5518.0 83.90 + 5542.9 84.20 + 5567.8 84.51 + 5592.7 84.82 + 5617.6 85.13 + 5642.5 85.43 + 5667.4 85.74 + 5692.3 86.05 + 5717.2 86.35 + 5742.1 86.66 + 5767.0 86.96 + 5791.9 87.27 + 5816.8 87.57 + 5841.7 87.88 + 5866.6 88.18 + 5891.5 88.49 + 5916.4 88.79 + 5941.3 89.10 + 5966.2 89.40 + 5991.1 89.70 + 6016.0 90.01 + 6040.9 90.31 + 6065.8 90.61 + 6090.7 90.92 + 6115.6 91.22 + 6140.5 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110.46 + 7759.0 110.75 + 7783.9 111.04 + 7808.8 111.32 + 7833.7 111.61 + 7858.6 111.90 + 7883.5 112.19 + 7908.4 112.48 + 7933.3 112.77 + 7958.2 113.06 + 7983.1 113.35 + 8008.0 113.64 + 8032.9 113.92 + 8057.8 114.21 + 8082.7 114.50 + 8107.6 114.79 + 8132.5 115.08 + 8157.4 115.36 + 8182.3 115.65 + 8207.2 115.94 + 8232.1 116.22 + 8257.0 116.51 + 8281.9 116.80 + 8306.8 117.08 + 8331.7 117.37 + 8356.6 117.66 + 8381.5 117.94 + 8406.4 118.23 + 8431.3 118.51 + 8456.2 118.80 + 8481.1 119.09 + 8506.0 119.37 + 8530.9 119.66 + 8555.8 119.94 + 8580.7 120.23 + 8605.6 120.51 + 8630.5 120.80 + 8655.4 121.08 + 8680.3 121.36 + 8705.2 121.65 + 8730.1 121.93 + 8755.0 122.22 + 8779.9 122.50 + 8804.8 122.78 + 8829.7 123.07 + 8854.6 123.35 + 8879.5 123.63 + 8904.4 123.92 + 8929.3 124.20 + 8954.2 124.48 + 8979.1 124.76 + 9004.0 125.05 + 9028.9 125.33 + 9053.8 125.61 + 9078.7 125.89 + 9103.6 126.18 + 9128.5 126.46 + 9153.4 126.74 + 9178.3 127.02 + 9203.2 127.30 + 9228.1 127.58 + 9253.0 127.86 + 9277.9 128.14 + 9302.8 128.43 + 9327.7 128.71 + 9352.6 128.99 + 9377.5 129.27 + 9402.4 129.55 + 9427.3 129.83 + 9452.2 130.11 + 9477.1 130.39 + 9502.0 130.67 + 9526.9 130.95 + 9551.8 131.23 + 9576.7 131.51 + 9601.6 131.78 + 9626.5 132.06 + 9651.4 132.34 + 9676.3 132.62 + 9701.2 132.90 + 9726.1 133.18 + 9751.0 133.46 + 9775.9 133.74 + 9800.8 134.01 + 9825.7 134.29 + 9850.6 134.57 + 9875.5 134.85 + 9900.4 135.13 + 9925.3 135.40 + 9950.2 135.68 + 9975.1 135.96 + 10000.0 136.23 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/013_Al_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/013_Al_2_eIMFP.txt new file mode 100644 index 0000000..28f3b90 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/013_Al_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Al + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 26.98154 + +DENSITY: 2.7000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 3.17 + 54.9 3.27 + 59.8 3.37 + 64.6 3.47 + 69.5 3.57 + 74.4 3.67 + 79.3 3.77 + 84.1 3.87 + 89.0 3.97 + 93.9 4.07 + 98.8 4.17 + 103.6 4.28 + 108.5 4.38 + 113.4 4.48 + 118.3 4.58 + 123.1 4.68 + 128.0 4.78 + 132.9 4.88 + 137.8 4.98 + 142.6 5.07 + 147.5 5.17 + 152.4 5.27 + 157.3 5.37 + 162.1 5.47 + 167.0 5.56 + 171.9 5.66 + 176.8 5.76 + 181.6 5.86 + 186.5 5.95 + 191.4 6.05 + 196.3 6.14 + 201.1 6.24 + 206.0 6.33 + 210.9 6.43 + 215.8 6.52 + 220.6 6.62 + 225.5 6.71 + 230.4 6.80 + 235.3 6.90 + 240.1 6.99 + 245.0 7.08 + 249.9 7.17 + 254.8 7.27 + 259.6 7.36 + 264.5 7.45 + 269.4 7.54 + 274.3 7.63 + 279.1 7.72 + 284.0 7.81 + 288.9 7.90 + 293.8 7.99 + 298.6 8.08 + 303.5 8.17 + 308.4 8.26 + 313.3 8.35 + 318.1 8.44 + 323.0 8.53 + 327.9 8.62 + 332.8 8.71 + 337.6 8.80 + 342.5 8.88 + 347.4 8.97 + 352.3 9.06 + 357.1 9.15 + 362.0 9.23 + 366.9 9.32 + 371.8 9.41 + 376.6 9.49 + 381.5 9.58 + 386.4 9.67 + 391.3 9.75 + 396.1 9.84 + 401.0 9.93 + 405.9 10.01 + 410.8 10.10 + 415.6 10.18 + 420.5 10.27 + 425.4 10.35 + 430.3 10.44 + 435.1 10.52 + 440.0 10.61 + 444.9 10.69 + 449.8 10.78 + 454.6 10.86 + 459.5 10.94 + 464.4 11.03 + 469.3 11.11 + 474.1 11.19 + 479.0 11.28 + 483.9 11.36 + 488.8 11.44 + 493.6 11.53 + 498.5 11.61 + 503.4 11.69 + 508.3 11.78 + 513.1 11.86 + 518.0 11.94 + 522.9 12.02 + 527.8 12.11 + 532.6 12.19 + 537.5 12.27 + 542.4 12.35 + 547.3 12.43 + 552.1 12.51 + 557.0 12.60 + 561.9 12.68 + 566.8 12.76 + 571.6 12.84 + 576.5 12.92 + 581.4 13.00 + 586.3 13.08 + 591.1 13.16 + 596.0 13.24 + 600.9 13.32 + 605.8 13.40 + 610.6 13.48 + 615.5 13.56 + 620.4 13.64 + 625.3 13.72 + 630.1 13.80 + 635.0 13.88 + 639.9 13.96 + 644.8 14.04 + 649.6 14.12 + 654.5 14.20 + 659.4 14.28 + 664.3 14.36 + 669.1 14.44 + 674.0 14.52 + 678.9 14.60 + 683.8 14.68 + 688.6 14.76 + 693.5 14.83 + 698.4 14.91 + 703.3 14.99 + 708.1 15.07 + 713.0 15.15 + 717.9 15.23 + 722.8 15.30 + 727.6 15.38 + 732.5 15.46 + 737.4 15.54 + 742.3 15.62 + 747.1 15.69 + 752.0 15.77 + 756.9 15.85 + 761.8 15.93 + 766.6 16.00 + 771.5 16.08 + 776.4 16.16 + 781.3 16.24 + 786.1 16.31 + 791.0 16.39 + 795.9 16.47 + 800.8 16.54 + 805.6 16.62 + 810.5 16.70 + 815.4 16.77 + 820.3 16.85 + 825.1 16.93 + 830.0 17.00 + 834.9 17.08 + 839.8 17.16 + 844.6 17.23 + 849.5 17.31 + 854.4 17.38 + 859.3 17.46 + 864.1 17.54 + 869.0 17.61 + 873.9 17.69 + 878.8 17.76 + 883.6 17.84 + 888.5 17.92 + 893.4 17.99 + 898.3 18.07 + 903.1 18.14 + 908.0 18.22 + 912.9 18.29 + 917.8 18.37 + 922.6 18.44 + 927.5 18.52 + 932.4 18.59 + 937.3 18.67 + 942.1 18.74 + 947.0 18.82 + 951.9 18.89 + 956.8 18.97 + 961.6 19.04 + 966.5 19.12 + 971.4 19.19 + 976.3 19.27 + 981.1 19.34 + 986.0 19.41 + 990.9 19.49 + 995.8 19.56 + 1000.6 19.64 + 1005.5 19.71 + 1010.4 19.79 + 1015.3 19.86 + 1020.1 19.93 + 1025.0 20.01 + 1029.9 20.08 + 1034.8 20.16 + 1039.6 20.23 + 1044.5 20.30 + 1049.4 20.38 + 1054.3 20.45 + 1059.1 20.52 + 1064.0 20.60 + 1068.9 20.67 + 1073.8 20.74 + 1078.6 20.82 + 1083.5 20.89 + 1088.4 20.96 + 1093.3 21.04 + 1098.1 21.11 + 1103.0 21.18 + 1107.9 21.26 + 1112.8 21.33 + 1117.6 21.40 + 1122.5 21.48 + 1127.4 21.55 + 1132.3 21.62 + 1137.1 21.69 + 1142.0 21.77 + 1146.9 21.84 + 1151.8 21.91 + 1156.6 21.99 + 1161.5 22.06 + 1166.4 22.13 + 1171.3 22.20 + 1176.1 22.28 + 1181.0 22.35 + 1185.9 22.42 + 1190.8 22.49 + 1195.6 22.56 + 1200.5 22.64 + 1205.4 22.71 + 1210.3 22.78 + 1215.1 22.85 + 1220.0 22.93 + 1224.9 23.00 + 1229.8 23.07 + 1234.6 23.14 + 1239.5 23.21 + 1244.4 23.28 + 1249.3 23.36 + 1254.1 23.43 + 1259.0 23.50 + 1263.9 23.57 + 1268.8 23.64 + 1273.6 23.71 + 1278.5 23.79 + 1283.4 23.86 + 1288.3 23.93 + 1293.1 24.00 + 1298.0 24.07 + 1302.9 24.14 + 1307.8 24.21 + 1312.6 24.29 + 1317.5 24.36 + 1322.4 24.43 + 1327.3 24.50 + 1332.1 24.57 + 1337.0 24.64 + 1341.9 24.71 + 1346.8 24.78 + 1351.6 24.85 + 1356.5 24.92 + 1361.4 25.00 + 1366.3 25.07 + 1371.1 25.14 + 1376.0 25.21 + 1380.9 25.28 + 1385.8 25.35 + 1390.6 25.42 + 1395.5 25.49 + 1400.4 25.56 + 1405.3 25.63 + 1410.1 25.70 + 1415.0 25.77 + 1419.9 25.84 + 1424.8 25.91 + 1429.6 25.98 + 1434.5 26.05 + 1439.4 26.12 + 1444.3 26.19 + 1449.1 26.26 + 1454.0 26.33 + 1458.9 26.40 + 1463.8 26.47 + 1468.6 26.54 + 1473.5 26.61 + 1478.4 26.68 + 1483.3 26.75 + 1488.1 26.82 + 1493.0 26.89 + 1497.9 26.96 + 1502.8 27.03 + 1507.6 27.10 + 1512.5 27.17 + 1517.4 27.24 + 1522.3 27.31 + 1527.1 27.38 + 1532.0 27.45 + 1536.9 27.52 + 1541.8 27.59 + 1546.6 27.66 + 1551.5 27.73 + 1556.4 27.80 + 1561.3 27.87 + 1566.1 27.94 + 1571.0 28.01 + 1575.9 28.08 + 1580.8 28.15 + 1585.6 28.21 + 1590.5 28.28 + 1595.4 28.35 + 1600.3 28.42 + 1605.1 28.49 + 1610.0 28.56 + 1614.9 28.63 + 1619.8 28.70 + 1624.6 28.77 + 1629.5 28.84 + 1634.4 28.91 + 1639.3 28.97 + 1644.1 29.04 + 1649.0 29.11 + 1653.9 29.18 + 1658.8 29.25 + 1663.6 29.32 + 1668.5 29.39 + 1673.4 29.46 + 1678.3 29.52 + 1683.1 29.59 + 1688.0 29.66 + 1692.9 29.73 + 1697.8 29.80 + 1702.6 29.87 + 1707.5 29.94 + 1712.4 30.00 + 1717.3 30.07 + 1722.1 30.14 + 1727.0 30.21 + 1731.9 30.28 + 1736.8 30.35 + 1741.6 30.41 + 1746.5 30.48 + 1751.4 30.55 + 1756.3 30.62 + 1761.1 30.69 + 1766.0 30.75 + 1770.9 30.82 + 1775.8 30.89 + 1780.6 30.96 + 1785.5 31.03 + 1790.4 31.10 + 1795.3 31.16 + 1800.1 31.23 + 1805.0 31.30 + 1809.9 31.37 + 1814.8 31.43 + 1819.6 31.50 + 1824.5 31.57 + 1829.4 31.64 + 1834.3 31.71 + 1839.1 31.77 + 1844.0 31.84 + 1848.9 31.91 + 1853.8 31.98 + 1858.6 32.04 + 1863.5 32.11 + 1868.4 32.18 + 1873.3 32.25 + 1878.1 32.31 + 1883.0 32.38 + 1887.9 32.45 + 1892.8 32.52 + 1897.6 32.58 + 1902.5 32.65 + 1907.4 32.72 + 1912.3 32.79 + 1917.1 32.85 + 1922.0 32.92 + 1926.9 32.99 + 1931.8 33.06 + 1936.6 33.12 + 1941.5 33.19 + 1946.4 33.26 + 1951.3 33.32 + 1956.1 33.39 + 1961.0 33.46 + 1965.9 33.53 + 1970.8 33.59 + 1975.6 33.66 + 1980.5 33.73 + 1985.4 33.79 + 1990.3 33.86 + 1995.1 33.93 + 2000.0 33.99 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/013_Al_3_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/013_Al_3_eIMFP.txt new file mode 100644 index 0000000..ff51568 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/013_Al_3_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Al + +SOURCE: + Chen + Y. F. Chen, Private communication + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 26.98154 + +DENSITY: 2.7000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 100.0 5.39 + 104.8 5.50 + 109.5 5.60 + 114.3 5.70 + 119.0 5.80 + 123.8 5.90 + 128.5 6.00 + 133.3 6.10 + 138.0 6.19 + 142.8 6.29 + 147.5 6.39 + 152.3 6.49 + 157.0 6.58 + 161.8 6.68 + 166.5 6.78 + 171.3 6.87 + 176.0 6.97 + 180.8 7.06 + 185.5 7.16 + 190.3 7.25 + 195.0 7.34 + 199.8 7.44 + 204.5 7.53 + 209.3 7.62 + 214.0 7.72 + 218.8 7.81 + 223.5 7.90 + 228.3 7.99 + 233.0 8.09 + 237.8 8.18 + 242.5 8.27 + 247.3 8.36 + 252.0 8.45 + 256.8 8.54 + 261.5 8.63 + 266.3 8.72 + 271.0 8.81 + 275.8 8.90 + 280.5 8.99 + 285.3 9.08 + 290.0 9.17 + 294.8 9.26 + 299.5 9.35 + 304.3 9.44 + 309.0 9.52 + 313.8 9.61 + 318.5 9.70 + 323.3 9.79 + 328.0 9.88 + 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1957.3 35.74 + 1962.0 35.81 + 1966.8 35.88 + 1971.5 35.95 + 1976.3 36.02 + 1981.0 36.09 + 1985.8 36.16 + 1990.5 36.23 + 1995.3 36.30 + 2000.0 36.36 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_1_eIMFP.txt new file mode 100644 index 0000000..00392b1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Si + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 28.08550 + +DENSITY: 2.3290 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.07 + 54.9 4.17 + 59.8 4.28 + 64.6 4.40 + 69.5 4.51 + 74.4 4.63 + 79.3 4.75 + 84.1 4.87 + 89.0 4.99 + 93.9 5.12 + 98.8 5.24 + 103.6 5.37 + 108.5 5.49 + 113.4 5.61 + 118.3 5.74 + 123.1 5.86 + 128.0 5.99 + 132.9 6.11 + 137.8 6.23 + 142.6 6.36 + 147.5 6.48 + 152.4 6.60 + 157.3 6.72 + 162.1 6.84 + 167.0 6.97 + 171.9 7.09 + 176.8 7.21 + 181.6 7.33 + 186.5 7.45 + 191.4 7.57 + 196.3 7.69 + 201.1 7.81 + 206.0 7.92 + 210.9 8.04 + 215.8 8.16 + 220.6 8.28 + 225.5 8.39 + 230.4 8.51 + 235.3 8.63 + 240.1 8.74 + 245.0 8.86 + 249.9 8.97 + 254.8 9.09 + 259.6 9.20 + 264.5 9.32 + 269.4 9.43 + 274.3 9.54 + 279.1 9.66 + 284.0 9.77 + 288.9 9.88 + 293.8 10.00 + 298.6 10.11 + 303.5 10.22 + 308.4 10.33 + 313.3 10.44 + 318.1 10.55 + 323.0 10.67 + 327.9 10.78 + 332.8 10.89 + 337.6 11.00 + 342.5 11.11 + 347.4 11.22 + 352.3 11.33 + 357.1 11.43 + 362.0 11.54 + 366.9 11.65 + 371.8 11.76 + 376.6 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+ 727.6 19.21 + 732.5 19.31 + 737.4 19.41 + 742.3 19.51 + 747.1 19.60 + 752.0 19.70 + 756.9 19.80 + 761.8 19.89 + 766.6 19.99 + 771.5 20.09 + 776.4 20.18 + 781.3 20.28 + 786.1 20.37 + 791.0 20.47 + 795.9 20.57 + 800.8 20.66 + 805.6 20.76 + 810.5 20.85 + 815.4 20.95 + 820.3 21.05 + 825.1 21.14 + 830.0 21.24 + 834.9 21.33 + 839.8 21.43 + 844.6 21.52 + 849.5 21.62 + 854.4 21.71 + 859.3 21.81 + 864.1 21.90 + 869.0 22.00 + 873.9 22.09 + 878.8 22.18 + 883.6 22.28 + 888.5 22.37 + 893.4 22.47 + 898.3 22.56 + 903.1 22.66 + 908.0 22.75 + 912.9 22.84 + 917.8 22.94 + 922.6 23.03 + 927.5 23.12 + 932.4 23.22 + 937.3 23.31 + 942.1 23.41 + 947.0 23.50 + 951.9 23.59 + 956.8 23.69 + 961.6 23.78 + 966.5 23.87 + 971.4 23.96 + 976.3 24.06 + 981.1 24.15 + 986.0 24.24 + 990.9 24.34 + 995.8 24.43 + 1000.6 24.52 + 1005.5 24.61 + 1010.4 24.71 + 1015.3 24.80 + 1020.1 24.89 + 1025.0 24.98 + 1029.9 25.07 + 1034.8 25.17 + 1039.6 25.26 + 1044.5 25.35 + 1049.4 25.44 + 1054.3 25.53 + 1059.1 25.63 + 1064.0 25.72 + 1068.9 25.81 + 1073.8 25.90 + 1078.6 25.99 + 1083.5 26.08 + 1088.4 26.18 + 1093.3 26.27 + 1098.1 26.36 + 1103.0 26.45 + 1107.9 26.54 + 1112.8 26.63 + 1117.6 26.72 + 1122.5 26.81 + 1127.4 26.90 + 1132.3 26.99 + 1137.1 27.09 + 1142.0 27.18 + 1146.9 27.27 + 1151.8 27.36 + 1156.6 27.45 + 1161.5 27.54 + 1166.4 27.63 + 1171.3 27.72 + 1176.1 27.81 + 1181.0 27.90 + 1185.9 27.99 + 1190.8 28.08 + 1195.6 28.17 + 1200.5 28.26 + 1205.4 28.35 + 1210.3 28.44 + 1215.1 28.53 + 1220.0 28.62 + 1224.9 28.71 + 1229.8 28.80 + 1234.6 28.89 + 1239.5 28.98 + 1244.4 29.07 + 1249.3 29.16 + 1254.1 29.25 + 1259.0 29.34 + 1263.9 29.42 + 1268.8 29.51 + 1273.6 29.60 + 1278.5 29.69 + 1283.4 29.78 + 1288.3 29.87 + 1293.1 29.96 + 1298.0 30.05 + 1302.9 30.14 + 1307.8 30.23 + 1312.6 30.31 + 1317.5 30.40 + 1322.4 30.49 + 1327.3 30.58 + 1332.1 30.67 + 1337.0 30.76 + 1341.9 30.85 + 1346.8 30.93 + 1351.6 31.02 + 1356.5 31.11 + 1361.4 31.20 + 1366.3 31.29 + 1371.1 31.38 + 1376.0 31.46 + 1380.9 31.55 + 1385.8 31.64 + 1390.6 31.73 + 1395.5 31.82 + 1400.4 31.90 + 1405.3 31.99 + 1410.1 32.08 + 1415.0 32.17 + 1419.9 32.26 + 1424.8 32.34 + 1429.6 32.43 + 1434.5 32.52 + 1439.4 32.61 + 1444.3 32.69 + 1449.1 32.78 + 1454.0 32.87 + 1458.9 32.96 + 1463.8 33.04 + 1468.6 33.13 + 1473.5 33.22 + 1478.4 33.30 + 1483.3 33.39 + 1488.1 33.48 + 1493.0 33.57 + 1497.9 33.65 + 1502.8 33.74 + 1507.6 33.83 + 1512.5 33.91 + 1517.4 34.00 + 1522.3 34.09 + 1527.1 34.17 + 1532.0 34.26 + 1536.9 34.35 + 1541.8 34.43 + 1546.6 34.52 + 1551.5 34.61 + 1556.4 34.69 + 1561.3 34.78 + 1566.1 34.87 + 1571.0 34.95 + 1575.9 35.04 + 1580.8 35.13 + 1585.6 35.21 + 1590.5 35.30 + 1595.4 35.39 + 1600.3 35.47 + 1605.1 35.56 + 1610.0 35.64 + 1614.9 35.73 + 1619.8 35.82 + 1624.6 35.90 + 1629.5 35.99 + 1634.4 36.07 + 1639.3 36.16 + 1644.1 36.24 + 1649.0 36.33 + 1653.9 36.42 + 1658.8 36.50 + 1663.6 36.59 + 1668.5 36.67 + 1673.4 36.76 + 1678.3 36.84 + 1683.1 36.93 + 1688.0 37.02 + 1692.9 37.10 + 1697.8 37.19 + 1702.6 37.27 + 1707.5 37.36 + 1712.4 37.44 + 1717.3 37.53 + 1722.1 37.61 + 1727.0 37.70 + 1731.9 37.78 + 1736.8 37.87 + 1741.6 37.95 + 1746.5 38.04 + 1751.4 38.12 + 1756.3 38.21 + 1761.1 38.29 + 1766.0 38.38 + 1770.9 38.46 + 1775.8 38.55 + 1780.6 38.63 + 1785.5 38.72 + 1790.4 38.80 + 1795.3 38.89 + 1800.1 38.97 + 1805.0 39.06 + 1809.9 39.14 + 1814.8 39.23 + 1819.6 39.31 + 1824.5 39.39 + 1829.4 39.48 + 1834.3 39.56 + 1839.1 39.65 + 1844.0 39.73 + 1848.9 39.82 + 1853.8 39.90 + 1858.6 39.99 + 1863.5 40.07 + 1868.4 40.15 + 1873.3 40.24 + 1878.1 40.32 + 1883.0 40.41 + 1887.9 40.49 + 1892.8 40.57 + 1897.6 40.66 + 1902.5 40.74 + 1907.4 40.83 + 1912.3 40.91 + 1917.1 40.99 + 1922.0 41.08 + 1926.9 41.16 + 1931.8 41.25 + 1936.6 41.33 + 1941.5 41.41 + 1946.4 41.50 + 1951.3 41.58 + 1956.1 41.66 + 1961.0 41.75 + 1965.9 41.83 + 1970.8 41.92 + 1975.6 42.00 + 1980.5 42.08 + 1985.4 42.17 + 1990.3 42.25 + 1995.1 42.33 + 2000.0 42.42 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_2_eIMFP.txt new file mode 100644 index 0000000..d5f992d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Si + +SOURCE: + Tung et al. + US Air Force Report RADC-TR-76-125 (April 1976) + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 28.08550 + +DENSITY: 2.3290 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 40.0 1.38 + 64.9 2.08 + 89.8 2.73 + 114.7 3.35 + 139.6 3.95 + 164.5 4.53 + 189.4 5.10 + 214.3 5.65 + 239.2 6.20 + 264.1 6.74 + 289.0 7.27 + 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_3_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_3_eIMFP.txt new file mode 100644 index 0000000..08a8ca3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_3_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Si + +SOURCE: + Elastic peak electron spectroscopy + + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +COMMENT: + Gergely et al., Vacuum 48 (1997) 621 + +ATOMIC WEIGHT: 28.08550 + +DENSITY: 2.3290 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 100.0 4.43 + 112.3 4.86 + 124.5 5.28 + 136.8 5.69 + 149.0 6.09 + 161.3 6.49 + 173.5 6.88 + 185.8 7.26 + 198.0 7.64 + 210.3 8.02 + 222.5 8.39 + 234.8 8.75 + 247.0 9.11 + 259.3 9.47 + 271.5 9.83 + 283.8 10.18 + 296.0 10.53 + 308.3 10.87 + 320.5 11.22 + 332.8 11.56 + 345.0 11.89 + 357.3 12.23 + 369.5 12.56 + 381.8 12.89 + 394.0 13.22 + 406.3 13.55 + 418.5 13.87 + 430.8 14.20 + 443.0 14.52 + 455.3 14.84 + 467.5 15.15 + 479.8 15.47 + 492.0 15.78 + 504.3 16.10 + 516.5 16.41 + 528.8 16.72 + 541.0 17.02 + 553.3 17.33 + 565.5 17.64 + 577.8 17.94 + 590.0 18.24 + 602.3 18.54 + 614.5 18.84 + 626.8 19.14 + 639.0 19.44 + 651.3 19.74 + 663.5 20.03 + 675.8 20.33 + 688.0 20.62 + 700.3 20.91 + 712.5 21.20 + 724.8 21.49 + 737.0 21.78 + 749.3 22.07 + 761.5 22.36 + 773.8 22.64 + 786.0 22.93 + 798.3 23.21 + 810.5 23.49 + 822.8 23.78 + 835.0 24.06 + 847.3 24.34 + 859.5 24.62 + 871.8 24.90 + 884.0 25.18 + 896.3 25.46 + 908.5 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99.98 + 5000.0 100.18 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_4_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_4_eIMFP.txt new file mode 100644 index 0000000..5e26544 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_4_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Si + +SOURCE: + Elastic peak electron spectroscopy + + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +COMMENT: + Lesiak et al., Proc. ECASIA 95, Wiley, Chichester (1996), p. 619 + +ATOMIC WEIGHT: 28.08550 + +DENSITY: 2.3290 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 100.0 4.94 + 103.5 5.07 + 107.0 5.20 + 110.5 5.32 + 114.0 5.45 + 117.5 5.57 + 121.0 5.70 + 124.5 5.82 + 128.0 5.94 + 131.5 6.06 + 135.0 6.18 + 138.5 6.30 + 142.0 6.42 + 145.5 6.53 + 149.0 6.65 + 152.5 6.77 + 156.0 6.88 + 159.5 7.00 + 163.0 7.11 + 166.5 7.22 + 170.0 7.34 + 173.5 7.45 + 177.0 7.56 + 180.5 7.67 + 184.0 7.78 + 187.5 7.89 + 191.0 8.00 + 194.5 8.11 + 198.0 8.22 + 201.5 8.33 + 205.0 8.44 + 208.5 8.54 + 212.0 8.65 + 215.5 8.76 + 219.0 8.86 + 222.5 8.97 + 226.0 9.07 + 229.5 9.18 + 233.0 9.28 + 236.5 9.38 + 240.0 9.49 + 243.5 9.59 + 247.0 9.69 + 250.5 9.79 + 254.0 9.90 + 257.5 10.00 + 261.0 10.10 + 264.5 10.20 + 268.0 10.30 + 271.5 10.40 + 275.0 10.50 + 278.5 10.60 + 282.0 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1496.5 37.09 + 1500.0 37.16 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_5_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_5_eIMFP.txt new file mode 100644 index 0000000..80ce0aa --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/014_Si_5_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Si + +SOURCE: + Elastic peak electron spectroscopy + + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +COMMENT: + Koch, Thesis, Eberhard-Karls-Universitat, Tubingen, Germany (1996) + +ATOMIC WEIGHT: 28.08550 + +DENSITY: 2.3290 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy 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2196.0 47.12 + 2200.0 47.20 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/015_P_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/015_P_1_eIMFP.txt new file mode 100644 index 0000000..a9b38b3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/015_P_1_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + P + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +COMMENT: + Black phosphorus (density equal to 2.69 g/cm**3) + +ATOMIC WEIGHT: 30.97376 + +DENSITY: 2.6900 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/015_P_2_eIMFP.txt new file mode 100644 index 0000000..63f35d9 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/015_P_2_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + P + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +COMMENT: + Red phosphorus (density equal to 2.16 g/cm**3) + +ATOMIC WEIGHT: 30.97376 + +DENSITY: 2.1600 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.15 + 54.9 4.29 + 59.8 4.41 + 64.6 4.52 + 69.5 4.63 + 74.4 4.74 + 79.3 4.85 + 84.1 4.95 + 89.0 5.06 + 93.9 5.17 + 98.8 5.28 + 103.6 5.39 + 108.5 5.50 + 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/015_P_3_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + P + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +COMMENT: + White phosphorus (density equal to 1.823 g/cm**3) + +ATOMIC WEIGHT: 30.97376 + +DENSITY: 1.8230 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.03 + 54.9 4.19 + 59.8 4.32 + 64.6 4.45 + 69.5 4.57 + 74.4 4.69 + 79.3 4.81 + 84.1 4.93 + 89.0 5.05 + 93.9 5.17 + 98.8 5.29 + 103.6 5.41 + 108.5 5.53 + 113.4 5.66 + 118.3 5.78 + 123.1 5.90 + 128.0 6.02 + 132.9 6.14 + 137.8 6.26 + 142.6 6.38 + 147.5 6.50 + 152.4 6.62 + 157.3 6.74 + 162.1 6.86 + 167.0 6.98 + 171.9 7.10 + 176.8 7.22 + 181.6 7.34 + 186.5 7.46 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35.13 + 1551.5 35.22 + 1556.4 35.31 + 1561.3 35.40 + 1566.1 35.49 + 1571.0 35.57 + 1575.9 35.66 + 1580.8 35.75 + 1585.6 35.84 + 1590.5 35.93 + 1595.4 36.02 + 1600.3 36.11 + 1605.1 36.20 + 1610.0 36.29 + 1614.9 36.38 + 1619.8 36.47 + 1624.6 36.55 + 1629.5 36.64 + 1634.4 36.73 + 1639.3 36.82 + 1644.1 36.91 + 1649.0 37.00 + 1653.9 37.09 + 1658.8 37.17 + 1663.6 37.26 + 1668.5 37.35 + 1673.4 37.44 + 1678.3 37.53 + 1683.1 37.62 + 1688.0 37.71 + 1692.9 37.79 + 1697.8 37.88 + 1702.6 37.97 + 1707.5 38.06 + 1712.4 38.15 + 1717.3 38.23 + 1722.1 38.32 + 1727.0 38.41 + 1731.9 38.50 + 1736.8 38.59 + 1741.6 38.67 + 1746.5 38.76 + 1751.4 38.85 + 1756.3 38.94 + 1761.1 39.03 + 1766.0 39.11 + 1770.9 39.20 + 1775.8 39.29 + 1780.6 39.38 + 1785.5 39.46 + 1790.4 39.55 + 1795.3 39.64 + 1800.1 39.73 + 1805.0 39.81 + 1809.9 39.90 + 1814.8 39.99 + 1819.6 40.08 + 1824.5 40.16 + 1829.4 40.25 + 1834.3 40.34 + 1839.1 40.43 + 1844.0 40.51 + 1848.9 40.60 + 1853.8 40.69 + 1858.6 40.78 + 1863.5 40.86 + 1868.4 40.95 + 1873.3 41.04 + 1878.1 41.12 + 1883.0 41.21 + 1887.9 41.30 + 1892.8 41.38 + 1897.6 41.47 + 1902.5 41.56 + 1907.4 41.65 + 1912.3 41.73 + 1917.1 41.82 + 1922.0 41.91 + 1926.9 41.99 + 1931.8 42.08 + 1936.6 42.17 + 1941.5 42.25 + 1946.4 42.34 + 1951.3 42.43 + 1956.1 42.51 + 1961.0 42.60 + 1965.9 42.69 + 1970.8 42.77 + 1975.6 42.86 + 1980.5 42.94 + 1985.4 43.03 + 1990.3 43.12 + 1995.1 43.20 + 2000.0 43.29 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/016_S_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/016_S_eIMFP.txt new file mode 100644 index 0000000..8dd7446 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/016_S_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + S + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 32.06600 + +DENSITY: 2.0700 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.25 + 54.9 4.39 + 59.8 4.51 + 64.6 4.62 + 69.5 4.72 + 74.4 4.83 + 79.3 4.93 + 84.1 5.04 + 89.0 5.14 + 93.9 5.25 + 98.8 5.36 + 103.6 5.46 + 108.5 5.57 + 113.4 5.68 + 118.3 5.79 + 123.1 5.90 + 128.0 6.02 + 132.9 6.13 + 137.8 6.24 + 142.6 6.35 + 147.5 6.46 + 152.4 6.58 + 157.3 6.69 + 162.1 6.80 + 167.0 6.91 + 171.9 7.03 + 176.8 7.14 + 181.6 7.25 + 186.5 7.36 + 191.4 7.48 + 196.3 7.59 + 201.1 7.70 + 206.0 7.81 + 210.9 7.92 + 215.8 8.03 + 220.6 8.14 + 225.5 8.26 + 230.4 8.37 + 235.3 8.48 + 240.1 8.59 + 245.0 8.70 + 249.9 8.81 + 254.8 8.92 + 259.6 9.03 + 264.5 9.14 + 269.4 9.24 + 274.3 9.35 + 279.1 9.46 + 284.0 9.57 + 288.9 9.68 + 293.8 9.79 + 298.6 9.90 + 303.5 10.00 + 308.4 10.11 + 313.3 10.22 + 318.1 10.32 + 323.0 10.43 + 327.9 10.54 + 332.8 10.64 + 337.6 10.75 + 342.5 10.86 + 347.4 10.96 + 352.3 11.07 + 357.1 11.17 + 362.0 11.28 + 366.9 11.39 + 371.8 11.49 + 376.6 11.60 + 381.5 11.70 + 386.4 11.80 + 391.3 11.91 + 396.1 12.01 + 401.0 12.12 + 405.9 12.22 + 410.8 12.32 + 415.6 12.43 + 420.5 12.53 + 425.4 12.63 + 430.3 12.74 + 435.1 12.84 + 440.0 12.94 + 444.9 13.05 + 449.8 13.15 + 454.6 13.25 + 459.5 13.35 + 464.4 13.45 + 469.3 13.56 + 474.1 13.66 + 479.0 13.76 + 483.9 13.86 + 488.8 13.96 + 493.6 14.06 + 498.5 14.16 + 503.4 14.27 + 508.3 14.37 + 513.1 14.47 + 518.0 14.57 + 522.9 14.67 + 527.8 14.77 + 532.6 14.87 + 537.5 14.97 + 542.4 15.07 + 547.3 15.17 + 552.1 15.27 + 557.0 15.37 + 561.9 15.47 + 566.8 15.56 + 571.6 15.66 + 576.5 15.76 + 581.4 15.86 + 586.3 15.96 + 591.1 16.06 + 596.0 16.16 + 600.9 16.26 + 605.8 16.35 + 610.6 16.45 + 615.5 16.55 + 620.4 16.65 + 625.3 16.75 + 630.1 16.84 + 635.0 16.94 + 639.9 17.04 + 644.8 17.14 + 649.6 17.23 + 654.5 17.33 + 659.4 17.43 + 664.3 17.52 + 669.1 17.62 + 674.0 17.72 + 678.9 17.81 + 683.8 17.91 + 688.6 18.01 + 693.5 18.10 + 698.4 18.20 + 703.3 18.30 + 708.1 18.39 + 713.0 18.49 + 717.9 18.58 + 722.8 18.68 + 727.6 18.78 + 732.5 18.87 + 737.4 18.97 + 742.3 19.06 + 747.1 19.16 + 752.0 19.25 + 756.9 19.35 + 761.8 19.44 + 766.6 19.54 + 771.5 19.63 + 776.4 19.73 + 781.3 19.82 + 786.1 19.92 + 791.0 20.01 + 795.9 20.11 + 800.8 20.20 + 805.6 20.29 + 810.5 20.39 + 815.4 20.48 + 820.3 20.58 + 825.1 20.67 + 830.0 20.76 + 834.9 20.86 + 839.8 20.95 + 844.6 21.05 + 849.5 21.14 + 854.4 21.23 + 859.3 21.33 + 864.1 21.42 + 869.0 21.51 + 873.9 21.61 + 878.8 21.70 + 883.6 21.79 + 888.5 21.89 + 893.4 21.98 + 898.3 22.07 + 903.1 22.16 + 908.0 22.26 + 912.9 22.35 + 917.8 22.44 + 922.6 22.53 + 927.5 22.63 + 932.4 22.72 + 937.3 22.81 + 942.1 22.90 + 947.0 23.00 + 951.9 23.09 + 956.8 23.18 + 961.6 23.27 + 966.5 23.36 + 971.4 23.46 + 976.3 23.55 + 981.1 23.64 + 986.0 23.73 + 990.9 23.82 + 995.8 23.91 + 1000.6 24.00 + 1005.5 24.10 + 1010.4 24.19 + 1015.3 24.28 + 1020.1 24.37 + 1025.0 24.46 + 1029.9 24.55 + 1034.8 24.64 + 1039.6 24.73 + 1044.5 24.82 + 1049.4 24.92 + 1054.3 25.01 + 1059.1 25.10 + 1064.0 25.19 + 1068.9 25.28 + 1073.8 25.37 + 1078.6 25.46 + 1083.5 25.55 + 1088.4 25.64 + 1093.3 25.73 + 1098.1 25.82 + 1103.0 25.91 + 1107.9 26.00 + 1112.8 26.09 + 1117.6 26.18 + 1122.5 26.27 + 1127.4 26.36 + 1132.3 26.45 + 1137.1 26.54 + 1142.0 26.63 + 1146.9 26.72 + 1151.8 26.81 + 1156.6 26.90 + 1161.5 26.99 + 1166.4 27.08 + 1171.3 27.17 + 1176.1 27.25 + 1181.0 27.34 + 1185.9 27.43 + 1190.8 27.52 + 1195.6 27.61 + 1200.5 27.70 + 1205.4 27.79 + 1210.3 27.88 + 1215.1 27.97 + 1220.0 28.06 + 1224.9 28.15 + 1229.8 28.23 + 1234.6 28.32 + 1239.5 28.41 + 1244.4 28.50 + 1249.3 28.59 + 1254.1 28.68 + 1259.0 28.77 + 1263.9 28.85 + 1268.8 28.94 + 1273.6 29.03 + 1278.5 29.12 + 1283.4 29.21 + 1288.3 29.29 + 1293.1 29.38 + 1298.0 29.47 + 1302.9 29.56 + 1307.8 29.65 + 1312.6 29.74 + 1317.5 29.82 + 1322.4 29.91 + 1327.3 30.00 + 1332.1 30.09 + 1337.0 30.17 + 1341.9 30.26 + 1346.8 30.35 + 1351.6 30.44 + 1356.5 30.52 + 1361.4 30.61 + 1366.3 30.70 + 1371.1 30.79 + 1376.0 30.87 + 1380.9 30.96 + 1385.8 31.05 + 1390.6 31.14 + 1395.5 31.22 + 1400.4 31.31 + 1405.3 31.40 + 1410.1 31.48 + 1415.0 31.57 + 1419.9 31.66 + 1424.8 31.74 + 1429.6 31.83 + 1434.5 31.92 + 1439.4 32.01 + 1444.3 32.09 + 1449.1 32.18 + 1454.0 32.27 + 1458.9 32.35 + 1463.8 32.44 + 1468.6 32.53 + 1473.5 32.61 + 1478.4 32.70 + 1483.3 32.78 + 1488.1 32.87 + 1493.0 32.96 + 1497.9 33.04 + 1502.8 33.13 + 1507.6 33.22 + 1512.5 33.30 + 1517.4 33.39 + 1522.3 33.47 + 1527.1 33.56 + 1532.0 33.65 + 1536.9 33.73 + 1541.8 33.82 + 1546.6 33.90 + 1551.5 33.99 + 1556.4 34.08 + 1561.3 34.16 + 1566.1 34.25 + 1571.0 34.33 + 1575.9 34.42 + 1580.8 34.50 + 1585.6 34.59 + 1590.5 34.68 + 1595.4 34.76 + 1600.3 34.85 + 1605.1 34.93 + 1610.0 35.02 + 1614.9 35.10 + 1619.8 35.19 + 1624.6 35.27 + 1629.5 35.36 + 1634.4 35.44 + 1639.3 35.53 + 1644.1 35.62 + 1649.0 35.70 + 1653.9 35.79 + 1658.8 35.87 + 1663.6 35.96 + 1668.5 36.04 + 1673.4 36.13 + 1678.3 36.21 + 1683.1 36.30 + 1688.0 36.38 + 1692.9 36.46 + 1697.8 36.55 + 1702.6 36.63 + 1707.5 36.72 + 1712.4 36.80 + 1717.3 36.89 + 1722.1 36.97 + 1727.0 37.06 + 1731.9 37.14 + 1736.8 37.23 + 1741.6 37.31 + 1746.5 37.40 + 1751.4 37.48 + 1756.3 37.56 + 1761.1 37.65 + 1766.0 37.73 + 1770.9 37.82 + 1775.8 37.90 + 1780.6 37.99 + 1785.5 38.07 + 1790.4 38.15 + 1795.3 38.24 + 1800.1 38.32 + 1805.0 38.41 + 1809.9 38.49 + 1814.8 38.58 + 1819.6 38.66 + 1824.5 38.74 + 1829.4 38.83 + 1834.3 38.91 + 1839.1 38.99 + 1844.0 39.08 + 1848.9 39.16 + 1853.8 39.25 + 1858.6 39.33 + 1863.5 39.41 + 1868.4 39.50 + 1873.3 39.58 + 1878.1 39.66 + 1883.0 39.75 + 1887.9 39.83 + 1892.8 39.92 + 1897.6 40.00 + 1902.5 40.08 + 1907.4 40.17 + 1912.3 40.25 + 1917.1 40.33 + 1922.0 40.42 + 1926.9 40.50 + 1931.8 40.58 + 1936.6 40.67 + 1941.5 40.75 + 1946.4 40.83 + 1951.3 40.92 + 1956.1 41.00 + 1961.0 41.08 + 1965.9 41.16 + 1970.8 41.25 + 1975.6 41.33 + 1980.5 41.41 + 1985.4 41.50 + 1990.3 41.58 + 1995.1 41.66 + 2000.0 41.75 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/019_K_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/019_K_eIMFP.txt new file mode 100644 index 0000000..25a979d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/019_K_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + K + +SOURCE: + Tanuma, Powell and Penn + Unpublished data + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 39.09830 + +DENSITY: 0.8900 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 7.25 + 54.9 7.46 + 59.8 7.69 + 64.6 7.94 + 69.5 8.20 + 74.4 8.47 + 79.3 8.74 + 84.1 9.02 + 89.0 9.30 + 93.9 9.58 + 98.8 9.87 + 103.6 10.15 + 108.5 10.43 + 113.4 10.72 + 118.3 11.00 + 123.1 11.29 + 128.0 11.57 + 132.9 11.85 + 137.8 12.13 + 142.6 12.41 + 147.5 12.69 + 152.4 12.97 + 157.3 13.25 + 162.1 13.53 + 167.0 13.81 + 171.9 14.09 + 176.8 14.36 + 181.6 14.64 + 186.5 14.91 + 191.4 15.18 + 196.3 15.46 + 201.1 15.73 + 206.0 16.00 + 210.9 16.27 + 215.8 16.54 + 220.6 16.81 + 225.5 17.07 + 230.4 17.34 + 235.3 17.61 + 240.1 17.87 + 245.0 18.14 + 249.9 18.40 + 254.8 18.67 + 259.6 18.93 + 264.5 19.19 + 269.4 19.45 + 274.3 19.71 + 279.1 19.98 + 284.0 20.24 + 288.9 20.49 + 293.8 20.75 + 298.6 21.01 + 303.5 21.27 + 308.4 21.53 + 313.3 21.78 + 318.1 22.04 + 323.0 22.29 + 327.9 22.55 + 332.8 22.80 + 337.6 23.06 + 342.5 23.31 + 347.4 23.56 + 352.3 23.81 + 357.1 24.07 + 362.0 24.32 + 366.9 24.57 + 371.8 24.82 + 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/020_Ca_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/020_Ca_eIMFP.txt new file mode 100644 index 0000000..89f80c8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/020_Ca_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ca + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 40.07800 + +DENSITY: 1.5400 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.70 + 54.9 4.91 + 59.8 5.12 + 64.6 5.32 + 69.5 5.53 + 74.4 5.72 + 79.3 5.92 + 84.1 6.11 + 89.0 6.30 + 93.9 6.50 + 98.8 6.69 + 103.6 6.87 + 108.5 7.06 + 113.4 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/021_Sc_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Sc + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 44.95591 + +DENSITY: 2.9900 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.63 + 54.9 4.53 + 59.8 4.48 + 64.6 4.47 + 69.5 4.48 + 74.4 4.50 + 79.3 4.55 + 84.1 4.60 + 89.0 4.66 + 93.9 4.72 + 98.8 4.80 + 103.6 4.87 + 108.5 4.95 + 113.4 5.03 + 118.3 5.11 + 123.1 5.20 + 128.0 5.28 + 132.9 5.37 + 137.8 5.46 + 142.6 5.55 + 147.5 5.64 + 152.4 5.73 + 157.3 5.82 + 162.1 5.91 + 167.0 6.00 + 171.9 6.09 + 176.8 6.19 + 181.6 6.28 + 186.5 6.37 + 191.4 6.46 + 196.3 6.55 + 201.1 6.65 + 206.0 6.74 + 210.9 6.83 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40.18 + 2000.0 40.26 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/024_Cr_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/024_Cr_1_eIMFP.txt new file mode 100644 index 0000000..4717810 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/024_Cr_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Cr + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 51.99610 + +DENSITY: 7.1500 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.43 + 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/024_Cr_2_eIMFP.txt new file mode 100644 index 0000000..e5fd934 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/024_Cr_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Cr + +SOURCE: + Gergely et al. + Surface Sci. 331-333 (1995) 1203 + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +ATOMIC WEIGHT: 51.99610 + +DENSITY: 7.1500 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 500.0 9.45 + 506.3 9.52 + 512.5 9.60 + 518.8 9.68 + 525.0 9.76 + 531.3 9.83 + 537.5 9.91 + 543.8 9.99 + 550.0 10.06 + 556.3 10.14 + 562.5 10.22 + 568.8 10.29 + 575.0 10.37 + 581.3 10.44 + 587.5 10.51 + 593.8 10.59 + 600.0 10.66 + 606.3 10.74 + 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file mode 100644 index 0000000..47e1625 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/025_Mn_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Mn + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 54.93805 + +DENSITY: 7.3000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.61 + 54.9 4.60 + 59.8 4.58 + 64.6 4.56 + 69.5 4.55 + 74.4 4.55 + 79.3 4.56 + 84.1 4.58 + 89.0 4.60 + 93.9 4.63 + 98.8 4.67 + 103.6 4.71 + 108.5 4.76 + 113.4 4.81 + 118.3 4.87 + 123.1 4.92 + 128.0 4.98 + 132.9 5.04 + 137.8 5.10 + 142.6 5.17 + 147.5 5.23 + 152.4 5.30 + 157.3 5.37 + 162.1 5.44 + 167.0 5.50 + 171.9 5.57 + 176.8 5.64 + 181.6 5.71 + 186.5 5.78 + 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27.59 + 1990.3 27.65 + 1995.1 27.70 + 2000.0 27.75 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/026_Fe_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/026_Fe_2_eIMFP.txt new file mode 100644 index 0000000..43483a0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/026_Fe_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Fe + +SOURCE: + Kwei, Chen, Tung and Wang + Surface Sci. 293 (1993) 202; Y. F. Chen, Private communication + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 55.84500 + +DENSITY: 7.8700 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 100.0 5.10 + 104.8 5.12 + 109.5 5.14 + 114.3 5.17 + 119.0 5.20 + 123.8 5.24 + 128.5 5.28 + 133.3 5.32 + 138.0 5.36 + 142.8 5.40 + 147.5 5.45 + 152.3 5.49 + 157.0 5.54 + 161.8 5.59 + 166.5 5.64 + 171.3 5.69 + 176.0 5.74 + 180.8 5.80 + 185.5 5.85 + 190.3 5.90 + 195.0 5.96 + 199.8 6.01 + 204.5 6.07 + 209.3 6.13 + 214.0 6.19 + 218.8 6.24 + 223.5 6.30 + 228.3 6.36 + 233.0 6.42 + 237.8 6.48 + 242.5 6.54 + 247.3 6.60 + 252.0 6.66 + 256.8 6.72 + 261.5 6.78 + 266.3 6.84 + 271.0 6.90 + 275.8 6.96 + 280.5 7.02 + 285.3 7.08 + 290.0 7.15 + 294.8 7.21 + 299.5 7.27 + 304.3 7.33 + 309.0 7.39 + 313.8 7.46 + 318.5 7.52 + 323.3 7.58 + 328.0 7.64 + 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27.68 + 1971.5 27.73 + 1976.3 27.78 + 1981.0 27.84 + 1985.8 27.89 + 1990.5 27.94 + 1995.3 28.00 + 2000.0 28.05 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/026_Fe_3_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/026_Fe_3_eIMFP.txt new file mode 100644 index 0000000..2a8fe53 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/026_Fe_3_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Fe + +SOURCE: + Elastic peak electron spectroscopy + + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +COMMENT: + Koch, Thesis, Eberhard-Karls-Universitat, Tubingen, Germany (1996) + +ATOMIC WEIGHT: 55.84500 + +DENSITY: 7.8700 g/cm**3 + +TABULATION: + 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1986.0 23.03 + 1989.5 23.06 + 1993.0 23.09 + 1996.5 23.13 + 2000.0 23.16 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/027_Co_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/027_Co_1_eIMFP.txt new file mode 100644 index 0000000..b44e4c1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/027_Co_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Co + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 58.93320 + +DENSITY: 8.9000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/028_Ni_1_eIMFP.txt new file mode 100644 index 0000000..24d0be5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/028_Ni_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ni + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 58.69340 + +DENSITY: 8.8600 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.77 + 54.9 4.78 + 59.8 4.73 + 64.6 4.68 + 69.5 4.63 + 74.4 4.59 + 79.3 4.56 + 84.1 4.54 + 89.0 4.54 + 93.9 4.54 + 98.8 4.55 + 103.6 4.57 + 108.5 4.60 + 113.4 4.63 + 118.3 4.66 + 123.1 4.70 + 128.0 4.74 + 132.9 4.78 + 137.8 4.83 + 142.6 4.87 + 147.5 4.92 + 152.4 4.97 + 157.3 5.03 + 162.1 5.08 + 167.0 5.13 + 171.9 5.19 + 176.8 5.24 + 181.6 5.30 + 186.5 5.36 + 191.4 5.42 + 196.3 5.47 + 201.1 5.53 + 206.0 5.59 + 210.9 5.65 + 215.8 5.71 + 220.6 5.77 + 225.5 5.83 + 230.4 5.89 + 235.3 5.95 + 240.1 6.01 + 245.0 6.07 + 249.9 6.13 + 254.8 6.19 + 259.6 6.25 + 264.5 6.31 + 269.4 6.37 + 274.3 6.43 + 279.1 6.50 + 284.0 6.56 + 288.9 6.62 + 293.8 6.68 + 298.6 6.74 + 303.5 6.80 + 308.4 6.86 + 313.3 6.92 + 318.1 6.98 + 323.0 7.04 + 327.9 7.10 + 332.8 7.17 + 337.6 7.23 + 342.5 7.29 + 347.4 7.35 + 352.3 7.41 + 357.1 7.47 + 362.0 7.53 + 366.9 7.59 + 371.8 7.65 + 376.6 7.71 + 381.5 7.77 + 386.4 7.83 + 391.3 7.89 + 396.1 7.95 + 401.0 8.01 + 405.9 8.07 + 410.8 8.13 + 415.6 8.19 + 420.5 8.25 + 425.4 8.31 + 430.3 8.37 + 435.1 8.43 + 440.0 8.49 + 444.9 8.55 + 449.8 8.60 + 454.6 8.66 + 459.5 8.72 + 464.4 8.78 + 469.3 8.84 + 474.1 8.90 + 479.0 8.96 + 483.9 9.02 + 488.8 9.08 + 493.6 9.13 + 498.5 9.19 + 503.4 9.25 + 508.3 9.31 + 513.1 9.37 + 518.0 9.43 + 522.9 9.48 + 527.8 9.54 + 532.6 9.60 + 537.5 9.66 + 542.4 9.72 + 547.3 9.77 + 552.1 9.83 + 557.0 9.89 + 561.9 9.95 + 566.8 10.01 + 571.6 10.06 + 576.5 10.12 + 581.4 10.18 + 586.3 10.24 + 591.1 10.29 + 596.0 10.35 + 600.9 10.41 + 605.8 10.46 + 610.6 10.52 + 615.5 10.58 + 620.4 10.63 + 625.3 10.69 + 630.1 10.75 + 635.0 10.80 + 639.9 10.86 + 644.8 10.92 + 649.6 10.97 + 654.5 11.03 + 659.4 11.09 + 664.3 11.14 + 669.1 11.20 + 674.0 11.26 + 678.9 11.31 + 683.8 11.37 + 688.6 11.42 + 693.5 11.48 + 698.4 11.54 + 703.3 11.59 + 708.1 11.65 + 713.0 11.70 + 717.9 11.76 + 722.8 11.82 + 727.6 11.87 + 732.5 11.93 + 737.4 11.98 + 742.3 12.04 + 747.1 12.09 + 752.0 12.15 + 756.9 12.20 + 761.8 12.26 + 766.6 12.31 + 771.5 12.37 + 776.4 12.42 + 781.3 12.48 + 786.1 12.53 + 791.0 12.59 + 795.9 12.64 + 800.8 12.70 + 805.6 12.75 + 810.5 12.81 + 815.4 12.86 + 820.3 12.92 + 825.1 12.97 + 830.0 13.03 + 834.9 13.08 + 839.8 13.14 + 844.6 13.19 + 849.5 13.24 + 854.4 13.30 + 859.3 13.35 + 864.1 13.41 + 869.0 13.46 + 873.9 13.51 + 878.8 13.57 + 883.6 13.62 + 888.5 13.68 + 893.4 13.73 + 898.3 13.78 + 903.1 13.84 + 908.0 13.89 + 912.9 13.95 + 917.8 14.00 + 922.6 14.05 + 927.5 14.11 + 932.4 14.16 + 937.3 14.21 + 942.1 14.27 + 947.0 14.32 + 951.9 14.37 + 956.8 14.43 + 961.6 14.48 + 966.5 14.53 + 971.4 14.59 + 976.3 14.64 + 981.1 14.69 + 986.0 14.75 + 990.9 14.80 + 995.8 14.85 + 1000.6 14.91 + 1005.5 14.96 + 1010.4 15.01 + 1015.3 15.07 + 1020.1 15.12 + 1025.0 15.17 + 1029.9 15.22 + 1034.8 15.28 + 1039.6 15.33 + 1044.5 15.38 + 1049.4 15.43 + 1054.3 15.49 + 1059.1 15.54 + 1064.0 15.59 + 1068.9 15.64 + 1073.8 15.70 + 1078.6 15.75 + 1083.5 15.80 + 1088.4 15.85 + 1093.3 15.91 + 1098.1 15.96 + 1103.0 16.01 + 1107.9 16.06 + 1112.8 16.11 + 1117.6 16.17 + 1122.5 16.22 + 1127.4 16.27 + 1132.3 16.32 + 1137.1 16.38 + 1142.0 16.43 + 1146.9 16.48 + 1151.8 16.53 + 1156.6 16.58 + 1161.5 16.63 + 1166.4 16.69 + 1171.3 16.74 + 1176.1 16.79 + 1181.0 16.84 + 1185.9 16.89 + 1190.8 16.94 + 1195.6 17.00 + 1200.5 17.05 + 1205.4 17.10 + 1210.3 17.15 + 1215.1 17.20 + 1220.0 17.25 + 1224.9 17.30 + 1229.8 17.36 + 1234.6 17.41 + 1239.5 17.46 + 1244.4 17.51 + 1249.3 17.56 + 1254.1 17.61 + 1259.0 17.66 + 1263.9 17.71 + 1268.8 17.77 + 1273.6 17.82 + 1278.5 17.87 + 1283.4 17.92 + 1288.3 17.97 + 1293.1 18.02 + 1298.0 18.07 + 1302.9 18.12 + 1307.8 18.17 + 1312.6 18.22 + 1317.5 18.28 + 1322.4 18.33 + 1327.3 18.38 + 1332.1 18.43 + 1337.0 18.48 + 1341.9 18.53 + 1346.8 18.58 + 1351.6 18.63 + 1356.5 18.68 + 1361.4 18.73 + 1366.3 18.78 + 1371.1 18.83 + 1376.0 18.88 + 1380.9 18.93 + 1385.8 18.98 + 1390.6 19.03 + 1395.5 19.08 + 1400.4 19.13 + 1405.3 19.18 + 1410.1 19.23 + 1415.0 19.29 + 1419.9 19.34 + 1424.8 19.39 + 1429.6 19.44 + 1434.5 19.49 + 1439.4 19.54 + 1444.3 19.59 + 1449.1 19.64 + 1454.0 19.69 + 1458.9 19.74 + 1463.8 19.79 + 1468.6 19.84 + 1473.5 19.89 + 1478.4 19.94 + 1483.3 19.99 + 1488.1 20.04 + 1493.0 20.09 + 1497.9 20.14 + 1502.8 20.19 + 1507.6 20.23 + 1512.5 20.28 + 1517.4 20.33 + 1522.3 20.38 + 1527.1 20.43 + 1532.0 20.48 + 1536.9 20.53 + 1541.8 20.58 + 1546.6 20.63 + 1551.5 20.68 + 1556.4 20.73 + 1561.3 20.78 + 1566.1 20.83 + 1571.0 20.88 + 1575.9 20.93 + 1580.8 20.98 + 1585.6 21.03 + 1590.5 21.08 + 1595.4 21.13 + 1600.3 21.18 + 1605.1 21.22 + 1610.0 21.27 + 1614.9 21.32 + 1619.8 21.37 + 1624.6 21.42 + 1629.5 21.47 + 1634.4 21.52 + 1639.3 21.57 + 1644.1 21.62 + 1649.0 21.67 + 1653.9 21.72 + 1658.8 21.77 + 1663.6 21.81 + 1668.5 21.86 + 1673.4 21.91 + 1678.3 21.96 + 1683.1 22.01 + 1688.0 22.06 + 1692.9 22.11 + 1697.8 22.16 + 1702.6 22.21 + 1707.5 22.25 + 1712.4 22.30 + 1717.3 22.35 + 1722.1 22.40 + 1727.0 22.45 + 1731.9 22.50 + 1736.8 22.55 + 1741.6 22.60 + 1746.5 22.64 + 1751.4 22.69 + 1756.3 22.74 + 1761.1 22.79 + 1766.0 22.84 + 1770.9 22.89 + 1775.8 22.94 + 1780.6 22.98 + 1785.5 23.03 + 1790.4 23.08 + 1795.3 23.13 + 1800.1 23.18 + 1805.0 23.23 + 1809.9 23.27 + 1814.8 23.32 + 1819.6 23.37 + 1824.5 23.42 + 1829.4 23.47 + 1834.3 23.52 + 1839.1 23.56 + 1844.0 23.61 + 1848.9 23.66 + 1853.8 23.71 + 1858.6 23.76 + 1863.5 23.81 + 1868.4 23.85 + 1873.3 23.90 + 1878.1 23.95 + 1883.0 24.00 + 1887.9 24.05 + 1892.8 24.09 + 1897.6 24.14 + 1902.5 24.19 + 1907.4 24.24 + 1912.3 24.29 + 1917.1 24.33 + 1922.0 24.38 + 1926.9 24.43 + 1931.8 24.48 + 1936.6 24.53 + 1941.5 24.57 + 1946.4 24.62 + 1951.3 24.67 + 1956.1 24.72 + 1961.0 24.77 + 1965.9 24.81 + 1970.8 24.86 + 1975.6 24.91 + 1980.5 24.96 + 1985.4 25.00 + 1990.3 25.05 + 1995.1 25.10 + 2000.0 25.15 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/028_Ni_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/028_Ni_2_eIMFP.txt new file mode 100644 index 0000000..3c598e4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/028_Ni_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ni + +SOURCE: + Powell and Jablonski + J. Phys. Chem. Reference Data 28 (1999) 19 + Evaluation of calculated and measured IMFP values + + +ATOMIC WEIGHT: 58.69340 + +DENSITY: 8.8600 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.91 + 74.9 4.55 + 99.8 4.53 + 124.6 4.65 + 149.5 4.85 + 174.4 5.08 + 199.3 5.34 + 224.1 5.62 + 249.0 5.90 + 273.9 6.19 + 298.8 6.49 + 323.6 6.78 + 348.5 7.08 + 373.4 7.38 + 398.3 7.68 + 423.1 7.98 + 448.0 8.28 + 472.9 8.57 + 497.8 8.87 + 522.6 9.16 + 547.5 9.46 + 572.4 9.75 + 597.3 10.04 + 622.1 10.33 + 647.0 10.62 + 671.9 10.90 + 696.8 11.19 + 721.6 11.47 + 746.5 11.76 + 771.4 12.04 + 796.3 12.32 + 821.1 12.60 + 846.0 12.88 + 870.9 13.15 + 895.8 13.43 + 920.6 13.70 + 945.5 13.98 + 970.4 14.25 + 995.3 14.52 + 1020.1 14.79 + 1045.0 15.06 + 1069.9 15.33 + 1094.8 15.59 + 1119.6 15.86 + 1144.5 16.12 + 1169.4 16.39 + 1194.3 16.65 + 1219.1 16.91 + 1244.0 17.17 + 1268.9 17.43 + 1293.8 17.69 + 1318.6 17.95 + 1343.5 18.21 + 1368.4 18.46 + 1393.3 18.72 + 1418.1 18.98 + 1443.0 19.23 + 1467.9 19.48 + 1492.8 19.74 + 1517.6 19.99 + 1542.5 20.24 + 1567.4 20.49 + 1592.3 20.74 + 1617.1 20.99 + 1642.0 21.24 + 1666.9 21.48 + 1691.8 21.73 + 1716.6 21.98 + 1741.5 22.22 + 1766.4 22.47 + 1791.3 22.71 + 1816.1 22.96 + 1841.0 23.20 + 1865.9 23.44 + 1890.8 23.68 + 1915.6 23.92 + 1940.5 24.16 + 1965.4 24.40 + 1990.3 24.64 + 2015.1 24.88 + 2040.0 25.12 + 2064.9 25.36 + 2089.8 25.60 + 2114.6 25.83 + 2139.5 26.07 + 2164.4 26.30 + 2189.3 26.54 + 2214.1 26.77 + 2239.0 27.01 + 2263.9 27.24 + 2288.8 27.47 + 2313.6 27.71 + 2338.5 27.94 + 2363.4 28.17 + 2388.3 28.40 + 2413.1 28.63 + 2438.0 28.86 + 2462.9 29.09 + 2487.8 29.32 + 2512.6 29.55 + 2537.5 29.78 + 2562.4 30.01 + 2587.3 30.24 + 2612.1 30.46 + 2637.0 30.69 + 2661.9 30.92 + 2686.8 31.14 + 2711.6 31.37 + 2736.5 31.59 + 2761.4 31.82 + 2786.3 32.04 + 2811.1 32.27 + 2836.0 32.49 + 2860.9 32.71 + 2885.8 32.93 + 2910.6 33.16 + 2935.5 33.38 + 2960.4 33.60 + 2985.3 33.82 + 3010.1 34.04 + 3035.0 34.26 + 3059.9 34.48 + 3084.8 34.70 + 3109.6 34.92 + 3134.5 35.14 + 3159.4 35.36 + 3184.3 35.58 + 3209.1 35.80 + 3234.0 36.02 + 3258.9 36.23 + 3283.8 36.45 + 3308.6 36.67 + 3333.5 36.88 + 3358.4 37.10 + 3383.3 37.32 + 3408.1 37.53 + 3433.0 37.75 + 3457.9 37.96 + 3482.8 38.18 + 3507.6 38.39 + 3532.5 38.61 + 3557.4 38.82 + 3582.3 39.03 + 3607.1 39.25 + 3632.0 39.46 + 3656.9 39.67 + 3681.8 39.88 + 3706.6 40.10 + 3731.5 40.31 + 3756.4 40.52 + 3781.3 40.73 + 3806.1 40.94 + 3831.0 41.15 + 3855.9 41.36 + 3880.8 41.57 + 3905.6 41.78 + 3930.5 41.99 + 3955.4 42.20 + 3980.3 42.41 + 4005.1 42.62 + 4030.0 42.83 + 4054.9 43.03 + 4079.8 43.24 + 4104.6 43.45 + 4129.5 43.66 + 4154.4 43.87 + 4179.3 44.07 + 4204.1 44.28 + 4229.0 44.49 + 4253.9 44.69 + 4278.8 44.90 + 4303.6 45.10 + 4328.5 45.31 + 4353.4 45.51 + 4378.3 45.72 + 4403.1 45.92 + 4428.0 46.13 + 4452.9 46.33 + 4477.8 46.54 + 4502.6 46.74 + 4527.5 46.95 + 4552.4 47.15 + 4577.3 47.35 + 4602.1 47.55 + 4627.0 47.76 + 4651.9 47.96 + 4676.8 48.16 + 4701.6 48.36 + 4726.5 48.57 + 4751.4 48.77 + 4776.3 48.97 + 4801.1 49.17 + 4826.0 49.37 + 4850.9 49.57 + 4875.8 49.77 + 4900.6 49.97 + 4925.5 50.17 + 4950.4 50.37 + 4975.3 50.57 + 5000.1 50.77 + 5025.0 50.97 + 5049.9 51.17 + 5074.8 51.37 + 5099.6 51.57 + 5124.5 51.77 + 5149.4 51.97 + 5174.3 52.17 + 5199.1 52.36 + 5224.0 52.56 + 5248.9 52.76 + 5273.8 52.96 + 5298.6 53.15 + 5323.5 53.35 + 5348.4 53.55 + 5373.3 53.75 + 5398.1 53.94 + 5423.0 54.14 + 5447.9 54.34 + 5472.8 54.53 + 5497.6 54.73 + 5522.5 54.92 + 5547.4 55.12 + 5572.3 55.31 + 5597.1 55.51 + 5622.0 55.70 + 5646.9 55.90 + 5671.8 56.09 + 5696.6 56.29 + 5721.5 56.48 + 5746.4 56.68 + 5771.3 56.87 + 5796.1 57.06 + 5821.0 57.26 + 5845.9 57.45 + 5870.8 57.64 + 5895.6 57.84 + 5920.5 58.03 + 5945.4 58.22 + 5970.3 58.42 + 5995.1 58.61 + 6020.0 58.80 + 6044.9 58.99 + 6069.8 59.18 + 6094.6 59.38 + 6119.5 59.57 + 6144.4 59.76 + 6169.3 59.95 + 6194.1 60.14 + 6219.0 60.33 + 6243.9 60.52 + 6268.8 60.72 + 6293.6 60.91 + 6318.5 61.10 + 6343.4 61.29 + 6368.3 61.48 + 6393.1 61.67 + 6418.0 61.86 + 6442.9 62.05 + 6467.8 62.24 + 6492.6 62.42 + 6517.5 62.61 + 6542.4 62.80 + 6567.3 62.99 + 6592.1 63.18 + 6617.0 63.37 + 6641.9 63.56 + 6666.8 63.75 + 6691.6 63.93 + 6716.5 64.12 + 6741.4 64.31 + 6766.3 64.50 + 6791.1 64.69 + 6816.0 64.87 + 6840.9 65.06 + 6865.8 65.25 + 6890.6 65.44 + 6915.5 65.62 + 6940.4 65.81 + 6965.3 66.00 + 6990.1 66.18 + 7015.0 66.37 + 7039.9 66.56 + 7064.8 66.74 + 7089.6 66.93 + 7114.5 67.11 + 7139.4 67.30 + 7164.3 67.49 + 7189.1 67.67 + 7214.0 67.86 + 7238.9 68.04 + 7263.8 68.23 + 7288.6 68.41 + 7313.5 68.60 + 7338.4 68.78 + 7363.3 68.97 + 7388.1 69.15 + 7413.0 69.33 + 7437.9 69.52 + 7462.8 69.70 + 7487.6 69.89 + 7512.5 70.07 + 7537.4 70.25 + 7562.3 70.44 + 7587.1 70.62 + 7612.0 70.81 + 7636.9 70.99 + 7661.8 71.17 + 7686.6 71.35 + 7711.5 71.54 + 7736.4 71.72 + 7761.3 71.90 + 7786.1 72.09 + 7811.0 72.27 + 7835.9 72.45 + 7860.8 72.63 + 7885.6 72.81 + 7910.5 73.00 + 7935.4 73.18 + 7960.3 73.36 + 7985.1 73.54 + 8010.0 73.72 + 8034.9 73.90 + 8059.8 74.09 + 8084.6 74.27 + 8109.5 74.45 + 8134.4 74.63 + 8159.3 74.81 + 8184.1 74.99 + 8209.0 75.17 + 8233.9 75.35 + 8258.8 75.53 + 8283.6 75.71 + 8308.5 75.89 + 8333.4 76.07 + 8358.3 76.25 + 8383.1 76.43 + 8408.0 76.61 + 8432.9 76.79 + 8457.8 76.97 + 8482.6 77.15 + 8507.5 77.33 + 8532.4 77.51 + 8557.3 77.69 + 8582.1 77.87 + 8607.0 78.05 + 8631.9 78.22 + 8656.8 78.40 + 8681.6 78.58 + 8706.5 78.76 + 8731.4 78.94 + 8756.3 79.12 + 8781.1 79.29 + 8806.0 79.47 + 8830.9 79.65 + 8855.8 79.83 + 8880.6 80.01 + 8905.5 80.18 + 8930.4 80.36 + 8955.3 80.54 + 8980.1 80.72 + 9005.0 80.89 + 9029.9 81.07 + 9054.8 81.25 + 9079.6 81.42 + 9104.5 81.60 + 9129.4 81.78 + 9154.3 81.95 + 9179.1 82.13 + 9204.0 82.31 + 9228.9 82.48 + 9253.8 82.66 + 9278.6 82.84 + 9303.5 83.01 + 9328.4 83.19 + 9353.3 83.36 + 9378.1 83.54 + 9403.0 83.71 + 9427.9 83.89 + 9452.8 84.07 + 9477.6 84.24 + 9502.5 84.42 + 9527.4 84.59 + 9552.3 84.77 + 9577.1 84.94 + 9602.0 85.12 + 9626.9 85.29 + 9651.8 85.47 + 9676.6 85.64 + 9701.5 85.82 + 9726.4 85.99 + 9751.3 86.16 + 9776.1 86.34 + 9801.0 86.51 + 9825.9 86.69 + 9850.8 86.86 + 9875.6 87.03 + 9900.5 87.21 + 9925.4 87.38 + 9950.3 87.56 + 9975.1 87.73 + 10000.0 87.90 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/029_Cu_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/029_Cu_1_eIMFP.txt new file mode 100644 index 0000000..39f69fc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/029_Cu_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Cu + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 63.54600 + +DENSITY: 8.9600 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.88 + 54.9 4.93 + 59.8 4.92 + 64.6 4.91 + 69.5 4.89 + 74.4 4.88 + 79.3 4.87 + 84.1 4.88 + 89.0 4.89 + 93.9 4.91 + 98.8 4.94 + 103.6 4.97 + 108.5 5.01 + 113.4 5.05 + 118.3 5.09 + 123.1 5.14 + 128.0 5.19 + 132.9 5.24 + 137.8 5.30 + 142.6 5.35 + 147.5 5.41 + 152.4 5.47 + 157.3 5.53 + 162.1 5.59 + 167.0 5.65 + 171.9 5.71 + 176.8 5.78 + 181.6 5.84 + 186.5 5.91 + 191.4 5.97 + 196.3 6.04 + 201.1 6.10 + 206.0 6.17 + 210.9 6.23 + 215.8 6.30 + 220.6 6.37 + 225.5 6.43 + 230.4 6.50 + 235.3 6.57 + 240.1 6.63 + 245.0 6.70 + 249.9 6.77 + 254.8 6.84 + 259.6 6.90 + 264.5 6.97 + 269.4 7.04 + 274.3 7.10 + 279.1 7.17 + 284.0 7.24 + 288.9 7.31 + 293.8 7.37 + 298.6 7.44 + 303.5 7.51 + 308.4 7.57 + 313.3 7.64 + 318.1 7.71 + 323.0 7.78 + 327.9 7.84 + 332.8 7.91 + 337.6 7.98 + 342.5 8.04 + 347.4 8.11 + 352.3 8.18 + 357.1 8.24 + 362.0 8.31 + 366.9 8.37 + 371.8 8.44 + 376.6 8.51 + 381.5 8.57 + 386.4 8.64 + 391.3 8.70 + 396.1 8.77 + 401.0 8.84 + 405.9 8.90 + 410.8 8.97 + 415.6 9.03 + 420.5 9.10 + 425.4 9.16 + 430.3 9.23 + 435.1 9.29 + 440.0 9.36 + 444.9 9.42 + 449.8 9.49 + 454.6 9.55 + 459.5 9.62 + 464.4 9.68 + 469.3 9.75 + 474.1 9.81 + 479.0 9.87 + 483.9 9.94 + 488.8 10.00 + 493.6 10.07 + 498.5 10.13 + 503.4 10.19 + 508.3 10.26 + 513.1 10.32 + 518.0 10.39 + 522.9 10.45 + 527.8 10.51 + 532.6 10.58 + 537.5 10.64 + 542.4 10.70 + 547.3 10.77 + 552.1 10.83 + 557.0 10.89 + 561.9 10.96 + 566.8 11.02 + 571.6 11.08 + 576.5 11.14 + 581.4 11.21 + 586.3 11.27 + 591.1 11.33 + 596.0 11.39 + 600.9 11.46 + 605.8 11.52 + 610.6 11.58 + 615.5 11.64 + 620.4 11.70 + 625.3 11.77 + 630.1 11.83 + 635.0 11.89 + 639.9 11.95 + 644.8 12.01 + 649.6 12.08 + 654.5 12.14 + 659.4 12.20 + 664.3 12.26 + 669.1 12.32 + 674.0 12.38 + 678.9 12.44 + 683.8 12.51 + 688.6 12.57 + 693.5 12.63 + 698.4 12.69 + 703.3 12.75 + 708.1 12.81 + 713.0 12.87 + 717.9 12.93 + 722.8 12.99 + 727.6 13.05 + 732.5 13.11 + 737.4 13.17 + 742.3 13.23 + 747.1 13.29 + 752.0 13.35 + 756.9 13.41 + 761.8 13.47 + 766.6 13.54 + 771.5 13.60 + 776.4 13.66 + 781.3 13.71 + 786.1 13.77 + 791.0 13.83 + 795.9 13.89 + 800.8 13.95 + 805.6 14.01 + 810.5 14.07 + 815.4 14.13 + 820.3 14.19 + 825.1 14.25 + 830.0 14.31 + 834.9 14.37 + 839.8 14.43 + 844.6 14.49 + 849.5 14.55 + 854.4 14.61 + 859.3 14.67 + 864.1 14.73 + 869.0 14.78 + 873.9 14.84 + 878.8 14.90 + 883.6 14.96 + 888.5 15.02 + 893.4 15.08 + 898.3 15.14 + 903.1 15.20 + 908.0 15.25 + 912.9 15.31 + 917.8 15.37 + 922.6 15.43 + 927.5 15.49 + 932.4 15.55 + 937.3 15.60 + 942.1 15.66 + 947.0 15.72 + 951.9 15.78 + 956.8 15.84 + 961.6 15.89 + 966.5 15.95 + 971.4 16.01 + 976.3 16.07 + 981.1 16.13 + 986.0 16.18 + 990.9 16.24 + 995.8 16.30 + 1000.6 16.36 + 1005.5 16.41 + 1010.4 16.47 + 1015.3 16.53 + 1020.1 16.59 + 1025.0 16.64 + 1029.9 16.70 + 1034.8 16.76 + 1039.6 16.82 + 1044.5 16.87 + 1049.4 16.93 + 1054.3 16.99 + 1059.1 17.04 + 1064.0 17.10 + 1068.9 17.16 + 1073.8 17.22 + 1078.6 17.27 + 1083.5 17.33 + 1088.4 17.39 + 1093.3 17.44 + 1098.1 17.50 + 1103.0 17.56 + 1107.9 17.61 + 1112.8 17.67 + 1117.6 17.73 + 1122.5 17.78 + 1127.4 17.84 + 1132.3 17.90 + 1137.1 17.95 + 1142.0 18.01 + 1146.9 18.07 + 1151.8 18.12 + 1156.6 18.18 + 1161.5 18.23 + 1166.4 18.29 + 1171.3 18.35 + 1176.1 18.40 + 1181.0 18.46 + 1185.9 18.52 + 1190.8 18.57 + 1195.6 18.63 + 1200.5 18.68 + 1205.4 18.74 + 1210.3 18.80 + 1215.1 18.85 + 1220.0 18.91 + 1224.9 18.96 + 1229.8 19.02 + 1234.6 19.07 + 1239.5 19.13 + 1244.4 19.19 + 1249.3 19.24 + 1254.1 19.30 + 1259.0 19.35 + 1263.9 19.41 + 1268.8 19.46 + 1273.6 19.52 + 1278.5 19.57 + 1283.4 19.63 + 1288.3 19.69 + 1293.1 19.74 + 1298.0 19.80 + 1302.9 19.85 + 1307.8 19.91 + 1312.6 19.96 + 1317.5 20.02 + 1322.4 20.07 + 1327.3 20.13 + 1332.1 20.18 + 1337.0 20.24 + 1341.9 20.29 + 1346.8 20.35 + 1351.6 20.40 + 1356.5 20.46 + 1361.4 20.51 + 1366.3 20.57 + 1371.1 20.62 + 1376.0 20.68 + 1380.9 20.73 + 1385.8 20.79 + 1390.6 20.84 + 1395.5 20.90 + 1400.4 20.95 + 1405.3 21.00 + 1410.1 21.06 + 1415.0 21.11 + 1419.9 21.17 + 1424.8 21.22 + 1429.6 21.28 + 1434.5 21.33 + 1439.4 21.39 + 1444.3 21.44 + 1449.1 21.49 + 1454.0 21.55 + 1458.9 21.60 + 1463.8 21.66 + 1468.6 21.71 + 1473.5 21.77 + 1478.4 21.82 + 1483.3 21.87 + 1488.1 21.93 + 1493.0 21.98 + 1497.9 22.04 + 1502.8 22.09 + 1507.6 22.14 + 1512.5 22.20 + 1517.4 22.25 + 1522.3 22.31 + 1527.1 22.36 + 1532.0 22.41 + 1536.9 22.47 + 1541.8 22.52 + 1546.6 22.58 + 1551.5 22.63 + 1556.4 22.68 + 1561.3 22.74 + 1566.1 22.79 + 1571.0 22.84 + 1575.9 22.90 + 1580.8 22.95 + 1585.6 23.00 + 1590.5 23.06 + 1595.4 23.11 + 1600.3 23.17 + 1605.1 23.22 + 1610.0 23.27 + 1614.9 23.33 + 1619.8 23.38 + 1624.6 23.43 + 1629.5 23.49 + 1634.4 23.54 + 1639.3 23.59 + 1644.1 23.65 + 1649.0 23.70 + 1653.9 23.75 + 1658.8 23.81 + 1663.6 23.86 + 1668.5 23.91 + 1673.4 23.96 + 1678.3 24.02 + 1683.1 24.07 + 1688.0 24.12 + 1692.9 24.18 + 1697.8 24.23 + 1702.6 24.28 + 1707.5 24.34 + 1712.4 24.39 + 1717.3 24.44 + 1722.1 24.49 + 1727.0 24.55 + 1731.9 24.60 + 1736.8 24.65 + 1741.6 24.71 + 1746.5 24.76 + 1751.4 24.81 + 1756.3 24.86 + 1761.1 24.92 + 1766.0 24.97 + 1770.9 25.02 + 1775.8 25.07 + 1780.6 25.13 + 1785.5 25.18 + 1790.4 25.23 + 1795.3 25.28 + 1800.1 25.34 + 1805.0 25.39 + 1809.9 25.44 + 1814.8 25.49 + 1819.6 25.55 + 1824.5 25.60 + 1829.4 25.65 + 1834.3 25.70 + 1839.1 25.76 + 1844.0 25.81 + 1848.9 25.86 + 1853.8 25.91 + 1858.6 25.97 + 1863.5 26.02 + 1868.4 26.07 + 1873.3 26.12 + 1878.1 26.17 + 1883.0 26.23 + 1887.9 26.28 + 1892.8 26.33 + 1897.6 26.38 + 1902.5 26.44 + 1907.4 26.49 + 1912.3 26.54 + 1917.1 26.59 + 1922.0 26.64 + 1926.9 26.70 + 1931.8 26.75 + 1936.6 26.80 + 1941.5 26.85 + 1946.4 26.90 + 1951.3 26.95 + 1956.1 27.01 + 1961.0 27.06 + 1965.9 27.11 + 1970.8 27.16 + 1975.6 27.21 + 1980.5 27.27 + 1985.4 27.32 + 1990.3 27.37 + 1995.1 27.42 + 2000.0 27.47 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/029_Cu_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/029_Cu_2_eIMFP.txt new file mode 100644 index 0000000..80e9f3a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/029_Cu_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Cu + +SOURCE: + Powell and Jablonski + J. Phys. Chem. Reference Data 28 (1999) 19 + Evaluation of calculated and measured IMFP values + + +ATOMIC WEIGHT: 63.54600 + +DENSITY: 8.9600 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.17 + 74.9 4.94 + 99.8 4.99 + 124.6 5.17 + 149.5 5.41 + 174.4 5.69 + 199.3 5.98 + 224.1 6.30 + 249.0 6.62 + 273.9 6.95 + 298.8 7.28 + 323.6 7.61 + 348.5 7.95 + 373.4 8.29 + 398.3 8.62 + 423.1 8.96 + 448.0 9.29 + 472.9 9.63 + 497.8 9.96 + 522.6 10.30 + 547.5 10.63 + 572.4 10.96 + 597.3 11.29 + 622.1 11.62 + 647.0 11.95 + 671.9 12.27 + 696.8 12.60 + 721.6 12.92 + 746.5 13.24 + 771.4 13.57 + 796.3 13.89 + 821.1 14.20 + 846.0 14.52 + 870.9 14.84 + 895.8 15.15 + 920.6 15.47 + 945.5 15.78 + 970.4 16.09 + 995.3 16.41 + 1020.1 16.72 + 1045.0 17.02 + 1069.9 17.33 + 1094.8 17.64 + 1119.6 17.95 + 1144.5 18.25 + 1169.4 18.55 + 1194.3 18.86 + 1219.1 19.16 + 1244.0 19.46 + 1268.9 19.76 + 1293.8 20.06 + 1318.6 20.36 + 1343.5 20.66 + 1368.4 20.95 + 1393.3 21.25 + 1418.1 21.55 + 1443.0 21.84 + 1467.9 22.13 + 1492.8 22.43 + 1517.6 22.72 + 1542.5 23.01 + 1567.4 23.30 + 1592.3 23.59 + 1617.1 23.88 + 1642.0 24.17 + 1666.9 24.46 + 1691.8 24.74 + 1716.6 25.03 + 1741.5 25.32 + 1766.4 25.60 + 1791.3 25.89 + 1816.1 26.17 + 1841.0 26.45 + 1865.9 26.74 + 1890.8 27.02 + 1915.6 27.30 + 1940.5 27.58 + 1965.4 27.86 + 1990.3 28.14 + 2015.1 28.42 + 2040.0 28.70 + 2064.9 28.98 + 2089.8 29.26 + 2114.6 29.53 + 2139.5 29.81 + 2164.4 30.08 + 2189.3 30.36 + 2214.1 30.63 + 2239.0 30.91 + 2263.9 31.18 + 2288.8 31.46 + 2313.6 31.73 + 2338.5 32.00 + 2363.4 32.27 + 2388.3 32.54 + 2413.1 32.82 + 2438.0 33.09 + 2462.9 33.36 + 2487.8 33.63 + 2512.6 33.89 + 2537.5 34.16 + 2562.4 34.43 + 2587.3 34.70 + 2612.1 34.97 + 2637.0 35.23 + 2661.9 35.50 + 2686.8 35.77 + 2711.6 36.03 + 2736.5 36.30 + 2761.4 36.56 + 2786.3 36.83 + 2811.1 37.09 + 2836.0 37.35 + 2860.9 37.62 + 2885.8 37.88 + 2910.6 38.14 + 2935.5 38.40 + 2960.4 38.67 + 2985.3 38.93 + 3010.1 39.19 + 3035.0 39.45 + 3059.9 39.71 + 3084.8 39.97 + 3109.6 40.23 + 3134.5 40.49 + 3159.4 40.75 + 3184.3 41.00 + 3209.1 41.26 + 3234.0 41.52 + 3258.9 41.78 + 3283.8 42.03 + 3308.6 42.29 + 3333.5 42.55 + 3358.4 42.80 + 3383.3 43.06 + 3408.1 43.31 + 3433.0 43.57 + 3457.9 43.82 + 3482.8 44.08 + 3507.6 44.33 + 3532.5 44.59 + 3557.4 44.84 + 3582.3 45.09 + 3607.1 45.35 + 3632.0 45.60 + 3656.9 45.85 + 3681.8 46.10 + 3706.6 46.36 + 3731.5 46.61 + 3756.4 46.86 + 3781.3 47.11 + 3806.1 47.36 + 3831.0 47.61 + 3855.9 47.86 + 3880.8 48.11 + 3905.6 48.36 + 3930.5 48.61 + 3955.4 48.86 + 3980.3 49.10 + 4005.1 49.35 + 4030.0 49.60 + 4054.9 49.85 + 4079.8 50.10 + 4104.6 50.34 + 4129.5 50.59 + 4154.4 50.84 + 4179.3 51.08 + 4204.1 51.33 + 4229.0 51.58 + 4253.9 51.82 + 4278.8 52.07 + 4303.6 52.31 + 4328.5 52.56 + 4353.4 52.80 + 4378.3 53.05 + 4403.1 53.29 + 4428.0 53.54 + 4452.9 53.78 + 4477.8 54.02 + 4502.6 54.27 + 4527.5 54.51 + 4552.4 54.75 + 4577.3 54.99 + 4602.1 55.24 + 4627.0 55.48 + 4651.9 55.72 + 4676.8 55.96 + 4701.6 56.20 + 4726.5 56.44 + 4751.4 56.69 + 4776.3 56.93 + 4801.1 57.17 + 4826.0 57.41 + 4850.9 57.65 + 4875.8 57.89 + 4900.6 58.13 + 4925.5 58.37 + 4950.4 58.61 + 4975.3 58.84 + 5000.1 59.08 + 5025.0 59.32 + 5049.9 59.56 + 5074.8 59.80 + 5099.6 60.04 + 5124.5 60.27 + 5149.4 60.51 + 5174.3 60.75 + 5199.1 60.99 + 5224.0 61.22 + 5248.9 61.46 + 5273.8 61.70 + 5298.6 61.93 + 5323.5 62.17 + 5348.4 62.41 + 5373.3 62.64 + 5398.1 62.88 + 5423.0 63.11 + 5447.9 63.35 + 5472.8 63.58 + 5497.6 63.82 + 5522.5 64.05 + 5547.4 64.29 + 5572.3 64.52 + 5597.1 64.76 + 5622.0 64.99 + 5646.9 65.22 + 5671.8 65.46 + 5696.6 65.69 + 5721.5 65.92 + 5746.4 66.16 + 5771.3 66.39 + 5796.1 66.62 + 5821.0 66.85 + 5845.9 67.09 + 5870.8 67.32 + 5895.6 67.55 + 5920.5 67.78 + 5945.4 68.01 + 5970.3 68.25 + 5995.1 68.48 + 6020.0 68.71 + 6044.9 68.94 + 6069.8 69.17 + 6094.6 69.40 + 6119.5 69.63 + 6144.4 69.86 + 6169.3 70.09 + 6194.1 70.32 + 6219.0 70.55 + 6243.9 70.78 + 6268.8 71.01 + 6293.6 71.24 + 6318.5 71.47 + 6343.4 71.70 + 6368.3 71.93 + 6393.1 72.16 + 6418.0 72.38 + 6442.9 72.61 + 6467.8 72.84 + 6492.6 73.07 + 6517.5 73.30 + 6542.4 73.52 + 6567.3 73.75 + 6592.1 73.98 + 6617.0 74.21 + 6641.9 74.43 + 6666.8 74.66 + 6691.6 74.89 + 6716.5 75.11 + 6741.4 75.34 + 6766.3 75.57 + 6791.1 75.79 + 6816.0 76.02 + 6840.9 76.24 + 6865.8 76.47 + 6890.6 76.70 + 6915.5 76.92 + 6940.4 77.15 + 6965.3 77.37 + 6990.1 77.60 + 7015.0 77.82 + 7039.9 78.05 + 7064.8 78.27 + 7089.6 78.50 + 7114.5 78.72 + 7139.4 78.94 + 7164.3 79.17 + 7189.1 79.39 + 7214.0 79.62 + 7238.9 79.84 + 7263.8 80.06 + 7288.6 80.29 + 7313.5 80.51 + 7338.4 80.73 + 7363.3 80.96 + 7388.1 81.18 + 7413.0 81.40 + 7437.9 81.62 + 7462.8 81.85 + 7487.6 82.07 + 7512.5 82.29 + 7537.4 82.51 + 7562.3 82.74 + 7587.1 82.96 + 7612.0 83.18 + 7636.9 83.40 + 7661.8 83.62 + 7686.6 83.84 + 7711.5 84.06 + 7736.4 84.29 + 7761.3 84.51 + 7786.1 84.73 + 7811.0 84.95 + 7835.9 85.17 + 7860.8 85.39 + 7885.6 85.61 + 7910.5 85.83 + 7935.4 86.05 + 7960.3 86.27 + 7985.1 86.49 + 8010.0 86.71 + 8034.9 86.93 + 8059.8 87.15 + 8084.6 87.37 + 8109.5 87.59 + 8134.4 87.81 + 8159.3 88.02 + 8184.1 88.24 + 8209.0 88.46 + 8233.9 88.68 + 8258.8 88.90 + 8283.6 89.12 + 8308.5 89.34 + 8333.4 89.55 + 8358.3 89.77 + 8383.1 89.99 + 8408.0 90.21 + 8432.9 90.42 + 8457.8 90.64 + 8482.6 90.86 + 8507.5 91.08 + 8532.4 91.29 + 8557.3 91.51 + 8582.1 91.73 + 8607.0 91.95 + 8631.9 92.16 + 8656.8 92.38 + 8681.6 92.60 + 8706.5 92.81 + 8731.4 93.03 + 8756.3 93.24 + 8781.1 93.46 + 8806.0 93.68 + 8830.9 93.89 + 8855.8 94.11 + 8880.6 94.32 + 8905.5 94.54 + 8930.4 94.75 + 8955.3 94.97 + 8980.1 95.18 + 9005.0 95.40 + 9029.9 95.62 + 9054.8 95.83 + 9079.6 96.04 + 9104.5 96.26 + 9129.4 96.47 + 9154.3 96.69 + 9179.1 96.90 + 9204.0 97.12 + 9228.9 97.33 + 9253.8 97.55 + 9278.6 97.76 + 9303.5 97.97 + 9328.4 98.19 + 9353.3 98.40 + 9378.1 98.61 + 9403.0 98.83 + 9427.9 99.04 + 9452.8 99.25 + 9477.6 99.47 + 9502.5 99.68 + 9527.4 99.89 + 9552.3 100.11 + 9577.1 100.32 + 9602.0 100.53 + 9626.9 100.74 + 9651.8 100.96 + 9676.6 101.17 + 9701.5 101.38 + 9726.4 101.59 + 9751.3 101.81 + 9776.1 102.02 + 9801.0 102.23 + 9825.9 102.44 + 9850.8 102.65 + 9875.6 102.86 + 9900.5 103.08 + 9925.4 103.29 + 9950.3 103.50 + 9975.1 103.71 + 10000.0 103.92 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/029_Cu_3_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/029_Cu_3_eIMFP.txt new file mode 100644 index 0000000..5b5732c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/029_Cu_3_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Cu + +SOURCE: + Ding and Shimizu + Scanning 18 (1996) 92 + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 63.54600 + +DENSITY: 8.9600 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 10.0 19.19 + 35.0 6.13 + 60.0 5.13 + 84.9 5.07 + 109.9 5.26 + 134.9 5.53 + 159.9 5.83 + 184.8 6.16 + 209.8 6.49 + 234.8 6.82 + 259.8 7.16 + 284.7 7.50 + 309.7 7.83 + 334.7 8.17 + 359.7 8.50 + 384.6 8.83 + 409.6 9.16 + 434.6 9.48 + 459.6 9.81 + 484.5 10.13 + 509.5 10.45 + 534.5 10.77 + 559.5 11.09 + 584.4 11.40 + 609.4 11.72 + 634.4 12.03 + 659.4 12.34 + 684.3 12.65 + 709.3 12.96 + 734.3 13.27 + 759.3 13.57 + 784.2 13.88 + 809.2 14.18 + 834.2 14.48 + 859.2 14.78 + 884.1 15.08 + 909.1 15.38 + 934.1 15.68 + 959.1 15.98 + 984.0 16.27 + 1009.0 16.57 + 1034.0 16.86 + 1059.0 17.15 + 1083.9 17.45 + 1108.9 17.74 + 1133.9 18.03 + 1158.9 18.32 + 1183.8 18.61 + 1208.8 18.89 + 1233.8 19.18 + 1258.8 19.47 + 1283.7 19.75 + 1308.7 20.04 + 1333.7 20.32 + 1358.7 20.61 + 1383.6 20.89 + 1408.6 21.17 + 1433.6 21.46 + 1458.6 21.74 + 1483.5 22.02 + 1508.5 22.30 + 1533.5 22.58 + 1558.5 22.86 + 1583.4 23.13 + 1608.4 23.41 + 1633.4 23.69 + 1658.4 23.97 + 1683.3 24.24 + 1708.3 24.52 + 1733.3 24.79 + 1758.3 25.07 + 1783.2 25.34 + 1808.2 25.61 + 1833.2 25.89 + 1858.2 26.16 + 1883.1 26.43 + 1908.1 26.70 + 1933.1 26.98 + 1958.1 27.25 + 1983.0 27.52 + 2008.0 27.79 + 2033.0 28.06 + 2058.0 28.33 + 2082.9 28.59 + 2107.9 28.86 + 2132.9 29.13 + 2157.9 29.40 + 2182.8 29.67 + 2207.8 29.93 + 2232.8 30.20 + 2257.8 30.46 + 2282.7 30.73 + 2307.7 31.00 + 2332.7 31.26 + 2357.7 31.53 + 2382.6 31.79 + 2407.6 32.05 + 2432.6 32.32 + 2457.6 32.58 + 2482.5 32.84 + 2507.5 33.11 + 2532.5 33.37 + 2557.5 33.63 + 2582.4 33.89 + 2607.4 34.15 + 2632.4 34.41 + 2657.4 34.67 + 2682.3 34.93 + 2707.3 35.19 + 2732.3 35.45 + 2757.3 35.71 + 2782.2 35.97 + 2807.2 36.23 + 2832.2 36.49 + 2857.2 36.75 + 2882.1 37.01 + 2907.1 37.26 + 2932.1 37.52 + 2957.1 37.78 + 2982.0 38.04 + 3007.0 38.29 + 3032.0 38.55 + 3057.0 38.81 + 3081.9 39.06 + 3106.9 39.32 + 3131.9 39.57 + 3156.9 39.83 + 3181.8 40.08 + 3206.8 40.34 + 3231.8 40.59 + 3256.8 40.85 + 3281.7 41.10 + 3306.7 41.35 + 3331.7 41.61 + 3356.7 41.86 + 3381.6 42.11 + 3406.6 42.37 + 3431.6 42.62 + 3456.6 42.87 + 3481.5 43.12 + 3506.5 43.37 + 3531.5 43.63 + 3556.5 43.88 + 3581.4 44.13 + 3606.4 44.38 + 3631.4 44.63 + 3656.4 44.88 + 3681.3 45.13 + 3706.3 45.38 + 3731.3 45.63 + 3756.3 45.88 + 3781.2 46.13 + 3806.2 46.38 + 3831.2 46.63 + 3856.2 46.88 + 3881.1 47.13 + 3906.1 47.37 + 3931.1 47.62 + 3956.1 47.87 + 3981.0 48.12 + 4006.0 48.37 + 4031.0 48.61 + 4056.0 48.86 + 4080.9 49.11 + 4105.9 49.35 + 4130.9 49.60 + 4155.9 49.85 + 4180.8 50.09 + 4205.8 50.34 + 4230.8 50.59 + 4255.8 50.83 + 4280.7 51.08 + 4305.7 51.32 + 4330.7 51.57 + 4355.7 51.81 + 4380.6 52.06 + 4405.6 52.30 + 4430.6 52.55 + 4455.6 52.79 + 4480.5 53.04 + 4505.5 53.28 + 4530.5 53.53 + 4555.5 53.77 + 4580.4 54.01 + 4605.4 54.26 + 4630.4 54.50 + 4655.4 54.74 + 4680.3 54.99 + 4705.3 55.23 + 4730.3 55.47 + 4755.3 55.71 + 4780.2 55.96 + 4805.2 56.20 + 4830.2 56.44 + 4855.2 56.68 + 4880.1 56.92 + 4905.1 57.17 + 4930.1 57.41 + 4955.1 57.65 + 4980.0 57.89 + 5005.0 58.13 + 5030.0 58.37 + 5055.0 58.61 + 5079.9 58.85 + 5104.9 59.09 + 5129.9 59.33 + 5154.9 59.57 + 5179.8 59.81 + 5204.8 60.05 + 5229.8 60.29 + 5254.8 60.53 + 5279.7 60.77 + 5304.7 61.01 + 5329.7 61.25 + 5354.7 61.49 + 5379.6 61.73 + 5404.6 61.97 + 5429.6 62.21 + 5454.6 62.44 + 5479.5 62.68 + 5504.5 62.92 + 5529.5 63.16 + 5554.5 63.40 + 5579.4 63.63 + 5604.4 63.87 + 5629.4 64.11 + 5654.4 64.35 + 5679.3 64.58 + 5704.3 64.82 + 5729.3 65.06 + 5754.3 65.30 + 5779.2 65.53 + 5804.2 65.77 + 5829.2 66.01 + 5854.2 66.24 + 5879.1 66.48 + 5904.1 66.71 + 5929.1 66.95 + 5954.1 67.19 + 5979.0 67.42 + 6004.0 67.66 + 6029.0 67.89 + 6054.0 68.13 + 6078.9 68.36 + 6103.9 68.60 + 6128.9 68.83 + 6153.9 69.07 + 6178.8 69.30 + 6203.8 69.54 + 6228.8 69.77 + 6253.8 70.01 + 6278.7 70.24 + 6303.7 70.48 + 6328.7 70.71 + 6353.7 70.95 + 6378.6 71.18 + 6403.6 71.41 + 6428.6 71.65 + 6453.6 71.88 + 6478.5 72.11 + 6503.5 72.35 + 6528.5 72.58 + 6553.5 72.81 + 6578.4 73.05 + 6603.4 73.28 + 6628.4 73.51 + 6653.4 73.75 + 6678.3 73.98 + 6703.3 74.21 + 6728.3 74.44 + 6753.3 74.68 + 6778.2 74.91 + 6803.2 75.14 + 6828.2 75.37 + 6853.2 75.60 + 6878.1 75.84 + 6903.1 76.07 + 6928.1 76.30 + 6953.1 76.53 + 6978.0 76.76 + 7003.0 76.99 + 7028.0 77.22 + 7053.0 77.46 + 7077.9 77.69 + 7102.9 77.92 + 7127.9 78.15 + 7152.9 78.38 + 7177.8 78.61 + 7202.8 78.84 + 7227.8 79.07 + 7252.8 79.30 + 7277.7 79.53 + 7302.7 79.76 + 7327.7 79.99 + 7352.7 80.22 + 7377.6 80.45 + 7402.6 80.68 + 7427.6 80.91 + 7452.6 81.14 + 7477.5 81.37 + 7502.5 81.60 + 7527.5 81.83 + 7552.5 82.06 + 7577.4 82.29 + 7602.4 82.51 + 7627.4 82.74 + 7652.4 82.97 + 7677.3 83.20 + 7702.3 83.43 + 7727.3 83.66 + 7752.3 83.89 + 7777.2 84.12 + 7802.2 84.34 + 7827.2 84.57 + 7852.2 84.80 + 7877.1 85.03 + 7902.1 85.26 + 7927.1 85.48 + 7952.1 85.71 + 7977.0 85.94 + 8002.0 86.17 + 8027.0 86.39 + 8052.0 86.62 + 8076.9 86.85 + 8101.9 87.08 + 8126.9 87.30 + 8151.9 87.53 + 8176.8 87.76 + 8201.8 87.98 + 8226.8 88.21 + 8251.8 88.44 + 8276.7 88.66 + 8301.7 88.89 + 8326.7 89.12 + 8351.7 89.34 + 8376.6 89.57 + 8401.6 89.80 + 8426.6 90.02 + 8451.6 90.25 + 8476.5 90.47 + 8501.5 90.70 + 8526.5 90.93 + 8551.5 91.15 + 8576.4 91.38 + 8601.4 91.60 + 8626.4 91.83 + 8651.4 92.05 + 8676.3 92.28 + 8701.3 92.51 + 8726.3 92.73 + 8751.3 92.96 + 8776.2 93.18 + 8801.2 93.41 + 8826.2 93.63 + 8851.2 93.86 + 8876.1 94.08 + 8901.1 94.30 + 8926.1 94.53 + 8951.1 94.75 + 8976.0 94.98 + 9001.0 95.20 + 9026.0 95.43 + 9051.0 95.65 + 9075.9 95.88 + 9100.9 96.10 + 9125.9 96.32 + 9150.9 96.55 + 9175.8 96.77 + 9200.8 96.99 + 9225.8 97.22 + 9250.8 97.44 + 9275.7 97.67 + 9300.7 97.89 + 9325.7 98.11 + 9350.7 98.34 + 9375.6 98.56 + 9400.6 98.78 + 9425.6 99.01 + 9450.6 99.23 + 9475.5 99.45 + 9500.5 99.67 + 9525.5 99.90 + 9550.5 100.12 + 9575.4 100.34 + 9600.4 100.57 + 9625.4 100.79 + 9650.4 101.01 + 9675.3 101.23 + 9700.3 101.46 + 9725.3 101.68 + 9750.3 101.90 + 9775.2 102.12 + 9800.2 102.34 + 9825.2 102.57 + 9850.2 102.79 + 9875.1 103.01 + 9900.1 103.23 + 9925.1 103.45 + 9950.1 103.67 + 9975.0 103.90 + 10000.0 104.12 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/030_Zn_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/030_Zn_eIMFP.txt new file mode 100644 index 0000000..23ca4f3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/030_Zn_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Zn + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 65.39000 + +DENSITY: 7.1400 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.19 + 54.9 4.29 + 59.8 4.35 + 64.6 4.39 + 69.5 4.42 + 74.4 4.46 + 79.3 4.49 + 84.1 4.53 + 89.0 4.57 + 93.9 4.62 + 98.8 4.67 + 103.6 4.72 + 108.5 4.77 + 113.4 4.83 + 118.3 4.89 + 123.1 4.96 + 128.0 5.02 + 132.9 5.09 + 137.8 5.15 + 142.6 5.22 + 147.5 5.29 + 152.4 5.36 + 157.3 5.43 + 162.1 5.50 + 167.0 5.57 + 171.9 5.64 + 176.8 5.72 + 181.6 5.79 + 186.5 5.86 + 191.4 5.94 + 196.3 6.01 + 201.1 6.08 + 206.0 6.16 + 210.9 6.23 + 215.8 6.30 + 220.6 6.38 + 225.5 6.45 + 230.4 6.53 + 235.3 6.60 + 240.1 6.68 + 245.0 6.75 + 249.9 6.82 + 254.8 6.90 + 259.6 6.97 + 264.5 7.05 + 269.4 7.12 + 274.3 7.19 + 279.1 7.27 + 284.0 7.34 + 288.9 7.42 + 293.8 7.49 + 298.6 7.56 + 303.5 7.64 + 308.4 7.71 + 313.3 7.79 + 318.1 7.86 + 323.0 7.93 + 327.9 8.01 + 332.8 8.08 + 337.6 8.15 + 342.5 8.22 + 347.4 8.30 + 352.3 8.37 + 357.1 8.44 + 362.0 8.52 + 366.9 8.59 + 371.8 8.66 + 376.6 8.73 + 381.5 8.80 + 386.4 8.88 + 391.3 8.95 + 396.1 9.02 + 401.0 9.09 + 405.9 9.16 + 410.8 9.24 + 415.6 9.31 + 420.5 9.38 + 425.4 9.45 + 430.3 9.52 + 435.1 9.59 + 440.0 9.66 + 444.9 9.73 + 449.8 9.81 + 454.6 9.88 + 459.5 9.95 + 464.4 10.02 + 469.3 10.09 + 474.1 10.16 + 479.0 10.23 + 483.9 10.30 + 488.8 10.37 + 493.6 10.44 + 498.5 10.51 + 503.4 10.58 + 508.3 10.65 + 513.1 10.72 + 518.0 10.79 + 522.9 10.86 + 527.8 10.93 + 532.6 11.00 + 537.5 11.06 + 542.4 11.13 + 547.3 11.20 + 552.1 11.27 + 557.0 11.34 + 561.9 11.41 + 566.8 11.48 + 571.6 11.55 + 576.5 11.62 + 581.4 11.68 + 586.3 11.75 + 591.1 11.82 + 596.0 11.89 + 600.9 11.96 + 605.8 12.03 + 610.6 12.09 + 615.5 12.16 + 620.4 12.23 + 625.3 12.30 + 630.1 12.36 + 635.0 12.43 + 639.9 12.50 + 644.8 12.57 + 649.6 12.63 + 654.5 12.70 + 659.4 12.77 + 664.3 12.84 + 669.1 12.90 + 674.0 12.97 + 678.9 13.04 + 683.8 13.10 + 688.6 13.17 + 693.5 13.24 + 698.4 13.30 + 703.3 13.37 + 708.1 13.44 + 713.0 13.50 + 717.9 13.57 + 722.8 13.64 + 727.6 13.70 + 732.5 13.77 + 737.4 13.84 + 742.3 13.90 + 747.1 13.97 + 752.0 14.03 + 756.9 14.10 + 761.8 14.17 + 766.6 14.23 + 771.5 14.30 + 776.4 14.36 + 781.3 14.43 + 786.1 14.49 + 791.0 14.56 + 795.9 14.62 + 800.8 14.69 + 805.6 14.76 + 810.5 14.82 + 815.4 14.89 + 820.3 14.95 + 825.1 15.02 + 830.0 15.08 + 834.9 15.15 + 839.8 15.21 + 844.6 15.28 + 849.5 15.34 + 854.4 15.41 + 859.3 15.47 + 864.1 15.53 + 869.0 15.60 + 873.9 15.66 + 878.8 15.73 + 883.6 15.79 + 888.5 15.86 + 893.4 15.92 + 898.3 15.99 + 903.1 16.05 + 908.0 16.11 + 912.9 16.18 + 917.8 16.24 + 922.6 16.31 + 927.5 16.37 + 932.4 16.43 + 937.3 16.50 + 942.1 16.56 + 947.0 16.63 + 951.9 16.69 + 956.8 16.75 + 961.6 16.82 + 966.5 16.88 + 971.4 16.94 + 976.3 17.01 + 981.1 17.07 + 986.0 17.13 + 990.9 17.20 + 995.8 17.26 + 1000.6 17.32 + 1005.5 17.39 + 1010.4 17.45 + 1015.3 17.51 + 1020.1 17.58 + 1025.0 17.64 + 1029.9 17.70 + 1034.8 17.76 + 1039.6 17.83 + 1044.5 17.89 + 1049.4 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/031_Ga_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/031_Ga_2_eIMFP.txt new file mode 100644 index 0000000..406d936 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/031_Ga_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ga + +SOURCE: + Koch + Thesis, Eberhard-Karls-Universitat, Tubingen, Germany (1996) + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +ATOMIC WEIGHT: 69.72300 + +DENSITY: 5.9100 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/031_Ga_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/031_Ga_eIMFP.txt new file mode 100644 index 0000000..da014f8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/031_Ga_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ga + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 69.72300 + +DENSITY: 5.9100 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.81 + 54.9 4.86 + 59.8 4.91 + 64.6 4.97 + 69.5 5.04 + 74.4 5.11 + 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30.85 + 1458.9 30.94 + 1463.8 31.02 + 1468.6 31.10 + 1473.5 31.18 + 1478.4 31.26 + 1483.3 31.34 + 1488.1 31.42 + 1493.0 31.50 + 1497.9 31.58 + 1502.8 31.66 + 1507.6 31.74 + 1512.5 31.82 + 1517.4 31.90 + 1522.3 31.98 + 1527.1 32.06 + 1532.0 32.15 + 1536.9 32.23 + 1541.8 32.31 + 1546.6 32.39 + 1551.5 32.47 + 1556.4 32.55 + 1561.3 32.63 + 1566.1 32.71 + 1571.0 32.79 + 1575.9 32.87 + 1580.8 32.95 + 1585.6 33.03 + 1590.5 33.11 + 1595.4 33.19 + 1600.3 33.27 + 1605.1 33.35 + 1610.0 33.43 + 1614.9 33.51 + 1619.8 33.58 + 1624.6 33.66 + 1629.5 33.74 + 1634.4 33.82 + 1639.3 33.90 + 1644.1 33.98 + 1649.0 34.06 + 1653.9 34.14 + 1658.8 34.22 + 1663.6 34.30 + 1668.5 34.38 + 1673.4 34.46 + 1678.3 34.54 + 1683.1 34.62 + 1688.0 34.70 + 1692.9 34.78 + 1697.8 34.86 + 1702.6 34.93 + 1707.5 35.01 + 1712.4 35.09 + 1717.3 35.17 + 1722.1 35.25 + 1727.0 35.33 + 1731.9 35.41 + 1736.8 35.49 + 1741.6 35.57 + 1746.5 35.64 + 1751.4 35.72 + 1756.3 35.80 + 1761.1 35.88 + 1766.0 35.96 + 1770.9 36.04 + 1775.8 36.12 + 1780.6 36.20 + 1785.5 36.27 + 1790.4 36.35 + 1795.3 36.43 + 1800.1 36.51 + 1805.0 36.59 + 1809.9 36.67 + 1814.8 36.74 + 1819.6 36.82 + 1824.5 36.90 + 1829.4 36.98 + 1834.3 37.06 + 1839.1 37.14 + 1844.0 37.21 + 1848.9 37.29 + 1853.8 37.37 + 1858.6 37.45 + 1863.5 37.53 + 1868.4 37.60 + 1873.3 37.68 + 1878.1 37.76 + 1883.0 37.84 + 1887.9 37.92 + 1892.8 37.99 + 1897.6 38.07 + 1902.5 38.15 + 1907.4 38.23 + 1912.3 38.31 + 1917.1 38.38 + 1922.0 38.46 + 1926.9 38.54 + 1931.8 38.62 + 1936.6 38.69 + 1941.5 38.77 + 1946.4 38.85 + 1951.3 38.93 + 1956.1 39.00 + 1961.0 39.08 + 1965.9 39.16 + 1970.8 39.24 + 1975.6 39.31 + 1980.5 39.39 + 1985.4 39.47 + 1990.3 39.55 + 1995.1 39.62 + 2000.0 39.70 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/032_Ge_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/032_Ge_1_eIMFP.txt new file mode 100644 index 0000000..a5987b2 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/032_Ge_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ge + +SOURCE: + Tanuma, Powell and Penn + Unpublished data + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 72.61000 + +DENSITY: 5.3234 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 3.98 + 54.9 4.08 + 59.8 4.18 + 64.6 4.28 + 69.5 4.38 + 74.4 4.49 + 79.3 4.59 + 84.1 4.69 + 89.0 4.80 + 93.9 4.90 + 98.8 5.01 + 103.6 5.11 + 108.5 5.22 + 113.4 5.32 + 118.3 5.43 + 123.1 5.54 + 128.0 5.64 + 132.9 5.75 + 137.8 5.85 + 142.6 5.96 + 147.5 6.06 + 152.4 6.16 + 157.3 6.27 + 162.1 6.37 + 167.0 6.47 + 171.9 6.58 + 176.8 6.68 + 181.6 6.78 + 186.5 6.88 + 191.4 6.99 + 196.3 7.09 + 201.1 7.19 + 206.0 7.29 + 210.9 7.39 + 215.8 7.49 + 220.6 7.59 + 225.5 7.69 + 230.4 7.79 + 235.3 7.89 + 240.1 7.99 + 245.0 8.08 + 249.9 8.18 + 254.8 8.28 + 259.6 8.38 + 264.5 8.48 + 269.4 8.57 + 274.3 8.67 + 279.1 8.77 + 284.0 8.86 + 288.9 8.96 + 293.8 9.05 + 298.6 9.15 + 303.5 9.24 + 308.4 9.34 + 313.3 9.43 + 318.1 9.53 + 323.0 9.62 + 327.9 9.72 + 332.8 9.81 + 337.6 9.90 + 342.5 10.00 + 347.4 10.09 + 352.3 10.18 + 357.1 10.27 + 362.0 10.37 + 366.9 10.46 + 371.8 10.55 + 376.6 10.64 + 381.5 10.73 + 386.4 10.83 + 391.3 10.92 + 396.1 11.01 + 401.0 11.10 + 405.9 11.19 + 410.8 11.28 + 415.6 11.37 + 420.5 11.46 + 425.4 11.55 + 430.3 11.64 + 435.1 11.73 + 440.0 11.82 + 444.9 11.91 + 449.8 12.00 + 454.6 12.09 + 459.5 12.18 + 464.4 12.26 + 469.3 12.35 + 474.1 12.44 + 479.0 12.53 + 483.9 12.62 + 488.8 12.71 + 493.6 12.79 + 498.5 12.88 + 503.4 12.97 + 508.3 13.05 + 513.1 13.14 + 518.0 13.23 + 522.9 13.32 + 527.8 13.40 + 532.6 13.49 + 537.5 13.58 + 542.4 13.66 + 547.3 13.75 + 552.1 13.83 + 557.0 13.92 + 561.9 14.01 + 566.8 14.09 + 571.6 14.18 + 576.5 14.26 + 581.4 14.35 + 586.3 14.43 + 591.1 14.52 + 596.0 14.60 + 600.9 14.69 + 605.8 14.77 + 610.6 14.86 + 615.5 14.94 + 620.4 15.03 + 625.3 15.11 + 630.1 15.19 + 635.0 15.28 + 639.9 15.36 + 644.8 15.45 + 649.6 15.53 + 654.5 15.61 + 659.4 15.70 + 664.3 15.78 + 669.1 15.86 + 674.0 15.95 + 678.9 16.03 + 683.8 16.11 + 688.6 16.19 + 693.5 16.28 + 698.4 16.36 + 703.3 16.44 + 708.1 16.52 + 713.0 16.61 + 717.9 16.69 + 722.8 16.77 + 727.6 16.85 + 732.5 16.94 + 737.4 17.02 + 742.3 17.10 + 747.1 17.18 + 752.0 17.26 + 756.9 17.34 + 761.8 17.43 + 766.6 17.51 + 771.5 17.59 + 776.4 17.67 + 781.3 17.75 + 786.1 17.83 + 791.0 17.91 + 795.9 17.99 + 800.8 18.07 + 805.6 18.15 + 810.5 18.23 + 815.4 18.32 + 820.3 18.40 + 825.1 18.48 + 830.0 18.56 + 834.9 18.64 + 839.8 18.72 + 844.6 18.80 + 849.5 18.88 + 854.4 18.96 + 859.3 19.04 + 864.1 19.12 + 869.0 19.20 + 873.9 19.27 + 878.8 19.35 + 883.6 19.43 + 888.5 19.51 + 893.4 19.59 + 898.3 19.67 + 903.1 19.75 + 908.0 19.83 + 912.9 19.91 + 917.8 19.99 + 922.6 20.07 + 927.5 20.14 + 932.4 20.22 + 937.3 20.30 + 942.1 20.38 + 947.0 20.46 + 951.9 20.54 + 956.8 20.62 + 961.6 20.69 + 966.5 20.77 + 971.4 20.85 + 976.3 20.93 + 981.1 21.01 + 986.0 21.08 + 990.9 21.16 + 995.8 21.24 + 1000.6 21.32 + 1005.5 21.40 + 1010.4 21.47 + 1015.3 21.55 + 1020.1 21.63 + 1025.0 21.71 + 1029.9 21.78 + 1034.8 21.86 + 1039.6 21.94 + 1044.5 22.02 + 1049.4 22.09 + 1054.3 22.17 + 1059.1 22.25 + 1064.0 22.32 + 1068.9 22.40 + 1073.8 22.48 + 1078.6 22.55 + 1083.5 22.63 + 1088.4 22.71 + 1093.3 22.78 + 1098.1 22.86 + 1103.0 22.94 + 1107.9 23.01 + 1112.8 23.09 + 1117.6 23.17 + 1122.5 23.24 + 1127.4 23.32 + 1132.3 23.40 + 1137.1 23.47 + 1142.0 23.55 + 1146.9 23.62 + 1151.8 23.70 + 1156.6 23.78 + 1161.5 23.85 + 1166.4 23.93 + 1171.3 24.00 + 1176.1 24.08 + 1181.0 24.15 + 1185.9 24.23 + 1190.8 24.31 + 1195.6 24.38 + 1200.5 24.46 + 1205.4 24.53 + 1210.3 24.61 + 1215.1 24.68 + 1220.0 24.76 + 1224.9 24.83 + 1229.8 24.91 + 1234.6 24.98 + 1239.5 25.06 + 1244.4 25.13 + 1249.3 25.21 + 1254.1 25.28 + 1259.0 25.36 + 1263.9 25.43 + 1268.8 25.51 + 1273.6 25.58 + 1278.5 25.66 + 1283.4 25.73 + 1288.3 25.81 + 1293.1 25.88 + 1298.0 25.95 + 1302.9 26.03 + 1307.8 26.10 + 1312.6 26.18 + 1317.5 26.25 + 1322.4 26.33 + 1327.3 26.40 + 1332.1 26.48 + 1337.0 26.55 + 1341.9 26.62 + 1346.8 26.70 + 1351.6 26.77 + 1356.5 26.85 + 1361.4 26.92 + 1366.3 26.99 + 1371.1 27.07 + 1376.0 27.14 + 1380.9 27.21 + 1385.8 27.29 + 1390.6 27.36 + 1395.5 27.44 + 1400.4 27.51 + 1405.3 27.58 + 1410.1 27.66 + 1415.0 27.73 + 1419.9 27.80 + 1424.8 27.88 + 1429.6 27.95 + 1434.5 28.02 + 1439.4 28.10 + 1444.3 28.17 + 1449.1 28.24 + 1454.0 28.32 + 1458.9 28.39 + 1463.8 28.46 + 1468.6 28.54 + 1473.5 28.61 + 1478.4 28.68 + 1483.3 28.75 + 1488.1 28.83 + 1493.0 28.90 + 1497.9 28.97 + 1502.8 29.05 + 1507.6 29.12 + 1512.5 29.19 + 1517.4 29.26 + 1522.3 29.34 + 1527.1 29.41 + 1532.0 29.48 + 1536.9 29.55 + 1541.8 29.63 + 1546.6 29.70 + 1551.5 29.77 + 1556.4 29.84 + 1561.3 29.92 + 1566.1 29.99 + 1571.0 30.06 + 1575.9 30.13 + 1580.8 30.20 + 1585.6 30.28 + 1590.5 30.35 + 1595.4 30.42 + 1600.3 30.49 + 1605.1 30.56 + 1610.0 30.64 + 1614.9 30.71 + 1619.8 30.78 + 1624.6 30.85 + 1629.5 30.92 + 1634.4 31.00 + 1639.3 31.07 + 1644.1 31.14 + 1649.0 31.21 + 1653.9 31.28 + 1658.8 31.35 + 1663.6 31.43 + 1668.5 31.50 + 1673.4 31.57 + 1678.3 31.64 + 1683.1 31.71 + 1688.0 31.78 + 1692.9 31.85 + 1697.8 31.93 + 1702.6 32.00 + 1707.5 32.07 + 1712.4 32.14 + 1717.3 32.21 + 1722.1 32.28 + 1727.0 32.35 + 1731.9 32.42 + 1736.8 32.50 + 1741.6 32.57 + 1746.5 32.64 + 1751.4 32.71 + 1756.3 32.78 + 1761.1 32.85 + 1766.0 32.92 + 1770.9 32.99 + 1775.8 33.06 + 1780.6 33.13 + 1785.5 33.20 + 1790.4 33.28 + 1795.3 33.35 + 1800.1 33.42 + 1805.0 33.49 + 1809.9 33.56 + 1814.8 33.63 + 1819.6 33.70 + 1824.5 33.77 + 1829.4 33.84 + 1834.3 33.91 + 1839.1 33.98 + 1844.0 34.05 + 1848.9 34.12 + 1853.8 34.19 + 1858.6 34.26 + 1863.5 34.33 + 1868.4 34.40 + 1873.3 34.47 + 1878.1 34.54 + 1883.0 34.61 + 1887.9 34.68 + 1892.8 34.75 + 1897.6 34.82 + 1902.5 34.89 + 1907.4 34.96 + 1912.3 35.03 + 1917.1 35.10 + 1922.0 35.17 + 1926.9 35.24 + 1931.8 35.31 + 1936.6 35.38 + 1941.5 35.45 + 1946.4 35.52 + 1951.3 35.59 + 1956.1 35.66 + 1961.0 35.73 + 1965.9 35.80 + 1970.8 35.87 + 1975.6 35.94 + 1980.5 36.01 + 1985.4 36.08 + 1990.3 36.15 + 1995.1 36.22 + 2000.0 36.29 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/032_Ge_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/032_Ge_2_eIMFP.txt new file mode 100644 index 0000000..4022468 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/032_Ge_2_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Ge + +SOURCE: + Elastic peak electron spectroscopy + + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +COMMENT: + Gergely et al., Vacuum 48 (1997) 621 + +ATOMIC WEIGHT: 72.61000 + +DENSITY: 5.3234 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 100.0 4.76 + 112.3 5.13 + 124.5 5.48 + 136.8 5.82 + 149.0 6.15 + 161.3 6.47 + 173.5 6.78 + 185.8 7.08 + 198.0 7.38 + 210.3 7.66 + 222.5 7.95 + 234.8 8.22 + 247.0 8.50 + 259.3 8.76 + 271.5 9.03 + 283.8 9.29 + 296.0 9.54 + 308.3 9.79 + 320.5 10.04 + 332.8 10.28 + 345.0 10.52 + 357.3 10.76 + 369.5 11.00 + 381.8 11.23 + 394.0 11.46 + 406.3 11.68 + 418.5 11.91 + 430.8 12.13 + 443.0 12.35 + 455.3 12.57 + 467.5 12.78 + 479.8 13.00 + 492.0 13.21 + 504.3 13.42 + 516.5 13.62 + 528.8 13.83 + 541.0 14.03 + 553.3 14.24 + 565.5 14.44 + 577.8 14.64 + 590.0 14.83 + 602.3 15.03 + 614.5 15.23 + 626.8 15.42 + 639.0 15.61 + 651.3 15.80 + 663.5 15.99 + 675.8 16.18 + 688.0 16.37 + 700.3 16.55 + 712.5 16.74 + 724.8 16.92 + 737.0 17.10 + 749.3 17.29 + 761.5 17.47 + 773.8 17.65 + 786.0 17.82 + 798.3 18.00 + 810.5 18.18 + 822.8 18.35 + 835.0 18.53 + 847.3 18.70 + 859.5 18.87 + 871.8 19.05 + 884.0 19.22 + 896.3 19.39 + 908.5 19.56 + 920.8 19.72 + 933.0 19.89 + 945.3 20.06 + 957.5 20.22 + 969.8 20.39 + 982.0 20.55 + 994.3 20.72 + 1006.5 20.88 + 1018.8 21.04 + 1031.0 21.20 + 1043.3 21.37 + 1055.5 21.53 + 1067.8 21.69 + 1080.0 21.84 + 1092.3 22.00 + 1104.5 22.16 + 1116.8 22.32 + 1129.0 22.47 + 1141.3 22.63 + 1153.5 22.78 + 1165.8 22.94 + 1178.0 23.09 + 1190.3 23.25 + 1202.5 23.40 + 1214.8 23.55 + 1227.0 23.70 + 1239.3 23.85 + 1251.5 24.00 + 1263.8 24.15 + 1276.0 24.30 + 1288.3 24.45 + 1300.5 24.60 + 1312.8 24.75 + 1325.0 24.90 + 1337.3 25.04 + 1349.5 25.19 + 1361.8 25.34 + 1374.0 25.48 + 1386.3 25.63 + 1398.5 25.77 + 1410.8 25.92 + 1423.0 26.06 + 1435.3 26.20 + 1447.5 26.35 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of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +COMMENT: + Lesiak et al., Proc. ECASIA 95, Wiley, Chichester (1996), p. 619 + +ATOMIC WEIGHT: 72.61000 + +DENSITY: 5.3234 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 100.0 5.15 + 103.5 5.26 + 107.0 5.36 + 110.5 5.47 + 114.0 5.57 + 117.5 5.68 + 121.0 5.78 + 124.5 5.88 + 128.0 5.98 + 131.5 6.08 + 135.0 6.17 + 138.5 6.27 + 142.0 6.36 + 145.5 6.46 + 149.0 6.55 + 152.5 6.64 + 156.0 6.74 + 159.5 6.83 + 163.0 6.92 + 166.5 7.01 + 170.0 7.10 + 173.5 7.18 + 177.0 7.27 + 180.5 7.36 + 184.0 7.44 + 187.5 7.53 + 191.0 7.61 + 194.5 7.70 + 198.0 7.78 + 201.5 7.86 + 205.0 7.94 + 208.5 8.03 + 212.0 8.11 + 215.5 8.19 + 219.0 8.27 + 222.5 8.35 + 226.0 8.43 + 229.5 8.51 + 233.0 8.58 + 236.5 8.66 + 240.0 8.74 + 243.5 8.82 + 247.0 8.89 + 250.5 8.97 + 254.0 9.04 + 257.5 9.12 + 261.0 9.19 + 264.5 9.27 + 268.0 9.34 + 271.5 9.41 + 275.0 9.49 + 278.5 9.56 + 282.0 9.63 + 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1500.0 26.43 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/032_Ge_4_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/032_Ge_4_eIMFP.txt new file mode 100644 index 0000000..ea93ccc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/032_Ge_4_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Ge + +SOURCE: + Elastic peak electron spectroscopy + + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +COMMENT: + Koch, Thesis, Eberhard-Karls-Universitat, Tubingen, Germany (1996) + +ATOMIC WEIGHT: 72.61000 + +DENSITY: 5.3234 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/033_As_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/033_As_eIMFP.txt new file mode 100644 index 0000000..de74646 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/033_As_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + As + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 74.92160 + +DENSITY: 5.7500 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.59 + 54.9 4.62 + 59.8 4.65 + 64.6 4.69 + 69.5 4.73 + 74.4 4.78 + 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100644 index 0000000..3b5fd9c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/034_Se_1_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Se + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +COMMENT: + Alpha selenium (density equal to 4.39 g/cm**3) + +ATOMIC WEIGHT: 78.96000 + +DENSITY: 4.3900 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.41 + 54.9 4.49 + 59.8 4.56 + 64.6 4.63 + 69.5 4.70 + 74.4 4.77 + 79.3 4.85 + 84.1 4.94 + 89.0 5.02 + 93.9 5.11 + 98.8 5.20 + 103.6 5.29 + 108.5 5.39 + 113.4 5.48 + 118.3 5.58 + 123.1 5.68 + 128.0 5.78 + 132.9 5.88 + 137.8 5.98 + 142.6 6.08 + 147.5 6.18 + 152.4 6.28 + 157.3 6.38 + 162.1 6.48 + 167.0 6.58 + 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Se + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +COMMENT: + Vitreous selenium (density equal to 4.28 g/cm**3) + +ATOMIC WEIGHT: 78.96000 + +DENSITY: 4.2800 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.40 + 54.9 4.48 + 59.8 4.55 + 64.6 4.62 + 69.5 4.70 + 74.4 4.78 + 79.3 4.86 + 84.1 4.95 + 89.0 5.03 + 93.9 5.12 + 98.8 5.22 + 103.6 5.31 + 108.5 5.41 + 113.4 5.51 + 118.3 5.60 + 123.1 5.70 + 128.0 5.80 + 132.9 5.90 + 137.8 6.01 + 142.6 6.11 + 147.5 6.21 + 152.4 6.31 + 157.3 6.41 + 162.1 6.52 + 167.0 6.62 + 171.9 6.72 + 176.8 6.82 + 181.6 6.92 + 186.5 7.03 + 191.4 7.13 + 196.3 7.23 + 201.1 7.33 + 206.0 7.44 + 210.9 7.54 + 215.8 7.64 + 220.6 7.74 + 225.5 7.84 + 230.4 7.94 + 235.3 8.05 + 240.1 8.15 + 245.0 8.25 + 249.9 8.35 + 254.8 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37.25 + 1936.6 37.33 + 1941.5 37.40 + 1946.4 37.48 + 1951.3 37.55 + 1956.1 37.63 + 1961.0 37.70 + 1965.9 37.78 + 1970.8 37.85 + 1975.6 37.93 + 1980.5 38.00 + 1985.4 38.08 + 1990.3 38.15 + 1995.1 38.23 + 2000.0 38.30 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/034_Se_3_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/034_Se_3_eIMFP.txt new file mode 100644 index 0000000..5235982 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/034_Se_3_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Se + +SOURCE: + Gries + Surface Interface Anal. 24 (1996) 38. + Predictive formula based on calculated IMFPs of Tanuma et al. + and an atomistic model (G-1 equation) + +COMMENT: + Gray selenium (density equal to 4.81 g/cm**3) + +ATOMIC WEIGHT: 78.96000 + +DENSITY: 4.8100 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 200.0 6.56 + 204.5 6.66 + 209.0 6.75 + 213.5 6.84 + 218.0 6.94 + 222.5 7.03 + 227.0 7.12 + 231.5 7.22 + 236.0 7.31 + 240.5 7.40 + 245.0 7.49 + 249.5 7.58 + 254.0 7.67 + 258.5 7.76 + 263.0 7.85 + 267.5 7.94 + 272.0 8.03 + 276.5 8.12 + 281.0 8.21 + 285.5 8.30 + 290.0 8.39 + 294.5 8.48 + 299.0 8.57 + 303.5 8.65 + 308.0 8.74 + 312.5 8.83 + 317.0 8.92 + 321.5 9.00 + 326.0 9.09 + 330.5 9.18 + 335.0 9.27 + 339.5 9.35 + 344.0 9.44 + 348.5 9.52 + 353.0 9.61 + 357.5 9.70 + 362.0 9.78 + 366.5 9.87 + 371.0 9.95 + 375.5 10.04 + 380.0 10.12 + 384.5 10.21 + 389.0 10.29 + 393.5 10.37 + 398.0 10.46 + 402.5 10.54 + 407.0 10.63 + 411.5 10.71 + 416.0 10.79 + 420.5 10.88 + 425.0 10.96 + 429.5 11.04 + 434.0 11.13 + 438.5 11.21 + 443.0 11.29 + 447.5 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35.56 + 1986.5 35.62 + 1991.0 35.68 + 1995.5 35.75 + 2000.0 35.81 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/037_Rb_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/037_Rb_eIMFP.txt new file mode 100644 index 0000000..056aa07 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/037_Rb_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Rb + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 85.46780 + +DENSITY: 1.5300 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms 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Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/038_Sr_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/038_Sr_eIMFP.txt new file mode 100644 index 0000000..897bc85 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/038_Sr_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Sr + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 87.62000 + +DENSITY: 2.6400 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.66 + 54.9 5.88 + 59.8 6.09 + 64.6 6.30 + 69.5 6.51 + 74.4 6.72 + 79.3 6.93 + 84.1 7.14 + 89.0 7.34 + 93.9 7.55 + 98.8 7.76 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0000000..156acf0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/039_Y_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Y + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 88.90585 + +DENSITY: 4.4700 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.96 + 54.9 4.93 + 59.8 4.93 + 64.6 4.96 + 69.5 5.00 + 74.4 5.06 + 79.3 5.12 + 84.1 5.20 + 89.0 5.28 + 93.9 5.37 + 98.8 5.46 + 103.6 5.55 + 108.5 5.65 + 113.4 5.75 + 118.3 5.85 + 123.1 5.95 + 128.0 6.06 + 132.9 6.16 + 137.8 6.27 + 142.6 6.37 + 147.5 6.48 + 152.4 6.59 + 157.3 6.69 + 162.1 6.80 + 167.0 6.91 + 171.9 7.02 + 176.8 7.12 + 181.6 7.23 + 186.5 7.34 + 191.4 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35.24 + 1975.6 35.31 + 1980.5 35.38 + 1985.4 35.45 + 1990.3 35.52 + 1995.1 35.59 + 2000.0 35.66 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/041_Nb_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/041_Nb_eIMFP.txt new file mode 100644 index 0000000..c94ae60 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/041_Nb_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Nb + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 92.90638 + +DENSITY: 8.5700 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/042_Mo_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/042_Mo_1_eIMFP.txt new file mode 100644 index 0000000..ecb2cb0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/042_Mo_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Mo + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 95.94000 + +DENSITY: 10.2000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.11 + 54.9 4.84 + 59.8 4.66 + 64.6 4.54 + 69.5 4.46 + 74.4 4.42 + 79.3 4.40 + 84.1 4.40 + 89.0 4.41 + 93.9 4.43 + 98.8 4.46 + 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/042_Mo_2_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Mo + +SOURCE: + Elastic peak electron spectroscopy + + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +COMMENT: + Gergely et al., Surface Sci. 331-333 (1995) 1203 + +ATOMIC WEIGHT: 95.94000 + +DENSITY: 10.2000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 500.0 7.46 + 506.3 7.53 + 512.5 7.61 + 518.8 7.68 + 525.0 7.75 + 531.3 7.82 + 537.5 7.89 + 543.8 7.96 + 550.0 8.03 + 556.3 8.10 + 562.5 8.17 + 568.8 8.24 + 575.0 8.31 + 581.3 8.38 + 587.5 8.45 + 593.8 8.51 + 600.0 8.58 + 606.3 8.65 + 612.5 8.72 + 618.8 8.79 + 625.0 8.86 + 631.3 8.92 + 637.5 8.99 + 643.8 9.06 + 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/042_Mo_3_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Mo + +SOURCE: + Elastic peak electron spectroscopy + + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +COMMENT: + Lesiak et al., Proc. ECASIA 95, Wiley, Chichester (1996), p. 619 + +ATOMIC WEIGHT: 95.94000 + +DENSITY: 10.2000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.44 + 54.9 4.62 + 59.8 4.79 + 64.6 4.95 + 69.5 5.11 + 74.4 5.26 + 79.3 5.40 + 84.1 5.54 + 89.0 5.67 + 93.9 5.80 + 98.8 5.93 + 103.6 6.05 + 108.5 6.17 + 113.4 6.29 + 118.3 6.40 + 123.1 6.51 + 128.0 6.62 + 132.9 6.73 + 137.8 6.83 + 142.6 6.93 + 147.5 7.03 + 152.4 7.13 + 157.3 7.23 + 162.1 7.32 + 167.0 7.41 + 171.9 7.50 + 176.8 7.59 + 181.6 7.68 + 186.5 7.77 + 191.4 7.85 + 196.3 7.94 + 201.1 8.02 + 206.0 8.10 + 210.9 8.19 + 215.8 8.26 + 220.6 8.34 + 225.5 8.42 + 230.4 8.50 + 235.3 8.57 + 240.1 8.65 + 245.0 8.72 + 249.9 8.80 + 254.8 8.87 + 259.6 8.94 + 264.5 9.01 + 269.4 9.08 + 274.3 9.15 + 279.1 9.22 + 284.0 9.29 + 288.9 9.36 + 293.8 9.42 + 298.6 9.49 + 303.5 9.55 + 308.4 9.62 + 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21.21 + 1985.4 21.23 + 1990.3 21.25 + 1995.1 21.27 + 2000.0 21.29 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/044_Ru_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/044_Ru_eIMFP.txt new file mode 100644 index 0000000..8a53444 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/044_Ru_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ru + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 101.07000 + +DENSITY: 12.1000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/045_Rh_eIMFP.txt new file mode 100644 index 0000000..a0671b6 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/045_Rh_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Rh + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 102.90550 + +DENSITY: 12.4000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.79 + 54.9 4.60 + 59.8 4.44 + 64.6 4.31 + 69.5 4.21 + 74.4 4.15 + 79.3 4.10 + 84.1 4.08 + 89.0 4.07 + 93.9 4.07 + 98.8 4.07 + 103.6 4.09 + 108.5 4.11 + 113.4 4.14 + 118.3 4.17 + 123.1 4.21 + 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17.47 + 951.9 17.54 + 956.8 17.61 + 961.6 17.67 + 966.5 17.74 + 971.4 17.81 + 976.3 17.87 + 981.1 17.94 + 986.0 18.01 + 990.9 18.07 + 995.8 18.14 + 1000.6 18.21 + 1005.5 18.27 + 1010.4 18.34 + 1015.3 18.41 + 1020.1 18.47 + 1025.0 18.54 + 1029.9 18.60 + 1034.8 18.67 + 1039.6 18.74 + 1044.5 18.80 + 1049.4 18.87 + 1054.3 18.93 + 1059.1 19.00 + 1064.0 19.07 + 1068.9 19.13 + 1073.8 19.20 + 1078.6 19.26 + 1083.5 19.33 + 1088.4 19.39 + 1093.3 19.46 + 1098.1 19.53 + 1103.0 19.59 + 1107.9 19.66 + 1112.8 19.72 + 1117.6 19.79 + 1122.5 19.85 + 1127.4 19.92 + 1132.3 19.98 + 1137.1 20.05 + 1142.0 20.11 + 1146.9 20.18 + 1151.8 20.24 + 1156.6 20.31 + 1161.5 20.37 + 1166.4 20.44 + 1171.3 20.50 + 1176.1 20.57 + 1181.0 20.63 + 1185.9 20.70 + 1190.8 20.76 + 1195.6 20.83 + 1200.5 20.89 + 1205.4 20.96 + 1210.3 21.02 + 1215.1 21.08 + 1220.0 21.15 + 1224.9 21.21 + 1229.8 21.28 + 1234.6 21.34 + 1239.5 21.41 + 1244.4 21.47 + 1249.3 21.53 + 1254.1 21.60 + 1259.0 21.66 + 1263.9 21.73 + 1268.8 21.79 + 1273.6 21.85 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26.07 + 1605.1 26.13 + 1610.0 26.19 + 1614.9 26.25 + 1619.8 26.31 + 1624.6 26.37 + 1629.5 26.44 + 1634.4 26.50 + 1639.3 26.56 + 1644.1 26.62 + 1649.0 26.68 + 1653.9 26.74 + 1658.8 26.80 + 1663.6 26.87 + 1668.5 26.93 + 1673.4 26.99 + 1678.3 27.05 + 1683.1 27.11 + 1688.0 27.17 + 1692.9 27.23 + 1697.8 27.30 + 1702.6 27.36 + 1707.5 27.42 + 1712.4 27.48 + 1717.3 27.54 + 1722.1 27.60 + 1727.0 27.66 + 1731.9 27.72 + 1736.8 27.78 + 1741.6 27.85 + 1746.5 27.91 + 1751.4 27.97 + 1756.3 28.03 + 1761.1 28.09 + 1766.0 28.15 + 1770.9 28.21 + 1775.8 28.27 + 1780.6 28.33 + 1785.5 28.39 + 1790.4 28.45 + 1795.3 28.51 + 1800.1 28.58 + 1805.0 28.64 + 1809.9 28.70 + 1814.8 28.76 + 1819.6 28.82 + 1824.5 28.88 + 1829.4 28.94 + 1834.3 29.00 + 1839.1 29.06 + 1844.0 29.12 + 1848.9 29.18 + 1853.8 29.24 + 1858.6 29.30 + 1863.5 29.36 + 1868.4 29.42 + 1873.3 29.48 + 1878.1 29.54 + 1883.0 29.60 + 1887.9 29.66 + 1892.8 29.72 + 1897.6 29.78 + 1902.5 29.84 + 1907.4 29.91 + 1912.3 29.97 + 1917.1 30.03 + 1922.0 30.09 + 1926.9 30.15 + 1931.8 30.21 + 1936.6 30.27 + 1941.5 30.33 + 1946.4 30.39 + 1951.3 30.45 + 1956.1 30.51 + 1961.0 30.57 + 1965.9 30.63 + 1970.8 30.69 + 1975.6 30.75 + 1980.5 30.81 + 1985.4 30.87 + 1990.3 30.92 + 1995.1 30.98 + 2000.0 31.04 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/046_Pd_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/046_Pd_2_eIMFP.txt new file mode 100644 index 0000000..4e31ede --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/046_Pd_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Pd + +SOURCE: + Kwei, Chen, Tung and Wang + Surface Sci. 293 (1993) 202; Y. F. Chen, Private communication + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 106.42000 + +DENSITY: 12.0000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 100.0 4.90 + 104.8 4.90 + 109.5 4.91 + 114.3 4.93 + 119.0 4.95 + 123.8 4.98 + 128.5 5.02 + 133.3 5.05 + 138.0 5.10 + 142.8 5.14 + 147.5 5.19 + 152.3 5.23 + 157.0 5.29 + 161.8 5.34 + 166.5 5.39 + 171.3 5.45 + 176.0 5.51 + 180.8 5.57 + 185.5 5.63 + 190.3 5.69 + 195.0 5.75 + 199.8 5.82 + 204.5 5.88 + 209.3 5.95 + 214.0 6.01 + 218.8 6.08 + 223.5 6.15 + 228.3 6.22 + 233.0 6.28 + 237.8 6.35 + 242.5 6.42 + 247.3 6.49 + 252.0 6.56 + 256.8 6.63 + 261.5 6.70 + 266.3 6.77 + 271.0 6.84 + 275.8 6.91 + 280.5 6.99 + 285.3 7.06 + 290.0 7.13 + 294.8 7.20 + 299.5 7.27 + 304.3 7.34 + 309.0 7.42 + 313.8 7.49 + 318.5 7.56 + 323.3 7.63 + 328.0 7.71 + 332.8 7.78 + 337.5 7.85 + 342.3 7.92 + 347.0 8.00 + 351.8 8.07 + 356.5 8.14 + 361.3 8.21 + 366.0 8.29 + 370.8 8.36 + 375.5 8.43 + 380.3 8.50 + 385.0 8.58 + 389.8 8.65 + 394.5 8.72 + 399.3 8.79 + 404.0 8.87 + 408.8 8.94 + 413.5 9.01 + 418.3 9.08 + 423.0 9.16 + 427.8 9.23 + 432.5 9.30 + 437.3 9.37 + 442.0 9.44 + 446.8 9.52 + 451.5 9.59 + 456.3 9.66 + 461.0 9.73 + 465.8 9.81 + 470.5 9.88 + 475.3 9.95 + 480.0 10.02 + 484.8 10.09 + 489.5 10.16 + 494.3 10.24 + 499.0 10.31 + 503.8 10.38 + 508.5 10.45 + 513.3 10.52 + 518.0 10.59 + 522.8 10.66 + 527.5 10.74 + 532.3 10.81 + 537.0 10.88 + 541.8 10.95 + 546.5 11.02 + 551.3 11.09 + 556.0 11.16 + 560.8 11.23 + 565.5 11.30 + 570.3 11.37 + 575.0 11.45 + 579.8 11.52 + 584.5 11.59 + 589.3 11.66 + 594.0 11.73 + 598.8 11.80 + 603.5 11.87 + 608.3 11.94 + 613.0 12.01 + 617.8 12.08 + 622.5 12.15 + 627.3 12.22 + 632.0 12.29 + 636.8 12.36 + 641.5 12.43 + 646.3 12.50 + 651.0 12.57 + 655.8 12.64 + 660.5 12.71 + 665.3 12.77 + 670.0 12.84 + 674.8 12.91 + 679.5 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17.74 + 1021.5 17.81 + 1026.3 17.87 + 1031.0 17.94 + 1035.8 18.00 + 1040.5 18.07 + 1045.3 18.13 + 1050.0 18.20 + 1054.8 18.26 + 1059.5 18.33 + 1064.3 18.39 + 1069.0 18.46 + 1073.8 18.52 + 1078.5 18.59 + 1083.3 18.65 + 1088.0 18.71 + 1092.8 18.78 + 1097.5 18.84 + 1102.3 18.91 + 1107.0 18.97 + 1111.8 19.04 + 1116.5 19.10 + 1121.3 19.16 + 1126.0 19.23 + 1130.8 19.29 + 1135.5 19.36 + 1140.3 19.42 + 1145.0 19.48 + 1149.8 19.55 + 1154.5 19.61 + 1159.3 19.68 + 1164.0 19.74 + 1168.8 19.80 + 1173.5 19.87 + 1178.3 19.93 + 1183.0 19.99 + 1187.8 20.06 + 1192.5 20.12 + 1197.3 20.18 + 1202.0 20.25 + 1206.8 20.31 + 1211.5 20.37 + 1216.3 20.44 + 1221.0 20.50 + 1225.8 20.56 + 1230.5 20.63 + 1235.3 20.69 + 1240.0 20.75 + 1244.8 20.81 + 1249.5 20.88 + 1254.3 20.94 + 1259.0 21.00 + 1263.8 21.07 + 1268.5 21.13 + 1273.3 21.19 + 1278.0 21.25 + 1282.8 21.32 + 1287.5 21.38 + 1292.3 21.44 + 1297.0 21.50 + 1301.8 21.57 + 1306.5 21.63 + 1311.3 21.69 + 1316.0 21.75 + 1320.8 21.82 + 1325.5 21.88 + 1330.3 21.94 + 1335.0 22.00 + 1339.8 22.07 + 1344.5 22.13 + 1349.3 22.19 + 1354.0 22.25 + 1358.8 22.31 + 1363.5 22.38 + 1368.3 22.44 + 1373.0 22.50 + 1377.8 22.56 + 1382.5 22.62 + 1387.3 22.69 + 1392.0 22.75 + 1396.8 22.81 + 1401.5 22.87 + 1406.3 22.93 + 1411.0 22.99 + 1415.8 23.06 + 1420.5 23.12 + 1425.3 23.18 + 1430.0 23.24 + 1434.8 23.30 + 1439.5 23.36 + 1444.3 23.42 + 1449.0 23.49 + 1453.8 23.55 + 1458.5 23.61 + 1463.3 23.67 + 1468.0 23.73 + 1472.8 23.79 + 1477.5 23.85 + 1482.3 23.91 + 1487.0 23.97 + 1491.8 24.04 + 1496.5 24.10 + 1501.3 24.16 + 1506.0 24.22 + 1510.8 24.28 + 1515.5 24.34 + 1520.3 24.40 + 1525.0 24.46 + 1529.8 24.52 + 1534.5 24.58 + 1539.3 24.64 + 1544.0 24.70 + 1548.8 24.76 + 1553.5 24.83 + 1558.3 24.89 + 1563.0 24.95 + 1567.8 25.01 + 1572.5 25.07 + 1577.3 25.13 + 1582.0 25.19 + 1586.8 25.25 + 1591.5 25.31 + 1596.3 25.37 + 1601.0 25.43 + 1605.8 25.49 + 1610.5 25.55 + 1615.3 25.61 + 1620.0 25.67 + 1624.8 25.73 + 1629.5 25.79 + 1634.3 25.85 + 1639.0 25.91 + 1643.8 25.97 + 1648.5 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1966.8 29.98 + 1971.5 30.04 + 1976.3 30.09 + 1981.0 30.15 + 1985.8 30.21 + 1990.5 30.27 + 1995.3 30.33 + 2000.0 30.38 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/046_Pd_3_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/046_Pd_3_eIMFP.txt new file mode 100644 index 0000000..cc862f5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/046_Pd_3_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Pd + +SOURCE: + Krawczyk et al. + Surface Interface Anal. 25 (1997) 356 + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +ATOMIC WEIGHT: 106.42000 + +DENSITY: 12.0000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 200.0 7.04 + 202.0 7.07 + 204.0 7.10 + 206.0 7.13 + 208.0 7.15 + 210.0 7.18 + 212.0 7.21 + 214.0 7.23 + 216.0 7.26 + 218.0 7.29 + 220.0 7.31 + 222.0 7.34 + 224.0 7.36 + 226.0 7.39 + 228.0 7.42 + 230.0 7.44 + 232.0 7.47 + 234.0 7.49 + 236.0 7.52 + 238.0 7.54 + 240.0 7.57 + 242.0 7.59 + 244.0 7.62 + 246.0 7.64 + 248.0 7.67 + 250.0 7.69 + 252.0 7.71 + 254.0 7.74 + 256.0 7.76 + 258.0 7.79 + 260.0 7.81 + 262.0 7.83 + 264.0 7.86 + 266.0 7.88 + 268.0 7.90 + 270.0 7.93 + 272.0 7.95 + 274.0 7.97 + 276.0 7.99 + 278.0 8.02 + 280.0 8.04 + 282.0 8.06 + 284.0 8.08 + 286.0 8.11 + 288.0 8.13 + 290.0 8.15 + 292.0 8.17 + 294.0 8.20 + 296.0 8.22 + 298.0 8.24 + 300.0 8.26 + 302.0 8.28 + 304.0 8.30 + 306.0 8.32 + 308.0 8.35 + 310.0 8.37 + 312.0 8.39 + 314.0 8.41 + 316.0 8.43 + 318.0 8.45 + 320.0 8.47 + 322.0 8.49 + 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0000000..6d80165 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/047_Ag_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ag + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 107.86820 + +DENSITY: 10.5000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 6.12 + 54.9 5.97 + 59.8 5.74 + 64.6 5.52 + 69.5 5.32 + 74.4 5.17 + 79.3 5.04 + 84.1 4.95 + 89.0 4.88 + 93.9 4.83 + 98.8 4.79 + 103.6 4.77 + 108.5 4.76 + 113.4 4.76 + 118.3 4.77 + 123.1 4.78 + 128.0 4.80 + 132.9 4.82 + 137.8 4.85 + 142.6 4.88 + 147.5 4.92 + 152.4 4.95 + 157.3 4.99 + 162.1 5.03 + 167.0 5.08 + 171.9 5.12 + 176.8 5.17 + 181.6 5.21 + 186.5 5.26 + 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1897.6 22.99 + 1902.5 23.04 + 1907.4 23.08 + 1912.3 23.13 + 1917.1 23.18 + 1922.0 23.22 + 1926.9 23.27 + 1931.8 23.31 + 1936.6 23.36 + 1941.5 23.40 + 1946.4 23.45 + 1951.3 23.50 + 1956.1 23.54 + 1961.0 23.59 + 1965.9 23.63 + 1970.8 23.68 + 1975.6 23.72 + 1980.5 23.77 + 1985.4 23.81 + 1990.3 23.86 + 1995.1 23.91 + 2000.0 23.95 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/047_Ag_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/047_Ag_2_eIMFP.txt new file mode 100644 index 0000000..6dfd4d2 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/047_Ag_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ag + +SOURCE: + Powell and Jablonski + J. Phys. Chem. Reference Data 28 (1999) 19 + Evaluation of calculated and measured IMFP values + + +ATOMIC WEIGHT: 107.86820 + +DENSITY: 10.5000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 6.43 + 74.9 5.10 + 99.8 4.70 + 124.6 4.65 + 149.5 4.77 + 174.4 4.96 + 199.3 5.21 + 224.1 5.48 + 249.0 5.77 + 273.9 6.07 + 298.8 6.38 + 323.6 6.70 + 348.5 7.01 + 373.4 7.33 + 398.3 7.65 + 423.1 7.96 + 448.0 8.28 + 472.9 8.60 + 497.8 8.91 + 522.6 9.22 + 547.5 9.54 + 572.4 9.85 + 597.3 10.16 + 622.1 10.46 + 647.0 10.77 + 671.9 11.07 + 696.8 11.37 + 721.6 11.67 + 746.5 11.97 + 771.4 12.27 + 796.3 12.56 + 821.1 12.86 + 846.0 13.15 + 870.9 13.44 + 895.8 13.73 + 920.6 14.02 + 945.5 14.30 + 970.4 14.59 + 995.3 14.87 + 1020.1 15.15 + 1045.0 15.44 + 1069.9 15.72 + 1094.8 15.99 + 1119.6 16.27 + 1144.5 16.55 + 1169.4 16.82 + 1194.3 17.10 + 1219.1 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/049_In_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/049_In_eIMFP.txt new file mode 100644 index 0000000..fdf63f3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/049_In_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + In + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 114.81800 + +DENSITY: 7.3100 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.39 + 54.9 5.42 + 59.8 5.46 + 64.6 5.52 + 69.5 5.58 + 74.4 5.65 + 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/050_Sn_1_eIMFP.txt new file mode 100644 index 0000000..b7d4d10 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/050_Sn_1_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Sn + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +COMMENT: + White tin + +ATOMIC WEIGHT: 118.71000 + +DENSITY: 7.2650 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.12 + 54.9 5.14 + 59.8 5.16 + 64.6 5.20 + 69.5 5.25 + 74.4 5.31 + 79.3 5.38 + 84.1 5.45 + 89.0 5.53 + 93.9 5.61 + 98.8 5.70 + 103.6 5.79 + 108.5 5.89 + 113.4 5.98 + 118.3 6.08 + 123.1 6.18 + 128.0 6.28 + 132.9 6.38 + 137.8 6.48 + 142.6 6.58 + 147.5 6.69 + 152.4 6.79 + 157.3 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1848.9 37.21 + 1853.8 37.29 + 1858.6 37.37 + 1863.5 37.44 + 1868.4 37.52 + 1873.3 37.60 + 1878.1 37.68 + 1883.0 37.75 + 1887.9 37.83 + 1892.8 37.91 + 1897.6 37.98 + 1902.5 38.06 + 1907.4 38.14 + 1912.3 38.22 + 1917.1 38.29 + 1922.0 38.37 + 1926.9 38.45 + 1931.8 38.52 + 1936.6 38.60 + 1941.5 38.68 + 1946.4 38.76 + 1951.3 38.83 + 1956.1 38.91 + 1961.0 38.99 + 1965.9 39.06 + 1970.8 39.14 + 1975.6 39.22 + 1980.5 39.29 + 1985.4 39.37 + 1990.3 39.45 + 1995.1 39.52 + 2000.0 39.60 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/050_Sn_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/050_Sn_2_eIMFP.txt new file mode 100644 index 0000000..d082692 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/050_Sn_2_eIMFP.txt @@ 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42.20 + 1936.6 42.28 + 1941.5 42.37 + 1946.4 42.45 + 1951.3 42.54 + 1956.1 42.62 + 1961.0 42.71 + 1965.9 42.79 + 1970.8 42.88 + 1975.6 42.96 + 1980.5 43.04 + 1985.4 43.13 + 1990.3 43.21 + 1995.1 43.30 + 2000.0 43.38 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/052_Te_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/052_Te_1_eIMFP.txt new file mode 100644 index 0000000..8de483d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/052_Te_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Te + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 127.60000 + +DENSITY: 6.2400 g/cm**3 + +TABULATION: + 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/052_Te_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/052_Te_2_eIMFP.txt new file mode 100644 index 0000000..6cbd94e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/052_Te_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Te + +SOURCE: + Koch + Thesis, Eberhard-Karls-Universitat, Tubingen, Germany (1996) + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +ATOMIC WEIGHT: 127.60000 + +DENSITY: 6.2400 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms 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39.03 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/055_Cs_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/055_Cs_eIMFP.txt new file mode 100644 index 0000000..7a19cb4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/055_Cs_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Cs + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 132.90545 + +DENSITY: 1.9300 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 9.11 + 54.9 9.52 + 59.8 9.93 + 64.6 10.33 + 69.5 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/056_Ba_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/056_Ba_eIMFP.txt new file mode 100644 index 0000000..827cabc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/056_Ba_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ba + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 137.32700 + +DENSITY: 3.6200 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 6.42 + 54.9 6.63 + 59.8 6.84 + 64.6 7.06 + 69.5 7.27 + 74.4 7.48 + 79.3 7.70 + 84.1 7.91 + 89.0 8.13 + 93.9 8.34 + 98.8 8.56 + 103.6 8.77 + 108.5 8.98 + 113.4 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+++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/057_La_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + La + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 138.90550 + +DENSITY: 6.1500 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.58 + 54.9 5.66 + 59.8 5.75 + 64.6 5.85 + 69.5 5.96 + 74.4 6.07 + 79.3 6.19 + 84.1 6.31 + 89.0 6.43 + 93.9 6.56 + 98.8 6.69 + 103.6 6.82 + 108.5 6.95 + 113.4 7.09 + 118.3 7.22 + 123.1 7.36 + 128.0 7.49 + 132.9 7.63 + 137.8 7.77 + 142.6 7.90 + 147.5 8.04 + 152.4 8.18 + 157.3 8.31 + 162.1 8.45 + 167.0 8.59 + 171.9 8.72 + 176.8 8.86 + 181.6 9.00 + 186.5 9.13 + 191.4 9.27 + 196.3 9.40 + 201.1 9.54 + 206.0 9.68 + 210.9 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1990.3 33.46 + 1995.1 33.52 + 2000.0 33.59 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/059_Pr_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/059_Pr_eIMFP.txt new file mode 100644 index 0000000..99ee920 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/059_Pr_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Pr + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 140.90765 + +DENSITY: 6.7700 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.70 + 54.9 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/060_Nd_eIMFP.txt new file mode 100644 index 0000000..8f82927 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/060_Nd_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Nd + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 144.24000 + +DENSITY: 7.0100 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.73 + 54.9 4.72 + 59.8 4.72 + 64.6 4.72 + 69.5 4.74 + 74.4 4.77 + 79.3 4.80 + 84.1 4.85 + 89.0 4.90 + 93.9 4.96 + 98.8 5.02 + 103.6 5.09 + 108.5 5.15 + 113.4 5.23 + 118.3 5.30 + 123.1 5.38 + 128.0 5.45 + 132.9 5.53 + 137.8 5.61 + 142.6 5.69 + 147.5 5.78 + 152.4 5.86 + 157.3 5.94 + 162.1 6.03 + 167.0 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/064_Gd_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/064_Gd_eIMFP.txt new file mode 100644 index 0000000..cac8e1b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/064_Gd_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Gd + +SOURCE: + Tanuma, Powell and Penn + Unpublished data + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 157.25000 + +DENSITY: 7.9000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 3.99 + 54.9 3.98 + 59.8 4.00 + 64.6 4.04 + 69.5 4.09 + 74.4 4.16 + 79.3 4.22 + 84.1 4.30 + 89.0 4.38 + 93.9 4.46 + 98.8 4.54 + 103.6 4.63 + 108.5 4.71 + 113.4 4.80 + 118.3 4.89 + 123.1 4.98 + 128.0 5.07 + 132.9 5.17 + 137.8 5.26 + 142.6 5.35 + 147.5 5.44 + 152.4 5.53 + 157.3 5.63 + 162.1 5.72 + 167.0 5.81 + 171.9 5.90 + 176.8 6.00 + 181.6 6.09 + 186.5 6.18 + 191.4 6.27 + 196.3 6.36 + 201.1 6.45 + 206.0 6.55 + 210.9 6.64 + 215.8 6.73 + 220.6 6.82 + 225.5 6.91 + 230.4 7.00 + 235.3 7.09 + 240.1 7.18 + 245.0 7.27 + 249.9 7.36 + 254.8 7.45 + 259.6 7.54 + 264.5 7.63 + 269.4 7.72 + 274.3 7.81 + 279.1 7.89 + 284.0 7.98 + 288.9 8.07 + 293.8 8.16 + 298.6 8.25 + 303.5 8.33 + 308.4 8.42 + 313.3 8.51 + 318.1 8.60 + 323.0 8.68 + 327.9 8.77 + 332.8 8.86 + 337.6 8.94 + 342.5 9.03 + 347.4 9.11 + 352.3 9.20 + 357.1 9.28 + 362.0 9.37 + 366.9 9.46 + 371.8 9.54 + 376.6 9.63 + 381.5 9.71 + 386.4 9.79 + 391.3 9.88 + 396.1 9.96 + 401.0 10.05 + 405.9 10.13 + 410.8 10.21 + 415.6 10.30 + 420.5 10.38 + 425.4 10.46 + 430.3 10.55 + 435.1 10.63 + 440.0 10.71 + 444.9 10.80 + 449.8 10.88 + 454.6 10.96 + 459.5 11.04 + 464.4 11.13 + 469.3 11.21 + 474.1 11.29 + 479.0 11.37 + 483.9 11.45 + 488.8 11.53 + 493.6 11.62 + 498.5 11.70 + 503.4 11.78 + 508.3 11.86 + 513.1 11.94 + 518.0 12.02 + 522.9 12.10 + 527.8 12.18 + 532.6 12.26 + 537.5 12.34 + 542.4 12.42 + 547.3 12.50 + 552.1 12.58 + 557.0 12.66 + 561.9 12.74 + 566.8 12.82 + 571.6 12.90 + 576.5 12.98 + 581.4 13.06 + 586.3 13.14 + 591.1 13.22 + 596.0 13.30 + 600.9 13.38 + 605.8 13.46 + 610.6 13.53 + 615.5 13.61 + 620.4 13.69 + 625.3 13.77 + 630.1 13.85 + 635.0 13.93 + 639.9 14.00 + 644.8 14.08 + 649.6 14.16 + 654.5 14.24 + 659.4 14.32 + 664.3 14.39 + 669.1 14.47 + 674.0 14.55 + 678.9 14.63 + 683.8 14.70 + 688.6 14.78 + 693.5 14.86 + 698.4 14.93 + 703.3 15.01 + 708.1 15.09 + 713.0 15.17 + 717.9 15.24 + 722.8 15.32 + 727.6 15.39 + 732.5 15.47 + 737.4 15.55 + 742.3 15.62 + 747.1 15.70 + 752.0 15.78 + 756.9 15.85 + 761.8 15.93 + 766.6 16.00 + 771.5 16.08 + 776.4 16.16 + 781.3 16.23 + 786.1 16.31 + 791.0 16.38 + 795.9 16.46 + 800.8 16.53 + 805.6 16.61 + 810.5 16.68 + 815.4 16.76 + 820.3 16.83 + 825.1 16.91 + 830.0 16.98 + 834.9 17.06 + 839.8 17.13 + 844.6 17.21 + 849.5 17.28 + 854.4 17.36 + 859.3 17.43 + 864.1 17.51 + 869.0 17.58 + 873.9 17.65 + 878.8 17.73 + 883.6 17.80 + 888.5 17.88 + 893.4 17.95 + 898.3 18.03 + 903.1 18.10 + 908.0 18.17 + 912.9 18.25 + 917.8 18.32 + 922.6 18.39 + 927.5 18.47 + 932.4 18.54 + 937.3 18.62 + 942.1 18.69 + 947.0 18.76 + 951.9 18.84 + 956.8 18.91 + 961.6 18.98 + 966.5 19.05 + 971.4 19.13 + 976.3 19.20 + 981.1 19.27 + 986.0 19.35 + 990.9 19.42 + 995.8 19.49 + 1000.6 19.57 + 1005.5 19.64 + 1010.4 19.71 + 1015.3 19.78 + 1020.1 19.86 + 1025.0 19.93 + 1029.9 20.00 + 1034.8 20.07 + 1039.6 20.14 + 1044.5 20.22 + 1049.4 20.29 + 1054.3 20.36 + 1059.1 20.43 + 1064.0 20.51 + 1068.9 20.58 + 1073.8 20.65 + 1078.6 20.72 + 1083.5 20.79 + 1088.4 20.87 + 1093.3 20.94 + 1098.1 21.01 + 1103.0 21.08 + 1107.9 21.15 + 1112.8 21.22 + 1117.6 21.29 + 1122.5 21.37 + 1127.4 21.44 + 1132.3 21.51 + 1137.1 21.58 + 1142.0 21.65 + 1146.9 21.72 + 1151.8 21.79 + 1156.6 21.86 + 1161.5 21.94 + 1166.4 22.01 + 1171.3 22.08 + 1176.1 22.15 + 1181.0 22.22 + 1185.9 22.29 + 1190.8 22.36 + 1195.6 22.43 + 1200.5 22.50 + 1205.4 22.57 + 1210.3 22.64 + 1215.1 22.71 + 1220.0 22.78 + 1224.9 22.86 + 1229.8 22.93 + 1234.6 23.00 + 1239.5 23.07 + 1244.4 23.14 + 1249.3 23.21 + 1254.1 23.28 + 1259.0 23.35 + 1263.9 23.42 + 1268.8 23.49 + 1273.6 23.56 + 1278.5 23.63 + 1283.4 23.70 + 1288.3 23.77 + 1293.1 23.84 + 1298.0 23.91 + 1302.9 23.98 + 1307.8 24.05 + 1312.6 24.12 + 1317.5 24.19 + 1322.4 24.26 + 1327.3 24.33 + 1332.1 24.39 + 1337.0 24.46 + 1341.9 24.53 + 1346.8 24.60 + 1351.6 24.67 + 1356.5 24.74 + 1361.4 24.81 + 1366.3 24.88 + 1371.1 24.95 + 1376.0 25.02 + 1380.9 25.09 + 1385.8 25.16 + 1390.6 25.23 + 1395.5 25.30 + 1400.4 25.36 + 1405.3 25.43 + 1410.1 25.50 + 1415.0 25.57 + 1419.9 25.64 + 1424.8 25.71 + 1429.6 25.78 + 1434.5 25.85 + 1439.4 25.92 + 1444.3 25.98 + 1449.1 26.05 + 1454.0 26.12 + 1458.9 26.19 + 1463.8 26.26 + 1468.6 26.33 + 1473.5 26.40 + 1478.4 26.46 + 1483.3 26.53 + 1488.1 26.60 + 1493.0 26.67 + 1497.9 26.74 + 1502.8 26.81 + 1507.6 26.87 + 1512.5 26.94 + 1517.4 27.01 + 1522.3 27.08 + 1527.1 27.15 + 1532.0 27.21 + 1536.9 27.28 + 1541.8 27.35 + 1546.6 27.42 + 1551.5 27.49 + 1556.4 27.55 + 1561.3 27.62 + 1566.1 27.69 + 1571.0 27.76 + 1575.9 27.83 + 1580.8 27.89 + 1585.6 27.96 + 1590.5 28.03 + 1595.4 28.10 + 1600.3 28.16 + 1605.1 28.23 + 1610.0 28.30 + 1614.9 28.37 + 1619.8 28.43 + 1624.6 28.50 + 1629.5 28.57 + 1634.4 28.64 + 1639.3 28.70 + 1644.1 28.77 + 1649.0 28.84 + 1653.9 28.91 + 1658.8 28.97 + 1663.6 29.04 + 1668.5 29.11 + 1673.4 29.18 + 1678.3 29.24 + 1683.1 29.31 + 1688.0 29.38 + 1692.9 29.44 + 1697.8 29.51 + 1702.6 29.58 + 1707.5 29.64 + 1712.4 29.71 + 1717.3 29.78 + 1722.1 29.85 + 1727.0 29.91 + 1731.9 29.98 + 1736.8 30.05 + 1741.6 30.11 + 1746.5 30.18 + 1751.4 30.25 + 1756.3 30.31 + 1761.1 30.38 + 1766.0 30.45 + 1770.9 30.51 + 1775.8 30.58 + 1780.6 30.65 + 1785.5 30.71 + 1790.4 30.78 + 1795.3 30.85 + 1800.1 30.91 + 1805.0 30.98 + 1809.9 31.04 + 1814.8 31.11 + 1819.6 31.18 + 1824.5 31.24 + 1829.4 31.31 + 1834.3 31.38 + 1839.1 31.44 + 1844.0 31.51 + 1848.9 31.57 + 1853.8 31.64 + 1858.6 31.71 + 1863.5 31.77 + 1868.4 31.84 + 1873.3 31.90 + 1878.1 31.97 + 1883.0 32.04 + 1887.9 32.10 + 1892.8 32.17 + 1897.6 32.23 + 1902.5 32.30 + 1907.4 32.37 + 1912.3 32.43 + 1917.1 32.50 + 1922.0 32.56 + 1926.9 32.63 + 1931.8 32.70 + 1936.6 32.76 + 1941.5 32.83 + 1946.4 32.89 + 1951.3 32.96 + 1956.1 33.02 + 1961.0 33.09 + 1965.9 33.15 + 1970.8 33.22 + 1975.6 33.29 + 1980.5 33.35 + 1985.4 33.42 + 1990.3 33.48 + 1995.1 33.55 + 2000.0 33.61 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/065_Tb_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/065_Tb_eIMFP.txt new file mode 100644 index 0000000..ad7b622 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/065_Tb_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Tb + +SOURCE: + Tanuma, Powell and Penn + Unpublished data + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 158.92534 + +DENSITY: 8.2300 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.17 + 54.9 4.10 + 59.8 4.06 + 64.6 4.04 + 69.5 4.04 + 74.4 4.05 + 79.3 4.08 + 84.1 4.11 + 89.0 4.15 + 93.9 4.20 + 98.8 4.25 + 103.6 4.31 + 108.5 4.37 + 113.4 4.43 + 118.3 4.49 + 123.1 4.56 + 128.0 4.63 + 132.9 4.70 + 137.8 4.77 + 142.6 4.84 + 147.5 4.91 + 152.4 4.98 + 157.3 5.06 + 162.1 5.13 + 167.0 5.20 + 171.9 5.28 + 176.8 5.35 + 181.6 5.43 + 186.5 5.50 + 191.4 5.58 + 196.3 5.65 + 201.1 5.73 + 206.0 5.80 + 210.9 5.88 + 215.8 5.95 + 220.6 6.03 + 225.5 6.10 + 230.4 6.18 + 235.3 6.25 + 240.1 6.33 + 245.0 6.40 + 249.9 6.48 + 254.8 6.55 + 259.6 6.63 + 264.5 6.70 + 269.4 6.78 + 274.3 6.85 + 279.1 6.93 + 284.0 7.00 + 288.9 7.08 + 293.8 7.15 + 298.6 7.22 + 303.5 7.30 + 308.4 7.37 + 313.3 7.45 + 318.1 7.52 + 323.0 7.59 + 327.9 7.67 + 332.8 7.74 + 337.6 7.81 + 342.5 7.89 + 347.4 7.96 + 352.3 8.03 + 357.1 8.11 + 362.0 8.18 + 366.9 8.25 + 371.8 8.32 + 376.6 8.40 + 381.5 8.47 + 386.4 8.54 + 391.3 8.61 + 396.1 8.68 + 401.0 8.76 + 405.9 8.83 + 410.8 8.90 + 415.6 8.97 + 420.5 9.04 + 425.4 9.11 + 430.3 9.18 + 435.1 9.25 + 440.0 9.33 + 444.9 9.40 + 449.8 9.47 + 454.6 9.54 + 459.5 9.61 + 464.4 9.68 + 469.3 9.75 + 474.1 9.82 + 479.0 9.89 + 483.9 9.96 + 488.8 10.03 + 493.6 10.10 + 498.5 10.17 + 503.4 10.24 + 508.3 10.31 + 513.1 10.38 + 518.0 10.45 + 522.9 10.52 + 527.8 10.59 + 532.6 10.65 + 537.5 10.72 + 542.4 10.79 + 547.3 10.86 + 552.1 10.93 + 557.0 11.00 + 561.9 11.07 + 566.8 11.14 + 571.6 11.20 + 576.5 11.27 + 581.4 11.34 + 586.3 11.41 + 591.1 11.48 + 596.0 11.55 + 600.9 11.61 + 605.8 11.68 + 610.6 11.75 + 615.5 11.82 + 620.4 11.88 + 625.3 11.95 + 630.1 12.02 + 635.0 12.09 + 639.9 12.15 + 644.8 12.22 + 649.6 12.29 + 654.5 12.36 + 659.4 12.42 + 664.3 12.49 + 669.1 12.56 + 674.0 12.62 + 678.9 12.69 + 683.8 12.76 + 688.6 12.82 + 693.5 12.89 + 698.4 12.96 + 703.3 13.02 + 708.1 13.09 + 713.0 13.16 + 717.9 13.22 + 722.8 13.29 + 727.6 13.35 + 732.5 13.42 + 737.4 13.49 + 742.3 13.55 + 747.1 13.62 + 752.0 13.68 + 756.9 13.75 + 761.8 13.81 + 766.6 13.88 + 771.5 13.95 + 776.4 14.01 + 781.3 14.08 + 786.1 14.14 + 791.0 14.21 + 795.9 14.27 + 800.8 14.34 + 805.6 14.40 + 810.5 14.47 + 815.4 14.53 + 820.3 14.60 + 825.1 14.66 + 830.0 14.73 + 834.9 14.79 + 839.8 14.86 + 844.6 14.92 + 849.5 14.99 + 854.4 15.05 + 859.3 15.11 + 864.1 15.18 + 869.0 15.24 + 873.9 15.31 + 878.8 15.37 + 883.6 15.44 + 888.5 15.50 + 893.4 15.56 + 898.3 15.63 + 903.1 15.69 + 908.0 15.76 + 912.9 15.82 + 917.8 15.88 + 922.6 15.95 + 927.5 16.01 + 932.4 16.07 + 937.3 16.14 + 942.1 16.20 + 947.0 16.27 + 951.9 16.33 + 956.8 16.39 + 961.6 16.46 + 966.5 16.52 + 971.4 16.58 + 976.3 16.65 + 981.1 16.71 + 986.0 16.77 + 990.9 16.83 + 995.8 16.90 + 1000.6 16.96 + 1005.5 17.02 + 1010.4 17.09 + 1015.3 17.15 + 1020.1 17.21 + 1025.0 17.28 + 1029.9 17.34 + 1034.8 17.40 + 1039.6 17.46 + 1044.5 17.53 + 1049.4 17.59 + 1054.3 17.65 + 1059.1 17.71 + 1064.0 17.78 + 1068.9 17.84 + 1073.8 17.90 + 1078.6 17.96 + 1083.5 18.02 + 1088.4 18.09 + 1093.3 18.15 + 1098.1 18.21 + 1103.0 18.27 + 1107.9 18.34 + 1112.8 18.40 + 1117.6 18.46 + 1122.5 18.52 + 1127.4 18.58 + 1132.3 18.65 + 1137.1 18.71 + 1142.0 18.77 + 1146.9 18.83 + 1151.8 18.89 + 1156.6 18.95 + 1161.5 19.02 + 1166.4 19.08 + 1171.3 19.14 + 1176.1 19.20 + 1181.0 19.26 + 1185.9 19.32 + 1190.8 19.38 + 1195.6 19.45 + 1200.5 19.51 + 1205.4 19.57 + 1210.3 19.63 + 1215.1 19.69 + 1220.0 19.75 + 1224.9 19.81 + 1229.8 19.87 + 1234.6 19.93 + 1239.5 20.00 + 1244.4 20.06 + 1249.3 20.12 + 1254.1 20.18 + 1259.0 20.24 + 1263.9 20.30 + 1268.8 20.36 + 1273.6 20.42 + 1278.5 20.48 + 1283.4 20.54 + 1288.3 20.60 + 1293.1 20.66 + 1298.0 20.73 + 1302.9 20.79 + 1307.8 20.85 + 1312.6 20.91 + 1317.5 20.97 + 1322.4 21.03 + 1327.3 21.09 + 1332.1 21.15 + 1337.0 21.21 + 1341.9 21.27 + 1346.8 21.33 + 1351.6 21.39 + 1356.5 21.45 + 1361.4 21.51 + 1366.3 21.57 + 1371.1 21.63 + 1376.0 21.69 + 1380.9 21.75 + 1385.8 21.81 + 1390.6 21.87 + 1395.5 21.93 + 1400.4 21.99 + 1405.3 22.05 + 1410.1 22.11 + 1415.0 22.17 + 1419.9 22.23 + 1424.8 22.29 + 1429.6 22.35 + 1434.5 22.41 + 1439.4 22.47 + 1444.3 22.53 + 1449.1 22.59 + 1454.0 22.65 + 1458.9 22.71 + 1463.8 22.77 + 1468.6 22.83 + 1473.5 22.89 + 1478.4 22.95 + 1483.3 23.00 + 1488.1 23.06 + 1493.0 23.12 + 1497.9 23.18 + 1502.8 23.24 + 1507.6 23.30 + 1512.5 23.36 + 1517.4 23.42 + 1522.3 23.48 + 1527.1 23.54 + 1532.0 23.60 + 1536.9 23.66 + 1541.8 23.72 + 1546.6 23.77 + 1551.5 23.83 + 1556.4 23.89 + 1561.3 23.95 + 1566.1 24.01 + 1571.0 24.07 + 1575.9 24.13 + 1580.8 24.19 + 1585.6 24.25 + 1590.5 24.30 + 1595.4 24.36 + 1600.3 24.42 + 1605.1 24.48 + 1610.0 24.54 + 1614.9 24.60 + 1619.8 24.66 + 1624.6 24.72 + 1629.5 24.77 + 1634.4 24.83 + 1639.3 24.89 + 1644.1 24.95 + 1649.0 25.01 + 1653.9 25.07 + 1658.8 25.13 + 1663.6 25.18 + 1668.5 25.24 + 1673.4 25.30 + 1678.3 25.36 + 1683.1 25.42 + 1688.0 25.48 + 1692.9 25.53 + 1697.8 25.59 + 1702.6 25.65 + 1707.5 25.71 + 1712.4 25.77 + 1717.3 25.82 + 1722.1 25.88 + 1727.0 25.94 + 1731.9 26.00 + 1736.8 26.06 + 1741.6 26.11 + 1746.5 26.17 + 1751.4 26.23 + 1756.3 26.29 + 1761.1 26.35 + 1766.0 26.40 + 1770.9 26.46 + 1775.8 26.52 + 1780.6 26.58 + 1785.5 26.64 + 1790.4 26.69 + 1795.3 26.75 + 1800.1 26.81 + 1805.0 26.87 + 1809.9 26.93 + 1814.8 26.98 + 1819.6 27.04 + 1824.5 27.10 + 1829.4 27.16 + 1834.3 27.21 + 1839.1 27.27 + 1844.0 27.33 + 1848.9 27.39 + 1853.8 27.44 + 1858.6 27.50 + 1863.5 27.56 + 1868.4 27.62 + 1873.3 27.67 + 1878.1 27.73 + 1883.0 27.79 + 1887.9 27.85 + 1892.8 27.90 + 1897.6 27.96 + 1902.5 28.02 + 1907.4 28.07 + 1912.3 28.13 + 1917.1 28.19 + 1922.0 28.25 + 1926.9 28.30 + 1931.8 28.36 + 1936.6 28.42 + 1941.5 28.47 + 1946.4 28.53 + 1951.3 28.59 + 1956.1 28.65 + 1961.0 28.70 + 1965.9 28.76 + 1970.8 28.82 + 1975.6 28.87 + 1980.5 28.93 + 1985.4 28.99 + 1990.3 29.05 + 1995.1 29.10 + 2000.0 29.16 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/066_Dy_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/066_Dy_eIMFP.txt new file mode 100644 index 0000000..6f73609 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/066_Dy_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Dy + +SOURCE: + Tanuma, Powell and Penn + Unpublished data + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 162.50000 + +DENSITY: 8.5500 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 3.91 + 54.9 3.91 + 59.8 3.91 + 64.6 3.94 + 69.5 3.97 + 74.4 4.01 + 79.3 4.06 + 84.1 4.11 + 89.0 4.17 + 93.9 4.23 + 98.8 4.30 + 103.6 4.36 + 108.5 4.43 + 113.4 4.50 + 118.3 4.58 + 123.1 4.65 + 128.0 4.73 + 132.9 4.80 + 137.8 4.88 + 142.6 4.96 + 147.5 5.04 + 152.4 5.11 + 157.3 5.19 + 162.1 5.27 + 167.0 5.35 + 171.9 5.43 + 176.8 5.51 + 181.6 5.59 + 186.5 5.67 + 191.4 5.74 + 196.3 5.82 + 201.1 5.90 + 206.0 5.98 + 210.9 6.06 + 215.8 6.14 + 220.6 6.22 + 225.5 6.30 + 230.4 6.38 + 235.3 6.46 + 240.1 6.53 + 245.0 6.61 + 249.9 6.69 + 254.8 6.77 + 259.6 6.85 + 264.5 6.92 + 269.4 7.00 + 274.3 7.08 + 279.1 7.16 + 284.0 7.23 + 288.9 7.31 + 293.8 7.39 + 298.6 7.47 + 303.5 7.54 + 308.4 7.62 + 313.3 7.70 + 318.1 7.77 + 323.0 7.85 + 327.9 7.92 + 332.8 8.00 + 337.6 8.08 + 342.5 8.15 + 347.4 8.23 + 352.3 8.30 + 357.1 8.38 + 362.0 8.45 + 366.9 8.53 + 371.8 8.60 + 376.6 8.68 + 381.5 8.75 + 386.4 8.83 + 391.3 8.90 + 396.1 8.98 + 401.0 9.05 + 405.9 9.12 + 410.8 9.20 + 415.6 9.27 + 420.5 9.34 + 425.4 9.42 + 430.3 9.49 + 435.1 9.57 + 440.0 9.64 + 444.9 9.71 + 449.8 9.78 + 454.6 9.86 + 459.5 9.93 + 464.4 10.00 + 469.3 10.07 + 474.1 10.15 + 479.0 10.22 + 483.9 10.29 + 488.8 10.36 + 493.6 10.44 + 498.5 10.51 + 503.4 10.58 + 508.3 10.65 + 513.1 10.72 + 518.0 10.79 + 522.9 10.86 + 527.8 10.94 + 532.6 11.01 + 537.5 11.08 + 542.4 11.15 + 547.3 11.22 + 552.1 11.29 + 557.0 11.36 + 561.9 11.43 + 566.8 11.50 + 571.6 11.57 + 576.5 11.64 + 581.4 11.71 + 586.3 11.78 + 591.1 11.85 + 596.0 11.92 + 600.9 11.99 + 605.8 12.06 + 610.6 12.13 + 615.5 12.20 + 620.4 12.27 + 625.3 12.34 + 630.1 12.41 + 635.0 12.48 + 639.9 12.55 + 644.8 12.62 + 649.6 12.69 + 654.5 12.76 + 659.4 12.82 + 664.3 12.89 + 669.1 12.96 + 674.0 13.03 + 678.9 13.10 + 683.8 13.17 + 688.6 13.24 + 693.5 13.30 + 698.4 13.37 + 703.3 13.44 + 708.1 13.51 + 713.0 13.58 + 717.9 13.64 + 722.8 13.71 + 727.6 13.78 + 732.5 13.85 + 737.4 13.92 + 742.3 13.98 + 747.1 14.05 + 752.0 14.12 + 756.9 14.19 + 761.8 14.25 + 766.6 14.32 + 771.5 14.39 + 776.4 14.45 + 781.3 14.52 + 786.1 14.59 + 791.0 14.65 + 795.9 14.72 + 800.8 14.79 + 805.6 14.86 + 810.5 14.92 + 815.4 14.99 + 820.3 15.05 + 825.1 15.12 + 830.0 15.19 + 834.9 15.25 + 839.8 15.32 + 844.6 15.39 + 849.5 15.45 + 854.4 15.52 + 859.3 15.58 + 864.1 15.65 + 869.0 15.72 + 873.9 15.78 + 878.8 15.85 + 883.6 15.91 + 888.5 15.98 + 893.4 16.05 + 898.3 16.11 + 903.1 16.18 + 908.0 16.24 + 912.9 16.31 + 917.8 16.37 + 922.6 16.44 + 927.5 16.50 + 932.4 16.57 + 937.3 16.63 + 942.1 16.70 + 947.0 16.76 + 951.9 16.83 + 956.8 16.89 + 961.6 16.96 + 966.5 17.02 + 971.4 17.09 + 976.3 17.15 + 981.1 17.22 + 986.0 17.28 + 990.9 17.35 + 995.8 17.41 + 1000.6 17.48 + 1005.5 17.54 + 1010.4 17.61 + 1015.3 17.67 + 1020.1 17.73 + 1025.0 17.80 + 1029.9 17.86 + 1034.8 17.93 + 1039.6 17.99 + 1044.5 18.06 + 1049.4 18.12 + 1054.3 18.18 + 1059.1 18.25 + 1064.0 18.31 + 1068.9 18.37 + 1073.8 18.44 + 1078.6 18.50 + 1083.5 18.57 + 1088.4 18.63 + 1093.3 18.69 + 1098.1 18.76 + 1103.0 18.82 + 1107.9 18.88 + 1112.8 18.95 + 1117.6 19.01 + 1122.5 19.07 + 1127.4 19.14 + 1132.3 19.20 + 1137.1 19.26 + 1142.0 19.33 + 1146.9 19.39 + 1151.8 19.45 + 1156.6 19.52 + 1161.5 19.58 + 1166.4 19.64 + 1171.3 19.71 + 1176.1 19.77 + 1181.0 19.83 + 1185.9 19.89 + 1190.8 19.96 + 1195.6 20.02 + 1200.5 20.08 + 1205.4 20.15 + 1210.3 20.21 + 1215.1 20.27 + 1220.0 20.33 + 1224.9 20.40 + 1229.8 20.46 + 1234.6 20.52 + 1239.5 20.58 + 1244.4 20.65 + 1249.3 20.71 + 1254.1 20.77 + 1259.0 20.83 + 1263.9 20.89 + 1268.8 20.96 + 1273.6 21.02 + 1278.5 21.08 + 1283.4 21.14 + 1288.3 21.20 + 1293.1 21.27 + 1298.0 21.33 + 1302.9 21.39 + 1307.8 21.45 + 1312.6 21.51 + 1317.5 21.58 + 1322.4 21.64 + 1327.3 21.70 + 1332.1 21.76 + 1337.0 21.82 + 1341.9 21.88 + 1346.8 21.95 + 1351.6 22.01 + 1356.5 22.07 + 1361.4 22.13 + 1366.3 22.19 + 1371.1 22.25 + 1376.0 22.32 + 1380.9 22.38 + 1385.8 22.44 + 1390.6 22.50 + 1395.5 22.56 + 1400.4 22.62 + 1405.3 22.68 + 1410.1 22.74 + 1415.0 22.81 + 1419.9 22.87 + 1424.8 22.93 + 1429.6 22.99 + 1434.5 23.05 + 1439.4 23.11 + 1444.3 23.17 + 1449.1 23.23 + 1454.0 23.29 + 1458.9 23.35 + 1463.8 23.42 + 1468.6 23.48 + 1473.5 23.54 + 1478.4 23.60 + 1483.3 23.66 + 1488.1 23.72 + 1493.0 23.78 + 1497.9 23.84 + 1502.8 23.90 + 1507.6 23.96 + 1512.5 24.02 + 1517.4 24.08 + 1522.3 24.14 + 1527.1 24.20 + 1532.0 24.26 + 1536.9 24.32 + 1541.8 24.38 + 1546.6 24.45 + 1551.5 24.51 + 1556.4 24.57 + 1561.3 24.63 + 1566.1 24.69 + 1571.0 24.75 + 1575.9 24.81 + 1580.8 24.87 + 1585.6 24.93 + 1590.5 24.99 + 1595.4 25.05 + 1600.3 25.11 + 1605.1 25.17 + 1610.0 25.23 + 1614.9 25.29 + 1619.8 25.35 + 1624.6 25.41 + 1629.5 25.47 + 1634.4 25.53 + 1639.3 25.59 + 1644.1 25.65 + 1649.0 25.71 + 1653.9 25.77 + 1658.8 25.83 + 1663.6 25.88 + 1668.5 25.94 + 1673.4 26.00 + 1678.3 26.06 + 1683.1 26.12 + 1688.0 26.18 + 1692.9 26.24 + 1697.8 26.30 + 1702.6 26.36 + 1707.5 26.42 + 1712.4 26.48 + 1717.3 26.54 + 1722.1 26.60 + 1727.0 26.66 + 1731.9 26.72 + 1736.8 26.78 + 1741.6 26.84 + 1746.5 26.90 + 1751.4 26.95 + 1756.3 27.01 + 1761.1 27.07 + 1766.0 27.13 + 1770.9 27.19 + 1775.8 27.25 + 1780.6 27.31 + 1785.5 27.37 + 1790.4 27.43 + 1795.3 27.49 + 1800.1 27.55 + 1805.0 27.60 + 1809.9 27.66 + 1814.8 27.72 + 1819.6 27.78 + 1824.5 27.84 + 1829.4 27.90 + 1834.3 27.96 + 1839.1 28.02 + 1844.0 28.08 + 1848.9 28.13 + 1853.8 28.19 + 1858.6 28.25 + 1863.5 28.31 + 1868.4 28.37 + 1873.3 28.43 + 1878.1 28.49 + 1883.0 28.54 + 1887.9 28.60 + 1892.8 28.66 + 1897.6 28.72 + 1902.5 28.78 + 1907.4 28.84 + 1912.3 28.90 + 1917.1 28.95 + 1922.0 29.01 + 1926.9 29.07 + 1931.8 29.13 + 1936.6 29.19 + 1941.5 29.25 + 1946.4 29.30 + 1951.3 29.36 + 1956.1 29.42 + 1961.0 29.48 + 1965.9 29.54 + 1970.8 29.60 + 1975.6 29.65 + 1980.5 29.71 + 1985.4 29.77 + 1990.3 29.83 + 1995.1 29.89 + 2000.0 29.94 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/067_Ho_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/067_Ho_eIMFP.txt new file mode 100644 index 0000000..fb8d078 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/067_Ho_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ho + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 164.93032 + +DENSITY: 8.8000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.95 + 54.9 4.88 + 59.8 4.83 + 64.6 4.80 + 69.5 4.78 + 74.4 4.78 + 79.3 4.80 + 84.1 4.82 + 89.0 4.86 + 93.9 4.90 + 98.8 4.95 + 103.6 5.00 + 108.5 5.06 + 113.4 5.12 + 118.3 5.18 + 123.1 5.25 + 128.0 5.32 + 132.9 5.39 + 137.8 5.46 + 142.6 5.53 + 147.5 5.61 + 152.4 5.68 + 157.3 5.76 + 162.1 5.84 + 167.0 5.91 + 171.9 5.99 + 176.8 6.07 + 181.6 6.15 + 186.5 6.22 + 191.4 6.30 + 196.3 6.38 + 201.1 6.46 + 206.0 6.54 + 210.9 6.62 + 215.8 6.70 + 220.6 6.78 + 225.5 6.86 + 230.4 6.94 + 235.3 7.02 + 240.1 7.10 + 245.0 7.18 + 249.9 7.26 + 254.8 7.34 + 259.6 7.42 + 264.5 7.50 + 269.4 7.58 + 274.3 7.66 + 279.1 7.74 + 284.0 7.81 + 288.9 7.89 + 293.8 7.97 + 298.6 8.05 + 303.5 8.13 + 308.4 8.21 + 313.3 8.29 + 318.1 8.37 + 323.0 8.45 + 327.9 8.52 + 332.8 8.60 + 337.6 8.68 + 342.5 8.76 + 347.4 8.84 + 352.3 8.91 + 357.1 8.99 + 362.0 9.07 + 366.9 9.15 + 371.8 9.22 + 376.6 9.30 + 381.5 9.38 + 386.4 9.45 + 391.3 9.53 + 396.1 9.61 + 401.0 9.68 + 405.9 9.76 + 410.8 9.84 + 415.6 9.91 + 420.5 9.99 + 425.4 10.07 + 430.3 10.14 + 435.1 10.22 + 440.0 10.29 + 444.9 10.37 + 449.8 10.44 + 454.6 10.52 + 459.5 10.60 + 464.4 10.67 + 469.3 10.75 + 474.1 10.82 + 479.0 10.90 + 483.9 10.97 + 488.8 11.04 + 493.6 11.12 + 498.5 11.19 + 503.4 11.27 + 508.3 11.34 + 513.1 11.42 + 518.0 11.49 + 522.9 11.56 + 527.8 11.64 + 532.6 11.71 + 537.5 11.79 + 542.4 11.86 + 547.3 11.93 + 552.1 12.01 + 557.0 12.08 + 561.9 12.15 + 566.8 12.23 + 571.6 12.30 + 576.5 12.37 + 581.4 12.45 + 586.3 12.52 + 591.1 12.59 + 596.0 12.66 + 600.9 12.74 + 605.8 12.81 + 610.6 12.88 + 615.5 12.95 + 620.4 13.03 + 625.3 13.10 + 630.1 13.17 + 635.0 13.24 + 639.9 13.31 + 644.8 13.38 + 649.6 13.46 + 654.5 13.53 + 659.4 13.60 + 664.3 13.67 + 669.1 13.74 + 674.0 13.81 + 678.9 13.88 + 683.8 13.96 + 688.6 14.03 + 693.5 14.10 + 698.4 14.17 + 703.3 14.24 + 708.1 14.31 + 713.0 14.38 + 717.9 14.45 + 722.8 14.52 + 727.6 14.59 + 732.5 14.66 + 737.4 14.73 + 742.3 14.80 + 747.1 14.87 + 752.0 14.94 + 756.9 15.01 + 761.8 15.08 + 766.6 15.15 + 771.5 15.22 + 776.4 15.29 + 781.3 15.36 + 786.1 15.43 + 791.0 15.50 + 795.9 15.57 + 800.8 15.64 + 805.6 15.71 + 810.5 15.78 + 815.4 15.85 + 820.3 15.92 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1161.5 20.62 + 1166.4 20.69 + 1171.3 20.76 + 1176.1 20.82 + 1181.0 20.89 + 1185.9 20.95 + 1190.8 21.02 + 1195.6 21.08 + 1200.5 21.15 + 1205.4 21.21 + 1210.3 21.28 + 1215.1 21.34 + 1220.0 21.41 + 1224.9 21.47 + 1229.8 21.54 + 1234.6 21.60 + 1239.5 21.67 + 1244.4 21.73 + 1249.3 21.80 + 1254.1 21.86 + 1259.0 21.93 + 1263.9 21.99 + 1268.8 22.06 + 1273.6 22.12 + 1278.5 22.19 + 1283.4 22.25 + 1288.3 22.32 + 1293.1 22.38 + 1298.0 22.44 + 1302.9 22.51 + 1307.8 22.57 + 1312.6 22.64 + 1317.5 22.70 + 1322.4 22.77 + 1327.3 22.83 + 1332.1 22.89 + 1337.0 22.96 + 1341.9 23.02 + 1346.8 23.09 + 1351.6 23.15 + 1356.5 23.21 + 1361.4 23.28 + 1366.3 23.34 + 1371.1 23.41 + 1376.0 23.47 + 1380.9 23.53 + 1385.8 23.60 + 1390.6 23.66 + 1395.5 23.73 + 1400.4 23.79 + 1405.3 23.85 + 1410.1 23.92 + 1415.0 23.98 + 1419.9 24.04 + 1424.8 24.11 + 1429.6 24.17 + 1434.5 24.23 + 1439.4 24.30 + 1444.3 24.36 + 1449.1 24.42 + 1454.0 24.49 + 1458.9 24.55 + 1463.8 24.61 + 1468.6 24.68 + 1473.5 24.74 + 1478.4 24.80 + 1483.3 24.87 + 1488.1 24.93 + 1493.0 24.99 + 1497.9 25.06 + 1502.8 25.12 + 1507.6 25.18 + 1512.5 25.25 + 1517.4 25.31 + 1522.3 25.37 + 1527.1 25.43 + 1532.0 25.50 + 1536.9 25.56 + 1541.8 25.62 + 1546.6 25.69 + 1551.5 25.75 + 1556.4 25.81 + 1561.3 25.87 + 1566.1 25.94 + 1571.0 26.00 + 1575.9 26.06 + 1580.8 26.12 + 1585.6 26.19 + 1590.5 26.25 + 1595.4 26.31 + 1600.3 26.37 + 1605.1 26.44 + 1610.0 26.50 + 1614.9 26.56 + 1619.8 26.62 + 1624.6 26.69 + 1629.5 26.75 + 1634.4 26.81 + 1639.3 26.87 + 1644.1 26.93 + 1649.0 27.00 + 1653.9 27.06 + 1658.8 27.12 + 1663.6 27.18 + 1668.5 27.25 + 1673.4 27.31 + 1678.3 27.37 + 1683.1 27.43 + 1688.0 27.49 + 1692.9 27.55 + 1697.8 27.62 + 1702.6 27.68 + 1707.5 27.74 + 1712.4 27.80 + 1717.3 27.86 + 1722.1 27.93 + 1727.0 27.99 + 1731.9 28.05 + 1736.8 28.11 + 1741.6 28.17 + 1746.5 28.23 + 1751.4 28.30 + 1756.3 28.36 + 1761.1 28.42 + 1766.0 28.48 + 1770.9 28.54 + 1775.8 28.60 + 1780.6 28.66 + 1785.5 28.73 + 1790.4 28.79 + 1795.3 28.85 + 1800.1 28.91 + 1805.0 28.97 + 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/068_Er_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Er + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 167.26000 + +DENSITY: 9.0700 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.98 + 54.9 4.91 + 59.8 4.85 + 64.6 4.81 + 69.5 4.79 + 74.4 4.79 + 79.3 4.80 + 84.1 4.82 + 89.0 4.85 + 93.9 4.89 + 98.8 4.94 + 103.6 4.99 + 108.5 5.04 + 113.4 5.10 + 118.3 5.16 + 123.1 5.23 + 128.0 5.30 + 132.9 5.37 + 137.8 5.44 + 142.6 5.51 + 147.5 5.58 + 152.4 5.65 + 157.3 5.73 + 162.1 5.80 + 167.0 5.88 + 171.9 5.96 + 176.8 6.03 + 181.6 6.11 + 186.5 6.19 + 191.4 6.27 + 196.3 6.35 + 201.1 6.42 + 206.0 6.50 + 210.9 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/070_Yb_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/070_Yb_eIMFP.txt new file mode 100644 index 0000000..6722072 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/070_Yb_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Yb + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 173.04000 + +DENSITY: 6.9000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 4.85 + 54.9 4.86 + 59.8 4.88 + 64.6 4.90 + 69.5 4.94 + 74.4 4.99 + 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file mode 100644 index 0000000..0d3fe9e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/071_Lu_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Lu + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 174.96700 + +DENSITY: 9.8400 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.07 + 54.9 4.97 + 59.8 4.89 + 64.6 4.83 + 69.5 4.80 + 74.4 4.79 + 79.3 4.79 + 84.1 4.80 + 89.0 4.83 + 93.9 4.86 + 98.8 4.90 + 103.6 4.95 + 108.5 5.00 + 113.4 5.06 + 118.3 5.12 + 123.1 5.18 + 128.0 5.24 + 132.9 5.31 + 137.8 5.37 + 142.6 5.44 + 147.5 5.51 + 152.4 5.58 + 157.3 5.65 + 162.1 5.73 + 167.0 5.80 + 171.9 5.87 + 176.8 5.95 + 181.6 6.02 + 186.5 6.10 + 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28.98 + 1887.9 29.04 + 1892.8 29.10 + 1897.6 29.16 + 1902.5 29.22 + 1907.4 29.28 + 1912.3 29.34 + 1917.1 29.39 + 1922.0 29.45 + 1926.9 29.51 + 1931.8 29.57 + 1936.6 29.63 + 1941.5 29.69 + 1946.4 29.75 + 1951.3 29.80 + 1956.1 29.86 + 1961.0 29.92 + 1965.9 29.98 + 1970.8 30.04 + 1975.6 30.10 + 1980.5 30.15 + 1985.4 30.21 + 1990.3 30.27 + 1995.1 30.33 + 2000.0 30.39 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/072_Hf_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/072_Hf_eIMFP.txt new file mode 100644 index 0000000..c3157e9 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/072_Hf_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Hf + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP 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36.88 + 1975.6 36.95 + 1980.5 37.02 + 1985.4 37.09 + 1990.3 37.16 + 1995.1 37.23 + 2000.0 37.30 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/073_Ta_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/073_Ta_1_eIMFP.txt new file mode 100644 index 0000000..5338b79 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/073_Ta_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ta + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 180.94790 + +DENSITY: 16.4000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/073_Ta_2_eIMFP.txt new file mode 100644 index 0000000..525b0ed --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/073_Ta_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Ta + +SOURCE: + Lesiak, Jablonski and Gergely + Vacuum 40 (1990) 67 + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +ATOMIC WEIGHT: 180.94790 + +DENSITY: 16.4000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 500.0 5.37 + 506.3 5.41 + 512.5 5.46 + 518.8 5.50 + 525.0 5.55 + 531.3 5.59 + 537.5 5.64 + 543.8 5.68 + 550.0 5.72 + 556.3 5.77 + 562.5 5.81 + 568.8 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0000000..060ee87 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/074_W_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + W + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 183.84000 + +DENSITY: 19.3000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.05 + 54.9 4.75 + 59.8 4.54 + 64.6 4.39 + 69.5 4.28 + 74.4 4.21 + 79.3 4.16 + 84.1 4.14 + 89.0 4.12 + 93.9 4.12 + 98.8 4.13 + 103.6 4.15 + 108.5 4.17 + 113.4 4.20 + 118.3 4.23 + 123.1 4.26 + 128.0 4.30 + 132.9 4.34 + 137.8 4.38 + 142.6 4.43 + 147.5 4.47 + 152.4 4.52 + 157.3 4.57 + 162.1 4.61 + 167.0 4.66 + 171.9 4.71 + 176.8 4.77 + 181.6 4.82 + 186.5 4.87 + 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Stat. 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Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/075_Re_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/075_Re_eIMFP.txt new file mode 100644 index 0000000..582f837 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/075_Re_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Re + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 186.20700 + +DENSITY: 20.8000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.09 + 54.9 4.78 + 59.8 4.51 + 64.6 4.29 + 69.5 4.13 + 74.4 4.00 + 79.3 3.91 + 84.1 3.84 + 89.0 3.79 + 93.9 3.76 + 98.8 3.74 + 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/078_Pt_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/078_Pt_1_eIMFP.txt new file mode 100644 index 0000000..e95d576 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/078_Pt_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Pt + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 17 (1991) 911. + IMFP values determined from optical data and a theoretical model + + +ATOMIC WEIGHT: 195.07800 + +DENSITY: 21.5000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 5.01 + 54.9 4.78 + 59.8 4.59 + 64.6 4.45 + 69.5 4.34 + 74.4 4.26 + 79.3 4.21 + 84.1 4.18 + 89.0 4.16 + 93.9 4.15 + 98.8 4.15 + 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Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/078_Pt_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Pt + +SOURCE: + Lesiak et al. + Surface Sci. 223, (1989) 213 + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +ATOMIC WEIGHT: 195.07800 + +DENSITY: 21.5000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 270.0 5.38 + 275.2 5.43 + 280.4 5.48 + 285.6 5.52 + 290.8 5.57 + 296.0 5.61 + 301.2 5.66 + 306.4 5.70 + 311.6 5.74 + 316.8 5.79 + 322.0 5.83 + 327.2 5.87 + 332.4 5.91 + 337.6 5.95 + 342.8 5.99 + 348.0 6.04 + 353.2 6.08 + 358.4 6.12 + 363.6 6.16 + 368.8 6.20 + 374.0 6.24 + 379.2 6.27 + 384.4 6.31 + 389.6 6.35 + 394.8 6.39 + 400.0 6.43 + 405.2 6.46 + 410.4 6.50 + 415.6 6.54 + 420.8 6.58 + 426.0 6.61 + 431.2 6.65 + 436.4 6.68 + 441.6 6.72 + 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/078_Pt_4_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/078_Pt_4_eIMFP.txt new file mode 100644 index 0000000..815007b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/078_Pt_4_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Pt + +SOURCE: + Beilschmidt, Tilinin and Werner + Surface Interface Anal. 22 (1994) 120 + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering accounted by the approximate analytical theory + +COMMENT: + Ni reference + +ATOMIC WEIGHT: 195.07800 + +DENSITY: 21.5000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/078_Pt_5_eIMFP.txt new file mode 100644 index 0000000..7d74bba --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/078_Pt_5_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Pt + +SOURCE: + Beilschmidt, Tilinin and Werner + Surface Interface Anal. 22 (1994) 120 + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering accounted by the approximate analytical theory + +COMMENT: + Al reference + +ATOMIC WEIGHT: 195.07800 + +DENSITY: 21.5000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 250.0 3.77 + 253.1 3.80 + 256.3 3.83 + 259.4 3.86 + 262.5 3.90 + 265.6 3.93 + 268.8 3.96 + 271.9 3.99 + 275.0 4.02 + 278.1 4.05 + 281.3 4.08 + 284.4 4.11 + 287.5 4.14 + 290.6 4.17 + 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693.5 10.03 + 698.4 10.07 + 703.3 10.12 + 708.1 10.17 + 713.0 10.21 + 717.9 10.26 + 722.8 10.31 + 727.6 10.35 + 732.5 10.40 + 737.4 10.45 + 742.3 10.50 + 747.1 10.54 + 752.0 10.59 + 756.9 10.64 + 761.8 10.68 + 766.6 10.73 + 771.5 10.77 + 776.4 10.82 + 781.3 10.87 + 786.1 10.91 + 791.0 10.96 + 795.9 11.01 + 800.8 11.05 + 805.6 11.10 + 810.5 11.15 + 815.4 11.19 + 820.3 11.24 + 825.1 11.28 + 830.0 11.33 + 834.9 11.38 + 839.8 11.42 + 844.6 11.47 + 849.5 11.51 + 854.4 11.56 + 859.3 11.61 + 864.1 11.65 + 869.0 11.70 + 873.9 11.74 + 878.8 11.79 + 883.6 11.83 + 888.5 11.88 + 893.4 11.93 + 898.3 11.97 + 903.1 12.02 + 908.0 12.06 + 912.9 12.11 + 917.8 12.15 + 922.6 12.20 + 927.5 12.24 + 932.4 12.29 + 937.3 12.33 + 942.1 12.38 + 947.0 12.42 + 951.9 12.47 + 956.8 12.51 + 961.6 12.56 + 966.5 12.60 + 971.4 12.65 + 976.3 12.69 + 981.1 12.74 + 986.0 12.78 + 990.9 12.83 + 995.8 12.87 + 1000.6 12.92 + 1005.5 12.96 + 1010.4 13.01 + 1015.3 13.05 + 1020.1 13.10 + 1025.0 13.14 + 1029.9 13.19 + 1034.8 13.23 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16.15 + 1366.3 16.20 + 1371.1 16.24 + 1376.0 16.28 + 1380.9 16.32 + 1385.8 16.37 + 1390.6 16.41 + 1395.5 16.45 + 1400.4 16.50 + 1405.3 16.54 + 1410.1 16.58 + 1415.0 16.62 + 1419.9 16.67 + 1424.8 16.71 + 1429.6 16.75 + 1434.5 16.79 + 1439.4 16.84 + 1444.3 16.88 + 1449.1 16.92 + 1454.0 16.96 + 1458.9 17.00 + 1463.8 17.05 + 1468.6 17.09 + 1473.5 17.13 + 1478.4 17.17 + 1483.3 17.22 + 1488.1 17.26 + 1493.0 17.30 + 1497.9 17.34 + 1502.8 17.38 + 1507.6 17.43 + 1512.5 17.47 + 1517.4 17.51 + 1522.3 17.55 + 1527.1 17.59 + 1532.0 17.64 + 1536.9 17.68 + 1541.8 17.72 + 1546.6 17.76 + 1551.5 17.80 + 1556.4 17.85 + 1561.3 17.89 + 1566.1 17.93 + 1571.0 17.97 + 1575.9 18.01 + 1580.8 18.05 + 1585.6 18.10 + 1590.5 18.14 + 1595.4 18.18 + 1600.3 18.22 + 1605.1 18.26 + 1610.0 18.31 + 1614.9 18.35 + 1619.8 18.39 + 1624.6 18.43 + 1629.5 18.47 + 1634.4 18.51 + 1639.3 18.55 + 1644.1 18.60 + 1649.0 18.64 + 1653.9 18.68 + 1658.8 18.72 + 1663.6 18.76 + 1668.5 18.80 + 1673.4 18.85 + 1678.3 18.89 + 1683.1 18.93 + 1688.0 18.97 + 1692.9 19.01 + 1697.8 19.05 + 1702.6 19.09 + 1707.5 19.13 + 1712.4 19.18 + 1717.3 19.22 + 1722.1 19.26 + 1727.0 19.30 + 1731.9 19.34 + 1736.8 19.38 + 1741.6 19.42 + 1746.5 19.46 + 1751.4 19.51 + 1756.3 19.55 + 1761.1 19.59 + 1766.0 19.63 + 1770.9 19.67 + 1775.8 19.71 + 1780.6 19.75 + 1785.5 19.79 + 1790.4 19.83 + 1795.3 19.87 + 1800.1 19.92 + 1805.0 19.96 + 1809.9 20.00 + 1814.8 20.04 + 1819.6 20.08 + 1824.5 20.12 + 1829.4 20.16 + 1834.3 20.20 + 1839.1 20.24 + 1844.0 20.28 + 1848.9 20.32 + 1853.8 20.36 + 1858.6 20.41 + 1863.5 20.45 + 1868.4 20.49 + 1873.3 20.53 + 1878.1 20.57 + 1883.0 20.61 + 1887.9 20.65 + 1892.8 20.69 + 1897.6 20.73 + 1902.5 20.77 + 1907.4 20.81 + 1912.3 20.85 + 1917.1 20.89 + 1922.0 20.93 + 1926.9 20.97 + 1931.8 21.01 + 1936.6 21.06 + 1941.5 21.10 + 1946.4 21.14 + 1951.3 21.18 + 1956.1 21.22 + 1961.0 21.26 + 1965.9 21.30 + 1970.8 21.34 + 1975.6 21.38 + 1980.5 21.42 + 1985.4 21.46 + 1990.3 21.50 + 1995.1 21.54 + 2000.0 21.58 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/079_Au_2_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/079_Au_2_eIMFP.txt new file mode 100644 index 0000000..315413c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/079_Au_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Au + +SOURCE: + Powell and Jablonski + J. Phys. Chem. Reference Data 28 (1999) 19 + Evaluation of calculated and measured IMFP values + + +ATOMIC WEIGHT: 196.96655 + +DENSITY: 19.3000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 6.30 + 74.9 5.12 + 99.8 4.73 + 124.6 4.66 + 149.5 4.73 + 174.4 4.88 + 199.3 5.08 + 224.1 5.31 + 249.0 5.56 + 273.9 5.82 + 298.8 6.09 + 323.6 6.37 + 348.5 6.65 + 373.4 6.93 + 398.3 7.21 + 423.1 7.49 + 448.0 7.77 + 472.9 8.06 + 497.8 8.34 + 522.6 8.62 + 547.5 8.90 + 572.4 9.18 + 597.3 9.46 + 622.1 9.73 + 647.0 10.01 + 671.9 10.28 + 696.8 10.56 + 721.6 10.83 + 746.5 11.10 + 771.4 11.37 + 796.3 11.63 + 821.1 11.90 + 846.0 12.17 + 870.9 12.43 + 895.8 12.69 + 920.6 12.95 + 945.5 13.21 + 970.4 13.47 + 995.3 13.73 + 1020.1 13.99 + 1045.0 14.24 + 1069.9 14.50 + 1094.8 14.75 + 1119.6 15.00 + 1144.5 15.25 + 1169.4 15.51 + 1194.3 15.75 + 1219.1 16.00 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31.09 + 2910.6 31.30 + 2935.5 31.51 + 2960.4 31.71 + 2985.3 31.92 + 3010.1 32.13 + 3035.0 32.33 + 3059.9 32.54 + 3084.8 32.75 + 3109.6 32.95 + 3134.5 33.16 + 3159.4 33.36 + 3184.3 33.56 + 3209.1 33.77 + 3234.0 33.97 + 3258.9 34.18 + 3283.8 34.38 + 3308.6 34.58 + 3333.5 34.78 + 3358.4 34.98 + 3383.3 35.19 + 3408.1 35.39 + 3433.0 35.59 + 3457.9 35.79 + 3482.8 35.99 + 3507.6 36.19 + 3532.5 36.39 + 3557.4 36.59 + 3582.3 36.79 + 3607.1 36.99 + 3632.0 37.19 + 3656.9 37.38 + 3681.8 37.58 + 3706.6 37.78 + 3731.5 37.98 + 3756.4 38.17 + 3781.3 38.37 + 3806.1 38.57 + 3831.0 38.76 + 3855.9 38.96 + 3880.8 39.16 + 3905.6 39.35 + 3930.5 39.55 + 3955.4 39.74 + 3980.3 39.94 + 4005.1 40.13 + 4030.0 40.32 + 4054.9 40.52 + 4079.8 40.71 + 4104.6 40.91 + 4129.5 41.10 + 4154.4 41.29 + 4179.3 41.48 + 4204.1 41.68 + 4229.0 41.87 + 4253.9 42.06 + 4278.8 42.25 + 4303.6 42.44 + 4328.5 42.64 + 4353.4 42.83 + 4378.3 43.02 + 4403.1 43.21 + 4428.0 43.40 + 4452.9 43.59 + 4477.8 43.78 + 4502.6 43.97 + 4527.5 44.16 + 4552.4 44.35 + 4577.3 44.54 + 4602.1 44.72 + 4627.0 44.91 + 4651.9 45.10 + 4676.8 45.29 + 4701.6 45.48 + 4726.5 45.66 + 4751.4 45.85 + 4776.3 46.04 + 4801.1 46.23 + 4826.0 46.41 + 4850.9 46.60 + 4875.8 46.79 + 4900.6 46.97 + 4925.5 47.16 + 4950.4 47.34 + 4975.3 47.53 + 5000.1 47.71 + 5025.0 47.90 + 5049.9 48.08 + 5074.8 48.27 + 5099.6 48.45 + 5124.5 48.64 + 5149.4 48.82 + 5174.3 49.01 + 5199.1 49.19 + 5224.0 49.37 + 5248.9 49.56 + 5273.8 49.74 + 5298.6 49.92 + 5323.5 50.11 + 5348.4 50.29 + 5373.3 50.47 + 5398.1 50.65 + 5423.0 50.84 + 5447.9 51.02 + 5472.8 51.20 + 5497.6 51.38 + 5522.5 51.56 + 5547.4 51.74 + 5572.3 51.93 + 5597.1 52.11 + 5622.0 52.29 + 5646.9 52.47 + 5671.8 52.65 + 5696.6 52.83 + 5721.5 53.01 + 5746.4 53.19 + 5771.3 53.37 + 5796.1 53.55 + 5821.0 53.73 + 5845.9 53.91 + 5870.8 54.09 + 5895.6 54.26 + 5920.5 54.44 + 5945.4 54.62 + 5970.3 54.80 + 5995.1 54.98 + 6020.0 55.16 + 6044.9 55.33 + 6069.8 55.51 + 6094.6 55.69 + 6119.5 55.87 + 6144.4 56.04 + 6169.3 56.22 + 6194.1 56.40 + 6219.0 56.58 + 6243.9 56.75 + 6268.8 56.93 + 6293.6 57.11 + 6318.5 57.28 + 6343.4 57.46 + 6368.3 57.63 + 6393.1 57.81 + 6418.0 57.99 + 6442.9 58.16 + 6467.8 58.34 + 6492.6 58.51 + 6517.5 58.69 + 6542.4 58.86 + 6567.3 59.04 + 6592.1 59.21 + 6617.0 59.39 + 6641.9 59.56 + 6666.8 59.73 + 6691.6 59.91 + 6716.5 60.08 + 6741.4 60.26 + 6766.3 60.43 + 6791.1 60.60 + 6816.0 60.78 + 6840.9 60.95 + 6865.8 61.12 + 6890.6 61.30 + 6915.5 61.47 + 6940.4 61.64 + 6965.3 61.81 + 6990.1 61.99 + 7015.0 62.16 + 7039.9 62.33 + 7064.8 62.50 + 7089.6 62.67 + 7114.5 62.85 + 7139.4 63.02 + 7164.3 63.19 + 7189.1 63.36 + 7214.0 63.53 + 7238.9 63.70 + 7263.8 63.87 + 7288.6 64.04 + 7313.5 64.22 + 7338.4 64.39 + 7363.3 64.56 + 7388.1 64.73 + 7413.0 64.90 + 7437.9 65.07 + 7462.8 65.24 + 7487.6 65.41 + 7512.5 65.58 + 7537.4 65.75 + 7562.3 65.92 + 7587.1 66.09 + 7612.0 66.25 + 7636.9 66.42 + 7661.8 66.59 + 7686.6 66.76 + 7711.5 66.93 + 7736.4 67.10 + 7761.3 67.27 + 7786.1 67.44 + 7811.0 67.60 + 7835.9 67.77 + 7860.8 67.94 + 7885.6 68.11 + 7910.5 68.28 + 7935.4 68.44 + 7960.3 68.61 + 7985.1 68.78 + 8010.0 68.95 + 8034.9 69.11 + 8059.8 69.28 + 8084.6 69.45 + 8109.5 69.62 + 8134.4 69.78 + 8159.3 69.95 + 8184.1 70.12 + 8209.0 70.28 + 8233.9 70.45 + 8258.8 70.61 + 8283.6 70.78 + 8308.5 70.95 + 8333.4 71.11 + 8358.3 71.28 + 8383.1 71.44 + 8408.0 71.61 + 8432.9 71.78 + 8457.8 71.94 + 8482.6 72.11 + 8507.5 72.27 + 8532.4 72.44 + 8557.3 72.60 + 8582.1 72.77 + 8607.0 72.93 + 8631.9 73.10 + 8656.8 73.26 + 8681.6 73.43 + 8706.5 73.59 + 8731.4 73.75 + 8756.3 73.92 + 8781.1 74.08 + 8806.0 74.25 + 8830.9 74.41 + 8855.8 74.57 + 8880.6 74.74 + 8905.5 74.90 + 8930.4 75.07 + 8955.3 75.23 + 8980.1 75.39 + 9005.0 75.56 + 9029.9 75.72 + 9054.8 75.88 + 9079.6 76.04 + 9104.5 76.21 + 9129.4 76.37 + 9154.3 76.53 + 9179.1 76.69 + 9204.0 76.86 + 9228.9 77.02 + 9253.8 77.18 + 9278.6 77.34 + 9303.5 77.51 + 9328.4 77.67 + 9353.3 77.83 + 9378.1 77.99 + 9403.0 78.15 + 9427.9 78.31 + 9452.8 78.48 + 9477.6 78.64 + 9502.5 78.80 + 9527.4 78.96 + 9552.3 79.12 + 9577.1 79.28 + 9602.0 79.44 + 9626.9 79.60 + 9651.8 79.77 + 9676.6 79.93 + 9701.5 80.09 + 9726.4 80.25 + 9751.3 80.41 + 9776.1 80.57 + 9801.0 80.73 + 9825.9 80.89 + 9850.8 81.05 + 9875.6 81.21 + 9900.5 81.37 + 9925.4 81.53 + 9950.3 81.69 + 9975.1 81.85 + 10000.0 82.01 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/079_Au_3_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/079_Au_3_eIMFP.txt new file mode 100644 index 0000000..9f3f35a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/079_Au_3_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Au + +SOURCE: + Beilschmidt, Tilinin and Werner + Surface Interface Anal. 22 (1994) 120 + IMFPs determined from the intensity of the elastic 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17.55 + 1500.0 17.57 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/079_Au_4_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/079_Au_4_eIMFP.txt new file mode 100644 index 0000000..ef2af54 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/079_Au_4_eIMFP.txt @@ -0,0 +1,425 @@ + +ELEMENT: + Au + +SOURCE: + Beilschmidt, Tilinin and Werner + Surface Interface Anal. 22 (1994) 120 + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering accounted by the approximate analytical theory + +COMMENT: + Ni reference + +ATOMIC WEIGHT: 196.96655 + +DENSITY: 19.3000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/081_Tl_1_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/081_Tl_1_eIMFP.txt new file mode 100644 index 0000000..44a5cfb --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/081_Tl_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Tl + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 204.38330 + +DENSITY: 11.8000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 6.66 + 54.9 6.54 + 59.8 6.48 + 64.6 6.45 + 69.5 6.45 + 74.4 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(eIMFPD)/data/eIMFPD_OpticalData_NIST/081_Tl_2_eIMFP.txt new file mode 100644 index 0000000..2a0c281 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/081_Tl_2_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Tl + +SOURCE: + Koch + Thesis, Eberhard-Karls-Universitat, Tubingen, Germany (1996) + IMFPs determined from the intensity of the elastic peak + Multiple elastic scattering simulated by the Monte Carlo method + +ATOMIC WEIGHT: 204.38330 + +DENSITY: 11.8000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 600.0 9.45 + 603.5 9.50 + 607.0 9.54 + 610.5 9.59 + 614.0 9.63 + 617.5 9.68 + 621.0 9.72 + 624.5 9.77 + 628.0 9.81 + 631.5 9.86 + 635.0 9.90 + 638.5 9.95 + 642.0 9.99 + 645.5 10.04 + 649.0 10.08 + 652.5 10.12 + 656.0 10.17 + 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index 0000000..5a53369 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/082_Pb_1_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Pb + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 207.20000 + +DENSITY: 11.3000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 6.17 + 54.9 6.06 + 59.8 6.00 + 64.6 5.97 + 69.5 5.96 + 74.4 5.98 + 79.3 6.01 + 84.1 6.06 + 89.0 6.12 + 93.9 6.18 + 98.8 6.25 + 103.6 6.33 + 108.5 6.41 + 113.4 6.50 + 118.3 6.59 + 123.1 6.68 + 128.0 6.77 + 132.9 6.87 + 137.8 6.97 + 142.6 7.07 + 147.5 7.17 + 152.4 7.27 + 157.3 7.37 + 162.1 7.47 + 167.0 7.57 + 171.9 7.68 + 176.8 7.78 + 181.6 7.88 + 186.5 7.99 + 191.4 8.09 + 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simulated by the Monte Carlo method + +ATOMIC WEIGHT: 208.98038 + +DENSITY: 9.7900 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 600.0 12.31 + 604.0 12.37 + 608.0 12.44 + 612.0 12.50 + 616.0 12.57 + 620.0 12.63 + 624.0 12.70 + 628.0 12.76 + 632.0 12.82 + 636.0 12.89 + 640.0 12.95 + 644.0 13.02 + 648.0 13.08 + 652.0 13.14 + 656.0 13.21 + 660.0 13.27 + 664.0 13.34 + 668.0 13.40 + 672.0 13.46 + 676.0 13.53 + 680.0 13.59 + 684.0 13.65 + 688.0 13.72 + 692.0 13.78 + 696.0 13.84 + 700.0 13.91 + 704.0 13.97 + 708.0 14.03 + 712.0 14.09 + 716.0 14.16 + 720.0 14.22 + 724.0 14.28 + 728.0 14.34 + 732.0 14.41 + 736.0 14.47 + 740.0 14.53 + 744.0 14.59 + 748.0 14.66 + 752.0 14.72 + 756.0 14.78 + 760.0 14.84 + 764.0 14.90 + 768.0 14.96 + 772.0 15.03 + 776.0 15.09 + 780.0 15.15 + 784.0 15.21 + 788.0 15.27 + 792.0 15.33 + 796.0 15.40 + 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2144.0 33.74 + 2148.0 33.79 + 2152.0 33.84 + 2156.0 33.89 + 2160.0 33.94 + 2164.0 33.99 + 2168.0 34.04 + 2172.0 34.09 + 2176.0 34.14 + 2180.0 34.19 + 2184.0 34.24 + 2188.0 34.29 + 2192.0 34.34 + 2196.0 34.39 + 2200.0 34.44 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/090_Th_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/090_Th_eIMFP.txt new file mode 100644 index 0000000..41cb609 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/090_Th_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Th + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 232.03810 + +DENSITY: 11.7000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 6.39 + 54.9 6.27 + 59.8 6.20 + 64.6 6.16 + 69.5 6.16 + 74.4 6.17 + 79.3 6.21 + 84.1 6.25 + 89.0 6.31 + 93.9 6.38 + 98.8 6.46 + 103.6 6.54 + 108.5 6.62 + 113.4 6.71 + 118.3 6.80 + 123.1 6.90 + 128.0 6.99 + 132.9 7.09 + 137.8 7.19 + 142.6 7.29 + 147.5 7.40 + 152.4 7.50 + 157.3 7.61 + 162.1 7.71 + 167.0 7.82 + 171.9 7.92 + 176.8 8.03 + 181.6 8.14 + 186.5 8.24 + 191.4 8.35 + 196.3 8.46 + 201.1 8.57 + 206.0 8.67 + 210.9 8.78 + 215.8 8.89 + 220.6 9.00 + 225.5 9.10 + 230.4 9.21 + 235.3 9.32 + 240.1 9.43 + 245.0 9.53 + 249.9 9.64 + 254.8 9.75 + 259.6 9.85 + 264.5 9.96 + 269.4 10.07 + 274.3 10.17 + 279.1 10.28 + 284.0 10.39 + 288.9 10.49 + 293.8 10.60 + 298.6 10.70 + 303.5 10.81 + 308.4 10.91 + 313.3 11.02 + 318.1 11.12 + 323.0 11.23 + 327.9 11.33 + 332.8 11.44 + 337.6 11.54 + 342.5 11.65 + 347.4 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/091_Pa_eIMFP.txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/091_Pa_eIMFP.txt new file mode 100644 index 0000000..6c15e9e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/091_Pa_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + Pa + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 231.03588 + +DENSITY: 15.4000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 6.58 + 54.9 6.26 + 59.8 6.03 + 64.6 5.88 + 69.5 5.78 + 74.4 5.71 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100644 index 0000000..230166e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_OpticalData_NIST/092_U_eIMFP.txt @@ -0,0 +1,422 @@ + +ELEMENT: + U + +SOURCE: + Tanuma, Powell and Penn + Surface Interface Anal. 21 (1994) 165. + IMFP values determined from TPP-2M equation + + +ATOMIC WEIGHT: 238.02890 + +DENSITY: 19.1000 g/cm**3 + +TABULATION: + +______________________________________________________________________________ + + Energy IMFP + eV Angstroms +______________________________________________________________________________ + 50.0 6.99 + 54.9 6.42 + 59.8 6.03 + 64.6 5.76 + 69.5 5.57 + 74.4 5.43 + 79.3 5.34 + 84.1 5.28 + 89.0 5.25 + 93.9 5.23 + 98.8 5.23 + 103.6 5.24 + 108.5 5.26 + 113.4 5.29 + 118.3 5.32 + 123.1 5.36 + 128.0 5.40 + 132.9 5.45 + 137.8 5.49 + 142.6 5.55 + 147.5 5.60 + 152.4 5.66 + 157.3 5.71 + 162.1 5.77 + 167.0 5.83 + 171.9 5.90 + 176.8 5.96 + 181.6 6.02 + 186.5 6.09 + 191.4 6.15 + 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11.25 + 566.8 11.31 + 571.6 11.37 + 576.5 11.44 + 581.4 11.50 + 586.3 11.57 + 591.1 11.63 + 596.0 11.70 + 600.9 11.76 + 605.8 11.82 + 610.6 11.89 + 615.5 11.95 + 620.4 12.01 + 625.3 12.08 + 630.1 12.14 + 635.0 12.21 + 639.9 12.27 + 644.8 12.33 + 649.6 12.40 + 654.5 12.46 + 659.4 12.52 + 664.3 12.58 + 669.1 12.65 + 674.0 12.71 + 678.9 12.77 + 683.8 12.84 + 688.6 12.90 + 693.5 12.96 + 698.4 13.02 + 703.3 13.09 + 708.1 13.15 + 713.0 13.21 + 717.9 13.27 + 722.8 13.34 + 727.6 13.40 + 732.5 13.46 + 737.4 13.52 + 742.3 13.58 + 747.1 13.65 + 752.0 13.71 + 756.9 13.77 + 761.8 13.83 + 766.6 13.89 + 771.5 13.96 + 776.4 14.02 + 781.3 14.08 + 786.1 14.14 + 791.0 14.20 + 795.9 14.26 + 800.8 14.32 + 805.6 14.38 + 810.5 14.45 + 815.4 14.51 + 820.3 14.57 + 825.1 14.63 + 830.0 14.69 + 834.9 14.75 + 839.8 14.81 + 844.6 14.87 + 849.5 14.93 + 854.4 14.99 + 859.3 15.05 + 864.1 15.12 + 869.0 15.18 + 873.9 15.24 + 878.8 15.30 + 883.6 15.36 + 888.5 15.42 + 893.4 15.48 + 898.3 15.54 + 903.1 15.60 + 908.0 15.66 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19.64 + 1244.4 19.69 + 1249.3 19.75 + 1254.1 19.81 + 1259.0 19.87 + 1263.9 19.92 + 1268.8 19.98 + 1273.6 20.04 + 1278.5 20.09 + 1283.4 20.15 + 1288.3 20.21 + 1293.1 20.26 + 1298.0 20.32 + 1302.9 20.38 + 1307.8 20.43 + 1312.6 20.49 + 1317.5 20.55 + 1322.4 20.60 + 1327.3 20.66 + 1332.1 20.72 + 1337.0 20.77 + 1341.9 20.83 + 1346.8 20.89 + 1351.6 20.94 + 1356.5 21.00 + 1361.4 21.06 + 1366.3 21.11 + 1371.1 21.17 + 1376.0 21.22 + 1380.9 21.28 + 1385.8 21.34 + 1390.6 21.39 + 1395.5 21.45 + 1400.4 21.51 + 1405.3 21.56 + 1410.1 21.62 + 1415.0 21.67 + 1419.9 21.73 + 1424.8 21.79 + 1429.6 21.84 + 1434.5 21.90 + 1439.4 21.95 + 1444.3 22.01 + 1449.1 22.06 + 1454.0 22.12 + 1458.9 22.18 + 1463.8 22.23 + 1468.6 22.29 + 1473.5 22.34 + 1478.4 22.40 + 1483.3 22.45 + 1488.1 22.51 + 1493.0 22.56 + 1497.9 22.62 + 1502.8 22.68 + 1507.6 22.73 + 1512.5 22.79 + 1517.4 22.84 + 1522.3 22.90 + 1527.1 22.95 + 1532.0 23.01 + 1536.9 23.06 + 1541.8 23.12 + 1546.6 23.17 + 1551.5 23.23 + 1556.4 23.28 + 1561.3 23.34 + 1566.1 23.39 + 1571.0 23.45 + 1575.9 23.50 + 1580.8 23.56 + 1585.6 23.61 + 1590.5 23.67 + 1595.4 23.72 + 1600.3 23.78 + 1605.1 23.83 + 1610.0 23.89 + 1614.9 23.94 + 1619.8 24.00 + 1624.6 24.05 + 1629.5 24.11 + 1634.4 24.16 + 1639.3 24.22 + 1644.1 24.27 + 1649.0 24.33 + 1653.9 24.38 + 1658.8 24.44 + 1663.6 24.49 + 1668.5 24.55 + 1673.4 24.60 + 1678.3 24.65 + 1683.1 24.71 + 1688.0 24.76 + 1692.9 24.82 + 1697.8 24.87 + 1702.6 24.93 + 1707.5 24.98 + 1712.4 25.03 + 1717.3 25.09 + 1722.1 25.14 + 1727.0 25.20 + 1731.9 25.25 + 1736.8 25.31 + 1741.6 25.36 + 1746.5 25.41 + 1751.4 25.47 + 1756.3 25.52 + 1761.1 25.58 + 1766.0 25.63 + 1770.9 25.68 + 1775.8 25.74 + 1780.6 25.79 + 1785.5 25.85 + 1790.4 25.90 + 1795.3 25.95 + 1800.1 26.01 + 1805.0 26.06 + 1809.9 26.12 + 1814.8 26.17 + 1819.6 26.22 + 1824.5 26.28 + 1829.4 26.33 + 1834.3 26.39 + 1839.1 26.44 + 1844.0 26.49 + 1848.9 26.55 + 1853.8 26.60 + 1858.6 26.65 + 1863.5 26.71 + 1868.4 26.76 + 1873.3 26.81 + 1878.1 26.87 + 1883.0 26.92 + 1887.9 26.98 + 1892.8 27.03 + 1897.6 27.08 + 1902.5 27.14 + 1907.4 27.19 + 1912.3 27.24 + 1917.1 27.30 + 1922.0 27.35 + 1926.9 27.40 + 1931.8 27.46 + 1936.6 27.51 + 1941.5 27.56 + 1946.4 27.62 + 1951.3 27.67 + 1956.1 27.72 + 1961.0 27.77 + 1965.9 27.83 + 1970.8 27.88 + 1975.6 27.93 + 1980.5 27.99 + 1985.4 28.04 + 1990.3 28.09 + 1995.1 28.15 + 2000.0 28.20 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_PCC.mat b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_PCC.mat new file mode 100644 index 0000000..308485d Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_PCC.mat differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_export2matlab.mlx b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_export2matlab.mlx new file mode 100644 index 0000000..c052d54 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/data/eIMFPD_export2matlab.mlx differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S1.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S1.m new file mode 100644 index 0000000..870d549 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S1.m @@ -0,0 +1,48 @@ +function imfp = eimfp_S1(ke_dat, rho, M, Egap, Z) +% imfp = eimfp_S1(ke_dat, rho, M, Egap, Z) +% Function that determines the electron inelastic mean free path (IMFP) +% based on the S1 equation described by M. P. Seah [1]. The IMFP here +% additionally depends on the value of Z and this formalism is compatible +% for elemental or binary materials. +% +% REFERENCE: +% [1] M. P. Seah, “An accurate and simple universal curve for the +% energy-dependent electron inelastic mean free path,†+% Surf. Interface Anal., vol. 44, no. 4, pp. 497–503, 2012, +% doi: 10.1002/sia.4816. +% +% IN: +% - ke_dat: N×1 vector of the input electron kinetic energy (for PES; KE = BE - PHI) [eV] +% - rho: scalar of the density of the material (g/cc) +% - M: scalar of the atomic or molecular weight (in amu == g/mol) +% - Egap: scalar of the band gap energy (eV) +% - Z: scalar of the atomic mass number of the element (or average for compound) (Z) +% +% OUT: +% - imfp: N×1 column vector of the electron IMFP values [Angstroms] + +%% Default parameters (Parameters for Silicon) +if nargin < 5; Z = 14; end +if nargin < 4; Egap = 1.12000; end +if nargin < 3; M = 28.085000; end +if nargin < 2; rho = 2.3300000; end +if isempty(Z); Z = 14; end +if isempty(Egap); Egap = 1.12000; end % eV +if isempty(M); M = 28.085000; end % amu == g/mol +if isempty(rho); rho = 2.3300000; end % g/cc +% -- Defining the constants +NA = 6.02214086e23; % Avogadro constant +%% - 1 - Determination of the IMFP using S1 formalism (M P Seah) +% If the kinetic energy is negative, assume it is zero +ke_dat(ke_dat<0) = 0; +% Evaluating the imfp +a = ((1e21 .* M) ./ (rho .* NA)).^(1./3); % nm +% Relativistic corrected equation +imfp = (4 + 0.44 .* Z.^(0.5) + 0.104 .* ke_dat.^(0.872)) .* a.^(1.7) ./ (Z.^(0.3) .* (1 - 0.02 .*Egap)); % IMFP in nanometres +% If isnan, return zero +imfp(isnan(imfp)) = 0; +% Convert IMFP from nm to Angstroms +imfp = 10 .* imfp; +%% Ensuring the imfp is a column vector +if size(imfp, 2) >1; imfp = imfp'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S1_mpd.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S1_mpd.m new file mode 100644 index 0000000..3817762 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S1_mpd.m @@ -0,0 +1,40 @@ +function imfp = eimfp_S1_mpd(ke_dat, material) +% imfp = eimfp_S1_mpd(ke_dat, material) +% Function that determines the electron inelastic mean free path (IMFP) +% based on the S1 equation described by M. P. Seah [1]. The IMFP here +% additionally depends on the value of Z and this formalism is compatible +% for elemental or binary materials. In this function, you can define the +% material as a string and it will look it up the relevant parameters in +% the Material Properties Database (MPD) ('MPD_PCC.mat') and determine +% the imfp using the S1 equation. +% +% REFERENCE: +% [1] M. P. Seah, “An accurate and simple universal curve for the +% energy-dependent electron inelastic mean free path,†+% Surf. Interface Anal., vol. 44, no. 4, pp. 497–503, 2012, +% doi: 10.1002/sia.4816. +% +% IN: +% - ke_dat: N×1 vector of the input electron kinetic energy (for PES; KE = BE - PHI) [eV] +% - material: string of the material whose imfp is to be determined; e.g. "Si", "SiO2", "InAs", "Al2O3"... +% +% OUT: +% - imfp: N×1 column vector of the electron IMFP values [Angstroms] + +%% Default parameters (Parameters for Silicon) +if nargin < 2; material = "Si"; end +if isempty(material); material = "Si"; end +%% - 1 - Extracting the material parameters from the materials database +% - Extracting the material properties +material_props = get_mpd_props(material); +% - Extracting the material properties required for the S1 formalism +rho = material_props.DENSITY; +Nv = material_props.ELECT_VALENCY; +M = material_props.ATOM_MASS; +Egap = material_props.ELE_BGAP; +Z = material_props.ATOM_ZNUM; +%% - 2 - Determination of the IMFP via S1 formalism +imfp = eimfp_S1(ke_dat, rho, M, Egap, Z); % extract imfp in Angstroms +%% Ensuring the imfp is a column vector +if size(imfp, 2) >1; imfp = imfp'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S2_avg.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S2_avg.m new file mode 100644 index 0000000..9aa9b15 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S2_avg.m @@ -0,0 +1,35 @@ +function imfp = eimfp_S2_avg(ke_dat, Z) +% imfp = eimfp_S2_avg(ke_dat, Z) +% Function that determines the electron inelastic mean free path (IMFP) +% based on the S2 equation described by M. P. Seah [1]. The IMFP here +% only depends on the value of Z. +% +% REFERENCE: +% [1] M. P. Seah, “An accurate and simple universal curve for the +% energy-dependent electron inelastic mean free path,†+% Surf. Interface Anal., vol. 44, no. 4, pp. 497–503, 2012, +% doi: 10.1002/sia.4816. +% +% IN: +% - ke_dat: N×1 vector of the input electron kinetic energy (for PES; KE = BE - PHI) [eV] +% - Z: scalar of the atomic mass number (Z) (or average for compounds) +% +% OUT: +% - imfp: N×1 column vector of the electron IMFP values [Angstroms] + +%% Default parameters (Parameters for Silicon) +if nargin < 2; Z = 14; end +if isempty(Z); Z = 14; end + +%% - 1 - Determination of the IMFP TPP-2M +% If the kinetic energy is negative, assume it is zero +ke_dat(ke_dat<0) = 0; +% Evaluating the imfp +a = 2.5; % Average atomic spacing in Angstroms +% Relativistic corrected equation +imfp = a .* ((1.52 + 0.167 .* Z.^(0.5) + 0.0394 .* ke_dat.^(0.872)) ./ Z.^(0.3)); % IMFP in Angstroms +% If isnan, return zero +imfp(isnan(imfp)) = 0; +%% Ensuring the imfp is a column vector +if size(imfp, 2) >1; imfp = imfp'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S2_avg_mpd.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S2_avg_mpd.m new file mode 100644 index 0000000..d77b159 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_S2_avg_mpd.m @@ -0,0 +1,42 @@ +function imfp = eimfp_S2_avg_mpd(ke_dat, material) +% imfp = eimfp_S2_avg_mpd(ke_dat, material) +% Function that determines the electron inelastic mean free path (IMFP) +% based on the S2 equation described by M. P. Seah [1]. The IMFP here +% only depends on the value of Z. In this function, you can define the +% material as a string and it will look it up the relevant parameters in +% the Material Properties Database (MPD) ('MPD_PCC.mat') and determine +% the imfp using the S2 equation. +% +% REFERENCE: +% [1] M. P. Seah, “An accurate and simple universal curve for the +% energy-dependent electron inelastic mean free path,†+% Surf. Interface Anal., vol. 44, no. 4, pp. 497–503, 2012, +% doi: 10.1002/sia.4816. +% +% IN: +% - ke_dat: N×1 vector of the input electron kinetic energy (for PES; KE = BE - PHI) [eV] +% - material: string of the material whose imfp is to be determined; e.g. "Si", "SiO2", "InAs", "Al2O3"... +% +% OUT: +% - imfp: N×1 column vector of the electron IMFP values [Angstroms] + +%% Default parameters (Parameters for Silicon) +if nargin < 2; material = "Si"; end +if isempty(material); material = "Si"; end +%% - 1 - Extracting the material parameters from the materials database +% - Extracting the material properties +material_props = get_mpd_props(material); +% - Extracting the material properties required for the S2 formalism +Z = material_props.ATOM_ZNUM; +%% - 2 - Determination of the IMFP TPP-2M +% If the kinetic energy is negative, assume it is zero +ke_dat(ke_dat<0) = 0; +% Evaluating the imfp +a = 2.5; % Average atomic spacing in Angstroms +% Relativistic corrected equation +imfp = a .* ((1.52 + 0.167 .* Z.^(0.5) + 0.0394 .* ke_dat.^(0.872)) ./ Z.^(0.3)); % IMFP in Angstroms +% If isnan, return zero +imfp(isnan(imfp)) = 0; +%% Ensuring the imfp is a column vector +if size(imfp, 2) >1; imfp = imfp'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_optical.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_optical.m new file mode 100644 index 0000000..6d3eae2 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_optical.m @@ -0,0 +1,49 @@ +function [imfp, dimfp] = eimfp_optical(ke_dat, element) +% [imfp, dimfp] = eimfp_optical(ke_dat, element) +% Function that determines the mean and uncertainty of the experimental values +% of the electron IMFP taken from optical / experimental data. The data +% used is from the NIST Electron Inelastic-Mean-Free-Path Database [1]. +% Any NaN output values means no experimental data exists for the input +% kinetic energy, otherwise, the output is the mean and range of the +% experimental values. +% +% REFERENCE: +% [1] NIST Electron Inelastic-Mean-Free-Path Database: http://dx.doi.org/10.18434/T48C78. +% +% IN: +% - ke_dat: N×1 vector of the input electron kinetic energy (for PES; KE = BE - PHI) [eV] +% - element: char/string of the element; e.g. "H", "He", "Si", "In"... +% +% OUT: +% - imfp: N×1 column vector of the electron IMFP values [Angstroms] +% - dimfp: N×1 column vector of the IMFP uncertainties [Angstroms] + +%% Default parameters (Parameters for Silicon) +if nargin < 2; element = []; end +if isempty(element); element = []; end +%% - 1 - Extracting the IMFP from the optical IMFP database +[ek0, imfp0] = get_eimfpd_props(element); +%% - 2 - Calculate the average and variance of the IMFP values for all datasets +imfp = []; dimfp = []; +% - Filing through all the kinetic energies to be determined +for i = 1:length(ke_dat) + % -- Extract the value of the closest kinetic energy from the optical data + ke_i = ke_dat(i); + imfp_i = []; + for j = 1:size(ek0, 2) + imfp_i(j) = interp1(ek0(:,j), imfp0(:,j), ke_i, 'linear'); + end + % -- Extract the value of the closest kinetic energy from the optical data + imfp_i(isnan(imfp_i)) = []; + if isempty(imfp_i) + imfp(i) = NaN; + dimfp(i) = NaN; + else + imfp(i) = mean(imfp_i); + dimfp(i) = 0.5*range(imfp_i); + end +end +%% Ensuring the imfp is a column vector +if size(imfp, 2) >1; imfp = imfp'; end +if size(dimfp, 2) >1; dimfp = dimfp'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_tpp2m.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_tpp2m.m new file mode 100644 index 0000000..4ea63f0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_tpp2m.m @@ -0,0 +1,63 @@ +function imfp = eimfp_tpp2m(ke_dat, rho, Nv, M, Egap) +% imfp = eimfp_tpp2m(ke_dat, rho, Nv, M, Egap) +% Function that determines the electron inelastic mean free path (IMFP) +% based on the TPP-2M energy compensation factor [1], which is a more +% accurate method than the standard universal curve determination. The +% input parameters of the materials are now required. The TPP-2M equation +% is also relativistically corrected here, as per reference [2]. +% +% REFERENCE: +% [1] Tanuma, S., Powell, C. J., & Penn, D. R. (1987). +% Proposed formula for electron inelastic mean free paths based on +% calculations for 31 materials. Surface Science Letters, 192(1), +% L849–L857. https://doi.org/10.1016/0167-2584(87)90829-2 +% [2] Shinotsuka H, Tanuma S, Powell CJ, Penn DR. Calculations of +% electron inelastic mean free paths. XII. Data for 42 inorganic +% compounds over the 50 eV to 200 keV range with the full Penn +% algorithm. Surf Interface Anal. 2018;51(4):427-457. +% doi:10.1002/sia.6598 +% [1] M. P. Seah, “An accurate and simple universal curve for the +% energy-dependent electron inelastic mean free path,†+% Surf. Interface Anal., vol. 44, no. 4, pp. 497–503, 2012, +% doi: 10.1002/sia.4816. + +% +% IN: +% - ke_dat: N×1 vector of the input electron kinetic energy (for PES; KE = BE - PHI) [eV] +% - rho: scalar of the density of the material (g/cc) +% - Nv: scalar of the number of valence electrons per atom (for an element) +% - M: scalar of the atomic or molecular weight (in amu == g/mol) +% - Egap: scalar of the band gap energy (eV) +% +% OUT: +% - imfp: N×1 column vector of the electron IMFP values [Angstroms] + +%% Default parameters (Parameters for Silicon) +if nargin < 5; Egap = 1.12000; end +if nargin < 4; M = 28.085000; end +if nargin < 3; Nv = 4; end +if nargin < 2; rho = 2.3300000; end +if isempty(Egap); Egap = 1.12000; end % eV +if isempty(M); M = 28.085000; end % amu == g/mol +if isempty(Nv); Nv = 4; end % integer +if isempty(rho); rho = 2.3300000; end % g/cc +%% - 1 - Determination of the IMFP TPP-2M +% If the kinetic energy is negative, assume it is zero +ke_dat(ke_dat<0) = 0; +% Evaluating the imfp +Ep = 28.816 .* sqrt(Nv .* rho ./ M); % eV +alpha = (1 + ke_dat ./ 1021999.8) ./ (1 + ke_dat ./ 510998.9).^2; % relativistic correction +beta = -1.0 + 9.44 ./ sqrt(Ep.^2 + Egap.^2) + 0.69 .* rho.^(0.1); % (eV−1 nm−1) +gamma = 0.191 .* rho.^(-0.5); % eV−1 +U = (Ep ./ 28.816).^2; +D = 534 - 208 .* U; % eV nm−1 +C = 19.7 - 9.1 .* U; % nm−1 +% Relativistic corrected equation +imfp = alpha .* ke_dat ./ (Ep.^2 .* (beta .* log(alpha .* gamma .* ke_dat) - (C./ke_dat) + (D./(ke_dat.^2)))); % IMFP in nanometres +% If isnan, return zero +imfp(isnan(imfp)) = 0; +% Convert IMFP from nm to Angstroms +imfp = 10 .* imfp; +%% Ensuring the imfp is a column vector +if size(imfp, 2) >1; imfp = imfp'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_tpp2m_avg.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_tpp2m_avg.m new file mode 100644 index 0000000..68bbaec --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_tpp2m_avg.m @@ -0,0 +1,26 @@ +function imfp = eimfp_tpp2m_avg(ke_dat) +% imfp = eimfp_tpp2m_avg(ke_dat) +% Function that determines the electron inelastic mean free path (IMFP) +% that is based on the average trend line of photoelectron kinetic +% energies for multiple material systems. This method is considered +% better than the universal method, but less precise than the TPP-2M +% calculations, where the specific material parameters are used. +% +% IN: +% - ke_dat: N×1 vector of the input electron kinetic energy (for PES; KE = BE - PHI) [eV] +% +% OUT: +% - imfp: N×1 column vector of the electron IMFP values [Angstroms] + +%% - 1 - Determination of the IMFP using universal formula +% If the kinetic energy is negative, assume it is zero +ke_dat(ke_dat<0) = 0; +% Evaluating the imfp +imfp = 0.01997 .* ke_dat .^ (0.6659); % IMFP in nano-metres +% If isnan, return zero +imfp(isnan(imfp)) = 0; +% Convert IMFP from nm to Angstroms +imfp = 10 .* imfp; +%% Ensuring the imfp is a column vector +if size(imfp, 2) >1; imfp = imfp'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_tpp2m_mpd.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_tpp2m_mpd.m new file mode 100644 index 0000000..fb6a180 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_tpp2m_mpd.m @@ -0,0 +1,41 @@ +function imfp = eimfp_tpp2m_mpd(ke_dat, material) +% imfp = eimfp_tpp2m_mpd(ke_dat, material) +% Function that determines the electron inelastic mean free path (IMFP) +% based on the TPP-2M energy compensation factor, which is a more +% accurate method than the standard universal curve determination. The +% input parameters of the materials however are now required. In this +% function, you can define the material as a string and it will look it +% up the relevant parameters in the Material Properties Database (MPD) +% ('MPD_PCC.mat') and determine the imfp using the TPP-2M equation. +% +% REFERENCE: +% Tanuma, S., Powell, C. J., & Penn, D. R. (1987). +% Proposed formula for electron inelastic mean free paths based on +% calculations for 31 materials. Surface Science Letters, 192(1), +% L849–L857. https://doi.org/10.1016/0167-2584(87)90829-2 +% +% IN: +% - ke_dat: N×1 vector of the input electron kinetic energy (for PES; KE = HV - BE - PHI) [eV] +% - material: string of the material whose imfp is to be determined; e.g. "Si", "SiO2", "Al2O3"... +% +% OUT: +% - imfp: N×1 column vector of the electron IMFP values [Angstroms] + +%% Default parameters (Parameters for Silicon) +if nargin < 2; material = "Si"; end +if isempty(material); material = "Si"; end +%% - 1 - Extracting the material parameters from the materials database +% - Ensure the input is a string +material = string(material); +% - Extracting the material properties +material_props = get_mpd_props(material); +% - Extracting the material properties required to determine the TPP-2M IMFP +rho = material_props.DENSITY; +Nv = material_props.ELECT_VALENCY; +M = material_props.ATOM_MASS; +Egap = material_props.ELE_BGAP; +%% - 2 - Determination of the IMFP TPP-2M +imfp = eimfp_tpp2m(ke_dat, rho, Nv, M, Egap); +%% Ensuring the imfp is a column vector +if size(imfp, 2) >1; imfp = imfp'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_universal.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_universal.m new file mode 100644 index 0000000..0349231 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/eimfp_calculators/eimfp_universal.m @@ -0,0 +1,25 @@ +function imfp = eimfp_universal(ke_dat) +% imfp = eimfp_universal(ke_dat) +% Function that determines the universal electron inelastic mean free +% path (IMFP) in elements based on the KE^0.5 equation. This gives a +% good, first order approximation of the IMFP values, with the only +% required input being the electron kinetic energy. +% +% IN: +% - ke_dat: N×1 column vector of the input electron kinetic energy (for PES; KE = BE - PHI) [eV] +% +% OUT: +% - imfp: N×1 column vector of the electron IMFP values [Angstroms] + +%% - 1 - Determination of the IMFP using universal formula +% If the kinetic energy is negative, assume it is zero +ke_dat(ke_dat<0) = 0; +% Evaluating the imfp +imfp = (143 ./ ke_dat.^2) + 0.054 .* sqrt(ke_dat); % IMFP in nano-metres +% If isnan, return zero +imfp(isnan(imfp)) = 0; +% Convert IMFP from nm to Angstroms +imfp = 10 .* imfp; +%% Ensuring the imfp is a column vector +if size(imfp, 2) >1; imfp = imfp'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/get_eimfpd_props.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/get_eimfpd_props.m new file mode 100644 index 0000000..582f777 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/get_eimfpd_props.m @@ -0,0 +1,45 @@ +function [ke_dat, imfp] = get_eimfpd_props(element) +% [ke_dat, imfp] = get_eimfpd_props(element) +% This is a function that extracts all of the experimental IMFPs from the +% Electron Inelastic Mean Free Path Database (eIMFPD) for the element +% defined here by the user. This database contains all the experimental +% IMFP values for elements 1 - 92, for kinetic energies in the approximate +% range of 10 - 10,000 eV. +% +% IN: +% - element: char/string of the element; e.g. "H", "He", "Si", "In"... +% +% OUT: +% - ke_dat: N×M array of the N'th electron kinetic energies taken from M'th file. +% - imfp: N×M array of the N'th imfp taken from M'th file. + +%% Default parameters +if nargin < 1; element = []; end +if isempty(element); element = []; end + +%% - 1 - Loading the eIMFP properties from our MATLAB database +eIMFPD_PCC = load('eIMFPD_PCC.mat'); eIMFPD_PCC = eIMFPD_PCC.eIMFPD_PCC; + +%% - 2 - Find the index of the element defined by the user +% -- Find the element +if ~isempty(element) + % -- Find the row-number / index for the element of choice (case-insensitive) + element = char(element); + ele_indx = find(strcmpi([eIMFPD_PCC.ATOM_SYMB], element)); + if isempty(ele_indx) + msg = 'Element could not be identified. Only use atomic-symbols for elements 1 - 92; H, He, Li, Be..., Pa, U'; error(msg) + end +% -- If no element is defined, return an error +else + msg = 'Element could not be identified. Only use atomic-symbols for elements 1 - 92; H, He, Li, Be..., Pa, U'; error(msg) +end + +%% - 3 - Extracting the IMFP data +data = eIMFPD_PCC.DataTable{ele_indx}; +ke_dat = []; +imfp = []; +for i = 1:eIMFPD_PCC.Length(ele_indx) + ke_dat(:,i) = table2array(data(:,2*i-1)); + imfp(:,i) = table2array(data(:,2*i)); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/view_eimfp_props.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/view_eimfp_props.m new file mode 100644 index 0000000..15dd551 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Electron Inelastic Mean Free Path Database (eIMFPD)/view_eimfp_props.m @@ -0,0 +1,80 @@ +function view_eimfp_props(material) +% view_eimfp_props(material) +% This is a function that plots the eIMFP curves of a particular material +% defined by the user using all availabe calculators. This can be used to +% quickly view all the available eIMFP data for a particular element / +% material. +% +% IN: +% - material: string of the material whose imfp is to be shown; e.g. "Si", "SiO2", "Al2O3"... +% +% OUT: (figure output) + +%% Default parameters (Parameters for Silicon) +if nargin < 1; material = "Si"; end +if isempty(material); material = "Si"; end +%% - 1 - Extracting the material parameters from the materials database +% - Extracting the material properties +material_props = get_mpd_props(material); +% - Extracting the material properties required for the S1 formalism +rho = material_props.DENSITY; +Nv = material_props.ELECT_VALENCY; +M = material_props.ATOM_MASS; +Egap = material_props.ELE_BGAP; +Z = material_props.ATOM_ZNUM; +%% - 2 - Extracting the eIMFP properties from each calculator +ele_imfp = struct(); +% -- Defining the kinetic energy range +ele_imfp.Ek = linspace(1, 5e5, 1e5); +% -- Optical data +[ele_imfp.imfp_opt, ele_imfp.dimfp_opt] = eimfp_optical(ele_imfp.Ek, material); +% -- S1 & S2 predictive equations +ele_imfp.imfp_S1 = eimfp_S1_mpd(ele_imfp.Ek, material); +ele_imfp.imfp_S2_avg = eimfp_S2_avg(ele_imfp.Ek, Z); +% -- TPP2M predictive equations +ele_imfp.imfp_tpp2m = eimfp_tpp2m_mpd(ele_imfp.Ek, material); +ele_imfp.imfp_tpp2m_avg = eimfp_tpp2m_avg(ele_imfp.Ek); +% -- Unversal curve +ele_imfp.imfp_universal = eimfp_universal(ele_imfp.Ek); +%% - 3 - Plotting the eIMFP figure +% -- Initialising the figure +fig = figure(); hold on; +fig.Position(3) = 600; +fig.Position(4) = 450; +grid on; grid minor; +% - PLOTTING OPTICAL/EXPERIMENTAL DATA +errorbar(ele_imfp.Ek, ele_imfp.imfp_opt, ele_imfp.dimfp_opt, ele_imfp.dimfp_opt, 'rx-'); +% - PLOTTING TPP2M-CURVE +loglog(ele_imfp.Ek, ele_imfp.imfp_tpp2m, ':', 'color', 'b', 'LineWidth', 2.0); +% - PLOTTING TPP2M-AVERAGE-CURVE +loglog(ele_imfp.Ek, ele_imfp.imfp_tpp2m_avg, '--', 'color', 'b', 'LineWidth', 2.0); +% - PLOTTING S1-CURVE +loglog(ele_imfp.Ek, ele_imfp.imfp_S1, ':', 'color', 'g', 'LineWidth', 2.0); +% - PLOTTING S2-AVERAGE-CURVE +loglog(ele_imfp.Ek, ele_imfp.imfp_S2_avg, '--', 'color', 'g', 'LineWidth', 2.0); +% - PLOTTING UNIVERSAL CURVE +loglog(ele_imfp.Ek, ele_imfp.imfp_universal, '-', 'color', 'k', 'LineWidth', 3.0); +% - FORMATTING THE FIGURE +% -- Plotting the x- and y-axes +a = line([0 0], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); +b = line([-1e5, 1e5], [0 0], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); +a.Annotation.LegendInformation.IconDisplayStyle = 'off'; +b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Labelling the x- and y-axes +xlabel('$$ \bf Electron\ Kinetic\ Energy\ [eV] $$', 'interpreter', 'latex'); +ylabel('$$ \bf IMFP\ [Angstrom] $$', 'interpreter', 'latex'); +ax = gca; +ax.FontSize = 12; +ax.XLim = [1, 1e4]; ax.YLim = [1, 1e3]; +ax.XScale = 'log'; ax.YScale = 'log'; +text(0.05, 0.07, string(material), 'FontSize', 18, 'color', 'k', 'Units','normalized', 'FontWeight', 'bold'); +% -- Add a legend +h = zeros(6, 1); +h(1) = plot(NaN,NaN,'k-', 'LineWidth', 3.0); +h(2) = plot(NaN,NaN,'rx-'); +h(3) = plot(NaN,NaN,'b:', 'LineWidth', 2.0); +h(4) = plot(NaN,NaN,'b--', 'LineWidth', 2.0); +h(5) = plot(NaN,NaN,'g:', 'LineWidth', 2.0); +h(6) = plot(NaN,NaN,'g--', 'LineWidth', 2.0); +legend(h, 'Universal','Optical/Experiment','TPP-2M','TPP-2M(avg)','S1','S2(avg)', 'fontsize', 10); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/data/MPD_PCC.accdb b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/data/MPD_PCC.accdb new file mode 100644 index 0000000..39d9822 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/data/MPD_PCC.accdb differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/data/MPD_PCC.mat b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/data/MPD_PCC.mat new file mode 100644 index 0000000..7538869 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/data/MPD_PCC.mat differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/data/MPD_PCC_export2matlab.mlx b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/data/MPD_PCC_export2matlab.mlx new file mode 100644 index 0000000..fa54abc Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/data/MPD_PCC_export2matlab.mlx differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/get_mpd_props.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/get_mpd_props.m new file mode 100644 index 0000000..91ef59a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Material Properties Database (MPD)/get_mpd_props.m @@ -0,0 +1,31 @@ +function material_props = get_mpd_props(material) +% material_props = get_mpd_props(material) +% This is a function that extracts all of the parameters from the +% Materials Properties Database (MPD) for the material defined here by +% the user. +% +% IN: +% - material: char/string of the material; e.g. "Si", "SiO2", "Al2O3"... +% +% OUT: +% - material_props: MATLAB table which contains all of the material parameters. + +%% Default parameters +if nargin < 1; material = []; end +if isempty(material); material = []; end + +%% - 1 - Extracting the material parameters from the materials properties database +% -- Loading in the materials database +MPD_PCC = load('MPD_PCC.mat'); MPD_PCC = MPD_PCC.MPD_PCC; +% -- Making the input material be in a 'char' format +material = char(material); +% -- Find the row-number / index for the material of choice +atom_symbols = MPD_PCC.ATOM_SYMB; +idx = find(strcmpi(atom_symbols(:), material)); +% -- Extract the properties of the desired material +if ~isempty(idx); material_props = MPD_PCC(idx,:); +% -- If no material is identified, return an error +else; msg = 'Material could not be identified or does not exist in database.'; material_props = []; +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/001_H_K(1s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/001_H_K(1s).txt new file mode 100644 index 0000000..dcee4ae --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/001_H_K(1s).txt @@ -0,0 +1,107 @@ +16.7 3.635 3.634 3.637 2 2 2 +20 2.215 2.215 2.216 2 2 2 +21.2 1.884 1.884 1.885 2 2 2 +25 1.186 1.186 1.187 2 2 2 +26.8 0.9737 0.9739 0.9745 2 2 2 +30 0.7055 0.7057 0.7061 2 2 2 +35 0.4523 0.4523 0.4526 2 2 2 +40 0.3065 0.3064 0.3066 2 2 2 +40.8 0.2892 0.2892 0.2893 2 2 2 +45 0.2167 0.2167 0.2168 2 2 2 +50 0.1586 0.1586 0.1587 2 2 2 +55 0.1194 0.1194 0.1194 2 2 2 +60 0.09199 0.09196 0.092 2 2 2 +65 0.07227 0.07225 0.07228 2 2 2 +70 0.05773 0.05774 0.05776 2 2 2 +75 0.0468 0.04682 0.04684 2 2 2 +80 0.03844 0.03846 0.03847 2 2 2 +85 0.03193 0.03195 0.03196 2 2 2 +90 0.0268 0.02681 0.02682 2 2 2 +95 0.0227 0.0227 0.02271 2 2 2 +100 0.01939 0.01938 0.01938 2 2 2 +105 0.01668 0.01667 0.01667 2 2 2 +110 0.01444 0.01443 0.01443 2 2 2 +115 0.01258 0.01257 0.01257 2 2 2 +120 0.01101 0.01101 0.01101 2 2 2 +125 0.009699 0.009691 0.009693 2 2 2 +130 0.008581 0.008573 0.008575 2 2 2 +132.3 0.008123 0.008115 0.008117 2 2 2 +135 0.007625 0.007617 0.007619 2 2 2 +140 0.006802 0.006796 0.006798 2 2 2 +145 0.00609 0.006087 0.006089 2 2 2 +150 0.005471 0.005471 0.005473 2 2 2 +151.4 0.005313 0.005314 0.005315 2 2 2 +155 0.004932 0.004935 0.004936 2 2 2 +160 0.00446 0.004465 0.004466 2 2 2 +165 0.004046 0.004051 0.004052 2 2 2 +170 0.00368 0.003687 0.003687 2 2 2 +175 0.003357 0.003364 0.003364 2 2 2 +180 0.003071 0.003076 0.003077 2 2 2 +185 0.002816 0.002821 0.002821 2 2 2 +190 0.002589 0.002592 0.002592 2 2 2 +195 0.002386 0.002386 0.002386 2 2 2 +200 0.002202 0.002201 0.002201 2 2 2 +205 0.002035 0.002035 0.002035 2 2 2 +210 0.001884 0.001884 0.001884 2 2 2 +215 0.001748 0.001748 0.001748 2 2 2 +220 0.001624 0.001624 0.001624 2 2 2 +225 0.001511 0.001512 0.001512 2 2 2 +230 0.001409 0.001409 0.001409 2 2 2 +235 0.001316 0.001315 0.001315 2 2 2 +240 0.00123 0.00123 0.001229 2 2 2 +245 0.001152 0.001151 0.001151 2 2 2 +250 0.00108 0.001079 0.001078 2 2 2 +255 0.001013 0.001012 0.001012 2 2 2 +260 0.0009519 0.0009508 0.0009508 2 2 2 +265 0.0008949 0.0008943 0.0008943 2 2 2 +270 0.0008421 0.0008421 0.0008421 2 2 2 +275 0.0007932 0.0007938 0.0007937 2 2 2 +280 0.0007477 0.000749 0.000749 2 2 2 +285 0.0007057 0.0007075 0.0007074 2 2 2 +290 0.0006669 0.0006689 0.0006688 2 2 2 +295 0.0006313 0.000633 0.0006329 2 2 2 +300 0.0005985 0.0005996 0.0005994 2 2 2 +305 0.0005681 0.0005684 0.0005683 2 2 2 +310 0.0005398 0.0005393 0.0005391 2 2 2 +320 0.0004883 0.0004866 0.0004865 2 2 2 +340 0.0004001 0.0003997 0.0003997 2 2 2 +360 0.000332 0.000332 0.000332 2 2 2 +380 0.0002801 0.0002784 0.0002784 2 2 2 +400 0.0002368 0.0002355 0.0002356 2 2 2 +420 0.0002002 0.0002008 0.0002009 2 2 2 +440 0.0001719 0.0001725 0.0001726 2 2 2 +460 0.0001496 0.0001492 0.0001492 2 2 2 +480 0.0001296 0.0001297 0.0001298 2 2 2 +500 0.0001125 0.0001135 0.0001135 2 2 2 +520 9.944e-05 9.981e-05 9.98e-05 2 2 2 +540 8.856e-05 8.816e-05 8.815e-05 2 2 2 +560 7.851e-05 7.82e-05 7.821e-05 2 2 2 +580 6.968e-05 6.967e-05 6.967e-05 2 2 2 +600 6.224e-05 6.23e-05 6.23e-05 2 2 2 +620 5.598e-05 5.592e-05 5.591e-05 2 2 2 +640 5.052e-05 5.035e-05 5.035e-05 2 2 2 +660 4.543e-05 4.548e-05 4.548e-05 2 2 2 +680 4.086e-05 4.121e-05 4.121e-05 2 2 2 +700 3.713e-05 3.746e-05 3.744e-05 2 2 2 +720 3.406e-05 3.413e-05 3.41e-05 2 2 2 +740 3.126e-05 3.117e-05 3.114e-05 2 2 2 +760 2.87e-05 2.853e-05 2.85e-05 2 2 2 +780 2.639e-05 2.617e-05 2.615e-05 2 2 2 +800 2.424e-05 2.405e-05 2.404e-05 2 2 2 +850 1.969e-05 1.966e-05 1.966e-05 2 2 2 +900 1.59e-05 1.626e-05 1.625e-05 2 2 2 +950 1.336e-05 1.36e-05 1.357e-05 2 2 2 +1000 1.159e-05 1.146e-05 1.144e-05 2 2 2 +1041 1.028e-05 1.001e-05 1e-05 2 2 2 +1050 9.986e-06 9.724e-06 9.719e-06 2 2 2 +1100 8.422e-06 8.311e-06 8.319e-06 2 2 2 +1150 6.941e-06 7.162e-06 7.17e-06 2 2 2 +1200 6.027e-06 6.218e-06 6.218e-06 2 2 2 +1250 5.544e-06 5.423e-06 5.423e-06 2 2 2 +1253.6 5.522e-06 5.371e-06 5.371e-06 2 2 2 +1300 5.165e-06 4.743e-06 4.755e-06 2 2 2 +1350 4.455e-06 4.165e-06 4.19e-06 2 2 2 +1400 3.487e-06 3.684e-06 3.708e-06 2 2 2 +1450 2.849e-06 3.288e-06 3.296e-06 2 2 2 +1486.6 2.755e-06 3.034e-06 3.031e-06 2 2 2 +1500 2.78e-06 2.947e-06 2.942e-06 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/002_He_K(1s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/002_He_K(1s).txt new file mode 100644 index 0000000..ca5894a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/002_He_K(1s).txt @@ -0,0 +1,105 @@ +25 7.305 7.306 7.31 2 2 2 +26.8 6.44 6.448 6.452 2 2 2 +30 5.203 5.211 5.214 2 2 2 +35 3.831 3.828 3.829 2 2 2 +40 2.897 2.893 2.895 2 2 2 +40.8 2.777 2.773 2.774 2 2 2 +45 2.242 2.242 2.244 2 2 2 +50 1.772 1.776 1.777 2 2 2 +55 1.43 1.433 1.433 2 2 2 +60 1.174 1.174 1.174 2 2 2 +65 0.9769 0.9751 0.9754 2 2 2 +70 0.8213 0.8193 0.8196 2 2 2 +75 0.6965 0.6955 0.6959 2 2 2 +80 0.5955 0.5959 0.5962 2 2 2 +85 0.5135 0.5147 0.5149 2 2 2 +90 0.4465 0.4478 0.4479 2 2 2 +95 0.3914 0.3921 0.3922 2 2 2 +100 0.3454 0.3454 0.3454 2 2 2 +105 0.3065 0.3058 0.3058 2 2 2 +110 0.273 0.272 0.2721 2 2 2 +115 0.244 0.2431 0.2432 2 2 2 +120 0.2186 0.2181 0.2182 2 2 2 +125 0.1964 0.1964 0.1965 2 2 2 +130 0.1771 0.1775 0.1776 2 2 2 +132.3 0.1691 0.1696 0.1697 2 2 2 +135 0.1603 0.161 0.1611 2 2 2 +140 0.1457 0.1464 0.1465 2 2 2 +145 0.133 0.1336 0.1336 2 2 2 +150 0.1219 0.1222 0.1222 2 2 2 +151.4 0.119 0.1192 0.1192 2 2 2 +155 0.1121 0.112 0.112 2 2 2 +160 0.1032 0.1029 0.1029 2 2 2 +165 0.09526 0.09478 0.09479 2 2 2 +170 0.08798 0.08746 0.08747 2 2 2 +175 0.08131 0.08086 0.08088 2 2 2 +180 0.07519 0.07489 0.07493 2 2 2 +185 0.06959 0.0695 0.06954 2 2 2 +190 0.0645 0.0646 0.06464 2 2 2 +195 0.05991 0.06016 0.06018 2 2 2 +200 0.05577 0.0561 0.05612 2 2 2 +205 0.05206 0.0524 0.05241 2 2 2 +210 0.04873 0.04901 0.04901 2 2 2 +215 0.04572 0.0459 0.0459 2 2 2 +220 0.043 0.04304 0.04303 2 2 2 +225 0.04049 0.0404 0.0404 2 2 2 +230 0.03817 0.03797 0.03797 2 2 2 +235 0.03599 0.03572 0.03573 2 2 2 +240 0.03394 0.03365 0.03365 2 2 2 +245 0.03199 0.03172 0.03173 2 2 2 +250 0.03015 0.02994 0.02995 2 2 2 +255 0.0284 0.02828 0.0283 2 2 2 +260 0.02677 0.02675 0.02676 2 2 2 +265 0.02525 0.02532 0.02533 2 2 2 +270 0.02384 0.02399 0.024 2 2 2 +275 0.02255 0.02275 0.02276 2 2 2 +280 0.02137 0.02159 0.0216 2 2 2 +285 0.02029 0.02051 0.02051 2 2 2 +290 0.01932 0.0195 0.0195 2 2 2 +295 0.01842 0.01855 0.01855 2 2 2 +300 0.0176 0.01766 0.01765 2 2 2 +305 0.01683 0.01682 0.01682 2 2 2 +310 0.0161 0.01603 0.01603 2 2 2 +315 0.01541 0.01529 0.01529 2 2 2 +320 0.01475 0.01459 0.01459 2 2 2 +340 0.01228 0.01218 0.01218 2 2 2 +360 0.01018 0.01026 0.01026 2 2 2 +380 0.008602 0.008718 0.008718 2 2 2 +400 0.007465 0.007463 0.007459 2 2 2 +420 0.006526 0.006425 0.006425 2 2 2 +440 0.005631 0.005565 0.005569 2 2 2 +460 0.004812 0.004849 0.004853 2 2 2 +480 0.004165 0.004251 0.004252 2 2 2 +500 0.003704 0.003745 0.003743 2 2 2 +520 0.003349 0.003312 0.00331 2 2 2 +540 0.003007 0.002939 0.002939 2 2 2 +560 0.002649 0.002618 0.00262 2 2 2 +580 0.002314 0.002342 0.002344 2 2 2 +600 0.00205 0.002104 0.002104 2 2 2 +620 0.001866 0.001896 0.001895 2 2 2 +640 0.00173 0.001713 0.001712 2 2 2 +660 0.001596 0.001551 0.001551 2 2 2 +680 0.001443 0.001408 0.001409 2 2 2 +700 0.001281 0.001281 0.001283 2 2 2 +720 0.001138 0.00117 0.001171 2 2 2 +740 0.001034 0.001072 0.001072 2 2 2 +760 0.0009666 0.000984 0.0009831 2 2 2 +780 0.0009169 0.0009045 0.0009036 2 2 2 +800 0.000863 0.0008325 0.0008322 2 2 2 +850 0.0006757 0.0006825 0.0006832 2 2 2 +900 0.0005483 0.0005676 0.0005671 2 2 2 +950 0.0004977 0.0004758 0.0004755 2 2 2 +1000 0.0004038 0.0004018 0.0004024 2 2 2 +1041 0.0003331 0.000353 0.0003531 2 2 2 +1050 0.0003241 0.0003435 0.0003434 2 2 2 +1100 0.0003035 0.0002957 0.0002953 2 2 2 +1150 0.0002681 0.0002555 0.0002558 2 2 2 +1200 0.0002116 0.0002227 0.000223 2 2 2 +1250 0.0001896 0.0001957 0.0001955 2 2 2 +1253.6 0.0001893 0.0001939 0.0001937 2 2 2 +1300 0.0001854 0.0001724 0.0001724 2 2 2 +1350 0.0001565 0.0001524 0.0001527 2 2 2 +1400 0.0001245 0.0001358 0.000136 2 2 2 +1450 0.0001181 0.0001217 0.0001216 2 2 2 +1486.6 0.0001197 0.0001124 0.0001123 2 2 2 +1500 0.0001184 0.0001091 0.0001091 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/003_Li_K(1s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/003_Li_K(1s).txt new file mode 100644 index 0000000..8bf4ba9 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/003_Li_K(1s).txt @@ -0,0 +1,102 @@ +60 3.248 3.246 3.247 2 2 2 +65 3.264 3.26 3.261 2 2 2 +70 3.086 3.086 3.087 2 2 2 +75 2.829 2.831 2.833 2 2 2 +80 2.552 2.555 2.556 2 2 2 +85 2.283 2.286 2.286 2 2 2 +90 2.036 2.036 2.037 2 2 2 +95 1.813 1.812 1.813 2 2 2 +100 1.615 1.614 1.614 2 2 2 +105 1.441 1.439 1.44 2 2 2 +110 1.289 1.287 1.288 2 2 2 +115 1.155 1.154 1.154 2 2 2 +120 1.038 1.038 1.038 2 2 2 +125 0.9361 0.9361 0.9367 2 2 2 +130 0.8467 0.8471 0.8476 2 2 2 +132.3 0.8093 0.8099 0.8104 2 2 2 +135 0.7682 0.769 0.7694 2 2 2 +140 0.6992 0.7001 0.7005 2 2 2 +145 0.6384 0.6393 0.6396 2 2 2 +150 0.5846 0.5853 0.5856 2 2 2 +151.4 0.5707 0.5713 0.5716 2 2 2 +155 0.5368 0.5373 0.5375 2 2 2 +160 0.4943 0.4945 0.4947 2 2 2 +165 0.4562 0.4561 0.4563 2 2 2 +170 0.422 0.4217 0.4219 2 2 2 +175 0.3912 0.3907 0.3908 2 2 2 +180 0.3633 0.3627 0.3628 2 2 2 +185 0.338 0.3373 0.3375 2 2 2 +190 0.3149 0.3143 0.3145 2 2 2 +195 0.2939 0.2933 0.2935 2 2 2 +200 0.2746 0.2742 0.2744 2 2 2 +205 0.257 0.2568 0.2569 2 2 2 +210 0.2408 0.2407 0.2409 2 2 2 +215 0.226 0.226 0.2262 2 2 2 +220 0.2123 0.2125 0.2127 2 2 2 +225 0.1998 0.2001 0.2002 2 2 2 +230 0.1882 0.1886 0.1887 2 2 2 +235 0.1775 0.1779 0.178 2 2 2 +240 0.1676 0.1681 0.1681 2 2 2 +245 0.1585 0.1589 0.159 2 2 2 +250 0.15 0.1504 0.1505 2 2 2 +255 0.1422 0.1425 0.1425 2 2 2 +260 0.1349 0.1351 0.1352 2 2 2 +265 0.1281 0.1282 0.1283 2 2 2 +270 0.1217 0.1218 0.1218 2 2 2 +275 0.1158 0.1158 0.1158 2 2 2 +280 0.1103 0.1102 0.1102 2 2 2 +285 0.105 0.1049 0.1049 2 2 2 +290 0.1001 0.09993 0.09996 2 2 2 +295 0.09553 0.09528 0.0953 2 2 2 +300 0.09118 0.0909 0.09093 2 2 2 +305 0.08707 0.08679 0.08682 2 2 2 +310 0.08319 0.08291 0.08294 2 2 2 +315 0.07951 0.07926 0.07929 2 2 2 +320 0.07604 0.07581 0.07585 2 2 2 +325 0.07275 0.07256 0.0726 2 2 2 +330 0.06963 0.06949 0.06953 2 2 2 +335 0.06668 0.06659 0.06663 2 2 2 +340 0.06388 0.06385 0.06389 2 2 2 +345 0.06124 0.06125 0.06129 2 2 2 +350 0.05873 0.05879 0.05883 2 2 2 +355 0.05636 0.05647 0.0565 2 2 2 +360 0.05412 0.05426 0.05429 2 2 2 +380 0.04629 0.04649 0.0465 2 2 2 +400 0.03999 0.04012 0.04013 2 2 2 +420 0.03486 0.03487 0.03487 2 2 2 +440 0.03058 0.03048 0.03048 2 2 2 +460 0.02694 0.0268 0.0268 2 2 2 +480 0.0238 0.02368 0.02369 2 2 2 +500 0.02108 0.02103 0.02105 2 2 2 +520 0.01873 0.01876 0.01878 2 2 2 +540 0.01673 0.01681 0.01682 2 2 2 +560 0.01502 0.01512 0.01512 2 2 2 +580 0.01358 0.01365 0.01365 2 2 2 +600 0.01233 0.01235 0.01235 2 2 2 +620 0.01124 0.01122 0.01122 2 2 2 +640 0.01027 0.01021 0.01021 2 2 2 +660 0.009389 0.00932 0.009322 2 2 2 +680 0.008581 0.008527 0.008531 2 2 2 +700 0.007843 0.00782 0.007825 2 2 2 +720 0.007176 0.007189 0.007193 2 2 2 +740 0.006582 0.006623 0.006626 2 2 2 +760 0.006059 0.006114 0.006116 2 2 2 +780 0.005603 0.005656 0.005656 2 2 2 +800 0.005205 0.005242 0.005241 2 2 2 +850 0.004388 0.004364 0.004363 2 2 2 +900 0.00371 0.003666 0.003667 2 2 2 +950 0.003116 0.003108 0.00311 2 2 2 +1000 0.002628 0.002657 0.002658 2 2 2 +1041 0.002321 0.00235 0.00235 2 2 2 +1050 0.002264 0.002289 0.002288 2 2 2 +1100 0.00199 0.001984 0.001983 2 2 2 +1150 0.001756 0.001728 0.001728 2 2 2 +1200 0.001532 0.001513 0.001514 2 2 2 +1250 0.001327 0.001333 0.001334 2 2 2 +1253.6 0.001313 0.001321 0.001322 2 2 2 +1300 0.001159 0.00118 0.00118 2 2 2 +1350 0.001034 0.001049 0.001049 2 2 2 +1400 0.000939 0.0009371 0.0009367 2 2 2 +1450 0.0008543 0.0008393 0.0008392 2 2 2 +1486.6 0.0007912 0.0007758 0.0007762 2 2 2 +1500 0.0007678 0.0007542 0.0007547 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/003_Li_L1(2s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/003_Li_L1(2s).txt new file mode 100644 index 0000000..f114e1e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/003_Li_L1(2s).txt @@ -0,0 +1,108 @@ +10.2 1.235 1.239 1.241 2 2 2 +15 0.8072 0.8065 0.8078 2 2 2 +16.7 0.6906 0.6938 0.6947 2 2 2 +20 0.5274 0.5258 0.5263 2 2 2 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/004_Be_K(1s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/004_Be_K(1s).txt new file mode 100644 index 0000000..edbfc90 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/004_Be_K(1s).txt @@ -0,0 +1,99 @@ +120 2.338 2.337 2.338 2 2 2 +125 2.048 2.045 2.046 2 2 2 +130 1.86 1.858 1.859 2 2 2 +132.3 1.791 1.79 1.791 2 2 2 +135 1.72 1.719 1.72 2 2 2 +140 1.605 1.605 1.606 2 2 2 +145 1.504 1.505 1.506 2 2 2 +150 1.411 1.412 1.413 2 2 2 +151.4 1.386 1.387 1.388 2 2 2 +155 1.324 1.325 1.326 2 2 2 +160 1.241 1.242 1.243 2 2 2 +165 1.162 1.163 1.164 2 2 2 +170 1.088 1.089 1.089 2 2 2 +175 1.018 1.018 1.019 2 2 2 +180 0.9525 0.9528 0.9533 2 2 2 +185 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/004_Be_L1(2s).txt new file mode 100644 index 0000000..a3e0fb8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/004_Be_L1(2s).txt @@ -0,0 +1,109 @@ +10 1.989 1.999 2.012 2 2 2 +10.2 2.027 2.035 2.047 2 2 2 +15 2.043 2.043 2.053 2 2 2 +16.71 1.896 1.904 1.911 2 2 2 +20 1.627 1.626 1.632 2 2 2 +21.22 1.535 1.531 1.536 2 2 2 +25 1.272 1.272 1.276 2 2 2 +26.86 1.161 1.165 1.168 2 2 2 +30 1.005 1.01 1.013 2 2 2 +35 0.8187 0.816 0.8178 2 2 2 +40 0.6685 0.6689 0.6705 2 2 2 +40.81 0.6471 0.6486 0.6501 2 2 2 +45 0.5522 0.5556 0.5567 2 2 2 +50 0.4667 0.4662 0.4669 2 2 2 +55 0.396 0.3942 0.3949 2 2 2 +60 0.3347 0.336 0.3366 2 2 2 +65 0.2863 0.2886 0.2889 2 2 2 +70 0.2495 0.2493 0.2495 2 2 2 +75 0.2182 0.2166 0.2168 2 2 2 +80 0.1896 0.1893 0.1895 2 2 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2 2 2 +1253.6 0.0001535 0.0001638 0.0001641 2 2 2 +1300 0.0001524 0.0001477 0.0001474 2 2 2 +1350 0.0001239 0.0001318 0.0001319 2 2 2 +1400 0.000125 0.0001187 0.0001184 2 2 2 +1450 0.0001062 0.0001064 0.0001066 2 2 2 +1486.6 8.797e-05 9.903e-05 9.897e-05 2 2 2 +1500 9.573e-05 9.647e-05 9.636e-05 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/005_B_K(1s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/005_B_K(1s).txt new file mode 100644 index 0000000..bc59f73 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/005_B_K(1s).txt @@ -0,0 +1,92 @@ +200 1.335 1.335 1.336 2 2 2 +205 1.227 1.226 1.227 2 2 2 +210 1.159 1.158 1.159 2 2 2 +215 1.109 1.109 1.109 2 2 2 +220 1.067 1.067 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Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/005_B_L1(2s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/005_B_L1(2s).txt new file mode 100644 index 0000000..12cbb0e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/005_B_L1(2s).txt @@ -0,0 +1,108 @@ +15 1.588 1.594 1.602 2 2 2 +16.71 1.716 1.72 1.728 2 2 2 +20 1.763 1.757 1.763 2 2 2 +21.22 1.74 1.734 1.739 2 2 2 +25 1.611 1.611 1.616 2 2 2 +26.86 1.536 1.54 1.544 2 2 2 +30 1.414 1.417 1.42 2 2 2 +35 1.236 1.233 1.236 2 2 2 +40 1.074 1.071 1.074 2 2 2 +40.81 1.049 1.047 1.05 2 2 2 +45 0.9306 0.9323 0.9344 2 2 2 +50 0.8121 0.8135 0.815 2 2 2 +55 0.7131 0.7115 0.7128 2 2 2 +60 0.6264 0.6239 0.6251 2 2 2 +65 0.5494 0.5488 0.55 2 2 2 +70 0.4831 0.4845 0.4855 2 2 2 +75 0.4278 0.4293 0.4301 2 2 2 +80 0.3817 0.3818 0.3824 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/006_C_L1(2s).txt new file mode 100644 index 0000000..460e1d7 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/006_C_L1(2s).txt @@ -0,0 +1,107 @@ +20 1.149 1.149 1.158 2 2 2 +21.22 1.23 1.234 1.243 2 2 2 +25 1.358 1.365 1.371 2 2 2 +26.86 1.378 1.38 1.386 2 2 2 +30 1.37 1.367 1.372 2 2 2 +35 1.293 1.291 1.296 2 2 2 +40 1.188 1.192 1.196 2 2 2 +40.81 1.17 1.175 1.179 2 2 2 +45 1.084 1.089 1.092 2 2 2 +50 0.9885 0.9892 0.9915 2 2 2 +55 0.8984 0.8958 0.8979 2 2 2 +60 0.8124 0.8102 0.8122 2 2 2 +65 0.7323 0.7327 0.7346 2 2 2 +70 0.6606 0.6632 0.6647 2 2 2 +75 0.5982 0.6009 0.6021 2 2 2 +80 0.544 0.5452 0.5461 2 2 2 +85 0.4962 0.4954 0.4963 2 2 2 +90 0.4528 0.451 0.4518 2 2 2 +95 0.4131 0.4115 0.4123 2 2 2 +100 0.3768 0.3763 0.3771 2 2 2 +105 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Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/007_N_K(1s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/007_N_K(1s).txt new file mode 100644 index 0000000..45fe787 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/007_N_K(1s).txt @@ -0,0 +1,82 @@ +405 0.7032 0.7031 0.7034 2 2 2 +410 0.6547 0.6545 0.6548 2 2 2 +415 0.6281 0.6277 0.628 2 2 2 +420 0.6107 0.6103 0.6105 2 2 2 +425 0.5978 0.5973 0.5976 2 2 2 +430 0.587 0.5865 0.5868 2 2 2 +435 0.5769 0.5765 0.5768 2 2 2 +440 0.5669 0.5665 0.5668 2 2 2 +445 0.5566 0.5563 0.5565 2 2 2 +450 0.5458 0.5455 0.5458 2 2 2 +455 0.5346 0.5343 0.5346 2 2 2 +460 0.5229 0.5227 0.523 2 2 2 +465 0.5109 0.5107 0.511 2 2 2 +470 0.4987 0.4986 0.4989 2 2 2 +475 0.4865 0.4865 0.4868 2 2 2 +480 0.4744 0.4745 0.4747 2 2 2 +485 0.4625 0.4626 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/008_O_K(1s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/008_O_K(1s).txt new file mode 100644 index 0000000..13b1fa6 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/008_O_K(1s).txt @@ -0,0 +1,77 @@ +540 0.514 0.5139 0.5142 2 2 2 +545 0.49 0.4898 0.49 2 2 2 +550 0.4771 0.4769 0.4771 2 2 2 +555 0.4686 0.4683 0.4685 2 2 2 +560 0.462 0.4617 0.4619 2 2 2 +565 0.4562 0.4559 0.4561 2 2 2 +570 0.4506 0.4504 0.4506 2 2 2 +575 0.445 0.4447 0.4449 2 2 2 +580 0.4391 0.4388 0.439 2 2 2 +585 0.4328 0.4326 0.4328 2 2 2 +590 0.4261 0.4259 0.4262 2 2 2 +595 0.4192 0.419 0.4192 2 2 2 +600 0.4119 0.4118 0.412 2 2 2 +605 0.4045 0.4043 0.4045 2 2 2 +610 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0.04004 2 2 2 +1500 0.03907 0.03904 0.03906 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/008_O_L1(2s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/008_O_L1(2s).txt new file mode 100644 index 0000000..601d9a4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/008_O_L1(2s).txt @@ -0,0 +1,104 @@ +30 0.5241 0.5207 0.5254 2 2 2 +35 0.7227 0.722 0.7272 2 2 2 +40 0.8238 0.8278 0.8326 2 2 2 +40.81 0.8342 0.8385 0.8432 2 2 2 +45 0.8696 0.8731 0.8771 2 2 2 +50 0.8816 0.8815 0.885 2 2 2 +55 0.8705 0.8681 0.8713 2 2 2 +60 0.8441 0.8418 0.8448 2 2 2 +65 0.8087 0.8082 0.8111 2 2 2 +70 0.7693 0.7709 0.7735 2 2 2 +75 0.7292 0.7319 0.7342 2 2 2 +80 0.6901 0.6926 0.6945 2 2 2 +85 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/009_F_K(1s).txt new file mode 100644 index 0000000..0e4dbc3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/009_F_K(1s).txt @@ -0,0 +1,77 @@ +690 0.4103 0.4103 0.4105 2 2 2 +695 0.3869 0.3868 0.387 2 2 2 +700 0.3778 0.3777 0.3779 2 2 2 +705 0.3727 0.3726 0.3728 2 2 2 +710 0.3691 0.369 0.3692 2 2 2 +715 0.3661 0.366 0.3661 2 2 2 +720 0.3633 0.3631 0.3633 2 2 2 +725 0.3603 0.3601 0.3603 2 2 2 +730 0.3571 0.357 0.3571 2 2 2 +735 0.3537 0.3535 0.3537 2 2 2 +740 0.3499 0.3498 0.35 2 2 2 +745 0.3459 0.3457 0.3459 2 2 2 +750 0.3416 0.3414 0.3416 2 2 2 +755 0.337 0.3369 0.3371 2 2 2 +760 0.3323 0.3322 0.3323 2 2 2 +765 0.3274 0.3273 0.3275 2 2 2 +770 0.3224 0.3223 0.3225 2 2 2 +775 0.3173 0.3173 0.3174 2 2 2 +780 0.3123 0.3122 0.3124 2 2 2 +785 0.3072 0.3071 0.3073 2 2 2 +790 0.3022 0.3021 0.3023 2 2 2 +795 0.2972 0.2972 0.2974 2 2 2 +800 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/009_F_L1(2s).txt new file mode 100644 index 0000000..6f1f196 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/009_F_L1(2s).txt @@ -0,0 +1,104 @@ +40 0.4967 0.4937 0.4979 2 2 2 +40.81 0.5185 0.5159 0.5201 2 2 2 +45 0.607 0.6071 0.6115 2 2 2 +50 0.6717 0.6746 0.6786 2 2 2 +55 0.7072 0.7101 0.7136 2 2 2 +60 0.723 0.7238 0.7269 2 2 2 +65 0.7242 0.7228 0.7256 2 2 2 +70 0.7145 0.7119 0.7146 2 2 2 +75 0.6969 0.6945 0.6971 2 2 2 +80 0.6742 0.6729 0.6754 2 2 2 +85 0.6486 0.6487 0.6511 2 2 2 +90 0.6219 0.623 0.6252 2 2 2 +95 0.595 0.5967 0.5987 2 2 2 +100 0.5686 0.5702 0.572 2 2 2 +105 0.543 0.5441 0.5456 2 2 2 +110 0.5183 0.5184 0.5199 2 2 2 +115 0.4943 0.4936 0.4949 2 2 2 +120 0.471 0.4696 0.4709 2 2 2 +125 0.4484 0.4467 0.448 2 2 2 +130 0.4265 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Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/009_F_L23(2p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/009_F_L23(2p).txt new file mode 100644 index 0000000..a90131c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/009_F_L23(2p).txt @@ -0,0 +1,107 @@ +20 8.917 8.907 8.887 0.08679 0.08499 0.08987 +21.22 9.305 9.304 9.287 0.2535 0.2525 0.2566 +25 9.839 9.845 9.832 0.607 0.6076 0.6098 +26.86 9.876 9.875 9.862 0.7244 0.725 0.7265 +30 9.742 9.726 9.716 0.8741 0.8743 0.8751 +35 9.223 9.21 9.204 1.036 1.036 1.036 +40 8.535 8.538 8.534 1.145 1.145 1.145 +40.81 8.417 8.422 8.418 1.16 1.16 1.159 +45 7.803 7.809 7.805 1.224 1.224 1.224 +50 7.075 7.071 7.068 1.284 1.283 1.283 +55 6.363 6.352 6.35 1.33 1.329 1.328 +60 5.681 5.672 5.671 1.365 1.365 1.364 +65 5.045 5.043 5.043 1.394 1.394 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/011_Na_K(1s).txt new file mode 100644 index 0000000..838aed4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/011_Na_K(1s).txt @@ -0,0 +1,65 @@ +1065 0.2078 0.2078 0.2079 2 2 2 +1070 0.2268 0.2267 0.2269 2 2 2 +1075 0.2401 0.2399 0.2401 2 2 2 +1080 0.2481 0.2479 0.2481 2 2 2 +1085 0.2522 0.252 0.2522 2 2 2 +1090 0.2536 0.2534 0.2536 2 2 2 +1095 0.253 0.2529 0.253 2 2 2 +1100 0.2513 0.2511 0.2512 2 2 2 +1105 0.2487 0.2485 0.2487 2 2 2 +1110 0.2456 0.2454 0.2456 2 2 2 +1115 0.2423 0.2422 0.2423 2 2 2 +1120 0.2389 0.2388 0.2389 2 2 2 +1125 0.2356 0.2354 0.2355 2 2 2 +1130 0.2323 0.2321 0.2323 2 2 2 +1135 0.2291 0.229 0.2291 2 2 2 +1140 0.2261 0.2259 0.2261 2 2 2 +1145 0.2232 0.2231 0.2232 2 2 2 +1150 0.2205 0.2203 0.2205 2 2 2 +1155 0.2179 0.2177 0.2179 2 2 2 +1160 0.2154 0.2152 0.2154 2 2 2 +1165 0.213 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/011_Na_L1(2s).txt @@ -0,0 +1,100 @@ +70 .5067 .5042 .5077 2 2 2 +75 .5673 .5645 .5681 2 2 2 +80 .6029 .6014 .6052 2 2 2 +85 .6202 .6206 .6243 2 2 2 +90 .6247 .6266 .6302 2 2 2 +95 .6205 .6232 .6264 2 2 2 +100 .6104 .6131 .6161 2 2 2 +105 .5965 .5986 .6013 2 2 2 +110 .5802 .5814 .5838 2 2 2 +115 .5624 .5625 .5647 2 2 2 +120 .5437 .5428 .5449 2 2 2 +125 .5246 .523 .525 2 2 2 +130 .5054 .5035 .5054 2 2 2 +132.3 .4967 .4946 .4965 2 2 2 +135 .4865 .4844 .4863 2 2 2 +140 .4679 .466 .4679 2 2 2 +145 .4499 .4484 .4502 2 2 2 +150 .4325 .4315 .4333 2 2 2 +151.4 .4278 .4269 .4287 2 2 2 +155 .4159 .4155 .4171 2 2 2 +160 .4 .4002 .4018 2 2 2 +165 .385 .3857 .3872 2 2 2 +170 .3708 .3718 .3732 2 2 2 +175 .3573 .3586 .36 2 2 2 +180 .3446 .3461 .3473 2 2 2 +185 .3326 .3341 .3352 2 2 2 +190 .3213 .3227 .3237 2 2 2 +195 .3106 .3117 .3127 2 2 2 +200 .3004 .3012 .3021 2 2 2 +205 .2907 .2912 .292 2 2 2 +210 .2814 .2816 .2824 2 2 2 +215 .2725 .2724 .2731 2 2 2 +220 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0.007842 0.007953 0.007963 2 2 2 +1350 0.007244 0.007269 0.007275 2 2 2 +1400 0.006728 0.006658 0.006664 2 2 2 +1450 0.006214 0.00611 0.006119 2 2 2 +1486.6 0.005825 0.005748 0.005759 2 2 2 +1500 0.005682 0.005623 0.005634 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/011_Na_L23(2p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/011_Na_L23(2p).txt new file mode 100644 index 0000000..167f64a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/011_Na_L23(2p).txt @@ -0,0 +1,104 @@ +40 3.991 3.989 3.98 -0.3934 -0.3939 -0.3885 +40.81 4.292 4.288 4.28 -0.2907 -0.2915 -0.2863 +45 5.709 5.707 5.702 0.1599 0.1588 0.1627 +50 7.007 7.013 7.011 0.5156 0.5152 0.5177 +55 7.817 7.826 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9.318e-05 2 2 2 +1486.6 8.622e-05 8.758e-05 8.77e-05 2 2 2 +1500 8.412e-05 8.572e-05 8.582e-05 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/012_Mg_K(1s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/012_Mg_K(1s).txt new file mode 100644 index 0000000..d96737a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/012_Mg_K(1s).txt @@ -0,0 +1,43 @@ +1295 0.2073 0.2071 0.2073 2 2 2 +1300 0.204 0.2038 0.204 2 2 2 +1305 0.2018 0.2017 0.2018 2 2 2 +1310 0.2008 0.2007 0.2008 2 2 2 +1315 0.2006 0.2004 0.2005 2 2 2 +1320 0.2006 0.2005 0.2006 2 2 2 +1325 0.2007 0.2005 0.2006 2 2 2 +1330 0.2004 0.2003 0.2004 2 2 2 +1335 0.1999 0.1997 0.1998 2 2 2 +1340 0.1989 0.1987 0.1988 2 2 2 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/012_Mg_L23(2p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/012_Mg_L23(2p).txt new file mode 100644 index 0000000..eb5ca4b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/012_Mg_L23(2p).txt @@ -0,0 +1,102 @@ +60 3.289 3.295 3.29 -0.2697 -0.263 -0.2577 +65 5.154 5.142 5.137 0.1565 0.1576 0.1612 +70 6.243 6.223 6.221 0.4836 0.4825 0.4848 +75 6.703 6.691 6.692 0.7051 0.7038 0.7052 +80 6.796 6.798 6.8 0.8607 0.8599 0.8607 +85 6.695 6.709 6.711 0.9753 0.975 0.9753 +90 6.492 6.511 6.513 1.063 1.063 1.063 +95 6.228 6.246 6.247 1.133 1.133 1.133 +100 5.925 5.938 5.938 1.189 1.189 1.189 +105 5.598 5.603 5.603 1.236 1.236 1.235 +110 5.258 5.256 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Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/013_Al_L1(2s).txt @@ -0,0 +1,99 @@ +120 0.5785 0.5779 0.581 2 2 2 +125 0.538 0.5368 0.5396 2 2 2 +130 0.5249 0.5236 0.5263 2 2 2 +132.3 0.5224 0.5212 0.5238 2 2 2 +135 0.5206 0.5196 0.5222 2 2 2 +140 0.518 0.5174 0.52 2 2 2 +145 0.5139 0.5138 0.5163 2 2 2 +150 0.5074 0.5077 0.5101 2 2 2 +151.4 0.5051 0.5055 0.5079 2 2 2 +155 0.4983 0.499 0.5013 2 2 2 +160 0.4874 0.4883 0.4905 2 2 2 +165 0.4753 0.4762 0.4784 2 2 2 +170 0.4627 0.4636 0.4656 2 2 2 +175 0.4501 0.4508 0.4527 2 2 2 +180 0.4377 0.4383 0.4401 2 2 2 +185 0.4258 0.4261 0.4278 2 2 2 +190 0.4143 0.4145 0.4161 2 2 2 +195 0.4033 0.4032 0.4048 2 2 2 +200 0.3927 0.3924 0.3939 2 2 2 +205 0.3824 0.382 0.3834 2 2 2 +210 0.3724 0.3718 0.3732 2 2 2 +215 0.3626 0.3619 0.3633 2 2 2 +220 0.3529 0.3522 0.3535 2 2 2 +225 0.3434 0.3427 0.344 2 2 2 +230 0.3341 0.3334 0.3347 2 2 2 +235 0.3249 0.3244 0.3256 2 2 2 +240 0.316 0.3155 0.3167 2 2 2 +245 0.3072 0.3069 0.3081 2 2 2 +250 0.2988 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/014_Si_L1(2s).txt @@ -0,0 +1,96 @@ +151.4 0.5043 0.5039 0.5065 2 2 2 +155 0.4846 0.4839 0.4864 2 2 2 +160 0.474 0.4732 0.4756 2 2 2 +165 0.4714 0.4706 0.4729 2 2 2 +170 0.4701 0.4695 0.4718 2 2 2 +175 0.4673 0.4669 0.4692 2 2 2 +180 0.462 0.4619 0.4641 2 2 2 +185 0.4545 0.4546 0.4568 2 2 2 +190 0.4452 0.4455 0.4476 2 2 2 +195 0.4349 0.4353 0.4373 2 2 2 +200 0.4241 0.4247 0.4266 2 2 2 +205 0.4134 0.414 0.4158 2 2 2 +210 0.4031 0.4036 0.4054 2 2 2 +215 0.3931 0.3936 0.3953 2 2 2 +220 0.3837 0.3841 0.3857 2 2 2 +225 0.3747 0.375 0.3766 2 2 2 +230 0.3661 0.3663 0.3678 2 2 2 +235 0.3578 0.3579 0.3593 2 2 2 +240 0.3498 0.3497 0.3511 2 2 2 +245 0.3419 0.3417 0.3431 2 2 2 +250 0.3341 0.3339 0.3352 2 2 2 +255 0.3264 0.3261 0.3274 2 2 2 +260 0.3188 0.3185 0.3197 2 2 2 +265 0.3113 0.311 0.3122 2 2 2 +270 0.3039 0.3036 0.3047 2 2 2 +275 0.2967 0.2963 0.2974 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/015_P_L23(2p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/015_P_L23(2p).txt new file mode 100644 index 0000000..b97f48d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/015_P_L23(2p).txt @@ -0,0 +1,97 @@ +140 2.328 2.332 2.331 0.5395 0.5411 0.5438 +145 5.075 5.077 5.077 0.4161 0.4174 0.4205 +150 4.872 4.87 4.87 0.4993 0.4998 0.5025 +151.4 4.758 4.755 4.755 0.5311 0.5315 0.534 +155 4.536 4.532 4.532 0.6142 0.6144 0.6164 +160 4.369 4.365 4.365 0.722 0.7219 0.7234 +165 4.285 4.282 4.282 0.8165 0.8164 0.8174 +170 4.222 4.22 4.221 0.8982 0.898 0.8987 +175 4.148 4.147 4.148 0.9686 0.9685 0.9688 +180 4.05 4.051 4.052 1.029 1.029 1.029 +185 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and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/015_P_M1(3s).txt new file mode 100644 index 0000000..36eaec3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/015_P_M1(3s).txt @@ -0,0 +1,107 @@ +20 0.122 0.122 0.1322 2 2 2 +21.22 0.1714 0.173 0.1842 2 2 2 +25 0.301 0.3042 0.3156 2 2 2 +26.86 0.3491 0.3506 0.3616 2 2 2 +30 0.4073 0.4054 0.4156 2 2 2 +35 0.4501 0.448 0.4572 2 2 2 +40 0.4549 0.4566 0.4645 2 2 2 +40.81 0.4538 0.4559 0.4636 2 2 2 +45 0.4433 0.446 0.4525 2 2 2 +50 0.4245 0.4247 0.4302 2 2 2 +55 0.4003 0.3983 0.403 2 2 2 +60 0.372 0.3701 0.3744 2 2 2 +65 0.3425 0.3424 0.3462 2 2 2 +70 0.3148 0.3163 0.3195 2 2 2 +75 0.2904 0.2922 0.2949 2 2 2 +80 0.2694 0.2702 0.2726 2 2 2 +85 0.2509 0.2502 0.2523 2 2 2 +90 0.2337 0.2321 0.2341 2 2 2 +95 0.2174 0.2159 0.2177 2 2 2 +100 0.2019 0.2012 0.203 2 2 2 +105 0.1877 0.188 0.1896 2 2 2 +110 0.1751 0.1761 0.1775 2 2 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0.001435 0.00149 0.001493 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/015_P_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/015_P_M23(3p).txt new file mode 100644 index 0000000..66b7292 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/015_P_M23(3p).txt @@ -0,0 +1,108 @@ +10.2 40.9 40.88 40.73 1.204 1.204 1.202 +15 9.498 9.499 9.444 1.791 1.791 1.785 +16.7 5.256 5.256 5.216 1.865 1.865 1.861 +20 1.763 1.762 1.74 1.752 1.751 1.753 +21.2 1.232 1.232 1.214 1.584 1.583 1.587 +25 0.5235 0.5236 0.5134 0.576 0.574 0.573 +26.8 0.4252 0.4256 0.4176 0.09121 0.08962 0.08483 +30 0.3846 0.3851 0.3799 -0.2529 -0.2532 -0.2552 +35 0.4342 0.435 0.4322 0.03874 0.03902 0.04382 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/016_S_M1(3s).txt new file mode 100644 index 0000000..90b5361 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/016_S_M1(3s).txt @@ -0,0 +1,105 @@ +25 0.1921 0.1922 0.2038 2 2 2 +26.86 0.2482 0.2502 0.2622 2 2 2 +30 0.3253 0.3285 0.3402 2 2 2 +35 0.4072 0.4068 0.4173 2 2 2 +40 0.4463 0.4432 0.4526 2 2 2 +40.81 0.4493 0.4463 0.4556 2 2 2 +45 0.4545 0.453 0.4616 2 2 2 +50 0.4453 0.4467 0.4542 2 2 2 +55 0.4284 0.4308 0.4371 2 2 2 +60 0.4084 0.4095 0.4149 2 2 2 +65 0.3865 0.3857 0.3904 2 2 2 +70 0.3631 0.3611 0.3654 2 2 2 +75 0.3389 0.3372 0.3411 2 2 2 +80 0.315 0.3146 0.3181 2 2 2 +85 0.2927 0.2936 0.2967 2 2 2 +90 0.2726 0.2743 0.277 2 2 2 +95 0.2551 0.2566 0.259 2 2 2 +100 0.2397 0.2404 0.2426 2 2 2 +105 0.226 0.2257 0.2276 2 2 2 +110 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--git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/017_Cl_L23(2p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/017_Cl_L23(2p).txt new file mode 100644 index 0000000..322366d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/017_Cl_L23(2p).txt @@ -0,0 +1,92 @@ +210 1.185 1.187 1.186 0.4035 0.405 0.4084 +215 4.957 4.96 4.962 0.5511 0.552 0.5546 +220 4.765 4.765 4.766 0.5627 0.5633 0.5658 +225 4.051 4.049 4.05 0.6211 0.6215 0.6236 +230 3.675 3.673 3.673 0.6936 0.6938 0.6955 +235 3.48 3.478 3.478 0.7661 0.7661 0.7674 +240 3.366 3.364 3.364 0.8338 0.8337 0.8347 +245 3.284 3.282 3.283 0.8954 0.8953 0.896 +250 3.209 3.208 3.209 0.9509 0.9508 0.9512 +255 3.132 3.132 3.133 1.001 1.001 1.001 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1.159 +1500 0.0019 0.001892 0.001891 1.155 1.155 1.155 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/018_Ar_L1(2s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/018_Ar_L1(2s).txt new file mode 100644 index 0000000..451c16b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/018_Ar_L1(2s).txt @@ -0,0 +1,87 @@ +315 0.2871 0.2866 0.2881 2 2 2 +320 0.2957 0.2952 0.2967 2 2 2 +325 0.3011 0.3005 0.302 2 2 2 +330 0.3043 0.3037 0.3052 2 2 2 +335 0.3057 0.3051 0.3066 2 2 2 +340 0.3054 0.3049 0.3064 2 2 2 +345 0.3037 0.3032 0.3047 2 2 2 +350 0.3008 0.3004 0.3019 2 2 2 +355 0.2971 0.2967 0.2982 2 2 2 +360 0.2926 0.2924 0.2938 2 2 2 +365 0.2878 0.2876 0.289 2 2 2 +370 0.2827 0.2826 0.284 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/018_Ar_M1(3s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/018_Ar_M1(3s).txt new file mode 100644 index 0000000..c446ad1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/018_Ar_M1(3s).txt @@ -0,0 +1,104 @@ +30 0.1293 0.1283 0.1386 2 2 2 +35 0.243 0.2433 0.2553 2 2 2 +40 0.3248 0.3263 0.3379 2 2 2 +40.81 0.3353 0.3366 0.3482 2 2 2 +45 0.3785 0.3787 0.3895 2 2 2 +50 0.4092 0.4079 0.4178 2 2 2 +55 0.422 0.4204 0.4294 2 2 2 +60 0.422 0.4212 0.4295 2 2 2 +65 0.4139 0.4143 0.4217 2 2 2 +70 0.4012 0.4022 0.4088 2 2 2 +75 0.3861 0.387 0.3929 2 2 2 +80 0.3698 0.3701 0.3753 2 2 2 +85 0.3528 0.3523 0.3571 2 2 2 +90 0.3354 0.3346 0.3389 2 2 2 +95 0.3182 0.3173 0.3213 2 2 2 +100 0.3013 0.3007 0.3044 2 2 2 +105 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2 +1500 0.00304 0.003034 0.003042 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/018_Ar_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/018_Ar_M23(3p).txt new file mode 100644 index 0000000..505427a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/018_Ar_M23(3p).txt @@ -0,0 +1,107 @@ +15 16.72 16.7 16.53 1.948 1.948 1.941 +20 50.13 50.2 50.02 1.42 1.42 1.415 +21.22 38.01 38.02 37.86 1.542 1.542 1.535 +25 13.52 13.49 13.4 1.784 1.783 1.776 +26.86 8.091 8.077 8.009 1.829 1.829 1.824 +30 3.589 3.598 3.552 1.755 1.755 1.756 +35 1.266 1.273 1.245 1.05 1.051 1.055 +40 0.7567 0.7576 0.7402 0.03177 0.02726 0.02178 +40.81 0.734 0.7344 0.7182 -0.06933 -0.07364 -0.07921 +45 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/020_Ca_L1(2s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/020_Ca_L1(2s).txt new file mode 100644 index 0000000..fea7c4a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/020_Ca_L1(2s).txt @@ -0,0 +1,80 @@ +435 0.2569 0.2565 0.2578 2 2 2 +440 0.2504 0.25 0.2513 2 2 2 +445 0.2474 0.2469 0.2482 2 2 2 +450 0.246 0.2456 0.2468 2 2 2 +455 0.2449 0.2445 0.2458 2 2 2 +460 0.2434 0.2431 0.2443 2 2 2 +465 0.2412 0.2409 0.2421 2 2 2 +470 0.2383 0.238 0.2392 2 2 2 +475 0.2349 0.2347 0.2359 2 2 2 +480 0.2314 0.2313 0.2324 2 2 2 +485 0.2279 0.2278 0.2289 2 2 2 +490 0.2245 0.2244 0.2256 2 2 2 +495 0.2213 0.2213 0.2224 2 2 2 +500 0.2183 0.2183 0.2194 2 2 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/020_Ca_N1(4s).txt @@ -0,0 +1,108 @@ +10.2 0.113 0.1127 0.1356 2 2 2 +15 0.201 0.2013 0.2184 2 2 2 +16.7 0.2059 0.2063 0.2212 2 2 2 +20 0.2024 0.2026 0.2139 2 2 2 +21.2 0.1989 0.199 0.2093 2 2 2 +25 0.1846 0.1848 0.1927 2 2 2 +26.8 0.1773 0.1776 0.1846 2 2 2 +30 0.1645 0.1649 0.1707 2 2 2 +35 0.1461 0.1462 0.1506 2 2 2 +40 0.1294 0.1296 0.133 2 2 2 +40.8 0.1269 0.1271 0.1304 2 2 2 +45 0.1147 0.1149 0.1177 2 2 2 +50 0.1021 0.1023 0.1045 2 2 2 +55 0.09131 0.09132 0.0932 2 2 2 +60 0.08197 0.08193 0.08352 2 2 2 +65 0.0739 0.07388 0.07525 2 2 2 +70 0.06701 0.06699 0.06816 2 2 2 +75 0.06113 0.06105 0.06208 2 2 2 +80 0.05605 0.05591 0.05682 2 2 2 +85 0.05155 0.05143 0.05225 2 2 2 +90 0.04756 0.04751 0.04825 2 2 2 +95 0.04406 0.04406 0.04473 2 2 2 +100 0.04104 0.041 0.0416 2 2 2 +105 0.03837 0.03827 0.03882 2 2 2 +110 0.03593 0.03582 0.03633 2 2 2 +115 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/022_Ti_M23(3p).txt @@ -0,0 +1,102 @@ +45 2.289 2.283 2.224 1.076 1.075 1.083 +50 1.426 1.427 1.385 1.311 1.312 1.32 +55 0.9663 0.9683 0.9378 0.3641 0.3656 0.3588 +60 0.8343 0.8358 0.8136 -0.349 -0.3495 -0.3613 +65 0.8538 0.855 0.8388 -0.4684 -0.4687 -0.4713 +70 0.9271 0.9277 0.9158 -0.2848 -0.2842 -0.2789 +75 1.012 1.011 1.003 -0.03334 -0.03265 -0.02412 +80 1.09 1.089 1.082 0.2029 0.2032 0.212 +85 1.156 1.154 1.15 0.4055 0.4053 0.4135 +90 1.206 1.205 1.202 0.5745 0.574 0.581 +95 1.241 1.241 1.239 0.7147 0.7142 0.7198 +100 1.262 1.263 1.262 0.8313 0.8309 0.8353 +105 1.27 1.272 1.272 0.9286 0.9284 0.9318 +110 1.268 1.271 1.271 1.01 1.01 1.013 +115 1.259 1.261 1.262 1.08 1.08 1.081 +120 1.243 1.245 1.246 1.139 1.139 1.14 +125 1.223 1.225 1.226 1.19 1.19 1.19 +130 1.201 1.201 1.202 1.234 1.234 1.233 +132.3 1.19 1.189 1.19 1.252 1.252 1.251 +135 1.175 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/023_V_L1(2s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/023_V_L1(2s).txt new file mode 100644 index 0000000..8387e5e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/023_V_L1(2s).txt @@ -0,0 +1,75 @@ +620 0.202 0.2018 0.2029 2 2 2 +625 0.1928 0.1926 0.1936 2 2 2 +630 0.188 0.1878 0.1888 2 2 2 +635 0.1857 0.1855 0.1865 2 2 2 +640 0.1846 0.1844 0.1854 2 2 2 +645 0.184 0.1838 0.1848 2 2 2 +650 0.1834 0.1832 0.1842 2 2 2 +655 0.1825 0.1824 0.1834 2 2 2 +660 0.1813 0.1812 0.1822 2 2 2 +665 0.1798 0.1797 0.1807 2 2 2 +670 0.1781 0.178 0.179 2 2 2 +675 0.1762 0.1761 0.1771 2 2 2 +680 0.1742 0.1742 0.1751 2 2 2 +685 0.1723 0.1722 0.1731 2 2 2 +690 0.1703 0.1703 0.1712 2 2 2 +695 0.1685 0.1685 0.1694 2 2 2 +700 0.1668 0.1668 0.1677 2 2 2 +705 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/023_V_L23(2p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/023_V_L23(2p).txt new file mode 100644 index 0000000..bbd743a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/023_V_L23(2p).txt @@ -0,0 +1,77 @@ +530 1.477 1.476 1.476 0.4831 0.484 0.4876 +535 1.686 1.685 1.686 0.5418 0.5425 0.5456 +540 1.764 1.763 1.763 0.6153 0.6158 0.6185 +545 1.753 1.752 1.752 0.6797 0.6801 0.6823 +550 1.713 1.711 1.712 0.7352 0.7355 0.7373 +555 1.67 1.669 1.669 0.7839 0.784 0.7856 +560 1.633 1.632 1.632 0.8274 0.8275 0.8288 +565 1.602 1.601 1.601 0.8671 0.8671 0.8681 +570 1.575 1.574 1.574 0.9036 0.9036 0.9044 +575 1.549 1.548 1.549 0.9374 0.9374 0.938 +580 1.523 1.522 1.523 0.9688 0.9688 0.9692 +585 1.496 1.495 1.496 0.998 0.998 0.9982 +590 1.468 1.467 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Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/023_V_M1(3s).txt new file mode 100644 index 0000000..d8a46c5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/023_V_M1(3s).txt @@ -0,0 +1,100 @@ +80 0.4294 0.4277 0.4406 2 2 2 +85 0.4163 0.4146 0.4261 2 2 2 +90 0.4073 0.4064 0.417 2 2 2 +95 0.4002 0.4004 0.4103 2 2 2 +100 0.3938 0.3948 0.404 2 2 2 +105 0.3871 0.3887 0.3973 2 2 2 +110 0.3798 0.3814 0.3894 2 2 2 +115 0.3716 0.373 0.3804 2 2 2 +120 0.3625 0.3634 0.3704 2 2 2 +125 0.3527 0.3531 0.3596 2 2 2 +130 0.3423 0.3422 0.3483 2 2 2 +132.3 0.3375 0.3371 0.343 2 2 2 +135 0.3318 0.3312 0.3369 2 2 2 +140 0.3211 0.3202 0.3256 2 2 2 +145 0.3106 0.3094 0.3145 2 2 2 +150 0.3003 0.2991 0.3039 2 2 2 +151.4 0.2974 0.2963 0.301 2 2 2 +155 0.2902 0.2892 0.2937 2 2 2 +160 0.2806 0.2797 0.284 2 2 2 +165 0.2713 0.2706 0.2748 2 2 2 +170 0.2623 0.262 0.266 2 2 2 +175 0.2538 0.2537 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/024_Cr_L1(2s).txt new file mode 100644 index 0000000..5421922 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/024_Cr_L1(2s).txt @@ -0,0 +1,74 @@ +680 0.1775 0.1773 0.1783 2 2 2 +685 0.1811 0.1808 0.1818 2 2 2 +690 0.18 0.1797 0.1807 2 2 2 +695 0.1775 0.1773 0.1783 2 2 2 +700 0.1749 0.1747 0.1756 2 2 2 +705 0.1726 0.1723 0.1733 2 2 2 +710 0.1706 0.1704 0.1714 2 2 2 +715 0.169 0.1688 0.1698 2 2 2 +720 0.1677 0.1675 0.1684 2 2 2 +725 0.1665 0.1663 0.1672 2 2 2 +730 0.1654 0.1652 0.1661 2 2 2 +735 0.1643 0.1641 0.1651 2 2 2 +740 0.1632 0.163 0.164 2 2 2 +745 0.162 0.1619 0.1628 2 2 2 +750 0.1608 0.1607 0.1615 2 2 2 +755 0.1594 0.1593 0.1602 2 2 2 +760 0.1581 0.158 0.1589 2 2 2 +765 0.1566 0.1566 0.1574 2 2 2 +770 0.1552 0.1551 0.156 2 2 2 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/024_Cr_L23(2p).txt new file mode 100644 index 0000000..09010a3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/024_Cr_L23(2p).txt @@ -0,0 +1,76 @@ +585 2.481 2.481 2.482 0.6075 0.608 0.6108 +590 1.619 1.619 1.62 0.5312 0.5317 0.5351 +595 1.612 1.612 1.612 0.5723 0.5727 0.5758 +600 1.645 1.644 1.645 0.6303 0.6306 0.6333 +605 1.65 1.65 1.65 0.6864 0.6867 0.689 +610 1.631 1.63 1.631 0.7376 0.7377 0.7397 +615 1.596 1.596 1.596 0.7835 0.7836 0.7852 +620 1.556 1.556 1.556 0.8248 0.8249 0.8262 +625 1.516 1.516 1.516 0.8621 0.8622 0.8632 +630 1.478 1.478 1.478 0.896 0.896 0.8969 +635 1.444 1.443 1.444 0.927 0.927 0.9277 +640 1.413 1.412 1.413 0.9556 0.9556 0.956 +645 1.385 1.384 1.385 0.982 0.982 0.9823 +650 1.359 1.358 1.359 1.007 1.007 1.007 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/024_Cr_M23(3p).txt @@ -0,0 +1,101 @@ +55 1.944 1.942 1.887 1.792 1.792 1.802 +60 1.191 1.193 1.153 1.34 1.342 1.35 +65 0.8232 0.8253 0.7949 0.5387 0.54 0.5349 +70 0.6836 0.685 0.6623 -0.1675 -0.1682 -0.1827 +75 0.6671 0.6683 0.6511 -0.4458 -0.4467 -0.4547 +80 0.7094 0.7102 0.6973 -0.379 -0.3787 -0.3765 +85 0.7731 0.7734 0.7635 -0.1742 -0.1733 -0.1651 +90 0.8398 0.8392 0.8317 0.0506 0.05135 0.06171 +95 0.9003 0.8991 0.8934 0.2537 0.2539 0.2643 +100 0.9513 0.9498 0.9456 0.4264 0.4262 0.4357 +105 0.9921 0.9907 0.9877 0.571 0.5705 0.5787 +110 1.023 1.022 1.02 0.6921 0.6915 0.6985 +115 1.046 1.046 1.044 0.7943 0.7938 0.7995 +120 1.06 1.061 1.061 0.8814 0.8811 0.8856 +125 1.069 1.071 1.07 0.9564 0.9562 0.9597 +130 1.072 1.074 1.074 1.021 1.021 1.024 +132.3 1.071 1.074 1.074 1.049 1.049 1.051 +135 1.07 1.072 1.072 1.078 1.078 1.08 +140 1.064 1.066 1.066 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/025_Mn_L1(2s).txt new file mode 100644 index 0000000..12014be --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/025_Mn_L1(2s).txt @@ -0,0 +1,71 @@ +760 0.1715 0.1714 0.1724 2 2 2 +765 0.1639 0.1638 0.1648 2 2 2 +770 0.1597 0.1596 0.1605 2 2 2 +775 0.1574 0.1573 0.1582 2 2 2 +780 0.1563 0.1562 0.1571 2 2 2 +785 0.1558 0.1556 0.1565 2 2 2 +790 0.1554 0.1553 0.1561 2 2 2 +795 0.1549 0.1549 0.1557 2 2 2 +800 0.1544 0.1543 0.1551 2 2 2 +805 0.1536 0.1535 0.1544 2 2 2 +810 0.1526 0.1525 0.1533 2 2 2 +815 0.1514 0.1513 0.1522 2 2 2 +820 0.1501 0.15 0.1509 2 2 2 +825 0.1487 0.1487 0.1495 2 2 2 +830 0.1473 0.1473 0.1481 2 2 2 +835 0.1459 0.1459 0.1467 2 2 2 +840 0.1445 0.1445 0.1453 2 2 2 +845 0.1432 0.1432 0.144 2 2 2 +850 0.142 0.142 0.1428 2 2 2 +855 0.1408 0.1408 0.1416 2 2 2 +860 0.1396 0.1396 0.1404 2 2 2 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/025_Mn_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/025_Mn_N1(4s).txt new file mode 100644 index 0000000..7140ba4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/025_Mn_N1(4s).txt @@ -0,0 +1,108 @@ +10.2 0.02006 0.01986 0.004612 2 2 2 +15 0.0751 0.07521 0.09918 2 2 2 +16.7 0.1066 0.1069 0.1307 2 2 2 +20 0.1436 0.1439 0.1647 2 2 2 +21.2 0.151 0.1513 0.1708 2 2 2 +25 0.162 0.1621 0.1779 2 2 2 +26.8 0.1628 0.163 0.1772 2 2 2 +30 0.1606 0.1608 0.1728 2 2 2 +35 0.1525 0.1526 0.162 2 2 2 +40 0.1424 0.1423 0.1499 2 2 2 +40.8 0.1407 0.1406 0.1479 2 2 2 +45 0.1317 0.1317 0.1379 2 2 2 +50 0.1214 0.1214 0.1265 2 2 2 +55 0.1116 0.1117 0.1161 2 2 2 +60 0.1027 0.1028 0.1065 2 2 2 +65 0.09453 0.09457 0.09775 2 2 2 +70 0.08706 0.08711 0.08986 2 2 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/026_Fe_M1(3s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/026_Fe_M1(3s).txt new file mode 100644 index 0000000..3922e3e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/026_Fe_M1(3s).txt @@ -0,0 +1,100 @@ +100 0.391 0.3912 0.4051 2 2 2 +105 0.3694 0.3685 0.3807 2 2 2 +110 0.3563 0.3552 0.3663 2 2 2 +115 0.3475 0.3467 0.357 2 2 2 +120 0.3411 0.3408 0.3504 2 2 2 +125 0.3358 0.3361 0.3452 2 2 2 +130 0.3311 0.3317 0.3404 2 2 2 +132.3 0.3289 0.3297 0.3381 2 2 2 +135 0.3263 0.3273 0.3354 2 2 2 +140 0.3213 0.3224 0.3301 2 2 2 +145 0.3158 0.3169 0.3242 2 2 2 +150 0.3099 0.3109 0.3178 2 2 2 +151.4 0.3082 0.3091 0.3159 2 2 2 +155 0.3037 0.3043 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--git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/026_Fe_M45(3d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/026_Fe_M45(3d).txt new file mode 100644 index 0000000..c8eb6fa --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/026_Fe_M45(3d).txt @@ -0,0 +1,108 @@ +15 3.236 3.24 3.163 0.6453 0.6441 0.6502 +16.71 3.576 3.571 3.511 0.2113 0.2097 0.215 +20 4.47 4.467 4.429 -0.1242 -0.1236 -0.1149 +21.22 4.833 4.833 4.801 -0.1604 -0.1586 -0.1492 +25 5.964 5.97 5.948 -0.1522 -0.1497 -0.1404 +26.86 6.497 6.497 6.477 -0.1177 -0.1168 -0.1081 +30 7.303 7.293 7.278 -0.04682 -0.04859 -0.04083 +35 8.241 8.231 8.221 0.06573 0.06361 0.07008 +40 8.714 8.72 8.713 0.1657 0.1664 0.1716 +40.81 8.751 8.758 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/027_Co_N1(4s).txt new file mode 100644 index 0000000..28fe697 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/027_Co_N1(4s).txt @@ -0,0 +1,108 @@ +10.2 0.1513 0.1514 0.08788 2 2 2 +15 0.02738 0.02735 0.04709 2 2 2 +16.7 0.05795 0.05801 0.08111 2 2 2 +20 0.1031 0.1034 0.1261 2 2 2 +21.2 0.114 0.1144 0.1362 2 2 2 +25 0.1346 0.135 0.1533 2 2 2 +26.8 0.1391 0.1395 0.1562 2 2 2 +30 0.1421 0.1425 0.1568 2 2 2 +35 0.1395 0.1399 0.1512 2 2 2 +40 0.1331 0.1334 0.1425 2 2 2 +40.8 0.1319 0.1322 0.141 2 2 2 +45 0.1252 0.1254 0.1329 2 2 2 +50 0.1169 0.1172 0.1234 2 2 2 +55 0.1088 0.1091 0.1143 2 2 2 +60 0.1011 0.1014 0.1058 2 2 2 +65 0.09395 0.09416 0.09799 2 2 2 +70 0.08728 0.08744 0.09077 2 2 2 +75 0.08111 0.08124 0.08416 2 2 2 +80 0.07545 0.07556 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/028_Ni_M1(3s).txt new file mode 100644 index 0000000..75d2f50 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/028_Ni_M1(3s).txt @@ -0,0 +1,98 @@ +120 0.3409 0.3408 0.3532 2 2 2 +125 0.3258 0.3254 0.3367 2 2 2 +130 0.316 0.3157 0.3261 2 2 2 +132.3 0.3125 0.3123 0.3224 2 2 2 +135 0.3092 0.3091 0.3188 2 2 2 +140 0.3042 0.3043 0.3135 2 2 2 +145 0.3002 0.3005 0.3092 2 2 2 +150 0.2966 0.297 0.3053 2 2 2 +151.4 0.2956 0.2961 0.3042 2 2 2 +155 0.2931 0.2936 0.3015 2 2 2 +160 0.2894 0.2899 0.2975 2 2 2 +165 0.2854 0.2859 0.2931 2 2 2 +170 0.2811 0.2815 0.2884 2 2 2 +175 0.2764 0.2767 0.2833 2 2 2 +180 0.2715 0.2716 0.2779 2 2 2 +185 0.2662 0.2663 0.2723 2 2 2 +190 0.2609 0.2608 0.2665 2 2 2 +195 0.2554 0.2551 0.2606 2 2 2 +200 0.2498 0.2495 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/029_Cu_M1(3s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/029_Cu_M1(3s).txt new file mode 100644 index 0000000..6ada0a8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/029_Cu_M1(3s).txt @@ -0,0 +1,98 @@ +125 0.2926 0.293 0.3048 2 2 2 +130 0.2944 0.2947 0.306 2 2 2 +132.3 0.2939 0.2943 0.3052 2 2 2 +135 0.2928 0.2931 0.3038 2 2 2 +140 0.2898 0.29 0.3001 2 2 2 +145 0.2861 0.2864 0.2959 2 2 2 +150 0.2822 0.2824 0.2915 2 2 2 +151.4 0.2812 0.2813 0.2902 2 2 2 +155 0.2783 0.2785 0.2871 2 2 2 +160 0.2744 0.2746 0.2827 2 2 2 +165 0.2706 0.2707 0.2784 2 2 2 +170 0.2667 0.2668 0.2742 2 2 2 +175 0.2628 0.2629 0.27 2 2 2 +180 0.2589 0.259 0.2658 2 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/029_Cu_M23(3p).txt new file mode 100644 index 0000000..1f39fa3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/029_Cu_M23(3p).txt @@ -0,0 +1,101 @@ +80 1.22 1.214 1.163 1.305 1.303 1.318 +85 0.9449 0.9421 0.9005 1.473 1.472 1.487 +90 0.7141 0.714 0.6801 1.117 1.119 1.127 +95 0.566 0.5671 0.5393 0.5593 0.5638 0.5577 +100 0.4876 0.489 0.4661 0.004737 0.009444 -0.008841 +105 0.459 0.4604 0.4416 -0.3681 -0.3655 -0.3848 +110 0.4627 0.4642 0.4486 -0.5064 -0.5058 -0.5165 +115 0.4853 0.487 0.4741 -0.4696 -0.4696 -0.4698 +120 0.5177 0.5195 0.5088 -0.3409 -0.3405 -0.3329 +125 0.5538 0.5557 0.5467 -0.1791 -0.178 -0.166 +130 0.5902 0.5919 0.5844 -0.01499 -0.01349 0.0005087 +132.3 0.6064 0.608 0.601 0.05713 0.05876 0.07306 +135 0.6249 0.6262 0.6198 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/029_Cu_M45(3d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/029_Cu_M45(3d).txt new file mode 100644 index 0000000..17ce7a6 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/029_Cu_M45(3d).txt @@ -0,0 +1,107 @@ +16.7 6.284 6.282 6.172 -0.1929 -0.1929 -0.1768 +20 7.038 7.036 6.961 -0.2483 -0.2484 -0.2308 +21.2 7.285 7.283 7.217 -0.2447 -0.2448 -0.2274 +25 7.987 7.985 7.939 -0.2003 -0.2002 -0.1843 +26.8 8.285 8.283 8.243 -0.1708 -0.1707 -0.1558 +30 8.765 8.764 8.733 -0.114 -0.1139 -0.1006 +35 9.398 9.397 9.375 -0.02401 -0.02394 -0.01306 +40 9.881 9.879 9.863 0.06113 0.06114 0.07003 +40.8 9.944 9.941 9.926 0.07413 0.07413 0.08275 +45 10.2 10.2 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/030_Zn_L1(2s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/030_Zn_L1(2s).txt new file mode 100644 index 0000000..fa49830 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/030_Zn_L1(2s).txt @@ -0,0 +1,63 @@ +1160 0.1258 0.1257 0.1265 2 2 2 +1165 0.1192 0.119 0.1198 2 2 2 +1170 0.1147 0.1145 0.1153 2 2 2 +1175 0.1118 0.1117 0.1124 2 2 2 +1180 0.1101 0.1099 0.1107 2 2 2 +1185 0.109 0.1089 0.1096 2 2 2 +1190 0.1084 0.1083 0.109 2 2 2 +1195 0.1081 0.108 0.1087 2 2 2 +1200 0.108 0.1078 0.1086 2 2 2 +1205 0.1078 0.1077 0.1084 2 2 2 +1210 0.1077 0.1076 0.1083 2 2 2 +1215 0.1075 0.1074 0.1081 2 2 2 +1220 0.1072 0.1071 0.1078 2 2 2 +1225 0.1068 0.1067 0.1074 2 2 2 +1230 0.1064 0.1063 0.107 2 2 2 +1235 0.1059 0.1058 0.1065 2 2 2 +1240 0.1053 0.1052 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/031_Ga_L1(2s).txt new file mode 100644 index 0000000..c17090a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/031_Ga_L1(2s).txt @@ -0,0 +1,49 @@ +1265 0.1089 0.1088 0.1095 2 2 2 +1270 0.1035 0.1034 0.1042 2 2 2 +1275 0.1017 0.1016 0.1023 2 2 2 +1280 0.1013 0.1012 0.1019 2 2 2 +1285 0.1015 0.1014 0.1021 2 2 2 +1290 0.1019 0.1018 0.1025 2 2 2 +1295 0.1021 0.102 0.1027 2 2 2 +1300 0.1021 0.102 0.1027 2 2 2 +1305 0.1019 0.1018 0.1025 2 2 2 +1310 0.1015 0.1014 0.1021 2 2 2 +1315 0.101 0.1009 0.1016 2 2 2 +1320 0.1004 0.1003 0.101 2 2 2 +1325 0.09971 0.09963 0.1003 2 2 2 +1330 0.09906 0.09899 0.09966 2 2 2 +1335 0.09844 0.09837 0.09904 2 2 2 +1340 0.09785 0.09778 0.09845 2 2 2 +1345 0.0973 0.09723 0.09789 2 2 2 +1350 0.09678 0.09672 0.09738 2 2 2 +1355 0.0963 0.09624 0.09689 2 2 2 +1360 0.09583 0.09578 0.09643 2 2 2 +1365 0.09539 0.09534 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Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/033_As_N1(4s).txt new file mode 100644 index 0000000..4e27df1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/033_As_N1(4s).txt @@ -0,0 +1,106 @@ +21.2 0.002413 0.002457 0.01487 2 2 2 +25 0.05392 0.05413 0.08397 2 2 2 +26.8 0.08345 0.08374 0.1164 2 2 2 +30 0.1298 0.1302 0.164 2 2 2 +35 0.18 0.1806 0.2121 2 2 2 +40 0.207 0.2075 0.2353 2 2 2 +40.8 0.2096 0.2102 0.2373 2 2 2 +45 0.2179 0.2183 0.2423 2 2 2 +50 0.2184 0.2187 0.2393 2 2 2 +55 0.2128 0.2129 0.2306 2 2 2 +60 0.2037 0.2037 0.219 2 2 2 +65 0.1929 0.1929 0.2062 2 2 2 +70 0.1816 0.1816 0.1932 2 2 2 +75 0.1705 0.1705 0.1807 2 2 2 +80 0.1599 0.1599 0.1689 2 2 2 +85 0.15 0.1501 0.158 2 2 2 +90 0.1409 0.1409 0.148 2 2 2 +95 0.1325 0.1325 0.1389 2 2 2 +100 0.1248 0.1247 0.1305 2 2 2 +105 0.1177 0.1176 0.1229 2 2 2 +110 0.1112 0.1111 0.1159 2 2 2 +115 0.1052 0.1051 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/034_Se_L23(2p).txt new file mode 100644 index 0000000..5e56684 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/034_Se_L23(2p).txt @@ -0,0 +1,13 @@ +1445 0.3833 0.3832 0.3832 0.5973 0.5976 0.6018 +1450 0.606 0.6057 0.606 0.5602 0.5606 0.5651 +1455 0.6198 0.6195 0.6197 0.564 0.5643 0.5688 +1460 0.5999 0.5996 0.5998 0.5906 0.5909 0.5951 +1465 0.5873 0.587 0.5872 0.6247 0.6249 0.6288 +1470 0.5832 0.5829 0.5831 0.6606 0.6608 0.6643 +1475 0.5842 0.5839 0.5841 0.6962 0.6964 0.6995 +1480 0.5874 0.5871 0.5873 0.7305 0.7306 0.7334 +1485 0.5907 0.5905 0.5907 0.7629 0.763 0.7655 +1486.6 0.5917 0.5914 0.5916 0.7728 0.7729 0.7753 +1490 0.5931 0.5928 0.5931 0.7932 0.7933 0.7955 +1495 0.5939 0.5937 0.5939 0.8214 0.8215 0.8234 +1500 0.5931 0.5928 0.5931 0.8475 0.8476 0.8493 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/034_Se_M1(3s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/034_Se_M1(3s).txt new file mode 100644 index 0000000..cf6dd87 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/034_Se_M1(3s).txt @@ -0,0 +1,92 @@ +220 0.229 0.2289 0.2364 2 2 2 +225 0.2333 0.233 0.2406 2 2 2 +230 0.2365 0.2362 0.2437 2 2 2 +235 0.2389 0.2386 0.246 2 2 2 +240 0.24 0.2397 0.247 2 2 2 +245 0.2395 0.2393 0.2465 2 2 2 +250 0.2377 0.2376 0.2445 2 2 2 +255 0.2348 0.2347 0.2415 2 2 2 +260 0.2312 0.2312 0.2377 2 2 2 +265 0.2271 0.2272 0.2335 2 2 2 +270 0.2229 0.2231 0.2292 2 2 2 +275 0.2188 0.219 0.2249 2 2 2 +280 0.2148 0.215 0.2207 2 2 2 +285 0.211 0.2113 0.2168 2 2 2 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/037_Rb_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/037_Rb_M23(3p).txt new file mode 100644 index 0000000..c1970b9 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/037_Rb_M23(3p).txt @@ -0,0 +1,46 @@ +240 0.892 0.8933 0.8898 -0.09437 -0.09213 -0.06734 +260 0.6842 0.6835 0.6799 -0.2577 -0.2579 -0.2329 +280 0.7105 0.7101 0.708 0.2275 0.2269 0.2447 +300 0.7089 0.7093 0.708 0.5397 0.5393 0.5515 +320 0.7036 0.7044 0.7037 0.7525 0.7524 0.7605 +340 0.6937 0.6945 0.6943 0.9125 0.9126 0.9175 +360 0.6769 0.6773 0.6775 1.035 1.035 1.038 +380 0.6562 0.656 0.6564 1.129 1.129 1.13 +400 0.6341 0.6336 0.6342 1.203 1.203 1.202 +420 0.6112 0.6104 0.6112 1.263 1.263 1.261 +440 0.5872 0.5864 0.5873 1.313 1.313 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/038_Sr_M45(3d).txt @@ -0,0 +1,96 @@ +150 0.4301 0.4296 0.4237 1.298 1.302 1.31 +151.4 0.4788 0.4787 0.4731 1.589 1.593 1.6 +155 0.7375 0.7386 0.7335 1.86 1.861 1.862 +160 1.424 1.427 1.422 1.276 1.276 1.275 +165 2.166 2.167 2.163 0.7445 0.7446 0.7455 +170 2.846 2.846 2.843 0.439 0.4388 0.4413 +175 3.437 3.436 3.433 0.2741 0.2736 0.2771 +180 3.905 3.903 3.901 0.1905 0.1898 0.1939 +185 4.249 4.248 4.245 0.1551 0.1543 0.1586 +190 4.502 4.501 4.499 0.1489 0.1481 0.1524 +195 4.698 4.697 4.696 0.1606 0.1599 0.1641 +200 4.856 4.856 4.855 0.1832 0.1827 0.1867 +205 4.985 4.986 4.985 0.2122 0.2119 0.2157 +210 5.084 5.086 5.085 0.2446 0.2446 0.2481 +215 5.152 5.154 5.154 0.2786 0.2787 0.282 +220 5.19 5.192 5.192 0.3129 0.3131 0.3162 +225 5.2 5.202 5.203 0.3468 0.3471 0.3499 +230 5.188 5.19 5.19 0.38 0.3804 0.3829 +235 5.158 5.16 5.16 0.4122 0.4127 0.415 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/039_Y_M1(3s).txt new file mode 100644 index 0000000..632f305 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/039_Y_M1(3s).txt @@ -0,0 +1,39 @@ +380 0.1872 0.187 0.1924 2 2 2 +400 0.181 0.1809 0.1859 2 2 2 +420 0.1725 0.1725 0.1771 2 2 2 +440 0.1634 0.1635 0.1677 2 2 2 +460 0.1558 0.156 0.1599 2 2 2 +480 0.1483 0.1485 0.1521 2 2 2 +500 0.1412 0.1413 0.1446 2 2 2 +520 0.1347 0.1348 0.1379 2 2 2 +540 0.1287 0.1287 0.1316 2 2 2 +560 0.1229 0.1229 0.1256 2 2 2 +580 0.1174 0.1173 0.1199 2 2 2 +600 0.1123 0.1122 0.1146 2 2 2 +620 0.1075 0.1074 0.1096 2 2 2 +640 0.1029 0.1029 0.105 2 2 2 +660 0.09861 0.09855 0.1005 2 2 2 +680 0.09452 0.09449 0.09637 2 2 2 +700 0.09068 0.09069 0.09246 2 2 2 +720 0.08707 0.08711 0.08879 2 2 2 +740 0.08366 0.08373 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/039_Y_N1(4s).txt new file mode 100644 index 0000000..7a065f1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/039_Y_N1(4s).txt @@ -0,0 +1,57 @@ +60 0.268 0.2678 0.3072 2 2 2 +80 0.2794 0.2797 0.3062 2 2 2 +100 0.2503 0.2493 0.2678 2 2 2 +120 0.2128 0.2133 0.2265 2 2 2 +132.3 0.1932 0.1938 0.2048 2 2 2 +140 0.1823 0.1826 0.1925 2 2 2 +151.4 0.1673 0.1672 0.1756 2 2 2 +160 0.1569 0.1565 0.1641 2 2 2 +180 0.1352 0.135 0.141 2 2 2 +200 0.1173 0.1176 0.1224 2 2 2 +220 0.103 0.1033 0.1073 2 2 2 +240 0.09141 0.09134 0.09467 2 2 2 +260 0.08164 0.0813 0.08413 2 2 2 +280 0.07308 0.07287 0.07532 2 2 2 +300 0.06561 0.06572 0.06785 2 2 2 +320 0.05929 0.0596 0.06145 2 2 2 +340 0.05404 0.0543 0.05591 2 2 2 +360 0.04962 0.04969 0.05111 2 2 2 +380 0.04574 0.04565 0.04692 2 2 2 +400 0.0422 0.0421 0.04324 2 2 2 +420 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/040_Zr_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/040_Zr_N1(4s).txt new file mode 100644 index 0000000..1fd78e0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/040_Zr_N1(4s).txt @@ -0,0 +1,57 @@ +60 0.2738 0.273 0.319 2 2 2 +80 0.2794 0.2804 0.31 2 2 2 +100 0.2624 0.2616 0.2826 2 2 2 +120 0.2276 0.2272 0.2424 2 2 2 +132.3 0.2072 0.2076 0.2203 2 2 2 +140 0.1957 0.1963 0.2078 2 2 2 +151.4 0.1804 0.1809 0.1907 2 2 2 +160 0.1699 0.1701 0.1789 2 2 2 +180 0.1481 0.1477 0.1547 2 2 2 +200 0.1294 0.1291 0.1347 2 2 2 +220 0.1136 0.1137 0.1184 2 2 2 +240 0.1006 0.101 0.1049 2 2 2 +260 0.09001 0.09012 0.09344 2 2 2 +280 0.0811 0.0809 0.08375 2 2 2 +300 0.07332 0.07303 0.07551 2 2 2 +320 0.06639 0.06627 0.06846 2 2 2 +340 0.06027 0.06043 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1.175 1.177 1.176 +1500 0.1094 0.1096 0.1096 1.173 1.175 1.174 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/041_Nb_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/041_Nb_N1(4s).txt new file mode 100644 index 0000000..f4df52d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/041_Nb_N1(4s).txt @@ -0,0 +1,100 @@ +70 .2721 .2719 .3119 2 2 2 +75 .2735 .2739 .3098 2 2 2 +80 .2726 .2733 .3058 2 2 2 +85 .2706 .2713 .3008 2 2 2 +90 .2678 .2682 .2952 2 2 2 +95 .2642 .2642 .2891 2 2 2 +100 .2598 .2594 .2824 2 2 2 +105 .2544 .2538 .275 2 2 2 +110 .2482 .2475 .2672 2 2 2 +115 .2413 .2406 .2589 2 2 2 +120 .2338 .2334 .2504 2 2 2 +125 .2261 .2259 .2417 2 2 2 +130 .2184 .2184 .2332 2 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/042_Mo_N1(4s).txt new file mode 100644 index 0000000..57fc4d0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/042_Mo_N1(4s).txt @@ -0,0 +1,56 @@ +80 0.2727 0.2727 0.3088 2 2 2 +100 0.2614 0.2618 0.2872 2 2 2 +120 0.2415 0.2407 0.2596 2 2 2 +132.3 0.2249 0.2243 0.2403 2 2 2 +140 0.214 0.2137 0.2282 2 2 2 +151.4 0.1982 0.1985 0.2111 2 2 2 +160 0.1872 0.1878 0.199 2 2 2 +180 0.1651 0.1655 0.1745 2 2 2 +200 0.1469 0.1467 0.154 2 2 2 +220 0.1309 0.1305 0.1366 2 2 2 +240 0.1167 0.1166 0.1217 2 2 2 +260 0.1045 0.1047 0.109 2 2 2 +280 0.09422 0.09449 0.09823 2 2 2 +300 0.08562 0.08572 0.08897 2 2 2 +320 0.07823 0.07811 0.08095 2 2 2 +340 0.07164 0.07143 0.07395 2 2 2 +360 0.06568 0.06555 0.0678 2 2 2 +380 0.06031 0.06037 0.06238 2 2 2 +400 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/043_Tc_M1(3s).txt new file mode 100644 index 0000000..76f3f13 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/043_Tc_M1(3s).txt @@ -0,0 +1,32 @@ +520 0.1594 0.1591 0.1637 2 2 2 +540 0.1467 0.1465 0.1506 2 2 2 +560 0.1433 0.1432 0.1471 2 2 2 +580 0.1372 0.1372 0.1409 2 2 2 +600 0.1314 0.1314 0.1349 2 2 2 +620 0.1264 0.1265 0.1298 2 2 2 +640 0.1216 0.1218 0.1249 2 2 2 +660 0.1169 0.1171 0.12 2 2 2 +680 0.1124 0.1126 0.1153 2 2 2 +700 0.1082 0.1084 0.1109 2 2 2 +720 0.1043 0.1044 0.1069 2 2 2 +740 0.1006 0.1007 0.103 2 2 2 +760 0.09706 0.09706 0.09927 2 2 2 +780 0.09365 0.09361 0.09571 2 2 2 +800 0.09041 0.09034 0.09234 2 2 2 +850 0.08299 0.08288 0.08466 2 2 2 +900 0.07634 0.07625 0.07784 2 2 2 +950 0.0704 0.07034 0.07177 2 2 2 +1000 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/044_Ru_M1(3s).txt new file mode 100644 index 0000000..e9e0ad4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/044_Ru_M1(3s).txt @@ -0,0 +1,30 @@ +560 0.1491 0.149 0.1533 2 2 2 +580 0.139 0.1389 0.1429 2 2 2 +600 0.1352 0.1352 0.139 2 2 2 +620 0.1311 0.1311 0.1347 2 2 2 +640 0.1259 0.126 0.1294 2 2 2 +660 0.1209 0.121 0.1242 2 2 2 +680 0.1164 0.1166 0.1195 2 2 2 +700 0.1124 0.1125 0.1153 2 2 2 +720 0.1085 0.1086 0.1113 2 2 2 +740 0.1046 0.1047 0.1073 2 2 2 +760 0.1009 0.101 0.1034 2 2 2 +780 0.09738 0.09741 0.0997 2 2 2 +800 0.09407 0.09407 0.09626 2 2 2 +850 0.08656 0.08651 0.08845 2 2 2 +900 0.07974 0.07967 0.08141 2 2 2 +950 0.07362 0.07356 0.07512 2 2 2 +1000 0.06819 0.06816 0.06957 2 2 2 +1041 0.06414 0.06414 0.06544 2 2 2 +1050 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/044_Ru_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/044_Ru_N1(4s).txt new file mode 100644 index 0000000..8119963 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/044_Ru_N1(4s).txt @@ -0,0 +1,56 @@ +80 0.2667 0.2665 0.3113 2 2 2 +100 0.2613 0.2618 0.2929 2 2 2 +120 0.2461 0.2464 0.2695 2 2 2 +132.3 0.2353 0.235 0.2547 2 2 2 +140 0.2274 0.2269 0.2449 2 2 2 +151.4 0.2145 0.214 0.2298 2 2 2 +160 0.2043 0.2041 0.2183 2 2 2 +180 0.1815 0.1819 0.1933 2 2 2 +200 0.162 0.1625 0.1718 2 2 2 +220 0.1459 0.146 0.1537 2 2 2 +240 0.1319 0.1316 0.1382 2 2 2 +260 0.1194 0.119 0.1246 2 2 2 +280 0.1081 0.1079 0.1128 2 2 2 +300 0.09812 0.09825 0.1025 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/045_Rh_N1(4s).txt new file mode 100644 index 0000000..4ab59af --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/045_Rh_N1(4s).txt @@ -0,0 +1,55 @@ +100 0.2619 0.2615 0.2958 2 2 2 +120 0.2455 0.2465 0.2718 2 2 2 +132.3 0.2362 0.2367 0.2583 2 2 2 +140 0.2298 0.2298 0.2495 2 2 2 +151.4 0.2192 0.2187 0.2359 2 2 2 +160 0.2104 0.2097 0.2254 2 2 2 +180 0.1889 0.1886 0.2014 2 2 2 +200 0.1689 0.1693 0.1797 2 2 2 +220 0.1519 0.1526 0.1612 2 2 2 +240 0.1378 0.1381 0.1453 2 2 2 +260 0.1256 0.1254 0.1316 2 2 2 +280 0.1146 0.1141 0.1195 2 2 2 +300 0.1045 0.1041 0.1088 2 2 2 +320 0.09544 0.09533 0.09948 2 2 2 +340 0.08742 0.08761 0.09128 2 2 2 +360 0.08047 0.08081 0.08407 2 2 2 +380 0.07446 0.07479 0.07769 2 2 2 +400 0.06923 0.06941 0.07201 2 2 2 +420 0.06458 0.06456 0.0669 2 2 2 +440 0.06034 0.06017 0.06231 2 2 2 +460 0.05641 0.05621 0.05816 2 2 2 +480 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/045_Rh_O1(5s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/045_Rh_O1(5s).txt new file mode 100644 index 0000000..404430a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/045_Rh_O1(5s).txt @@ -0,0 +1,108 @@ +10.2 0.01033 0.01038 0.005564 2 2 2 +15 0.01522 0.01518 0.04933 2 2 2 +16.7 0.02337 0.0233 0.05606 2 2 2 +20 0.03347 0.03347 0.06104 2 2 2 +21.2 0.03563 0.03567 0.06131 2 2 2 +25 0.0392 0.03936 0.05964 2 2 2 +26.8 0.03981 0.03997 0.05818 2 2 2 +30 0.03993 0.04006 0.05523 2 2 2 +35 0.0388 0.03885 0.05056 2 2 2 +40 0.03693 0.037 0.0463 2 2 2 +40.8 0.03661 0.03668 0.04567 2 2 2 +45 0.03488 0.03499 0.04256 2 2 2 +50 0.03288 0.033 0.03928 2 2 2 +55 0.03099 0.03109 0.03638 2 2 2 +60 0.0292 0.02927 0.03378 2 2 2 +65 0.02747 0.02754 0.03144 2 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/046_Pd_M1(3s).txt @@ -0,0 +1,27 @@ +620 0.1175 0.1172 0.1208 2 2 2 +640 0.1344 0.1342 0.1381 2 2 2 +660 0.1278 0.1276 0.1313 2 2 2 +680 0.1227 0.1226 0.1261 2 2 2 +700 0.1192 0.1192 0.1225 2 2 2 +720 0.116 0.116 0.1192 2 2 2 +740 0.1123 0.1124 0.1154 2 2 2 +760 0.1084 0.1086 0.1114 2 2 2 +780 0.1046 0.1048 0.1075 2 2 2 +800 0.101 0.1012 0.1038 2 2 2 +850 0.09328 0.09339 0.09569 2 2 2 +900 0.08637 0.08641 0.08846 2 2 2 +950 0.07996 0.07993 0.08177 2 2 2 +1000 0.07424 0.07415 0.07582 2 2 2 +1041 0.07003 0.06992 0.07146 2 2 2 +1050 0.06915 0.06904 0.07055 2 2 2 +1100 0.06449 0.06439 0.06577 2 2 2 +1150 0.06021 0.06014 0.0614 2 2 2 +1200 0.05631 0.05628 0.05744 2 2 2 +1250 0.05279 0.05279 0.05386 2 2 2 +1253.6 0.05255 0.05255 0.05361 2 2 2 +1300 0.0496 0.04962 0.0506 2 2 2 +1350 0.04668 0.04671 0.04762 2 2 2 +1400 0.044 0.04403 0.04487 2 2 2 +1450 0.04154 0.04157 0.04235 2 2 2 +1486.6 0.03988 0.0399 0.04064 2 2 2 +1500 0.0393 0.03931 0.04004 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/046_Pd_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/046_Pd_M23(3p).txt new file mode 100644 index 0000000..279b201 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/046_Pd_M23(3p).txt @@ -0,0 +1,31 @@ +540 0.5652 0.565 0.5641 -0.06345 -0.06291 -0.0352 +560 0.5976 0.5973 0.5972 0.2934 0.2934 0.3131 +580 0.585 0.5847 0.5849 0.5433 0.5432 0.5568 +600 0.5612 0.5611 0.5613 0.7126 0.7124 0.722 +620 0.5426 0.5426 0.5429 0.8379 0.8377 0.8443 +640 0.5279 0.5281 0.5285 0.9385 0.9384 0.9427 +660 0.5137 0.514 0.5145 1.023 1.023 1.025 +680 0.4987 0.499 0.4996 1.094 1.094 1.095 +700 0.4831 0.4835 0.4841 1.154 1.154 1.153 +720 0.4679 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/046_Pd_M45(3d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/046_Pd_M45(3d).txt new file mode 100644 index 0000000..175c425 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/046_Pd_M45(3d).txt @@ -0,0 +1,85 @@ +350 0.1223 0.1217 0.12 0.3619 0.363 0.3643 +355 0.1415 0.141 0.1392 1.046 1.051 1.057 +360 0.1766 0.1762 0.1745 1.637 1.642 1.648 +365 0.2553 0.2554 0.2537 1.915 1.917 1.919 +370 0.4187 0.4194 0.4179 1.8 1.799 1.798 +375 0.7221 0.7235 0.7224 1.488 1.487 1.484 +380 1.278 1.281 1.28 1.166 1.166 1.164 +385 1.995 1.997 1.997 0.8985 0.8984 0.898 +390 2.669 2.672 2.672 0.7069 0.7071 0.7078 +395 3.176 3.178 3.178 0.5752 0.5754 0.5769 +400 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/047_Ag_M23(3p).txt new file mode 100644 index 0000000..5b2d7ed --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/047_Ag_M23(3p).txt @@ -0,0 +1,29 @@ +580 0.5112 0.5107 0.5098 -0.1006 -0.09955 -0.07063 +600 0.5765 0.5757 0.5757 0.3042 0.3043 0.324 +620 0.5581 0.5574 0.5575 0.5416 0.5414 0.5553 +640 0.5393 0.5389 0.5391 0.7033 0.7031 0.713 +660 0.5254 0.5253 0.5256 0.8298 0.8296 0.8364 +680 0.5114 0.5114 0.5119 0.9336 0.9334 0.9377 +700 0.4959 0.4963 0.4968 1.019 1.019 1.021 +720 0.4805 0.4809 0.4815 1.088 1.088 1.089 +740 0.4659 0.4665 0.4671 1.146 1.146 1.145 +760 0.4525 0.4531 0.4537 1.195 1.195 1.193 +780 0.4396 0.4402 0.4409 1.237 1.237 1.234 +800 0.4271 0.4276 0.4282 1.274 1.274 1.271 +850 0.3964 0.3966 0.3973 1.349 1.349 1.344 +900 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/047_Ag_M45(3d).txt new file mode 100644 index 0000000..3a5a231 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/047_Ag_M45(3d).txt @@ -0,0 +1,83 @@ +385 0.1303 0.1299 0.128 0.3382 0.3389 0.34 +390 0.1404 0.14 0.1382 1.065 1.068 1.074 +395 0.1782 0.178 0.1763 1.746 1.749 1.754 +400 0.2797 0.2799 0.2784 1.99 1.99 1.99 +405 0.5112 0.5119 0.5107 1.802 1.801 1.797 +410 0.9906 0.9921 0.9912 1.443 1.443 1.439 +415 1.682 1.684 1.684 1.115 1.114 1.113 +420 2.391 2.393 2.393 0.8726 0.8726 0.8723 +425 2.969 2.97 2.971 0.7027 0.7027 0.7035 +430 3.392 3.393 3.394 0.5843 0.5843 0.5858 +435 3.689 3.689 3.69 0.5024 0.5024 0.5044 +440 3.886 3.886 3.886 0.4465 0.4464 0.4488 +445 4.002 4.001 4.002 0.4095 0.4093 0.4119 +450 4.054 4.052 4.054 0.3861 0.3859 0.3886 +455 4.056 4.054 4.056 0.3729 0.3726 0.3753 +460 4.024 4.022 4.023 0.3672 0.3668 0.3696 +465 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Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/047_Ag_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/047_Ag_N1(4s).txt new file mode 100644 index 0000000..f56a308 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/047_Ag_N1(4s).txt @@ -0,0 +1,55 @@ +100 0.2575 0.2573 0.2989 2 2 2 +120 0.2449 0.2453 0.2756 2 2 2 +132.3 0.2356 0.2362 0.2619 2 2 2 +140 0.2303 0.2307 0.2542 2 2 2 +151.4 0.2222 0.2223 0.243 2 2 2 +160 0.2157 0.2155 0.2344 2 2 2 +180 0.1985 0.1983 0.2137 2 2 2 +200 0.1804 0.1805 0.1932 2 2 2 +220 0.1635 0.1638 0.1745 2 2 2 +240 0.1488 0.1491 0.1581 2 2 2 +260 0.1361 0.1362 0.1439 2 2 2 +280 0.125 0.1248 0.1315 2 2 2 +300 0.1149 0.1146 0.1205 2 2 2 +320 0.1057 0.1055 0.1106 2 2 2 +340 0.09735 0.09732 0.1019 2 2 2 +360 0.08989 0.09001 0.09405 2 2 2 +380 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0.02102 0.02103 1.259 1.253 1.253 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/047_Ag_O1(5s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/047_Ag_O1(5s).txt new file mode 100644 index 0000000..d87c6d6 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/047_Ag_O1(5s).txt @@ -0,0 +1,108 @@ +10.2 0.02843 0.02846 0.001225 2 2 2 +15 0.009125 0.009122 0.04404 2 2 2 +16.7 0.01723 0.0172 0.05218 2 2 2 +20 0.02852 0.02851 0.05905 2 2 2 +21.2 0.03113 0.03116 0.05975 2 2 2 +25 0.03586 0.036 0.0589 2 2 2 +26.8 0.03686 0.037 0.05762 2 2 2 +30 0.03749 0.0376 0.05484 2 2 2 +35 0.03687 0.0369 0.05021 2 2 2 +40 0.03532 0.03535 0.04592 2 2 2 +40.8 0.03504 0.03507 0.04529 2 2 2 +45 0.03348 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100644 index 0000000..28b63ab --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/048_Cd_M1(3s).txt @@ -0,0 +1,22 @@ +720 0.1298 0.1294 0.1333 2 2 2 +740 0.1167 0.1164 0.1198 2 2 2 +760 0.1145 0.1143 0.1176 2 2 2 +780 0.1117 0.1116 0.1148 2 2 2 +800 0.108 0.108 0.111 2 2 2 +850 0.09972 0.09984 0.1025 2 2 2 +900 0.09247 0.09266 0.09508 2 2 2 +950 0.08577 0.08595 0.08812 2 2 2 +1000 0.07993 0.08004 0.08201 2 2 2 +1041 0.07553 0.07557 0.07738 2 2 2 +1050 0.0746 0.07463 0.0764 2 2 2 +1100 0.06975 0.06969 0.07131 2 2 2 +1150 0.06536 0.06525 0.06673 2 2 2 +1200 0.06133 0.06119 0.06255 2 2 2 +1250 0.05761 0.05747 0.05872 2 2 2 +1253.6 0.05736 0.05721 0.05846 2 2 2 +1300 0.0542 0.05407 0.05523 2 2 2 +1350 0.05106 0.05096 0.05204 2 2 2 +1400 0.04816 0.0481 0.0491 2 2 2 +1450 0.04548 0.04547 0.0464 2 2 2 +1486.6 0.04366 0.04367 0.04455 2 2 2 +1500 0.04302 0.04304 0.04391 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/048_Cd_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/048_Cd_M23(3p).txt new file mode 100644 index 0000000..7fb36fa --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/048_Cd_M23(3p).txt @@ -0,0 +1,27 @@ +620 0.4428 0.4425 0.4414 -0.1696 -0.1686 -0.1379 +640 0.545 0.5444 0.5444 0.2691 0.2692 0.2903 +660 0.5321 0.5315 0.5316 0.5112 0.511 0.526 +680 0.5212 0.5208 0.5211 0.6828 0.6826 0.6932 +700 0.5088 0.5087 0.5091 0.8175 0.8173 0.8245 +720 0.4937 0.4938 0.4942 0.9233 0.9232 0.9278 +740 0.4787 0.4789 0.4794 1.007 1.007 1.01 +760 0.465 0.4653 0.4659 1.075 1.075 1.076 +780 0.4522 0.4526 0.4532 1.133 1.133 1.133 +800 0.4396 0.44 0.4407 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/048_Cd_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/048_Cd_N1(4s).txt new file mode 100644 index 0000000..1e66494 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/048_Cd_N1(4s).txt @@ -0,0 +1,54 @@ +120 0.2511 0.2506 0.2841 2 2 2 +132.3 0.2402 0.2404 0.2687 2 2 2 +140 0.2357 0.2363 0.2622 2 2 2 +151.4 0.2289 0.2296 0.2525 2 2 2 +160 0.2229 0.2234 0.2443 2 2 2 +180 0.2061 0.206 0.2231 2 2 2 +200 0.1882 0.1878 0.2019 2 2 2 +220 0.1714 0.1713 0.1831 2 2 2 +240 0.1565 0.1567 0.1667 2 2 2 +260 0.1433 0.1436 0.1522 2 2 2 +280 0.1315 0.1318 0.1392 2 2 2 +300 0.1211 0.1211 0.1276 2 2 2 +320 0.1118 0.1116 0.1172 2 2 2 +340 0.1034 0.1031 0.1081 2 2 2 +360 0.09577 0.09549 0.1 2 2 2 +380 0.08885 0.08872 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/048_Cd_O1(5s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/048_Cd_O1(5s).txt new file mode 100644 index 0000000..b4bee16 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/048_Cd_O1(5s).txt @@ -0,0 +1,108 @@ +10.2 0.2828 0.284 0.02697 2 2 2 +15 0.003146 0.003125 0.0661 2 2 2 +16.7 0.01958 0.01953 0.09613 2 2 2 +20 0.05455 0.05456 0.1314 2 2 2 +21.2 0.06455 0.06463 0.1386 2 2 2 +25 0.08608 0.08648 0.149 2 2 2 +26.8 0.09212 0.09263 0.1499 2 2 2 +30 0.09853 0.09912 0.148 2 2 2 +35 0.1016 0.1021 0.1408 2 2 2 +40 0.1002 0.1006 0.1318 2 2 2 +40.8 0.09967 0.1002 0.1303 2 2 2 +45 0.09646 0.09699 0.1225 2 2 2 +50 0.09184 0.09238 0.1136 2 2 2 +55 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/049_In_M1(3s).txt @@ -0,0 +1,19 @@ +780 0.1122 0.112 0.1154 2 2 2 +800 0.1115 0.1113 0.1146 2 2 2 +850 0.1028 0.1028 0.1057 2 2 2 +900 0.09559 0.09569 0.09831 2 2 2 +950 0.08877 0.0889 0.09126 2 2 2 +1000 0.08277 0.08288 0.08501 2 2 2 +1041 0.07821 0.07828 0.08025 2 2 2 +1050 0.07727 0.07733 0.07926 2 2 2 +1100 0.07233 0.07233 0.07409 2 2 2 +1150 0.06781 0.06776 0.06937 2 2 2 +1200 0.06368 0.06359 0.06507 2 2 2 +1250 0.0599 0.05979 0.06115 2 2 2 +1253.6 0.05964 0.05952 0.06088 2 2 2 +1300 0.0564 0.05629 0.05755 2 2 2 +1350 0.05318 0.05308 0.05425 2 2 2 +1400 0.05021 0.05014 0.05122 2 2 2 +1450 0.04747 0.04742 0.04843 2 2 2 +1486.6 0.04559 0.04556 0.04652 2 2 2 +1500 0.04493 0.04491 0.04585 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/049_In_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/049_In_O23(5p).txt new file mode 100644 index 0000000..4a8107a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/049_In_O23(5p).txt @@ -0,0 +1,108 @@ +10 3.378 3.388 3.098 1.739 1.739 1.606 +10.2 3.199 3.209 2.932 1.75 1.751 1.619 +15 1.046 1.049 0.9396 1.888 1.888 1.807 +16.7 0.7527 0.7551 0.6709 1.891 1.891 1.831 +20 0.4277 0.4291 0.3756 1.848 1.848 1.828 +21.2 0.3556 0.3567 0.3105 1.819 1.819 1.811 +25 0.2105 0.2109 0.1806 1.689 1.688 1.714 +26.8 0.1688 0.169 0.1437 1.61 1.609 1.646 +30 0.1183 0.1183 0.09949 1.45 1.448 1.496 +35 0.0734 0.07338 0.06092 1.162 1.159 1.207 +40 0.04936 0.04936 0.04069 0.8572 0.8531 0.8838 +40.8 0.04663 0.04663 0.03842 0.8089 0.8047 0.8317 +45 0.03555 0.03553 0.02928 0.5657 0.5605 0.5671 +50 0.02714 0.02711 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/050_Sn_M1(3s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/050_Sn_M1(3s).txt new file mode 100644 index 0000000..fe06acf --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/050_Sn_M1(3s).txt @@ -0,0 +1,17 @@ +850 0.1071 0.107 0.1102 2 2 2 +900 0.09851 0.0985 0.1013 2 2 2 +950 0.09172 0.0918 0.09435 2 2 2 +1000 0.08555 0.08565 0.08796 2 2 2 +1041 0.08093 0.08103 0.08316 2 2 2 +1050 0.07993 0.08003 0.08212 2 2 2 +1100 0.07483 0.07489 0.07679 2 2 2 +1150 0.07027 0.07027 0.07201 2 2 2 +1200 0.06602 0.06597 0.06757 2 2 2 +1250 0.06216 0.06208 0.06355 2 2 2 +1253.6 0.0619 0.06181 0.06327 2 2 2 +1300 0.05861 0.05851 0.05987 2 2 2 +1350 0.05531 0.0552 0.05646 2 2 2 +1400 0.05227 0.05217 0.05334 2 2 2 +1450 0.04946 0.04938 0.05047 2 2 2 +1486.6 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/051_Sb_M1(3s).txt @@ -0,0 +1,16 @@ +900 0.1028 0.1027 0.1058 2 2 2 +950 0.09458 0.09458 0.09732 2 2 2 +1000 0.08837 0.08843 0.09091 2 2 2 +1041 0.08357 0.08364 0.08593 2 2 2 +1050 0.08262 0.08269 0.08495 2 2 2 +1100 0.07742 0.07747 0.07953 2 2 2 +1150 0.07265 0.07267 0.07455 2 2 2 +1200 0.06838 0.06837 0.07009 2 2 2 +1250 0.06438 0.06434 0.06592 2 2 2 +1253.6 0.06411 0.06406 0.06564 2 2 2 +1300 0.06075 0.06068 0.06214 2 2 2 +1350 0.0574 0.05732 0.05867 2 2 2 +1400 0.05428 0.05419 0.05545 2 2 2 +1450 0.05139 0.05131 0.05249 2 2 2 +1486.6 0.04942 0.04935 0.05047 2 2 2 +1500 0.04873 0.04866 0.04976 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/051_Sb_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/052_Te_M1(3s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/052_Te_M1(3s).txt new file mode 100644 index 0000000..f37a915 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/052_Te_M1(3s).txt @@ -0,0 +1,15 @@ +950 0.09812 0.09793 0.1009 2 2 2 +1000 0.09095 0.09088 0.09354 2 2 2 +1041 0.08657 0.0866 0.08907 2 2 2 +1050 0.08544 0.08548 0.08791 2 2 2 +1100 0.07988 0.07998 0.08219 2 2 2 +1150 0.07507 0.07519 0.07721 2 2 2 +1200 0.07054 0.07064 0.0725 2 2 2 +1250 0.06657 0.06663 0.06834 2 2 2 +1253.6 0.06629 0.06635 0.06805 2 2 2 +1300 0.06284 0.06285 0.06442 2 2 2 +1350 0.05942 0.05938 0.06084 2 2 2 +1400 0.0563 0.05622 0.05757 2 2 2 +1450 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_M1(3s).txt new file mode 100644 index 0000000..353a3f0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_M1(3s).txt @@ -0,0 +1,10 @@ +1150 0.08189 0.08184 0.0843 2 2 2 +1200 0.07776 0.07775 0.08003 2 2 2 +1250 0.0734 0.07342 0.07552 2 2 2 +1253.6 0.07311 0.07313 0.07523 2 2 2 +1300 0.06931 0.06934 0.07128 2 2 2 +1350 0.06562 0.06565 0.06745 2 2 2 +1400 0.06218 0.06219 0.06386 2 2 2 +1450 0.05902 0.05901 0.06056 2 2 2 +1486.6 0.05687 0.05684 0.05831 2 2 2 +1500 0.0561 0.05607 0.05752 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_M23(3p).txt new file mode 100644 index 0000000..7b6c1b1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_M23(3p).txt @@ -0,0 +1,14 @@ +1000 0.3846 0.3841 0.384 0.1409 0.141 0.1684 +1041 0.3812 0.3808 0.381 0.6684 0.6683 0.6806 +1050 0.378 0.3777 0.3779 0.7315 0.7313 0.7418 +1100 0.3605 0.3605 0.3608 0.9802 0.9802 0.9835 +1150 0.3415 0.3417 0.3421 1.125 1.125 1.124 +1200 0.3225 0.3227 0.3232 1.225 1.225 1.222 +1250 0.3049 0.3051 0.3056 1.298 1.298 1.292 +1253.6 0.3037 0.3039 0.3044 1.302 1.302 1.297 +1300 0.2882 0.2884 0.2888 1.353 1.353 1.346 +1350 0.2728 0.2728 0.2733 1.397 1.397 1.389 +1400 0.2584 0.2583 0.2588 1.432 1.431 1.423 +1450 0.245 0.2448 0.2452 1.46 1.46 1.451 +1486.6 0.2357 0.2354 0.2359 1.478 1.478 1.468 +1500 0.2324 0.2321 0.2326 1.484 1.484 1.474 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_M45(3d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_M45(3d).txt new file mode 100644 index 0000000..b9005c6 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_M45(3d).txt @@ -0,0 +1,72 @@ +755 5.774 5.776 5.78 0.9837 0.9835 0.9822 +760 3.324 3.325 3.326 0.9823 0.9821 0.9809 +765 3.431 3.432 3.433 0.8517 0.8516 0.8513 +770 3.44 3.44 3.442 0.7241 0.7241 0.7248 +775 3.253 3.253 3.255 0.6268 0.6269 0.6282 +780 3.053 3.053 3.054 0.556 0.5561 0.5579 +785 2.903 2.902 2.903 0.5056 0.5057 0.5078 +790 2.798 2.798 2.799 0.4702 0.4702 0.4726 +795 2.723 2.722 2.724 0.4458 0.4457 0.4483 +800 2.661 2.66 2.662 0.4295 0.4294 0.432 +805 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_N1(4s).txt new file mode 100644 index 0000000..3eed39e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_N1(4s).txt @@ -0,0 +1,47 @@ +220 0.2184 0.2181 0.2399 2 2 2 +240 0.2113 0.2113 0.2307 2 2 2 +260 0.1945 0.1948 0.2113 2 2 2 +280 0.1823 0.1827 0.1971 2 2 2 +300 0.1697 0.1699 0.1826 2 2 2 +320 0.1581 0.158 0.1692 2 2 2 +340 0.1478 0.1476 0.1575 2 2 2 +360 0.1383 0.1381 0.1469 2 2 2 +380 0.1294 0.1291 0.1371 2 2 2 +400 0.1211 0.1209 0.1281 2 2 2 +420 0.1136 0.1135 0.12 2 2 2 +440 0.1067 0.1067 0.1127 2 2 2 +460 0.1005 0.1005 0.1059 2 2 2 +480 0.09473 0.09479 0.09975 2 2 2 +500 0.08946 0.08951 0.09407 2 2 2 +520 0.08464 0.08466 0.08886 2 2 2 +540 0.08022 0.0802 0.08408 2 2 2 +560 0.07615 0.07608 0.07967 2 2 2 +580 0.07236 0.07226 0.0756 2 2 2 +600 0.06883 0.06871 0.07182 2 2 2 +620 0.06553 0.06541 0.06831 2 2 2 +640 0.06244 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Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_N23(4p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_N23(4p).txt new file mode 100644 index 0000000..3c7706f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/055_Cs_N23(4p).txt @@ -0,0 +1,49 @@ +180 0.5233 0.523 0.4858 -0.8716 -0.8716 -0.8707 +200 0.5092 0.5095 0.4851 -0.3402 -0.3406 -0.3038 +220 0.5006 0.5015 0.4837 0.07633 0.07654 0.1182 +240 0.4898 0.4906 0.4777 0.3704 0.371 0.4092 +260 0.4767 0.4769 0.4675 0.6001 0.6007 0.6327 +280 0.4605 0.4601 0.4532 0.7752 0.7756 0.8012 +300 0.443 0.4424 0.4372 0.9095 0.9096 0.9295 +320 0.4248 0.4242 0.4205 1.017 1.017 1.032 +340 0.406 0.4057 0.403 1.106 1.106 1.117 +360 0.3872 0.3872 0.3852 1.18 1.18 1.187 +380 0.369 0.3692 0.3678 1.241 1.241 1.245 +400 0.3518 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_M1(3s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_M1(3s).txt new file mode 100644 index 0000000..5c7c285 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_M1(3s).txt @@ -0,0 +1,9 @@ +1200 0.07916 0.07899 0.08139 2 2 2 +1250 0.07558 0.0755 0.07774 2 2 2 +1253.6 0.07531 0.07524 0.07747 2 2 2 +1300 0.07146 0.07146 0.07354 2 2 2 +1350 0.06764 0.0677 0.06962 2 2 2 +1400 0.06414 0.06423 0.06602 2 2 2 +1450 0.06086 0.06095 0.06261 2 2 2 +1486.6 0.05864 0.05872 0.0603 2 2 2 +1500 0.05785 0.05793 0.05948 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_M23(3p).txt new file mode 100644 index 0000000..2007156 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_M23(3p).txt @@ -0,0 +1,11 @@ +1100 0.3669 0.3666 0.3668 0.6387 0.6386 0.6519 +1150 0.3494 0.3493 0.3496 0.9319 0.9318 0.9366 +1200 0.3316 0.3317 0.3321 1.094 1.094 1.094 +1250 0.314 0.3142 0.3146 1.201 1.201 1.198 +1253.6 0.3128 0.313 0.3134 1.208 1.208 1.205 +1300 0.2974 0.2976 0.298 1.279 1.279 1.274 +1350 0.2818 0.2819 0.2823 1.337 1.337 1.33 +1400 0.2671 0.2671 0.2675 1.383 1.383 1.375 +1450 0.2535 0.2534 0.2538 1.42 1.419 1.411 +1486.6 0.244 0.2438 0.2443 1.442 1.442 1.433 +1500 0.2406 0.2404 0.2409 1.45 1.449 1.44 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_M45(3d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_M45(3d).txt new file mode 100644 index 0000000..38fc613 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_M45(3d).txt @@ -0,0 +1,71 @@ +810 0.1773 0.1772 0.1767 1.907 1.907 1.904 +815 1.447 1.447 1.447 1.233 1.233 1.23 +820 2.326 2.326 2.327 0.9382 0.9381 0.9372 +825 2.552 2.552 2.553 0.7572 0.7572 0.7576 +830 2.614 2.614 2.615 0.6406 0.6407 0.6419 +835 2.618 2.618 2.619 0.5614 0.5615 0.5633 +840 2.577 2.576 2.578 0.5064 0.5064 0.5085 +845 2.512 2.511 2.513 0.4682 0.4682 0.4706 +850 2.446 2.445 2.447 0.4424 0.4424 0.445 +855 2.39 2.389 2.391 0.4259 0.4258 0.4285 +860 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_N23(4p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_N23(4p).txt new file mode 100644 index 0000000..12272fc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/056_Ba_N23(4p).txt @@ -0,0 +1,48 @@ +200 0.5228 0.5219 0.4927 -0.8201 -0.8203 -0.7929 +220 0.5123 0.5123 0.4911 -0.2568 -0.2579 -0.2149 +240 0.5019 0.503 0.4878 0.1529 0.1526 0.1954 +260 0.4882 0.4897 0.4783 0.4325 0.4331 0.4703 +280 0.4736 0.4746 0.4661 0.644 0.6449 0.6754 +300 0.4572 0.4573 0.4509 0.8064 0.8072 0.8315 +320 0.4402 0.4395 0.4346 0.9323 0.9328 0.9515 +340 0.4225 0.4213 0.4177 1.035 1.035 1.049 +360 0.404 0.4029 0.4002 1.12 1.12 1.13 +380 0.3857 0.3849 0.383 1.189 1.189 1.195 +400 0.368 0.3676 0.3662 1.247 1.247 1.251 +420 0.3507 0.3509 0.3499 1.297 1.297 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/057_La_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/057_La_N1(4s).txt new file mode 100644 index 0000000..fc4d696 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/057_La_N1(4s).txt @@ -0,0 +1,45 @@ +260 0.2172 0.2168 0.2367 2 2 2 +280 0.1952 0.1951 0.2119 2 2 2 +300 0.183 0.1832 0.198 2 2 2 +320 0.1706 0.1709 0.184 2 2 2 +340 0.1601 0.1604 0.172 2 2 2 +360 0.15 0.1501 0.1605 2 2 2 +380 0.1409 0.1408 0.1502 2 2 2 +400 0.1326 0.1324 0.1408 2 2 2 +420 0.1248 0.1245 0.1321 2 2 2 +440 0.1175 0.1172 0.1241 2 2 2 +460 0.1109 0.1105 0.1169 2 2 2 +480 0.1046 0.1044 0.1103 2 2 2 +500 0.09886 0.09873 0.1041 2 2 2 +520 0.09352 0.09349 0.09845 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/057_La_P1(6s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/057_La_P1(6s).txt new file mode 100644 index 0000000..3493883 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/057_La_P1(6s).txt @@ -0,0 +1,108 @@ +10 0.03598 0.03622 0.3001 2 2 2 +10.2 0.04019 0.04047 0.3003 2 2 2 +15 0.1023 0.1031 0.2649 2 2 2 +16.7 0.1104 0.1112 0.2484 2 2 2 +20 0.1164 0.117 0.2195 2 2 2 +21.2 0.1165 0.1171 0.2101 2 2 2 +25 0.113 0.1138 0.1837 2 2 2 +26.8 0.1102 0.111 0.1728 2 2 2 +30 0.1044 0.1051 0.1553 2 2 2 +35 0.09423 0.09473 0.1321 2 2 2 +40 0.08431 0.0844 0.1131 2 2 2 +40.8 0.08278 0.08282 0.1104 2 2 2 +45 0.07506 0.07492 0.09745 2 2 2 +50 0.06678 0.06659 0.08468 2 2 2 +55 0.05969 0.05944 0.07425 2 2 2 +60 0.05357 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_M1(3s).txt @@ -0,0 +1,5 @@ +1350 0.07164 0.07157 0.07374 2 2 2 +1400 0.06806 0.06804 0.07006 2 2 2 +1450 0.06474 0.06476 0.06665 2 2 2 +1486.6 0.06238 0.06241 0.06421 2 2 2 +1500 0.06157 0.0616 0.06337 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_M23(3p).txt new file mode 100644 index 0000000..a2ab6b4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_M23(3p).txt @@ -0,0 +1,9 @@ +1200 0.3435 0.3429 0.343 0.5212 0.5211 0.5387 +1250 0.3298 0.3295 0.3297 0.8701 0.87 0.8768 +1253.6 0.3288 0.3285 0.3287 0.8867 0.8866 0.8928 +1300 0.3141 0.314 0.3143 1.05 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_N1(4s).txt new file mode 100644 index 0000000..e9a0b51 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_N1(4s).txt @@ -0,0 +1,44 @@ +280 0.1939 0.1937 0.2112 2 2 2 +300 0.1831 0.1833 0.1988 2 2 2 +320 0.1707 0.171 0.1847 2 2 2 +340 0.1605 0.1608 0.173 2 2 2 +360 0.1506 0.1508 0.1617 2 2 2 +380 0.1417 0.1417 0.1515 2 2 2 +400 0.1336 0.1335 0.1423 2 2 2 +420 0.1259 0.1257 0.1337 2 2 2 +440 0.1188 0.1185 0.1258 2 2 2 +460 0.1122 0.1119 0.1186 2 2 2 +480 0.1061 0.1059 0.112 2 2 2 +500 0.1004 0.1002 0.1059 2 2 2 +520 0.09507 0.09499 0.1002 2 2 2 +540 0.09018 0.09018 0.09502 2 2 2 +560 0.08566 0.08571 0.0902 2 2 2 +580 0.08147 0.08155 0.08572 2 2 2 +600 0.07759 0.07768 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_N23(4p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_N23(4p).txt new file mode 100644 index 0000000..14825b7 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_N23(4p).txt @@ -0,0 +1,47 @@ +220 0.5071 0.5069 0.4791 -0.8181 -0.8182 -0.7795 +240 0.4976 0.4978 0.4768 -0.262 -0.2625 -0.2141 +260 0.4887 0.4894 0.4739 0.1398 0.1398 0.1861 +280 0.4762 0.4771 0.4651 0.4168 0.4173 0.4572 +300 0.4628 0.4634 0.4541 0.6238 0.6244 0.6574 +320 0.4478 0.4478 0.4406 0.7849 0.7854 0.8118 +340 0.432 0.4315 0.4259 0.9102 0.9106 0.9312 +360 0.4158 0.4151 0.4107 1.012 1.012 1.028 +380 0.3991 0.3984 0.395 1.097 1.097 1.108 +400 0.3824 0.3818 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--git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_O23(5p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_O23(5p).txt new file mode 100644 index 0000000..3b0fa0b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/058_Ce_O23(5p).txt @@ -0,0 +1,104 @@ +25 13.98 13.97 12.09 1.713 1.713 1.685 +30 7.405 7.422 6.281 1.986 1.986 1.975 +35 4.178 4.173 3.426 1.805 1.804 1.846 +40 2.547 2.539 2.024 1.513 1.512 1.586 +40.81 2.368 2.361 1.874 1.46 1.459 1.535 +45 1.677 1.675 1.304 1.176 1.177 1.25 +50 1.184 1.187 0.9114 0.8398 0.8422 0.8899 +55 0.891 0.8945 0.6838 0.5368 0.5378 0.5499 +60 0.7079 0.71 0.5457 0.2869 0.2846 0.2664 +65 0.5889 0.5892 0.4586 0.0996 0.09559 0.06102 +70 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_M1(3s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_M1(3s).txt new file mode 100644 index 0000000..3eddbe5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_M1(3s).txt @@ -0,0 +1,4 @@ +1400 0.07027 0.0702 0.07235 2 2 2 +1450 0.06659 0.06656 0.06856 2 2 2 +1486.6 0.06419 0.06418 0.06609 2 2 2 +1500 0.06339 0.06339 0.06527 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_M23(3p).txt new file mode 100644 index 0000000..6041f14 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_M23(3p).txt @@ -0,0 +1,8 @@ +1250 0.3319 0.3315 0.3315 0.4429 0.4429 0.4634 +1253.6 0.3317 0.3313 0.3313 0.484 0.484 0.5032 +1300 0.3206 0.3204 0.3205 0.8315 0.8314 0.8395 +1350 0.3062 0.3061 0.3064 1.024 1.024 1.026 +1400 0.2919 0.292 0.2923 1.146 1.146 1.144 +1450 0.2779 0.2781 0.2784 1.232 1.232 1.228 +1486.6 0.2681 0.2683 0.2686 1.281 1.281 1.275 +1500 0.2646 0.2648 0.2651 1.296 1.296 1.29 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_M45(3d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_M45(3d).txt 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--git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_N45(4d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_N45(4d).txt new file mode 100644 index 0000000..2a432c8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_N45(4d).txt @@ -0,0 +1,98 @@ +125 1.055 1.051 1.014 -0.8006 -0.8001 -0.809 +130 1.807 1.8 1.76 -0.7724 -0.7731 -0.7648 +132.3 1.998 1.992 1.951 -0.4392 -0.4401 -0.4312 +135 2.003 1.998 1.957 -0.03182 -0.03254 -0.02543 +140 1.702 1.7 1.663 0.5765 0.5761 0.5802 +145 1.355 1.356 1.322 1.001 1.001 1.004 +150 1.062 1.064 1.034 1.272 1.272 1.276 +151.4 0.9915 0.9939 0.9649 1.321 1.321 1.325 +155 0.8333 0.8358 0.8095 1.388 1.388 1.393 +160 0.6659 0.6681 0.6451 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1.332 1.331 1.328 +1486.6 0.1028 0.1027 0.1029 1.331 1.33 1.327 +1500 0.1005 0.1005 0.1007 1.33 1.329 1.327 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_N67(4f).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_N67(4f).txt new file mode 100644 index 0000000..9e1502e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_N67(4f).txt @@ -0,0 +1,107 @@ +16.7 .3719 .3698 .3477 1.976 1.976 1.983 +20 .5821 .5789 .5634 1.773 1.772 1.75 +21.2 .6794 .6776 .664 1.658 1.656 1.632 +25 1.045 1.049 1.039 1.315 1.314 1.297 +26.8 1.239 1.242 1.234 1.182 1.183 1.17 +30 1.587 1.588 1.581 .9951 .9962 .9889 +35 2.084 2.079 2.073 .795 .7952 .7936 +40 2.487 2.484 2.481 .6647 .6649 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_O23(5p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_O23(5p).txt new file mode 100644 index 0000000..5e5a3ce --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/059_Pr_O23(5p).txt @@ -0,0 +1,104 @@ +25 3.87 3.864 2.406 0.07644 0.07641 0.09444 +30 8.121 8.136 6.894 1.997 1.997 1.972 +35 4.572 4.568 3.755 1.858 1.857 1.888 +40 2.769 2.761 2.199 1.594 1.593 1.664 +40.81 2.571 2.563 2.032 1.544 1.543 1.618 +45 1.807 1.804 1.399 1.273 1.273 1.354 +50 1.263 1.265 0.9638 0.9417 0.9436 1.005 +55 0.9402 0.9433 0.713 0.6327 0.6339 0.6608 +60 0.7392 0.7413 0.5614 0.3685 0.3669 0.3595 +65 0.6089 0.6093 0.4662 0.1619 0.1582 0.1281 +70 0.5211 0.5202 0.4045 0.01715 0.01379 -0.02376 +75 0.4594 0.4579 0.363 -0.06875 -0.07031 -0.1027 +80 0.4142 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/060_Nd_M1(3s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/060_Nd_M1(3s).txt new file mode 100644 index 0000000..778d894 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/060_Nd_M1(3s).txt @@ -0,0 +1,3 @@ +1450 0.06863 0.06856 0.0707 2 2 2 +1486.6 0.06587 0.06582 0.06785 2 2 2 +1500 0.06514 0.06511 0.0671 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/060_Nd_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/060_Nd_M23(3p).txt new file mode 100644 index 0000000..2d68ced --- /dev/null +++ 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_M1(3s).txt new file mode 100644 index 0000000..fed8786 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_M1(3s).txt @@ -0,0 +1,4 @@ +1486.6 0.0687 0.06868 0.07087 2 2 2 +1490 0.06712 0.0671 0.06923 2 2 2 +1495 0.06601 0.06599 0.06809 2 2 2 +1500 0.06588 0.06586 0.06795 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_M23(3p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_M23(3p).txt new file mode 100644 index 0000000..c815c77 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_M23(3p).txt @@ -0,0 +1,5 @@ +1350 0.3197 0.3194 0.3194 0.2328 0.2329 0.2613 +1400 0.3047 0.3045 0.3046 0.7299 0.7299 0.7417 +1450 0.2921 0.292 0.2922 0.9585 0.9585 0.9627 +1486.6 0.2826 0.2826 0.2828 1.064 1.064 1.065 +1500 0.2794 0.2794 0.2796 1.096 1.096 1.096 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_M45(3d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_M45(3d).txt new file mode 100644 index 0000000..8f54fe7 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_M45(3d).txt @@ -0,0 +1,65 @@ +1060 0.2344 0.2343 0.2339 1.663 1.662 1.658 +1065 0.8934 0.8932 0.8934 1.249 1.248 1.245 +1070 1.452 1.452 1.452 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_N1(4s).txt new file mode 100644 index 0000000..0ebdd93 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_N1(4s).txt @@ -0,0 +1,43 @@ +300 0.1892 0.1886 0.207 2 2 2 +320 0.1784 0.178 0.1944 2 2 2 +340 0.1683 0.1682 0.1829 2 2 2 +360 0.1579 0.1581 0.1712 2 2 2 +380 0.1492 0.1496 0.1614 2 2 2 +400 0.1409 0.1412 0.1519 2 2 2 +420 0.1333 0.1335 0.1432 2 2 2 +440 0.1265 0.1265 0.1353 2 2 2 +460 0.12 0.1199 0.1279 2 2 2 +480 0.1139 0.1136 0.1211 2 2 2 +500 0.1083 0.1079 0.1147 2 2 2 +520 0.103 0.1026 0.1089 2 2 2 +540 0.09798 0.09761 0.1035 2 2 2 +560 0.09326 0.09295 0.0984 2 2 2 +580 0.08884 0.08861 0.09369 2 2 2 +600 0.08471 0.08457 0.08931 2 2 2 +620 0.08084 0.0808 0.08524 2 2 2 +640 0.07723 0.07727 0.08142 2 2 2 +660 0.07385 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_O1(5s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_O1(5s).txt new file mode 100644 index 0000000..9f0a2e9 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_O1(5s).txt @@ -0,0 +1,57 @@ +60 0.2391 0.2407 0.3384 2 2 2 +80 0.2294 0.2285 0.2898 2 2 2 +100 0.1929 0.1935 0.2337 2 2 2 +120 0.1629 0.1628 0.1909 2 2 2 +132.3 0.147 0.1464 0.1694 2 2 2 +140 0.1376 0.137 0.1576 2 2 2 +151.4 0.1248 0.1247 0.1422 2 2 2 +160 0.1162 0.1164 0.132 2 2 2 +180 0.0998 0.1002 0.1124 2 2 2 +200 0.08728 0.08711 0.09685 2 2 2 +220 0.07679 0.07636 0.08434 2 2 2 +240 0.06764 0.06755 0.07419 2 2 2 +260 0.06002 0.06028 0.06587 2 2 2 +280 0.05399 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_P1(6s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_P1(6s).txt new file mode 100644 index 0000000..0eb5862 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/061_Pm_P1(6s).txt @@ -0,0 +1,108 @@ +10 0.02344 0.02359 0.2952 2 2 2 +10.2 0.0267 0.02687 0.294 2 2 2 +15 0.07678 0.07727 0.2399 2 2 2 +16.7 0.0835 0.08398 0.2212 2 2 2 +20 0.08869 0.08902 0.1906 2 2 2 +21.2 0.08895 0.08928 0.1812 2 2 2 +25 0.08673 0.08722 0.156 2 2 2 +26.8 0.08479 0.08532 0.146 2 2 2 +30 0.08069 0.0812 0.1305 2 2 2 +35 0.07351 0.07391 0.1107 2 2 2 +40 0.06638 0.06654 0.09476 2 2 2 +40.8 0.06528 0.0654 0.09252 2 2 2 +45 0.05968 0.05965 0.08187 2 2 2 +50 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/062_Sm_M23(3p).txt @@ -0,0 +1,4 @@ +1400 0.3052 0.3048 0.3048 0.1222 0.1223 0.1552 +1450 0.2979 0.2977 0.2978 0.661 0.661 0.6754 +1486.6 0.2886 0.2884 0.2886 0.8628 0.8627 0.8702 +1500 0.2856 0.2855 0.2857 0.9174 0.9174 0.9231 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/062_Sm_M45(3d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/062_Sm_M45(3d).txt new file mode 100644 index 0000000..774c4f4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/062_Sm_M45(3d).txt @@ -0,0 +1,64 @@ +1110 0.06123 0.0611 0.06064 1.958 1.959 1.962 +1115 0.512 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/062_Sm_N1(4s).txt new file mode 100644 index 0000000..5e17200 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/062_Sm_N1(4s).txt @@ -0,0 +1,86 @@ +315 .1801 .1797 .1973 2 2 2 +320 .1768 .1765 .1935 2 2 2 +325 .1754 .1751 .1918 2 2 2 +330 .1743 .1741 .1904 2 2 2 +335 .1729 .1727 .1887 2 2 2 +340 .1708 .1707 .1863 2 2 2 +345 .1683 .1682 .1834 2 2 2 +350 .1655 .1655 .1802 2 2 2 +355 .1627 .1627 .1771 2 2 2 +360 .1601 .1602 .1741 2 2 2 +365 .1576 .1578 .1713 2 2 2 +370 .1554 .1556 .1687 2 2 2 +375 .1533 .1535 .1663 2 2 2 +380 .1512 .1515 .164 2 2 2 +385 .1492 .1495 .1617 2 2 2 +390 .1472 .1475 .1594 2 2 2 +395 .1452 .1455 .1571 2 2 2 +400 .1432 .1435 .1548 2 2 2 +405 .1412 .1415 .1525 2 2 2 +410 .1392 .1395 .1503 2 2 2 +415 .1373 .1375 .1481 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/062_Sm_N67(4f).txt new file mode 100644 index 0000000..20e64a1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/062_Sm_N67(4f).txt @@ -0,0 +1,107 @@ +16.71 0.5436 0.5479 0.4792 1.387 1.388 1.455 +20 0.6512 0.6494 0.6004 1.876 1.873 1.903 +21.22 0.7216 0.718 0.6745 1.9 1.9 1.913 +25 1.032 1.03 0.9989 1.716 1.715 1.7 +26.86 1.229 1.23 1.204 1.57 1.569 1.551 +30 1.611 1.616 1.595 1.33 1.329 1.314 +35 2.275 2.278 2.263 1.028 1.029 1.021 +40 2.914 2.91 2.899 0.8241 0.8243 0.8221 +40.81 3.012 3.007 2.996 0.798 0.7981 0.7967 +45 3.481 3.476 3.468 0.6858 0.6858 0.687 +50 3.971 3.972 3.966 0.5889 0.5894 0.5927 +55 4.384 4.39 4.385 0.5198 0.5206 0.5248 +60 4.71 4.714 4.71 0.4702 0.4704 0.4752 +65 4.941 4.94 4.937 0.4344 0.4336 0.4386 +70 5.082 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index 0000000..ae00ea3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/063_Eu_M23(3p).txt @@ -0,0 +1,9 @@ +1465 0.3018 0.3018 0.3019 0.1727 0.1729 0.2048 +1470 0.3004 0.3003 0.3004 0.241 0.2412 0.2707 +1475 0.2963 0.2963 0.2963 0.3059 0.3061 0.3333 +1480 0.2929 0.2929 0.2929 0.3656 0.3657 0.3908 +1485 0.2911 0.2911 0.2911 0.4213 0.4215 0.4446 +1486.6 0.2908 0.2908 0.2908 0.4385 0.4387 0.4612 +1490 0.2905 0.2904 0.2905 0.474 0.4742 0.4954 +1495 0.2904 0.2903 0.2904 0.5236 0.5237 0.5432 +1500 0.2902 0.2901 0.2902 0.5697 0.5698 0.5877 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/063_Eu_M45(3d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/063_Eu_M45(3d).txt new file mode 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/063_Eu_P1(6s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/063_Eu_P1(6s).txt new file mode 100644 index 0000000..7ad0cbe --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/063_Eu_P1(6s).txt @@ -0,0 +1,108 @@ +10 0.01489 0.0151 0.2995 2 2 2 +10.2 0.01781 0.01804 0.2983 2 2 2 +15 0.06859 0.0688 0.2425 2 2 2 +16.7 0.07623 0.07635 0.2231 2 2 2 +20 0.08288 0.08275 0.1916 2 2 2 +21.2 0.08359 0.08342 0.182 2 2 2 +25 0.0825 0.08244 0.1563 2 2 2 +26.8 0.08098 0.08097 0.1462 2 2 2 +30 0.07749 0.07753 0.1306 2 2 2 +35 0.07107 0.07111 0.1108 2 2 2 +40 0.06446 0.06442 0.09495 2 2 2 +40.8 0.06343 0.06336 0.09272 2 2 2 +45 0.05817 0.05802 0.0821 2 2 2 +50 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/064_Gd_M45(3d).txt @@ -0,0 +1,57 @@ +1230 0.1706 0.1705 0.1702 1.738 1.738 1.733 +1235 0.6312 0.631 0.6312 1.289 1.289 1.285 +1240 1.064 1.064 1.064 0.9847 0.9846 0.9832 +1245 1.282 1.282 1.282 0.8015 0.8015 0.8016 +1250 1.412 1.411 1.412 0.6837 0.6837 0.6847 +1253.6 1.478 1.477 1.478 0.6229 0.623 0.6245 +1255 1.498 1.497 1.498 0.6032 0.6033 0.605 +1260 1.547 1.546 1.547 0.5462 0.5464 0.5484 +1265 1.565 1.564 1.565 0.5052 0.5054 0.5078 +1270 1.565 1.564 1.565 0.4758 0.4759 0.4786 +1275 1.556 1.555 1.557 0.4551 0.4552 0.458 +1280 1.546 1.545 1.546 0.4409 0.441 0.4439 +1285 1.536 1.535 1.536 0.4318 0.4319 0.4348 +1290 1.527 1.527 1.528 0.4265 0.4266 0.4295 +1295 1.518 1.518 1.519 0.4242 0.4242 0.4272 +1300 1.509 1.508 1.509 0.4241 0.4241 0.427 +1305 1.498 1.497 1.498 0.4257 0.4257 0.4287 +1310 1.485 1.484 1.485 0.4288 0.4288 0.4317 +1315 1.472 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/064_Gd_N1(4s).txt new file mode 100644 index 0000000..748063e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/064_Gd_N1(4s).txt @@ -0,0 +1,41 @@ +340 0.1851 0.1849 0.2036 2 2 2 +360 0.1637 0.1636 0.1792 2 2 2 +380 0.1576 0.1576 0.1719 2 2 2 +400 0.1484 0.1485 0.1614 2 2 2 +420 0.1411 0.1412 0.153 2 2 2 +440 0.134 0.1341 0.1449 2 2 2 +460 0.1273 0.1273 0.1371 2 2 2 +480 0.1212 0.1212 0.1302 2 2 2 +500 0.1156 0.1154 0.1238 2 2 2 +520 0.1102 0.11 0.1177 2 2 2 +540 0.105 0.1048 0.112 2 2 2 +560 0.1003 0.1 0.1067 2 2 2 +580 0.09586 0.09561 0.1018 2 2 2 +600 0.09164 0.09142 0.09722 2 2 2 +620 0.08763 0.08746 0.09289 2 2 2 +640 0.08387 0.08376 0.08884 2 2 2 +660 0.08036 0.08029 0.08507 2 2 2 +680 0.07706 0.07704 0.08154 2 2 2 +700 0.07395 0.07397 0.0782 2 2 2 +720 0.07102 0.07107 0.07506 2 2 2 +740 0.06826 0.06832 0.07209 2 2 2 +760 0.06568 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/065_Tb_O1(5s).txt @@ -0,0 +1,57 @@ +60 0.2022 0.2035 0.3177 2 2 2 +80 0.2145 0.2145 0.2889 2 2 2 +100 0.1906 0.1896 0.2392 2 2 2 +120 0.162 0.163 0.1979 2 2 2 +132.3 0.1476 0.1484 0.1772 2 2 2 +140 0.1396 0.1399 0.1655 2 2 2 +151.4 0.1287 0.1282 0.15 2 2 2 +160 0.121 0.1201 0.1397 2 2 2 +180 0.1044 0.1041 0.1195 2 2 2 +200 0.09058 0.0911 0.1035 2 2 2 +220 0.07985 0.0804 0.09045 2 2 2 +240 0.07154 0.07143 0.07976 2 2 2 +260 0.06446 0.0639 0.07095 2 2 2 +280 0.05795 0.05755 0.0636 2 2 2 +300 0.05207 0.05215 0.05738 2 2 2 +320 0.04713 0.04751 0.05205 2 2 2 +340 0.04321 0.04349 0.04745 2 2 2 +360 0.04005 0.03997 0.04347 2 2 2 +380 0.03723 0.03688 0.04 2 2 2 +400 0.0345 0.03413 0.03695 2 2 2 +420 0.03184 0.0317 0.03424 2 2 2 +440 0.02939 0.02953 0.03183 2 2 2 +460 0.02729 0.0276 0.02967 2 2 2 +480 0.02558 0.02586 0.02774 2 2 2 +500 0.02419 0.02429 0.02601 2 2 2 +520 0.02297 0.02286 0.02443 2 2 2 +540 0.02178 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/066_Dy_N67(4f).txt new file mode 100644 index 0000000..8d740ba --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/066_Dy_N67(4f).txt @@ -0,0 +1,106 @@ +21.22 0.8948 0.8975 0.7863 1.535 1.531 1.6 +25 1.039 1.034 0.9539 1.805 1.804 1.832 +26.86 1.162 1.156 1.087 1.793 1.793 1.801 +30 1.436 1.433 1.379 1.654 1.653 1.643 +35 2.001 2.006 1.967 1.342 1.342 1.328 +40 2.643 2.647 2.617 1.072 1.073 1.064 +40.81 2.748 2.752 2.723 1.036 1.036 1.028 +45 3.287 3.284 3.26 0.8736 0.8739 0.8706 +50 3.894 3.887 3.868 0.7308 0.7307 0.7313 +55 4.453 4.449 4.433 0.6263 0.6265 0.6296 +60 4.957 4.959 4.946 0.5485 0.5492 0.5538 +65 5.396 5.402 5.392 0.49 0.4908 0.4963 +70 5.761 5.766 5.757 0.446 0.4463 0.4523 +75 6.048 6.048 6.039 0.413 0.4124 0.4187 +80 6.261 6.255 6.248 0.3881 0.3868 0.3932 +85 6.411 6.402 6.396 0.3692 0.3677 0.3742 +90 6.511 6.503 6.499 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/066_Dy_O1(5s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/066_Dy_O1(5s).txt new file mode 100644 index 0000000..b3a9dab --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/066_Dy_O1(5s).txt @@ -0,0 +1,57 @@ +60 0.1931 0.1938 0.3123 2 2 2 +80 0.2096 0.21 0.2879 2 2 2 +100 0.189 0.188 0.2402 2 2 2 +120 0.1616 0.1625 0.1993 2 2 2 +132.3 0.1475 0.1483 0.1787 2 2 2 +140 0.1397 0.1401 0.1671 2 2 2 +151.4 0.129 0.1286 0.1517 2 2 2 +160 0.1214 0.1207 0.1413 2 2 2 +180 0.1052 0.1048 0.121 2 2 2 +200 0.09144 0.09183 0.1049 2 2 2 +220 0.08061 0.08115 0.0918 2 2 2 +240 0.0722 0.07219 0.08102 2 2 2 +260 0.06513 0.06464 0.0721 2 2 2 +280 0.05868 0.05826 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/066_Dy_P1(6s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/066_Dy_P1(6s).txt new file mode 100644 index 0000000..04d0134 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/066_Dy_P1(6s).txt @@ -0,0 +1,108 @@ +10 0.005644 0.005738 0.3189 2 2 2 +10.2 0.007765 0.00788 0.3173 2 2 2 +15 0.05628 0.05657 0.253 2 2 2 +16.7 0.06491 0.06519 0.2315 2 2 2 +20 0.07337 0.07348 0.197 2 2 2 +21.2 0.07466 0.07473 0.1865 2 2 2 +25 0.07515 0.07531 0.159 2 2 2 +26.8 0.07423 0.07445 0.1484 2 2 2 +30 0.0717 0.07196 0.1321 2 2 2 +35 0.06653 0.06677 0.1118 2 2 2 +40 0.06091 0.06105 0.09573 2 2 2 +40.8 0.06002 0.06013 0.09347 2 2 2 +45 0.05544 0.0554 0.08279 2 2 2 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/067_Ho_O1(5s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/067_Ho_O1(5s).txt new file mode 100644 index 0000000..837d37c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/067_Ho_O1(5s).txt @@ -0,0 +1,57 @@ +60 0.1838 0.1842 0.307 2 2 2 +80 0.2046 0.2051 0.2866 2 2 2 +100 0.1871 0.1861 0.241 2 2 2 +120 0.1611 0.1618 0.2006 2 2 2 +132.3 0.1473 0.1481 0.1801 2 2 2 +140 0.1396 0.1401 0.1687 2 2 2 +151.4 0.1292 0.1289 0.1533 2 2 2 +160 0.1217 0.1211 0.1429 2 2 2 +180 0.1058 0.1053 0.1225 2 2 2 +200 0.09217 0.09248 0.1063 2 2 2 +220 0.08133 0.08184 0.0931 2 2 2 +240 0.07284 0.07288 0.08223 2 2 2 +260 0.06574 0.06532 0.07321 2 2 2 +280 0.05932 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/067_Ho_P1(6s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/067_Ho_P1(6s).txt new file mode 100644 index 0000000..f0e4c9c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/067_Ho_P1(6s).txt @@ -0,0 +1,108 @@ +10.2 0.00532 0.005378 0.3246 2 2 2 +15 0.05237 0.05268 0.2571 2 2 2 +16.7 0.06126 0.06159 0.2347 2 2 2 +20 0.07025 0.07046 0.1991 2 2 2 +21.2 0.07172 0.0719 0.1883 2 2 2 +25 0.0727 0.07296 0.1602 2 2 2 +26.8 0.07197 0.0723 0.1493 2 2 2 +30 0.06974 0.07012 0.1327 2 2 2 +35 0.06498 0.06532 0.1122 2 2 2 +40 0.05968 0.05991 0.09604 2 2 2 +40.8 0.05884 0.05903 0.09377 2 2 2 +45 0.05448 0.0545 0.08304 2 2 2 +50 0.04947 0.04943 0.07243 2 2 2 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/068_Er_M45(3d).txt @@ -0,0 +1,13 @@ +1445 0.1075 0.1075 0.1072 1.862 1.862 1.858 +1450 0.3674 0.3673 0.3673 1.43 1.43 1.425 +1455 0.7153 0.7153 0.7156 1.126 1.126 1.123 +1460 0.9656 0.9655 0.966 0.9242 0.9241 0.9232 +1465 1.119 1.119 1.119 0.7896 0.7896 0.7898 +1470 1.222 1.221 1.222 0.6947 0.6948 0.6958 +1475 1.291 1.29 1.291 0.6252 0.6253 0.6268 +1480 1.331 1.331 1.332 0.5729 0.5731 0.575 +1485 1.351 1.35 1.351 0.5333 0.5334 0.5357 +1486.6 1.353 1.353 1.354 0.5227 0.5229 0.5252 +1490 1.356 1.355 1.356 0.5032 0.5034 0.5058 +1495 1.354 1.353 1.354 0.4805 0.4807 0.4834 +1500 1.349 1.348 1.349 0.4637 0.4639 0.4667 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/068_Er_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/068_Er_N1(4s).txt new file mode 100644 index 0000000..b0f797d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/068_Er_N1(4s).txt @@ -0,0 +1,39 @@ +380 0.1609 0.1606 0.1787 2 2 2 +400 0.151 0.1508 0.167 2 2 2 +420 0.1458 0.1457 0.1606 2 2 2 +440 0.1381 0.1381 0.1516 2 2 2 +460 0.1318 0.1319 0.1443 2 2 2 +480 0.1259 0.126 0.1375 2 2 2 +500 0.1202 0.1203 0.1309 2 2 2 +520 0.115 0.115 0.1248 2 2 2 +540 0.1102 0.1102 0.1193 2 2 2 +560 0.1056 0.1055 0.114 2 2 2 +580 0.1012 0.1011 0.1089 2 2 2 +600 0.0971 0.0969 0.1043 2 2 2 +620 0.09324 0.09301 0.09991 2 2 2 +640 0.08956 0.08932 0.0958 2 2 2 +660 0.08605 0.08582 0.09191 2 2 2 +680 0.0827 0.0825 0.08824 2 2 2 +700 0.07954 0.07938 0.08479 2 2 2 +720 0.07655 0.07643 0.08154 2 2 2 +740 0.07372 0.07364 0.07848 2 2 2 +760 0.07102 0.07099 0.07557 2 2 2 +780 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/069_Tm_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/069_Tm_N1(4s).txt new file mode 100644 index 0000000..087573e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/069_Tm_N1(4s).txt @@ -0,0 +1,38 @@ +400 0.1504 0.1502 0.1671 2 2 2 +420 0.1463 0.1462 0.1619 2 2 2 +440 0.1397 0.1397 0.1541 2 2 2 +460 0.1328 0.1329 0.146 2 2 2 +480 0.1271 0.1272 0.1393 2 2 2 +500 0.1216 0.1216 0.1329 2 2 2 +520 0.1163 0.1163 0.1267 2 2 2 +540 0.1114 0.1114 0.1211 2 2 2 +560 0.1069 0.1069 0.1158 2 2 2 +580 0.1026 0.1025 0.1108 2 2 2 +600 0.09844 0.09828 0.1061 2 2 2 +620 0.09455 0.09436 0.1017 2 2 2 +640 0.09089 0.09069 0.09755 2 2 2 +660 0.0874 0.0872 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/070_Yb_N23(4p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/070_Yb_N23(4p).txt new file mode 100644 index 0000000..bf500dc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/070_Yb_N23(4p).txt @@ -0,0 +1,41 @@ +340 0.4063 0.4061 0.3839 -0.7937 -0.793 -0.7011 +360 0.3947 0.3945 0.3755 -0.369 -0.3692 -0.2854 +380 0.3894 0.3894 0.3739 -0.01876 -0.01913 0.05564 +400 0.3831 0.3833 0.3703 0.2478 0.2476 0.3119 +420 0.3756 0.376 0.365 0.4461 0.4462 0.5008 +440 0.3681 0.3685 0.3592 0.6048 0.6051 0.6509 +460 0.3599 0.3602 0.3524 0.7346 0.7349 0.7729 +480 0.3513 0.3515 0.3448 0.8405 0.8409 0.872 +500 0.3428 0.3426 0.337 0.929 0.9293 0.9545 +520 0.334 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/070_Yb_P1(6s).txt @@ -0,0 +1,108 @@ +10.2 0.0006286 0.0006296 0.3481 2 2 2 +15 0.04115 0.04146 0.27 2 2 2 +16.7 0.05071 0.05109 0.2451 2 2 2 +20 0.0612 0.06156 0.2059 2 2 2 +21.2 0.06319 0.06353 0.1942 2 2 2 +25 0.06563 0.06604 0.1639 2 2 2 +26.8 0.06547 0.06595 0.1523 2 2 2 +30 0.06411 0.06465 0.135 2 2 2 +35 0.06049 0.06098 0.1136 2 2 2 +40 0.0561 0.05648 0.09711 2 2 2 +40.8 0.05539 0.05573 0.09481 2 2 2 +45 0.05163 0.05179 0.08392 2 2 2 +50 0.04725 0.04726 0.07318 2 2 2 +55 0.04308 0.04308 0.06435 2 2 2 +60 0.03937 0.03931 0.05702 2 2 2 +65 0.03604 0.03595 0.0509 2 2 2 +70 0.03306 0.03299 0.04576 2 2 2 +75 0.03049 0.03039 0.0414 2 2 2 +80 0.02824 0.02809 0.03769 2 2 2 +85 0.02618 0.02606 0.0345 2 2 2 +90 0.02432 0.02426 0.03173 2 2 2 +95 0.02273 0.02266 0.02931 2 2 2 +100 0.02129 0.02122 0.02719 2 2 2 +105 0.01993 0.01994 0.02532 2 2 2 +110 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diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/071_Lu_N23(4p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/071_Lu_N23(4p).txt new file mode 100644 index 0000000..a5ca012 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/071_Lu_N23(4p).txt @@ -0,0 +1,40 @@ +360 0.4015 0.4014 0.3814 -0.7426 -0.742 -0.6435 +380 0.3901 0.3899 0.3725 -0.3215 -0.3216 -0.2353 +400 0.3843 0.3843 0.37 0.01582 0.01553 0.09111 +420 0.3775 0.3777 0.3656 0.2727 0.2726 0.3369 +440 0.3698 0.3701 0.3598 0.4632 0.4632 0.5177 +460 0.3623 0.3626 0.3539 0.6166 0.6169 0.6624 +480 0.3541 0.3543 0.3469 0.743 0.7433 0.781 +500 0.3455 0.3456 0.3392 0.8461 0.8465 0.8774 +520 0.337 0.3369 0.3315 0.9321 0.9324 0.9574 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/072_Hf_N67(4f).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/072_Hf_N67(4f).txt new file mode 100644 index 0000000..7324d85 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/072_Hf_N67(4f).txt @@ -0,0 +1,103 @@ +40 0.9992 1 0.9113 0.7288 0.7408 0.7643 +40.81 0.9905 0.9931 0.9066 0.8059 0.8176 0.8438 +45 0.9633 0.9696 0.8974 1.229 1.234 1.269 +50 1.018 1.023 0.9648 1.61 1.608 1.636 +55 1.189 1.188 1.142 1.677 1.676 1.687 +60 1.461 1.456 1.418 1.518 1.518 1.517 +65 1.798 1.793 1.762 1.288 1.288 1.284 +70 2.174 2.172 2.147 1.073 1.073 1.069 +75 2.576 2.578 2.557 0.8956 0.8954 0.8939 +80 2.997 3.003 2.985 0.7556 0.7557 0.7563 +85 3.431 3.438 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/072_Hf_O45(5d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/072_Hf_O45(5d).txt new file mode 100644 index 0000000..10c8c35 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/072_Hf_O45(5d).txt @@ -0,0 +1,109 @@ +10 10.53 10.55 10.09 0.1564 0.159 0.2954 +10.2 10.75 10.77 10.32 0.148 0.1506 0.2867 +15 13.61 13.6 13.32 0.2256 0.2237 0.3134 +16.71 13.44 13.45 13.21 0.2843 0.2847 0.3582 +20 11.86 11.86 11.67 0.4024 0.404 0.4526 +21.22 11.05 11.04 10.86 0.4461 0.4469 0.4882 +25 8.446 8.434 8.304 0.5742 0.5731 0.5967 +26.86 7.302 7.305 7.191 0.6324 0.6315 0.6485 +30 5.712 5.723 5.632 0.7256 0.7256 0.7334 +35 3.936 3.928 3.863 0.8654 0.8653 0.8624 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/072_Hf_P1(6s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/072_Hf_P1(6s).txt new file mode 100644 index 0000000..06dd59a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/072_Hf_P1(6s).txt @@ -0,0 +1,108 @@ +10.2 0.01508 0.01485 0.3505 2 2 2 +15 0.03011 0.03038 0.3223 2 2 2 +16.7 0.04592 0.04619 0.3014 2 2 2 +20 0.06687 0.06695 0.2635 2 2 2 +21.2 0.07176 0.07176 0.2513 2 2 2 +25 0.08066 0.08056 0.2178 2 2 2 +26.8 0.08242 0.08235 0.2044 2 2 2 +30 0.08319 0.08321 0.1836 2 2 2 +35 0.08084 0.08092 0.1571 2 2 2 +40 0.07634 0.07636 0.1357 2 2 2 +40.8 0.07552 0.07552 0.1327 2 2 2 +45 0.07097 0.07086 0.1181 2 2 2 +50 0.06533 0.06513 0.1034 2 2 2 +55 0.05973 0.05958 0.09102 2 2 2 +60 0.05452 0.05443 0.08063 2 2 2 +65 0.0498 0.04976 0.07186 2 2 2 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and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/073_Ta_O23(5p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/073_Ta_O23(5p).txt new file mode 100644 index 0000000..50311f8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/073_Ta_O23(5p).txt @@ -0,0 +1,102 @@ +45 5.827 5.82 4.55 1.835 1.835 1.798 +50 4.245 4.252 3.275 1.997 1.997 1.971 +55 2.984 2.989 2.231 1.899 1.899 1.93 +60 2.127 2.126 1.528 1.713 1.712 1.799 +65 1.563 1.559 1.08 1.483 1.481 1.601 +70 1.189 1.184 0.7948 1.233 1.231 1.357 +75 0.9341 0.9309 0.6102 0.9811 0.9799 1.085 +80 0.7567 0.755 0.4879 0.7396 0.7401 0.8069 +85 0.6302 0.6298 0.4052 0.5192 0.5211 0.5438 +90 0.5386 0.5391 0.3483 0.3282 0.3307 0.3137 +95 0.4713 0.4722 0.3089 0.1722 0.1742 0.1293 +100 0.4212 0.4222 0.2812 0.05337 0.05421 -0.003798 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/073_Ta_P1(6s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/073_Ta_P1(6s).txt new file mode 100644 index 0000000..4ee04ad --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/073_Ta_P1(6s).txt @@ -0,0 +1,108 @@ +10.2 0.03545 0.03571 0.3539 2 2 2 +15 0.02301 0.02321 0.34 2 2 2 +16.7 0.0397 0.04002 0.3197 2 2 2 +20 0.06339 0.06376 0.2815 2 2 2 +21.2 0.06922 0.06956 0.2689 2 2 2 +25 0.0805 0.08087 0.234 2 2 2 +26.8 0.0831 0.08355 0.22 2 2 2 +30 0.08504 0.08562 0.1981 2 2 2 +35 0.08393 0.08457 0.1702 2 2 2 +40 0.08023 0.08076 0.1477 2 2 2 +40.8 0.0795 0.08 0.1445 2 2 2 +45 0.07537 0.07567 0.1291 2 2 2 +50 0.07001 0.0701 0.1135 2 2 2 +55 0.06453 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/074_W_P1(6s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/074_W_P1(6s).txt new file mode 100644 index 0000000..b80adb8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/074_W_P1(6s).txt @@ -0,0 +1,108 @@ +10.2 0.0661 0.06608 0.3564 2 2 2 +15 0.01613 0.01639 0.3543 2 2 2 +16.7 0.03291 0.0333 0.3345 2 2 2 +20 0.05866 0.05912 0.2958 2 2 2 +21.2 0.06529 0.06573 0.2827 2 2 2 +25 0.07876 0.07919 0.2466 2 2 2 +26.8 0.08218 0.08267 0.2319 2 2 2 +30 0.08527 0.08587 0.2092 2 2 2 +35 0.08542 0.08608 0.1802 2 2 2 +40 0.08258 0.08311 0.1569 2 2 2 +40.8 0.08196 0.08247 0.1536 2 2 2 +45 0.0783 0.0786 0.1377 2 2 2 +50 0.07332 0.0734 0.1215 2 2 2 +55 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/075_Re_O45(5d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/075_Re_O45(5d).txt new file mode 100644 index 0000000..17bd38d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/075_Re_O45(5d).txt @@ -0,0 +1,107 @@ +15 15.8 15.79 14.89 -0.04807 -0.04725 0.06146 +16.71 19.63 19.63 18.88 -0.06189 -0.05976 0.04876 +20 26.32 26.29 25.67 0.05984 0.06008 0.1464 +21.22 28.08 28.03 27.44 0.1178 0.1171 0.1941 +25 29.56 29.53 29.03 0.2935 0.2922 0.3438 +26.86 28.28 28.27 27.81 0.3734 0.3728 0.4142 +30 24.51 24.51 24.12 0.4984 0.4987 0.5259 +35 17.93 17.91 17.62 0.676 0.6762 0.687 +40 12.79 12.77 12.55 0.8322 0.8322 0.8318 +40.81 12.1 12.09 11.89 0.8558 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/075_Re_P1(6s).txt new file mode 100644 index 0000000..bc4835c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/075_Re_P1(6s).txt @@ -0,0 +1,108 @@ +10.2 0.1055 0.1042 0.3599 2 2 2 +15 0.0105 0.01076 0.3673 2 2 2 +16.7 0.02677 0.02707 0.3477 2 2 2 +20 0.05408 0.05419 0.3081 2 2 2 +21.2 0.06144 0.06143 0.2946 2 2 2 +25 0.07694 0.07668 0.2571 2 2 2 +26.8 0.08113 0.08084 0.2419 2 2 2 +30 0.0853 0.08504 0.2184 2 2 2 +35 0.08663 0.08641 0.1885 2 2 2 +40 0.08454 0.08428 0.1646 2 2 2 +40.8 0.08402 0.08375 0.1612 2 2 2 +45 0.08075 0.08037 0.145 2 2 2 +50 0.07606 0.0756 0.1285 2 2 2 +55 0.07093 0.07052 0.1144 2 2 2 +60 0.06575 0.06545 0.1022 2 2 2 +65 0.0608 0.0606 0.0918 2 2 2 +70 0.05617 0.05606 0.08278 2 2 2 +75 0.05195 0.05189 0.07497 2 2 2 +80 0.04814 0.0481 0.0682 2 2 2 +85 0.0447 0.04467 0.06231 2 2 2 +90 0.04156 0.04158 0.05717 2 2 2 +95 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/076_Os_O1(5s).txt new file mode 100644 index 0000000..cf9299a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/076_Os_O1(5s).txt @@ -0,0 +1,55 @@ +100 0.1921 0.1924 0.2951 2 2 2 +120 0.1897 0.1903 0.2673 2 2 2 +132.3 0.1832 0.1831 0.2482 2 2 2 +140 0.1775 0.177 0.2357 2 2 2 +151.4 0.1679 0.1672 0.2178 2 2 2 +160 0.1605 0.1598 0.2053 2 2 2 +180 0.1441 0.144 0.1802 2 2 2 +200 0.1296 0.13 0.1594 2 2 2 +220 0.117 0.1173 0.1416 2 2 2 +240 0.1061 0.106 0.1263 2 2 2 +260 0.09641 0.09608 0.1133 2 2 2 +280 0.08781 0.08752 0.1023 2 2 2 +300 0.08012 0.08004 0.09284 2 2 2 +320 0.07332 0.07346 0.08464 2 2 2 +340 0.06741 0.06763 0.07745 2 2 2 +360 0.06231 0.06246 0.07114 2 2 2 +380 0.05789 0.05786 0.06559 2 2 2 +400 0.05395 0.05377 0.0607 2 2 2 +420 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/078_Pt_N23(4p).txt new file mode 100644 index 0000000..8fbbaad --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/078_Pt_N23(4p).txt @@ -0,0 +1,33 @@ +500 0.3008 0.3004 0.2808 -0.8197 -0.8183 -0.7244 +520 0.3582 0.3576 0.3466 -0.4256 -0.4251 -0.3123 +540 0.3591 0.3584 0.3489 -0.03161 -0.03183 0.05875 +560 0.3484 0.3479 0.3393 0.2159 0.2154 0.2901 +580 0.3409 0.3406 0.3331 0.4044 0.4039 0.4664 +600 0.3337 0.3336 0.3271 0.5604 0.56 0.6119 +620 0.3256 0.3257 0.32 0.6878 0.6876 0.7304 +640 0.3173 0.3175 0.3125 0.7905 0.7904 0.8258 +660 0.3095 0.3098 0.3053 0.8751 0.8751 0.9042 +680 0.3022 0.3025 0.2986 0.9474 0.9474 0.9711 +700 0.2952 0.2954 0.292 1.011 1.011 1.03 +720 0.2881 0.2882 0.2853 1.067 1.068 1.082 +740 0.281 0.281 0.2784 1.117 1.118 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Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/078_Pt_N45(4d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/078_Pt_N45(4d).txt new file mode 100644 index 0000000..79e74e4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/078_Pt_N45(4d).txt @@ -0,0 +1,86 @@ +330 0.306 0.3052 0.2914 0.2386 0.2398 0.2425 +335 0.2885 0.2879 0.2751 0.3551 0.3583 0.3674 +340 0.2752 0.2747 0.2629 0.5459 0.5508 0.5687 +345 0.2702 0.27 0.2593 0.776 0.7814 0.8073 +350 0.2771 0.2772 0.2677 0.8735 0.8776 0.9032 +355 0.2911 0.2913 0.283 0.6972 0.6992 0.7164 +360 0.3063 0.3067 0.2993 0.396 0.3968 0.4064 +365 0.3218 0.3221 0.3155 0.09904 0.09933 0.1048 +370 0.3378 0.3381 0.3322 -0.1534 -0.1533 -0.1492 +375 0.3546 0.3549 0.3497 -0.3566 -0.3566 -0.3519 +380 0.372 0.3722 0.3675 -0.5146 -0.5146 -0.5084 +385 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/078_Pt_O1(5s).txt @@ -0,0 +1,55 @@ +100 0.1913 0.1913 0.3126 2 2 2 +120 0.1851 0.1856 0.2727 2 2 2 +132.3 0.1811 0.1813 0.2553 2 2 2 +140 0.1779 0.1778 0.2451 2 2 2 +151.4 0.1717 0.1713 0.2301 2 2 2 +160 0.1661 0.1655 0.2188 2 2 2 +180 0.1512 0.151 0.1936 2 2 2 +200 0.1367 0.1369 0.1715 2 2 2 +220 0.1241 0.1243 0.1529 2 2 2 +240 0.1133 0.1133 0.1374 2 2 2 +260 0.1038 0.1036 0.124 2 2 2 +280 0.09503 0.09481 0.1124 2 2 2 +300 0.08706 0.08696 0.1022 2 2 2 +320 0.07993 0.07998 0.09328 2 2 2 +340 0.07368 0.07381 0.08551 2 2 2 +360 0.06825 0.06835 0.07872 2 2 2 +380 0.06349 0.06349 0.07274 2 2 2 +400 0.05924 0.05913 0.06742 2 2 2 +420 0.05537 0.05518 0.06267 2 2 2 +440 0.0518 0.0516 0.05838 2 2 2 +460 0.04849 0.04836 0.05452 2 2 2 +480 0.04545 0.04541 0.05104 2 2 2 +500 0.04268 0.04273 0.04789 2 2 2 +520 0.04019 0.0403 0.04503 2 2 2 +540 0.03795 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/079_Au_N1(4s).txt new file mode 100644 index 0000000..2bd8508 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/079_Au_N1(4s).txt @@ -0,0 +1,27 @@ +620 0.1256 0.1253 0.1402 2 2 2 +640 0.111 0.1107 0.1235 2 2 2 +660 0.1053 0.1051 0.117 2 2 2 +680 0.1031 0.103 0.1143 2 2 2 +700 0.1004 0.1003 0.1111 2 2 2 +720 0.09702 0.097 0.1072 2 2 2 +740 0.09363 0.09364 0.1033 2 2 2 +760 0.09057 0.09061 0.09975 2 2 2 +780 0.08781 0.08786 0.09655 2 2 2 +800 0.08518 0.08523 0.0935 2 2 2 +850 0.07882 0.07883 0.08615 2 2 2 +900 0.07309 0.07305 0.07955 2 2 2 +950 0.06804 0.06795 0.07379 2 2 2 +1000 0.06341 0.0633 0.06855 2 2 2 +1041 0.0599 0.0598 0.06463 2 2 2 +1050 0.05917 0.05907 0.06382 2 2 2 +1100 0.05535 0.05528 0.05959 2 2 2 +1150 0.05187 0.05184 0.05577 2 2 2 +1200 0.04868 0.04868 0.05228 2 2 2 +1250 0.04577 0.04581 0.04911 2 2 2 +1253.6 0.04558 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/079_Au_N67(4f).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/079_Au_N67(4f).txt new file mode 100644 index 0000000..934cbcf --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/079_Au_N67(4f).txt @@ -0,0 +1,98 @@ +115 0.451 0.4488 0.4317 0.3631 0.3658 0.3677 +120 0.5003 0.4985 0.4802 0.4862 0.4914 0.4959 +125 0.5154 0.5144 0.4963 0.6545 0.6614 0.6689 +130 0.5164 0.5163 0.4992 0.8648 0.8718 0.8824 +132.3 0.5159 0.5162 0.4996 0.9716 0.9782 0.99 +135 0.5166 0.5174 0.5015 1.1 1.106 1.119 +140 0.5262 0.5277 0.513 1.324 1.327 1.341 +145 0.5534 0.5553 0.5418 1.49 1.492 1.503 +150 0.6056 0.6074 0.595 1.565 1.564 1.573 +151.4 0.6247 0.6264 0.6143 1.566 1.566 1.573 +155 0.6829 0.6843 0.6729 1.535 1.535 1.539 +160 0.7847 0.7855 0.775 1.432 1.432 1.434 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/082_Pb_P23(6p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/082_Pb_P23(6p).txt new file mode 100644 index 0000000..cec9f91 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/082_Pb_P23(6p).txt @@ -0,0 +1,108 @@ +10.2 11.88 11.89 9.133 1.723 1.723 1.071 +15 3.806 3.807 2.693 1.89 1.89 1.377 +16.7 2.733 2.733 1.875 1.897 1.897 1.464 +20 1.561 1.561 1.009 1.865 1.865 1.593 +21.2 1.303 1.303 0.8248 1.842 1.842 1.627 +25 0.7825 0.7826 0.4654 1.74 1.74 1.687 +26.8 0.6322 0.6323 0.3658 1.681 1.681 1.692 +30 0.4484 0.4485 0.248 1.562 1.562 1.667 +35 0.2822 0.2821 0.1469 1.353 1.353 1.546 +40 0.1903 0.1902 0.09461 1.128 1.128 1.342 +40.8 0.1797 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/083_Bi_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/083_Bi_N1(4s).txt new file mode 100644 index 0000000..892ba6f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/083_Bi_N1(4s).txt @@ -0,0 +1,20 @@ +760 0.09197 0.0917 0.1025 2 2 2 +780 0.09615 0.09591 0.107 2 2 2 +800 0.09334 0.09317 0.1037 2 2 2 +850 0.08627 0.08624 0.09554 2 2 2 +900 0.07986 0.07991 0.08817 2 2 2 +950 0.07459 0.07466 0.08209 2 2 2 +1000 0.06956 0.06962 0.07629 2 2 2 +1041 0.06596 0.06598 0.07213 2 2 2 +1050 0.06521 0.06522 0.07126 2 2 2 +1100 0.06114 0.06111 0.06659 2 2 2 +1150 0.05745 0.05739 0.06239 2 2 2 +1200 0.0541 0.05402 0.0586 2 2 2 +1250 0.05096 0.05088 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/083_Bi_N45(4d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/083_Bi_N45(4d).txt new file mode 100644 index 0000000..b5e735b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/083_Bi_N45(4d).txt @@ -0,0 +1,80 @@ +460 0.1705 0.1701 0.1632 0.1557 0.1555 0.1542 +465 0.1998 0.1996 0.1933 0.8144 0.8166 0.8322 +470 0.3813 0.382 0.3791 1.917 1.918 1.921 +475 0.5639 0.5652 0.5653 1.738 1.737 1.731 +480 0.5805 0.5815 0.5818 1.184 1.184 1.184 +485 0.5911 0.5919 0.5923 0.7206 0.7209 0.7265 +490 0.5999 0.6005 0.601 0.3618 0.3623 0.3723 +495 0.6023 0.6027 0.6034 0.09169 0.09208 0.1056 +500 0.6003 0.6005 0.6012 -0.1068 -0.1065 -0.09041 +505 0.5974 0.5974 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/084_Po_N45(4d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/084_Po_N45(4d).txt new file mode 100644 index 0000000..98204d1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/084_Po_N45(4d).txt @@ -0,0 +1,77 @@ +495 0.2084 0.2083 0.2032 0.8117 0.8137 0.8264 +500 0.6146 0.6164 0.6178 1.881 1.879 1.868 +505 0.7674 0.7693 0.7728 1.541 1.54 1.531 +510 0.692 0.6932 0.6954 1.041 1.041 1.041 +515 0.6731 0.6739 0.6757 0.6313 0.6317 0.6378 +520 0.6657 0.6662 0.6679 0.3139 0.3143 0.3251 +525 0.6564 0.6566 0.6583 0.07482 0.07523 0.08939 +530 0.6458 0.6459 0.6474 -0.101 -0.1007 -0.08407 +535 0.6369 0.6368 0.6383 -0.2279 -0.2278 -0.2094 +540 0.6312 0.631 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/085_At_N1(4s).txt new file mode 100644 index 0000000..20f314c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/085_At_N1(4s).txt @@ -0,0 +1,17 @@ +850 0.08839 0.08825 0.09848 2 2 2 +900 0.0833 0.08324 0.09248 2 2 2 +950 0.07809 0.07809 0.08642 2 2 2 +1000 0.07285 0.07288 0.08037 2 2 2 +1041 0.06909 0.06911 0.07602 2 2 2 +1050 0.06827 0.06829 0.07507 2 2 2 +1100 0.06403 0.06404 0.07019 2 2 2 +1150 0.06025 0.06023 0.06585 2 2 2 +1200 0.05673 0.05669 0.06183 2 2 2 +1250 0.05353 0.05348 0.0582 2 2 2 +1253.6 0.05331 0.05326 0.05795 2 2 2 +1300 0.05057 0.05052 0.05487 2 2 2 +1350 0.04782 0.04778 0.0518 2 2 2 +1400 0.0453 0.04527 0.04899 2 2 2 +1450 0.04296 0.04295 0.0464 2 2 2 +1486.6 0.04135 0.04135 0.04462 2 2 2 +1500 0.04079 0.04079 0.044 2 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/086_Rn_N67(4f).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/086_Rn_N67(4f).txt new file mode 100644 index 0000000..a01a5b8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/086_Rn_N67(4f).txt @@ -0,0 +1,88 @@ +270 0.3028 0.3009 0.2934 0.2674 0.2671 0.2669 +275 0.2479 0.2466 0.2406 0.2846 0.2846 0.2846 +280 0.225 0.2241 0.2189 0.3983 0.3997 0.4013 +285 0.2217 0.2213 0.2164 0.674 0.6775 0.6823 +290 0.2365 0.2365 0.2319 1.104 1.109 1.117 +295 0.2716 0.2722 0.2678 1.555 1.559 1.567 +300 0.3292 0.3302 0.3261 1.87 1.872 1.877 +305 0.4091 0.4107 0.4067 1.994 1.995 1.995 +310 0.5094 0.5113 0.5075 1.971 1.971 1.968 +315 0.6327 0.6347 0.6311 1.863 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/091_Pa_N23(4p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/091_Pa_N23(4p).txt new file mode 100644 index 0000000..8dca713 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/091_Pa_N23(4p).txt @@ -0,0 +1,14 @@ +1000 0.2574 0.2571 0.2533 0.2152 0.2147 0.3001 +1041 0.2488 0.2487 0.2455 0.6083 0.608 0.6599 +1050 0.2469 0.2469 0.2439 0.6651 0.6647 0.7117 +1100 0.2354 0.2355 0.2331 0.8947 0.8946 0.9215 +1150 0.2243 0.2245 0.2226 1.044 1.044 1.057 +1200 0.2138 0.2141 0.2125 1.149 1.149 1.154 +1250 0.2038 0.2039 0.2027 1.23 1.23 1.227 +1253.6 0.2031 0.2032 0.202 1.235 1.235 1.232 +1300 0.1944 0.1945 0.1935 1.294 1.294 1.286 +1350 0.1855 0.1855 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_N67(4f).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_N67(4f).txt new file mode 100644 index 0000000..9466d91 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_N67(4f).txt @@ -0,0 +1,78 @@ +485 0.1171 0.1167 0.1143 0.1712 0.1705 0.1692 +490 0.1189 0.1186 0.1161 0.02119 0.0198 0.01694 +495 0.1214 0.1211 0.1188 -0.03902 -0.04027 -0.04317 +500 0.1328 0.1327 0.1304 0.179 0.179 0.179 +505 0.1594 0.1595 0.1573 0.6477 0.6486 0.6515 +510 0.2078 0.2081 0.206 1.142 1.143 1.145 +515 0.2845 0.2851 0.2831 1.497 1.497 1.496 +520 0.3932 0.3941 0.3922 1.674 1.674 1.67 +525 0.5338 0.5349 0.5332 1.715 1.714 1.709 +530 0.7048 0.7062 0.7046 1.672 1.672 1.665 +535 0.9056 0.9071 0.9056 1.585 1.585 1.578 +540 1.134 1.136 1.135 1.478 1.478 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Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_O1(5s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_O1(5s).txt new file mode 100644 index 0000000..bf13168 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_O1(5s).txt @@ -0,0 +1,44 @@ +280 0.1657 0.1653 0.2235 2 2 2 +300 0.1581 0.158 0.2097 2 2 2 +320 0.1472 0.1474 0.1925 2 2 2 +340 0.1386 0.1389 0.1789 2 2 2 +360 0.1303 0.1306 0.1662 2 2 2 +380 0.1228 0.1229 0.1548 2 2 2 +400 0.116 0.116 0.1447 2 2 2 +420 0.1096 0.1094 0.1354 2 2 2 +440 0.1035 0.1033 0.1268 2 2 2 +460 0.09797 0.09775 0.1192 2 2 2 +480 0.09279 0.09259 0.1122 2 2 2 +500 0.08792 0.08778 0.1058 2 2 2 +520 0.08337 0.0833 0.09984 2 2 2 +540 0.07917 0.07917 0.09443 2 2 2 +560 0.07529 0.07534 0.08946 2 2 2 +580 0.07168 0.07177 0.08486 2 2 2 +600 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_O23(5p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_O23(5p).txt new file mode 100644 index 0000000..3813e11 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_O23(5p).txt @@ -0,0 +1,92 @@ +215 0.4299 0.4292 0.2958 -0.8334 -0.8343 -0.9553 +220 0.4192 0.4186 0.2972 -0.8751 -0.8752 -0.9588 +225 0.4143 0.4138 0.2995 -0.7917 -0.7914 -0.8293 +230 0.4087 0.4083 0.3002 -0.6963 -0.696 -0.6976 +235 0.4021 0.4019 0.3 -0.6082 -0.6081 -0.5798 +240 0.3952 0.3952 0.2995 -0.5261 -0.5261 -0.4724 +245 0.3888 0.3889 0.2993 -0.4462 -0.4463 -0.3709 +250 0.383 0.3832 0.2993 -0.3669 -0.3672 -0.274 +255 0.3778 0.3782 0.2992 -0.2892 -0.2894 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_O67(5f).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_O67(5f).txt new file mode 100644 index 0000000..4d8c8da --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/094_Pu_O67(5f).txt @@ -0,0 +1,106 @@ +20 1.302 1.302 1.084 1.817 1.815 1.896 +21.22 1.473 1.47 1.274 1.877 1.876 1.911 +25 2.367 2.361 2.221 1.625 1.625 1.587 +26.86 3.003 3.002 2.881 1.424 1.423 1.385 +30 4.312 4.318 4.222 1.119 1.118 1.093 +35 6.708 6.71 6.64 0.7833 0.7834 0.7806 +40 9.085 9.075 9.021 0.5885 0.5882 0.5976 +40.81 9.45 9.439 9.387 0.5657 0.5653 0.576 +45 11.21 11.2 11.15 0.4742 0.4741 0.4892 +50 12.9 12.91 12.87 0.4066 0.4073 0.4245 +55 14.01 14.02 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/095_Am_N23(4p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/095_Am_N23(4p).txt new file mode 100644 index 0000000..39f8dec --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/095_Am_N23(4p).txt @@ -0,0 +1,10 @@ +1150 0.2377 0.2373 0.2339 0.2626 0.2621 0.3484 +1200 0.228 0.2279 0.225 0.6775 0.6771 0.7251 +1250 0.2181 0.2182 0.2158 0.8961 0.8958 0.9234 +1253.6 0.2174 0.2175 0.2151 0.9081 0.9079 0.9343 +1300 0.2086 0.2088 0.2068 1.039 1.039 1.053 +1350 0.1996 0.1998 0.1981 1.141 1.141 1.146 +1400 0.1909 0.1912 0.1898 1.22 1.22 1.217 +1450 0.1828 0.183 0.1818 1.282 1.282 1.274 +1486.6 0.1772 0.1773 0.1763 1.32 1.32 1.308 +1500 0.1752 0.1753 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/095_Am_O1(5s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/095_Am_O1(5s).txt new file mode 100644 index 0000000..e1a1065 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/095_Am_O1(5s).txt @@ -0,0 +1,44 @@ +280 0.1684 0.1681 0.2294 2 2 2 +300 0.1602 0.1601 0.2142 2 2 2 +320 0.15 0.1502 0.1976 2 2 2 +340 0.1409 0.1412 0.1831 2 2 2 +360 0.1329 0.1332 0.1706 2 2 2 +380 0.1252 0.1254 0.1588 2 2 2 +400 0.1183 0.1184 0.1485 2 2 2 +420 0.1119 0.1119 0.1391 2 2 2 +440 0.1059 0.1057 0.1305 2 2 2 +460 0.1002 0.1001 0.1226 2 2 2 +480 0.09504 0.09486 0.1155 2 2 2 +500 0.09016 0.09002 0.1089 2 2 2 +520 0.08558 0.08549 0.1029 2 2 2 +540 0.08132 0.08129 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and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/096_Cm_N1(4s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/096_Cm_N1(4s).txt new file mode 100644 index 0000000..4721896 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/096_Cm_N1(4s).txt @@ -0,0 +1,6 @@ +1300 0.06439 0.06434 0.07178 2 2 2 +1350 0.06097 0.06096 0.06782 2 2 2 +1400 0.058 0.05802 0.06438 2 2 2 +1450 0.05524 0.05527 0.06119 2 2 2 +1486.6 0.05326 0.0533 0.05891 2 2 2 +1500 0.05259 0.05263 0.05813 2 2 2 diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/096_Cm_N23(4p).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/096_Cm_N67(4f).txt new file mode 100644 index 0000000..ba477bc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/096_Cm_N67(4f).txt @@ -0,0 +1,76 @@ +545 0.1014 0.101 0.09887 0.146 0.1451 0.1435 +550 0.1046 0.1042 0.1021 -0.04323 -0.04505 -0.04857 +555 0.1082 0.1079 0.1058 -0.1497 -0.1514 -0.1552 +560 0.1211 0.121 0.1191 0.03156 0.03126 0.03053 +565 0.1502 0.1503 0.1484 0.4923 0.4931 0.4954 +570 0.2026 0.203 0.2012 0.9862 0.9868 0.9886 +575 0.2871 0.2878 0.2861 1.346 1.346 1.345 +580 0.4095 0.4106 0.4091 1.538 1.537 1.533 +585 0.5705 0.572 0.5706 1.598 1.597 1.591 +590 0.7668 0.7685 0.7673 1.576 1.575 1.569 +595 0.9948 0.9968 0.9957 1.509 1.509 1.502 +600 1.251 1.253 1.252 1.421 1.42 1.414 +605 1.529 1.531 1.531 1.324 1.324 1.319 +610 1.819 1.821 1.82 1.227 1.227 1.223 +615 2.108 2.109 2.109 1.134 1.135 1.131 +620 2.383 2.385 2.384 1.048 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(PIXSAD)/data/PIXSAD_Data_YehLindau1985/098_Cf_N67(4f).txt new file mode 100644 index 0000000..4cb98d4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/098_Cf_N67(4f).txt @@ -0,0 +1,75 @@ +600 0.09208 0.09185 0.08989 0.1415 0.1409 0.1393 +605 0.09419 0.094 0.09204 -0.03217 -0.03333 -0.03671 +610 0.09661 0.09647 0.09459 -0.1451 -0.1463 -0.1501 +615 0.106 0.1059 0.1041 -0.01643 -0.01679 -0.01813 +620 0.1273 0.1274 0.1256 0.3709 0.3714 0.3732 +625 0.1663 0.1665 0.1648 0.8352 0.8357 0.838 +630 0.2301 0.2304 0.2288 1.216 1.216 1.216 +635 0.3253 0.3259 0.3244 1.451 1.451 1.448 +640 0.4555 0.4563 0.455 1.555 1.555 1.55 +645 0.621 0.622 0.6207 1.568 1.568 1.562 +650 0.8205 0.8217 0.8206 1.526 1.526 1.52 +655 1.053 1.054 1.053 1.455 1.455 1.448 +660 1.314 1.315 1.315 1.369 1.369 1.364 +665 1.597 1.599 1.598 1.279 1.279 1.274 +670 1.89 1.892 1.891 1.191 1.191 1.186 +675 2.18 2.182 2.182 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/101_Md_P45(6d).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/101_Md_P45(6d).txt new file mode 100644 index 0000000..6db97d8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/101_Md_P45(6d).txt @@ -0,0 +1,109 @@ +10 9.108 9.104 8.494 0.09671 0.096 0.3694 +10.2 9.198 9.193 8.593 0.1038 0.1029 0.3694 +15 8.384 8.39 7.988 0.3516 0.3527 0.4771 +16.71 7.317 7.314 6.973 0.4419 0.4426 0.5338 +20 5.299 5.294 5.051 0.6015 0.601 0.646 +21.22 4.668 4.668 4.453 0.6554 0.655 0.6873 +25 3.189 3.191 3.041 0.8086 0.8086 0.8113 +26.86 2.675 2.673 2.545 0.8778 0.8777 0.8698 +30 2.017 2.013 1.915 0.9863 0.9863 0.9649 +35 1.325 1.327 1.261 1.142 1.142 1.107 +40 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a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/103_Lr_P1(6s).txt b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/103_Lr_P1(6s).txt new file mode 100644 index 0000000..e811600 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_Data_YehLindau1985/103_Lr_P1(6s).txt @@ -0,0 +1,102 @@ +50 0.1298 0.1298 0.7722 2 2 2 +55 0.1484 0.1475 0.6724 2 2 2 +60 0.1612 0.1612 0.6091 2 2 2 +65 0.1706 0.1716 0.5634 2 2 2 +70 0.1774 0.1788 0.526 2 2 2 +75 0.1814 0.1827 0.4921 2 2 2 +80 0.1828 0.1836 0.4599 2 2 2 +85 0.1819 0.182 0.4291 2 2 2 +90 0.179 0.1786 0.4 2 2 2 +95 0.1747 0.1741 0.373 2 2 2 +100 0.1696 0.169 0.3485 2 2 2 +105 0.1641 0.1638 0.3263 2 2 2 +110 0.1585 0.1585 0.3064 2 2 2 +115 0.153 0.1533 0.2885 2 2 2 +120 0.1477 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Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_PCC.mat differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_export2matlab.mlx b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_export2matlab.mlx new file mode 100644 index 0000000..f1cca24 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/data/PIXSAD_export2matlab.mlx differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/get_pixsad_props.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/get_pixsad_props.m new file mode 100644 index 0000000..987ca0c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/get_pixsad_props.m @@ -0,0 +1,118 @@ +function [hv, xsect, asymmetry] = get_pixsad_props(element, corelevel, hvi) +% [hv, xsect, asymmetry] = get_pixsad_props(element, corelevel, hvi) +% This is a function that extracts all of the parameters from the +% Photoionisation Cross-Section and Asymmetry Database (PIXSAD) for the +% element defined here by the user. This database contains all the +% photoionisation cross-sections and asymmetry parameters for elements 1 +% - 103, for orbitals that are probed with soft x-ray radiation (20 - +% 1500 eV). +% +% IN: +% - element: char/string of the element; e.g. "H", "He", "Si", "In"... +% - corelevel: char/string of the core-level to be probed; e.g. "1s", "2s", "2p", "4d"... +% - hvi: photon energy value (or range [min, max]) over which the cross-section and asymmetries will be determined. +% +% OUT: +% - hv: 1×N vector (or table) of the interpolated / nearest photon energies to the input based on the data. +% - xsect: 1×N vector (or table) of the photoionisation cross-sections. +% - asymmetry: 1×N vector (or table) of the asymmetries. +% NOTE: if any of the outputs are NaN, this means you are outside of the +% range of photon energies for the defined data. + +%% Default parameters +if nargin < 2; corelevel = []; end +if nargin < 3; hvi = []; end +if isempty(corelevel); corelevel = []; end +if isempty(hvi); hvi = []; end +% -- Sorting the photon energy to ascending order +hvi = sort(hvi); + +%% - 1 - Loading the PIXS properties from our MATLAB database +PIXSAD_PCC = load('PIXSAD_PCC.mat'); PIXSAD_PCC = PIXSAD_PCC.PIXSAD_PCC; + +%% - 2 - Find the index of the element defined by the user +% -- Find the element +if ~isempty(element) + % -- Find the row-number / index for the element of choice (case-insensitive) + element = char(element); + ele_indx = find(strcmpi([PIXSAD_PCC.ATOM_SYMB], element)); + if isempty(ele_indx) + msg = 'Element could not be identified. Only use atomic-symbols for elements 1 - 103; H, He, Li, Be..., No, Lr'; error(msg) + end +% -- If no element is defined, return an error +else + msg = 'Element could not be identified. Only use atomic-symbols for elements 1 - 103; H, He, Li, Be..., No, Lr'; + error(msg) +end + +%% - 3 - Extracting the photoionisation data +%% - A - When no core-level is defined, output all the data +if isempty(corelevel) && isempty(hvi) + data = PIXSAD_PCC.DataTable{ele_indx}; + hv = data(:,1); + xsect = data(:,2:2:end); + asymmetry = data(:,3:2:end); +elseif isempty(corelevel) + data = PIXSAD_PCC.DataTable{ele_indx}; + hv = data.hv; + [~, lbindx] = min(abs(hv - min(hvi(:)))); + [~, ubindx] = min(abs(hv - max(hvi(:)))); + % -- For a single photon energy entry + if lbindx == ubindx + hv = data(lbindx,1); + xsect = data(lbindx,2:2:end); + asymmetry = data(lbindx,3:2:end); + % -- For a multiple photon energies + else + hv = data(lbindx:ubindx,1); + xsect = data(lbindx:ubindx,2:2:end); + asymmetry = data(lbindx:ubindx,3:2:end); + end +else + %% - A - Find the index of the core-level defined by the user + element_cls = PIXSAD_PCC.FileNames{ele_indx}; + % -- Find the core-level for the element of choice + if ~isempty(corelevel) && length(corelevel) == 2 + corelevel = lower(char(corelevel)); + cl_indx = find(contains(lower(element_cls), corelevel)); + if isempty(cl_indx) + msg = sprintf("Core-level not found. For element %s, only the following core-levels have data; ", element); + for i = 1:length(element_cls); msg = msg + string(element_cls{i}(end-6:end-5)) + ", "; end + error(msg) + end + % -- Extracting the data from the PIXS database + Data = PIXSAD_PCC.DataInt{ele_indx}{cl_indx}; + % -- If no core-level are defined, make user input one + else + msg = sprintf("Core-level not found. For element %s, only the following core-levels have data; ", element); + for i = 1:length(element_cls); msg = msg + string(element_cls{i}(end-6:end-5)) + ", "; end + error(msg) + end + %% - B - Extract the photoionisaion cross-section and asymmetry for the chosen photon energy + % -- Printing output text for the element and core-level selected +% fprintf("PIXS DATA: Symbol: %s, Core-Level: %s", element, corelevel); + % --- If photon energy is empty, default to all values + if isempty(hvi) + hv = Data(:,1); + xsect = Data(:,2); + asymmetry = Data(:,3); + % --- For a range of photon energies + elseif length(hvi) > 1 + for i = 1:length(hvi) + [~, hv_indx] = min(abs(Data(:,1) - hvi(i))); + % -- Extracting the relevant parameters + hv(i) = Data(hv_indx,1); + xsect(i) = Data(hv_indx,2); + asymmetry(i) = Data(hv_indx,3); + end + % --- For a single photon energy + else + % -- Find the index for the photon enegy + [~, hv_indx] = min(abs(Data(:,1) - hvi)); + % -- Extracting the relevant parameters + hv = Data(hv_indx,1); + xsect = Data(hv_indx,2); + asymmetry = Data(hv_indx,3); + end +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/view_pixsad_props.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/view_pixsad_props.m new file mode 100644 index 0000000..7de9da0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Cross-Section and Asymmetry Database (PIXSAD)/view_pixsad_props.m @@ -0,0 +1,55 @@ +function view_pixsad_props(element) +% view_pixsad_props(element) +% This is a function that plots the photoionisation cross-sections and +% asymmetry parameters of all the core-levels for a particular element +% defined by the user. This can be used to quickly view all the available +% data for a particular element. +% +% IN: +% - element: char/string of the element; e.g. "H", "He", "Si", "In"... +% +% OUT: (figure output) + +%% Default parameters (Parameters for Silicon) +if nargin < 1; element = "Si"; end +if isempty(element); element = "Si"; end +%% - Extracting the PIXSA properties from the Database +[hv, xsect, asymmetry] = get_pixsad_props(element); +%% - Initialising the figure +fig = figure(); hold on; +fig.Position(3) = 2*560; +fig.Position(4) = 420; +%% - Plotting the photoionisation cross-section +subplot(121); hold on; +if istable(xsect) + for i = 1:size(xsect,2) + plot(hv{:,1}, xsect{:,i}, '.-'); + end + legend(xsect.Properties.VariableNames, 'location', 'best'); +else + plot(hv, xsect, '.-'); +end +title('Photoionisation Cross Section (sigma)'); +xlabel('$$ \bf Photon\ Energy\ [eV] $$', 'interpreter', 'latex'); +ylabel('$$ \bf Cross\ Section\ [Mbarn] $$', 'interpreter', 'latex'); +ax = gca; +ax.YScale = 'log'; +grid on; +text(0.05, 0.07, string(element), 'FontSize', 18, 'color', 'k', 'Units','normalized', 'FontWeight', 'bold'); +% - Plotting the asymmetry +subplot(122); hold on; +if istable(asymmetry) + for i = 1:size(asymmetry,2) + plot(hv{:,1}, asymmetry{:,i}, '.-'); + end + legend(asymmetry.Properties.VariableNames, 'location', 'best'); +else + plot(hv, asymmetry, '.-'); +end +title(' Asymmetry Parameter (beta) '); +xlabel('$$ \bf Photon\ Energy\ [eV] $$', 'interpreter', 'latex'); +ylabel('$$ \bf Asymmetry $$', 'interpreter', 'latex'); +grid on; +text(0.05, 0.07, string(element), 'FontSize', 18, 'color', 'k', 'Units','normalized', 'FontWeight', 'bold'); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Energy and Fluorescence Database (PIEFD)/IUPAC Notation/IUPAC_notation-01.png b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Energy and Fluorescence Database (PIEFD)/IUPAC 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b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Energy and Fluorescence Database (PIEFD)/data/PIEFD_PCC_export2matlab.mlx new file mode 100644 index 0000000..a868b8c Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Energy and Fluorescence Database (PIEFD)/data/PIEFD_PCC_export2matlab.mlx differ diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Energy and Fluorescence Database (PIEFD)/get_piefd_props.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Energy and Fluorescence Database (PIEFD)/get_piefd_props.m new file mode 100644 index 0000000..e8209ad --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Energy and Fluorescence Database (PIEFD)/get_piefd_props.m @@ -0,0 +1,34 @@ +function piefd_props = get_piefd_props(element) +% piefd_props = get_piefd_props(element) +% This is a function that extracts all of the parameters from the +% Photoionisation Energy and Fluorescence Database (PIEFD) for the element +% defined here by the user. This database contains all the binding +% energies, emission / fluorescence lines, emission / fluorescence +% relative intensities and fluorescence yield. +% +% IN: +% - element: char/string of the element; e.g. "H", "He", "Si", "In"... +% +% OUT: +% - piefd_props: MATLAB table which contains all of the PIEFD parameters. + +%% Default parameters +if nargin < 1; element = []; end +if isempty(element); element = []; end + +%% - 1 - Extracting the material parameters from the materials properties database +% -- Loading in the materials database +PIEFD_PCC = load('PIEFD_PCC.mat'); PIEFD_PCC = PIEFD_PCC.PIEFD_PCC; +% -- Making the input material be in a 'char' format +element = char(element); +% -- Find the row-number / index for the material of choice +atom_symbols = PIEFD_PCC.ATOM_SYMB; +idx = find(strcmpi(atom_symbols(:), element)); +% -- Extract the properties of the desired material +if ~isempty(idx); piefd_props = PIEFD_PCC(idx,:); +% -- If no material is identified, return an error +else; msg = 'Material could not be identified or does not exist in database.'; piefd_props = []; +end +% -- Printing output text +% fprintf("LOADED DATA: ID: %i, Name: %s, Symbol: %s", piefd_props.ID, piefd_props.ATOM_NAME{1}, piefd_props.ATOM_SYMB{1}); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Energy and Fluorescence Database (PIEFD)/view_be_spectrum.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Energy and Fluorescence Database (PIEFD)/view_be_spectrum.m new file mode 100644 index 0000000..853e3b1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Photoionisation Energy and Fluorescence Database (PIEFD)/view_be_spectrum.m @@ -0,0 +1,76 @@ +function view_be_spectrum(element) +% view_be_spectrum(element) +% This is a function that plots the photoionisation cross-sections and +% asymmetry parameters of all the core-levels for a particular element +% defined by the user. This can be used to quickly view all the available +% data for a particular element. +% +% IN: +% - element: vector or single string of the elements; e.g. "H", "He", "Si", "In"... +% +% OUT: (figure output) + +%% Default parameters (Parameters for Silicon) +if nargin < 1; element = ["Si", "O", "Al"]; end +if isempty(element); element = ["Si", "O", "Al"]; end +% -- Ensuring the input is a string +element = convertCharsToStrings(element); + +%% - Filing through all the elements and extracting binding energies +for i = 1:length(element) + % - Extracting the PIXSA properties from the Database + piefd_props = get_piefd_props(element(i)); + piefd_BE = table2cell(piefd_props); + piefd_BE(1:5) = []; piefd_BE(25:end) = []; + piefd_BE = cell2mat(piefd_BE); + % -- Defining the x- and y-axis values + x(:,i) = -1* piefd_BE; + y(:,i) = 0.05*i + ones(size(x(:,i))); +end +%% - Defining the labels of the core-levels extracted +% LABEL = {... +% 'K1',... % 1s +% 'L1', 'L2', 'L3',... % 2s, 2p +% 'M1', 'M2', 'M3', 'M4', 'M5',... % 3s, 3p, 3d +% 'N1', 'N2', 'N3', 'N4', 'N5', 'N6', 'N7',... % 4s, 4p, 4d, 4f +% 'O1', 'O2', 'O3', 'O4', 'O5',... % 5s, 5p, 5d +% 'P1', 'P2', 'P3',... % 6s, 6p +% }; +LABEL = {... + '1s',... % K1 + '2s', '2p(1/2)', '2p(3/2)',... % L1,L2,L3 + '3s', '3p(1/2)', '3p(3/2)', '3d(3/2)','3d(5/2)',... % M1,M2,M3,M4,M5 + '4s', '4p(1/2)', '4p(3/2)', '4d(3/2)','4d(5/2)', '4f(5/2)', '4f(7/2)',... % N1,N2,N3,N4,N5,N6,N7 + '5s', '5p(1/2)', '5p(3/2)', '5d(3/2)','5d(5/2)',... % O1,O2,O3,O4,O5 + '6s', '6p(1/2)', '6p(3/2)',... % P1,P2,P3 + }; +yoff = linspace(0,1,length(LABEL)); +%% - Plotting the binding energy spectrum +fig = figure(); hold on; +fig.Position(3) = 800; +fig.Position(4) = 400; +% -- Plotting the binding energy spectrum +for i = 1:length(element) + stem(x(:,i), y(:,i), '-', 'linewidth', 3.0, 'marker', 'none'); +end +% -- Adding labels to each component +for i = 1:length(element) + for j = 1:length(x(:,i)) + label = sprintf('%s(%s)', string(element(i)), string(LABEL{j})); + text(x(j,i), y(j,i) - yoff(j), label, 'Rotation',45, 'FontWeight','bold', 'FontSize',10); + end +end +% -- Formatting the figure +title_str = "["; +for i = 1:length(element) + if i == length(element); title_str = title_str + string(element(i)) + "] : BE spectrum"; + else; title_str = title_str + string(element(i)) + ", "; + end +end +title(title_str); +xlabel('$$ \bf Binding\ Energy\ [eV] $$', 'interpreter', 'latex'); +ylabel('$$ \bf Intensity\ [arb.] $$', 'interpreter', 'latex'); +box off; +ylim([0, 1.25*max(y(:))]); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Physics Constants/physics_constants.m b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Physics Constants/physics_constants.m new file mode 100644 index 0000000..510b92b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/MaterialsDatabase_PCC/Physics Constants/physics_constants.m @@ -0,0 +1,65 @@ +function pc = physics_constants() +% pc = phys_consts() +% This function creates a MATLAB structure that returns all the physical +% constants necessary in Physics calculations. The physical constants are +% defined using the International System of Units (SI). +% +% IN: (none) +% +% OUT: +% - pc: MATLAB structure that contains all of the relevant physics constants. +%% - 1 - DEFINING ALL THE PHYSICS CONSTANTS +pc = struct(); +pc.G = 6.6743015e-11; % Newtonian constant of gravitation [m3â‹…kg−1â‹…s−2] +pc.c = 299792458.; % speed of light in vacuum [mâ‹…s−1] +pc.h = 6.62607015e-34; % Planck constant [Jâ‹…Hz−1] +pc.hbar = pc.h/2/pi; % reduced Planck constant [Jâ‹…s] +pc.mu0 = 1.25663706212e-6; % vacuum magnetic permeability [Nâ‹…A−2] +pc.Z0 = pc.mu0*pc.c; % characteristic impedance of vacuum [Ω] +pc.eps0 = 1/pc.mu0/pc.c^2; % vacuum electric permittivity [Fâ‹…m−1] +pc.ke = 1/4/pi/pc.eps0; % Coulomb constant [Nâ‹…m2â‹…C−2] +pc.kB = 1.380649e-23; % Boltzmann constant [Jâ‹…K−1] +pc.sigma = 5.670374419e-8; % Stefan–Boltzmann constant [Wâ‹…m−2â‹…K−4] +pc.c1 = 3.741771852e-16; % first radiation constant [Wâ‹…m2] +pc.c1L = 1.191042972e-16; % first radiation constant for spectral radiance [Wâ‹…m2â‹…sr−1] +pc.c2 = pc.h*pc.c/pc.kB; % second radiation constant [mâ‹…K] +pc.b = 2.897771955e-3; % Wien wavelength displacement law constant [mâ‹…K] +pc.bprime = pc.c/pc.b; % Wien frequency displacement law constant [Hzâ‹…K−1] +pc.bentropy = 3.002916077e-3; % Wien entropy displacement law constant [mâ‹…K] +pc.e = 1.602176634e-19; % elementary charge [C] +pc.G0 = 2*pc.e^2/pc.h; % conductance quantum [S] +pc.G0i = pc.h/2/pc.e^2; % inverse conductance quantum [Ω] +pc.Rk = pc.h/pc.e^2; % von Klitzing constant [Ω] +pc.Kj = 2*pc.e/pc.h; % Josephson constant [Hzâ‹…V−1] +pc.Phi0 = pc.h/2/pc.e; % magnetic flux quantum [Wb] +pc.alpha = pc.e^2/4/pi/pc.eps0/pc.hbar/pc.c; % fine-structure constant +pc.me = 9.109383701528e-31; % electron mass [kg] +pc.mp = 1.6726219236951e-27; % proton mass [kg] +pc.mn = 1.6749274980495e-27; % neutron mass [kg] +pc.mmu = 1.88353162742e-28; % muon mass [kg] +pc.mtau = 3.1675421e-27; % tau mass [kg] +pc.mt = 3.078453e-25; % top quark mass [kg] +pc.mpe = 1836.15267343; % proton-to-electron mass ratio +pc.mWZ = 0.8815317; % W-to-Z mass ratio +pc.ge = -2.0023193043625635; % electron g-factor +pc.gmu = -2.002331841813; % muon g-factor +pc.gp = 5.585694689316; % proton g-factor +pc.qc = pc.h/2/pc.me; % quantum of circulation [m2â‹…s−1] +pc.muB = 9.2740100783e-24; % Bohr magneton +pc.muN = 5.0507837461e-27; % nuclear magneton +pc.re = pc.e^2*pc.ke/pc.me/pc.c^2; % classical electron radius [m] +pc.sigma_e = 8*pi/3*pc.re^2; % Thomson cross section [m2] +pc.alpha0 = pc.hbar^2/pc.ke/pc.me/pc.e^2; % Bohr radius [m] +pc.Eh = pc.alpha^2*pc.c^2*pc.me; % Hartree energy [J] +pc.Ry = pc.Eh/2; % Rydberg unit of energy [J] +pc.Rinf = pc.alpha^2*pc.me*pc.c/2/pc.h; % Rydberg constant [m−1] +pc.Gf = (pc.h*pc.c)^3; % Fermi coupling constant [J−2] +pc.NA = 6.02214076e23; % Avogadro constant [mol−1] +pc.R = pc.NA*pc.kB; % molar gas constant [Jâ‹…mol−1â‹…K−1] +pc.F = pc.NA*pc.e; % Faraday constant [Câ‹…mol−1] +pc.NAh = pc.NA*pc.h; % molar Planck constant [Jâ‹…sâ‹…mol−1] +pc.m_C12 = 1.99264687992e-26; % atomic mass of carbon-12 [kg] +pc.M_C12 = 11.9999999958E-3; % molar mass of carbon-12 [kgâ‹…mol−1] +pc.mu = 1.66053906660e-27; % atomic mass constant [kg] +pc.Mu = 0.99999999965e-3; % molar mass constant [kgâ‹…mol−1] +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/0_ReadMeImages/000_MPD.png b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/0_ReadMeImages/000_MPD.png new file mode 100644 index 0000000..fdeb1e5 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/0_ReadMeImages/000_MPD.png differ diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/0_ReadMeImages/000_PIEFD.png b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/0_ReadMeImages/000_PIEFD.png new file mode 100644 index 0000000..afc0110 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/0_ReadMeImages/000_PIEFD.png differ diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/0_ReadMeImages/000_PIXSAD.png 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b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F000 - job file generators/ADRESS_JobFileGenerator_CLvsHV.m @@ -0,0 +1,144 @@ +function ADRESS_JobFileGenerator_CLvsHV() +% ADRESS_JobFileGenerator_CLvsHV() +% This is a function that generates a text-file that is compatible to use +% in the 'Restore Tab' button on 'SmartGUI' at the ADRESS beamline. It +% allows the user to create a list of scans to be taken as a function of +% photon energy, where each scan can be referenced to a known Fermi-edge, +% if desired. Very useful for XPS vs photon energy data sets. +%% (A) Defining the input parameters +FILENAME = char("ADRESS_JobFile_CLvsHV_" + string(datestr(now,'yyyymmdd_HHMMSS'))); +REPEATS = 1; % Total number of repeat acquisitions (or Sweeps) for high statistics (only applies to sample measurements, not Ef) +% -- Photon Energy cell array to file through +PHOTON_ENERGY{1} = [370,450,578,650,786,850,950,1050]; % Photon energy list #1 +PHOTON_ENERGY{2} = [650,786,850,950,1050]; % Photon energy list #2 +PHOTON_ENERGY{3} = [1050]; % Photon energy list #3 +%% (B) Set the SAMPLE measurement position +% - SAMPLE POSITION +x_samp ='-3.60'; +y_samp ='-4.20'; +z_samp ='5.098'; +tilt_samp ='0.00'; +theta_samp ='-11.00'; +phi_samp ='-233.00'; +ADef_samp = '0.0'; +% - SAMPLE ACQUISITION SETTINGS +slit_samp = '1'; +dt_samp = '0.1'; +pol_samp = 'LV'; +mode_samp = 'MAM'; +Ep_samp = '100'; +%% (C) Set the Fermi-level REFERENCE position +use_ref = 1; % Set whether you want to use a reference; 1 = True, 0 = False +% - REFERENCE POSITION +x_ref = x_samp; +y_ref = y_samp; +z_ref = z_samp; +tilt_ref = tilt_samp; +theta_ref = theta_samp; +phi_ref = phi_samp; +ADef_ref = ADef_samp; +% - REFERENCE ACQUISITION SETTINGS +name_ref = 'EF'; % name_ref = 'AuEF'; % name_ref = 'Au4d'; +Eb_ref = '-2'; % Eb_ref = '-88:0.02:-80'; +slit_ref = '20'; % slit_ref = '1'; +dt_ref = '20'; % dt_ref = '0.1'; +pol_ref = pol_samp; +mode_ref = mode_samp; +Ep_ref = Ep_samp; +%% (D) Initialising the JobFile with the entries +POSITION = {}; +%% - PHOTON ENERGIES #1 +POSITION{1} = struct(); +% -- In4d +ii=1; +POSITION{1}(ii).name='In4d'; POSITION{1}(ii).mode=mode_samp; POSITION{1}(ii).Ep=Ep_samp; +POSITION{1}(ii).pol=pol_samp; POSITION{1}(ii).slit=slit_samp; POSITION{1}(ii).dT=dt_samp; +POSITION{1}(ii).Eb='-33:0.02:-13'; +POSITION{1}(ii).tilt=tilt_samp; POSITION{1}(ii).theta=theta_samp; POSITION{1}(ii).phi=phi_samp; +POSITION{1}(ii).x=x_samp; POSITION{1}(ii).y=y_samp; POSITION{1}(ii).z=z_samp; +% -- As3d +ii=ii+1; +POSITION{1}(ii).name='As3d'; POSITION{1}(ii).mode=mode_samp; POSITION{1}(ii).Ep=Ep_samp; +POSITION{1}(ii).pol=pol_samp; POSITION{1}(ii).slit=slit_samp; POSITION{1}(ii).dT=dt_samp; +POSITION{1}(ii).Eb='-51:0.02:-37'; +POSITION{1}(ii).tilt=tilt_samp; POSITION{1}(ii).theta=theta_samp; POSITION{1}(ii).phi=phi_samp; +POSITION{1}(ii).x=x_samp; POSITION{1}(ii).y=y_samp; POSITION{1}(ii).z=z_samp; +% -- Al2p +ii=ii+1; +POSITION{1}(ii).name='Al2p'; POSITION{1}(ii).mode=mode_samp; POSITION{1}(ii).Ep=Ep_samp; +POSITION{1}(ii).pol=pol_samp; POSITION{1}(ii).slit=slit_samp; POSITION{1}(ii).dT=dt_samp; +POSITION{1}(ii).Eb='-82:0.02:-71'; +POSITION{1}(ii).tilt=tilt_samp; POSITION{1}(ii).theta=theta_samp; POSITION{1}(ii).phi=phi_samp; +POSITION{1}(ii).x=x_samp; POSITION{1}(ii).y=y_samp; POSITION{1}(ii).z=z_samp; +% -- Pb4f +ii=ii+1; +POSITION{1}(ii).name='Pb4f'; POSITION{1}(ii).mode=mode_samp; POSITION{1}(ii).Ep=Ep_samp; +POSITION{1}(ii).pol=pol_samp; POSITION{1}(ii).slit=slit_samp; POSITION{1}(ii).dT=dt_samp; +POSITION{1}(ii).Eb='-147:0.02:-134'; +POSITION{1}(ii).tilt=tilt_samp; POSITION{1}(ii).theta=theta_samp; POSITION{1}(ii).phi=phi_samp; +POSITION{1}(ii).x=x_samp; POSITION{1}(ii).y=y_samp; POSITION{1}(ii).z=z_samp; +% -- C1s +ii=ii+1; +POSITION{1}(ii).name='C1s'; POSITION{1}(ii).mode=mode_samp; POSITION{1}(ii).Ep=Ep_samp; +POSITION{1}(ii).pol=pol_samp; POSITION{1}(ii).slit=slit_samp; POSITION{1}(ii).dT=dt_samp; +POSITION{1}(ii).Eb='-290:0.02:-280'; +POSITION{1}(ii).tilt=tilt_samp; POSITION{1}(ii).theta=theta_samp; POSITION{1}(ii).phi=phi_samp; +POSITION{1}(ii).x=x_samp; POSITION{1}(ii).y=y_samp; POSITION{1}(ii).z=z_samp; +%% - PHOTON ENERGIES #2 +POSITION{2} = struct(); +% -- In3d +kk=1; +POSITION{2}(kk).name='In3d';POSITION{2}(kk).mode=mode_samp;POSITION{2}(kk).Ep=Ep_samp; +POSITION{2}(kk).pol=pol_samp;POSITION{2}(kk).slit=slit_samp;POSITION{2}(kk).dT=dt_samp; +POSITION{2}(kk).Eb='-449:0.02:-440'; +POSITION{2}(kk).tilt=tilt_samp;POSITION{2}(kk).theta=theta_samp;POSITION{2}(kk).phi=phi_samp; +POSITION{2}(kk).x=x_samp;POSITION{2}(kk).y=y_samp;POSITION{2}(kk).z=z_samp; +% -- O1s +kk=kk+1; +POSITION{2}(kk).name='O1s';POSITION{2}(kk).mode=mode_samp;POSITION{2}(kk).Ep=Ep_samp; +POSITION{2}(kk).pol=pol_samp;POSITION{2}(kk).slit=slit_samp;POSITION{2}(kk).dT=dt_samp; +POSITION{2}(kk).Eb='-535:0.02:-525'; +POSITION{2}(kk).tilt=tilt_samp;POSITION{2}(kk).theta=theta_samp;POSITION{2}(kk).phi=phi_samp; +POSITION{2}(kk).x=x_samp;POSITION{2}(kk).y=y_samp;POSITION{2}(kk).z=z_samp; +%% - PHOTON ENERGIES #3 +POSITION{3} = struct(); +% -- Survey Scan +hh=1; +POSITION{3}(hh).name='Survey';POSITION{3}(hh).mode=mode_samp;POSITION{3}(hh).Ep=Ep_samp; +POSITION{3}(hh).pol=pol_samp;POSITION{3}(hh).slit=slit_samp;POSITION{3}(hh).dT='0.1'; +POSITION{3}(hh).Eb='-555:0.2:5'; +POSITION{3}(hh).tilt=tilt_samp;POSITION{3}(hh).theta=theta_samp;POSITION{3}(hh).phi=phi_samp; +POSITION{3}(hh).x=x_samp;POSITION{3}(hh).y=y_samp;POSITION{3}(hh).z=z_samp; + +%% (E) Generate the JobFile Table +fid = fopen([FILENAME '.txt'],'wt'); +head = '/*File|Comment|hv|Pol|Slit|Mode|Epass|Eb/Ek|Range|dt(s)|Sweeps|Theta|Tilt|Azimuth|X|Y|Z*/'; fprintf(fid,'%s\n',head); +index = 1; +Energies = sort(unique(cell2mat(PHOTON_ENERGY))); +% - Filing through each one of the photon energies +for hv = Energies + % -- If necessary, acquire EF reference at the start + if use_ref == 1 + line=strcat(num2str(index, '%02.f'),'_',name_ref,'_hv=',num2str(hv),'||',num2str(hv),'|',pol_ref,'|',slit_ref,'|',mode_ref,'|',Ep_ref,'|','Eb','|',Eb_ref,'|',ADef_ref,'|',dt_ref,'|1|',theta_ref,'|',tilt_ref,'|',phi_ref,'|',x_ref,'|',y_ref,'|',z_ref,'|'); + fprintf(fid,'%s\n',line); + index=index+1; + end + % -- Filing through all the core-levels + for n = 1:length(PHOTON_ENERGY) + if ismember(hv,PHOTON_ENERGY{n}) + for kk=1:length(POSITION{n}) + line=strcat(num2str(index, '%02.f'),'_',POSITION{n}(kk).name,'_hv=',num2str(hv),'||',sprintf("ones(%i)*",REPEATS)+num2str(hv),'|',POSITION{n}(kk).pol,'|',POSITION{n}(kk).slit,'|',POSITION{n}(kk).mode,'|',POSITION{n}(kk).Ep,'|','Eb','|',POSITION{n}(kk).Eb,'|',ADef_samp,'|',POSITION{n}(kk).dT,'|1|',POSITION{n}(kk).theta,'|',POSITION{n}(kk).tilt,'|',POSITION{n}(kk).phi,'|',POSITION{n}(kk).x,'|',POSITION{n}(kk).y,'|',POSITION{n}(kk).z,'|'); + fprintf(fid,'%s\n',line); + index=index+1; + end + end + end + % -- If necessary, acquire EF reference at the end + if use_ref == 1 + line=strcat(num2str(index, '%02.f'),'_',name_ref,'_hv=',num2str(hv),'||',num2str(hv),'|',pol_ref,'|',slit_ref,'|',mode_ref,'|',Ep_ref,'|','Eb','|',Eb_ref,'|',ADef_ref,'|',dt_ref,'|1|',theta_ref,'|',tilt_ref,'|',phi_ref,'|',x_ref,'|',y_ref,'|',z_ref,'|'); + fprintf(fid,'%s\n',line); + index=index+1; + end +end +fclose(fid); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F000 - job file generators/ADRESS_JobFileGenerator_CLvsPOS.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F000 - job file generators/ADRESS_JobFileGenerator_CLvsPOS.m new file mode 100644 index 0000000..fd14293 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F000 - job file generators/ADRESS_JobFileGenerator_CLvsPOS.m @@ -0,0 +1,86 @@ +function ADRESS_JobFileGenerator_CLvsPOS() +% ADRESS_JobFileGenerator_CLvsPOS() +% This is a function that generates a text-file that is compatible to use +% in the 'Restore Tab' button on 'SmartGUI' at the ADRESS beamline. It +% allows the user to create a list of scans to be taken as a function of +% position, where each scan can be referenced to a known Fermi-edge, if +% desired. Very useful for ARPES / XPS vs z-position data-sets, to +% determine the homogeneity of a sample. +%% (A) Defining the input parameters +FILENAME = char("ADRESS_JobFile_CLvsPOS_" + string(datestr(now,'yyyymmdd_HHMMSS'))); +PHOTON_ENERGY = 578; % Photon energy of the XPS +REPEATS = 1; % Total number of repeat acquisitions (or Sweeps) for high statistics (only applies to sample measurements, not Ef) +%% (B) Set the SAMPLE measurement position +% - SAMPLE POSITION +x_samp = -0.4:0.2:0.4; % can be a single value or vector +y_samp ='-4.20'; +z_samp = -0.4:0.2:0.4; % can be a single value or vector +tilt_samp ='0.00'; +theta_samp ='-11.00'; +phi_samp ='-233.00'; +ADef_samp = '0.0'; +% - SAMPLE ACQUISITION SETTINGS +slit_samp = '1'; +dt_samp = '0.1'; +pol_samp = 'LV'; +mode_samp = 'MAM'; +Ep_samp = '100'; +%% (C) Set the Fermi-level REFERENCE position +use_ref = 1; % Set whether you want to use a reference; 1 = True, 0 = False +% - REFERENCE POSITION +x_ref = x_samp; +y_ref = y_samp; +z_ref = z_samp; +tilt_ref = tilt_samp; +theta_ref = theta_samp; +phi_ref = phi_samp; +ADef_ref = ADef_samp; +% - REFERENCE ACQUISITION SETTINGS +name_ref = 'EF'; % name_ref = 'AuEF'; % name_ref = 'Au4d'; +Eb_ref = '-2'; % Eb_ref = '-88:0.02:-80'; +slit_ref = '20'; % slit_ref = '1'; +dt_ref = '20'; % dt_ref = '0.1'; +pol_ref = pol_samp; +mode_ref = mode_samp; +Ep_ref = Ep_samp; +%% (D) Initialising the JobFile with measurement information +POSITION = struct(); +% -- aRPES / XPS info +ii=1; +POSITION(ii).name='As3d'; POSITION(ii).mode=mode_samp; POSITION(ii).Ep=Ep_samp; +POSITION(ii).pol=pol_samp; POSITION(ii).slit=slit_samp; POSITION(ii).dT=dt_samp; +POSITION(ii).Eb='-51:0.02:-39'; +POSITION(ii).tilt=tilt_samp; POSITION(ii).theta=theta_samp; POSITION(ii).phi=phi_samp; +POSITION(ii).x=x_samp; POSITION(ii).y=y_samp; POSITION(ii).z=z_samp; +%% (E) Generate the JobFile Table +fid = fopen([FILENAME '.txt'],'wt'); +head = '/*File|Comment|hv|Pol|Slit|Mode|Epass|Eb/Ek|Range|dt(s)|Sweeps|Theta|Tilt|Azimuth|X|Y|Z*/'; fprintf(fid,'%s\n',head); +index = 1; +hv = PHOTON_ENERGY; +% - Filing through each one of the photon energies +for ix = 1:length(x_samp) + for iz = 1:length(z_samp) + % -- Filing through core-levels + for kk=1:length(POSITION) + line=strcat(num2str(index, '%02.f'),'_',POSITION(kk).name,'_hv=',num2str(hv),'||',sprintf("ones(%i)*",REPEATS)+num2str(hv),'|',POSITION(kk).pol,'|',POSITION(kk).slit,'|',POSITION(kk).mode,'|',POSITION(kk).Ep,'|','Eb','|',POSITION(kk).Eb,'|',ADef_ref,'|',POSITION(kk).dT,'|1|',POSITION(kk).theta,'|',POSITION(kk).tilt,'|',POSITION(kk).phi,'|',num2str(POSITION(kk).x(ix)),'|',POSITION(kk).y,'|',num2str(POSITION(kk).z(iz)),'|'); + fprintf(fid,'%s\n',line); + index=index+1; + end + % -- If necessary, acquire EF reference + if use_ref == 1 + if length(string(x_ref)) == 1 && length(string(z_ref)) == 1 + line=strcat(num2str(index, '%02.f'),'_',name_ref,'_hv=',num2str(hv),'||',num2str(hv),'|',pol_ref,'|',slit_ref,'|',mode_ref,'|',Ep_ref,'|','Eb','|',Eb_ref,'|',ADef_ref,'|',dt_ref,'|1|',theta_ref,'|',tilt_ref,'|',phi_ref,'|',num2str(x_ref),'|',y_ref,'|',num2str(z_ref),'|'); + elseif length(string(x_ref)) > 1 && length(string(z_ref)) == 1 + line=strcat(num2str(index, '%02.f'),'_',name_ref,'_hv=',num2str(hv),'||',num2str(hv),'|',pol_ref,'|',slit_ref,'|',mode_ref,'|',Ep_ref,'|','Eb','|',Eb_ref,'|',ADef_ref,'|',dt_ref,'|1|',theta_ref,'|',tilt_ref,'|',phi_ref,'|',num2str(x_ref(ix)),'|',y_ref,'|',num2str(z_ref),'|'); + elseif length(string(x_ref)) == 1 && length(string(z_ref)) > 1 + line=strcat(num2str(index, '%02.f'),'_',name_ref,'_hv=',num2str(hv),'||',num2str(hv),'|',pol_ref,'|',slit_ref,'|',mode_ref,'|',Ep_ref,'|','Eb','|',Eb_ref,'|',ADef_ref,'|',dt_ref,'|1|',theta_ref,'|',tilt_ref,'|',phi_ref,'|',num2str(x_ref),'|',y_ref,'|',num2str(z_ref(iz)),'|'); + else + line=strcat(num2str(index, '%02.f'),'_',name_ref,'_hv=',num2str(hv),'||',num2str(hv),'|',pol_ref,'|',slit_ref,'|',mode_ref,'|',Ep_ref,'|','Eb','|',Eb_ref,'|',ADef_ref,'|',dt_ref,'|1|',theta_ref,'|',tilt_ref,'|',phi_ref,'|',num2str(x_ref(ix)),'|',y_ref,'|',num2str(z_ref(iz)),'|'); + end + fprintf(fid,'%s\n',line); + index=index+1; + end + end +end +fclose(fid); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F000 - job file generators/ADRESS_JobFileGenerator_CLvsTIME.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F000 - job file generators/ADRESS_JobFileGenerator_CLvsTIME.m new file mode 100644 index 0000000..77ad382 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F000 - job file generators/ADRESS_JobFileGenerator_CLvsTIME.m @@ -0,0 +1,92 @@ +function ADRESS_JobFileGenerator_CLvsTIME() +% ADRESS_JobFileGenerator_CLvsTIME() +% This is a function that generates a text-file that is compatible to use +% in the 'Restore Tab' button on 'SmartGUI' at the ADRESS beamline. It +% allows the user to create a list of scans to be taken as a function of +% time, where each scan can be referenced to a known Fermi-edge, if +% desired. Very useful for ARPES / XPS vs time data sets, to build high +% statistics for analysis. +%% (A) Defining the input parameters +FILENAME = char("ADRESS_JobFile_CLvsTIME_" + string(datestr(now,'yyyymmdd_HHMMSS'))); +CYCLES = 12; % Total number of periodic cycles to run +PHOTON_ENERGY = 578; % Photon energy of the XPS +REPEATS = 1; % Total number of repeat acquisitions (or Sweeps) for high statistics (only applies to sample measurements, not Ef) +%% (B) Set the SAMPLE measurement position +% - SAMPLE POSITION +x_samp ='-3.60'; +y_samp ='-4.20'; +z_samp ='5.098'; +tilt_samp ='0.00'; +theta_samp ='-11.00'; +phi_samp ='-233.00'; +ADef_samp = '0.0'; +% - SAMPLE ACQUISITION SETTINGS +slit_samp = '1'; +dt_samp = '0.1'; +pol_samp = 'LV'; +mode_samp = 'MAM'; +Ep_samp = '100'; +%% (C) Set the Fermi-level REFERENCE position +use_ref = 1; % Set whether you want to use a reference; 1 = True, 0 = False +% - REFERENCE POSITION +x_ref = x_samp; +y_ref = y_samp; +z_ref = z_samp; +tilt_ref = tilt_samp; +theta_ref = theta_samp; +phi_ref = phi_samp; +ADef_ref = ADef_samp; +% - REFERENCE ACQUISITION SETTINGS +name_ref = 'EF'; % name_ref = 'AuEF'; % name_ref = 'Au4d'; +Eb_ref = '-2'; % Eb_ref = '-88:0.02:-80'; +slit_ref = '20'; % slit_ref = '1'; +dt_ref = '20'; % dt_ref = '0.1'; +pol_ref = pol_samp; +mode_ref = mode_samp; +Ep_ref = Ep_samp; +%% (D) Initialising the JobFile with the first entries +POSITION = struct(); +% - Regular Energy Jobs to be Cycled +% -- In4d +ii=1; +POSITION(ii).name='In4d'; POSITION(ii).mode=mode_samp; POSITION(ii).Ep=Ep_samp; +POSITION(ii).pol=pol_samp; POSITION(ii).slit=slit_samp; POSITION(ii).dT=dt_samp; +POSITION(ii).Eb='-26:0.02:-15'; +POSITION(ii).tilt=tilt_samp; POSITION(ii).theta=theta_samp; POSITION(ii).phi=phi_samp; +POSITION(ii).x=x_samp; POSITION(ii).y=y_samp; POSITION(ii).z=z_samp; +% -- As3d +ii=ii+1; +POSITION(ii).name='As3d'; POSITION(ii).mode=mode_samp; POSITION(ii).Ep=Ep_samp; +POSITION(ii).pol=pol_samp; POSITION(ii).slit=slit_samp; POSITION(ii).dT=dt_samp; +POSITION(ii).Eb='-51:0.02:-39'; +POSITION(ii).tilt=tilt_samp; POSITION(ii).theta=theta_samp; POSITION(ii).phi=phi_samp; +POSITION(ii).x=x_samp; POSITION(ii).y=y_samp; POSITION(ii).z=z_samp; +% -- In3d +ii=ii+1; +POSITION(ii).name='In3d';POSITION(ii).mode=mode_samp;POSITION(ii).Ep=Ep_samp; +POSITION(ii).pol=pol_samp;POSITION(ii).slit=slit_samp;POSITION(ii).dT=dt_samp; +POSITION(ii).Eb='-457:0.02:-450'; +POSITION(ii).tilt=tilt_samp;POSITION(ii).theta=theta_samp;POSITION(ii).phi=phi_samp; +POSITION(ii).x=x_samp;POSITION(ii).y=y_samp;POSITION(ii).z=z_samp; +%% (E) Generate the JobFile Table +fid = fopen([FILENAME '.txt'],'wt'); +head = '/*File|Comment|hv|Pol|Slit|Mode|Epass|Eb/Ek|Range|dt(s)|Sweeps|Theta|Tilt|Azimuth|X|Y|Z*/'; fprintf(fid,'%s\n',head); +index = 1; +Energies = PHOTON_ENERGY .* ones(1,CYCLES); +% - Filing through each one of the photon energies +for hv = Energies + % -- If necessary, acquire EF reference first + if use_ref == 1 + line=strcat(num2str(index, '%02.f'),'_',name_ref,'_hv=',num2str(hv),'||',num2str(hv),'|',pol_ref,'|',slit_ref,'|',mode_ref,'|',Ep_ref,'|','Eb','|',Eb_ref,'|',ADef_ref,'|',dt_ref,'|1|',theta_ref,'|',tilt_ref,'|',phi_ref,'|',x_ref,'|',y_ref,'|',z_ref,'|'); + fprintf(fid,'%s\n',line); + index=index+1; + end + % -- Filing through core-levels + for kk=1:length(POSITION) + line=strcat(num2str(index, '%02.f'),'_',POSITION(kk).name,'_hv=',num2str(hv),'||',sprintf("ones(%i)*",REPEATS)+num2str(hv),'|',POSITION(kk).pol,'|',POSITION(kk).slit,'|',POSITION(kk).mode,'|',POSITION(kk).Ep,'|','Eb','|',POSITION(kk).Eb,'|',ADef_ref,'|',POSITION(kk).dT,'|1|',POSITION(kk).theta,'|',POSITION(kk).tilt,'|',POSITION(kk).phi,'|',POSITION(kk).x,'|',POSITION(kk).y,'|',POSITION(kk).z,'|'); + fprintf(fid,'%s\n',line); + index=index+1; + end +end +fclose(fid); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/bzone_props.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/bzone_props.m new file mode 100644 index 0000000..4a442e5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/bzone_props.m @@ -0,0 +1,38 @@ +function bzone_props(bzOverlay, bz_args) +% bzone_props(bzOverlay, bz_args) +% Function that will plot the BZ overlay once it has been determined via +% the 'extract_lattice()' and 'extract_bz_overlay()' functions. Allows +% the user to choose some properties of the BZ plots too. This function +% allows for a constant, global formatting for Brilluoin Zone & +% Overlay properties within the PESTools package. +% +% REQ. FUNCTIONS: none +% +% IN: +% - bzOverlay: data structure that contains all the BZ data. +% - bz_args: {1×3} cell of {bz_offset, bz_col, bz_lwidth} +% bz_offset: [1×2] vector of the x- and y-origin of the BZ ([xShift, yShift]) +% bz_col: [1×3] vector of the line color of the Brillouin zone overlayer +% bz_lwidth: single, scalar of the linewidth thickness +% +% OUT: (none) plot of the BZ overlay + +%% Default parameters +if nargin < 2; bz_args = cell(1,3); end +if isempty(bz_args); bz_args = cell(1,3); end +%% - 1 - Initialising the BZ overlay parameters +% - Extracting the BZ values +bz_offset = bz_args{1}; if isempty(bz_offset); bz_offset = [0 0]; end +bz_col = bz_args{2}; if isempty(bz_col); bz_col = [1 1 1]; end +bz_lwidth = bz_args{3}; if isempty(bz_lwidth); bz_lwidth = 1.5; end +% - Extracting the initial axis limits +xl = xlim; yl = ylim; +%% - 2 - Plotting the BZ overlay +for ii = 1:size(bzOverlay.X, 2) + plot(bzOverlay.X{ii} - bz_offset(1), bzOverlay.Y{ii} - bz_offset(2), 'w-', 'color', bz_col, 'linewidth', bz_lwidth); +end +xticks(round(-20*bzOverlay.gX:bzOverlay.gX/2:20*bzOverlay.gX,2)); +yticks(round(-20*bzOverlay.gY:bzOverlay.gY/2:20*bzOverlay.gY,2)); +% - Pinning axes limits to original values +axis([xl(1), xl(2), yl(1), yl(2)]); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/colbar_props.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/colbar_props.m new file mode 100644 index 0000000..fbece96 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/colbar_props.m @@ -0,0 +1,42 @@ +function colbar_props(cbar_pos, cbar_tickside) +% colbar_props(cbar_pos, cbar_tickside) +% This function outlines the consistent parameters to be used for the +% colorbar settings. The user can control the position and side of the +% tick marks, otherwise, the settings below are used for all figures +% plotted with the PESTools package. This allow for a constant, global +% formatting for colorbar properties. +% +% REQ. FUNCTIONS: none +% +% IN: +% - cbar_pos: [1×4] vector of colorbar position in normalised units [left, bottom, width, height] +% - cbar_tickside: char of either 'left' or 'right' for the y-axis ticks +% +% OUT: (none) + +%% Default parameters +if nargin < 1; cbar_pos = [0.925 0.125 0.025 0.175]; cbar_tickside='right'; end +if nargin < 2; cbar_tickside = 'right'; end +if isempty(cbar_pos); cbar_pos = [0.925 0.125 0.025 0.175]; end +if isempty(cbar_tickside); cbar_tickside='right'; end +%% 1 - Defining the colorbar +cb = colorbar; +% Colorbar font properties +cb.FontName = 'Helvetica'; +cb.FontSize = 9; +% Colorbar tick properties +cb.TickLabelInterpreter = 'latex'; +cb.TickLength = 0.04; +cb.TickDirection = 'both'; +cb.YAxisLocation = cbar_tickside; +% Colorbar position properties +cb.Position = cbar_pos; +% Colorbar box properties +cb.Color = [0 0 0]; +cb.Box = 'on'; +cb.LineWidth = 1.0; +if cb.Limits(1) < 0 || cb.Limits(1) == 0 + cb.Ticks = sort([0.98*cb.Limits(1), 0.5*(cb.Limits(2)), 0.98*cb.Limits(2)]); +else; cb.Ticks = sort([1.02*cb.Limits(1), 0.5*(cb.Limits(2)), 0.98*cb.Limits(2)]); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/gca_props.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/gca_props.m new file mode 100644 index 0000000..83c8df0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/gca_props.m @@ -0,0 +1,47 @@ +function gca_props(plot_axes_lines) +% gca_props(plot_axes_lines) +% This function outlines a constant, global formatting for axes properties +% and parameters for all figures plotted with the PESTools package. +% +% REQ. FUNCTIONS: none +% +% IN: +% - plot_axes_lines: if 1, will plot the x- and y-axes as black, dashed lines. +% +% OUT: (none) + +%% Default parameters +if nargin < 1; plot_axes_lines = 1; end +if isempty(plot_axes_lines); plot_axes_lines = 1; end +%% 1 - Defining the axes properties +ax = gca; +% Font properties +ax.FontName = 'Helvetica'; +ax.FontWeight = 'normal'; +ax.FontSize = 12; +% Tick properties +ax.TickLabelInterpreter = 'latex'; +ax.XMinorTick = 'off'; +ax.YMinorTick = 'off'; +ax.TickDir = 'in'; +ax.TickLength = [0.015 0.025]; +ax.XColor = [0 0 0]; +ax.YColor = [0 0 0]; +% Ruler properties +ax.XAxisLocation = 'bottom'; % 'bottom' | 'top' | 'origin' +ax.YAxisLocation = 'left'; % 'left' | 'right' | 'origin' +% Box Styling properties +ax.LineWidth = 1.0; +ax.Box = 'on'; +ax.Layer = 'Top'; +%% 2 - Plotting the x- and y-axes +xl = xlim; yl = ylim; +axis([xl(1), xl(2), yl(1), yl(2)]); +% -- If true, plot axes lines and remove them from the legend +if plot_axes_lines == 1 + a = line([0 0], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + b = line([-1e5, 1e5], [0 0], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + a.Annotation.LegendInformation.IconDisplayStyle = 'off'; + b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/img_props.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/img_props.m new file mode 100644 index 0000000..a675c97 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/img_props.m @@ -0,0 +1,71 @@ +function img_props(colmap, type, plot_axes_lines) +% img_props(colmap, type) +% This function outlines the consistent axes and figure +% parameters to be used for 2D images. Each field can be edited to what +% the user desires. Specific inputs are used to isolate the +% different types of figures that are plotted. This allows for a constant +% global formatting for 2D ARPES images within the PESTools package. +% +% REQ. FUNCTIONS: none +% +% IN: +% - colmap: char of either: hot, parula, jet, gray, bone, hsv, cool, spring, +% summer, autumn, winter, copper, pink, lines, colorcube, +% prism, flag . +% - type: string of either "theta" or "kx" for the x-axis label +% +% OUT: (none) + +%% Default parameters +if nargin < 1; colmap = 'hot'; type = "kx"; end +if nargin < 2; type = "kx"; end +if nargin < 3; plot_axes_lines = 1; end +if isempty(colmap); colmap = 'hot'; end +if isempty(type); type = "kx"; end +if isempty(plot_axes_lines); plot_axes_lines = 1; end +%% 1 - Defining the axes properties +ax = gca; +% Font properties +ax.FontName = 'Helvetica'; +ax.FontWeight = 'normal'; +ax.FontSize = 12; +% Tick properties +ax.TickLabelInterpreter = 'latex'; +ax.XMinorTick = 'off'; +ax.YMinorTick = 'off'; +ax.TickDir = 'in'; +ax.TickLength = [0.01 0.025]; +ax.XColor = [0 0 0]; +ax.YColor = [0 0 0]; +% Ruler properties +ax.XAxisLocation = 'bottom'; % 'bottom' | 'top' | 'origin' +ax.YAxisLocation = 'left'; % 'left' | 'right' | 'origin' +% Box Styling properties +ax.Color = [0, 0, 0]; +ax.LineWidth = 1.2; +ax.Box = 'on'; +ax.Layer = 'Top'; +% Axis labels and limits +if type == "raw_tht" || type == "tht" + xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); +elseif type == "kx" + xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); +end +ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +%% 2 - Defining the figure properties +% fig = gcf; +% fig.Color = [1 1 1]; +% fig.InvertHardcopy = 'off'; +%% 3 - Colorbar properties +colormap(colmap); +%% 4 - Plotting the x- and y-axes +xl = xlim; yl = ylim; +axis([xl(1), xl(2), yl(1), yl(2)]); +% -- If true, plot axes lines and remove them from the legend +if plot_axes_lines == 1 + a = line([0 0], [-1e5, 1e5], 'Color', [1 1 1 0.5], 'LineWidth', 1., 'Linestyle', ':'); + b = line([-1e5, 1e5], [0 0], 'Color', [1 1 1 0.5], 'LineWidth', 1., 'Linestyle', ':'); + a.Annotation.LegendInformation.IconDisplayStyle = 'off'; + b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/loglog_props.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/loglog_props.m new file mode 100644 index 0000000..5420e34 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/loglog_props.m @@ -0,0 +1,41 @@ +function loglog_props() +% loglog_props() +% This function outlines a constant, global formatting for axes properties +% and parameters for all figures plotted with the PESTools package. These +% properties ensure that a log-log plot is made, with consistant +% properties as 'gca_props()'. +% +% REQ. FUNCTIONS: none +% +% IN: (none) +% +% OUT: (none) + +%% 1 - Defining the axes properties +ax = gca; +% Font properties +ax.FontName = 'Helvetica'; +ax.FontWeight = 'normal'; +ax.FontSize = 12; +% Tick properties +ax.TickLabelInterpreter = 'latex'; +ax.XMinorTick = 'off'; +ax.YMinorTick = 'off'; +ax.TickDir = 'in'; +ax.TickLength = [0.02 0.025]; +ax.XColor = [0 0 0]; +ax.YColor = [0 0 0]; +% Ruler properties +ax.XAxisLocation = 'bottom'; % 'bottom' | 'top' | 'origin' +ax.YAxisLocation = 'left'; % 'left' | 'right' | 'origin' +% Box Styling properties +ax.LineWidth = 1.0; +ax.Box = 'on'; +ax.Layer = 'Top'; +% Making it a log-log plot +ax.XScale = 'log'; +ax.YScale = 'log'; +%% 2 - Plotting the x- and y-axes +xl = xlim; yl = ylim; +axis([xl(1), xl(2), yl(1), yl(2)]); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/plot_props.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/plot_props.m new file mode 100644 index 0000000..ab5e41f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/plot_props.m @@ -0,0 +1,97 @@ +function pp = plot_props() +% pp = plot_props() +% This function outlines the consistent colors, markers and lines to be +% used when plotting the figures associated with all the state fitting +% analysis. Whenever a figure is plotted using the PESTools package, you +% will most likely see this function being called. +% +% REQ. FUNCTIONS: none +% +% IN: (none) +% +% OUT: +% - pp: MATLAB structure that contains all of the figure and plot properties. + +% - Initialising plot property structure +pp = struct(); + +%% FIGURE SIZE PROPERTIES +pp.fontsize = 12; +% -- LANDSCAPE FIGURE SIZE +pp.fig3x2 = [600, 400]; +pp.fig4x3 = [800, 600]; +pp.fig4x5 = [400, 500]; % best size in my opinion for portrait +pp.fig16x9 = [640, 360]; +pp.fig16x10 = [1280, 800]; +pp.fig16x15 = [1280, 1200]; +% -- PORTRAIT FIGURE SIZE +pp.fig2x3 = [400, 600]; +pp.fig3x4 = [600, 800]; +pp.fig5x4 = [500, 400]; % best size in my opinion for landscape +pp.fig9x16 = [360, 640]; +pp.fig10x16 = [800, 1280]; +pp.fig15x16 = [1200, 1280]; +pp.fig13x12 = [600, 650]; +% -- SQUARE FIGURE SIZE +pp.fig4x4 = [400 400]; +pp.fig6x6 = [600 600]; +pp.fig8x8 = [800 800]; +pp.fig10x10 = [1000 1000]; +% -- FIGURE POSITION +pp.figpos = [100 100]; + +%% GENERAL PROPERTIES +pp.lwidth = 1.0; +pp.llwidth = 2.0; +pp.msize = 9.0; +pp.mmsize = 12.0; +pp.falpha = 0.50; +pp.ffalpha = 0.80; +pp.csize = 3.0; +pp.ccsize = 6.0; +pp.bzlwidth = 2.0; +pp.clims = [0, 1]; + +%% DEFINING THE COLORS SCHEME +% - FIT COMPONENT COLORS +pp.col.dat = {... + [0.9, 0.1, 0.1],... %% RED FOR EXPERIMENTAL DATA + [0, 0, 0]... %% BLACK FOR BEST FIT + }; +% -- CUT COMPONENT COLOURS +pp.col.cut = {... + [0.0, 0.0, 0.0],... %% BLACK (FDD) + [0.2, 0.6, 0.2],... %% GREEN (EDC) + [0.2, 0.2, 0.8],... %% BLUE (MDC) + [0.1, 0.1, 0.6],... %% BLUE (ROI) + }; +% - FIT COMPONENT COLORS +pp.col.fit = num2cell([0.25,0.25,0.25;lines(20)], 2); + +%% DEFINING THE MARKER STYLES +% -- CUT COMPONENT COLOURS +pp.mstyle.cut = {... + 'x',... % (FDD) + 's',... % (EDC) + '^',... % (MDC) + 'x',... % (ROI) + }; +% -- FIT COMPONENT COLOURS +pp.mstyle.fits = {... + 'x',... % (n = 1) + '+',... % (n = 2) + 'o',... % (n = 3) + '^',... % (n = 4) + '.',... % (n = 5) + 's',... % (n = 6) + 'p',... % (n = 7) + }; + +%% MISCELLANEOUS PLOT PROPERTIES +% -- High-symmtry ticks for lattice vectors in silicon +pp.si_ebkticks = {... + sort(-116:1.16:116),... % GX + sort(-116:0.5*1.16:116),... % XW + sort([-5*1.64:1.64:5*1.64, 0.41, -0.41]),... % GKX + }; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/xline_n.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/xline_n.m new file mode 100644 index 0000000..87713a1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/xline_n.m @@ -0,0 +1,27 @@ +function xline_n(values, line_style) +% xline_n(values, line_style) +% This function plots single (or multiple) vertical lines that cross the +% x-axis at the defined 'values'. The user can also choose the line style +% of the lines. +% +% REQ. FUNCTIONS: none +% +% IN: +% - values: 1 x N vector that contains all the x-values. +% - line_style: char of the line style to be used for the plot. +% +% OUT: (none) + +%% Default parameters +if nargin < 1; values = []; line_style = '-'; end +if nargin < 2; line_style = '-'; end +if isempty(values); values = []; end +if isempty(line_style); line_style = '-'; end + +%% 1 - Plotting the vertical lines at the x-values +axis_value = axis; +hold on; +for ii = 1:length(values) + plot([values(ii), values(ii)], axis_value(3:4), line_style); +end +hold off \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/yline_n.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/yline_n.m new file mode 100644 index 0000000..8391919 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F001 - general plot properties/yline_n.m @@ -0,0 +1,27 @@ +function yline_n(values,line_style) +% yline_n(values,line_style) +% This function plots single (or multiple) horizontal lines that cross the +% y-axis at the defined 'values'. The user can also choose the line style +% of the lines. +% +% REQ. FUNCTIONS: none +% +% IN: +% - values: 1 x N vector that contains all the y-values. +% - line_style: char of the line style to be used for the plot. +% +% OUT: (none) + +%% Default parameters +if nargin < 1; values = []; line_style = '-'; end +if nargin < 2; line_style = '-'; end +if isempty(values); values = []; end +if isempty(line_style); line_style = '-'; end + +%% 1 - Plotting the horizontal lines at the y-values +axis_value = axis; +hold on; +for ii = 1:length(values) + plot(axis_value(1:2), [values(ii),values(ii)], line_style); +end +hold off \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/extract_bz_overlay.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/extract_bz_overlay.m new file mode 100644 index 0000000..cb3c714 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/extract_bz_overlay.m @@ -0,0 +1,251 @@ +function bzOverlay = extract_bz_overlay(reciStr, crystal_plane, plot_results) +% bzOverlay = extract_bz_overlay(reciStr, crystal_plane, plot_results) +% This is a function that extracts the planar Brilluoin zone +% along the defined crystal plane (h,k,l) in miller indices notation. +% This Brilluoin zone plane then represents the planar slice that +% that is probed through via ARPES by changing the scan parameter. +% +% IN: +% - reciStr: MATLAB data structure containing reciprocal-space data from 'extract_lattice()' +% - crystal_plane: string of the crystal plane to extract in "(hkl)" format. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - bzOverlay MATLAB data structure containing all BZ plane information below; +% .(crystal): string of the crystal type. +% .(crystal_plane): string of the (h,k,l) plane extracted. +% .(area): area of the planar BZ unit cell. +% .(X): cell array of the x vertices of the planar BZ cell slice. +% .(Y): cell array of the y vertices of the planar BZ cell slice. +% .(gX): double of the reciprocal-tesselation vector in x. +% .(gY): double of the reciprocal-tesselation vector in y. + +%% Default parameters +if nargin < 2; crystal_plane = "001"; plot_results = 0; end +if nargin < 3; plot_results = 0; end +if isempty(crystal_plane); crystal_plane = "(001)"; end +if isempty(plot_results); plot_results = 0; end +disp('-> Extracting plane slice of BZ...') +wbar = waitbar(0, 'Extracting BZ overlay...', 'Name', 'extract_bz_overlay'); + +%% Initialising the input variables +crystal = reciStr.crystal; +G1 = reciStr.G1; +G2 = reciStr.G2; +G3 = reciStr.G3; +Gbz = reciStr.Gbz; +%% 1 - Extracting the First Brilluoin Zone boundary +% - Extracting the point cloud for the First Brilluoin Zone +x_pts = cell2mat(Gbz(:,1)); +y_pts = cell2mat(Gbz(:,2)); +z_pts = cell2mat(Gbz(:,3)); +cloud_pts = [x_pts, y_pts, z_pts]; +% - Projecting the point cloud onto the desired planar slice +% --- For the (100) plane +if crystal_plane == "(100)" + proj_vec = [0,1,1]; + proj_pts = cloud_pts .* proj_vec; + xpts1 = proj_pts(:,2); + ypts1 = proj_pts(:,3); +% --- For the (010) plane +elseif crystal_plane == "(010)" + proj_vec = [1,0,1]; + proj_pts = cloud_pts .* proj_vec; + xpts1 = proj_pts(:,1); + ypts1 = proj_pts(:,3); +% --- For the (001) plane +elseif crystal_plane == "(001)" + proj_vec = [1,1,0]; + proj_pts = cloud_pts .* proj_vec; + xpts1 = proj_pts(:,1); + ypts1 = proj_pts(:,2); +% --- For the (110) plane +elseif crystal_plane == "(110)" + proj_vec = [1,0,1]; + R = [cosd(45) -sind(45) 0; sind(45) cosd(45) 0; 0 0 1]; + cloud_pts = cloud_pts * R; + proj_pts = cloud_pts .* proj_vec; + xpts1 = proj_pts(:,1); + ypts1 = proj_pts(:,3); +end +% - Shifting the boundary points to the origin +xpts1 = xpts1 - (max(xpts1(:))+min(xpts1(:)))/2; +ypts1 = ypts1 - (max(ypts1(:))+min(ypts1(:)))/2; + +%% 2 - Creating the boundary Brilluoin Zone polygon and finding the area of a single zone +[b_indx, area] = boundary(xpts1, ypts1, 0.1); +xpts1 = xpts1(b_indx); +ypts1 = ypts1(b_indx); + +%% 3 - Tessalating the polygons to get the overlay +l=1; +% Iterating over all (or most of!) reciprocal space +for i = -6:6 + for j = -10:35 + % -- For the (100) plane + if crystal_plane == "(100)" + % -- Applying the tessalated shifts + X{l} = xpts1 + i*G2(2) + j*G3(2); + Y{l} = ypts1 + i*G2(3) + j*G3(3); + % -- For the (010) plane + elseif crystal_plane == "(010)" + % -- Applying the tessalated shifts + X{l} = xpts1 + i*G1(1) + j*G3(1); + Y{l} = ypts1 + i*G1(3) + j*G3(3); + % -- For the (001) plane + elseif crystal_plane == "(001)" + % -- Applying the tessalated shifts + X{l} = xpts1 + i*G1(1) + j*G2(1); + Y{l} = ypts1 + i*G1(2) + j*G2(2); + % -- For the (110) plane + elseif crystal_plane == "(110)" + % --- Extracting the shift vectors + xshift = norm(0.5*G1 + 0.5*G2); + yshift = norm(0.5*G3); + % -- Applying the tessalated shifts + if mod(i,2) == 1 + X{l} = xpts1 + i*xshift; + Y{l} = ypts1 + yshift + j*2*max(yshift); + else + X{l} = xpts1 + i*xshift; + Y{l} = ypts1 + j*2*max(yshift); + end + end + l = l + 1; + end +end +%% Assigning the overlay structure to a MATLAB structure +waitbar(1, wbar, 'Assigning the BZ overlay variables...', 'Name', 'extract_lattice'); +% - Real-space information +bzOverlay.crystal = crystal; +bzOverlay.crystal_plane = crystal_plane; +bzOverlay.area = area; +bzOverlay.X = X; +bzOverlay.Y = Y; +if crystal_plane == "(100)" + bzOverlay.gX = norm(G2); + bzOverlay.gY = norm(G3); +elseif crystal_plane == "(010)" + bzOverlay.gX = norm(G1); + bzOverlay.gY = norm(G3); +elseif crystal_plane == "(001)" + bzOverlay.gX = norm(G1); + bzOverlay.gY = norm(G2); +elseif crystal_plane == "(110)" + bzOverlay.gX = norm(G1 + G2); + bzOverlay.gY = norm(G3); +end +%% Close wait-bar +close(wbar); +%% Figure summary of the real- and reciprocal-space structures +if plot_results == 1 + + fig = figure(); set(fig, 'position', [1,1,950,650]); + + %% - RECIPROCAL-SPACE FIGURE + subplot(1,2,1); hold on; + % -- Plotting the axes lines + line([min(reciStr.G(:,1)), max(reciStr.G(:,1))], [0 0], [0,0], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + line([0 0], [min(reciStr.G(:,2)), max(reciStr.G(:,2))], [0, 0], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + line([0 0], [0, 0], [min(reciStr.G(:,3)), max(reciStr.G(:,3))], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + % -- Plotting the translational real-space lattice vectors + plot3([0,reciStr.G1(1)],[0,reciStr.G1(2)],[0,reciStr.G1(3)], '-', 'linewidth', 3, 'color', [0.3, 0.8, 0.3]); + plot3([0,reciStr.G2(1)],[0,reciStr.G2(2)],[0,reciStr.G2(3)], '-', 'linewidth', 3, 'color', [0.3, 0.8, 0.3]); + plot3([0,reciStr.G3(1)],[0,reciStr.G3(2)],[0,reciStr.G3(3)], '-', 'linewidth', 3, 'color', [0.3, 0.8, 0.3]); + % -- Plotting the multiple translations of the real-space vectors + plot3(reciStr.G(:,1),reciStr.G(:,2),reciStr.G(:,3),'b.','markersize',20); + % -- Plotting all the nearest neighbour points + for i = 1:2:size(reciStr.Gnn,1) + plot3([reciStr.Gnn(i,1), reciStr.Gnn(i+1,1)], [reciStr.Gnn(i,2), reciStr.Gnn(i+1,2)], [reciStr.Gnn(i,3), reciStr.Gnn(i+1,3)], 'k-', 'linewidth', 1); + end + % -- Plotting the first Brilluoin Zone + for i = 1:size(reciStr.Gbz,1) + patch(reciStr.Gbz{i,1}, reciStr.Gbz{i,2}, reciStr.Gbz{i,3},[0.3 0.8 0.3], 'FaceAlpha',0.75, 'EdgeColor', 'none'); + end + % -- Plotting a path of the brilluoin zone slice + xP = [-1e3, 1e3, 1e3, -1e3, -1e3]; + yP = [1e3, 1e3, -1e3, -1e3, 1e3]; + zP = [0, 0, 0, 0, 0]; + if crystal_plane == "(100)" + patch(zP, xP, yP, [0.7, 0.7, 0.7], 'FaceAlpha',0.75, 'EdgeColor', 'none'); + elseif crystal_plane == "(010)" + patch(xP, zP+reciStr.G2(2), yP, [0.7, 0.7, 0.7], 'FaceAlpha',0.75, 'EdgeColor', 'none'); + elseif crystal_plane == "(001)" + patch(xP, yP, zP, [0.7, 0.7, 0.7], 'FaceAlpha',0.75, 'EdgeColor', 'none'); + elseif crystal_plane == "(110)" + xP = [1e3, 1e3, -1e3, -1e3, 1e3]; + yP = [1e3, 1e3, -1e3, -1e3, 1e3]+reciStr.G2(2); + zP = [-1e3, 1e3, 1e3, -1e3, -1e3]; + patch(xP, yP, zP, [0.7, 0.7, 0.7], 'FaceAlpha',0.75, 'EdgeColor', 'none'); + end + % -- Defining the axes properties + % - Figure formatting + ax = gca; + % Font properties + ax.FontName = 'Helvetica'; ax.FontSize = 14; + % Tick properties + ax.TickLabelInterpreter = 'latex'; + ax.TickDir = 'both'; + % Box Styling properties + ax.LineWidth = 1.2; + % Axis labels, limits and ticks + xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + zlabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + xticks(round(-10*norm(G1):norm(G1):10*norm(G1),2)); + yticks(round(-10*norm(G2):norm(G2):10*norm(G2),2)); + zticks(round(-10*norm(G3):norm(G3):10*norm(G3),2)); + % -- Modify the view + view(3); camlight(-30,24); + title_txt2 = sprintf("%s; Reciprocal; Brilluoin Zone", crystal); + title(title_txt2); + axis tight equal; rotate3d on; + pbaspect([1,1,1]); + axis(reciStr.Glims); + + %% - BRILLUOIN ZONE PLANAR SLICE + subplot(1,2,2); hold on; + for i = 1:size(X, 2) + plot(X{i}, Y{i}, 'k-','linewidth', 2); + end + % -- Defining the axes properties + % - Figure formatting + ax = gca; + % Font properties + ax.FontName = 'Helvetica'; ax.FontSize = 14; + % Tick properties + ax.TickLabelInterpreter = 'latex'; + ax.TickDir = 'both'; + % Box Styling properties + ax.LineWidth = 1.2; + % Axis labels, limits and ticks + title_txt = sprintf("%s; BZNavi through %s", bzOverlay.crystal, bzOverlay.crystal_plane); + title(title_txt); + xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + xticks(round(-100*norm(bzOverlay.gX):0.5*norm(bzOverlay.gX):100*norm(bzOverlay.gX),2)); + yticks(round(-100*norm(bzOverlay.gY):0.5*norm(bzOverlay.gY):100*norm(bzOverlay.gY),2)); + axis(1.5*[-norm(bzOverlay.gX), norm(bzOverlay.gX), -norm(bzOverlay.gY),norm(bzOverlay.gY)]); + axis equal; + % Axis labels, limits and ticks + title_txt = sprintf("BZ plane; %s", crystal_plane); + title(title_txt); + axis equal; + if crystal_plane == "(100)" + xlabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + elseif crystal_plane == "(010)" + xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + elseif crystal_plane == "(001)" + xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + elseif crystal_plane == "(110)" + xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + end + xticks(round(-10*bzOverlay.gX:0.5*bzOverlay.gX:10*bzOverlay.gX,2)); + yticks(round(-10*bzOverlay.gY:0.5*bzOverlay.gY:10*bzOverlay.gY,2)); + axis([-bzOverlay.gX, bzOverlay.gX, -bzOverlay.gY, bzOverlay.gY]*1.05); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/extract_hv_overlay.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/extract_hv_overlay.m new file mode 100644 index 0000000..70375ce --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/extract_hv_overlay.m @@ -0,0 +1,163 @@ +function hvOverlay = extract_hv_overlay(hv, navi_args, bzOverlay, plot_results) +% hvOverlay = extract_hv_overlay(hv, navi_args, bzOverlay, plot_results) +% This is a function that extracts the crystallographic vectors +% of a general crystal structure in both real- and reciprocal- +% space based on the inputs. All 14 Bravais lattices can be +% defined, including primitive-, base-, face- and body-centered +% lattices. The outputs are two MATLAB structures that contain +% all of the real- and reciprocal-space data. +% +% IN: +% - hv: single or 1x2 vector of [minHv, maxHv] for the user defined photon energy. +% - navi_args: MATLAB data structure containing all of the navigation arguments below; +% .(ePhi): Work function of analyser +% .(alpha): Angle between analyser and sample normal (July 2022: 20deg, from August 2022: 9deg). +% .(thtM): Primary manipulator rotation +% .(eBref): Binding energy reference +% .(thtAref): Analyser angle to sample normal in geometry is at origin +% .(kxref): kx reference is at origin +% .(tltM): Primary tilt rotation is set to origin +% .(V000): User defined inner potential. +% - bzOverlay: MATLAB data structure containing all BZ plane information from 'extract_bz_overlay()'; +% .(crystal): string of the crystal type. +% .(crystal_plane): string of the (h,k,l) plane extracted. +% .(area): area of the planar BZ unit cell. +% .(X): cell array of the x vertices of the planar BZ cell slice. +% .(Y): cell array of the y vertices of the planar BZ cell slice. +% .(gX): double of the reciprocal-tesselation vector in x. +% .(gY): double of the reciprocal-tesselation vector in y. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. + +%% Default parameters +navi_default_args.ePhi = 4.5; +navi_default_args.alpha = 9.0; % present geometry 9deg; Old geometry 20deg; +navi_default_args.thtM = 0; +navi_default_args.eBref = 0; +navi_default_args.thtAref = 0; +navi_default_args.kxref = 0; +navi_default_args.tltM = 0; +navi_default_args.V000 = 12.57; +if nargin < 2; navi_args = navi_default_args; bzOverlay = []; plot_results = 1; end +if nargin < 3; bzOverlay = []; plot_results = 1; end +if nargin < 4; plot_results = 1; end +if isempty(hv); hv = [350, 1500]; end +if isempty(navi_args); navi_args = navi_default_args; end +if isempty(plot_results); plot_results = 1; end +disp('-> Extracting k-space ARPES scan line...') + +%% 1.1 - Extracting the wave-vector path in k-space for the ARPES scan +tht = linspace(-12, 12, 5e2); +if length(hv) == 1 + surfNormX = SurfNormX(hv, navi_args.eBref, navi_args.kxref, navi_args.thtM, navi_args.thtAref, navi_args.alpha); + kx = Kxx(hv, navi_args.eBref, navi_args.thtM, tht, surfNormX, navi_args.alpha); + kz = Kzz(hv, navi_args.eBref, navi_args.thtM, tht, navi_args.tltM, navi_args.V000, surfNormX, navi_args.alpha); +elseif length(hv) == 2 + hv = sort(hv); hv = [hv(1), hv(end)]; + surfNormX(1,:) = SurfNormX(hv(1), navi_args.eBref, navi_args.kxref, navi_args.thtM, navi_args.thtAref, navi_args.alpha); + kx(1,:) = Kxx(hv(1), navi_args.eBref, navi_args.thtM, tht, surfNormX(1,:), navi_args.alpha); + kz(1,:) = Kzz(hv(1), navi_args.eBref, navi_args.thtM, tht, navi_args.tltM, navi_args.V000, surfNormX(1,:), navi_args.alpha); + surfNormX(2,:) = SurfNormX(hv(2), navi_args.eBref, navi_args.kxref, navi_args.thtM, navi_args.thtAref, navi_args.alpha); + kx(2,:) = Kxx(hv(2), navi_args.eBref, navi_args.thtM, tht, surfNormX(2,:), navi_args.alpha); + kz(2,:) = Kzz(hv(2), navi_args.eBref, navi_args.thtM, tht, navi_args.tltM, navi_args.V000, surfNormX(2,:), navi_args.alpha); +elseif length(hv) > 2 + for i = 1:length(hv) + surfNormX(i,:) = SurfNormX(hv(i), navi_args.eBref, navi_args.kxref, navi_args.thtM, navi_args.thtAref, navi_args.alpha); + kx(i,:) = Kxx(hv(i), navi_args.eBref, navi_args.thtM, tht, surfNormX(i,:), navi_args.alpha); + kz(i,:) = Kzz(hv(i), navi_args.eBref, navi_args.thtM, tht, navi_args.tltM, navi_args.V000, surfNormX(i,:), navi_args.alpha); + end +end +%% 1.2 - Extracting the kz-broadening +eKE = hv - navi_args.ePhi + navi_args.eBref; +imfp = 10 .* (143 ./ eKE .^2 + 0.054.*sqrt(eKE)); +dkz = 1 ./ imfp; + +%% 2 - Updating the figure with the photon energy path +if plot_results == 1 + %% 2.1 - Plotting the BZ planar slice + if ~ishandle(360579) + figX = figure(360579); + figX.Name = 'BZ Navigation'; + hold on; + % --- Formatting the figure + ax = gca; ax.TickLabelInterpreter = 'latex'; ax.TickDir = 'both'; + title('extract_hv_overlay()', 'Interpreter', 'none'); + xlabel('$$ \bf k_x\ (\AA^{-1}) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf k_{\perp}\ (\AA^{-1}) $$', 'Interpreter', 'latex'); + line([0, 0], [-1e5, 1e5], 'color', 'c', 'linestyle', '-'); + % --- Plotting the BZ overlay + if ~isempty(bzOverlay) + for i = 1:size(bzOverlay.X, 2) + plot(bzOverlay.X{i}, bzOverlay.Y{i}, 'k-','linewidth', 2); + end + xticks(round(-1e3*norm(bzOverlay.gX):0.5*norm(bzOverlay.gX):1e3*norm(bzOverlay.gX),2)); + yticks(round(-1e3*norm(bzOverlay.gY):0.5*norm(bzOverlay.gY):1e3*norm(bzOverlay.gY),2)); + title_txt = sprintf("%s - %s", bzOverlay.crystal, bzOverlay.crystal_plane); + title(title_txt); + end + else + figure(360579); + end + + %% 2.2 - Plotting the k-space patches probed with ARPES + col = rand(1,3); + % - For a single photon energy + if length(hv) == 1 + % -- Extract the planar limits of the ARPES scan + kx_lower = (kx); kz_lower = (kz - dkz)'; + kx_upper = (kx); kz_upper = (kz + dkz)'; + % -- Plotting the ARPES scan plane which includes the Kz broadening + patch([kx_upper, fliplr(kx_lower)], [kz_upper, fliplr(kz_lower)], col, 'edgecolor', 'none', 'facealpha', 0.5); + % -- Plotting the ARPES scan line + plot(kx, kz, '-', 'linewidth', 2, 'color', col); + % -- Adding text + text(max(kx(:)), min(kz_lower(:)), sprintf("%.0f eV", hv),... + 'color', col, 'Fontsize', 12, 'horizontalalignment', 'left', 'FontWeight','bold'); + % - For a range of photon energies + elseif length(hv) == 2 + % -- Extract the planar limits of the ARPES scan + kx_lower = (kx(1,:)); kz_lower = (kz(1,:) - dkz(1)); + kx_upper = (kx(2,:)); kz_upper = (kz(2,:) + dkz(2)); + % -- Plotting the ARPES scan plane which includes the Kz broadening + patch([kx_upper, fliplr(kx_lower)], [kz_upper, fliplr(kz_lower)], col, 'edgecolor', 'none', 'facealpha', 0.5); + % -- Plotting the ARPES scan line + plot(kx(1,:), kz(1,:), '-', 'linewidth', 2, 'color', col); + plot(kx(2,:), kz(2,:), '-', 'linewidth', 2, 'color', col); + % -- Adding text + text(max(kx(1,:)), min(kz_lower(:)), sprintf("%.0f eV", hv(1)),... + 'color', col, 'Fontsize', 12, 'horizontalalignment', 'left', 'FontWeight','bold'); + text(max(kx(2,:)), max(kz_upper(:)), sprintf("%.0f eV", hv(2)),... + 'color', col, 'Fontsize', 12, 'horizontalalignment', 'left', 'FontWeight','bold'); + % - For an array of photon energies + elseif length(hv) > 3 + kx_lower = {}; kx_upper = {}; + kz_lower = {}; kz_upper = {}; + for i = 1:length(hv) + col = rand(1,3); + % -- Extract the planar limits of the ARPES scan + kx_lower{i} = (kx(i,:))'; kz_lower{i} = (kz(i,:) - dkz(i))'; + kx_upper{i} = (kx(i,:))'; kz_upper{i} = (kz(i,:) + dkz(i))'; + % -- Plotting the ARPES scan line + plot(kx(i,:), kz(i,:), '-', 'linewidth', 2, 'color', col); + % -- Adding text + text(max(kx(i,:)), min(kz_lower{i}(:)), sprintf("%.0f eV", hv(i)),... + 'color', col, 'Fontsize', 12, 'horizontalalignment', 'left', 'FontWeight','bold'); + end + kx_lower = cell2mat(kx_lower); kx_upper = cell2mat(kx_upper); + kz_lower = cell2mat(kz_lower); kz_upper = cell2mat(kz_upper); + end + % - Adding the axes limits + axis equal; grid on; + xlim([min(kx_upper(:)), max(kx_upper(:))]*1.05); + ylim([0.95*min(kz_lower(:)), 1.05*max(kz_upper(:))]); +end +%% 4.0 - Assigning the data structure +hvOverlay = struct(); +hvOverlay.navi_args = navi_args; +hvOverlay.bzOverlay = bzOverlay; +hvOverlay.imfp = imfp; +hvOverlay.dkz = dkz; +hvOverlay.kx = kx; +hvOverlay.kz = kz; +% hvOverlay.kx_lower = kx_lower; +% hvOverlay.kx_upper = kx_upper; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/extract_lattice.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/extract_lattice.m new file mode 100644 index 0000000..554866d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/extract_lattice.m @@ -0,0 +1,463 @@ +function [realStr, reciStr] = extract_lattice(crystal_args, plot_results) +% [realStr, reciStr] = extract_lattice(crystal_args, plot_results) +% This is a function that extracts the crystallographic vectors +% of a general crystal structure in both real- and reciprocal- +% space based on the inputs. All 14 Bravais lattices can be +% defined, including primitive-, base-, face- and body-centered +% lattices. The outputs are two MATLAB structures that contain +% all of the real- and reciprocal-space data. +% +% IN: +% - crystal_args: 1x3 cell of {crystal, (a, b, c), (alpha, beta, gamma)} described below; +% -- crystalType; "CUB-cP-Oh", "CUB-cI-Oh", "CUB-cF-Oh", +% "HEX-hP-D6h", "RHL-hR-D3d", +% "TET-tP-D4h", "TET-tI-D4h", +% "ORC-oP-D2h", "ORC-oS-D2h", "ORC-oI-D2h", "ORC-oF-D2h", +% "MCL-mP-C2h", "MCL-mS-C2h", +% "TRI-aP-Ci" . +% -- (a, b, c); 1x3 row-vector of the side lengths of the crystal systems unit cell (Angstroms). +% -- (alpha, beta, gamma); 1x3 row vector the opposite angles of the crystal systems unit cell (degrees). +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - realStr: MATLAB data structure containing all real-space information below. +% .(crystal): string of the crystal type. +% .(T1): a1 primitive translation vector. +% .(T2): a2 primitive translation vector. +% .(T3): a3 primitive translation vector. +% .(Tb0): atomic basis vectors. +% .(Tvol): volume of the real-space unit cell. +% .(T): atomic positions over multiple primitive-translations to show crystal structure. +% .(Tlims): axes limits in 3D for the lattice structure T. +% .(Tnn): linked lines between nearest neighbour atomsdisplayed in .(T). +% .(Tws): Wigner-Seitz cell in real-space. +% - reciStr: MATLAB data structure containing all reciprocal-space information below. +% .(crystal): string of the crystal type. +% .(G1): b1 primitive reciprocal vector. +% .(G2): b2 primitive reciprocal vector. +% .(G3): b3 primitive reciprocal vector. +% .(Gb0): atomic basis vectors in reciprocal space. +% .(Gvol): volume of the reciprocal-space unit cell. +% .(G): reciprocal lattice over multiple translations. +% .(Glims): axes limits in 3D for the lattice structure G. +% .(Gnn): linked lines between nearest neighbour reciprocal-points displayed in .(G). +% .(Gbz): First Brilluoin zone in reciprocal-space. + +%% Default parameters +if nargin < 1; crystal_args = {"CUB-cF-Oh", [5.431, 5.431, 5.431], [90, 90, 90]}; plot_results = 0; end +if nargin < 2; plot_results = 0; end +if isempty(crystal_args); crystal_args = {"CUB-cF-Oh", [5.431, 5.431, 5.431], [90, 90, 90]}; end +if isempty(plot_results); plot_results = 0; end +disp('-> Extracting 3D BZ...') +wbar = waitbar(0, 'Extracting crystallographic variables...', 'Name', 'extract_lattice'); + +%% Initialising the input variables +crystal = crystal_args{1}; +a = crystal_args{2}(1); +b = crystal_args{2}(2); +c = crystal_args{2}(3); +alpha = crystal_args{3}(1) * pi/180; +beta = crystal_args{3}(2) * pi/180; +gamma = crystal_args{3}(3) * pi/180; + +%% 1 - Defining the real-space unit cell from a general triclinic geometry +% -- Extracting the triclinic coefficients for real-space unit vectors +w1 = cos(alpha) - cos(beta) * cos(gamma)/(sin(beta) * sin(gamma)); +w2 = sin(gamma)^2 - cos(beta)^2 - cos(alpha)^2 + 2*cos(alpha) *cos(beta) * cos(gamma); +w2 = sqrt(w2) / (sin(beta) * sin(gamma)); +% -- Defining the real-space unit vectors +T1 = [a, 0, 0]; +T2 = [b * cos(gamma), b * sin(gamma), 0]; +T3 = [c * cos(beta), c * w1*sin(beta), c*w2*sin(beta)]; +% -- Extracting the volume of the real-space unit cell +Tvol = cross(T1, T2)*T3'; +%% 2 - Defining the basis of the Bravais Lattice out of the 14 possible choices +% - 2.1 - The 7 Primitive (Simple) Bravais lattices +if crystal == "CUB-cP-Oh" || crystal == "HEX-hP-D6h" || crystal == "RHL-hR-D3d" ||... + crystal == "TET-tP-D4h" || crystal == "ORC-oP-D2h" || crystal == "MCL-mP-C2h" ||... + crystal == "TRI-aP-Ci" + Tb0 = [0, 0, 0]; +% - 2.2 - The 2 Base-Centered Bravais Lattices +elseif crystal == "ORC-oS-D2h" || crystal == "MCL-mS-C2h" + Tb0 = [0, 0, 0;... + 0.5*(T1+T2)]; +% - 2.3 - The 3 Body-Centered Bravais Lattices +elseif crystal == "CUB-cI-Oh" || crystal == "TET-tI-D4h" || crystal == "ORC-oI-D2h" + Tb0 = [0, 0, 0;... + 0.5*(T1+T2+T3)]; +% - 2.4 - The 2 Face-Centered Bravais Lattices +elseif crystal == "CUB-cF-Oh" || crystal == "ORC-oF-D2h" + Tb0 = [0, 0, 0;... + 0.5*(T1+T2);... + 0.5*(T1+T3);... + 0.5*(T2+T3)]; +end +%% 3 - Extracting the real-space lattice over multiple translations of T +l=1; +for i=-1:1 + for j=0:2 + for k=-1:1 + for n = 1:size(Tb0,1) + T(l,:)=i*T1+j*T2+k*T3+Tb0(n,:); + l=l+1; + end + end + end +end +% - 3.1 - Finding the axes limited for a 2x2 super structure as in T +if crystal == "CUB-cP-Oh" || crystal == "HEX-hP-D6h" || crystal == "RHL-hR-D3d" ||... + crystal == "TET-tP-D4h" || crystal == "ORC-oP-D2h" || crystal == "MCL-mP-C2h" ||... + crystal == "TRI-aP-Ci" + Tlims = 1.04*[min(T(:,1)), max(T(:,1)), min(T(:,2)), max(T(:,2)), min(T(:,3)), max(T(:,3))]; +elseif crystal == "ORC-oS-D2h" || crystal == "MCL-mS-C2h" || crystal == "CUB-cI-Oh" ||... + crystal == "TET-tI-D4h" || crystal == "ORC-oI-D2h" || crystal == "CUB-cF-Oh" ||... + crystal == "ORC-oF-D2h" + Tlims = 1.04*[-1*norm(T1), norm(T1), 0, 2*norm(T2),-1*norm(T3), norm(T3)]; +end +%% 4 - Finding all vector paths to link all nearest neighbour points +Tnn = []; +% - Filing through all possible points given in the T-matrix +for i = 1:length(T)-1 + waitbar(i/length(T)-1, wbar, 'Extracting real-space lattice...', 'Name', 'extract_lattice'); + for j = i+1:length(T) + % -- Finding the Euclidean distance between the two lattice points + dist = sqrt((T(i,1)-T(j,1)).^2+(T(i,2)-T(j,2)).^2+(T(i,3)-T(j,3)).^2); + %% 4.1 - Applying geometrical constraints for nearest neighbour points + + % --- For the 7 Primitive (Simple) Bravais lattices + % Points are linked if their distance is identical to the + % length of T1, T2 or T3. + if crystal_args{1} == "CUB-cP-Oh" || crystal_args{1} == "HEX-hP-D6h" || crystal_args{1} == "RHL-hR-D3d" ||... + crystal_args{1} == "TET-tP-D4h" || crystal_args{1} == "ORC-oP-D2h" || crystal_args{1} == "MCL-mP-C2h" ||... + crystal_args{1} == "TRI-aP-Ci" + if (abs(dist-norm(T1))) <= 0.0001 || (abs(dist-norm(T2))) <= 0.0001 || (abs(dist-norm(T3))) <= 0.0001 + Tnn = vertcat(Tnn, [[T(i,1);T(j,1)], [T(i,2);T(j,2)], [T(i,3);T(j,3)]]); + end + + % --- For the 2 Base-Centered Bravais Lattices + % Points are linked if their distance is equal to the length + % of the BCC basis vector. Also, if their length is equal to + % T1, T2 or T3, with the condition that it is not divisible by + % the BCC basis vector (as the base-centered points are only + % joined within the horizontal plane of the vertices). + elseif crystal_args{1} == "ORC-oS-D2h" || crystal_args{1} == "MCL-mS-C2h" + if abs(dist-norm(Tb0(2,:))) <= 0.0001 + Tnn = vertcat(Tnn, [[T(i,1);T(j,1)], [T(i,2);T(j,2)], [T(i,3);T(j,3)]]); + elseif (mod(T(i,2), 2*Tb0(2,2)) == 0 || abs(T(i,2)) <= 0.0001 ) && ((abs(dist-norm(T1))) <= 0.0001 || (abs(dist-norm(T2))) <= 0.0001 || (abs(dist-norm(T3))) <= 0.0001) + Tnn = vertcat(Tnn, [[T(i,1);T(j,1)], [T(i,2);T(j,2)], [T(i,3);T(j,3)]]); + end + + % --- For the 3 Body-Centered Bravais Lattices + % Points are linked if their distance is equal to the length + % of the BCC basis vector. Also, if their length is equal to + % T1, T2 or T3, with the condition that it is not divisible by + % the BCC basis vector (as the body-centered points are only + % joined radially outwards to vertices of unit cell). + elseif crystal_args{1} == "CUB-cI-Oh" || crystal_args{1} == "TET-tI-D4h" || crystal_args{1} == "ORC-oI-D2h" + if abs(dist-norm(Tb0(2,:))) <= 0.0001 + Tnn = vertcat(Tnn, [[T(i,1);T(j,1)], [T(i,2);T(j,2)], [T(i,3);T(j,3)]]); + elseif mod(T(i,3), 2*Tb0(2,3)) == 0 && ((abs(dist-norm(T1))) <= 0.0001 || (abs(dist-norm(T2))) <= 0.0001 || (abs(dist-norm(T3))) <= 0.0001) + Tnn = vertcat(Tnn, [[T(i,1);T(j,1)], [T(i,2);T(j,2)], [T(i,3);T(j,3)]]); + end + + % --- For the 2 Face-Centered Bravais Lattices + % Points are linked if their distance is equal to the length + % of the FCC basis vector, with the proviso that the two points + % are coplanar and not an FCC point. This is applied along each + % dimension. Furthermore, if their length is equal to T1, T2 or T3, + % with the condition that it is not divisible by the FCC basis vector + % (as the face-centered points are only joined radially outwards to + % vertices of unit cell, not to other FCC points). + elseif crystal_args{1} == "CUB-cF-Oh" || crystal_args{1} == "ORC-oF-D2h" + if abs(dist-norm(Tb0(2,:))) <= 0.001 && abs(T(i,1)-T(j,1)) <= 0.001 && (abs(T(i,1)) <= 0.001 || mod(T(i,1), 2*Tb0(2,1)) == 0) + Tnn = vertcat(Tnn, [[T(i,1);T(j,1)], [T(i,2);T(j,2)], [T(i,3);T(j,3)]]); + elseif abs(dist-norm(Tb0(2,:))) <= 0.001 && abs(T(i,2)-T(j,2)) <= 0.001 && (abs(T(i,2)) <= 0.001 || mod(T(i,2), 2*Tb0(2,2)) == 0) + Tnn = vertcat(Tnn, [[T(i,1);T(j,1)], [T(i,2);T(j,2)], [T(i,3);T(j,3)]]); + elseif abs(dist-norm(Tb0(3,:))) <= 0.001 && abs(T(i,3)-T(j,3)) <= 0.001 && (abs(T(i,3)) <= 0.001 || mod(T(i,3), 2*Tb0(3,3)) == 0) + Tnn = vertcat(Tnn, [[T(i,1);T(j,1)], [T(i,2);T(j,2)], [T(i,3);T(j,3)]]); + elseif (abs(dist-norm(T1))) <= 0.0001 && abs(T(i,1)-T(j,1)) <= 0.001 && (abs(T(i,1)) <= 0.001 || mod(T(i,1), 2*Tb0(2,1)) == 0) && (abs(T(i,3)) <= 0.001 || mod(T(i,3), 2*Tb0(3,3)) == 0) + Tnn = vertcat(Tnn, [[T(i,1);T(j,1)], [T(i,2);T(j,2)], [T(i,3);T(j,3)]]); + elseif (abs(dist-norm(T2))) <= 0.0001 && abs(T(i,2)-T(j,2)) <= 0.001 && (abs(T(i,2)) <= 0.001 || mod(T(i,2), 2*Tb0(2,2)) == 0) && (abs(T(i,3)) <= 0.001 || mod(T(i,3), 2*Tb0(3,3)) == 0) + Tnn = vertcat(Tnn, [[T(i,1);T(j,1)], [T(i,2);T(j,2)], [T(i,3);T(j,3)]]); + end + + end + end +end +%% 5 - Computing the Voronoi diagram, which is identical to the Wigner-Seitz cell +% - Calculating Voronoi diagram +[T_c, T_v] = voronoin(T); +T_nx = T_c(T_v{floor(l/2)},:); +T_cell = convhulln(T_nx); +% - Defining the T_ws variable and shifting Wigner-Seitz cell to +T2 +for i = 1:size(T_cell,1) + Tws{i,1} = T_nx(T_cell(i,:),1)-T(floor(l/2),1)+T2(1); + Tws{i,2} = T_nx(T_cell(i,:),2)-T(floor(l/2),2)+T2(2); + Tws{i,3} = T_nx(T_cell(i,:),3)-T(floor(l/2),3)+T2(3); +end + + +%% A - Defining the reciprocal-space unit cell +% - A.1 - For simple and base-centered lattices, use T-vectors only +if crystal_args{1} == "CUB-cP-Oh" || crystal_args{1} == "HEX-hP-D6h" || crystal_args{1} == "RHL-hR-D3d" ||... + crystal_args{1} == "TET-tP-D4h" || crystal_args{1} == "ORC-oP-D2h" || crystal_args{1} == "MCL-mP-C2h" ||... + crystal_args{1} == "TRI-aP-Ci" || crystal_args{1} == "ORC-oS-D2h" || crystal_args{1} == "MCL-mS-C2h" + G1 = 2*pi*cross(T2,T3)/Tvol; + G2 = 2*pi*cross(T3,T1)/Tvol; + G3 = 2*pi*cross(T1,T2)/Tvol; +% - A.2 - For body- and face-centered lattices, scale by a factor of 2 +elseif crystal_args{1} == "CUB-cI-Oh" || crystal_args{1} == "TET-tI-D4h" || crystal_args{1} == "ORC-oI-D2h" ||... + crystal_args{1} == "CUB-cF-Oh" || crystal_args{1} == "ORC-oF-D2h" + G1 = 4*pi*cross(T2,T3)/Tvol; + G2 = 4*pi*cross(T3,T1)/Tvol; + G3 = 4*pi*cross(T1,T2)/Tvol; +end +% -- Extracting the volume of reciprocal unit cell +Gvol = cross(G1,G2)*G3'; +%% B - Extracting the corresponding Brilluoin Zone in reciprocal-space +% - B.1 - The 7 Primitive (Simple) Bravais lattices yield no basis +if crystal_args{1} == "CUB-cP-Oh" || crystal_args{1} == "HEX-hP-D6h" || crystal_args{1} == "RHL-hR-D3d" ||... + crystal_args{1} == "TET-tP-D4h" || crystal_args{1} == "ORC-oP-D2h" || crystal_args{1} == "MCL-mP-C2h" ||... + crystal_args{1} == "TRI-aP-Ci" + Gb0 = [0, 0, 0]; +% - B.2 - The 2 Base-Centered Bravais Lattices turn into base-centered in reciprocal space +elseif crystal_args{1} == "ORC-oS-D2h" || crystal_args{1} == "MCL-mS-C2h" + Gb0 = [0, 0, 0;... + 0.5*(G1+G2)]; +% - B.3 - The 3 Body-Centered Bravais Lattice turns to FCC in reciprocal space +elseif crystal_args{1} == "CUB-cI-Oh" || crystal_args{1} == "TET-tI-D4h" || crystal_args{1} == "ORC-oI-D2h" + Gb0 = [0, 0, 0;... + 0.5*(G1+G2);... + 0.5*(G1+G3);... + 0.5*(G2+G3)]; +% - B.4 - The 2 Face-Centered Bravais Lattices turns to BCC in reciprocal space +elseif crystal_args{1} == "CUB-cF-Oh" || crystal_args{1} == "ORC-oF-D2h" + Gb0 = [0, 0, 0;... + 0.5*(G1+G2+G3)]; +end +%% C - Extracting the reciprocal-space lattice over multiple translations of G +l=1; +for i=-1:1 + for j=0:2 + for k=-1:1 + for n = 1:size(Gb0,1) + G(l,:)=i*G1+j*G2+k*G3+Gb0(n,:); + l=l+1; + end + end + end +end +% - C.1 - Finding the axes limited for a 2x2 super structure as in G +if crystal == "CUB-cP-Oh" || crystal == "HEX-hP-D6h" || crystal == "RHL-hR-D3d" ||... + crystal == "TET-tP-D4h" || crystal == "ORC-oP-D2h" || crystal == "MCL-mP-C2h" ||... + crystal == "TRI-aP-Ci" + Glims = 1.04*[min(G(:,1)), max(G(:,1)), min(G(:,2)), max(G(:,2)), min(G(:,3)), max(G(:,3))]; +elseif crystal == "ORC-oS-D2h" || crystal == "MCL-mS-C2h" || crystal == "CUB-cI-Oh" ||... + crystal == "TET-tI-D4h" || crystal == "ORC-oI-D2h" || crystal == "CUB-cF-Oh" ||... + crystal == "ORC-oF-D2h" + Glims = 1.04*[-1*norm(G1), norm(G1), 0, 2*norm(G2),-1*norm(G3), norm(G3)]; +end + +%% D - Finding all vector paths to link all nearest neighbour points +Gnn = []; +% - Filing through all possible points given in the G-matrix +for i = 1:length(G)-1 + waitbar(i/length(G)-1, wbar, 'Extracting reciprocal-space lattice...', 'Name', 'extract_lattice'); + for j = i+1:length(G) + % -- Finding the Euclidean distance between the two lattice points + dist = sqrt((G(i,1)-G(j,1)).^2+(G(i,2)-G(j,2)).^2+(G(i,3)-G(j,3)).^2); + %% 4.1 - Applying geometrical constraints for nearest neighbour points + + % --- For the 7 Primitive (Simple) Reciprocal lattices + % Points are linked if their distance is identical to the + % length of G1, G2 or G3. + if crystal_args{1} == "CUB-cP-Oh" || crystal_args{1} == "HEX-hP-D6h" || crystal_args{1} == "RHL-hR-D3d" ||... + crystal_args{1} == "TET-tP-D4h" || crystal_args{1} == "ORC-oP-D2h" || crystal_args{1} == "MCL-mP-C2h" ||... + crystal_args{1} == "TRI-aP-Ci" + if (abs(dist-norm(G1))) <= 0.0001 || (abs(dist-norm(G2))) <= 0.0001 || (abs(dist-norm(G3))) <= 0.0001 + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + end + + % --- For the 2 Base-Centered Reciprocal Lattices + % Points are linked if their distance is equal to the length + % of the BCC basis vector. Also, if their length is equal to + % G1, G2 or G3, with the condition that it is not divisible by + % the BCC basis vector (as the base-centered points are only + % joined within the horizontal plane of the vertices). + elseif crystal_args{1} == "ORC-oS-D2h" || crystal_args{1} == "MCL-mS-C2h" + if abs(dist-norm(Gb0(2,:))) <= 0.0001 + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + elseif (mod(G(i,2), 2*Gb0(2,2)) == 0 || abs(G(i,2)) <= 0.0001 ) && ((abs(dist-norm(G1))) <= 0.0001 || (abs(dist-norm(G2))) <= 0.0001 || (abs(dist-norm(G3))) <= 0.0001) + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + end + + % --- For the 2 Body-Centered Reciprocal Lattices + % Points are linked if their distance is equal to the length + % of the BCC basis vector. Also, if their length is equal to + % G1, G2 or G3, with the condition that it is not divisible by + % the BCC basis vector (as the body-centered points are only + % joined radially outwards to vertices of unit cell). + elseif crystal_args{1} == "CUB-cF-Oh" || crystal_args{1} == "ORC-oF-D2h" + if abs(dist-norm(Gb0(2,:))) <= 0.0001 + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + elseif (mod(G(i,3), 2*Gb0(2,3)) == 0 || abs(G(i,3)) <= 0.001) && ((abs(dist-norm(G1))) <= 0.0001 || (abs(dist-norm(G2))) <= 0.0001 || (abs(dist-norm(G3))) <= 0.0001) + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + elseif (mod(G(i,2), 2*Gb0(2,2)) == 0 || abs(G(i,2)) <= 0.001) && ((abs(dist-norm(G1))) <= 0.0001 || (abs(dist-norm(G2))) <= 0.0001 || (abs(dist-norm(G3))) <= 0.0001) + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + end + + % --- For the 3 Face-Centered Reciprocal Lattices + % Points are linked if their distance is equal to the length + % of the FCC basis vector, with the proviso that the two points + % are coplanar and not an FCC point. This is applied along each + % dimension. Furthermore, if their length is equal to G1, G2 or G3, + % with the condition that it is not divisible by the FCC basis vector + % (as the face-centered points are only joined radially outwards to + % vertices of unit cell, not to other FCC points). + elseif crystal_args{1} == "CUB-cI-Oh" || crystal_args{1} == "TET-tI-D4h" || crystal_args{1} == "ORC-oI-D2h" + if abs(dist-norm(Gb0(2,:))) <= 0.001 && abs(G(i,1)-G(j,1)) <= 0.001 && (abs(G(i,1)) <= 0.001 || mod(G(i,1), 2*Gb0(2,1)) == 0) + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + elseif abs(dist-norm(Gb0(2,:))) <= 0.001 && abs(G(i,2)-G(j,2)) <= 0.001 && (abs(G(i,2)) <= 0.001 || mod(G(i,2), 2*Gb0(2,2)) == 0) + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + elseif abs(dist-norm(Gb0(3,:))) <= 0.001 && abs(G(i,3)-G(j,3)) <= 0.001 && (abs(G(i,3)) <= 0.001 || mod(G(i,3), 2*Gb0(3,3)) == 0) + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + elseif (abs(dist-norm(G1))) <= 0.0001 && abs(G(i,1)-G(j,1)) <= 0.001 && (abs(G(i,1)) <= 0.001 || mod(G(i,1), 2*Gb0(2,1)) == 0) && (abs(G(i,3)) <= 0.001 || mod(G(i,3), 2*Gb0(3,3)) == 0) + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + elseif (abs(dist-norm(G2))) <= 0.0001 && abs(G(i,2)-G(j,2)) <= 0.001 && (abs(G(i,2)) <= 0.001 || mod(G(i,2), 2*Gb0(2,2)) == 0) && (abs(G(i,3)) <= 0.001 || mod(G(i,3), 2*Gb0(3,3)) == 0) + Gnn = vertcat(Gnn, [[G(i,1);G(j,1)], [G(i,2);G(j,2)], [G(i,3);G(j,3)]]); + end + end + end +end +%% E - Computing the Voronoi diagram, which is identical to the First Brilluoin Zone +% - Calculating Voronoi diagram +[G_c, G_v] = voronoin(G); +G_nx = G_c(G_v{floor(l/2)},:); +G_cell = convhulln(G_nx); +% - Defining the G_bz variable and shifting Brilluoin zone to +G2 +for i = 1:size(G_cell,1) + Gbz{i,1} = G_nx(G_cell(i,:),1)-G(floor(l/2),1)+G2(1); + Gbz{i,2} = G_nx(G_cell(i,:),2)-G(floor(l/2),2)+G2(2); + Gbz{i,3} = G_nx(G_cell(i,:),3)-G(floor(l/2),3)+G2(3); +end + +%% Assigning the real- and reciprocal-information to MATLAB data structure +waitbar(1, wbar, 'Assigning real- and reciprocal-variables...', 'Name', 'extract_lattice'); +% - Real-space information +realStr.crystal = crystal; +realStr.T1 = T1; +realStr.T2 = T2; +realStr.T3 = T3; +realStr.Tb0 = Tb0; +realStr.Tvol = Tvol; +realStr.T = T; +realStr.Tlims = Tlims; +realStr.Tnn = Tnn; +realStr.Tws = Tws; +% - Reciprocal-space information +reciStr.crystal = crystal; +reciStr.G1 = G1; +reciStr.G2 = G2; +reciStr.G3 = G3; +reciStr.Gb0 = Gb0; +reciStr.Gvol = Gvol; +reciStr.G = G; +reciStr.Glims = Glims; +reciStr.Gnn = Gnn; +reciStr.Gbz = Gbz; +%% Close wait-bar +close(wbar); + +%% Figure summary of the real- and reciprocal-space structures +if plot_results == 1 + fig = figure(); set(fig, 'position', [1,1,950,650]); + + % - REAL-SPACE FIGURE + subplot(1,2,1); hold on; + % -- Plotting the axes lines + line([min(T(:,1)), max(T(:,1))], [0 0], [0,0], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + line([0 0], [min(T(:,2)), max(T(:,2))], [0, 0], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + line([0 0], [0, 0], [min(T(:,3)), max(T(:,3))], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + % -- Plotting the translational real-space lattice vectors + plot3([0,T1(1)],[0,T1(2)],[0,T1(3)], '-', 'linewidth', 3, 'color', [0.8, 0.3, 0.3]); + plot3([0,T2(1)],[0,T2(2)],[0,T2(3)], '-', 'linewidth', 3, 'color', [0.8, 0.3, 0.3]); + plot3([0,T3(1)],[0,T3(2)],[0,T3(3)], '-', 'linewidth', 3, 'color', [0.8, 0.3, 0.3]); + % -- Plotting the multiple translations of the real-space vectors + plot3(T(:,1),T(:,2),T(:,3),'b.','markersize',20); + % -- Plotting all the nearest neighbour points + for i = 1:2:size(Tnn,1) + plot3([Tnn(i,1), Tnn(i+1,1)], [Tnn(i,2), Tnn(i+1,2)], [Tnn(i,3), Tnn(i+1,3)], 'k-', 'linewidth', 1); + end + % -- Plotting the Wigner-Seitz cell + for i = 1:size(Tws,1) + patch(Tws{i,1}, Tws{i,2}, Tws{i,3},[0.8 0.3 0.3], 'FaceAlpha',0.75, 'EdgeColor', 'none'); + end + % - Figure formatting + ax = gca; + % Font properties + ax.FontName = 'Helvetica'; ax.FontSize = 14; + % Tick properties + ax.TickLabelInterpreter = 'latex'; + ax.TickDir = 'both'; + % Box Styling properties + ax.LineWidth = 1.2; + % Axis labels, limits and ticks + xlabel('$$ \bf x (\AA) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf y (\AA) $$', 'Interpreter', 'latex'); + zlabel('$$ \bf z (\AA) $$', 'Interpreter', 'latex'); + xticks(round(-10*norm(T1):norm(T1):10*norm(T1),2)); + yticks(round(-10*norm(T2):norm(T2):10*norm(T2),2)); + zticks(round(-10*norm(T3):norm(T3):10*norm(T3),2)); + % -- Modify the view + view(3); camlight(-30,24); + title_txt1 = sprintf("%s; Real; Wigner-Seitz", crystal); + title(title_txt1); + axis tight equal vis3d; rotate3d on; + pbaspect([1,1,1]); + axis(Tlims); + + % - RECIPROCAL-SPACE FIGURE + subplot(1,2,2); hold on; + % -- Plotting the axes lines + line([min(G(:,1)), max(G(:,1))], [0 0], [0,0], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + line([0 0], [min(G(:,2)), max(G(:,2))], [0, 0], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + line([0 0], [0, 0], [min(G(:,3)), max(G(:,3))], 'Color', [0 0 0], 'LineWidth', 0.75, 'Linestyle', '--'); + % -- Plotting the translational real-space lattice vectors + plot3([0,G1(1)],[0,G1(2)],[0,G1(3)], '-', 'linewidth', 3, 'color', [0.3, 0.8, 0.3]); + plot3([0,G2(1)],[0,G2(2)],[0,G2(3)], '-', 'linewidth', 3, 'color', [0.3, 0.8, 0.3]); + plot3([0,G3(1)],[0,G3(2)],[0,G3(3)], '-', 'linewidth', 3, 'color', [0.3, 0.8, 0.3]); + % -- Plotting the multiple translations of the real-space vectors + plot3(G(:,1),G(:,2),G(:,3),'b.','markersize',20); + % -- Plotting all the nearest neighbour points + for i = 1:2:size(Gnn,1) + plot3([Gnn(i,1), Gnn(i+1,1)], [Gnn(i,2), Gnn(i+1,2)], [Gnn(i,3), Gnn(i+1,3)], 'k-', 'linewidth', 1); + end + % -- Plotting the first Brilluoin Zone + for i = 1:size(Gbz,1) + patch(Gbz{i,1}, Gbz{i,2}, Gbz{i,3},[0.3 0.8 0.3], 'FaceAlpha',0.75, 'EdgeColor', 'none'); + end + % - Figure formatting + ax = gca; + % Font properties + ax.FontName = 'Helvetica'; ax.FontSize = 14; + % Tick properties + ax.TickLabelInterpreter = 'latex'; + ax.TickDir = 'both'; + % Box Styling properties + ax.LineWidth = 1.2; + % Axis labels, limits and ticks + xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + zlabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + xticks(round(-10*norm(G1):norm(G1):10*norm(G1),2)); + yticks(round(-10*norm(G2):norm(G2):10*norm(G2),2)); + zticks(round(-10*norm(G3):norm(G3):10*norm(G3),2)); + % -- Modify the view + view(3); camlight(-30,24); + title_txt2 = sprintf("%s; Reciprocal; Brilluoin Zone", crystal); + title(title_txt2); + axis tight equal vis3d; rotate3d on; + pbaspect([1,1,1]); + axis(Glims); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_GeCBValleys_3D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_GeCBValleys_3D.m new file mode 100644 index 0000000..fbb5eb3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_GeCBValleys_3D.m @@ -0,0 +1,69 @@ +function [] = plot_GeCBValleys_3D(eb_cut, origin, cb_shifts) +% [] = plot_SiCBValleys_3D(eb_cut, origin, cb_shifts) +% This function plots the iso-energetic surfaces of elliptical valleys +% for Silicon. This is 6 elliptical valleys, 85% along the Gamma-X high +% symmetry line. +% +% IN: +% - eb_cut: scalar of the energy above the CBM to slice for the iso-surface [eV]. +% - origin: 1x3 row vector of the origin location of the Gama point [x,y,z]. +% - cb_shifts: 1x3 row vector of the relative energy shift of each valley [eb_x, eb_y, eb_z]. +% +% OUT: (figure) + +%% Defining the default parameters +if nargin < 1; eb_cut = 0.2; origin = [0, 0, 0]; cb_shifts = [0, 0, 0]; end +if nargin < 2; origin = [0, 0, 0]; cb_shifts = [0, 0, 0]; end +if nargin < 3; cb_shifts = [0, 0, 0]; end +if isempty(eb_cut); eb_cut = 0.2; end +if isempty(origin); origin = [0, 0, 0]; end +if isempty(cb_shifts); cb_shifts = [0, 0, 0]; end + +%% 1.0 - Defining the constant parameters +x_ebshift = cb_shifts(1); y_ebshift = cb_shifts(2); z_ebshift = cb_shifts(3); +m0 = 9.11e-31; +hbar = 4.135e-15; +ml = 1.64*m0; +mt = 0.082*m0; +%% 1.1 - Defining the dispersions of the CB parabola's +k_calc = @(eb, eff_mass, eb_shift) sqrt(((2*eff_mass)/(hbar^2)) * (eb - eb_shift)); +%% 1.2 - Extracting the CB ellipsoids +k0 = sqrt(3)*pi/(5.657); % Defining the position of the CBM in k-space +% -- IsoE for x valleys +[X1_xx, X1_yy, X1_zz] = ellipsoid(k0 +origin(1), 0+origin(2), 0+origin(3), k_calc(eb_cut,ml,x_ebshift),k_calc(eb_cut,mt,x_ebshift),k_calc(eb_cut,mt,x_ebshift), 5e2); +[X2_xx, X2_yy, X2_zz] = ellipsoid(-k0+origin(1), 0+origin(2), 0+origin(3), k_calc(eb_cut,ml,x_ebshift),k_calc(eb_cut,mt,x_ebshift),k_calc(eb_cut,mt,x_ebshift), 5e2); +[X3_xx, X3_yy, X3_zz] = ellipsoid(origin(1), k0+origin(2), 0+origin(3), k_calc(eb_cut,mt,x_ebshift),k_calc(eb_cut,ml,x_ebshift),k_calc(eb_cut,mt,x_ebshift), 5e2); +[X4_xx, X4_yy, X4_zz] = ellipsoid(origin(1), -k0+origin(2), 0+origin(3), k_calc(eb_cut,mt,x_ebshift),k_calc(eb_cut,ml,x_ebshift),k_calc(eb_cut,mt,x_ebshift), 5e2); + +%% - 2.0 - Plotting the isoe surface +hold on; +% -- Defining plot constants +valley_col = [0.8, 0.4, 0]; +% -- Plotting M-valleys +% - #1 +h1 = surf(X1_xx, X1_yy, X1_zz, 'Edgecolor', 'none', 'facecolor', valley_col); +T1 = hgtransform('Parent',gca); h1.Parent=T1; T1.Matrix=makehgtform('xrotate',deg2rad(-15), 'yrotate',deg2rad(-35.264), 'zrotate',-pi/4); +% - #2 +h2 = surf(X2_xx, X2_yy, X2_zz, 'Edgecolor', 'none', 'facecolor', valley_col); +T2 = hgtransform('Parent',gca); h2.Parent=T2; T2.Matrix=makehgtform('xrotate',deg2rad(-15), 'yrotate',deg2rad(-35.264), 'zrotate',-pi/4); +% - #3 +h3 = surf(X1_xx, X1_yy, X1_zz, 'Edgecolor', 'none', 'facecolor', valley_col); +T3 = hgtransform('Parent',gca); h3.Parent=T3; T3.Matrix=makehgtform('xrotate',deg2rad(-15)+pi, 'yrotate',deg2rad(-35.264), 'zrotate',-pi/4); +% - #4 +h4 = surf(X2_xx, X2_yy, X2_zz, 'Edgecolor', 'none', 'facecolor', valley_col); +T4 = hgtransform('Parent',gca); h4.Parent=T4; T4.Matrix=makehgtform('xrotate',deg2rad(-15)+pi, 'yrotate',deg2rad(-35.264), 'zrotate',-pi/4); +% - #5 +h5 = surf(X3_xx, X3_yy, X3_zz, 'Edgecolor', 'none', 'facecolor', valley_col); +T5 = hgtransform('Parent',gca); h5.Parent=T5; T5.Matrix=makehgtform('xrotate',deg2rad(15),'yrotate',deg2rad(-35.264), 'zrotate',deg2rad(-45)); +% - #6 +h6 = surf(X4_xx, X4_yy, X4_zz, 'Edgecolor', 'none', 'facecolor', valley_col); +T6 = hgtransform('Parent',gca); h6.Parent=T6; T6.Matrix=makehgtform('xrotate',deg2rad(15),'yrotate',deg2rad(-35.264), 'zrotate',deg2rad(-45)); +% - #7 +h7 = surf(X3_xx, X3_yy, X3_zz, 'Edgecolor', 'none', 'facecolor', valley_col); +T7 = hgtransform('Parent',gca); h7.Parent=T7; T7.Matrix=makehgtform('xrotate',deg2rad(15)+pi,'yrotate',deg2rad(-35.264), 'zrotate',deg2rad(-45)); +% - #8 +h8 = surf(X4_xx, X4_yy, X4_zz, 'Edgecolor', 'none', 'facecolor', valley_col); +T8 = hgtransform('Parent',gca); h8.Parent=T8; T8.Matrix=makehgtform('xrotate',deg2rad(15)+pi,'yrotate',deg2rad(-35.264), 'zrotate',deg2rad(-45)); +% - 3.0 Formatting the figure +axis tight; axis equal; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_SiCBValleys_2D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_SiCBValleys_2D.m new file mode 100644 index 0000000..8f77e4f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_SiCBValleys_2D.m @@ -0,0 +1,99 @@ +function [] = plot_SiCBValleys_2D(eb_cut, origin, cb_shifts) +% [] = plot_SiCBValleys_2D(eb_cut, origin, cb_shifts) +% This function plots the iso-energetic surfaces of cylindrical valleys +% for Silicon. The out-of-plane axis of the valleys are cylindrical due +% to the 2D nature and lack of any dispersion. +% +% IN: +% - eb_cut: scalar of the energy above the CBM to slice for the iso-surface [eV]. +% - origin: 1x3 row vector of the origin location of the Gama point [x,y,z]. +% - cb_shifts: 1x3 row vector of the relative energy shift of each valley [eb_x, eb_y, eb_z]. +% +% OUT: (figure) + +%% Defining the default parameters +if nargin < 1; eb_cut = 0.2; origin = [0, 0, 0]; cb_shifts = [0, 0, 0]; end +if nargin < 2; origin = [0, 0, 0]; cb_shifts = [0, 0, 0]; end +if nargin < 3; cb_shifts = [0, 0, 0]; end +if isempty(eb_cut); eb_cut = 0.2; end +if isempty(origin); origin = [0, 0, 0]; end +if isempty(cb_shifts); cb_shifts = [0, 0, 0]; end + +%% 1.0 - Defining the constant parameters +x_ebshift = cb_shifts(1); y_ebshift = cb_shifts(2); z_ebshift = cb_shifts(3); +m0 = 9.11e-31; +hbar = 4.135e-15; +ml = 0.92*m0; +mt = 0.19*m0; +%% 1.1 - Defining the dispersions of the CB parabola's +k_calc = @(eb, eff_mass, eb_shift) sqrt(((2*eff_mass)/(hbar^2)) * (eb - eb_shift)); +%% 1.2 - Extracting the CB ellipsoids +k0 = 0.85; % Defining the position of the CBM in k-space +% -- IsoE for X-valleys (cylinders) +% --- Extracting unit cylindrical valleys with radius defined by ellipse +[pX_xx, pX_yy, pX_zz] = cylinder(k_calc(eb_cut,ml,y_ebshift), 1e3); +[mX_xx, mX_yy, mX_zz] = cylinder(k_calc(eb_cut,ml,y_ebshift), 1e3); +% --- Scaling the cylinder in z to be the same size as ellipses in k-space +pX_yy = pX_yy /2; +mX_yy = mX_yy /2; +pX_zz = 3*(k_calc(eb_cut,mt,z_ebshift))*(pX_zz-0.5); +mX_zz = 3*(k_calc(eb_cut,mt,z_ebshift))*(mX_zz-0.5); +% --- Shifting the valleys to the correct locations in k-space +pX_xx = pX_xx + k0 + origin(1); +pX_yy = pX_yy + 0 + origin(2); +pX_zz = pX_zz + 0 + origin(3); +mX_xx = mX_xx - k0 + origin(1); +mX_yy = mX_yy + 0 + origin(2); +mX_zz = mX_zz + 0 + origin(3); +% -- IsoE for Y-valleys (cylinders) +% --- Extracting unit cylindrical valleys with radius defined by ellipse +[pY_xx, pY_yy, pY_zz] = cylinder(k_calc(eb_cut,ml,y_ebshift), 1e3); +[mY_xx, mY_yy, mY_zz] = cylinder(k_calc(eb_cut,ml,y_ebshift), 1e3); +% --- Scaling the cylinder in z to be the same size as ellipses in k-space +pY_xx = pY_xx /2; +mY_xx = mY_xx /2; +pY_zz = 3*(k_calc(eb_cut,mt,z_ebshift))*(pY_zz-0.5); +mY_zz = 3*(k_calc(eb_cut,mt,z_ebshift))*(mY_zz-0.5); +% --- Shifting the valleys to the correct locations in k-space +pY_xx = pY_xx + 0+origin(1); +pY_yy = pY_yy + k0+origin(2); +pY_zz = pY_zz + 0 + origin(3); +mY_xx = mY_xx + 0+origin(1); +mY_yy = mY_yy - k0 + origin(2); +mY_zz = mY_zz + 0 + origin(3); +% -- IsoE for z valleys (cylinders) +% --- Extracting unit cylindrical valleys with radius defined by ellipse +[pZ_xx, pZ_yy, pZ_zz] = cylinder(k_calc(eb_cut,mt,z_ebshift), 1e3); +[mZ_xx, mZ_yy, mZ_zz] = cylinder(k_calc(eb_cut,mt,z_ebshift), 1e3); +% --- Scaling the cylinder in z to be the same size as ellipses in k-space +pZ_zz = 2*(k_calc(eb_cut,ml,z_ebshift))*(pZ_zz-0.5)*50; +mZ_zz = 2*(k_calc(eb_cut,ml,z_ebshift))*(mZ_zz-0.5); +% --- Shifting the valleys to the correct locations in k-space +pZ_xx = pZ_xx + 0+origin(1); +pZ_yy = pZ_yy + 0+origin(2); +pZ_zz = pZ_zz + k0 + origin(3); +mZ_xx = mZ_xx + 0+origin(1); +mZ_yy = mZ_yy + 0+origin(2); +mZ_zz = mZ_zz - k0 + origin(3); + +%% - 2.0 - Plotting the isoe surface +hold on; +% -- Defining plot constants +if cb_shifts(1)==0 && cb_shifts(2)==0 && cb_shifts(3)==0 + xy_valley_col = [0.1,0.6,0.1]; + z_valley_col = [0.1,0.6,0.1]; +else + xy_valley_col = [0.1,0.6,0.1]; + z_valley_col = [0.6,0.1,0.6]; +end +% -- Plotting X-valleys +surf(pX_xx, pX_yy, pX_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +surf(mX_xx, mX_yy, mX_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +% -- Plotting Y-valleys +surf(pY_xx, pY_yy, pY_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +surf(mY_xx, mY_yy, mY_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +% -- Plotting Z-valleys +surf(pZ_xx, pZ_yy, pZ_zz, 'Edgecolor', 'none', 'facecolor', z_valley_col); +% - 3.0 Formatting the figure +axis tight; axis equal; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_SiCBValleys_3D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_SiCBValleys_3D.m new file mode 100644 index 0000000..bad6fef --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_SiCBValleys_3D.m @@ -0,0 +1,63 @@ +function [] = plot_SiCBValleys_3D(eb_cut, origin, cb_shifts) +% [] = plot_SiCBValleys_3D(eb_cut, origin, cb_shifts) +% This function plots the iso-energetic surfaces of elliptical valleys +% for Silicon. This is 6 elliptical valleys, 85% along the Gamma-X high +% symmetry line. +% +% IN: +% - eb_cut: scalar of the energy above the CBM to slice for the iso-surface [eV]. +% - origin: 1x3 row vector of the origin location of the Gama point [x,y,z]. +% - cb_shifts: 1x3 row vector of the relative energy shift of each valley [eb_x, eb_y, eb_z]. +% +% OUT: (figure) + +%% Defining the default parameters +if nargin < 1; eb_cut = 0.2; origin = [0, 0, 0]; cb_shifts = [0, 0, 0]; end +if nargin < 2; origin = [0, 0, 0]; cb_shifts = [0, 0, 0]; end +if nargin < 3; cb_shifts = [0, 0, 0]; end +if isempty(eb_cut); eb_cut = 0.2; end +if isempty(origin); origin = [0, 0, 0]; end +if isempty(cb_shifts); cb_shifts = [0, 0, 0]; end + +%% 1.0 - Defining the constant parameters +x_ebshift = cb_shifts(1); y_ebshift = cb_shifts(2); z_ebshift = cb_shifts(3); +m0 = 9.11e-31; +hbar = 4.135e-15; +ml = 0.92*m0; +mt = 0.19*m0; +%% 1.1 - Defining the dispersions of the CB parabola's +k_calc = @(eb, eff_mass, eb_shift) sqrt(((2*eff_mass)/(hbar^2)) * (eb - eb_shift)); +%% 1.2 - Extracting the CB ellipsoids +k0 = 0.85; % Defining the position of the CBM in k-space +% -- IsoE for x valleys +[pX_xx, pX_yy, pX_zz] = ellipsoid(k0+origin(1), 0+origin(2), 0+origin(3), k_calc(eb_cut,ml,x_ebshift),k_calc(eb_cut,mt,x_ebshift),k_calc(eb_cut,mt,x_ebshift), 1e3); +[mX_xx, mX_yy, mX_zz] = ellipsoid(-k0+origin(1), 0+origin(2), 0+origin(3), k_calc(eb_cut,ml,x_ebshift),k_calc(eb_cut,mt,x_ebshift),k_calc(eb_cut,mt,x_ebshift), 1e3); +% -- IsoE for y valleys +[pY_xx, pY_yy, pY_zz] = ellipsoid(0+origin(1),k0+origin(2),0+origin(3),k_calc(eb_cut,mt,y_ebshift),k_calc(eb_cut,ml,y_ebshift),k_calc(eb_cut,mt,y_ebshift), 1e3); +[mY_xx, mY_yy, mY_zz] = ellipsoid(0+origin(1),-k0+origin(2),0+origin(3),k_calc(eb_cut,mt,y_ebshift),k_calc(eb_cut,ml,y_ebshift),k_calc(eb_cut,mt,y_ebshift), 1e3); +% -- IsoE for z valleys +[pZ_xx, pZ_yy, pZ_zz] = ellipsoid(0+origin(1),0+origin(2),k0+origin(3),k_calc(eb_cut,mt,z_ebshift),k_calc(eb_cut,mt,z_ebshift),k_calc(eb_cut,ml,z_ebshift), 1e3); +[mZ_xx, mZ_yy, mZ_zz] = ellipsoid(0+origin(1),0+origin(2),-k0+origin(3),k_calc(eb_cut,mt,z_ebshift),k_calc(eb_cut,mt,z_ebshift),k_calc(eb_cut,ml,z_ebshift), 1e3); + +%% - 2.0 - Plotting the isoe surface +hold on; +% -- Defining plot constants +if cb_shifts(1)==0 && cb_shifts(2)==0 && cb_shifts(3)==0 + xy_valley_col = [0.1,0.6,0.1]; + z_valley_col = [0.1,0.6,0.1]; +else + xy_valley_col = [0.1,0.6,0.1]; + z_valley_col = [0.6,0.1,0.6]; +end +% -- Plotting X-valleys +surf(pX_xx, pX_yy, pX_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +surf(mX_xx, mX_yy, mX_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +% -- Plotting Y-valleys +surf(pY_xx, pY_yy, pY_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +surf(mY_xx, mY_yy, mY_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +% -- Plotting Z-valleys +surf(pZ_xx, pZ_yy, pZ_zz, 'Edgecolor', 'none', 'facecolor', z_valley_col); +surf(mZ_xx, mZ_yy, mZ_zz, 'Edgecolor', 'none', 'facecolor', z_valley_col); +% - 3.0 Formatting the figure +axis tight; axis equal; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_SiCBValleys_q2D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_SiCBValleys_q2D.m new file mode 100644 index 0000000..6e62919 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_SiCBValleys_q2D.m @@ -0,0 +1,119 @@ +function [] = plot_SiCBValleys_q2D(eb_cut, origin, cb_shifts) +% [] = plot_SiCBValleys_q2D(eb_cut, origin, cb_shifts) +% This function plots the iso-energetic surfaces of elliptical valleys +% for Silicon. The 6 elliptical valleys are now broken in degeneracy, and +% colored differently to distinguish the 6XYZ -> 4XY + 2Z valley +% polarisation. +% +% IN: +% - eb_cut: scalar of the energy above the CBM to slice for the iso-surface [eV]. +% - origin: 1x3 row vector of the origin location of the Gama point [x,y,z]. +% - cb_shifts: 1x3 row vector of the relative energy shift of each valley [eb_x, eb_y, eb_z]. +% +% OUT: (figure) + +%% Defining the default parameters +if nargin < 1; eb_cut = 0.2; origin = [0, 0, 0]; cb_shifts = [0, 0, 0]; end +if nargin < 2; origin = [0, 0, 0]; cb_shifts = [0, 0, 0]; end +if nargin < 3; cb_shifts = [0, 0, 0]; end +if isempty(eb_cut); eb_cut = 0.2; end +if isempty(origin); origin = [0, 0, 0]; end +if isempty(cb_shifts); cb_shifts = [0, 0, 0]; end + +%% 1.0 - Defining the constant parameters +x_ebshift = cb_shifts(1); y_ebshift = cb_shifts(2); z_ebshift = cb_shifts(3); +m0 = 9.11e-31; +hbar = 4.135e-15; +ml = 0.92*m0; +mt = 0.19*m0; +%% 1.1 - Defining the dispersions of the CB parabola's +k_calc = @(eb, eff_mass, eb_shift) sqrt(((2*eff_mass)/(hbar^2)) * (eb - eb_shift)); +%% 1.2 - Extracting the CB as cylinders +k0 = 0.85; % Defining the position of the CBM in k-space +% -- IsoE for X-valleys (cylinders) +% --- Extracting unit cylindrical valleys with radius defined by ellipse +[pX_xx, pX_yy, pX_zz] = cylinder(k_calc(eb_cut,ml,y_ebshift), 1e3); +[mX_xx, mX_yy, mX_zz] = cylinder(k_calc(eb_cut,ml,y_ebshift), 1e3); +% --- Scaling the cylinder in z to be the same size as ellipses in k-space +pX_yy = pX_yy /2; +mX_yy = mX_yy /2; +pX_zz = 2*(k_calc(eb_cut,mt,z_ebshift))*(pX_zz-0.5); +mX_zz = 2*(k_calc(eb_cut,mt,z_ebshift))*(mX_zz-0.5); +% --- Shifting the valleys to the correct locations in k-space +pX_xx = pX_xx + k0 + origin(1); +pX_yy = pX_yy + 0 + origin(2); +pX_zz = pX_zz + 0 + origin(3); +mX_xx = mX_xx - k0 + origin(1); +mX_yy = mX_yy + 0 + origin(2); +mX_zz = mX_zz + 0 + origin(3); +% -- IsoE for Y-valleys (cylinders) +% --- Extracting unit cylindrical valleys with radius defined by ellipse +[pY_xx, pY_yy, pY_zz] = cylinder(k_calc(eb_cut,ml,y_ebshift), 1e3); +[mY_xx, mY_yy, mY_zz] = cylinder(k_calc(eb_cut,ml,y_ebshift), 1e3); +% --- Scaling the cylinder in z to be the same size as ellipses in k-space +pY_xx = pY_xx /2; +mY_xx = mY_xx /2; +pY_zz = 2*(k_calc(eb_cut,mt,z_ebshift))*(pY_zz-0.5); +mY_zz = 2*(k_calc(eb_cut,mt,z_ebshift))*(mY_zz-0.5); +% --- Shifting the valleys to the correct locations in k-space +pY_xx = pY_xx + 0+origin(1); +pY_yy = pY_yy + k0+origin(2); +pY_zz = pY_zz + 0 + origin(3); +mY_xx = mY_xx + 0+origin(1); +mY_yy = mY_yy - k0 + origin(2); +mY_zz = mY_zz + 0 + origin(3); +% -- IsoE for Z-valleys (cylinders) +% --- Extracting unit cylindrical valleys with radius defined by ellipse +[pZ_xx, pZ_yy, pZ_zz] = cylinder(k_calc(eb_cut,mt,z_ebshift), 1e3); +[mZ_xx, mZ_yy, mZ_zz] = cylinder(k_calc(eb_cut,mt,z_ebshift), 1e3); +% --- Scaling the cylinder in z to be the same size as ellipses in k-space +pZ_zz = 2*(k_calc(eb_cut,ml,z_ebshift))*(pZ_zz-0.5); +mZ_zz = 2*(k_calc(eb_cut,ml,z_ebshift))*(mZ_zz-0.5); +% --- Shifting the valleys to the correct locations in k-space +pZ_xx = pZ_xx + 0+origin(1); +pZ_yy = pZ_yy + 0+origin(2); +pZ_zz = pZ_zz + k0 + origin(3); +mZ_xx = mZ_xx + 0+origin(1); +mZ_yy = mZ_yy + 0+origin(2); +mZ_zz = mZ_zz - k0 + origin(3); + +%% - 2.0 - Plotting the isoe surface +hold on; +% -- Defining plot constants +if cb_shifts(1)==0 && cb_shifts(2)==0 && cb_shifts(3)==0 + xy_valley_col = [0.1,0.6,0.1]; + pz_valley_col = [0.6,0.1,0.6]; + mz_valley_col = pz_valley_col; +else + xy_valley_col = [0.1,0.6,0.1]; + pz_valley_col = [0.6,0.1,0.6]; + mz_valley_col = pz_valley_col; +end +% -- Plotting X-valleys +surf(pX_xx, pX_yy, pX_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +surf(mX_xx, mX_yy, mX_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +% -- Plotting Y-valleys +surf(pY_xx, pY_yy, pY_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +surf(mY_xx, mY_yy, mY_zz, 'Edgecolor', 'none', 'facecolor', xy_valley_col); +% -- Plotting Z-valleys +surf(pZ_xx, pZ_yy, pZ_zz, 'Edgecolor', 'none', 'facecolor', pz_valley_col); +surf(mZ_xx, mZ_yy, mZ_zz, 'Edgecolor', 'none', 'facecolor', mz_valley_col); +% - 2.1 - Plotting the caps to the cylinders +% - X-valleys +fill3(pX_xx(1,:), pX_yy(1,:), pX_zz(1,:), xy_valley_col, 'Edgecolor', 'none'); +fill3(pX_xx(end,:), pX_yy(end,:), pX_zz(end,:), xy_valley_col, 'Edgecolor', 'none'); +fill3(mX_xx(1,:), mX_yy(1,:), mX_zz(1,:), xy_valley_col, 'Edgecolor', 'none'); +fill3(mX_xx(end,:), mX_yy(end,:), mX_zz(end,:), xy_valley_col, 'Edgecolor', 'none'); +% - Y-valleys +fill3(pY_xx(1,:), pY_yy(1,:), pY_zz(1,:), xy_valley_col, 'Edgecolor', 'none'); +fill3(pY_xx(end,:), pY_yy(end,:), pY_zz(end,:), xy_valley_col, 'Edgecolor', 'none'); +fill3(mY_xx(1,:), mY_yy(1,:), mY_zz(1,:), xy_valley_col, 'Edgecolor', 'none'); +fill3(mY_xx(end,:), mY_yy(end,:), mY_zz(end,:), xy_valley_col, 'Edgecolor', 'none'); +% - Z-valleys +fill3(pZ_xx(1,:), pZ_yy(1,:), pZ_zz(1,:), pz_valley_col, 'Edgecolor', 'none'); +fill3(pZ_xx(end,:), pZ_yy(end,:), pZ_zz(end,:), pz_valley_col, 'Edgecolor', 'none'); +fill3(mZ_xx(1,:), mZ_yy(1,:), mZ_zz(1,:), pz_valley_col, 'Edgecolor', 'none'); +fill3(mZ_xx(end,:), mZ_yy(end,:), mZ_zz(end,:), pz_valley_col, 'Edgecolor', 'none'); +% - 3.0 Formatting the figure +axis tight; axis equal; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_TruncOctahedron.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_TruncOctahedron.m new file mode 100644 index 0000000..6a5724c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_TruncOctahedron.m @@ -0,0 +1,134 @@ +function [] = plot_TruncOctahedron(a_fcc, origin, colTrunc, colPyra) +% [] = plot_TruncOctahedron(a_fcc, origin, colTrunc, colPyra) +% This is a function that plots a construction of the +% truncated octahedron, showing the regular octahedron +% and the six right-square pyramids that are cut from it. +% +% IN: +% - a_fcc: scalar of the lattice constant of the FCC lattice [nm]. +% - origin: 1x3 row vector of the origin location of the truncated octahedron shape [x,y,z]. +% - colTrunc: 1x3 row vector of the color for the truncated part. +% - colPyra: 1x3 row vector of the color for the pyramid caps part. +% +% OUT: (figure) + +%% Setting the default input parameters +if nargin < 1; a_fcc = 5.43; origin = [0 0 0]; colTrunc = [0.2 0.2 0.6]; colPyra = [0.6 0.2 0.2]; end +if nargin < 2; origin = [0 0 0]; colTrunc = [0.2 0.2 0.6]; colPyra = [0.6 0.2 0.2]; end +if nargin < 3; colTrunc = [0.2 0.2 0.6]; colPyra = [0.6 0.2 0.2]; end +if nargin < 4; colPyra = [0.6 0.2 0.2]; end +if isempty(a_fcc); a_fcc = 5.43; end +if isempty(origin); origin = [0 0 0]; end +if isempty(colTrunc); colTrunc = [0.2 0.2 0.6]; end +if isempty(colPyra); colPyra = [0.6 0.2 0.2]; end + +%% Defining the functions constants +%Defining the variable constants +a_reci = 2*pi / a_fcc; +%Defining the plotting constants +fontSize = 20; +lineWidth = 2.; + +%% 1.0 - Defining the polygons of the truncated octahedron +%-Defining the hexagons in terms of a +hex = [ + [1, 0.5, 0, 0, 0.5, 1, 1]; + [0.5, 1, 1, 0.5, 0, 0, 0.5]; + [0, 0, 0.5, 1, 1, 0.5, 0] + ]*a_reci; +%-Defining the squares in terms of a +squ = [ + [1, 1, 1, 1, 1]; + [0.5, 0, -0.5, 0, 0.5]; + [0, 0.5, 0, -0.5, 0] + ]*a_reci; + +%% 1.1 - Symmetry relationships of all the truncated octahedron +%-Extracting all of the permutations of the hexagons +h1 = [hex(1,:)+origin(1); hex(2,:)+origin(2); hex(3,:)+origin(3)]; +h2 = [hex(1,:)+origin(1); -1*hex(2,:)+origin(2); hex(3,:)+origin(3)]; +h3 = [-1*hex(1,:)+origin(1); hex(2,:)+origin(2); hex(3,:)+origin(3)]; +h4 = [-1*hex(1,:)+origin(1); -1*hex(2,:)+origin(2); hex(3,:)+origin(3)]; +h5 = [hex(1,:)+origin(1); hex(2,:)+origin(2); -1*hex(3,:)+origin(3)]; +h6 = [hex(1,:)+origin(1); -1*hex(2,:)+origin(2); -1*hex(3,:)+origin(3)]; +h7 = [-1*hex(1,:)+origin(1); hex(2,:)+origin(2); -1*hex(3,:)+origin(3)]; +h8 = [-1*hex(1,:)+origin(1); -1*hex(2,:)+origin(2); -1*hex(3,:)+origin(3)]; +%-Extracting all of the permutations of the squares +s1 = [squ(1,:)+origin(1); squ(2,:)+origin(2); squ(3,:)+origin(3)]; +s2 = [-1*squ(1,:)+origin(1); squ(2,:)+origin(2); squ(3,:)+origin(3)]; +s3 = [squ(2,:)+origin(1); squ(1,:)+origin(2); -1*squ(3,:)+origin(3)]; +s4 = [squ(2,:)+origin(1); -1*squ(1,:)+origin(2); squ(3,:)+origin(3)]; +s5 = [squ(2,:)+origin(1); squ(3,:)+origin(2); squ(1,:)+origin(3)]; +s6 = [squ(2,:)+origin(1); squ(3,:)+origin(2); -1*squ(1,:)+origin(3)]; +%-Extracting the faces as a convex hull +x_oct = [h1(1,:), h2(1,:), h3(1,:), h4(1,:), h5(1,:), h6(1,:), h7(1,:), h8(1,:)]; +y_oct = [h1(2,:), h2(2,:), h3(2,:), h4(2,:), h5(2,:), h6(2,:), h7(2,:), h8(2,:)]; +z_oct = [h1(3,:), h2(3,:), h3(3,:), h4(3,:), h5(3,:), h6(3,:), h7(3,:), h8(3,:)]; +faces_oct = convhull(x_oct, y_oct, z_oct); + +%% 2.0 - Defining the polygons of the right-sqaure pyramids +%-Defining the triangles in terms of a +tri = [ + [1, 1, 1, 1, 1, 1.5, 1, 1, 1.5, 1]; + [0, 0.5, 0, -0.5, 0, 0, 0, 0.5, 0, -0.5]; + [0.5, 0, -0.5, 0, 0.5, 0, -0.5, 0, 0, 0] + ]* a_reci; + +%% 2.1 - Symmetry relationships of all the right-square pyramids +%-Extracting all of the permutations of the pyramids +p1 = [tri(1,:)+origin(1); tri(2,:)+origin(2); tri(3,:)+origin(3)]; +p2 = [-1*tri(1,:)+origin(1); tri(2,:)+origin(2); tri(3,:)+origin(3)]; +p3 = [tri(2,:)+origin(1); tri(1,:)+origin(2); -1*tri(3,:)+origin(3)]; +p4 = [tri(2,:)+origin(1); -1*tri(1,:)+origin(2); tri(3,:)+origin(3)]; +p5 = [tri(2,:)+origin(1); tri(3,:)+origin(2); tri(1,:)+origin(3)]; +p6 = [tri(2,:)+origin(1); tri(3,:)+origin(2); -1*tri(1,:)+origin(3)]; +%-Extracting the faces as a convex hull +x_pyr = [p1(1,:), p2(1,:), p3(1,:), p4(1,:), p5(1,:), p6(1,:)]; +y_pyr = [p1(2,:), p2(2,:), p3(2,:), p4(2,:), p5(2,:), p6(2,:)]; +z_pyr = [p1(3,:), p2(3,:), p3(3,:), p4(3,:), p5(3,:), p6(3,:)]; +faces_pyr = convhull(x_pyr, y_pyr, z_pyr); + + +%% 3.0 - Plotting the truncated octahedron Brilluoin zone +hold on; +%-Plotting the 3D Brilluoin zone shades +trisurf(faces_pyr,x_pyr,y_pyr,z_pyr,'FaceColor',colPyra,'EdgeColor','none') +trisurf(faces_oct,x_oct,y_oct,z_oct,'FaceColor',colTrunc,'EdgeColor','none') + +%--Plotting the hexagons +plot3(h1(1,:), h1(2,:), h1(3,:), 'k-', 'linewidth', lineWidth); +plot3(h2(1,:), h2(2,:), h2(3,:), 'k-', 'linewidth', lineWidth); +plot3(h3(1,:), h3(2,:), h3(3,:), 'k-', 'linewidth', lineWidth); +plot3(h4(1,:), h4(2,:), h4(3,:), 'k-', 'linewidth', lineWidth); +plot3(h5(1,:), h5(2,:), h5(3,:), 'k-', 'linewidth', lineWidth); +plot3(h6(1,:), h6(2,:), h6(3,:), 'k-', 'linewidth', lineWidth); +plot3(h7(1,:), h7(2,:), h7(3,:), 'k-', 'linewidth', lineWidth); +plot3(h8(1,:), h8(2,:), h8(3,:), 'k-', 'linewidth', lineWidth); +%--Plotting the squares +plot3(s1(1,:), s1(2,:), s1(3,:), 'k-', 'linewidth', lineWidth); +plot3(s2(1,:), s2(2,:), s2(3,:), 'k-', 'linewidth', lineWidth); +plot3(s3(1,:), s3(2,:), s3(3,:), 'k-', 'linewidth', lineWidth); +plot3(s4(1,:), s4(2,:), s4(3,:), 'k-', 'linewidth', lineWidth); +plot3(s5(1,:), s5(2,:), s5(3,:), 'k-', 'linewidth', lineWidth); +plot3(s6(1,:), s6(2,:), s6(3,:), 'k-', 'linewidth', lineWidth); +%--Plotting the pyramids +plot3(p1(1,:), p1(2,:), p1(3,:), 'w-', 'linewidth', lineWidth); +plot3(p2(1,:), p2(2,:), p2(3,:), 'w-', 'linewidth', lineWidth); +plot3(p3(1,:), p3(2,:), p3(3,:), 'w-', 'linewidth', lineWidth); +plot3(p4(1,:), p4(2,:), p4(3,:), 'w-', 'linewidth', lineWidth); +plot3(p5(1,:), p5(2,:), p5(3,:), 'w-', 'linewidth', lineWidth); +plot3(p6(1,:), p6(2,:), p6(3,:), 'w-', 'linewidth', lineWidth); + +%-Formatting the figure +%--Adding axes labels and limits +grid on; +xlabel(' $ k_x (\AA^{-1}) $ ', 'Interpreter', 'latex'); +ylabel(' $ k_y (\AA^{-1}) $ ', 'Interpreter', 'latex'); +zlabel(' $ k_z (\AA^{-1}) $ ', 'Interpreter', 'latex'); +axis([[-1, 1], [-1, 1], [-1, 1]]*1.0*a_reci); +set(gca,'fontsize', fontSize, 'xtick', -20:1:20, 'ytick', -20:1:20, 'ztick', -20:1:20); +%--Setting the axis and camera lighting +axis tight; axis vis3d; axis off; camlight(-112,24); +pbaspect([1 1 1]); +view(-158, 16); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_fccBZ_3D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_fccBZ_3D.m new file mode 100644 index 0000000..f232994 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F002 - brilluoin zone overlay/plot_fccBZ_3D.m @@ -0,0 +1,94 @@ +function [] = plot_fccBZ_3D(a_fcc, origin) +% [] = plot_fccBZ_3D(a_fcc, origin) +% This is a function that plots the Brilluoin zone of an FCC +% lattice, with a lattice constant a, origin location at [x0, y0, z0]. +% +% IN: +% - a_fcc: scalar of the lattice constant of the FCC lattice [nm]. +% - origin: 1x3 row vector of the origin location of the BZ [x,y,z] +% +% OUT: (figure) + +%% Setting the default parameters +if nargin < 1; a_fcc = 5.43; origin = [0 0 0]; end +if nargin < 2; origin = [0 0 0]; end +if isempty(a_fcc); a_fcc = 5.43; end +if isempty(origin); origin = [0 0 0]; end + +%% Defining the functions constants +% Defining the brilluoin zone plot constants +lineCol = [0 0 0]; +lineStyle = '-'; +lineWidth = 2; +% Defining the variable constants +a_reci = 2*pi / a_fcc; + +%% 1.0 - Defining the polygons of the truncated octahedron +%-Defining the hexagons in terms of a +hex = [ + [1, 0.5, 0, 0, 0.5, 1, 1]; + [0.5, 1, 1, 0.5, 0, 0, 0.5]; + [0, 0, 0.5, 1, 1, 0.5, 0] + ]*a_reci; +%-Defining the squares in terms of a +squ = [ + [1, 1, 1, 1, 1]; + [0.5, 0, -0.5, 0, 0.5]; + [0, 0.5, 0, -0.5, 0] + ]*a_reci; + +%% 1.1 - Symmetry relationships of all the polygons +%-Extracting all of the permutations of the hexagons +h1 = [hex(1,:)+origin(1); hex(2,:)+origin(2); hex(3,:)+origin(3)]; +h2 = [hex(1,:)+origin(1); -1*hex(2,:)+origin(2); hex(3,:)+origin(3)]; +h3 = [-1*hex(1,:)+origin(1); hex(2,:)+origin(2); hex(3,:)+origin(3)]; +h4 = [-1*hex(1,:)+origin(1); -1*hex(2,:)+origin(2); hex(3,:)+origin(3)]; +h5 = [hex(1,:)+origin(1); hex(2,:)+origin(2); -1*hex(3,:)+origin(3)]; +h6 = [hex(1,:)+origin(1); -1*hex(2,:)+origin(2); -1*hex(3,:)+origin(3)]; +h7 = [-1*hex(1,:)+origin(1); hex(2,:)+origin(2); -1*hex(3,:)+origin(3)]; +h8 = [-1*hex(1,:)+origin(1); -1*hex(2,:)+origin(2); -1*hex(3,:)+origin(3)]; +%-Extracting all of the permutations of the squares +s1 = [squ(1,:)+origin(1); squ(2,:)+origin(2); squ(3,:)+origin(3)]; +s2 = [-1*squ(1,:)+origin(1); squ(2,:)+origin(2); squ(3,:)+origin(3)]; +s3 = [squ(2,:)+origin(1); squ(1,:)+origin(2); -1*squ(3,:)+origin(3)]; +s4 = [squ(2,:)+origin(1); -1*squ(1,:)+origin(2); squ(3,:)+origin(3)]; +s5 = [squ(2,:)+origin(1); squ(3,:)+origin(2); squ(1,:)+origin(3)]; +s6 = [squ(2,:)+origin(1); squ(3,:)+origin(2); -1*squ(1,:)+origin(3)]; +%-Extracting the faces as a convex hull +x = [h1(1,:), h2(1,:), h3(1,:), h4(1,:), h5(1,:), h6(1,:), h7(1,:), h8(1,:)]; +y = [h1(2,:), h2(2,:), h3(2,:), h4(2,:), h5(2,:), h6(2,:), h7(2,:), h8(2,:)]; +z = [h1(3,:), h2(3,:), h3(3,:), h4(3,:), h5(3,:), h6(3,:), h7(3,:), h8(3,:)]; + +%% 2.0 - Plotting the truncated octahedron Brilluoin zone +hold on; +%--Plotting the hexagons +plot3(h1(1,:), h1(2,:), h1(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(h2(1,:), h2(2,:), h2(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(h3(1,:), h3(2,:), h3(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(h4(1,:), h4(2,:), h4(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(h5(1,:), h5(2,:), h5(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(h6(1,:), h6(2,:), h6(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(h7(1,:), h7(2,:), h7(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(h8(1,:), h8(2,:), h8(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +%--Plotting the squares +plot3(s1(1,:), s1(2,:), s1(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(s2(1,:), s2(2,:), s2(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(s3(1,:), s3(2,:), s3(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(s4(1,:), s4(2,:), s4(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(s5(1,:), s5(2,:), s5(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +plot3(s6(1,:), s6(2,:), s6(3,:), 'linewidth', lineWidth,... + 'linestyle', lineStyle, 'color', lineCol); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve.m new file mode 100644 index 0000000..32e01b0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve.m @@ -0,0 +1,84 @@ +function zdat = ARPESCurve(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, plot_result) +% zdat = ARPESCurve(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, plot_result) +% Function that evaluates a generic angle-resolved photoelectron +% spectroscopy (ARPES) curve in 2D. This can be used to model an ARPES +% spectrum, that is built up by a sum of individual Gaussians. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - cTYPE: type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - INT: scalar of the peak intensity of 2D PE curve. +% - XLOC: scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion [Ang^-1]. +% - YLOC: scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion [eV]. +% - XFWHM: scalar of the x-axis FWHM for each Gaussian (k-resolution) [Ang^-1] +% - YFWHM: scalar of the y-axis FWHM for each Gaussian (Eb-resolution) [eV] +% - MSTAR: scalar of the effective mass, which governs the curvature of the parabola. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat: [N×M] matrix of the output 2D parabolic ARPES dispersion. + +%% Default parameters +% Default based on inputs +if nargin < 10; plot_result = 0; end +if nargin < 9; MSTAR = 0.20; end +if nargin < 8; YFWHM = 0.25; end +if nargin < 7; XFWHM = 0.02; end +if nargin < 6; YLOC = 0.00; end +if nargin < 5; XLOC = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 3; cTYPE = "G2DA"; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "G2DA"; end +if isempty(INT); INT = 1.00; end +if isempty(XLOC); XLOC = 0.00; end +if isempty(YLOC); YLOC = 0.00; end +if isempty(XFWHM); XFWHM = 0.02; end +if isempty(YFWHM); YFWHM = 0.25; end +if isempty(MSTAR); MSTAR = 0.20; end +if isempty(plot_result); plot_result = 0; end + +%% - 1 - Determination of the angle-resolved photoemission spectrum +% Ensuring xdat is a row vector +if size(xdat, 1) > 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1; ydat = ydat'; end +% Filing through all the curves +for j = 1:length(cTYPE) + % Initialising the data + k_val = xdat; + eb_val = eb_calc(xdat, XLOC(j), YLOC(j), MSTAR(j)); + P_curve = zeros(length(ydat), length(xdat), length(k_val)); + % Extracting the primary curve components + for i = 1:length(k_val) + if strcmpi(cTYPE,"G2D"); P_curve(:,:,i) = G2D(xdat, ydat, INT(j), k_val(i), eb_val(i), XFWHM(j)); + elseif strcmpi(cTYPE,"L2D"); P_curve(:,:,i) = L2D(xdat, ydat, INT(j), k_val(i), eb_val(i), XFWHM(j)); + elseif strcmpi(cTYPE,"G2DA"); P_curve(:,:,i) = G2DA(xdat, ydat, INT(j), k_val(i), eb_val(i), XFWHM(j), YFWHM(j)); + end + end + % Summing the components together + zdat_temp{j} = sum(P_curve, 3); + % If isnan, return zero + zdat_temp{j}(isnan(zdat_temp{j})) = 0; +end +% Summing over all the data +zdat = zdat_temp{1}; +if length(zdat_temp) > 1; for i = 2:length(zdat_temp); zdat = zdat + zdat_temp{i}; end; end + +%% -- For Debugging +if plot_result == 1 + pp = plot_props(); + fig = figure(); + fig.Position(3) = pp.fig4x4(1); fig.Position(4) = pp.fig4x4(2); + hold on; + ImData(xdat, ydat, zdat); + img_props(); title('ARPESCurve()', 'Interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm.m new file mode 100644 index 0000000..18665fb --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm.m @@ -0,0 +1,90 @@ +function zdat = ARPESCurveNorm(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, plot_result) +% zdat = ARPESCurveNorm(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, plot_result) +% Function that evaluates a generic angle-resolved photoelectron +% spectroscopy (ARPES) curve in 2D. This can be used to model an ARPES +% spectrum, that is built up by a sum of individual Gaussians. The +% intensity is normalised across all EDCs. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - cTYPE: type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - INT: scalar of the peak intensity of 2D PE curve. +% - XLOC: scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion [Ang^-1]. +% - YLOC: scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion [eV]. +% - XFWHM: scalar of the x-axis FWHM for each Gaussian (k-resolution) [Ang^-1] +% - YFWHM: scalar of the y-axis FWHM for each Gaussian (Eb-resolution) [eV] +% - MSTAR: scalar of the effective mass, which governs the curvature of the parabola. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat: [N×M] matrix of the output 2D parabolic ARPES dispersion. + +%% Default parameters +% Default based on inputs +if nargin < 10; plot_result = 0; end +if nargin < 9; MSTAR = 0.20; end +if nargin < 8; YFWHM = 0.25; end +if nargin < 7; XFWHM = 0.02; end +if nargin < 6; YLOC = 0.00; end +if nargin < 5; XLOC = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 3; cTYPE = "G2DA"; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "G2DA"; end +if isempty(INT); INT = 1.00; end +if isempty(XLOC); XLOC = 0.00; end +if isempty(YLOC); YLOC = 0.00; end +if isempty(XFWHM); XFWHM = 0.02; end +if isempty(YFWHM); YFWHM = 0.25; end +if isempty(MSTAR); MSTAR = 0.20; end +if isempty(plot_result); plot_result = 0; end + +%% - 1 - Determination of the angle-resolved photoemission spectrum +% Ensuring xdat is a row vector +if size(xdat, 1) > 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1; ydat = ydat'; end +% Filing through all the curves +for j = 1:length(cTYPE) + % Initialising the data + k_val = xdat; + eb_val = eb_calc(xdat, XLOC(j), YLOC(j), MSTAR(j)); + P_curve = zeros(length(ydat), length(xdat), length(k_val)); + % Extracting the primary curve components + for i = 1:length(k_val) + if strcmpi(cTYPE,"G2D"); P_curve(:,:,i) = G2D(xdat, ydat, INT(j), k_val(i), eb_val(i), XFWHM(j)); + elseif strcmpi(cTYPE,"L2D"); P_curve(:,:,i) = L2D(xdat, ydat, INT(j), k_val(i), eb_val(i), XFWHM(j)); + elseif strcmpi(cTYPE,"G2DA"); P_curve(:,:,i) = G2DA(xdat, ydat, INT(j), k_val(i), eb_val(i), XFWHM(j), YFWHM(j)); + end + end + % Summing the components together + zdat_temp{j} = sum(P_curve, 3); + % If isnan, return zero + zdat_temp{j}(isnan(zdat_temp{j})) = 0; +end +% Summing over all the data +zdat = zdat_temp{1}; +if length(zdat_temp) > 1; for i = 2:length(zdat_temp); zdat = zdat + zdat_temp{i}; end; end + +%% - 2 - Normalising across all of the EDCs +for i = 1:size(zdat,2) + zdat(:,i) = zdat(:,i) ./ max(zdat(:,i)); +end + +%% -- For Debugging +if plot_result == 1 + pp = plot_props(); + fig = figure(); + fig.Position(3) = pp.fig4x4(1); fig.Position(4) = pp.fig4x4(2); + hold on; + ImData(xdat, ydat, zdat); + img_props(); title('ARPESCurveNorm()', 'Interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDD.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDD.m new file mode 100644 index 0000000..ed2aa82 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDD.m @@ -0,0 +1,79 @@ +function zdat = ARPESCurveNorm_FDD(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, plot_result) +% zdat = ARPESCurveNorm_FDD(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, plot_result) +% Function that evaluates a generic angle-resolved photoelectron +% spectroscopy (ARPES) curve in 2D. This can be used to model an ARPES +% spectrum, that is built up by a sum of individual Gaussians. The +% intensity is normalised across all EDCs. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - cTYPE: type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - INT: scalar of the peak intensity of 2D PE curve. +% - XLOC: scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion [Ang^-1]. +% - YLOC: scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion [eV]. +% - XFWHM: scalar of the x-axis FWHM for each Gaussian (k-resolution) [Ang^-1] +% - YFWHM: scalar of the y-axis FWHM for each Gaussian (Eb-resolution) [eV] +% - MSTAR: scalar of the effective mass, which governs the curvature of the parabola. +% - FDEF: scalar of the FDD Fermi-Level position. +% - FDT: scalar of the FDD temperature. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat: [N×M] matrix of the output 2D parabolic ARPES dispersion. + +%% Default parameters +% Default based on inputs +if nargin < 12; plot_result = 0; end +if nargin < 11; FDT = 12; end +if nargin < 10; FDEF = 0; end +if nargin < 9; MSTAR = 0.20; end +if nargin < 8; YFWHM = 0.25; end +if nargin < 7; XFWHM = 0.02; end +if nargin < 6; YLOC = 0.00; end +if nargin < 5; XLOC = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 3; cTYPE = "G2DA"; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "G2DA"; end +if isempty(INT); INT = 1.00; end +if isempty(XLOC); XLOC = 0.00; end +if isempty(YLOC); YLOC = 0.00; end +if isempty(XFWHM); XFWHM = 0.02; end +if isempty(YFWHM); YFWHM = 0.25; end +if isempty(MSTAR); MSTAR = 0.20; end +if isempty(FDT); FDT = 12; end +if isempty(FDEF); FDEF = 0; end +if isempty(plot_result); plot_result = 0; end + +%% - 1 - Determination of the angle-resolved photoemission spectrum +% Ensuring xdat is a row vector +if size(xdat, 1) > 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1; ydat = ydat'; end +% - Extracting the FDD curve +FDD_curve = FDD(ydat, FDEF, FDT); +% - Extracting the ARPES curve +ARPES_curve = ARPESCurveNorm(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR); +% - Multiplying the components together +zdat = ARPES_curve .* FDD_curve; +% int = INT .* (int / max(int)); +% If isnan, return zero +zdat(isnan(zdat)) = 0; + +%% -- For Debugging +if plot_result == 1 + pp = plot_props(); + fig = figure(); + fig.Position(3) = pp.fig4x4(1); fig.Position(4) = pp.fig4x4(2); + hold on; + ImData(xdat, ydat, zdat); + img_props(); title('ARPESCurveNorm_FDD()', 'Interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDDG.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDDG.m new file mode 100644 index 0000000..ab894a3 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDDG.m @@ -0,0 +1,82 @@ +function zdat = ARPESCurveNorm_FDDG(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, plot_result) +% zdat = ARPESCurveNorm_FDDG(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, plot_result) +% Function that evaluates a generic angle-resolved photoelectron +% spectroscopy (ARPES) curve in 2D. This can be used to model an ARPES +% spectrum, that is built up by a sum of individual Gaussians. The +% intensity is normalised across all EDCs. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - cTYPE: type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - INT: scalar of the peak intensity of 2D PE curve. +% - XLOC: scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion [Ang^-1]. +% - YLOC: scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion [eV]. +% - XFWHM: scalar of the x-axis FWHM for each Gaussian (k-resolution) [Ang^-1] +% - YFWHM: scalar of the y-axis FWHM for each Gaussian (Eb-resolution) [eV] +% - MSTAR: scalar of the effective mass, which governs the curvature of the parabola. +% - FDEF: scalar of the FDD Fermi-Level position. +% - FDT: scalar of the FDD temperature. +% - FDW: scalar of the FDD Gaussian width after convolution. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat: [N×M] matrix of the output 2D parabolic ARPES dispersion. + +%% Default parameters +% Default based on inputs +if nargin < 13; plot_result = 0; end +if nargin < 12; FDW = 0.05; end +if nargin < 11; FDT = 12; end +if nargin < 10; FDEF = 0; end +if nargin < 9; MSTAR = 0.20; end +if nargin < 8; YFWHM = 0.25; end +if nargin < 7; XFWHM = 0.02; end +if nargin < 6; YLOC = 0.00; end +if nargin < 5; XLOC = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 3; cTYPE = "G2DA"; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "G2DA"; end +if isempty(INT); INT = 1.00; end +if isempty(XLOC); XLOC = 0.00; end +if isempty(YLOC); YLOC = 0.00; end +if isempty(XFWHM); XFWHM = 0.02; end +if isempty(YFWHM); YFWHM = 0.25; end +if isempty(MSTAR); MSTAR = 0.20; end +if isempty(FDW); FDW = 0.05; end +if isempty(FDT); FDT = 12; end +if isempty(FDEF); FDEF = 0; end +if isempty(plot_result); plot_result = 0; end + +%% - 1 - Determination of the angle-resolved photoemission spectrum +% Ensuring xdat is a row vector +if size(xdat, 1) > 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1; ydat = ydat'; end +% - Extracting the FDD curve +FDD_curve = FDDG(ydat, FDEF, FDT, FDW); +% - Extracting the ARPES curve +ARPES_curve = ARPESCurveNorm(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR); +% - Multiplying the components together +zdat = ARPES_curve .* FDD_curve; +% int = INT .* (int / max(int)); +% If isnan, return zero +zdat(isnan(zdat)) = 0; + +%% -- For Debugging +if plot_result == 1 + pp = plot_props(); + fig = figure(); + fig.Position(3) = pp.fig4x4(1); fig.Position(4) = pp.fig4x4(2); + hold on; + ImData(xdat, ydat, zdat); + img_props(); title('ARPESCurveNorm_FDDG()', 'Interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDDGpL.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDDGpL.m new file mode 100644 index 0000000..9b0ac29 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDDGpL.m @@ -0,0 +1,91 @@ +function zdat = ARPESCurveNorm_FDDGpL(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO, plot_result) +% zdat = ARPESCurveNorm_FDDGpL(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO, plot_result) +% Function that evaluates a generic angle-resolved photoelectron +% spectroscopy (ARPES) curve in 2D. This can be used to model an ARPES +% spectrum, that is built up by a sum of individual Gaussians. The +% intensity is normalised across all EDCs. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - cTYPE: type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - INT: scalar of the peak intensity of 2D PE curve. +% - XLOC: scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion [Ang^-1]. +% - YLOC: scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion [eV]. +% - XFWHM: scalar of the x-axis FWHM for each Gaussian (k-resolution) [Ang^-1] +% - YFWHM: scalar of the y-axis FWHM for each Gaussian (Eb-resolution) [eV] +% - MSTAR: scalar of the effective mass, which governs the curvature of the parabola. +% - FDEF: scalar of the FDD Fermi-Level position. +% - FDT: scalar of the FDD temperature. +% - FDW: scalar of the FDD Gaussian width after convolution. +% - BGR: scalar of the gradient of the linear background. +% - BIN: scalar of the y-intercept of the linear background. +% - BCO: scalar of the constant background y-offset value. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat: [N×M] matrix of the output 2D parabolic ARPES dispersion. + +%% Default parameters +% Default based on inputs +if nargin < 16; plot_result = 0; end +if nargin < 15; BCO = 0.00; end +if nargin < 14; BIN = 1.00; end +if nargin < 13; BGR = 0.00; end +if nargin < 12; FDW = 0.05; end +if nargin < 11; FDT = 12; end +if nargin < 10; FDEF = 0; end +if nargin < 9; MSTAR = 0.20; end +if nargin < 8; YFWHM = 0.25; end +if nargin < 7; XFWHM = 0.02; end +if nargin < 6; YLOC = 0.00; end +if nargin < 5; XLOC = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 3; cTYPE = "G2DA"; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "G2DA"; end +if isempty(INT); INT = 1.00; end +if isempty(XLOC); XLOC = 0.00; end +if isempty(YLOC); YLOC = 0.00; end +if isempty(XFWHM); XFWHM = 0.02; end +if isempty(YFWHM); YFWHM = 0.25; end +if isempty(MSTAR); MSTAR = 0.20; end +if isempty(FDW); FDW = 0.05; end +if isempty(FDT); FDT = 12; end +if isempty(FDEF); FDEF = 0; end +if isempty(BGR); BGR = 0; end +if isempty(BIN); BIN = 1; end +if isempty(BCO); BCO = 0; end +if isempty(plot_result); plot_result = 0; end + +%% - 1 - Determination of the angle-resolved photoemission spectrum +% Ensuring xdat is a row vector +if size(xdat, 1) > 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1; ydat = ydat'; end +% - Extracting the FDD curve +FDD_curve = FDDG(ydat, FDEF, FDT, FDW); +% - Extracting the ARPES curve +ARPES_curve = ARPESCurveNorm(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR); +% - Multiplying the components together +zdat = (ARPES_curve + BGR.*ydat+BIN) .* FDD_curve + BCO; +% int = INT .* (int / max(int)); +% If isnan, return zero +zdat(isnan(zdat)) = 0; + +%% -- For Debugging +if plot_result == 1 + pp = plot_props(); + fig = figure(); + fig.Position(3) = pp.fig4x4(1); fig.Position(4) = pp.fig4x4(2); + hold on; + ImData(xdat, ydat, zdat); + img_props(); title('ARPESCurveNorm_FDDGpL()', 'Interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDDGsL.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDDGsL.m new file mode 100644 index 0000000..ce7f516 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurveNorm_FDDGsL.m @@ -0,0 +1,91 @@ +function zdat = ARPESCurveNorm_FDDGsL(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO, plot_result) +% zdat = ARPESCurveNorm_FDDGsL(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO, plot_result) +% Function that evaluates a generic angle-resolved photoelectron +% spectroscopy (ARPES) curve in 2D. This can be used to model an ARPES +% spectrum, that is built up by a sum of individual Gaussians. The +% intensity is normalised across all EDCs. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - cTYPE: type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - INT: scalar of the peak intensity of 2D PE curve. +% - XLOC: scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion [Ang^-1]. +% - YLOC: scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion [eV]. +% - XFWHM: scalar of the x-axis FWHM for each Gaussian (k-resolution) [Ang^-1] +% - YFWHM: scalar of the y-axis FWHM for each Gaussian (Eb-resolution) [eV] +% - MSTAR: scalar of the effective mass, which governs the curvature of the parabola. +% - FDEF: scalar of the FDD Fermi-Level position. +% - FDT: scalar of the FDD temperature. +% - FDW: scalar of the FDD Gaussian width after convolution. +% - BGR: scalar of the gradient of the linear background. +% - BIN: scalar of the y-intercept of the linear background. +% - BCO: scalar of the constant background y-offset value. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat: [N×M] matrix of the output 2D parabolic ARPES dispersion. + +%% Default parameters +% Default based on inputs +if nargin < 16; plot_result = 0; end +if nargin < 15; BCO = 0.00; end +if nargin < 14; BIN = 1.00; end +if nargin < 13; BGR = 0.00; end +if nargin < 12; FDW = 0.05; end +if nargin < 11; FDT = 12; end +if nargin < 10; FDEF = 0; end +if nargin < 9; MSTAR = 0.20; end +if nargin < 8; YFWHM = 0.25; end +if nargin < 7; XFWHM = 0.02; end +if nargin < 6; YLOC = 0.00; end +if nargin < 5; XLOC = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 3; cTYPE = "G2DA"; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "G2DA"; end +if isempty(INT); INT = 1.00; end +if isempty(XLOC); XLOC = 0.00; end +if isempty(YLOC); YLOC = 0.00; end +if isempty(XFWHM); XFWHM = 0.02; end +if isempty(YFWHM); YFWHM = 0.25; end +if isempty(MSTAR); MSTAR = 0.20; end +if isempty(FDW); FDW = 0.05; end +if isempty(FDT); FDT = 12; end +if isempty(FDEF); FDEF = 0; end +if isempty(BGR); BGR = 0; end +if isempty(BIN); BIN = 1; end +if isempty(BCO); BCO = 0; end +if isempty(plot_result); plot_result = 0; end + +%% - 1 - Determination of the angle-resolved photoemission spectrum +% Ensuring xdat is a row vector +if size(xdat, 1) > 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1; ydat = ydat'; end +% - Extracting the FDD curve +FDD_curve = FDDG(ydat, FDEF, FDT, FDW); +% - Extracting the ARPES curve +ARPES_curve = ARPESCurveNorm(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR); +% - Multiplying the components together +zdat = ARPES_curve.* (FDD_curve + BGR.*ydat) + BIN + BCO; +% int = INT .* (int / max(int)); +% If isnan, return zero +zdat(isnan(zdat)) = 0; + +%% -- For Debugging +if plot_result == 1 + pp = plot_props(); + fig = figure(); + fig.Position(3) = pp.fig4x4(1); fig.Position(4) = pp.fig4x4(2); + hold on; + ImData(xdat, ydat, zdat); + img_props(); title('ARPESCurveNorm_FDDGsL()', 'Interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDD.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDD.m new file mode 100644 index 0000000..bba8c55 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDD.m @@ -0,0 +1,78 @@ +function zdat = ARPESCurve_FDD(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, plot_result) +% zdat = ARPESCurve_FDD(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, plot_result) +% Function that evaluates a generic angle-resolved photoelectron +% spectroscopy (ARPES) curve in 2D. This can be used to model an ARPES +% spectrum, that is built up by a sum of individual Gaussians. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - cTYPE: type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - INT: scalar of the peak intensity of 2D PE curve. +% - XLOC: scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion [Ang^-1]. +% - YLOC: scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion [eV]. +% - XFWHM: scalar of the x-axis FWHM for each Gaussian (k-resolution) [Ang^-1] +% - YFWHM: scalar of the y-axis FWHM for each Gaussian (Eb-resolution) [eV] +% - MSTAR: scalar of the effective mass, which governs the curvature of the parabola. +% - FDEF: scalar of the FDD Fermi-Level position. +% - FDT: scalar of the FDD temperature. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat: [N×M] matrix of the output 2D parabolic ARPES dispersion. + +%% Default parameters +% Default based on inputs +if nargin < 12; plot_result = 0; end +if nargin < 11; FDT = 12; end +if nargin < 10; FDEF = 0; end +if nargin < 9; MSTAR = 0.20; end +if nargin < 8; YFWHM = 0.25; end +if nargin < 7; XFWHM = 0.02; end +if nargin < 6; YLOC = 0.00; end +if nargin < 5; XLOC = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 3; cTYPE = "G2DA"; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "G2DA"; end +if isempty(INT); INT = 1.00; end +if isempty(XLOC); XLOC = 0.00; end +if isempty(YLOC); YLOC = 0.00; end +if isempty(XFWHM); XFWHM = 0.02; end +if isempty(YFWHM); YFWHM = 0.25; end +if isempty(MSTAR); MSTAR = 0.20; end +if isempty(FDT); FDT = 12; end +if isempty(FDEF); FDEF = 0; end +if isempty(plot_result); plot_result = 0; end + +%% - 1 - Determination of the angle-resolved photoemission spectrum +% Ensuring xdat is a row vector +if size(xdat, 1) > 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1; ydat = ydat'; end +% - Extracting the FDD curve +FDD_curve = FDD(ydat, FDEF, FDT); +% - Extracting the ARPES curve +ARPES_curve = ARPESCurve(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR); +% - Multiplying the components together +zdat = ARPES_curve .* FDD_curve; +% int = INT .* (int / max(int)); +% If isnan, return zero +zdat(isnan(zdat)) = 0; + +%% -- For Debugging +if plot_result == 1 + pp = plot_props(); + fig = figure(); + fig.Position(3) = pp.fig4x4(1); fig.Position(4) = pp.fig4x4(2); + hold on; + ImData(xdat, ydat, zdat); + img_props(); title('ARPESCurve_FDD()', 'Interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDDG.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDDG.m new file mode 100644 index 0000000..c601d2e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDDG.m @@ -0,0 +1,81 @@ +function zdat = ARPESCurve_FDDG(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, plot_result) +% zdat = ARPESCurve_FDDG(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, plot_result) +% Function that evaluates a generic angle-resolved photoelectron +% spectroscopy (ARPES) curve in 2D. This can be used to model an ARPES +% spectrum, that is built up by a sum of individual Gaussians. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - cTYPE: type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - INT: scalar of the peak intensity of 2D PE curve. +% - XLOC: scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion [Ang^-1]. +% - YLOC: scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion [eV]. +% - XFWHM: scalar of the x-axis FWHM for each Gaussian (k-resolution) [Ang^-1] +% - YFWHM: scalar of the y-axis FWHM for each Gaussian (Eb-resolution) [eV] +% - MSTAR: scalar of the effective mass, which governs the curvature of the parabola. +% - FDEF: scalar of the FDD Fermi-Level position. +% - FDT: scalar of the FDD temperature. +% - FDW: scalar of the FDD Gaussian width after convolution. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat: [N×M] matrix of the output 2D parabolic ARPES dispersion. + +%% Default parameters +% Default based on inputs +if nargin < 13; plot_result = 0; end +if nargin < 12; FDW = 0.05; end +if nargin < 11; FDT = 12; end +if nargin < 10; FDEF = 0; end +if nargin < 9; MSTAR = 0.20; end +if nargin < 8; YFWHM = 0.25; end +if nargin < 7; XFWHM = 0.02; end +if nargin < 6; YLOC = 0.00; end +if nargin < 5; XLOC = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 3; cTYPE = "G2DA"; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "G2DA"; end +if isempty(INT); INT = 1.00; end +if isempty(XLOC); XLOC = 0.00; end +if isempty(YLOC); YLOC = 0.00; end +if isempty(XFWHM); XFWHM = 0.02; end +if isempty(YFWHM); YFWHM = 0.25; end +if isempty(MSTAR); MSTAR = 0.20; end +if isempty(FDW); FDW = 0.05; end +if isempty(FDT); FDT = 12; end +if isempty(FDEF); FDEF = 0; end +if isempty(plot_result); plot_result = 0; end + +%% - 1 - Determination of the angle-resolved photoemission spectrum +% Ensuring xdat is a row vector +if size(xdat, 1) > 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1; ydat = ydat'; end +% - Extracting the FDD curve +FDD_curve = FDDG(ydat, FDEF, FDT, FDW); +% - Extracting the ARPES curve +ARPES_curve = ARPESCurve(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR); +% - Multiplying the components together +zdat = ARPES_curve .* FDD_curve; +% int = INT .* (int / max(int)); +% If isnan, return zero +zdat(isnan(zdat)) = 0; + +%% -- For Debugging +if plot_result == 1 + pp = plot_props(); + fig = figure(); + fig.Position(3) = pp.fig4x4(1); fig.Position(4) = pp.fig4x4(2); + hold on; + ImData(xdat, ydat, zdat); + img_props(); title('ARPESCurve_FDDG()', 'Interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDDGpL.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDDGpL.m new file mode 100644 index 0000000..36deb19 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDDGpL.m @@ -0,0 +1,90 @@ +function zdat = ARPESCurve_FDDGpL(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO, plot_result) +% zdat = ARPESCurve_FDDGpL(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO, plot_result) +% Function that evaluates a generic angle-resolved photoelectron +% spectroscopy (ARPES) curve in 2D. This can be used to model an ARPES +% spectrum, that is built up by a sum of individual Gaussians. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - cTYPE: type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - INT: scalar of the peak intensity of 2D PE curve. +% - XLOC: scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion [Ang^-1]. +% - YLOC: scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion [eV]. +% - XFWHM: scalar of the x-axis FWHM for each Gaussian (k-resolution) [Ang^-1] +% - YFWHM: scalar of the y-axis FWHM for each Gaussian (Eb-resolution) [eV] +% - MSTAR: scalar of the effective mass, which governs the curvature of the parabola. +% - FDEF: scalar of the FDD Fermi-Level position. +% - FDT: scalar of the FDD temperature. +% - FDW: scalar of the FDD Gaussian width after convolution. +% - BGR: scalar of the gradient of the linear background. +% - BIN: scalar of the y-intercept of the linear background. +% - BCO: scalar of the constant background y-offset value. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat: [N×M] matrix of the output 2D parabolic ARPES dispersion. + +%% Default parameters +% Default based on inputs +if nargin < 16; plot_result = 0; end +if nargin < 15; BCO = 0.00; end +if nargin < 14; BIN = 1.00; end +if nargin < 13; BGR = 0.00; end +if nargin < 12; FDW = 0.05; end +if nargin < 11; FDT = 12; end +if nargin < 10; FDEF = 0; end +if nargin < 9; MSTAR = 0.20; end +if nargin < 8; YFWHM = 0.25; end +if nargin < 7; XFWHM = 0.02; end +if nargin < 6; YLOC = 0.00; end +if nargin < 5; XLOC = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 3; cTYPE = "G2DA"; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "G2DA"; end +if isempty(INT); INT = 1.00; end +if isempty(XLOC); XLOC = 0.00; end +if isempty(YLOC); YLOC = 0.00; end +if isempty(XFWHM); XFWHM = 0.02; end +if isempty(YFWHM); YFWHM = 0.25; end +if isempty(MSTAR); MSTAR = 0.20; end +if isempty(FDW); FDW = 0.05; end +if isempty(FDT); FDT = 12; end +if isempty(FDEF); FDEF = 0; end +if isempty(BGR); BGR = 0; end +if isempty(BIN); BIN = 1; end +if isempty(BCO); BCO = 0; end +if isempty(plot_result); plot_result = 0; end + +%% - 1 - Determination of the angle-resolved photoemission spectrum +% Ensuring xdat is a row vector +if size(xdat, 1) > 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1; ydat = ydat'; end +% - Extracting the FDD curve +FDD_curve = FDDG(ydat, FDEF, FDT, FDW); +% - Extracting the ARPES curve +ARPES_curve = ARPESCurve(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR); +% - Multiplying the components together +zdat = (ARPES_curve + BGR.*ydat+BIN) .* FDD_curve + BCO; +% int = INT .* (int / max(int)); +% If isnan, return zero +zdat(isnan(zdat)) = 0; + +%% -- For Debugging +if plot_result == 1 + pp = plot_props(); + fig = figure(); + fig.Position(3) = pp.fig4x4(1); fig.Position(4) = pp.fig4x4(2); + hold on; + ImData(xdat, ydat, zdat); + img_props(); title('ARPESCurve_FDDGpL()', 'Interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDDGsL.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDDGsL.m new file mode 100644 index 0000000..87d7206 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/ARPESCurve_FDDGsL.m @@ -0,0 +1,90 @@ +function zdat = ARPESCurve_FDDGsL(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO, plot_result) +% zdat = ARPESCurve_FDDGsL(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO, plot_result) +% Function that evaluates a generic angle-resolved photoelectron +% spectroscopy (ARPES) curve in 2D. This can be used to model an ARPES +% spectrum, that is built up by a sum of individual Gaussians. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - cTYPE: type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - INT: scalar of the peak intensity of 2D PE curve. +% - XLOC: scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion [Ang^-1]. +% - YLOC: scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion [eV]. +% - XFWHM: scalar of the x-axis FWHM for each Gaussian (k-resolution) [Ang^-1] +% - YFWHM: scalar of the y-axis FWHM for each Gaussian (Eb-resolution) [eV] +% - MSTAR: scalar of the effective mass, which governs the curvature of the parabola. +% - FDEF: scalar of the FDD Fermi-Level position. +% - FDT: scalar of the FDD temperature. +% - FDW: scalar of the FDD Gaussian width after convolution. +% - BGR: scalar of the gradient of the linear background. +% - BIN: scalar of the y-intercept of the linear background. +% - BCO: scalar of the constant background y-offset value. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat: [N×M] matrix of the output 2D parabolic ARPES dispersion. + +%% Default parameters +% Default based on inputs +if nargin < 16; plot_result = 0; end +if nargin < 15; BCO = 0.00; end +if nargin < 14; BIN = 1.00; end +if nargin < 13; BGR = 0.00; end +if nargin < 12; FDW = 0.05; end +if nargin < 11; FDT = 12; end +if nargin < 10; FDEF = 0; end +if nargin < 9; MSTAR = 0.20; end +if nargin < 8; YFWHM = 0.25; end +if nargin < 7; XFWHM = 0.02; end +if nargin < 6; YLOC = 0.00; end +if nargin < 5; XLOC = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 3; cTYPE = "G2DA"; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "G2DA"; end +if isempty(INT); INT = 1.00; end +if isempty(XLOC); XLOC = 0.00; end +if isempty(YLOC); YLOC = 0.00; end +if isempty(XFWHM); XFWHM = 0.02; end +if isempty(YFWHM); YFWHM = 0.25; end +if isempty(MSTAR); MSTAR = 0.20; end +if isempty(FDW); FDW = 0.05; end +if isempty(FDT); FDT = 12; end +if isempty(FDEF); FDEF = 0; end +if isempty(BGR); BGR = 0; end +if isempty(BIN); BIN = 1; end +if isempty(BCO); BCO = 0; end +if isempty(plot_result); plot_result = 0; end + +%% - 1 - Determination of the angle-resolved photoemission spectrum +% Ensuring xdat is a row vector +if size(xdat, 1) > 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1; ydat = ydat'; end +% - Extracting the FDD curve +FDD_curve = FDDG(ydat, FDEF, FDT, FDW); +% - Extracting the ARPES curve +ARPES_curve = ARPESCurve(xdat, ydat, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR); +% - Multiplying the components together +zdat = ARPES_curve.* (FDD_curve + BGR.*ydat) + BIN + BCO; +% int = INT .* (int / max(int)); +% If isnan, return zero +zdat(isnan(zdat)) = 0; + +%% -- For Debugging +if plot_result == 1 + pp = plot_props(); + fig = figure(); + fig.Position(3) = pp.fig4x4(1); fig.Position(4) = pp.fig4x4(2); + hold on; + ImData(xdat, ydat, zdat); + img_props(); title('ARPESCurve_FDDGsL()', 'Interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/G2D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/G2D.m new file mode 100644 index 0000000..6ef14cb --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/G2D.m @@ -0,0 +1,49 @@ +function int = G2D(xdat, ydat, peak, x0, y0, fwhm) +% int = G2D(xdat, ydat, peak, x0, y0, fwhm) +% Function that evaluates a 2D Gaussian curve after defining its amplitude +% and position in the x- and y-axis. The function assumes that the FWHM +% is identical both in the x- and y-dimensions. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - peak: scalar of the maximum peak height of the Gaussian. +% - x0: scalar of the peak position along the x-axis of the Gaussian. +% - y0: scalar of the peak position along the y-axis of the Gaussian. +% - fwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian along both x- and y-axes. +% +% OUT: +% - int: [N×M] array of the output Gaussian spot profile + +%% Default parameters +if nargin < 6; fwhm = 1; end +if nargin < 5; y0 = 0; end +if nargin < 4; x0 = 0; end +if nargin < 3; peak = 1; end +if isempty(fwhm); fwhm = 1; end +if isempty(y0); y0 = 0; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +% Validity check on inputs +if peak < 0; peak = 0; end +if fwhm < 0; fwhm = 0; end + +%% - 1 - Determination of the Gaussian curve intensities +% Ensuring xdat is a row vector +if size(xdat, 1) > 1 && size(xdat, 2) == 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1 && size(ydat, 1) == 1; ydat = ydat'; end +% Using the standard deviation as the input width so that the FWHM is correct +xsigma = fwhm ./ (2*sqrt(2*log(2))); +ysigma = fwhm ./ (2*sqrt(2*log(2))); +% Evaluating the normalised curve profile +int = (1 ./ (xsigma * sqrt(2*pi))) .* (1 ./ (ysigma * sqrt(2*pi))) .* exp(-0.5.*(((xdat-x0)./xsigma).^2 + ((ydat-y0)./ysigma).^2)); +% Scaling the curve profile to match the desired peak +int = int ./ max(int(:)); +int = peak .* int; +% If isnan, return zero +int(isnan(int)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/G2DA.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/G2DA.m new file mode 100644 index 0000000..31eacb6 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/G2DA.m @@ -0,0 +1,52 @@ +function int = G2DA(xdat, ydat, peak, x0, y0, xfwhm, yfwhm) +% int = G2DA(xdat, ydat, peak, x0, y0, xfwhm, yfwhm) +% Function that evaluates a 2D Gaussian curve after defining its position, +% full-width at half-maximum (FWHM) and amplitude in both the x- and +% y-axis. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - peak: scalar of the maximum peak height of the Gaussian. +% - x0: scalar of the peak position along the x-axis of the Gaussian. +% - y0: scalar of the peak position along the y-axis of the Gaussian. +% - xfwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian along the x-axis. +% - yfwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian along the y-axis. +% +% OUT: +% - int: [N×M] array of the output Asymetrical Gaussian spot profile + +%% Default parameters +if nargin < 7; yfwhm = 1; end +if nargin < 6; xfwhm = 1; end +if nargin < 5; y0 = 0; end +if nargin < 4; x0 = 0; end +if nargin < 3; peak = 1; end +if isempty(yfwhm); yfwhm = 1; end +if isempty(xfwhm); xfwhm = 1; end +if isempty(y0); y0 = 0; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +% Validity check on inputs +if peak < 0; peak = 0; end +if xfwhm < 0; xfwhm = 0; end +if yfwhm < 0; yfwhm = 0; end + +%% - 1 - Determination of the Gaussian curve intensities +% Ensuring xdat is a row vector +if size(xdat, 1) > 1 && size(xdat, 2) == 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1 && size(ydat, 1) == 1; ydat = ydat'; end +% Using the standard deviation as the input width so that the FWHM is correct +xsigma = xfwhm ./ (2*sqrt(2*log(2))); +ysigma = yfwhm ./ (2*sqrt(2*log(2))); +% Evaluating the normalised curve profile +int = (1 ./ (xsigma * sqrt(2*pi))) .* (1 ./ (ysigma * sqrt(2*pi))) .* exp(-0.5.*(((xdat-x0)./xsigma).^2 + ((ydat-y0)./ysigma).^2)); +% Scaling the curve profile to match the desired peak +int = int ./ max(int(:)); +int = peak .* int; +% If isnan, return zero +int(isnan(int)) = 0; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/L2D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/L2D.m new file mode 100644 index 0000000..69d8301 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/L2D.m @@ -0,0 +1,45 @@ +function int = L2D(xdat, ydat, peak, x0, y0, fwhm) +% int = L2D(xdat, ydat, peak, x0, y0, fwhm) +% Function that evaluates a 2D Lorentzian curve after defining its amplitude +% and position in the x- and y-axis. The function assumes that the FWHM +% is identical both in the x- and y-dimensions. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [1×M] row vector of the x-axis input domain (kx for ARPES) +% - ydat: [N×1] column vector of the y-axis input domain (Eb for ARPES) +% - peak: scalar of the maximum peak height of the Lorentzian. +% - x0: scalar of the peak position along the x-axis of the Lorentzian. +% - y0: scalar of the peak position along the y-axis of the Lorentzian. +% - fwhm: scalar of the full-width at half-maximum (FWHM) of the Lorentzian along both x- and y-axes. +% +% OUT: +% - int: [N×M] array of the output Lorentzian spot profile + +%% Default parameters +if nargin < 6; fwhm = 1; end +if nargin < 5; y0 = 0; end +if nargin < 4; x0 = 0; end +if nargin < 3; peak = 1; end +if isempty(fwhm); fwhm = 1; end +if isempty(y0); y0 = 0; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +% Validity check on inputs +if peak < 0; peak = 0; end +if fwhm < 0; fwhm = 0; end + +%% - 1 - Determination of the Lorentzian curve intensities +% Ensuring xdat is a row vector +if size(xdat, 1) > 1 && size(xdat, 2) == 1; xdat = xdat'; end +% Ensuring ydat is a column vector +if size(ydat, 2) > 1 && size(ydat, 1) == 1; ydat = ydat'; end +% Evaluating the normalised curve profile +int = (peak .* 0.5*fwhm./pi) ./ ((xdat - x0).^2 + (ydat - y0).^2 + (0.5*fwhm).^2).^1.5; +% Scaling the curve profile to match the desired peak +int = int ./ max(int(:)); +int = peak .* int; +% If isnan, return zero +int(isnan(int)) = 0; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/eb_calc.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/eb_calc.m new file mode 100644 index 0000000..814a5bf --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/eb_calc.m @@ -0,0 +1,35 @@ +function eb = eb_calc(k, k0, eb0, mstar) +% eb = eb_calc(k, k0, eb0, mstar) +% Function that evaluates the binding energy of a parabolic dispersion; +% k0, eb0 are the initial values at the base of the parabola and mstar +% defines the curvature of the parabolic disperison. +% +% REQ. FUNCTIONS: none +% +% IN: +% - k: Nx1 vector that yields the wave-vector values [Ang^-1]. +% - k0: scalar of the initial wave-vector at eb = 0 eV [Ang^-1]. +% - eb0: scalar of the initial binding energy at k = 0 Ang^-1 [eV]. +% - mstar: scalar of the effective mass which defines the curvature of the parabola [mstar*me]. +% +% OUT: +% - eb: Nx1 vector that yields the binding energy values [eV]. + +%% Default parameters +if nargin < 4; mstar = 1; end +if nargin < 3; eb0 = 0; end +if nargin < 2; k0 = 0; end +if isempty(mstar); mstar = 1; end +if isempty(eb0); eb0 = 0; end +if isempty(k0); k0 = 0; end + +%% - 1 - Determination of the output wave-vectors +% Ensuring eb is a column vector +if size(k, 2) > 1 && size(k, 1) == 1; k = k'; end +% Defining the physical constants +hbar = 4.135e-15; % Units of [eV s^−1] +% Calculating the binding energy values +eb = (3.8 / mstar) * (k - k0).^2 + eb0; +% If isnan, return zero +eb(isnan(eb)) = 0; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/k_calc.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/k_calc.m new file mode 100644 index 0000000..544f8b9 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/arpes model curves/k_calc.m @@ -0,0 +1,36 @@ +function k = k_calc(eb, k0, eb0, mstar) +% k = k_calc(eb, k0, eb0, mstar) +% Function that evaluates the wave-vector of a parabolic dispersion; +% k0, eb0 are the initial values at the base of the parabola and mstar +% defines the curvature of the parabolic disperison. +% +% REQ. FUNCTIONS: none +% +% IN: +% - eb: Nx1 vector that yields the binding energy values [eV]. +% - k0: scalar of the initial wave-vector at eb = 0 eV [Ang^-1]. +% - eb0: scalar of the initial binding energy at k = 0 Ang^-1 [eV]. +% - mstar: scalar of the effective mass which defines the curvature of the parabola [mstar*me]. +% +% OUT: +% - k: Nx1 vector of the output wave-vector, k, values [Ang^-1]. + +%% Default parameters +if nargin < 4; mstar = 1; end +if nargin < 3; eb0 = 0; end +if nargin < 2; k0 = 0; end +if isempty(mstar); mstar = 1; end +if isempty(eb0); eb0 = 0; end +if isempty(k0); k0 = 0; end + +%% - 1 - Determination of the output wave-vectors +% Ensuring eb is a column vector +if size(eb, 2) > 1 && size(eb, 1) == 1; eb = eb'; end +% Defining the physical constants +hbar = 4.135e-15; % Units of [eV s^−1] +% Calculating the wave-vector values +k = sqrt((mstar / 3.8180) .* (eb - eb0)) + k0; +k = real(k); +% If isnan, return zero +k(isnan(k)) = 0; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndPoly.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndPoly.m new file mode 100644 index 0000000..10bfa9d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndPoly.m @@ -0,0 +1,147 @@ +function [roi_xdat, roi_ydat, roi_bgrnd] = BgrndPoly(xdat, ydat, polyOrder, lhsVal, rhsVal, lhsWin, rhsWin, plot_result) +% [roi_xdat, roi_ydat, roi_bgrnd] = BgrndPoly(xdat, ydat, polyOrder, lhsVal, rhsVal, lhsWin, rhsWin, plot_result) +% Function that determines the best fit to the background of PES (or 1D) +% data using a polynomial function. The output is a column vector containing +% the background intensity, and the new domain and intensity of the data +% within the defined region of interest. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES) +% - ydat: N×1 column vector of the intensity range (intensity for PES) +% - polyOrder: scalar, positive integer of the Polynomial Order. +% - lhsVal: scalar of the LHS x-axis start position of the ROI. +% - rhsVal: scalar of the RHS x-axis end position of the ROI. +% - lhsWin: scalar of the LHS window size around the start position. +% - rhsWin: scalar of the RHS window size around the end position. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - roi_xdat: M×1 column vector of the ROI x-domain (binding energy for PES). +% - roi_ydat: M×1 column vector of the ROI y-values (intensity for PES). +% - roi_bgrnd: M×1 column vector of the best fit polynomial background to the ROI data. + +%% Default parameters +% - Setting the default conditions +if nargin < 3; polyOrder = 1; end +if nargin < 4; lhsVal = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if nargin < 5; rhsVal = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if nargin < 6; lhsWin = abs(0.02*range(xdat(:))); end +if nargin < 7; rhsWin = abs(0.02*range(xdat(:))); end +if nargin < 8; plot_result = 0; end +if isempty(polyOrder); polyOrder = 1; end +if isempty(lhsVal); lhsVal = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if isempty(rhsVal); rhsVal = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if isempty(lhsWin); lhsWin = abs(0.02*range(xdat(:))); end +if isempty(rhsWin); rhsWin = abs(0.02*range(xdat(:))); end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +% -- Making sure that the polynomial order is an integer value +polyOrder = floor(polyOrder(1)); +% -- If a vector / array of the LHS and RHS are entered, only select the first value +if length(lhsVal) > 1 + disp('Warning: lhsVal is defined as a vector, only choosing the first element.'); + lhsVal = lhsVal(1); +end +if length(rhsVal) > 1 + disp('Warning: rhsVal is defined as a vector, only choosing the first element.'); + rhsVal = rhsVal(1); +end +% -- If the LHS value is smaller than the RHS value, switch the assignment +if lhsVal > rhsVal + disp('Warning: lhsVal > rhsVal, values have been switched.'); + A = lhsVal; Awin = lhsWin; + B = rhsVal; Bwin = rhsWin; + lhsVal = B; lhsVal = Bwin; + rhsVal = A; rhsVal = Awin; +% -- If the LHS and RHS values are identical, no window can be defined +elseif lhsVal == rhsVal + error('Error: lhsVal == rhsVal, make sure you define a finite window size for the ROI.'); +end +% -- If a vector / array of the LHS and RHS windows are entered, only select the first value +if length(lhsWin) > 1 + disp('Warning: lhsWin is defined as a vector, only choosing the first element.'); + lhsWin = lhsWin(1); +end +if length(rhsWin) > 1 + disp('Warning: rhsWin is defined as a vector, only choosing the first element.'); + rhsWin = rhsWin(1); +end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% - 1 - Extracting the index START and END point of the background +% -- LHS index points +[~, lhsIndx_mu] = min(abs(xdat - lhsVal)); +[~, lhsIndx_lb] = min(abs(xdat - lhsVal - lhsWin)); +[~, lhsIndx_ub] = min(abs(xdat - lhsVal + lhsWin)); +% -- RHS index points +[~, rhsIndx_mu] = min(abs(xdat - rhsVal)); +[~, rhsIndx_lb] = min(abs(xdat - rhsVal - rhsWin)); +[~, rhsIndx_ub] = min(abs(xdat - rhsVal + rhsWin)); +% - ROI indexes +roi_indx = sort([lhsIndx_mu, rhsIndx_mu]); +lhsWin_indx = sort([lhsIndx_lb, lhsIndx_ub]); +rhsWin_indx = sort([rhsIndx_lb, rhsIndx_ub]); + +%% - 2 - Cropping the data over the ROI whose background is extracted +roi_xdat = xdat(roi_indx(1):roi_indx(2)); +roi_ydat = ydat(roi_indx(1):roi_indx(2)); +nRows = length(roi_xdat); + +%% - 3 - Determination of the Polynomial Background +% -- Extracting the data to be fitted with linear expressions +xdat_bgrnd = [xdat(lhsWin_indx(1):lhsWin_indx(2)); xdat(rhsWin_indx(1):rhsWin_indx(2))]; +ydat_bgrnd = [ydat(lhsWin_indx(1):lhsWin_indx(2)); ydat(rhsWin_indx(1):rhsWin_indx(2))]; +% -- Fitting the data to a polynomial of the correct order +fitType = char("poly" + string(floor(polyOrder))); +if polyOrder == 0 + % -- For zero-order polynomial, only use a constant line + roi_bgrnd = mean(ydat_bgrnd(:)).*ones(size(roi_xdat)); +else + % -- Fitting the data to a polynomial of the correct order + fitResult = fit(xdat_bgrnd, ydat_bgrnd, fitType); + % -- Extracting the background over a consistent domain + roi_bgrnd = fitResult(roi_xdat); +end +% -- Verifying outputs are all column vectors +if size(roi_xdat, 2) > 1; roi_xdat = roi_xdat'; end +if size(roi_ydat, 2) > 1; roi_ydat = roi_ydat'; end +if size(roi_bgrnd, 2) > 1; roi_bgrnd = roi_bgrnd'; end + +%% -- For Debugging +if plot_result == 1 + % - Initialising the figure object + figure(); hold on; + % -- Plotting the ROI, LHS and RHS analysis windows + ROI = [xdat(roi_indx(1)), xdat(roi_indx(2))]; + LHS = [xdat(lhsWin_indx(1)), xdat(lhsWin_indx(2))]; + RHS = [xdat(rhsWin_indx(1)), xdat(rhsWin_indx(2))]; + hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e4, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); + hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; + hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e4, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); + hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; + hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e4, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); + hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Plotting a vertical line to show the ROI + a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); + a.Annotation.LegendInformation.IconDisplayStyle = 'off'; + b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); + b.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Plotting the 1D data + plot(xdat, ydat, 'b-', 'linewidth', 0.5); + plot(roi_xdat, roi_ydat, 'b-', 'linewidth', 2); + plot(roi_xdat, roi_bgrnd, 'r-', 'linewidth', 2); + plot(roi_xdat, roi_ydat-roi_bgrnd, 'k-', 'linewidth', 2); + gca_props(); title('BgrndPoly()'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); + % -- Determining the best limits for the plot + axLim_y = [roi_ydat; roi_ydat-roi_bgrnd]; + axis([min(xdat(:)), max(xdat(:)), min(axLim_y(:)), max(axLim_y(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndShirley.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndShirley.m new file mode 100644 index 0000000..a212ced --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndShirley.m @@ -0,0 +1,163 @@ +function [roi_xdat, roi_ydat, roi_bgrnd] = BgrndShirley(xdat, ydat, lhsVal, rhsVal, lhsWin, rhsWin, plot_result) +% [roi_xdat, roi_ydat, roi_bgrnd] = BgrndShirley(xdat, ydat, lhsVal, rhsVal, lhsWin, rhsWin, plot_result) +% Function that determines the best fit to the background of PES (or 1D) +% data using a Shirley function. The output is a column vector containing +% the background intensity, and the new domain and intensity of the data +% within the defined region of interest. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES) +% - ydat: N×1 column vector of the intensity range (intensity for PES) +% - lhsVal: scalar of the LHS x-axis start position of the ROI. +% - rhsVal: scalar of the RHS x-axis end position of the ROI. +% - lhsWin: scalar of the LHS window size around the start position. +% - rhsWin: scalar of the RHS window size around the end position. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - roi_xdat: M×1 column vector of the ROI x-domain (binding energy for PES). +% - roi_ydat: M×1 column vector of the ROI y-values (intensity for PES). +% - roi_bgrnd: M×1 column vector of the best fit Shirley background to the ROI data. + +%% Default parameters +% - Setting the default conditions +if nargin < 3; lhsVal = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if nargin < 4; rhsVal = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if nargin < 5; lhsWin = abs(0.02*range(xdat(:))); end +if nargin < 6; rhsWin = abs(0.02*range(xdat(:))); end +if nargin < 7; plot_result = 0; end +if isempty(lhsVal); lhsVal = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if isempty(rhsVal); rhsVal = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if isempty(lhsWin); lhsWin = abs(0.02*range(xdat(:))); end +if isempty(rhsWin); rhsWin = abs(0.02*range(xdat(:))); end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +% -- If a vector / array of the LHS and RHS are entered, only select the first value +if length(lhsVal) > 1 + disp('Warning: lhsVal is defined as a vector, only choosing the first element.'); + lhsVal = lhsVal(1); +end +if length(rhsVal) > 1 + disp('Warning: rhsVal is defined as a vector, only choosing the first element.'); + rhsVal = rhsVal(1); +end +% -- If the LHS value is smaller than the RHS value, switch the assignment +if lhsVal > rhsVal + disp('Warning: lhsVal > rhsVal, values have been switched.'); + A = lhsVal; Awin = lhsWin; + B = rhsVal; Bwin = rhsWin; + lhsVal = B; lhsVal = Bwin; + rhsVal = A; rhsVal = Awin; +% -- If the LHS and RHS values are identical, no window can be defined +elseif lhsVal == rhsVal + error('Error: lhsVal == rhsVal, make sure you define a finite window size for the ROI.'); +end +% -- If a vector / array of the LHS and RHS windows are entered, only select the first value +if length(lhsWin) > 1 + disp('Warning: lhsWin is defined as a vector, only choosing the first element.'); + lhsWin = lhsWin(1); +end +if length(rhsWin) > 1 + disp('Warning: rhsWin is defined as a vector, only choosing the first element.'); + rhsWin = rhsWin(1); +end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% - 1 - Extracting the index START and END point of the background +% -- LHS index points +[~, lhsIndx_mu] = min(abs(xdat - lhsVal)); +[~, lhsIndx_lb] = min(abs(xdat - lhsVal - lhsWin)); +[~, lhsIndx_ub] = min(abs(xdat - lhsVal + lhsWin)); +% -- RHS index points +[~, rhsIndx_mu] = min(abs(xdat - rhsVal)); +[~, rhsIndx_lb] = min(abs(xdat - rhsVal - rhsWin)); +[~, rhsIndx_ub] = min(abs(xdat - rhsVal + rhsWin)); +% - ROI indexes +roi_indx = sort([lhsIndx_mu, rhsIndx_mu]); +lhsWin_indx = sort([lhsIndx_lb, lhsIndx_ub]); +rhsWin_indx = sort([rhsIndx_lb, rhsIndx_ub]); + +%% - 2 - Cropping the data over the ROI whose background is extracted +roi_xdat = xdat(roi_indx(1):roi_indx(2)); +roi_ydat = ydat(roi_indx(1):roi_indx(2)); +nRows = length(roi_xdat); + +%% - 3 - Extracting the mean value of the step heights of the Shirley background +% -- Extracting a small range for averaging the intensity values +I1 = mean(ydat(lhsWin_indx(1):lhsWin_indx(2))); +I2 = mean(ydat(rhsWin_indx(1):rhsWin_indx(2))); + +%% - 4 - Determination of the Shirley Background +% - Initialising the variables +Intensity = {}; +ShirBgrnd = {}; +% - Iterate 12 times to determine Shirley background +for N = 1:12 + % -- Create an initial guess of the background (use linear background) + if N == 1 + [~, ~, ShirBgrnd{1}] = BgrndPoly(xdat, ydat, 1, lhsVal, rhsVal, lhsWin, rhsWin); + Intensity{1} = roi_ydat - ShirBgrnd{1}; + % -- After initial guess, iterate to solution + else + % --- File through all data points within the EB range + for i = 1:nRows + if i == 1 + A1 = 0; + A2 = trapz(roi_xdat(i:end), Intensity{N-1}(i:end)); + elseif i == nRows + A1 = trapz(roi_xdat(1:i), Intensity{N-1}(1:i)); + A2 = 0; + else + A1 = trapz(roi_xdat(1:i), Intensity{N-1}(1:i)); + A2 = trapz(roi_xdat(i:end), Intensity{N-1}(i:end)); + end + ShirBgrnd{N}(i,1) = I2 + (I1 - I2) .* A2 ./ (A1 + A2); + end + Intensity{N} = roi_ydat - ShirBgrnd{N}; + end +end +% - Store the background intensity +roi_bgrnd = ShirBgrnd{end}; +% -- Verifying outputs are all column vectors +if size(roi_xdat, 2) > 1; roi_xdat = roi_xdat'; end +if size(roi_ydat, 2) > 1; roi_ydat = roi_ydat'; end +if size(roi_bgrnd, 2) > 1; roi_bgrnd = roi_bgrnd'; end + +%% -- For Debugging +if plot_result == 1 + % - Initialising the figure object + figure(); hold on; + % -- Plotting the ROI, LHS and RHS analysis windows + ROI = [xdat(roi_indx(1)), xdat(roi_indx(2))]; + LHS = [xdat(lhsWin_indx(1)), xdat(lhsWin_indx(2))]; + RHS = [xdat(rhsWin_indx(1)), xdat(rhsWin_indx(2))]; + hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e4, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); + hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; + hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e4, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); + hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; + hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e4, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); + hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Plotting a vertical line to show the ROI + a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); + a.Annotation.LegendInformation.IconDisplayStyle = 'off'; + b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); + b.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Plotting the 1D data + plot(xdat, ydat, 'b-', 'linewidth', 0.5); + plot(roi_xdat, roi_ydat, 'b-', 'linewidth', 2); + plot(roi_xdat, roi_bgrnd, 'r-', 'linewidth', 2); + plot(roi_xdat, roi_ydat-roi_bgrnd, 'k-', 'linewidth', 2); + gca_props(); title('BgrndShirley()'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); + % -- Determining the best limits for the plot + axLim_y = [roi_ydat; roi_ydat-roi_bgrnd]; + axis([min(xdat(:)), max(xdat(:)), min(axLim_y(:)), max(axLim_y(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndShirleyOffset.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndShirleyOffset.m new file mode 100644 index 0000000..ff9b045 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndShirleyOffset.m @@ -0,0 +1,143 @@ +function [roi_xdat, roi_ydat, roi_bgrnd] = BgrndShirleyOffset(xdat, ydat, lambda, delta, lhsVal, rhsVal, lhsWin, rhsWin, plot_result) +% [roi_xdat, roi_ydat, roi_bgrnd] = BgrndShirleyOffset(xdat, ydat, lambda, delta, lhsVal, rhsVal, lhsWin, rhsWin, plot_result) +% Function that determines the best fit to the background of PES (or 1D) data +% using an Offset Shirley function. This is a blend between a Shirley and +% linear background and is defined by the parameters lambda and delta. +% The output is a column vector containing the background intensity, and +% the new domain and intensity of the data within the defined region of interest. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES) +% - ydat: N×1 column vector of the intensity range (intensity for PES) +% - lambda: scalar for mixing ratio: lambda = 0 is Pure Shirley; lambda = 1 is Pure Linear. +% - delta: scalar for the Shirley curve offset in binding energy. +% - lhsVal: scalar of the LHS x-axis start position of the ROI. +% - rhsVal: scalar of the RHS x-axis end position of the ROI. +% - lhsWin: scalar of the LHS window size around the start position. +% - rhsWin: scalar of the RHS window size around the end position. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - roi_xdat: M×1 column vector of the ROI x-domain (binding energy for PES). +% - roi_ydat: M×1 column vector of the ROI y-values (intensity for PES). +% - roi_bgrnd: M×1 column vector of the best fit Shirley background to the ROI data. + +%% Default parameters +% - Setting the default conditions +if nargin < 3; lambda = 0.5; end +if nargin < 4; delta = 0; end +if nargin < 5; lhsVal = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if nargin < 6; rhsVal = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if nargin < 7; lhsWin = abs(0.02*range(xdat(:))); end +if nargin < 8; rhsWin = abs(0.02*range(xdat(:))); end +if nargin < 9; plot_result = 0; end +if isempty(lambda); lambda = 0.5; end +if isempty(delta); delta = 0; end +if isempty(lhsVal); lhsVal = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if isempty(rhsVal); rhsVal = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if isempty(lhsWin); lhsWin = abs(0.02*range(xdat(:))); end +if isempty(rhsWin); rhsWin = abs(0.02*range(xdat(:))); end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +% -- Setting the condition for the mixing terms lambda +if lambda < 0; lambda = 0; +elseif lambda > 1; lambda = 1; +end +% -- If a vector / array of the LHS and RHS are entered, only select the first value +if length(lhsVal) > 1 + disp('Warning: lhsVal is defined as a vector, only choosing the first element.'); + lhsVal = lhsVal(1); +end +if length(rhsVal) > 1 + disp('Warning: rhsVal is defined as a vector, only choosing the first element.'); + rhsVal = rhsVal(1); +end +% -- If the LHS value is smaller than the RHS value, switch the assignment +if lhsVal > rhsVal + disp('Warning: lhsVal > rhsVal, values have been switched.'); + A = lhsVal; Awin = lhsWin; + B = rhsVal; Bwin = rhsWin; + lhsVal = B; lhsVal = Bwin; + rhsVal = A; rhsVal = Awin; +% -- If the LHS and RHS values are identical, no window can be defined +elseif lhsVal == rhsVal + error('Error: lhsVal == rhsVal, make sure you define a finite window size for the ROI.'); +end +% -- If a vector / array of the LHS and RHS windows are entered, only select the first value +if length(lhsWin) > 1 + disp('Warning: lhsWin is defined as a vector, only choosing the first element.'); + lhsWin = lhsWin(1); +end +if length(rhsWin) > 1 + disp('Warning: rhsWin is defined as a vector, only choosing the first element.'); + rhsWin = rhsWin(1); +end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% - 1 - Extracting the index START and END point of the background +% -- LHS index points +[~, lhsIndx_mu] = min(abs(xdat - lhsVal)); +[~, lhsIndx_lb] = min(abs(xdat - lhsVal - lhsWin)); +[~, lhsIndx_ub] = min(abs(xdat - lhsVal + lhsWin)); +% -- RHS index points +[~, rhsIndx_mu] = min(abs(xdat - rhsVal)); +[~, rhsIndx_lb] = min(abs(xdat - rhsVal - rhsWin)); +[~, rhsIndx_ub] = min(abs(xdat - rhsVal + rhsWin)); +% - ROI indexes +roi_indx = sort([lhsIndx_mu, rhsIndx_mu]); +lhsWin_indx = sort([lhsIndx_lb, lhsIndx_ub]); +rhsWin_indx = sort([rhsIndx_lb, rhsIndx_ub]); + +%% - 2 - Cropping the data over the ROI whose background is extracted +roi_xdat = xdat(roi_indx(1):roi_indx(2)); +roi_ydat = ydat(roi_indx(1):roi_indx(2)); +nRows = length(roi_xdat); + +%% - 3 - Determination of the Offset Shirley Background +[~, ~, roi_bgrnd_lin] = BgrndPoly(xdat, ydat, 1, lhsVal, rhsVal, lhsWin, rhsWin); +[~, ~, roi_bgrnd_shrly] = BgrndShirley(xdat - delta, ydat, lhsVal, rhsVal, lhsWin, rhsWin); +% -- Determine the offset Shirley background +roi_bgrnd = roi_bgrnd_shrly.*(1-lambda) + lambda.*roi_bgrnd_lin; +% -- Verifying outputs are all column vectors +if size(roi_xdat, 2) > 1; roi_xdat = roi_xdat'; end +if size(roi_ydat, 2) > 1; roi_ydat = roi_ydat'; end +if size(roi_bgrnd, 2) > 1; roi_bgrnd = roi_bgrnd'; end + +%% -- For Debugging +if plot_result == 1 + % - Initialising the figure object + figure(); hold on; + % -- Plotting the ROI, LHS and RHS analysis windows + ROI = [xdat(roi_indx(1)), xdat(roi_indx(2))]; + LHS = [xdat(lhsWin_indx(1)), xdat(lhsWin_indx(2))]; + RHS = [xdat(rhsWin_indx(1)), xdat(rhsWin_indx(2))]; + hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e4, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); + hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; + hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e4, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); + hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; + hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e4, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); + hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Plotting a vertical line to show the ROI + a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); + a.Annotation.LegendInformation.IconDisplayStyle = 'off'; + b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); + b.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Plotting the 1D data + plot(xdat, ydat, 'b-', 'linewidth', 0.5); + plot(roi_xdat, roi_ydat, 'b-', 'linewidth', 2); + plot(roi_xdat, roi_bgrnd, 'r-', 'linewidth', 2); + plot(roi_xdat, roi_ydat-roi_bgrnd, 'k-', 'linewidth', 2); + gca_props(); title('BgrndShirleyOffset()'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); + % -- Determining the best limits for the plot + axLim_y = [roi_ydat; roi_ydat-roi_bgrnd]; + axis([min(xdat(:)), max(xdat(:)), min(axLim_y(:)), max(axLim_y(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndStepFDDGpL.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndStepFDDGpL.m new file mode 100644 index 0000000..794364d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndStepFDDGpL.m @@ -0,0 +1,154 @@ +function [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGpL(xdat, ydat, fdd_ef, fdd_T, fdd_fwhm, lhsVal, rhsVal, lhsWin, rhsWin, plot_result) +% [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGpL(xdat, ydat, fdd_ef, fdd_T, fdd_fwhm, lhsVal, rhsVal, lhsWin, rhsWin, plot_result) +% Function that determines the best fit to the background of PES (or 1D) +% data using a single FDD step. The output is a column vector containing +% the background intensity, and the new domain and intensity of the data +% within the defined region of interest. Here, a linear background is +% MULTIPLIED to the FDD function, so the background is fitted to the +% the gradient, intercept and constant. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES) +% - ydat: N×1 column vector of the intensity range (intensity for PES) +% - fdd_ef: scalar of the Fermi-level position (eV). +% - fdd_T: scalar of the temperature (K). +% - fdd_fwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian broadening term (eV). +% - lhsVal: scalar of the LHS x-axis start position of the ROI. +% - rhsVal: scalar of the RHS x-axis end position of the ROI. +% - lhsWin: scalar of the LHS window size around the start position. +% - rhsWin: scalar of the RHS window size around the end position. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - roi_xdat: M×1 column vector of the ROI x-domain (binding energy for PES). +% - roi_ydat: M×1 column vector of the ROI y-values (intensity for PES). +% - roi_bgrnd: M×1 column vector of the best fit polynomial background to the ROI data. + +%% Default parameters +% - Setting the default conditions +if nargin < 3; fdd_ef = 0.0; end +if nargin < 4; fdd_T = 12; end +if nargin < 5; fdd_fwhm = 0.1; end +if nargin < 6; lhsVal = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if nargin < 7; rhsVal = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if nargin < 8; lhsWin = abs(0.02*range(xdat(:))); end +if nargin < 9; rhsWin = abs(0.02*range(xdat(:))); end +if nargin < 10; plot_result = 0; end +if isempty(fdd_ef); fdd_ef = 0.0; end +if isempty(fdd_T); fdd_T = 12; end +if isempty(fdd_fwhm); fdd_fwhm = 0.1; end +if isempty(lhsVal); lhsVal = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if isempty(rhsVal); rhsVal = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if isempty(lhsWin); lhsWin = abs(0.02*range(xdat(:))); end +if isempty(rhsWin); rhsWin = abs(0.02*range(xdat(:))); end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +% -- Validity check on the FDD parameters +if fdd_T < 0; fdd_T = 0; end +if fdd_fwhm < 0; fdd_fwhm = 0; end +% -- If a vector / array of the LHS and RHS are entered, only select the first value +if length(lhsVal) > 1 + disp('Warning: lhsVal is defined as a vector, only choosing the first element.'); + lhsVal = lhsVal(1); +end +if length(rhsVal) > 1 + disp('Warning: rhsVal is defined as a vector, only choosing the first element.'); + rhsVal = rhsVal(1); +end +% -- If the LHS value is smaller than the RHS value, switch the assignment +if lhsVal > rhsVal + disp('Warning: lhsVal > rhsVal, values have been switched.'); + A = lhsVal; Awin = lhsWin; + B = rhsVal; Bwin = rhsWin; + lhsVal = B; lhsVal = Bwin; + rhsVal = A; rhsVal = Awin; +% -- If the LHS and RHS values are identical, no window can be defined +elseif lhsVal == rhsVal + error('Error: lhsVal == rhsVal, make sure you define a finite window size for the ROI.'); +end +% -- If a vector / array of the LHS and RHS windows are entered, only select the first value +if length(lhsWin) > 1 + disp('Warning: lhsWin is defined as a vector, only choosing the first element.'); + lhsWin = lhsWin(1); +end +if length(rhsWin) > 1 + disp('Warning: rhsWin is defined as a vector, only choosing the first element.'); + rhsWin = rhsWin(1); +end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% - 1 - Extracting the index START and END point of the background +% -- LHS index points +[~, lhsIndx_mu] = min(abs(xdat - lhsVal)); +[~, lhsIndx_lb] = min(abs(xdat - lhsVal - lhsWin)); +[~, lhsIndx_ub] = min(abs(xdat - lhsVal + lhsWin)); +% -- RHS index points +[~, rhsIndx_mu] = min(abs(xdat - rhsVal)); +[~, rhsIndx_lb] = min(abs(xdat - rhsVal - rhsWin)); +[~, rhsIndx_ub] = min(abs(xdat - rhsVal + rhsWin)); +% - ROI indexes +roi_indx = sort([lhsIndx_mu, rhsIndx_mu]); +lhsWin_indx = sort([lhsIndx_lb, lhsIndx_ub]); +rhsWin_indx = sort([rhsIndx_lb, rhsIndx_ub]); + +%% - 2 - Cropping the data over the ROI whose background is extracted +roi_xdat = xdat(roi_indx(1):roi_indx(2)); +roi_ydat = ydat(roi_indx(1):roi_indx(2)); +nRows = length(roi_xdat); + +%% - 3 - Determination & fitting of the FDD Background +% -- Extracting the data to be fitted with linear expressions +xdat_bgrnd = [xdat(lhsWin_indx(1):lhsWin_indx(2)); xdat(rhsWin_indx(1):rhsWin_indx(2))]; +ydat_bgrnd = [ydat(lhsWin_indx(1):lhsWin_indx(2)); ydat(rhsWin_indx(1):rhsWin_indx(2))]; +% -- Fitting the data to a polynomial of the correct order +fermi_fit = fittype(@(a, b, c, x) FDDGpL(x, fdd_ef, fdd_T, fdd_fwhm, a, b, c)); +a_start = 0.1; % lin_grad: scalar of the gradient of the linear background. +b_start = 1.0; % lin_offset: scalar of the y-intercept of the linear background. +c_start = 0.1; % const_bgrnd: scalar of the constant background y-offset value. +% Executing the fitting operation +[fit1,~,~] = fit(xdat_bgrnd,ydat_bgrnd,fermi_fit,'start',[a_start, b_start, c_start]); +fit1para = coeffvalues(fit1); +roi_bgrnd = FDDGpL(roi_xdat, fdd_ef, fdd_T, fdd_fwhm, fit1para(1), fit1para(2), fit1para(3)); +% -- Verifying outputs are all column vectors +if size(roi_xdat, 2) > 1; roi_xdat = roi_xdat'; end +if size(roi_ydat, 2) > 1; roi_ydat = roi_ydat'; end +if size(roi_bgrnd, 2) > 1; roi_bgrnd = roi_bgrnd'; end + +%% -- For Debugging +if plot_result == 1 + % - Initialising the figure object + figure(); hold on; + % -- Plotting the ROI, LHS and RHS analysis windows + ROI = [xdat(roi_indx(1)), xdat(roi_indx(2))]; + LHS = [xdat(lhsWin_indx(1)), xdat(lhsWin_indx(2))]; + RHS = [xdat(rhsWin_indx(1)), xdat(rhsWin_indx(2))]; + hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e4, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); + hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; + hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e4, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); + hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; + hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e4, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); + hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Plotting a vertical line to show the ROI + a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); + a.Annotation.LegendInformation.IconDisplayStyle = 'off'; + b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); + b.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Plotting the 1D data + plot(xdat, ydat, 'b-', 'linewidth', 0.5); + plot(roi_xdat, roi_ydat, 'b-', 'linewidth', 2); + plot(roi_xdat, roi_bgrnd, 'r-', 'linewidth', 2); + plot(roi_xdat, roi_ydat-roi_bgrnd, 'k-', 'linewidth', 2); + gca_props(); title('BgrndStepFDDGpL()'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); + % -- Determining the best limits for the plot + axLim_y = [roi_ydat; roi_ydat-roi_bgrnd]; + axis([min(xdat(:)), max(xdat(:)), min(axLim_y(:)), max(axLim_y(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndStepFDDGsL.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndStepFDDGsL.m new file mode 100644 index 0000000..2fce135 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/BgrndStepFDDGsL.m @@ -0,0 +1,154 @@ +function [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGsL(xdat, ydat, fdd_ef, fdd_T, fdd_fwhm, lhsVal, rhsVal, lhsWin, rhsWin, plot_result) +% [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGsL(xdat, ydat, fdd_ef, fdd_T, fdd_fwhm, lhsVal, rhsVal, lhsWin, rhsWin, plot_result) +% Function that determines the best fit to the background of PES (or 1D) +% data using a single FDD step. The output is a column vector containing +% the background intensity, and the new domain and intensity of the data +% within the defined region of interest. Here, a linear background is +% SUMMED to the FDD function, so the background is fitted to the +% the gradient, intercept and constant. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES) +% - ydat: N×1 column vector of the intensity range (intensity for PES) +% - fdd_ef: scalar of the Fermi-level position (eV). +% - fdd_T: scalar of the temperature (K). +% - fdd_fwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian broadening term (eV). +% - lhsVal: scalar of the LHS x-axis start position of the ROI. +% - rhsVal: scalar of the RHS x-axis end position of the ROI. +% - lhsWin: scalar of the LHS window size around the start position. +% - rhsWin: scalar of the RHS window size around the end position. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - roi_xdat: M×1 column vector of the ROI x-domain (binding energy for PES). +% - roi_ydat: M×1 column vector of the ROI y-values (intensity for PES). +% - roi_bgrnd: M×1 column vector of the best fit polynomial background to the ROI data. + +%% Default parameters +% - Setting the default conditions +if nargin < 3; fdd_ef = 0.0; end +if nargin < 4; fdd_T = 12; end +if nargin < 5; fdd_fwhm = 0.1; end +if nargin < 6; lhsVal = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if nargin < 7; rhsVal = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if nargin < 8; lhsWin = abs(0.02*range(xdat(:))); end +if nargin < 9; rhsWin = abs(0.02*range(xdat(:))); end +if nargin < 10; plot_result = 0; end +if isempty(fdd_ef); fdd_ef = 0.0; end +if isempty(fdd_T); fdd_T = 12; end +if isempty(fdd_fwhm); fdd_fwhm = 0.1; end +if isempty(lhsVal); lhsVal = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if isempty(rhsVal); rhsVal = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if isempty(lhsWin); lhsWin = abs(0.02*range(xdat(:))); end +if isempty(rhsWin); rhsWin = abs(0.02*range(xdat(:))); end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +% -- Validity check on the FDD parameters +if fdd_T < 0; fdd_T = 0; end +if fdd_fwhm < 0; fdd_fwhm = 0; end +% -- If a vector / array of the LHS and RHS are entered, only select the first value +if length(lhsVal) > 1 + disp('Warning: lhsVal is defined as a vector, only choosing the first element.'); + lhsVal = lhsVal(1); +end +if length(rhsVal) > 1 + disp('Warning: rhsVal is defined as a vector, only choosing the first element.'); + rhsVal = rhsVal(1); +end +% -- If the LHS value is smaller than the RHS value, switch the assignment +if lhsVal > rhsVal + disp('Warning: lhsVal > rhsVal, values have been switched.'); + A = lhsVal; Awin = lhsWin; + B = rhsVal; Bwin = rhsWin; + lhsVal = B; lhsVal = Bwin; + rhsVal = A; rhsVal = Awin; +% -- If the LHS and RHS values are identical, no window can be defined +elseif lhsVal == rhsVal + error('Error: lhsVal == rhsVal, make sure you define a finite window size for the ROI.'); +end +% -- If a vector / array of the LHS and RHS windows are entered, only select the first value +if length(lhsWin) > 1 + disp('Warning: lhsWin is defined as a vector, only choosing the first element.'); + lhsWin = lhsWin(1); +end +if length(rhsWin) > 1 + disp('Warning: rhsWin is defined as a vector, only choosing the first element.'); + rhsWin = rhsWin(1); +end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% - 1 - Extracting the index START and END point of the background +% -- LHS index points +[~, lhsIndx_mu] = min(abs(xdat - lhsVal)); +[~, lhsIndx_lb] = min(abs(xdat - lhsVal - lhsWin)); +[~, lhsIndx_ub] = min(abs(xdat - lhsVal + lhsWin)); +% -- RHS index points +[~, rhsIndx_mu] = min(abs(xdat - rhsVal)); +[~, rhsIndx_lb] = min(abs(xdat - rhsVal - rhsWin)); +[~, rhsIndx_ub] = min(abs(xdat - rhsVal + rhsWin)); +% - ROI indexes +roi_indx = sort([lhsIndx_mu, rhsIndx_mu]); +lhsWin_indx = sort([lhsIndx_lb, lhsIndx_ub]); +rhsWin_indx = sort([rhsIndx_lb, rhsIndx_ub]); + +%% - 2 - Cropping the data over the ROI whose background is extracted +roi_xdat = xdat(roi_indx(1):roi_indx(2)); +roi_ydat = ydat(roi_indx(1):roi_indx(2)); +nRows = length(roi_xdat); + +%% - 3 - Determination & fitting of the FDD Background +% -- Extracting the data to be fitted with linear expressions +xdat_bgrnd = [xdat(lhsWin_indx(1):lhsWin_indx(2)); xdat(rhsWin_indx(1):rhsWin_indx(2))]; +ydat_bgrnd = [ydat(lhsWin_indx(1):lhsWin_indx(2)); ydat(rhsWin_indx(1):rhsWin_indx(2))]; +% -- Fitting the data to a polynomial of the correct order +fermi_fit = fittype(@(a, b, c, x) FDDGsL(x, fdd_ef, fdd_T, fdd_fwhm, a, b, c)); +a_start = 0.1; % lin_grad: scalar of the gradient of the linear background. +b_start = 1.0; % lin_offset: scalar of the y-intercept of the linear background. +c_start = 0.1; % const_bgrnd: scalar of the constant background y-offset value. +% Executing the fitting operation +[fit1,~,~] = fit(xdat_bgrnd,ydat_bgrnd,fermi_fit,'start',[a_start, b_start, c_start]); +fit1para = coeffvalues(fit1); +roi_bgrnd = FDDGsL(roi_xdat, fdd_ef, fdd_T, fdd_fwhm, fit1para(1), fit1para(2), fit1para(3)); +% -- Verifying outputs are all column vectors +if size(roi_xdat, 2) > 1; roi_xdat = roi_xdat'; end +if size(roi_ydat, 2) > 1; roi_ydat = roi_ydat'; end +if size(roi_bgrnd, 2) > 1; roi_bgrnd = roi_bgrnd'; end + +%% -- For Debugging +if plot_result == 1 + % - Initialising the figure object + figure(); hold on; + % -- Plotting the ROI, LHS and RHS analysis windows + ROI = [xdat(roi_indx(1)), xdat(roi_indx(2))]; + LHS = [xdat(lhsWin_indx(1)), xdat(lhsWin_indx(2))]; + RHS = [xdat(rhsWin_indx(1)), xdat(rhsWin_indx(2))]; + hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e4, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); + hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; + hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e4, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); + hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; + hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e4, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); + hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Plotting a vertical line to show the ROI + a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); + a.Annotation.LegendInformation.IconDisplayStyle = 'off'; + b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); + b.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Plotting the 1D data + plot(xdat, ydat, 'b-', 'linewidth', 0.5); + plot(roi_xdat, roi_ydat, 'b-', 'linewidth', 2); + plot(roi_xdat, roi_bgrnd, 'r-', 'linewidth', 2); + plot(roi_xdat, roi_ydat-roi_bgrnd, 'k-', 'linewidth', 2); + gca_props(); title('BgrndStepFDDGsL()'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); + % -- Determining the best limits for the plot + axLim_y = [roi_ydat; roi_ydat-roi_bgrnd]; + axis([min(xdat(:)), max(xdat(:)), min(axLim_y(:)), max(axLim_y(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/PESBackground.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/PESBackground.m new file mode 100644 index 0000000..b97e245 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes background curves/PESBackground.m @@ -0,0 +1,89 @@ +function [roi_xdat, roi_ydat, roi_bgrnd] = PESBackground(xdat, ydat, bTYPE, LHS, RHS, BGR, ARGS, plot_result) +% [roi_xdat, roi_ydat, roi_bgrnd] = PESBackground(xdat, ydat, bTYPE, LHS, RHS, BGR, ARGS, plot_result) +% Function that evaluates the background associated with 1D data or +% photoelectron spectroscopy (PES) data acquired at the ADRESS beamline, +% SLS. The background type can be defined over a given region of interest +% (ROI). +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - ydat: N×1 column vector of the intensity range (intensity for PES). +% - bTYPE: string of the type of background to use for fitting. {Default: "Poly" ("none", "Poly", "Shir", "LinShir", "StepFDDGpL", "StepFDDGsL")} +% - LHS: scalar of the LHS x-axis START position of the ROI. {Default: 25th percentile.} +% - RHS: scalar of the RHS x-axis END position of the ROI. {Default: 75th percentile.} +% - BGR: scalar for a constant y-axis background to be included. {Default: 0} +% - ARGS: cell vector containing the arguments for the background type used; +% "none": 1×1 {} +% "Poly": 1×1 {polyOrder} +% "Shir": 1×1 {} +% "LinShir": 1×2 {lambda, delta} +% "StepFDDGpL": 1×3 {fdd_ef, fdd_T, fdd_fwhm} +% "StepFDDGsL": 1×3 {fdd_ef, fdd_T, fdd_fwhm} +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - roi_xdat: M×1 column vector of the ROI x-domain (binding energy for PES). +% - roi_ydat: M×1 column vector of the ROI y-values (intensity for PES). +% - roi_bgrnd: M×1 column vector of the best fit polynomial background to the ROI data. + +%% Default parameters +% - Setting the default conditions +if nargin < 3; bTYPE = "Poly"; end +if nargin < 4; LHS = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if nargin < 5; RHS = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if nargin < 6; BGR = 0.0; end +if nargin < 7; ARGS = {1}; end +if nargin < 8; plot_result = 0; end +if isempty(bTYPE); bTYPE = "Poly"; end +if isempty(LHS); LHS = mean(xdat(:)) - abs(0.25*range(xdat(:))); end +if isempty(RHS); RHS = mean(xdat(:)) + abs(0.25*range(xdat(:))); end +if isempty(BGR); BGR = 0; end +if isempty(ARGS); ARGS = {1}; end +if isempty(plot_result); plot_result = 0; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% - 1 - Determination of the PES background +% - EXTRACTING POLYNOMIAL BACKGROUND +if strcmpi(bTYPE,"Poly") + if length(ARGS) == 1; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndPoly(xdat, ydat, ARGS{1}, LHS, RHS, [], [], plot_result); + else; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndPoly(xdat, ydat, [], LHS, RHS, [], [], plot_result); + end +% - EXTRACTING SHIRLEY BACKGROUND +elseif strcmpi(bTYPE,"Shir") + [roi_xdat, roi_ydat, roi_bgrnd] = BgrndShirley(xdat, ydat, LHS, RHS, [], [], plot_result); +% - EXTRACTING LINEAR-SHIRLEY BACKGROUND +elseif strcmpi(bTYPE,"LinShir") + if length(ARGS) == 1; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndShirleyOffset(xdat, ydat, ARGS{1}, [], LHS, RHS, [], [], plot_result); + elseif length(ARGS) == 2; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndShirleyOffset(xdat, ydat, ARGS{1}, ARGS{2}, LHS, RHS, [], [], plot_result); + else; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndShirleyOffset(xdat, ydat, [], [], LHS, RHS, [], [], plot_result); + end +% - EXTRACTING STEP-FDD-PRODUCT BACKGROUND +elseif strcmpi(bTYPE,"StepFDDGpL") + if length(ARGS) == 1; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGpL(xdat, ydat, ARGS{1}, [], [], LHS, RHS, [], [], plot_result); + elseif length(ARGS) == 2; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGpL(xdat, ydat, ARGS{1}, ARGS{2}, [], LHS, RHS, [], [], plot_result); + elseif length(ARGS) == 3; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGpL(xdat, ydat, ARGS{1}, ARGS{2}, ARGS{3}, LHS, RHS, [], [], plot_result); + else; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGpL(xdat, ydat, [], [], [], LHS, RHS, [], [], plot_result); + end +% - EXTRACTING STEP-FDD-SUM BACKGROUND +elseif strcmpi(bTYPE,"StepFDDGsL") + if length(ARGS) == 1; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGsL(xdat, ydat, ARGS{1}, [], [], LHS, RHS, [], [], plot_result); + elseif length(ARGS) == 2; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGsL(xdat, ydat, ARGS{1}, ARGS{2}, [], LHS, RHS, [], [], plot_result); + elseif length(ARGS) == 3; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGsL(xdat, ydat, ARGS{1}, ARGS{2}, ARGS{3}, LHS, RHS, [], [], plot_result); + else; [roi_xdat, roi_ydat, roi_bgrnd] = BgrndStepFDDGsL(xdat, ydat, [], [], [], LHS, RHS, [], [], plot_result); + end +% - EXTRACTING NO BACKGROUND +elseif strcmpi(bTYPE,"none") + [~, lhsIndx] = min(abs(xdat - LHS)); + [~, rhsIndx] = min(abs(xdat - RHS)); + roi_xdat = xdat(lhsIndx:rhsIndx); + roi_ydat = ydat(lhsIndx:rhsIndx); + roi_bgrnd = 0.*roi_ydat; +end +% - Adding a constant background +roi_bgrnd = roi_bgrnd - BGR; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/AEB.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/AEB.m new file mode 100644 index 0000000..2435592 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/AEB.m @@ -0,0 +1,47 @@ +function ydat = AEB(xdat, x0, asym) +% ydat = AEB(xdat, x0, asym) +% Function that evaluates an asymmetric exponential blend (AEB), that is +% used to create the asymmetric Voigt-type lineshapes. The asymmetric profile +% obtained from the blend is: Y(x) = GL(x) + AEB(x) * (1 - GL(x)). +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - x0: scalar of the position where the AEB will start. +% - asym: asymmetry ratio; 0 for none, 0->1 is for LHS asymmetry, -1->0 is for RHS asymmetry. +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; x0 = 0.0; end +if nargin < 3; asym = 0.5; end +if isempty(x0); x0 = 0; end +if isempty(asym); asym = 0.5; end +%% Validity checks on the input parameters +% -- Padding the asymmetry to be between -1 -> 1 +if asym < -1; asym = -1; end +if asym > 1; asym = 1; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the Exponential Asymmetric Blend intensities +% Evaluating the asymmetric blend +if asym > 0 || asym == 0 + K = 1; % Coefficient + ydat = exp(-K/asym.*abs(xdat - x0)); + % For all values where xdat > x0, set to zero + [~, indx] = min(abs(xdat - x0)); + ydat(indx:end) = 0; +elseif asym < 0 + K = 1; % Coefficient + ydat = exp(K/asym.*abs(xdat - x0)); + % For all values where xdat < x0, set to zero + [~, indx] = min(abs(xdat - x0)); + ydat(1:indx) = 0; +end +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/DoniachSunjic.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/DoniachSunjic.m new file mode 100644 index 0000000..94d37b8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/DoniachSunjic.m @@ -0,0 +1,51 @@ +function ydat = DoniachSunjic(xdat, x0, peak, fwhm, asym) +% ydat = DoniachSunjic(xdat, x0, peak, fwhm, asym) +% Function that evaluates a Doniach-Sunjic curve after defining its position, +% full-width at half-maximum (FWHM), amplitude and asymmetry. The formula +% is used to characterise the asymmetry in the measured XPS of metallic +% systems. The problem with this function is that it lacks proper +% quantification, as F and E are both quantities that are related to the +% FWHM and peak position respectively, but not exactly equal to them. It +% is better to use Voigt lineshapes for fitting photoemission peaks. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - x0: scalar of the (approximate) peak position. +% - peak: scalar of the peak height. +% - fwhm: scalar of the (approximate) FWHM. +% - asym: asymmetry ratio; 0 for none, 1 is for maximum +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; x0 = 0; end +if nargin < 3; peak = 1; end +if nargin < 4; fwhm = 1; end +if nargin < 5; asym = 0.5; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +if isempty(fwhm); fwhm = 1; end +if isempty(asym); asym = 0.5; end +%% Validity checks on the input parameters +% -- If the FWHM is negative, set it to zero +if fwhm < 0; fwhm = 0; end +% -- If the asym is negative, set it to zero +if asym < 0; asym = 0; end +% -- If the asym is positive, set it to one +if asym > 1; asym = 1; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the Doniach-Sunjic curve intensities +% Evaluating the normalised curve profile +ydat = (cos(0.5*pi*asym + (1-asym).*atan((xdat - x0) / fwhm))) ./ ((fwhm.^2+(xdat-x0).^2).^((1-asym)/2)); +% Scaling the curve profile to match the desired peak +ydat = ydat ./ max(ydat(:)); +ydat = peak .* ydat; +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDD.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDD.m new file mode 100644 index 0000000..15adc3e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDD.m @@ -0,0 +1,33 @@ +function ydat = FDD(xdat, fdd_ef, fdd_T) +% ydat = FDD(xdat, fdd_ef, fdd_T) +% This function determines the Fermi-Dirac Distribution (FDD) given the +% fermi-energy (fdd_ef) and temperature (fdd_T). This is the pure, theoretical +% FDD function. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - fdd_ef: scalar of the Fermi-level position (eV). +% - fdd_T: scalar of the temperature (K). +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; fdd_ef = 0; end +if nargin < 3; fdd_T = 12; end +if isempty(fdd_ef); fdd_ef = 0; end +if isempty(fdd_T); fdd_T = 12; end +%% Validity checks on the input parameters +if fdd_T < 0; fdd_T = 0; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% 1 - Determination of the Fermi-Dirac Distribution +% Evaluating the FDD +ydat = 1 ./ (exp((xdat - fdd_ef) ./ (8.617e-5 .* fdd_T)) + 1); +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDDG.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDDG.m new file mode 100644 index 0000000..bc3637e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDDG.m @@ -0,0 +1,58 @@ +function ydat = FDDG(xdat, fdd_ef, fdd_T, fdd_fwhm) +% ydat = FDDG(xdat, fdd_ef, fdd_T, fdd_fwhm) +% This function determines the Fermi-Dirac Distribution (FDD) given the +% fermi-energy (fdd_ef) and temperature (fdd_T). A convolution is then made with +% a Gaussian, with a well-defined full-width half-maximum (fdd_fwhm) to +% include the broadening introducted by the beamline+analyzer resolution. +% +% REQ. FUNCTIONS: +% - FDD() +% - Gauss() +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - fdd_ef: scalar of the Fermi-level position (eV). +% - fdd_T: scalar of the temperature (K). +% - fdd_fwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian broadening term (eV). +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; fdd_ef = 0; end +if nargin < 3; fdd_T = 12; end +if nargin < 4; fdd_fwhm = 0; end +if isempty(fdd_ef); fdd_ef = 0; end +if isempty(fdd_T); fdd_T = 12; end +if isempty(fdd_fwhm); fdd_fwhm = 0; end +%% Validity checks on the input parameters +if fdd_T < 0; fdd_T = 0; end +if fdd_fwhm < 0; fdd_fwhm = 0; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% 1 - Determining the FDD and Gaussian functions to use +% - Defining a large domain that spans the desired domain +xdat_large = linspace(min(xdat(:)) - 2, max(xdat(:)) + 2, 1e4)'; +% - FDD function +int_fdd = FDD(xdat_large, fdd_ef, fdd_T); +% - Gaussian function +int_Gauss = Gauss(xdat_large, fdd_ef, 1, fdd_fwhm); +%% 2 - Convolving the FDD and Gaussian functions +y_conv = conv(int_fdd, int_Gauss, 'same'); +y_conv = y_conv / max(y_conv); +% - Eliminate edge effects of the convolution +for i = 0:size(y_conv, 1)-1 + y_conv_val = y_conv(end-i); if y_conv_val == 1; y_conv(1:end-i) = 1; break; end +end +% - Validity check that the Fermi-level is the same +[~, indx] = min(abs(y_conv - 0.5)); +ef_shift = xdat_large(indx) - fdd_ef; +% - Assigning the best fit Fermi function +fdd_fit = fit(xdat_large-ef_shift, y_conv, 'linearinterp'); +%% 3 - Defining the final intensity array +ydat = fdd_fit(xdat); +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDDGpL.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDDGpL.m new file mode 100644 index 0000000..2c2b1de --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDDGpL.m @@ -0,0 +1,57 @@ +function ydat = FDDGpL(xdat, fdd_ef, fdd_T, fdd_fwhm, lin_grad, lin_inter, const_bgrnd) +% ydat = FDDGpL(xdat, fdd_ef, fdd_T, fdd_fwhm, lin_grad, lin_inter, const_bgrnd) +% This function determines the Fermi-Dirac Distribution (FDD) given the +% fermi-energy (fdd_ef) and temperature (fdd_T). A convolution is then made with +% a Gaussian, with a well-defined full-width half-maximum (fdd_fwhm) to +% include the broadening introducted by the beamline+analyzer resolution. +% Furthermore, a linear background is MULTIPLIED to accound for any +% linear distortion of the Fermi-edge, defined by the gradient and intercept. +% An additional constant background is also added (const_bgrnd). +% +% REQ. FUNCTIONS: +% - FDDG() +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - fdd_ef: scalar of the Fermi-level position (eV). +% - fdd_T: scalar of the temperature (K). +% - fdd_fwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian broadening term (eV). +% - lin_grad: scalar of the gradient of the linear background. +% - lin_offset: scalar of the y-intercept of the linear background. +% - const_bgrnd: scalar of the constant background y-offset value. +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; fdd_ef = 0; end +if nargin < 3; fdd_T = 12; end +if nargin < 4; fdd_fwhm = 0; end +if nargin < 5; lin_grad = 0; end +if nargin < 6; lin_inter = 1; end +if nargin < 7; const_bgrnd = 0; end +if isempty(fdd_ef); fdd_ef = 0; end +if isempty(fdd_T); fdd_T = 12; end +if isempty(fdd_fwhm); fdd_fwhm = 0; end +if isempty(lin_grad); lin_grad = 0; end +if isempty(lin_inter); lin_inter = 1; end +if isempty(const_bgrnd);const_bgrnd = 0; end +%% Validity checks on the input parameters +if fdd_T < 0; fdd_T = 0; end +if fdd_fwhm < 0; fdd_fwhm = 0; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% 1 - Determining the FDD, linear and background intensities +% - FDD function +int_fdd = FDDG(xdat, fdd_ef, fdd_T, fdd_fwhm); +% - Linear function +int_linear = lin_grad .* xdat + lin_inter; +% - Background value +int_bgrnd = const_bgrnd; +%% 2 - Combining all the functions +ydat = int_bgrnd + int_linear .* int_fdd; +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDDGsL.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDDGsL.m new file mode 100644 index 0000000..d3af91b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/FDDGsL.m @@ -0,0 +1,57 @@ +function ydat = FDDGsL(xdat, fdd_ef, fdd_T, fdd_fwhm, lin_grad, lin_inter, const_bgrnd) +% ydat = FDDGsL(xdat, fdd_ef, fdd_T, fdd_fwhm, lin_grad, lin_inter, const_bgrnd) +% This function determines the Fermi-Dirac Distribution (FDD) given the +% fermi-energy (fdd_ef) and temperature (fdd_T). A convolution is then made with +% a Gaussian, with a well-defined full-width half-maximum (fdd_fwhm) to +% include the broadening introducted by the beamline+analyzer resolution. +% Furthermore, a linear background is SUMMED to accound for any +% linear distortion of the Fermi-edge, defined by the gradient and intercept. +% An additional constant background is also added (const_bgrnd). +% +% REQ. FUNCTIONS: +% - FDDG() +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - fdd_ef: scalar of the Fermi-level position (eV). +% - fdd_T: scalar of the temperature (K). +% - fdd_fwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian broadening term (eV). +% - lin_grad: scalar of the gradient of the linear background. +% - lin_offset: scalar of the y-intercept of the linear background. +% - const_bgrnd: scalar of the constant background y-offset value. +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; fdd_ef = 0; end +if nargin < 3; fdd_T = 12; end +if nargin < 4; fdd_fwhm = 0; end +if nargin < 5; lin_grad = 0; end +if nargin < 6; lin_inter = 1; end +if nargin < 7; const_bgrnd = 0; end +if isempty(fdd_ef); fdd_ef = 0; end +if isempty(fdd_T); fdd_T = 12; end +if isempty(fdd_fwhm); fdd_fwhm = 0; end +if isempty(lin_grad); lin_grad = 0; end +if isempty(lin_inter); lin_inter = 1; end +if isempty(const_bgrnd);const_bgrnd = 0; end +%% Validity checks on the input parameters +if fdd_T < 0; fdd_T = 0; end +if fdd_fwhm < 0; fdd_fwhm = 0; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% 1 - Determining the FDD, linear and background intensities +% - FDD function +int_fdd = FDDG(xdat, fdd_ef, fdd_T, fdd_fwhm); +% - Linear function +int_linear = lin_grad .* xdat + lin_inter; +% - Background value +int_bgrnd = const_bgrnd; +%% 2 - Combining all the functions +ydat = int_bgrnd + int_linear + int_fdd; +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/Gauss.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/Gauss.m new file mode 100644 index 0000000..e43520f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/Gauss.m @@ -0,0 +1,41 @@ +function ydat = Gauss(xdat, x0, peak, fwhm) +% ydat = Gauss(xdat, x0, peak, fwhm) +% Function that evaluates a Gaussian curve after defining its position, +% full-width at half-maximum (FWHM) and amplitude. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - x0: scalar of the peak position along the x-axis of the Gaussian. +% - peak: scalar of the peak height of the Gaussian. +% - fwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian. +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; x0 = 0; end +if nargin < 3; peak = 1; end +if nargin < 4; fwhm = 1; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +if isempty(fwhm); fwhm = 1; end +%% Validity checks on the input parameters +% -- If the FWHM is negative, set it to zero +if fwhm < 0; fwhm = 0; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the Gaussian curve intensities +% Using the standard deviation as the input width so that the FWHM is correct +sigma = fwhm ./ (2*sqrt(2*log(2))); +% Evaluating the normalised curve profile +ydat = (1 ./ (sigma * sqrt(2*pi))) .* exp(-0.5.*((xdat-x0)./sigma).^2); +% Scaling the curve profile to match the desired peak +ydat = ydat ./ max(ydat(:)); +ydat = peak .* ydat; +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/Lorentzian.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/Lorentzian.m new file mode 100644 index 0000000..0bc4557 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/Lorentzian.m @@ -0,0 +1,39 @@ +function ydat = Lorentzian(xdat, x0, peak, fwhm) +% ydat = Lorentzian(xdat, x0, peak, fwhm) +% Function that evaluates a Lorentzian curve after defining its position, +% full-width at half-maximum (FWHM) and amplitude. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - x0: scalar of the peak position along the x-axis of the Lorentzian. +% - peak: scalar of the peak height of the Lorentzian. +% - fwhm: scalar of the full-width at half-maximum (FWHM) of the Lorentzian. +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; x0 = 0; end +if nargin < 3; peak = 1; end +if nargin < 4; fwhm = 1; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +if isempty(fwhm); fwhm = 1; end +%% Validity checks on the input parameters +% -- If the FWHM is negative, set it to zero +if fwhm < 0; fwhm = 0; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the Lorentzian curve intensities +% Evaluating the normalised curve profile +ydat = (peak .* 0.5*fwhm./pi) ./ ((xdat - x0).^2 + (0.5*fwhm).^2); +% Scaling the curve profile to match the desired peak +ydat = ydat ./ max(ydat(:)); +ydat = peak .* ydat; +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/PESCurve.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/PESCurve.m new file mode 100644 index 0000000..712b3bb --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/PESCurve.m @@ -0,0 +1,107 @@ +function ydat = PESCurve(xdat, cTYPE, BE, INT, FWHM, MR, LSE, LSI, LSW, ASY, plot_result) +% ydat = PESCurve(xdat, cTYPE, BE, INT, FWHM, MR, LSE, LSI, LSW, ASY, plot_result) +% Function that evaluates a generic photoelectron spectroscopy (PES) +% curve, by defining a primary (P) and spin-orbit split (SOS) component. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for XPS) +% - cTYPE: type of curve to use for fitting. Default: "sGLA" ("sGLA", "pGLA", "sGL", "pGL", "G", "L", "DS") +% - BE: scalar of the binding energy of PE curve. +% - INT: scalar of the peak intensity of PE curve. +% - FWHM: scalar of the FWHM of the PE curve. +% - MR: scalar of the Mixing Ratio: 0 for pure Gaussian, 1 is for pure Lorentzian. +% - LSE: scalar of the binding energy of spin-orbit split PE curve. +% - LSI: scalar of the branching ratio of spin-orbit split PE curve. +% - LSW: scalar of the additional lorentzian width of spin-orbit split PE curve. +% - ASY: scalar of the PE curve asymmetry parameter (usually for metallic systems). +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - ydat: N×1 column vector of the output Voigt curve profile + +%% Default parameters +% Default based on inputs +if nargin < 2; cTYPE = "sGLA"; end +if nargin < 3; BE = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 5; FWHM = 0.25; end +if nargin < 6; MR = 0.50; end +if nargin < 7; LSE = 0; end +if nargin < 8; LSI = 0; end +if nargin < 9; LSW = 0; end +if nargin < 10; ASY = 0; end +if nargin < 11; plot_result = 0; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "sGLA"; end +if isempty(BE); BE = 0.00; end +if isempty(INT); INT = 1.00; end +if isempty(FWHM); FWHM = 0.25; end +if isempty(MR); MR = 0.50; end +if isempty(LSE); LSE = 0; end +if isempty(LSI); LSI = 0; end +if isempty(LSW); LSW = 0; end +if isempty(ASY); ASY = 0; end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +if INT < 0; INT = 0; end +if FWHM < 0; FWHM = 0; end +if MR < 0; MR = 0; end +if MR > 1; MR = 1; end +if LSI < 0; LSI = 0; end +if LSW < 0; LSW = 0; end +if ASY < -1; ASY = -1; end +if ASY > 1; ASY = 1; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the PES curve +% - Extracting the primary and spin-split components +if strcmpi(cTYPE,"sGLA") + P_curve = sGLA(xdat, BE, INT, FWHM, MR, ASY); + SOS_curve = sGLA(xdat, BE+LSE, LSI*INT, FWHM+LSW, MR, ASY); +elseif strcmpi(cTYPE,"pGLA") + P_curve = pGLA(xdat, BE, INT, FWHM, MR, ASY); + SOS_curve = pGLA(xdat, BE+LSE, LSI*INT, FWHM+LSW, MR, ASY); +elseif strcmpi(cTYPE,"sGL") + P_curve = sGL(xdat, BE, INT, FWHM, MR); + SOS_curve = sGL(xdat, BE+LSE, LSI*INT, FWHM+LSW, MR); +elseif strcmpi(cTYPE,"pGL") + P_curve = pGL(xdat, BE, INT, FWHM, MR); + SOS_curve = pGL(xdat, BE+LSE, LSI*INT, FWHM+LSW, MR); +elseif strcmpi(cTYPE,"G") + P_curve = Gauss(xdat, BE, INT, FWHM); + SOS_curve = Gauss(xdat, BE+LSE, LSI*INT, FWHM+LSW); +elseif strcmpi(cTYPE,"L") + P_curve = Lorentzian(xdat, BE, INT, FWHM); + SOS_curve = Lorentzian(xdat, BE+LSE, LSI*INT, FWHM+LSW); +elseif strcmpi(cTYPE,"DS") + P_curve = DoniachSunjic(xdat, BE, INT, FWHM, ASY); + SOS_curve = DoniachSunjic(xdat, BE+LSE, LSI*INT, FWHM+LSW, ASY); +else + error('cTYPE: Curve type not recognised.'); +end +% - Summing the components together +ydat = P_curve + SOS_curve; +% - If isnan, return zero +ydat(isnan(ydat)) = 0; + +%% - 2 - Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% -- For Debugging +if plot_result == 1 + % - Initialising the figure object + figure(); hold on; + % -- Plotting the 1D data + plot(xdat, ydat, 'b-', 'linewidth', 2); + gca_props(); title('PESCurve()', 'interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + legend({'PESCurve()'}, 'location', 'best', 'fontsize', 9); + % -- Determining the best limits for the plot + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/PESCurve_FDD.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/PESCurve_FDD.m new file mode 100644 index 0000000..dc634e8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/PESCurve_FDD.m @@ -0,0 +1,104 @@ +function ydat = PESCurve_FDD(xdat, cTYPE, BE, INT, FWHM, MR, LSE, LSI, LSW, ASY, FDEF, FDT, FDW, plot_result) +% ydat = PESCurve_FDD(xdat, cTYPE, BE, INT, FWHM, MR, LSE, LSI, LSW, ASY, FDEF, FDT, FDW, plot_result) +% Function that evaluates a generic photoelectron spectroscopy (PES) +% curve, by defining a primary (P) and spin-orbit split (SOS) component. +% A Fermi-Dirac Distribution (FDD) is also multiplied with the PES curve. +% This type of curve should be used to fit near Fermi-edge EDC cuts. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - cTYPE: type of curve to use for fitting. Default: "sGLA" ("sGLA", "pGLA", "sGL", "pGL", "G", "L", "DS") +% - BE: scalar of the binding energy of PE curve. +% - INT: scalar of the peak intensity of PE curve. +% - FWHM: scalar of the FWHM of the PE curve. +% - MR: scalar of the Mixing Ratio: 0 for pure Gaussian, 1 is for pure Lorentzian. +% - LSE: scalar of the binding energy of spin-orbit split PE curve. +% - LSI: scalar of the branching ratio of spin-orbit split PE curve. +% - LSW: scalar of the additional lorentzian width of spin-orbit split PE curve. +% - ASY: scalar of the PE curve asymmetry parameter (usually for metallic systems). +% - FDEF: scalar of the FDD Fermi-Level position. +% - FDT: scalar of the FDD temperature. +% - FDW: scalar of the FDD Gaussian width after convolution. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - ydat: N×1 column vector of the output FDD convolved Voigt curve profile + +%% Default parameters +% Default based on inputs +if nargin < 2; cTYPE = "sGLA"; end +if nargin < 3; BE = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 5; FWHM = 0.25; end +if nargin < 6; MR = 0.25; end +if nargin < 7; LSE = 0; end +if nargin < 8; LSI = 0; end +if nargin < 9; LSW = 0; end +if nargin < 10; ASY = 0; end +if nargin < 11; FDEF = 0; end +if nargin < 12; FDT = 12; end +if nargin < 13; FDW = 0.05; end +if nargin < 14; plot_result = 0; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "sGLA"; end +if isempty(BE); BE = 0.00; end +if isempty(INT); INT = 1.00; end +if isempty(FWHM); FWHM = 0.25; end +if isempty(MR); MR = 0.25; end +if isempty(LSE); LSE = 0; end +if isempty(LSI); LSI = 0; end +if isempty(LSW); LSW = 0; end +if isempty(ASY); ASY = 0; end +if isempty(FDEF); FDEF = 0; end +if isempty(FDT); FDT = 12; end +if isempty(FDW); FDW = 0.05; end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +if INT < 0; INT = 0; end +if FWHM < 0; FWHM = 0; end +if MR < 0; MR = 0; end +if MR > 1; MR = 1; end +if LSI < 0; LSI = 0; end +if LSW < 0; LSW = 0; end +if ASY < -1; ASY = -1; end +if ASY > 1; ASY = 1; end +if FDW < 0; FDW = 0; end +if FDT < 0; FDT = 0; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the photoemission spectrum +% - Extracting the FDD curve +FDD_curve = FDDG(xdat, FDEF, FDT, FDW); +% - Extracting the PES curve +PES_int = PESCurve(xdat, cTYPE, BE, INT, FWHM, MR, LSE, LSI, LSW, ASY); +% - Multiplying the components together +ydat = PES_int .* FDD_curve; +% ydat = INT .* (ydat / max(ydat)); +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +%% - 2 - Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% -- For Debugging +if plot_result == 1 + % - Initialising the figure object + figure(); hold on; + % -- Plotting the 1D data + plot(xdat, ydat, 'b-', 'linewidth', 2); + plot(xdat, PES_int, 'k-', 'linewidth', 1); + plot(xdat, FDD_curve, 'r-', 'linewidth', 2); + gca_props(); title('PESCurve_FDD()', 'interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + legend({'PESCurve_FDD()', 'PESCurve()', 'FDDG()'}, 'location', 'best', 'Interpreter','none'); + % -- Determining the best limits for the plot + Y = [ydat; PES_int; FDD_curve]; + axis([min(xdat(:)), max(xdat(:)), min(Y(:)), max(Y(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/PESCurve_POT.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/PESCurve_POT.m new file mode 100644 index 0000000..17d011f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/PESCurve_POT.m @@ -0,0 +1,121 @@ +function [ydat, ydat2D] = PESCurve_POT(xdat, cTYPE, BE, INT, FWHM, MR, LSE, LSI, LSW, ASY, MFP, ZPOT, EPOT, plot_result) +% [ydat, ydat2D] = PESCurve_POT(xdat, cTYPE, BE, INT, FWHM, MR, LSE, LSI, LSW, ASY, MFP, ZPOT, EPOT, plot_result) +% Function that evaluates a generic photoelectron spectroscopy (PES) +% curve, by defining a primary (P) and spin-orbit split (SOS) component. +% A potential profile is also mapped onto the curve +% This type of curve should be used to fit near Fermi-edge EDC cuts. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - cTYPE: type of curve to use for fitting. Default: "sGLA" ("sGLA", "pGLA", "sGL", "pGL", "G", "L", "DS") +% - BE: scalar of the binding energy of PE curve. +% - INT: scalar of the peak intensity of PE curve. +% - FWHM: scalar of the FWHM of the PE curve. +% - MR: scalar of the Mixing Ratio: 0 for pure Gaussian, 1 is for pure Lorentzian. +% - LSE: scalar of the binding energy of spin-orbit split PE curve. +% - LSI: scalar of the branching ratio of spin-orbit split PE curve. +% - LSW: scalar of the additional lorentzian width of spin-orbit split PE curve. +% - ASY: scalar of the PE curve asymmetry parameter (usually for metallic systems). +% - MFP: scalar of the mean-free path of the emitted photoelectrons (either from optical, TPP-2M or fits). +% - ZPOT: 1×M array of the z-domain (depth) of the potential profile. +% - EPOT: 1×M array of the potential energy relative to the Fermi-level. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - ydat: N×1 column vector of the output PES curve profile. +% - ydat2D: N×M array of all the PES curve profiles at each point in the potential profile. + +%% Default parameters +% Default based on inputs +if nargin < 2; cTYPE = "sGLA"; end +if nargin < 3; BE = 0.00; end +if nargin < 4; INT = 1.00; end +if nargin < 5; FWHM = 0.25; end +if nargin < 6; MR = 0.25; end +if nargin < 7; LSE = 0; end +if nargin < 8; LSI = 0; end +if nargin < 9; LSW = 0; end +if nargin < 10; ASY = 0; end +if nargin < 11; MFP = 1; end +if nargin < 12; EPOT = 0; end +if nargin < 13; ZPOT = 0; end +if nargin < 14; plot_result = 0; end +% Default based on empty inputs +if isempty(cTYPE); cTYPE = "sGLA"; end +if isempty(BE); BE = 0.00; end +if isempty(INT); INT = 1.00; end +if isempty(FWHM); FWHM = 0.25; end +if isempty(MR); MR = 0.25; end +if isempty(LSE); LSE = 0; end +if isempty(LSI); LSI = 0; end +if isempty(LSW); LSW = 0; end +if isempty(ASY); ASY = 0; end +if isempty(MFP); MFP = 1; end +if isempty(EPOT); EPOT = 0; end +if isempty(ZPOT); ZPOT = 0; end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +if INT < 0; INT = 0; end +if FWHM < 0; FWHM = 0; end +if MR < 0; MR = 0; end +if MR > 1; MR = 1; end +if LSI < 0; LSI = 0; end +if LSW < 0; LSW = 0; end +if ASY < -1; ASY = -1; end +if ASY > 1; ASY = 1; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the photoemission spectrum +% - Setting the potential to be zero at the BE value +EPOT = BE + EPOT; % EPOT = BE + (EPOT - EPOT(1)); +% - Extracting the PES curve +for i = 1:length(ZPOT) + ydat2D(:,i) = PESCurve(xdat, cTYPE, EPOT(i), INT.*exp(-ZPOT(i)./MFP), FWHM, MR, LSE, LSI, LSW, ASY); +end +% - Normalising all the individual curves for comparison +ydat2D = INT .* (ydat2D ./ max(ydat2D(:))); +% - Extracting the final intensity +ydat = sum(ydat2D, 2); +ydat = INT .* (ydat / max(ydat)); +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +%% - 2 - Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% -- For Debugging +% -- Initialising the figure +if plot_result == 1 + fig = figure(); set(fig, 'position', [10, 10, 900, 400]); + cols = jet(length(ZPOT)+2); + % -- Plotting all individual curves, shifted by the potential and the final sum + subplot(121); hold on; + % --- Plotting individual curves + for i = 1:length(ZPOT) + plot(xdat, ydat2D(:,i), 'k-', 'color', cols(i,:), 'linewidth', 0.5); + end + % --- Plotting the final curve + plot(xdat, ydat, 'k-', 'linewidth', 2); + % --- Formatting the figure + gca_props(); title('PESCurve_POT()', 'Interpreter','none'); + xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); + % -- Plotting the potential profile information + subplot(122); hold on; + % --- Image of the curve series shifted by potential and scaled by MFP + ImData(ZPOT, xdat, ydat2D); + % --- Plotting the potential energy curves + plot(ZPOT, EPOT, 'r-', 'linewidth', 2); + plot(ZPOT, BE*ones(size(ZPOT)), 'g-', 'linewidth', 1); + % --- Formatting the figure + img_props(); colormap jet; + xlabel('$$ \bf z (nm) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + axis([0, max(ZPOT(:)), min(xdat(:)), max(xdat(:))]); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/pGL.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/pGL.m new file mode 100644 index 0000000..276a955 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/pGL.m @@ -0,0 +1,46 @@ +function ydat = pGL(xdat, x0, peak, fwhm, mr) +% ydat = pGL(xdat, x0, peak, fwhm, mr) +% Function that evaluates a pseudo-Voigt curve by expressing the curve +% profile as a PRODUCT of Gaussian/Lorentzian curve types. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - x0: scalar of the peak position along the x-axis of the Voigt. +% - peak: scalar of the peak height of the Voigt. +% - fwhm: scalar of the full-width at half-maximum (FWHM) of the Voigt. +% - mr: mixing ratio; 0 for pure Gaussian, 1 is for pure Lorentzian +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; x0 = 0; end +if nargin < 3; peak = 1; end +if nargin < 4; fwhm = 1; end +if nargin < 5; mr = 0.5; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +if isempty(fwhm); fwhm = 1; end +if isempty(mr); mr = 0.5; end +%% Validity checks on the input parameters +% -- If the FWHM is negative, set it to zero +if fwhm < 0; fwhm = 0; end +% -- If the MR is negative, set it to zero +if mr < 0; mr = 0; end +% -- If the MR is > 1, set it to 1 +if mr > 1; mr = 1; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the Voigt (pGL) curve intensities +% Evaluating the normalised curve profile +ydat = exp(-4.*log(2).*(1-mr).*((xdat-x0).^2 ./ fwhm.^2)) ./ (1 + 4.*mr.*((xdat-x0).^2 ./ fwhm.^2)); +% Scaling the curve profile to match the desired peak +ydat = ydat ./ max(ydat(:)); +ydat = peak .* ydat; +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/pGLA.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/pGLA.m new file mode 100644 index 0000000..b3f6fca --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/pGLA.m @@ -0,0 +1,54 @@ +function ydat = pGLA(xdat, x0, peak, fwhm, mr, asym) +% ydat = pGLA(xdat, x0, peak, fwhm, mr, asym) +% Function that evaluates a, asymmetric pseudo-Voigt curve by expressing +% the curve profile as a PRODUCT of Gaussian/Lorentzian curve types. +% The curve is modified here with the asymmetric, exponential blend, +% where: pGLA(x) = pGL(x) + AEB(x) * (1 - pGL(x)). +% AEB(x) is determined from (AEB()). +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - x0: scalar of the peak position along the x-axis of the Voigt. +% - peak: scalar of the peak height of the Voigt. +% - fwhm: scalar of the full-width at half-maximum (FWHM) of the Voigt. +% - mr: mixing ratio; 0 for pure Gaussian, 1 is for pure Lorentzian +% - asym: asymmetry ratio; 0 for none, 1 is for maximum +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; x0 = 0; end +if nargin < 3; peak = 1; end +if nargin < 4; fwhm = 1; end +if nargin < 5; mr = 0.5; end +if nargin < 6; asym = 0.5; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +if isempty(fwhm); fwhm = 1; end +if isempty(mr); mr = 0.5; end +if isempty(asym); asym = 0.5; end +%% Validity checks on the input parameters +if fwhm < 0; fwhm = 0; end +if mr < 0; mr = 0; end +if mr > 1; mr = 1; end +if asym < -1; asym = -1; end +if asym > 1; asym = 1; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the Voigt (pGL) curve intensities +int_pGL = pGL(xdat, x0, peak, fwhm, mr); +%% - 2 - Determination of the Exponential Asymmetric Blend (AEB) intensities +int_AEB = AEB(xdat, x0, asym); +%% - 3 - Determination of pGLA curve intensities +ydat = int_pGL + int_AEB .* (max(int_pGL(:)) - int_pGL); +% Scaling the curve profile to match the desired peak +ydat = ydat ./ max(ydat(:)); +ydat = peak .* ydat; +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/pGLA_FDD.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/pGLA_FDD.m new file mode 100644 index 0000000..37a1bd0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/pGLA_FDD.m @@ -0,0 +1,67 @@ +function ydat = pGLA_FDD(xdat, x0, peak, fwhm, mr, asym, fdd_ef, fdd_T, fdd_fwhm) +% ydat = pGLA_FDD(xdat, x0, peak, fwhm, mr, asym, fdd_ef, fdd_T, fdd_fwhm) +% Function that evaluates an asymmetric pseudo-Voigt curve with the +% pGLA() function, after which it is multiplied by the Fermi-Dirac +% Distribution FDDG(). These curve shapes are used for fitting EDCs near +% the Fermi-edge, where the curve profiles may be chopped slightly due to +% the close proximity of the Fermi-edge. +% +% REQ. FUNCTIONS: +% - pGLA() +% - FDDG() +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - x0: scalar of the peak position along the x-axis of the Voigt. +% - peak: scalar of the peak height of the Voigt. +% - fwhm: scalar of the full-width at half-maximum (FWHM) of the Voigt. +% - mr: mixing ratio; 0 for pure Gaussian, 1 is for pure Lorentzian +% - asym: asymmetry ratio; 0 for none, 1 is for maximum +% - fdd_ef: scalar of the Fermi-level position (eV). +% - fdd_T: scalar of the temperature (K). +% - fdd_fwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian broadening term (eV). +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; x0 = 0; end +if nargin < 3; peak = 1; end +if nargin < 4; fwhm = 1; end +if nargin < 5; mr = 0.5; end +if nargin < 6; asym = 0.5; end +if nargin < 7; fdd_ef = 0; end +if nargin < 8; fdd_T = 12; end +if nargin < 9; fdd_fwhm = 0; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +if isempty(fwhm); fwhm = 1; end +if isempty(mr); mr = 0.5; end +if isempty(asym); asym = 0.5; end +if isempty(fdd_ef); fdd_ef = 0; end +if isempty(fdd_T); fdd_T = 12; end +if isempty(fdd_fwhm); fdd_fwhm = 0; end +%% Validity checks on the input parameters +if fwhm < 0; fwhm = 0; end +if mr < 0; mr = 0; end +if mr > 1; mr = 1; end +if asym < -1; asym = -1; end +if asym > 1; asym = 1; end +if fdd_T < 0; fdd_T = 0; end +if fdd_fwhm < 0; fdd_fwhm = 0; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% 1 - Determining the FDD and Gaussian functions to use +% - Extracting the intensity of the curve +int_pGLA = pGLA(xdat, x0, peak, fwhm, mr, asym); +% - Extracting the intensity of the FDD curve +int_FDDG = FDDG(xdat, fdd_ef, fdd_T, fdd_fwhm); + +%% 2 - Multiplying the two functions together +ydat = int_FDDG .* int_pGLA; +ydat = peak .* ydat / max(ydat); +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/sGL.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/sGL.m new file mode 100644 index 0000000..c1d7ad8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/sGL.m @@ -0,0 +1,46 @@ +function ydat = sGL(xdat, x0, peak, fwhm, mr) +% ydat = sGL(xdat, x0, peak, fwhm, mr) +% Function that evaluates a pseudo-Voigt curve by expressing the curve +% profile as a SUM of Gaussian/Lorentzian curve types. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - x0: scalar of the peak position along the x-axis of the Voigt. +% - peak: scalar of the peak height of the Voigt. +% - fwhm: scalar of the full-width at half-maximum (FWHM) of the Voigt. +% - mr: mixing ratio; 0 for pure Gaussian, 1 is for pure Lorentzian +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; x0 = 0; end +if nargin < 3; peak = 1; end +if nargin < 4; fwhm = 1; end +if nargin < 5; mr = 0.5; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +if isempty(fwhm); fwhm = 1; end +if isempty(mr); mr = 0.5; end +%% Validity checks on the input parameters +% -- If the FWHM is negative, set it to zero +if fwhm < 0; fwhm = 0; end +% -- If the MR is negative, set it to zero +if mr < 0; mr = 0; end +% -- If the MR is > 1, set it to 1 +if mr > 1; mr = 1; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the Voigt (pGL) curve intensities +% Evaluating the normalised curve profile +ydat = (1-mr).*exp(-4.*log(2).*((xdat-x0).^2 ./ fwhm.^2)) + mr ./ (1 + 4.*((xdat-x0).^2 ./ fwhm.^2)); +% Scaling the curve profile to match the desired peak +ydat = ydat ./ max(ydat(:)); +ydat = peak .* ydat; +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/sGLA.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/sGLA.m new file mode 100644 index 0000000..8f3befc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/sGLA.m @@ -0,0 +1,55 @@ +function ydat = sGLA(xdat, x0, peak, fwhm, mr, asym) +% ydat = sGLA(xdat, x0, peak, fwhm, mr, asym) +% Function that evaluates a, asymmetric pseudo-Voigt curve by expressing +% the curve profile as a SUM of Gaussian/Lorentzian curve types. +% The curve is modified here with the asymmetric, exponential blend, +% where: sGLA(x) = sGL(x) + AEB(x) * (1 - sGL(x)). +% AEB(x) is determined from (AEB()). +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - x0: scalar of the peak position along the x-axis of the Voigt. +% - peak: scalar of the peak height of the Voigt. +% - fwhm: scalar of the full-width at half-maximum (FWHM) of the Voigt. +% - mr: mixing ratio; 0 for pure Gaussian, 1 is for pure Lorentzian +% - asym: asymmetry ratio; 0 for none, 1 is for maximum +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; x0 = 0; end +if nargin < 3; peak = 1; end +if nargin < 4; fwhm = 1; end +if nargin < 5; mr = 0.5; end +if nargin < 6; asym = 0.5; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +if isempty(fwhm); fwhm = 1; end +if isempty(mr); mr = 0.5; end +if isempty(asym); asym = 0.5; end +%% Validity checks on the input parameters +% -- If the FWHM is negative, set it to zero +if fwhm < 0; fwhm = 0; end +% -- If the MR is negative, set it to zero +if mr < 0; mr = 0; end +% -- If the MR is > 1, set it to 1 +if mr > 1; mr = 1; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% - 1 - Determination of the Voigt (sGL) curve intensities +int_sGL = sGL(xdat, x0, peak, fwhm, mr); +%% - 2 - Determination of the Exponential Asymmetric Blend (AEB) intensities +int_AEB = AEB(xdat, x0, asym); +%% - 3 - Determination of sGLA curve intensities +ydat = int_sGL + int_AEB .* (max(int_sGL(:)) - int_sGL); +% Scaling the curve profile to match the desired peak +ydat = ydat ./ max(ydat(:)); +ydat = peak .* ydat; +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/sGLA_FDD.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/sGLA_FDD.m new file mode 100644 index 0000000..1021ef6 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F003 - model curves/pes model curves/sGLA_FDD.m @@ -0,0 +1,67 @@ +function ydat = sGLA_FDD(xdat, x0, peak, fwhm, mr, asym, fdd_ef, fdd_T, fdd_fwhm) +% ydat = sGLA_FDD(xdat, x0, peak, fwhm, mr, asym, fdd_ef, fdd_T, fdd_fwhm) +% Function that evaluates an asymmetric pseudo-Voigt curve with the +% sGLA() function, after which it is multiplied by the Fermi-Dirac +% Distribution FDDG(). These curve shapes are used for fitting EDCs near +% the Fermi-edge, where the curve profiles may be chopped slightly due to +% the close proximity of the Fermi-edge. +% +% REQ. FUNCTIONS: +% - sGLA() +% - FDDG() +% +% IN: +% - xdat: N×1 column vector of the input domain (binding energy for PES). +% - x0: scalar of the peak position along the x-axis of the Voigt. +% - peak: scalar of the peak height of the Voigt. +% - fwhm: scalar of the full-width at half-maximum (FWHM) of the Voigt. +% - mr: mixing ratio; 0 for pure Gaussian, 1 is for pure Lorentzian +% - asym: asymmetry ratio; 0 for none, 1 is for maximum +% - fdd_ef: scalar of the Fermi-level position (eV). +% - fdd_T: scalar of the temperature (K). +% - fdd_fwhm: scalar of the full-width at half-maximum (FWHM) of the Gaussian broadening term (eV). +% +% OUT: +% - ydat: N×1 column vector of the intensity range (intensity for PES). + +%% Default parameters +if nargin < 2; x0 = 0; end +if nargin < 3; peak = 1; end +if nargin < 4; fwhm = 1; end +if nargin < 5; mr = 0.5; end +if nargin < 6; asym = 0.5; end +if nargin < 7; fdd_ef = 0; end +if nargin < 8; fdd_T = 12; end +if nargin < 9; fdd_fwhm = 0; end +if isempty(x0); x0 = 0; end +if isempty(peak); peak = 1; end +if isempty(fwhm); fwhm = 1; end +if isempty(mr); mr = 0.5; end +if isempty(asym); asym = 0.5; end +if isempty(fdd_ef); fdd_ef = 0; end +if isempty(fdd_T); fdd_T = 12; end +if isempty(fdd_fwhm); fdd_fwhm = 0; end +%% Validity checks on the input parameters +if fwhm < 0; fwhm = 0; end +if mr < 0; mr = 0; end +if mr > 1; mr = 1; end +if asym < -1; asym = -1; end +if asym > 1; asym = 1; end +if fdd_T < 0; fdd_T = 0; end +if fdd_fwhm < 0; fdd_fwhm = 0; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end + +%% 1 - Determining the FDD and Gaussian functions to use +% - Extracting the intensity of the curve +int_sGLA = sGLA(xdat, x0, peak, fwhm, mr, asym); +% - Extracting the intensity of the FDD curve +int_FDDG = FDDG(xdat, fdd_ef, fdd_T, fdd_fwhm); + +%% 2 - Multiplying the two functions together +ydat = int_FDDG .* int_sGLA; +ydat = peak .* ydat / max(ydat); +% If isnan, return zero +ydat(isnan(ydat)) = 0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/Example_curvefit1D.mlx b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/Example_curvefit1D.mlx new file mode 100644 index 0000000..3f87215 Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/Example_curvefit1D.mlx differ diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/curvefit1D_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/curvefit1D_solver.m new file mode 100644 index 0000000..1324457 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/curvefit1D_solver.m @@ -0,0 +1,398 @@ +function fitStr = curvefit1D_solver(xdat, ydat, curve_type, init_params, bgrnd_type, init_bgrnd, solve_type) +% fitStr = curvefit1D_solver(xdat, ydat, curve_type, init_params, bgrnd_type, init_bgrnd, solve_type) +% Function that runs an Optimisation Algorithm to determine the best fit +% for N-curves of a 1D data set defined by 'xdat' (domain) and 'ydat' +% (range). If 'curve_type' is empty, an asymmetric pseudo-Voigt curve is +% used. 'init_params' is the cell array that defines the initial guess +% and lower-, upper-bound constraints of the fit parameters. +% +% IN: +% - xdat: [nX × 1] array of the x-axis data +% - ydat: [nY × 1] array of the y-axis data +% - curve_type: string of the type of curve to be used for fitting. Default: "sGLA" ("pGLA", "sGL", "pGL", "G", "L", "DS") +% - init_params: {3 × 1} cell array of {x0}{lb}{ub}, where each cell is an [N × 8] matrix of N'th peak parameters: [XLOC,YINT,FWHM,MR,ASY,LSX,LSY,LSW] +% - [bgrnd_type]: string of the type of background to use for fitting. Default: "none" ("Poly", "Shir", "LinShir") +% - [init_bgrnd]: {3 × 1} cell array of {x0}{lb}{ub}, where each cell is an [1 × 5] matrix of the background parameters: [LHS,RHS,ORD,LAM,DEL,BGR] +% - [solve_type]: string of the optimisation algorithm to use; "lsqcurvefit" (very fast, good), "fminunc" (quick, good), "simulannealbnd" (slow, best). +% Default: "lsqcurvefit" ("lsqcurvefit", "fminunc", "fmincon", "fminunc-std", "simulannealbnd", "simulannealbnd-std") +% +% OUT: +% - fitStr: MATLAB data-structure that contains all fit parameters / variables / information + +%% Default input parameters & consistency checks +pp = plot_props(); +% -- Defining input parameters if undefined +if nargin < 7; solve_type = "lsqcurvefit"; end +if nargin < 6; init_bgrnd{1} = [min(xdat(:)), max(xdat(:)), 1, 0.5, 0, 0]; init_bgrnd{2} = init_bgrnd{1}; init_bgrnd{2}(6) = -0.10; init_bgrnd{3} = init_bgrnd{1}; init_bgrnd{3}(6) = 0.10; end +if nargin < 5; bgrnd_type = "none"; end +if isempty(solve_type); solve_type = "lsqcurvefit"; end +if isempty(init_bgrnd); init_bgrnd{1} = [min(xdat(:)), max(xdat(:)), 1, 0.5, 0, 0]; init_bgrnd{2} = init_bgrnd{1}; init_bgrnd{2}(6) = -0.10; init_bgrnd{3} = init_bgrnd{1}; init_bgrnd{3}(6) = 0.10; end +if isempty(bgrnd_type); bgrnd_type = "none"; end +if isempty(curve_type); curve_type = "sGLA"; end +% -- Consistency check and finding the total number of curves +if size(init_params{1}, 1) ~= size(init_params{2}, 1) || size(init_params{2}, 1) ~= size(init_params{3}, 1) + error('The input parameter cell array is not a consistent size - check iparams input!'); +end +% -- Extracting the total number of curves +ncurves = size(init_params{1}, 1); +% -- Validity check on input parameters +for i = 1:ncurves + if size(init_params{1}, 2) == 4 + % --- Set the ASY, LSE, LSI and LSW components to zero + init_params{1}(i,5) = 0; init_params{1}(i,6) = 0; init_params{1}(i,7) = 0; init_params{1}(i,8) = 0; + init_params{2}(i,5) = 0; init_params{2}(i,6) = 0; init_params{2}(i,7) = 0; init_params{2}(i,8) = 0; + init_params{3}(i,5) = 0; init_params{3}(i,6) = 0; init_params{3}(i,7) = 0; init_params{3}(i,8) = 0; + elseif size(init_params{1}, 2) == 5 + % --- Set the LSE, LSI and LSW components to zero + init_params{1}(i,6) = 0; init_params{1}(i,7) = 0; init_params{1}(i,8) = 0; + init_params{2}(i,6) = 0; init_params{2}(i,7) = 0; init_params{2}(i,8) = 0; + init_params{3}(i,6) = 0; init_params{3}(i,7) = 0; init_params{3}(i,8) = 0; + elseif size(init_params{1}, 2) == 6 + % --- Set the LSI and LSW components to zero + init_params{1}(i,7) = 0; init_params{1}(i,8) = 0; + init_params{2}(i,7) = 0; init_params{2}(i,8) = 0; + init_params{3}(i,7) = 0; init_params{3}(i,8) = 0; + elseif size(init_params{1}, 2) == 7 + % --- Set the LSW components to zero + init_params{1}(i,8) = 0; + init_params{2}(i,8) = 0; + init_params{3}(i,8) = 0; + elseif size(init_params{1}, 2) > 8 || size(init_params{1}, 2) < 4 + error('Not enough input arguments defined - check iparams input!'); + end +end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Defining the initial conditions and limits of the optimisation method +x0 = [init_params{1}(:); init_bgrnd{1}(:)]; +lb = [init_params{2}(:); init_bgrnd{2}(:)]; +ub = [init_params{3}(:); init_bgrnd{3}(:)]; +% -- Defining the initial conditions and limits of the optimisation method +for i = 1:ncurves + indx = i:ncurves:(length(x0)-6); + X0 = x0(indx); LB = lb(indx); UB = ub(indx); + % --- parameters + if X0(2) < 0; x0(indx(2)) = 0; end % if YINT < 0, then make it 0 + if X0(3) < 0; x0(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if X0(4) < 0; x0(indx(4)) = 0; end % if MR < 0, then make it 0 + if X0(4) > 1; x0(indx(4)) = 1; end % if MR > 1, then make it 1 + if X0(5) < 0; x0(indx(5)) = 0; end % if ASY < 0, then make it 0 + if X0(7) < 0; x0(indx(7)) = 0; end % if LSY < 0, then make it 0 + if X0(8) < 0; x0(indx(8)) = 0; end % if LSW < 0, then make it 0 + % --- lower bounds + if LB(2) < 0; lb(indx(2)) = 0; end % if YINT < 0, then make it 0 + if LB(3) < 0; lb(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if LB(4) < 0; lb(indx(4)) = 0; end % if MR < 0, then make it 0 + if LB(4) > 1; lb(indx(4)) = 1; end % if MR > 1, then make it 1 + if LB(5) < 0; lb(indx(5)) = 0; end % if ASY < 0, then make it 0 + if LB(7) < 0; lb(indx(7)) = 0; end % if LSY < 0, then make it 0 + if LB(8) < 0; lb(indx(8)) = 0; end % if LSW < 0, then make it 0 + % --- lower bounds + if UB(2) < 0; ub(indx(2)) = 0; end % if YINT < 0, then make it 0 + if UB(3) < 0; ub(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if UB(4) < 0; ub(indx(4)) = 0; end % if MR < 0, then make it 0 + if UB(4) > 1; ub(indx(4)) = 1; end % if MR > 1, then make it 1 + if UB(5) < 0; ub(indx(5)) = 0; end % if ASY < 0, then make it 0 + if UB(7) < 0; ub(indx(7)) = 0; end % if LSY < 0, then make it 0 + if UB(8) < 0; ub(indx(8)) = 0; end % if LSW < 0, then make it 0 + % --- forcing the background polynomial order to be an integer + x0(end-3) = round(ceil(x0(end-3))); + lb(end-3) = round(ceil(lb(end-3))); + ub(end-3) = round(ceil(ub(end-3))); + % --- forcing the lambda parameters between 0->1 (linear vs shirley mixing ratio) + if x0(end-2) < 0; x0(end-2) = 0; end % if LAM < 0, then make it 0 + if lb(end-2) < 0; lb(end-2) = 0; end % if LAM < 0, then make it 0 + if ub(end-2) < 0; ub(end-2) = 0; end % if LAM < 0, then make it 0 + if x0(end-2) > 1; x0(end-2) = 1; end % if LAM > 1, then make it 1 + if lb(end-2) > 1; lb(end-2) = 1; end % if LAM > 1, then make it 1 + if ub(end-2) > 1; ub(end-2) = 1; end % if LAM > 1, then make it 1 +end +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - DEFINING THE ROI DATA AND FITTING ARGUMENTS +% -- Extracting the data to be fitted +[roi_xdat, roi_ydat, roi_bgrnd] = PESBackground(xdat, ydat, bgrnd_type, x0(end-5), x0(end-4), x0(end-3), x0(end-2), x0(end-1), x0(end)); +% -- Defining a structure that stores all relevant model and data variables +FitObj = struct(); +FitObj.xdat = xdat; +FitObj.ydat = ydat; +FitObj.roi_xdat = roi_xdat; +FitObj.roi_ydat = roi_ydat; +FitObj.roi_bgrnd = roi_bgrnd; +% -- Appending the input arguments to the global variable +FitObj.fit_args.solve_type = solve_type; +FitObj.fit_args.ncurves = ncurves; +FitObj.fit_args.curve_type = curve_type; +FitObj.fit_args.init_params = init_params; +FitObj.fit_args.bgrnd_type = bgrnd_type; +FitObj.fit_args.init_bgrnd = init_bgrnd; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 5e3; +FuncTol = 1e-10; % 1e-7; +StepTol = 1e-10; % 1e-7; +OptTol = 1e-10; % 1e-7; +ConTol = 1e-10; % 1e-7; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; + +%% - 3.1 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR CURVE FITTING +if solve_type == "lsqcurvefit" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqcurvefit,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); % 'Display', 'iter' + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqcurvefit(@(x,roi_xdat) full_pes_function(x,roi_xdat,FitObj), x0, roi_xdat, roi_ydat, lb, ub, options); + +%% - 3.2 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); % 'Display', 'iter' + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,grad,hessian] = fminunc(@(x) minimize_function(x,FitObj), x0, options); + +%% - 3.3 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,FitObj), x0, [], [], [], [], lb, ub, [], options); + +%% - 3.4 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION (MINIMISE STD) +elseif solve_type == "fmincon-std" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function_std(x,FitObj), x0, [], [], [], [], lb, ub, [], options); + + +%% - 3.5 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,FitObj), x0, lb, ub, options); + +%% - 3.6 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE STD +elseif solve_type == "simulannealbnd-std" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function_std(x,FitObj), x0, lb, ub, options); +end + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.curve_type = curve_type; +fitStr.init_params = init_params; +fitStr.bgrnd_type = bgrnd_type; +fitStr.init_bgrnd = init_bgrnd; +fitStr.ncurves = ncurves; +%% 4.2 - Storing the XPS data, background, model and minimisation variables +% -- Extracting the original data +fitStr.xdat = xdat; +fitStr.ydat = ydat; +% -- Extracting the X-DOMAIN and DATA +[fitStr.X, fitStr.D] = fit_data(params, FitObj); +% -- Extracting the MODEL +fitStr.M = fit_model(params, FitObj); +% -- Extracting the BACKGROUND +fitStr.B = fit_background(params, FitObj); +% -- Extracting the DATA - BACKGROUND +fitStr.DB = fitStr.D - fitStr.B; +fitStr.MB = fitStr.M + fitStr.B; +% -- Extracting the RESIDUALS (R = M - (D + B)) +fitStr.R = fitStr.D - (fitStr.M + fitStr.B); +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ = sum(fitStr.R.^2 ./ abs(fitStr.M + fitStr.B)); +fitStr.MINFUN = minimize_function(params, FitObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables for the PES background +fitStr.bgrnd_params = params(end-5:end); +fitStr.LHS = fitStr.bgrnd_params(1); +fitStr.RHS = fitStr.bgrnd_params(2); +fitStr.ORD = fitStr.bgrnd_params(3); +fitStr.LAM = fitStr.bgrnd_params(4); +fitStr.DEL = fitStr.bgrnd_params(5); +fitStr.BGR = fitStr.bgrnd_params(6); +%% 4.4 - Storing the final fit variables of each PES curve component +fitStr.XX = linspace(min(fitStr.X(:)), max(fitStr.X(:)), 1e3)'; +fitStr.YY = zeros(size(fitStr.XX)); +for i = 1:fitStr.ncurves + % --- Best fit components on new domain + fitStr.curve_params(i,:) = params(i:fitStr.ncurves:(end-6)); + fitStr.cYY(:,i) = PESCurve(fitStr.XX, fitStr.curve_type,... + fitStr.curve_params(i,1), fitStr.curve_params(i,2), fitStr.curve_params(i,3),... + fitStr.curve_params(i,4), fitStr.curve_params(i,6), fitStr.curve_params(i,7),... + fitStr.curve_params(i,8), fitStr.curve_params(i,5)); + fitStr.YY = fitStr.YY + fitStr.cYY(:,i); + % --- Storing each curve parameter + fitStr.XLOC(i) = fitStr.curve_params(i,1); + fitStr.YINT(i) = fitStr.curve_params(i,2); + fitStr.FWHM(i) = fitStr.curve_params(i,3); + fitStr.MR(i) = fitStr.curve_params(i,4); + fitStr.ASY(i) = fitStr.curve_params(i,5); + fitStr.LSX(i) = fitStr.curve_params(i,6); + fitStr.LSY(i) = fitStr.curve_params(i,7); + fitStr.LSW(i) = fitStr.curve_params(i,8); + % --- Storing the curve area information + fitStr.AREA(i) = trapz(fitStr.XX, fitStr.cYY(:,i)); +end +% --- Storing the normalised area contribution for quantification +fitStr.AREA0 = fitStr.AREA ./ trapz(fitStr.XX, fitStr.YY); + +end + +%% DEFINING THE RESIDUAL MINIMISATION FUNCTION TO XLOC MINIMISED +function MINFUN = minimize_function(x, FitObj) + % - 1 - Extracting the DATA + [~, D] = fit_data(x, FitObj); + % - 2 - Extracting the MODEL + M = fit_model(x, FitObj); + % - 3 - Extracting the BACKGROUND + B = fit_background(x, FitObj); + % - 4 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - (M + B); + % - 5 - Extracting the CHI-SQUARED value to be minimised + MINFUN = sum(R.^2 ./ abs(M + B)); +end + +%% DEFINING THE FUNCTION TO XLOC MINIMISED VIA STD +function MINFUN = minimize_function_std(x, FitObj) + % - 1 - Extracting the DATA + [~, D] = fit_data(x, FitObj); + % - 2 - Extracting the MODEL + M = fit_model(x, FitObj); + % - 3 - Extracting the BACKGROUND + B = fit_background(x, FitObj); + % - 4 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - (M + B); + % - 5 - Extracting the CHI-SQUARED value to be minimised + MINFUN = std(R.^2 ./ abs(M + B)); +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE XPS DATA TO XLOC FITTED +function [X, D] = fit_data(x, FitObj) + [X, D, ~] = PESBackground(FitObj.xdat, FitObj.ydat, FitObj.fit_args.bgrnd_type, x(end-5), x(end-4), x(end-3), x(end-2), x(end-1), x(end)); + D(isnan(D)) = 0; + if size(D, 2) > 1; D = D'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES BACKGROUND +function B = fit_background(x, FitObj) + [~, ~, B] = PESBackground(FitObj.xdat, FitObj.ydat, FitObj.fit_args.bgrnd_type, x(end-5), x(end-4), x(end-3), x(end-2), x(end-1), x(end)); + B(isnan(B)) = 0; + if size(B, 2) > 1; B = B'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES CURVE FIT +function M = fit_model(x, FitObj) + % - 1 - Extract the curve component for each state + comp_int = {}; + for i = 1:FitObj.fit_args.ncurves + % -- Extracting the arguments for the component curve + pes_args = x(i:FitObj.fit_args.ncurves:(end-6)); + % -- Extracting the component intensities + comp_int{i} = PESCurve(FitObj.roi_xdat, FitObj.fit_args.curve_type,... + pes_args(1), pes_args(2), pes_args(3),... + pes_args(4), pes_args(6), pes_args(7),... + pes_args(8), pes_args(5)); + end + % - 2 - Sum up all of the curve components to get the final model PES curve + pes_int = zeros(size(FitObj.roi_xdat)); + for i = 1:FitObj.fit_args.ncurves + pes_int = pes_int + comp_int{i}; + end + M = pes_int; + M(isnan(M)) = 0; + if size(M, 2) > 1; M = M'; end +end + +%% DEFINING THE FINAL FUNCTION THAT DESCRIXLOCS THE PES CURVE TO XLOC FITTED +function MB = full_pes_function(x, xdat, FitObj) + % - 1 - Extract the curve component for each state + comp_int = {}; + for i = 1:FitObj.fit_args.ncurves + % -- Extracting the arguments for the component curve + pes_args = x(i:FitObj.fit_args.ncurves:(end-6)); + % -- Extracting the component intensities + comp_int{i} = PESCurve(xdat, FitObj.fit_args.curve_type,... + pes_args(1), pes_args(2), pes_args(3),... + pes_args(4), pes_args(6), pes_args(7),... + pes_args(8), pes_args(5)); + end + % - 2 - Sum up all of the curve components to get the final model PES curve + pes_int = zeros(size(xdat)); + for i = 1:FitObj.fit_args.ncurves + pes_int = pes_int + comp_int{i}; + end + M = pes_int; + % - 3 - Determine the background to be used + [~, ~, B] = PESBackground(xdat, FitObj.roi_ydat, FitObj.fit_args.bgrnd_type, x(end-5), x(end-4), x(end-3), x(end-2), x(end-1), x(end)); + % - 4 - Final output is the sum of the model and background + MB = M + B; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/curvefit1D_view_fit.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/curvefit1D_view_fit.m new file mode 100644 index 0000000..b723b52 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/curvefit1D_view_fit.m @@ -0,0 +1,70 @@ +function fig = curvefit1D_view_fit(fitStr) +% fig = curvefit1D_view_fit(fitStr) +% This function is used to plot the results of the curve fitting +% performed by 'fitStr = curvefit1D_solver(...)'. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - fitStr: MATLAB data-structure that contains all fit parameters / variables / information +% +% OUT: +% - fig: MATLAB figure object showing the final best fit + +%% Initialising the plot parameters +pp = plot_props(); +% - Finding the optimal y-limits +minY = min([min(fitStr.cYY(:)), min(fitStr.M(:)), min(fitStr.D(:)), min(fitStr.B(:))]); +maxY = 1.25*max([max(fitStr.cYY(:)), max(fitStr.M(:)), max(fitStr.D(:)), max(fitStr.B(:))]); +ylims = [minY, maxY]; +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'Curve Fit 1D - Final Fit'); +fig.Position(3) = 2.5*pp.fig5x4(1); +fig.Position(4) = 1.0*pp.fig5x4(2); +% -- Plotting the raw data and background +subplot(121); hold on; +h = patch(... + [fitStr.init_bgrnd{1}(1), fitStr.init_bgrnd{1}(1), fitStr.init_bgrnd{1}(2), fitStr.init_bgrnd{1}(2), fitStr.init_bgrnd{1}(1)],... + [-1, 1, 1, -1, -1].*1e4, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', [0 0 0]); +h.Annotation.LegendInformation.IconDisplayStyle = 'off'; +plot(fitStr.xdat, fitStr.ydat, 'b-', 'linewidth', 0.5*pp.lwidth); +plot(fitStr.X, fitStr.D, 'b-', 'linewidth', pp.llwidth); +plot(fitStr.X, fitStr.B, 'r-', 'linewidth', pp.llwidth); +plot(fitStr.X, fitStr.DB, 'k-', 'linewidth', pp.llwidth); +gca_props(); grid on; +xlabel('$$ \bf X $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); +axis([min(fitStr.xdat(:)), max(fitStr.xdat(:)), ylims]); +legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); +title("Background Subtraction", 'interpreter', 'none', 'fontsize', 9); +% -- Plotting the best fit curve components and the initial model +subplot(4,2,[2,4,6]); hold on; +% -- Plotting all of the curve components +for i = 1:fitStr.ncurves + area(fitStr.XX, fitStr.cYY(:,i), 'FaceColor', pp.col.fit{i}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); + plot(fitStr.XX, fitStr.cYY(:,i), 'k-', 'linewidth', 0.25); +end +% -- Plotting the curve component energy locations +for i = 1:fitStr.ncurves + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + line([fitStr.init_params{1}(i,1), fitStr.init_params{1}(i,1)], [0, max(fitStr.cYY(:,i))],... + 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '-'); +end +% -- Plotting the experimental and fit spectra +plot(fitStr.X, fitStr.DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(fitStr.X, fitStr.M, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(fitStr.CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Y$$', 'Interpreter', 'latex'); +axis([min(fitStr.X(:)), max(fitStr.X(:)), ylims]); +title("Final Fit", 'interpreter', 'none', 'fontsize', 9); + +% -- Plotting the residuals of the model +subplot(4,2,8); hold on; +bar(fitStr.X, fitStr.R, 'facecolor', [0 0 0]); +gca_props(); grid on; +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +xlabel('$$ \bf X $$', 'Interpreter', 'latex'); diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/curvefit1D_view_init.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/curvefit1D_view_init.m new file mode 100644 index 0000000..ffb0f57 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/curvefit1D (needs debugging)/curvefit1D_view_init.m @@ -0,0 +1,166 @@ +function fig = curvefit1D_view_init(xdat, ydat, curve_type, init_params, bgrnd_type, init_bgrnd) +% fig = curvefit1D_view_init(xdat, ydat, curve_type, init_params, bgrnd_type, init_bgrnd) +% This function is used to plot the initial curve fitting model prior to +% using the 'curvefit1D_solver()' algorithm. This is used as an informative +% plot that allows you to view and create a better initial guess of the +% model prior to running the fitting algorithm. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - xdat: [nX x 1] array of the x-axis data +% - ydat: [nY x 1] array of the y-axis data +% - curve_type: string of the type of curve to be used for fitting. Default: "sGLA" ("pGLA", "sGL", "pGL", "G", "L", "DS") +% - init_params: {3 x 1} cell array of {x0}{lb}{ub}, where each cell is an [N x 8] matrix of N'th peak parameters: [XLOC,YINT,FWHM,MR,ASY,LSX,LSY,LSW] +% - [bgrnd_type]: string of the type of background to use for fitting. Default: "none" ("Poly", "Shir", "LinShir") +% - [init_bgrnd]: {3 x 1} cell array of {x0}{lb}{ub}, where each cell is an [1 x 5] matrix of the background parameters: [LHS,RHS,ORD,LAM,DEL,BGR] +% +% OUT: +% - fig: MATLAB figure object showing the initial model + +%% Default input parameters & consistency checks +pp = plot_props(); +% -- Defining input parameters if undefined +if nargin < 6; init_bgrnd{1} = [min(xdat(:)), max(xdat(:)), 1, 0.5, 0, 0]; init_bgrnd{2} = init_bgrnd{1}; init_bgrnd{2}(6) = min(ydat(:)); init_bgrnd{3} = init_bgrnd{1}; init_bgrnd{3}(6) = max(ydat(:)); end +if nargin < 5; bgrnd_type = "none"; end +if isempty(init_bgrnd); init_bgrnd{1} = [min(xdat(:)), max(xdat(:)), 1, 0.5, 0, 0]; init_bgrnd{2} = init_bgrnd{1}; init_bgrnd{2}(6) = min(ydat(:)); init_bgrnd{3} = init_bgrnd{1}; init_bgrnd{3}(6) = max(ydat(:)); end +if isempty(bgrnd_type); bgrnd_type = "none"; end +if isempty(curve_type); curve_type = "sGLA"; end +% -- Consistency check and finding the total number of curves +if size(init_params{1}, 1) ~= size(init_params{2}, 1) || size(init_params{2}, 1) ~= size(init_params{3}, 1) + error('The input parameter cell array is not a consistent size - check iparams input!'); +end +% -- Extracting the total number of curves +ncurves = size(init_params{1}, 1); +% -- Validity check on input parameters +for i = 1:ncurves + if size(init_params{1}, 2) == 4 + % --- Set the ASY, LSE, LSI and LSW components to zero + init_params{1}(i,5) = 0; init_params{1}(i,6) = 0; init_params{1}(i,7) = 0; init_params{1}(i,8) = 0; + init_params{2}(i,5) = 0; init_params{2}(i,6) = 0; init_params{2}(i,7) = 0; init_params{2}(i,8) = 0; + init_params{3}(i,5) = 0; init_params{3}(i,6) = 0; init_params{3}(i,7) = 0; init_params{3}(i,8) = 0; + elseif size(init_params{1}, 2) == 5 + % --- Set the LSE, LSI and LSW components to zero + init_params{1}(i,6) = 0; init_params{1}(i,7) = 0; init_params{1}(i,8) = 0; + init_params{2}(i,6) = 0; init_params{2}(i,7) = 0; init_params{2}(i,8) = 0; + init_params{3}(i,6) = 0; init_params{3}(i,7) = 0; init_params{3}(i,8) = 0; + elseif size(init_params{1}, 2) == 6 + % --- Set the LSI and LSW components to zero + init_params{1}(i,7) = 0; init_params{1}(i,8) = 0; + init_params{2}(i,7) = 0; init_params{2}(i,8) = 0; + init_params{3}(i,7) = 0; init_params{3}(i,8) = 0; + elseif size(init_params{1}, 2) == 7 + % --- Set the LSW components to zero + init_params{1}(i,8) = 0; + init_params{2}(i,8) = 0; + init_params{3}(i,8) = 0; + elseif size(init_params{1}, 2) > 8 || size(init_params{1}, 2) < 4 + error('Not enough input arguments defined - check iparams input!'); + end +end + +%% - 1 - Extracting all of the curve parameters +for i = 1:ncurves + XLOC(i) = init_params{1}(i,1); lbXLOC(i) = init_params{2}(i,1); ubXLOC(i) = init_params{3}(i,1); + YINT(i) = init_params{1}(i,2); lbYINT(i) = init_params{2}(i,2); ubYINT(i) = init_params{3}(i,2); + FWHM(i) = init_params{1}(i,3); lbFWHM(i) = init_params{2}(i,3); ubFWHM(i) = init_params{3}(i,3); + MR(i) = init_params{1}(i,4); lbMR(i) = init_params{2}(i,4); ubMR(i) = init_params{3}(i,4); + ASY(i) = init_params{1}(i,5); lbASY(i) = init_params{2}(i,5); ubASY(i) = init_params{3}(i,5); + LSX(i) = init_params{1}(i,6); lbLSX(i) = init_params{2}(i,6); ubLSX(i) = init_params{3}(i,6); + LSY(i) = init_params{1}(i,7); lbLSY(i) = init_params{2}(i,7); ubLSY(i) = init_params{3}(i,7); + LSW(i) = init_params{1}(i,8); lbLSW(i) = init_params{2}(i,8); ubLSW(i) = init_params{3}(i,8); +end + +%% - 2 - Extracting all background subtraction data and information +% -- Extracting the background +[X, D, B] = PESBackground(xdat, ydat,... + bgrnd_type, init_bgrnd{1}(1), init_bgrnd{1}(2), init_bgrnd{1}(3), init_bgrnd{1}(4), init_bgrnd{1}(5), init_bgrnd{1}(6)); + +%% - 3 - Extracting all model data and information +% -- Initialising the vectors to contain XPS data +DB = D - B; % Data after being background subtracted +M = zeros(size(X)); % XPS model data +% -- Filing through all curve components and extracting them seperately +cYY = []; +for i = 1:ncurves + cYY(:,i) = PESCurve(X, curve_type, XLOC(i), YINT(i), FWHM(i), MR(i), LSX(i), LSY(i), LSW(i), ASY(i)); + M = M + cYY(:,i); +end + +%% - 4 - Determination of the residuals and chi-squared +R = D - (M + B); % Residuals +CHISQ = sum(R.^2 ./ abs(M)); % Chi-squared + +%% - 5.1 - Plotting the initial model figure +% - Finding the optimal y-limits +minY = min([min(cYY(:)), min(M(:)), min(D(:)), min(B(:)), min(DB(:))]); +maxY = 1.25*max([max(cYY(:)), max(M(:)), max(D(:)), max(B(:)), max(DB(:))]); +ylims = [minY, maxY]; +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'Curve Fit 1D - Initial Model'); +fig.Position(3) = 2.5*pp.fig5x4(1); +fig.Position(4) = 1.0*pp.fig5x4(2); +% -- Plotting the raw data and background +subplot(121); hold on; +h = patch(... + [init_bgrnd{1}(1), init_bgrnd{1}(1), init_bgrnd{1}(2), init_bgrnd{1}(2), init_bgrnd{1}(1)],... + [-1, 1, 1, -1, -1].*1e4, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', [0 0 0]); +h.Annotation.LegendInformation.IconDisplayStyle = 'off'; +plot(xdat, ydat, 'b-', 'linewidth', 0.5*pp.lwidth); +plot(X, D, 'b-', 'linewidth', pp.llwidth); +plot(X, B, 'r-', 'linewidth', pp.llwidth); +plot(X, DB, 'k-', 'linewidth', pp.llwidth); +gca_props(); grid on; +xlabel('$$ \bf X $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); +axis([min(xdat(:)), max(xdat(:)), ylims]); +legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); +title("Background Subtraction", 'interpreter', 'none', 'fontsize', 9); +% -- Plotting the best fit curve components and the initial model +subplot(4,2,[2,4,6]); hold on; +% -- Plotting all of the curve components +for i = 1:ncurves + area(X, cYY(:,i), 'FaceColor', pp.col.fit{i}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); + plot(X, cYY(:,i), 'k-', 'linewidth', 0.25); +end +% -- Plotting the curve component energy locations +for i = 1:ncurves + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + line([init_params{1}(i,1), init_params{1}(i,1)], [0, max(cYY(:,i))],... + 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '-'); +end +% -- Plotting the experimental and fit spectra +plot(X, DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(X, M, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Y$$', 'Interpreter', 'latex'); +axis([min(X(:)), max(X(:)), ylims]); +title("Initial Model", 'interpreter', 'none', 'fontsize', 9); +% -- Plotting the uncertainties to allow for easier optimisation +for i = 1:ncurves + % --- Plotting the primary peak uncertainties + lbBE = init_params{2}(i,1); ubBE = init_params{3}(i,1); + lbINT = init_params{2}(i,2); ubINT = init_params{3}(i,2); + x_vals = [lbBE, lbBE, ubBE, ubBE, lbBE]; + y_vals = [lbINT, ubINT, ubINT, lbINT, lbINT]; + patch(x_vals, y_vals, pp.col.fit{i}, 'FaceAlpha', 0.65, 'EdgeAlpha', 0); + % --- Adding text to identify each peak index + text(max(x_vals), max(y_vals), string(i), 'interpreter', 'latex', 'fontsize', 14, 'color', 'k'); + % --- Plotting the spin-orbit split (SOS) peak uncertainties + x_vals = XLOC(i) + [lbLSX, lbLSX, ubLSX, ubLSX, lbLSX]; + y_vals = [lbINT*lbLSY, ubINT*ubLSY, ubINT*ubLSY, lbINT*lbLSY, lbINT*lbLSY]; + patch(x_vals, y_vals, pp.col.fit{i}, 'FaceAlpha', 0.65, 'EdgeAlpha', 0); +end + +% -- Plotting the residuals of the model +subplot(4,2,8); hold on; +bar(X, R, 'facecolor', [0 0 0]); +gca_props(); grid on; +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_crop1D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_crop1D.m new file mode 100644 index 0000000..bf57d36 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_crop1D.m @@ -0,0 +1,45 @@ +function [xdat_crop, ydat_crop] = data_crop1D(xdat, ydat, xdat_lims, plot_result) +% [xdat_crop, ydat_crop] = data_crop1D(xdat, ydat, xdat_lims, plot_result) +% This function crops 1D data along the x-axis (domain) and y-axis +% (range). The user defines the limits along the x-axis. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - xdat: [nX×1] array of the x-axis +% - ydat: [nY×1] array of the y-axis +% - xdat_lims: [1×2] row vector of x-axis limits +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - xdat_crop: [mX×1] array of the cropped x-axis +% - ydat_crop: [mY×1] array of the cropped y-axis + +%% Default parameters +if nargin < 3; xdat_lims=[min(xdat(:)), max(xdat(:))]; end +if nargin < 4; plot_result=0; end +if isempty(xdat_lims); xdat_lims=[min(xdat(:)), max(xdat(:))]; end +if isempty(plot_result); plot_result=0; end +% - Sorting the cropping limits in ascending order +xdat_lims = sort(xdat_lims); +%% 1 - Cropping the data +% - x-axis indices +[~, xIndxL] = min(abs(xdat(:) - xdat_lims(1))); +[~, xIndxU] = min(abs(xdat(:) - xdat_lims(2))); +x_indx = [xIndxL xIndxU]; +% - cropping x-axis +xdat_crop = xdat(x_indx(1):x_indx(2)); +ydat_crop = ydat(x_indx(1):x_indx(2)); +%% -- For Debugging +if plot_result == 1 + figure(); hold on; + plot(xdat, ydat, 'k:', 'linewidth', 1); + plot(xdat_crop, ydat_crop, 'k-', 'linewidth', 2); + line([1 1].*xdat_lims(1), [min(ydat(:)), max(ydat(:))], 'Color', [0 0 1], 'LineWidth', 1.5, 'Linestyle', '-'); + line([1 1].*xdat_lims(2), [min(ydat(:)), max(ydat(:))], 'Color', [0 0 1], 'LineWidth', 1.5, 'Linestyle', '-'); + gca_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end +end diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_crop2D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_crop2D.m new file mode 100644 index 0000000..f301a6c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_crop2D.m @@ -0,0 +1,88 @@ +function [xdat_crop, ydat_crop, ddat_crop] = data_crop2D(xdat, ydat, ddat, xdat_lims, ydat_lims, plot_result) +% [xdat_crop, ydat_crop, ddat_crop] = data_crop2D(xdat, ydat, ddat, xdat_lims, ydat_lims, plot_result) +% This function crops 2D data along the x- and y-axis. The user can +% define the limits along the x- and y-axis to be cropped. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - xdat: [1×nX] or [nY×nX] array of the x-axis data +% - ydat: [nY×1] or [nY×nX] array of the y-axis data +% - ddat: [nY×nX] array of the intensity data +% - xdat_lims: [1×2] row vector of x-axis limits +% - ydat_lims: [1×2] row vector of y-axis limits +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - xdat_crop: [mY×mX] array of the cropped x-axis +% - ydat_crop: [mY×mX] array of the cropped y-axis +% - ddat_crop: [mY×mX] array of the cropped intensity data + +%% Default parameters +if nargin < 4; xdat_lims=[min(xdat(:)), max(xdat(:))]; ydat_lims=[min(ydat(:)), max(ydat(:))]; end +if nargin < 5; ydat_lims=[min(ydat(:)), max(ydat(:))]; end +if nargin < 6; plot_result=0; end +if isempty(xdat_lims); xdat_lims=[min(xdat(:)), max(xdat(:))]; end +if isempty(ydat_lims); ydat_lims=[min(ydat(:)), max(ydat(:))]; end +if isempty(plot_result); plot_result=0; end +% - Sorting the cropping limits in ascending order +xdat_lims = sort(xdat_lims); +ydat_lims = sort(ydat_lims); +% - Initialising variables +xdat_crop = []; +ydat_crop = []; +ddat_crop = []; +%% 1 - Cropping the data +% - x-axis indices +if ~isempty(xdat) + [~, xIndxL] = min(abs(xdat(1,:) - xdat_lims(1))); + [~, xIndxU] = min(abs(xdat(1,:) - xdat_lims(2))); + x_indx = [xIndxL xIndxU]; +end +% - y-axis indices +if ~isempty(ydat) + [~, yIndxL] = min(abs(ydat(:,1) - ydat_lims(1))); + [~, yIndxU] = min(abs(ydat(:,1) - ydat_lims(2))); + y_indx = [yIndxL yIndxU]; +end +% - cropping x-axis +if ~isempty(xdat) + if size(xdat, 1) > 1 && isempty(ydat); xdat_crop = xdat(:, x_indx(1):x_indx(2)); + elseif size(xdat, 1) > 1; xdat_crop = xdat(y_indx(1):y_indx(2), x_indx(1):x_indx(2)); + else; xdat_crop = xdat(1,x_indx(1):x_indx(2)); + end +end +% - cropping y-axis +if ~isempty(ydat) + if size(ydat, 2) > 1 && isempty(xdat); ydat_crop = ydat(y_indx(1):y_indx(2), :); + elseif size(ydat, 2) > 1; ydat_crop = ydat(y_indx(1):y_indx(2), x_indx(1):x_indx(2)); + else; ydat_crop = ydat(y_indx(1):y_indx(2),1); + end +end +% - cropping the data +if isempty(ydat); ddat_crop = ddat(:,x_indx(1):x_indx(2)); +elseif isempty(xdat); ddat_crop = ddat(y_indx(1):y_indx(2),:); +else; ddat_crop = ddat(y_indx(1):y_indx(2), x_indx(1):x_indx(2)); +end +%% -- For Debugging +if plot_result == 1 + fig = figure(); + fig.Position(3) = 400*2; + fig.Position(4) = 400*0.9; + subplot(121); hold on; + h1 = pcolor(xdat, ydat, ddat); set(h1,'EdgeColor','None','FaceColor','Flat'); + xpts = [xdat_lims(1), xdat_lims(2), xdat_lims(2), xdat_lims(1), xdat_lims(1)]; + ypts = [ydat_lims(2), ydat_lims(2), ydat_lims(1), ydat_lims(1), ydat_lims(2)]; + plot(xpts, ypts, 'Color', 'c', 'LineWidth', 1.5, 'Linestyle', '-'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); + subplot(122); hold on; + h2 = pcolor(xdat_crop, ydat_crop, ddat_crop); set(h2,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat_crop(:)), max(xdat_crop(:)), min(ydat_crop(:)), max(ydat_crop(:))]); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_filter1D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_filter1D.m new file mode 100644 index 0000000..d59e392 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_filter1D.m @@ -0,0 +1,52 @@ +function ydat_fil = data_filter1D(ydat, filType, filVal, plot_result) +% ydat_fil = data_filter1D(ydat, filType, filVal, plot_result) +% This function applies a filtering / smoothing operation on 1D data. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - ydat: [nY×1] column vector of the output range. +% - filType: string of the type of filtering to use. Default: "spline" ("none","gaco1","binomial","savitzky-golay"). +% - filVal: scalar value of the filtering / smoothing strength. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - ydat_fil: [nY×1] column vector of the filtered data. + +%% Default parameters +if nargin < 2; filType = "savitzky-golay"; end +if nargin < 3; filVal = 5; end +if nargin < 4; plot_result=0; end +if isempty(filType); filType = "savitzky-golay"; end +if isempty(filVal); filVal = 5; end +if isempty(plot_result); plot_result=0; end +%% Validity checks on the input parameters +filType = string(filType); +if filVal < 0; filVal = 0; end + +%% 1 - Filtering the data +if strcmpi(filType,"none") + ydat_fil = ydat; +elseif strcmpi(filType,"gaco1") || strcmpi(filType,"g1") + ydat_fil = Gaco1(ydat, filVal); +elseif strcmpi(filType,"binomial") || strcmpi(filType,"bino") || strcmpi(filType,"b") + coeff = ones(1, 24); + ydat_fil = filter(coeff, filVal, ydat); +elseif strcmpi(filType,"savitzky-golay") || strcmpi(filType,"sav-gol") || strcmpi(filType,"sg") + ydat_fil = sgolayfilt(ydat, filVal, 11); +end +%% 2 - Setting NaN values to zero +ydat_fil(isnan(ydat_fil)) = 0; + +%% -- For Debugging +if plot_result == 1 + xdat = 1:length(ydat); + figure(); hold on; + plot(xdat, ydat, 'k:', 'linewidth', 1); + plot(xdat, ydat_fil, 'k-', 'linewidth', 2); + gca_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_filter2D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_filter2D.m new file mode 100644 index 0000000..a26fe02 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/data_filter2D.m @@ -0,0 +1,76 @@ +function zdat_fil = data_filter2D(zdat, filType, filXVal, filYVal, plot_result) +% zdat_fil = data_filter2D(zdat, filType, filXVal, filYVal, plot_result) +% This function applies a filtering / smoothing operation on 2D data. +% +% REQ. FUNCTIONS: +% - AA = Gaco2(A,hwX,hwY [,hsX] [,hsY]) +% - AA = GaussFlt2(Img,hwX,hwY,hsX,hsY) +% - AA = CurvatureFlt2(Img [,order] [,CX] [,CY]) +% - AA = LaplaceFlt2(Img [,y2xRatio] [,order]) +% +% IN: +% - zdat: [nX×nY] array of the intensity data. Smoothes along the [N×M] axis. +% - filType: string of the type of filtering to use. Default: "spline" ("none","Gaco2","GaussFlt2","LaplaceFlt2","CurvatureFlt2"). +% - filVal: scalar value of the x filtering / smoothing strength. +% - filVal: scalar value of the y filtering / smoothing strength. +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - zdat_fil: [nX×nY] array of the filtered intensity data. + +%% Default parameters +if nargin < 3; filType = "Gaco2"; end +if nargin < 4; filXVal = 1; end +if nargin < 5; filYVal = 1; end +if isempty(filType); filType = "Gaco2"; end +if isempty(filXVal); filXVal = 1; end +if isempty(filYVal); filYVal = 1; end +%% Validity checks on the input parameters +if filXVal < 0; filXVal = 0; end +if filYVal < 0; filYVal = 0; end + +%% 1 - Performing the filtering operation over all scans +zdat_fil = []; +for i = 1:size(zdat, 3) + if strcmpi(filType,"gaco2") + zdat_fil_01 = Gaco2(zdat(:,:,i), filXVal, filYVal); + elseif strcmpi(filType,"gaussflt2") || strcmpi(filType,"gauss2") + zdat_fil_01 = GaussFlt2(zdat(:,:,i), filXVal, filYVal, 40, 40); + elseif strcmpi(filType,"laplaceflt2") || strcmpi(filType,"laplace2") || strcmpi(filType,"l2") + zdat_fil_01 = GaussFlt2(zdat(:,:,i), 5, 5, 40, 40); + zdat_fil_01 = SetContrast(zdat_fil_01, 0.4, 0.999, 1.5); + zdat_fil_01 = LaplaceFlt2(zdat_fil_01, (filYVal./filXVal)); + elseif strcmpi(filType,"curvatureflt2") || strcmpi(filType,"curvature2") || strcmpi(filType,"c2") + zdat_fil_01 = GaussFlt2(zdat(:,:,i), 100, 100, 500, 500); + zdat_fil_01 = SetContrast(zdat_fil_01, 0.4, 0.999, 1.5); + zdat_fil_01 = CurvatureFlt2(zdat_fil_01, '2D', filXVal, filYVal); + zdat_fil_01 = GaussFlt2(zdat_fil_01, 1, 1, 10, 10); + zdat_fil_01 = SetContrast(zdat_fil_01, 0.2, 0.999); + elseif strcmpi(filType,"none") + zdat_fil_01 = zdat(:,:,i); + end + zdat_fil(:,:,i) = zdat_fil_01; +end +%% 2 - Setting NaN values to zero +zdat_fil(isnan(zdat_fil)) = 0; + +%% -- For Debugging +if plot_result == 1 + [xdat,ydat] = meshgrid(1:size(zdat,2), 1:size(zdat,1)); + fig = figure(); + fig.Position(3) = 400*2; + fig.Position(4) = 400*0.9; + subplot(121); hold on; + h1 = pcolor(xdat, ydat, zdat); set(h1,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); + subplot(122); hold on; + h2 = pcolor(xdat, ydat, zdat_fil); set(h2,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/find_peak_fwhm.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/find_peak_fwhm.m new file mode 100644 index 0000000..db3d88e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/find_peak_fwhm.m @@ -0,0 +1,207 @@ +function [fwhm, fwhmLocs] = find_peak_fwhm(xdat, ydat, xWin, type, plot_result) +% [fwhm, fwhmLocs] = find_peak_fwhm(xdat, ydat, xWin, type, plot_result) +% This function is used to determine both the fwhm of a data set using +% a range of different methods; spline interpolation or curve fitting a +% gaussian / voigt function. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - xdat: [N×1] column vector of the input domain. +% - ydat: [N×1] column vector of the output range. +% - xWin: [N×2] array that contains the x-windows where N peaks are expected to be found. +% - type: string of the type of method to use. Default: "spline" ("none","spline","gaco1","G","L","sGL","pGL","sGLA","pGLA"). +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - fwhm: scalar or [N×1] column vector of the fwhm of each peak defined. +% - fwhmLocs: [2N×2] column vector of the fwhm positions. + +%% Default parameters +if nargin < 3; xWin = []; end +if nargin < 4; type = "spline"; end +if nargin < 5; plot_result = 0; end +if isempty(xWin); xWin = []; end +if isempty(type); type = "spline"; end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +pp = plot_props(); +type = string(type); +% -- Making the default window-size if it is undefined +if isempty(xWin) + minWin = mean(xdat(:)) - abs(0.25*range(xdat(:))); + maxWin = mean(xdat(:)) + abs(0.25*range(xdat(:))); + xWin = [minWin, maxWin]; +end +% -- Making sure the window-size is an N×2 array +if size(xWin, 2) ~= 2; xWin = xWin'; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% 1 - Extracting the peak position and values +xVal = []; yVal = []; +fwhm = []; fwhmLocs = {}; +xdat_roi = {}; ydat_roi = {}; +xx = {}; yy = {}; +if length(xdat(:)) < 5e4; Nx = 5e4; else; Nx = length(xdat(:));end +for i = 1:size(xWin, 1) + % -- Finding the indices and ROI + [~, lbIndx] = min(abs(xdat - xWin(i,1))); + [~, ubIndx] = min(abs(xdat - xWin(i,2))); + Indx = [lbIndx, ubIndx]; + xdat_roi{i} = xdat(Indx(1):Indx(2)); + ydat_roi{i} = ydat(Indx(1):Indx(2)); + % -- Finding the maximum from the raw data + if strcmpi(type,"none") + xx{i} = xdat_roi{i}; + yy{i} = ydat_roi{i}; + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value from the gaussian smoothed data + elseif strcmpi(type,"gaco1") + xx{i} = linspace(min(xdat_roi{i}(:)), max(xdat_roi{i}(:)), Nx); + yy{i} = Gaco1(ydat_roi{i}, 2); + yy{i} = interp1(xdat_roi{i}, yy{i}, xx{i}); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a spline + elseif strcmpi(type,"spline") + xx{i} = linspace(min(xdat_roi{i}(:)), max(xdat_roi{i}(:)), Nx); + yy{i} = spline(xdat_roi{i}, ydat_roi{i}, xx{i}); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a gaussian + elseif strcmpi(type,"G") || strcmpi(type,"gauss") || strcmpi(type,"gaussian") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, x) Gauss(x, x0, peak, fwhm)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start]); + params = coeffvalues(fit1); + xx{i} = linspace(min(xdat_roi{i}(:)), max(xdat_roi{i}(:)), 1e3); + yy{i} = Gauss(xx{i}, params(1), params(2), params(3)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a lorentzian + elseif strcmpi(type,"L") || strcmpi(type,"lorz") || strcmpi(type,"lorentzian") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, x) Lorentzian(x, x0, peak, fwhm)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start]); + params = coeffvalues(fit1); + xx{i} = linspace(min(xdat_roi{i}(:)), max(xdat_roi{i}(:)), Nx); + yy{i} = Lorentzian(xx{i}, params(1), params(2), params(3)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a summed voigt + elseif strcmpi(type,"sGL") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, mr, x) sGL(x, x0, peak, fwhm, mr)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + mr_start = 0.5; + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start, mr_start]); + params = coeffvalues(fit1); + xx{i} = linspace(min(xdat_roi{i}(:)), max(xdat_roi{i}(:)), Nx); + yy{i} = sGL(xx{i}, params(1), params(2), params(3), params(4)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a multiplied voigt + elseif strcmpi(type,"pGL") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, mr, x) pGL(x, x0, peak, fwhm, mr)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + mr_start = 0.5; + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start, mr_start]); + params = coeffvalues(fit1); + xx{i} = linspace(min(xdat_roi{i}(:)), max(xdat_roi{i}(:)), Nx); + yy{i} = pGL(xx{i}, params(1), params(2), params(3), params(4)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a summed, asymmetric voigt + elseif strcmpi(type,"sGLA") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, mr, asym, x) sGLA(x, x0, peak, fwhm, mr, asym)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + mr_start = 0.5; + asym_start = 0.2; + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start, mr_start, asym_start]); + params = coeffvalues(fit1); + xx{i} = linspace(min(xdat_roi{i}(:)), max(xdat_roi{i}(:)), Nx); + yy{i} = sGLA(xx{i}, params(1), params(2), params(3), params(4), params(5)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a multiplied, asymmetric voigt + elseif strcmpi(type,"pGLA") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, mr, asym, x) pGLA(x, x0, peak, fwhm, mr, asym)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + mr_start = 0.5; + asym_start = 0.2; + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start, mr_start, asym_start]); + params = coeffvalues(fit1); + xx{i} = linspace(min(xdat_roi{i}(:)), max(xdat_roi{i}(:)), Nx); + yy{i} = pGLA(xx{i}, params(1), params(2), params(3), params(4), params(5)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + end + % -- Extracting the FWHM of the data + yHalf(i) = 0.5*yVal(i); % Find the half max value + index1 = find(yy{i}(:) >= yHalf(i), 1, 'first'); % Find where the data first drops below half the max + index2 = find(yy{i}(:) >= yHalf(i), 1, 'last'); % Find where the data last rises above half the max + fwhm(i) = abs(xx{i}(index2) - xx{i}(index1)); % Extracting FWHM + fwhmLocs{i,1} = [xx{i}(index1), yy{i}(index1); xx{i}(index2), yy{i}(index2)]; +end +fwhmLocs = cell2mat(fwhmLocs); +%% 2 - Ensuring the peak positions and location are column vectors +if size(fwhm, 2) > 1; fwhm = fwhm'; end + +%% -- For Debugging +if plot_result == 1 + fig = figure(); + fig.Position(3) = pp.fig4x4(1); + fig.Position(4) = pp.fig4x4(2); + hold on; + % Plotting the data + plot(xdat, ydat, 'b.-', 'linewidth', 0.5); + % Plotting the outcome of the peak finder + for i = 1:size(xWin, 1) + plot(xdat_roi{i}, ydat_roi{i}, 'r-','linewidth', 2.0); + plot(xx{i}, yy{i}, 'k-', 'linewidth', 2.5, 'Color', pp.col.fit{i}); + % -- Plotting peak position + plot(xVal(i), yVal(i), '.', 'markersize', 20, 'color', pp.col.fit{i}, 'linewidth', 2.5); + line([1 1].*xVal(i), [0, yVal(i)], 'Color', pp.col.fit{i}, 'LineWidth', 2.5, 'Linestyle', '-'); + % -- Plotting LHS point + plot(fwhmLocs(2*i-1,1), fwhmLocs(2*i-1,2), '.', 'markersize', 20, 'color', pp.col.fit{i}, 'linewidth', 2.5); + line([1 1].*fwhmLocs(2*i-1,1), [0, yVal(i)], 'Color', pp.col.fit{i}, 'LineWidth', 1.0, 'Linestyle', '--'); + % -- Plotting RHS point + plot(fwhmLocs(2*i,1), fwhmLocs(2*i,2), '.', 'markersize', 20, 'color', pp.col.fit{i}, 'linewidth', 2.5); + line([1 1].*fwhmLocs(2*i,1), [0, yVal(i)], 'Color', pp.col.fit{i}, 'LineWidth', 1.0, 'Linestyle', '--'); + % -- Printing useful information + fprintf(("%i) x = %.2f eV, y = %.2f, fwhm = %.2f \n"), i, xVal(i), yVal(i), fwhm(i)); + end + % - Formatting the figure + gca_props(0); grid on; title('find_peak_fwhm()', 'interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([mean(xWin(:))-0.75*range(xWin(:)), mean(xWin(:))+0.75*range(xWin(:)), min(ydat(:)), 1.10.*max(yVal(:))]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/find_peak_loc.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/find_peak_loc.m new file mode 100644 index 0000000..1ce8051 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/find_peak_loc.m @@ -0,0 +1,190 @@ +function [xVal, yVal] = find_peak_loc(xdat, ydat, xWin, type, plot_result) +% [xVal, yVal] = find_peak_loc(xdat, ydat, xWin, type, plot_results) +% This function is used to determine both the maximum value and position of +% a data set using a range of different methods; spline interpolation or +% curve fitting a gaussian / voigt function. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - xdat: [N×1] column vector of the input domain. +% - ydat: [N×1] column vector of the output range. +% - xWin: [N×2] array that contains the x-windows where N peaks are expected to be found. +% - type: string of the type of method to use. Default: "spline" ("none","spline","gaco1","G","L","sGL","pGL","sGLA","pGLA"). +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - xVal: scalar or [N×1] column vector of the maxima x-values. +% - yVal: scalar or [N×1] column vector of the maxima y-values. + +%% Default parameters +if nargin < 3; xWin = []; end +if nargin < 4; type = "spline"; end +if nargin < 5; plot_result = 0; end +if isempty(xWin); xWin = []; end +if isempty(type); type = "spline"; end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +pp = plot_props(); +type = string(type); +% -- Making the default window-size if it is undefined +if isempty(xWin) + minWin = mean(xdat(:)) - abs(0.475*range(xdat(:))); + maxWin = mean(xdat(:)) + abs(0.475*range(xdat(:))); + xWin = [minWin, maxWin]; +end +% -- Making sure the window-size is an N×2 array +if size(xWin, 2) ~= 2; xWin = xWin'; end +%% Ensuring the data is in the form of 1D column vectors +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end + +%% 1 - Extracting the peak position and values +Npoints = 5e3; +xVal = []; yVal = []; +xdat_roi = {}; ydat_roi = {}; +xx = {}; yy = {}; +for i = 1:size(xWin, 1) + % -- Finding the indices and ROI + [~, lbIndx] = min(abs(xdat - xWin(i,1))); + [~, ubIndx] = min(abs(xdat - xWin(i,2))); + Indx = [lbIndx, ubIndx]; + xdat_roi{i} = xdat(Indx(1):Indx(2)); + ydat_roi{i} = ydat(Indx(1):Indx(2)); + if length(xdat_roi{i}(:)) < Npoints; xx{i} = linspace(min(xdat_roi{i}(:)), max(xdat_roi{i}(:)), Npoints); + else; xx{i} = linspace(min(xdat_roi{i}(:)), max(xdat_roi{i}(:)), length(xdat_roi{i}(:))); + end + % -- Finding the maximum peak value from the raw data + if strcmpi(type,"none") + xx{i} = xdat_roi{i}; + yy{i} = ydat_roi{i}; + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value from the gaussian smoothed data + elseif strcmpi(type,"gaco1") + yy{i} = Gaco1(ydat_roi{i}, 2); + yy{i} = interp1(xdat_roi{i}, yy{i}, xx{i}); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a spline + elseif strcmpi(type,"spline") + yy{i} = spline(xdat_roi{i}, ydat_roi{i}, xx{i}); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a gaussian + elseif strcmpi(type,"G") || strcmpi(type,"gauss") || strcmpi(type,"gaussian") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, x) Gauss(x, x0, peak, fwhm)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start]); + params = coeffvalues(fit1); + yy{i} = Gauss(xx{i}, params(1), params(2), params(3)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a lorentzian + elseif strcmpi(type,"L") || strcmpi(type,"lorz") || strcmpi(type,"lorentzian") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, x) Lorentzian(x, x0, peak, fwhm)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start]); + params = coeffvalues(fit1); + yy{i} = Lorentzian(xx{i}, params(1), params(2), params(3)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a summed voigt + elseif strcmpi(type,"sGL") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, mr, x) sGL(x, x0, peak, fwhm, mr)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + mr_start = 0.5; + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start, mr_start]); + params = coeffvalues(fit1); + yy{i} = sGL(xx{i}, params(1), params(2), params(3), params(4)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a multiplied voigt + elseif strcmpi(type,"pGL") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, mr, x) pGL(x, x0, peak, fwhm, mr)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + mr_start = 0.5; + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start, mr_start]); + params = coeffvalues(fit1); + yy{i} = pGL(xx{i}, params(1), params(2), params(3), params(4)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a summed, asymmetric voigt + elseif strcmpi(type,"sGLA") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, mr, asym, x) sGLA(x, x0, peak, fwhm, mr, asym)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + mr_start = 0.5; + asym_start = 0.2; + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start, mr_start, asym_start]); + params = coeffvalues(fit1); + yy{i} = sGLA(xx{i}, params(1), params(2), params(3), params(4), params(5)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + % -- Finding the maximum peak value by fitting a multiplied, asymmetric voigt + elseif strcmpi(type,"pGLA") + % --- Defining the fit function + fit_func = fittype(@(x0, peak, fwhm, mr, asym, x) pGLA(x, x0, peak, fwhm, mr, asym)); + x0_start = mean(xdat_roi{i}(:)); + peak_start = max(ydat_roi{i}(:)); + fwhm_start = 0.5*range(xdat_roi{i}(:)); + mr_start = 0.5; + asym_start = 0.2; + % --- Executing the fitting operation + [fit1,~,~] = fit(xdat_roi{i},ydat_roi{i},fit_func,'start',[x0_start, peak_start, fwhm_start, mr_start, asym_start]); + params = coeffvalues(fit1); + yy{i} = pGLA(xx{i}, params(1), params(2), params(3), params(4), params(5)); + [yVal(i), maxInd] = max(yy{i}(:)); + xVal(i) = xx{i}(maxInd); + end +end +%% 2 - Ensuring the peak positions and location are column vectors +if size(xVal, 2) > 1; xVal = xVal'; end +if size(yVal, 2) > 1; yVal = yVal'; end + +%% -- For Debugging +if plot_result == 1 + fig = figure(); + fig.Position(3) = pp.fig4x4(1); + fig.Position(4) = pp.fig4x4(2); + hold on; + % Plotting the data + plot(xdat, ydat, 'b.-', 'linewidth', 0.5); + % Plotting the outcome of the peak finder + for i = 1:size(xWin, 1) + plot(xdat_roi{i}, ydat_roi{i}, 'r-','linewidth', 2.0); + plot(xx{i}, yy{i}, 'k-', 'linewidth', 2.5, 'Color', pp.col.fit{i}); + plot(xVal(i), yVal(i), '.', 'markersize', 20, 'color', pp.col.fit{i}, 'linewidth', 2.5); + line([1 1].*xVal(i), [0, yVal(i)], 'Color', pp.col.fit{i}, 'LineWidth', 2.5, 'Linestyle', '-'); + fprintf(("%i) x = %.2f eV, y = %.2f \n"), i, xVal(i), yVal(i)); + end + % - Formatting the figure + gca_props(0); grid on; title('find_peak_loc()', 'interpreter', 'none'); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + if min(ydat(:)) ~= max(yVal(:)) + axis([mean(xWin(:))-0.75*(range(xWin(:))), mean(xWin(:))+0.75*(range(xWin(:))),... + min(cell2mat(ydat_roi(:))), 1.10.*max(yVal(:))]); + end +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_rotate.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_rotate.m new file mode 100644 index 0000000..b07899f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_rotate.m @@ -0,0 +1,61 @@ +function [xdat_lt, ydat_lt] = lt_rotate(xdat, ydat, rot_args, plot_result) +% [xdat_lt, ydat_lt] = lt_rotate(xdat, ydat, rot_args, plot_result) +% Function to perform a Rotate transformation on 2D data. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [nX×nY] array of the x-axis (theta/kx) +% - ydat: [nX×nY] array of the y-axis (eb) +% - rot_args: {1×1} cell of {Rtheta} +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - xdat_lt: [nX×nY] array of the x-axis (theta/kx) after rotation +% - ydat_lt: [nX×nY] array of the y-axis (eb) after rotation + +%% Default parameters +if nargin < 3; rot_args = {0}; end +if isempty(rot_args); rot_args = {0}; end +%% Validity checks on the input parameters +if length(rot_args) ~= 1; rot_args = {0}; end + +%% - 1 - Initialising the transformation parameters +% - Extracting the transformation values +Rtheta = rot_args{1}; +% - Defining the 2D rotation matrix +R3Dmatrix = [... + cos(deg2rad(Rtheta)), sin(deg2rad(Rtheta));... + -sin(deg2rad(Rtheta)), cos(deg2rad(Rtheta))]; +%% 2 - Performing transformation operation +if length(xdat(:)) == length(ydat(:)) + XY = [xdat(:) ydat(:)]; % Create Matrix Of Vectors + rotXY = XY*R3Dmatrix'; % Multiply the vectors by the rotation matrix + xdat_lt = reshape(rotXY(:,1), size(xdat,1), []); + ydat_lt = reshape(rotXY(:,2), size(ydat,1), []); +else + xdat = repmat(xdat, [length(ydat), 1]); + ydat = repmat(ydat, [1, length(xdat)]); + xdat_lt = xdat*R3Dmatrix; + ydat_lt = ydat*R3Dmatrix; +end + +%% -- For Debugging +if plot_result == 1 + fig = figure(); + fig.Position(3) = 400*2; + fig.Position(4) = 400*0.9; + subplot(121); hold on; + h1 = pcolor(xdat, ydat, ydat.*0); set(h1,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); + subplot(122); hold on; + h2 = pcolor(xdat_lt, ydat_lt, ydat_lt.*0); set(h2,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat_lt(:)), max(xdat_lt(:)), min(ydat_lt(:)), max(ydat_lt(:))]); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_scale.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_scale.m new file mode 100644 index 0000000..431a458 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_scale.m @@ -0,0 +1,56 @@ +function [xdat_lt, ydat_lt] = lt_scale(xdat, ydat, scale_args, plot_result) +% [xdat_lt, ydat_lt] = lt_scale(xdat, ydat, scale_args, plot_result) +% Function to perform a Scaling transformation on 2D data. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [nX×nY] array of the x-axis (theta/kx) +% - ydat: [nX×nY] array of the y-axis (eb) +% - scale_args: {1×2} cell of {Sx, Sy} +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - xdat_lt: [nX×nY] array of the x-axis (theta/kx) after scaling +% - ydat_lt: [nX×nY] array of the y-axis (eb) after scaling + +%% Default parameters +if nargin < 3; scale_args = {1, 1}; end +if isempty(scale_args); scale_args = {1, 1}; end +%% Validity checks on the input parameters +if length(scale_args) ~= 2; scale_args = {0, 0}; end + +%% - 1 - Initialising the transformation parameters +% - Extracting the transformation values +Sx = scale_args{1}; +Sy = scale_args{2}; +% - Defining the transformation matrix +Smatrix = [... + Sx, 0, 0;... + 0, Sy, 0;... + 0, 0, 1]; +Stform = affine2d(Smatrix); + +%% 2 - Performing transformation operation +xdat_lt = Sx .* (xdat - mean(xdat(:))) + mean(xdat(:)); +ydat_lt = Sy .* (ydat - mean(ydat(:))) + mean(ydat(:)); + +%% -- For Debugging +if plot_result == 1 + fig = figure(); + fig.Position(3) = 400*2; + fig.Position(4) = 400*0.9; + subplot(121); hold on; + h1 = pcolor(xdat, ydat, ydat.*0); set(h1,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); + subplot(122); hold on; + h2 = pcolor(xdat_lt, ydat_lt, ydat_lt.*0); set(h2,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat_lt(:)), max(xdat_lt(:)), min(ydat_lt(:)), max(ydat_lt(:))]); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_shear.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_shear.m new file mode 100644 index 0000000..f9e988f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_shear.m @@ -0,0 +1,72 @@ +function [xdat_lt, ydat_lt] = lt_shear(xdat, ydat, shear_args, plot_result) +% [xdat_lt, ydat_lt] = lt_shear(xdat, ydat, shear_args, plot_result) +% Function to perform a Shear transformation on 2D data. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [nX×nY] array of the x-axis (theta/kx) +% - ydat: [nX×nY] array of the y-axis (eb) +% - shear_args: {1×2} cell of {Shx, Shy} +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - xdat_lt: [nX×nY] array of the x-axis (theta/kx) after shearing +% - ydat_lt: [nX×nY] array of the y-axis (eb) after shearing + +%% Default parameters +if nargin < 3; shear_args = {0, 0}; end +if isempty(shear_args); shear_args = {0, 0}; end +%% Validity checks on the input parameters +if length(shear_args) ~= 2; shear_args = {0, 0}; end + +%% - 1 - Initialising the transformation parameters +% - Extracting the transformation values +Shx = shear_args{1}; +Shy = shear_args{2}; +% - Defining the transformation matrix +Smatrix = [... + 1, Shy, 0;... + Shx, 1, 0;... + 0, 0, 1]; +Stform = affine2d(Smatrix); + +%% 2 - Performing transformation operation +shear_fnc = @ (slope, intercept, y) (y - intercept) ./ slope; +% - Applying x-shear corrections +if Shx == 0; x_shifts = zeros(size(ydat)); +else; x_shifts = shear_fnc(Shx, 0, ydat); +end +% - Applying y-shear corrections +if Shy == 0; y_shifts = zeros(size(xdat)); +else; y_shifts = shear_fnc(Shy, 0, xdat); +end +% - Extracting the initial mid-point of the data +Ox = mean(xdat(:)); +Oy = mean(ydat(:)); +% - Execute shear transformation +xdat_lt = (xdat + x_shifts); +ydat_lt = (ydat + y_shifts); +% - Recentering the data after shearing +xdat_lt = xdat_lt + (Ox - mean(xdat_lt(:))); +ydat_lt = ydat_lt + (Oy - mean(ydat_lt(:))); + +%% -- For Debugging +if plot_result == 1 + fig = figure(); + fig.Position(3) = 400*2; + fig.Position(4) = 400*0.9; + subplot(121); hold on; + h1 = pcolor(xdat, ydat, ydat.*0); set(h1,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); + subplot(122); hold on; + h2 = pcolor(xdat_lt, ydat_lt, ydat_lt.*0); set(h2,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat_lt(:)), max(xdat_lt(:)), min(ydat_lt(:)), max(ydat_lt(:))]); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_translate.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_translate.m new file mode 100644 index 0000000..e7bb7ab --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F004 - generic algorithms/lt_translate.m @@ -0,0 +1,56 @@ +function [xdat_lt, ydat_lt] = lt_translate(xdat, ydat, trans_args, plot_result) +% [xdat_lt, ydat_lt] = lt_translate(xdat, ydat, trans_args, plot_result) +% Function to perform a Translation transformation on 2D data. +% +% REQ. FUNCTIONS: none +% +% IN: +% - xdat: [nX×nY] array of the x-axis (theta/kx) +% - ydat: [nX×nY] array of the y-axis (eb) +% - trans_args: {1×2} cell of {Tx, Ty} +% - plot_result: if 1, will plot figure summary, otherwise it wont. +% +% OUT: +% - xdat_lt: [nX×nY] array of the x-axis (theta/kx) after translation +% - ydat_lt: [nX×nY] array of the y-axis (eb) after translation + +%% Default parameters +if nargin < 3; trans_args = {0, 0}; end +if isempty(trans_args); trans_args = {0, 0}; end +%% Validity checks on the input parameters +if length(trans_args) ~= 2; trans_args = {0, 0}; end + +%% - 1 - Initialising the transformation parameters +% - Extracting the transformation values +Tx = trans_args{1}; +Ty = trans_args{2}; +% - Defining the transformation matrix +Tmatrix = [... + 1, 0, 0;... + 0, 1, 0;... + Tx, Ty, 1]; +Ttform = affine2d(Tmatrix); + +%% 2 - Performing transformation operation +xdat_lt = xdat + Tx; +ydat_lt = ydat + Ty; + +%% -- For Debugging +if plot_result == 1 + fig = figure(); + fig.Position(3) = 400*2; + fig.Position(4) = 400*0.9; + subplot(121); hold on; + h1 = pcolor(xdat, ydat, ydat.*0); set(h1,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat(:)), max(xdat(:)), min(ydat(:)), max(ydat(:))]); + subplot(122); hold on; + h2 = pcolor(xdat_lt, ydat_lt, ydat_lt.*0); set(h2,'EdgeColor','None','FaceColor','Flat'); + img_props(); + xlabel('$$ \bf X $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Y $$', 'Interpreter', 'latex'); + axis([min(xdat_lt(:)), max(xdat_lt(:)), min(ydat_lt(:)), max(ydat_lt(:))]); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/resample_arpes_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/resample_arpes_data.m new file mode 100644 index 0000000..764f467 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/resample_arpes_data.m @@ -0,0 +1,91 @@ +function rs_arpes_data = resample_arpes_data(arpes_data, rs_num, rs_type) +% rs_arpes_data = resample_arpes_data(arpes_data, rs_num, rs_type) +% This is a function that resamples a collection of ARPES data using a +% Bayesian Bootstrap method. For N independent ARPES data, the data +% is resampled by using a linear combination of the available data each +% of which are scaled by coefficients (between 0 - 1) that are determined +% by a uniform random number generator. This sufficiently mixes all of +% the experimental data, to create a new 'pseudo' data set that can be +% used for statistical analysis. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - arpes_data: {1×N} cell-array that contains a collection of all ARPES data, loaded and processed using ARPESGUI. +% - rs_num: scalar number of the total number of resampled . +% - rs_type: string of the data resampling technique to use (if empty, Default: "BayesianBootstrap" ("BB"), or "JackKnife" ("JK")) +% +% OUT: (none, only the file is saved) +% - rs_arpes_data: {1×N} cell-array that contains all the resampled data. + +%% Default parameters +if nargin < 3; rs_type = "BB"; end +if nargin < 2; rs_num = 1e3; end +if isempty(rs_type); rs_type = "BB"; end +if isempty(rs_num); rs_num = 1e3; end + +%% - 1 - Verifying consistency of the ARPES data grid size +% -- Extracting the ARPES data dimensions +for i = 1:length(arpes_data) + eb_size(i) = size(arpes_data{i}.eb, 1); + kx_size(i) = size(arpes_data{i}.eb, 2); +end +% -- Storing the minimum index values, to ensure all original ARPES data has a consistent domain +eb_indx_min = min(eb_size(:)); % find the minimum eb size +kx_indx_min = min(kx_size(:)); % find the minimmum kx size +% -- Cropping the original ARPES data to have a consistent domain (if required) +for i = 1:length(arpes_data) + EB{i} = arpes_data{i}.eb(1:eb_indx_min, 1:kx_indx_min); + KX{i} = arpes_data{i}.kx(1:eb_indx_min, 1:kx_indx_min); + DATA{i} = arpes_data{i}.data(1:eb_indx_min, 1:kx_indx_min); +end + +%% - 2 - Defining the Eb and Kx dimensions for the resampled data +rs_arpes_data.Type = "Eb(k) - Resampled"; +rs_arpes_data.kx = KX{1}; +rs_arpes_data.eb = EB{1}; + +%% - 3.0 - Creating an artificial data set based on all the ARPES data +rs_kx = rs_arpes_data.kx; +rs_eb = rs_arpes_data.eb; +%% - 3.1 - Bayesian Bootstrap method +if lower(rs_type) == "bb" || lower(rs_type) == "bayesianbootstrap" + for n = 1:rs_num + % -- Initialising the resampled ARPES data arrays + rs_data = []; + rs_sf = []; + for i = 1:length(DATA) + rs_sf(i) = rand(1); + rs_data(:,:,i) = rs_sf(i).* DATA{i}; + end + % --- Applying cross-correlation analysis + [rs_data, ~] = SumScanXC(rs_eb(:,1), rs_data, 0.5); + rs_data(isnan(rs_data)) = 0; + % --- Renormalising the resampled ARPES data + rs_data = rs_data - min(rs_data(:)); + rs_data = rs_data ./ max(rs_data(:)); + % --- Storing the ARPES data into the resampled cell-array + rs_arpes_data.sf{n} = rs_sf; + rs_arpes_data.data{n} = rs_data; + end +elseif lower(rs_type) == "jk" || lower(rs_type) == "jackknife" + for n = 1:length(DATA) + % -- Initialising the resampled ARPES data arrays + rs_data = []; + rs_sf = ones(1,length(DATA)); + rs_sf(n) = 0; + for i = 1:length(DATA) + rs_data(:,:,i) = rs_sf(i).* DATA{i}; + end + % --- Applying cross-correlation analysis + [rs_data, ~] = SumScanXC(rs_eb(:,1), rs_data, 0.5); + rs_data(isnan(rs_data)) = 0; + % --- Renormalising the resampled ARPES data + rs_data = rs_data - min(rs_data(:)); + rs_data = rs_data ./ max(rs_data(:)); + % --- Storing the ARPES data into the resampled cell-array + rs_arpes_data.sf{n} = rs_sf; + rs_arpes_data.data{n} = rs_data; + end +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_cluster.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_cluster.m new file mode 100644 index 0000000..f16829b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_cluster.m @@ -0,0 +1,81 @@ +function fig = view_stat_cluster(params, labels, n_order) +% fig = view_stat_cluster(params, labels, n_order) +% This function is used to plot the output paramaters of fitting functions, +% where you want to keep track of the value of a fit parameters vs run +% number. This can be used to check for any large deviations of the fit +% parameters and whether you should impose any constraints if some +% solutions are unphysical. The cluster analysis plots consist of 3 +% layers; (1) the first is a pair-wise scatter plot of the fit +% parameters, allowing you to observe how repeatable and convergent each +% solution is; (2) the second is a colormap which is overlaid on the +% background of each pair-wise plot, showing you the frequency of each +% fit parameter. This allows you to identify the most probable solution. +% (3) if 'n_order' does not equal zero, it will plot a 2D Gaussian +% function around the pair-wise clusters to give an estimate of their +% mean position and standard deviation. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - params: (N x P) array of P fit parameters converged with +% N independent runs. For a system in which some +% parameters are common, you can define the params as a +% {1 x P} cell array, each of which has an (N x C) array +% of C common fit parameters with N independent runs. +% - labels: (1 x P) cell array that contains the labels of each fit +% parameter. +% - n_order: scalar of the number of Gaussians to use when trying to +% fit the cluster analysis. +% +% OUT: +% - fig: MATLAB figure object with the cluster analysis plotted. + +%% Default parameters +if nargin < 3; n_order = 0; end +if nargin < 2; labels = []; end +if isempty(labels); labels = []; end +if isempty(n_order); n_order = 0; end +% -- Initialising the plot parameters +pp = plot_props(); + +%% - 1 - INITIALISING VARIABLES +% -- Initialising the variables +P = size(params, 2); % number of independent parameters +N = size(params, 1); % number of independent runs + +%% - 2 - PLOTTING THE BEST FIT PARAMETERS AS A FIGURE MATRIX +for p = 1:P + % -- Initialising the figure + fig(p) = figure(); set(fig(p), 'Name', 'Statistical Analysis - Parameters vs Run Number'); + fig(p).Position(3) = P*pp.fig4x4(1); + fig(p).Position(4) = 1.0*pp.fig4x4(2); + for j = 1:P + % -- Plotting the best fit parameters as a cluster plot + subplot(1,P,j); hold on; + plot(params(:,p), params(:,j), 'k.', 'color', pp.col.fit{p}, 'markerfacecolor', pp.col.fit{p}, 'markersize', 10); + % -- Plotting the best fit parameters as a coloured histogram + N = hist3([params(:,p), params(:,j)], 'CDataMode','auto','FaceColor','interp'); + N_pcolor = N'; N_pcolor(size(N_pcolor,1)+1,size(N_pcolor,2)+1) = 0; + xl = linspace(min(params(:,p)),max(params(:,p)),size(N_pcolor,2)); % Columns of N_pcolor + yl = linspace(min(params(:,j)),max(params(:,j)),size(N_pcolor,1)); % Rows of N_pcolor + h = pcolor(xl,yl,N_pcolor); + h.ZData = -1*ones(size(N_pcolor)); % Shifting the map to be below data points + % -- Plotting the best fit Gaussian around the clusters + if n_order ~= 0 + if p ~= j + A = params(:,[p,j]); + GMModel = fitgmdist(A,n_order); + gmPDF = @(x,y) arrayfun(@(x0,y0) pdf(GMModel,[x0 y0]),x,y); + g = gca; fcontour(gmPDF,[g.XLim g.YLim]); + end + end + % -- Formatting the figure + xlabel(labels{p}, 'interpreter', 'latex'); + ylabel(labels{j}, 'interpreter', 'latex'); + if min(params(:,p)) ~= max(params(:,p)) && min(params(:,j)) ~= max(params(:,j)) + axis([min(params(:,p)),max(params(:,p)),min(params(:,j)),max(params(:,j))]); + end + gca_props(); ax = gca; ax.FontSize = 9; axis square; + end +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_cluster_prctile.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_cluster_prctile.m new file mode 100644 index 0000000..5e1cf39 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_cluster_prctile.m @@ -0,0 +1,70 @@ +function fig = view_stat_cluster_prctile(params, labels, chisq, prc) +% fig = view_stat_cluster_prctile(params, labels, chisq, prc) +% This function plots the same figure as in view_stat_cluster(), however, +% it isolates the clusters into two segments; either above or below the +% percentile [prc] value of the chi-squared [chisq] matrix. This allows +% you to identify the top 10% of the optimal fits, allowing you to select +% the best fit parameters more precisely. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - params: (N x P) array of P fit parameters converged with +% N independent runs. For a system in which some +% parameters are common, you can define the params as a +% {1 x P} cell array, each of which has an (N x C) array +% of C common fit parameters with N independent runs. +% - labels: (1 x P) cell array that contains the labels of each fit parameter. +% - chisq: (1 x M) vector that contains the chi-squared values for each one of the converged fits. +% - prc: scalar value between [0, 100] that thresholds all the fit +% parameters within a percentile, 0 < prc, of the chi- +% squared values. This allows you to isolate the best +% solutions for diagnostic testing. +% +% OUT: +% - fig: MATLAB figure object with the cluster analysis plotted. + +%% Default parameters +if nargin < 4; prc = 10; end +if isempty(chisq); error('Not enough arguments; make sure you input chisq.'); end +if isempty(labels); labels = []; end +if isempty(prc); prc = 10; end +% -- Initialising the plot parameters +pp = plot_props(); + +%% - 1 - INITIALISING VARIABLES +% -- Initialising the variables +P = size(params, 2); % number of independent parameters +% -- Extracting the percentile value +chisq_prctile = prctile(chisq, prc); +prctile_indx = chisq < chisq_prctile; +raw_indx = ~prctile_indx; + +%% - 2 - PLOTTING THE BEST FIT PARAMETERS AS A FIGURE MATRIX +for p = 1:P + % -- Initialising the figure + fig(p) = figure(); + fig(p).Position(3) = P*pp.fig4x4(1); + fig(p).Position(4) = 1.0*pp.fig4x4(2); + for j = 1:P + % -- Plotting the best fit parameters as a cluster plot + subplot(1,P,j); hold on; + plot(params(raw_indx,p), params(raw_indx,j), 'r.', 'markersize', 6); + plot(params(prctile_indx,p), params(prctile_indx,j), 'g.', 'markersize', 10); + % -- Plotting the best fit parameters as a coloured histogram + N = hist3([params(:,p), params(:,j)], 'CDataMode','auto','FaceColor','interp'); + N_pcolor = N'; N_pcolor(size(N_pcolor,1)+1,size(N_pcolor,2)+1) = 0; + xl = linspace(min(params(:,p)),max(params(:,p)),size(N_pcolor,2)); % Columns of N_pcolor + yl = linspace(min(params(:,j)),max(params(:,j)),size(N_pcolor,1)); % Rows of N_pcolor + h = pcolor(xl,yl,N_pcolor); + h.ZData = -1*ones(size(N_pcolor)); % Shifting the map to be below data points + % -- Formatting the figure + xlabel(labels{p}, 'interpreter', 'latex'); + ylabel(labels{j}, 'interpreter', 'latex'); + if min(params(:,p)) ~= max(params(:,p)) && min(params(:,j)) ~= max(params(:,j)) + axis([min(params(:,p)),max(params(:,p)),min(params(:,j)),max(params(:,j))]); + end + gca_props(); ax = gca; ax.FontSize = 9; axis square; + end +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_hist.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_hist.m new file mode 100644 index 0000000..4eb9ba4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_hist.m @@ -0,0 +1,47 @@ +function fig = view_stat_hist(params, labels) +% fig = view_stat_hist(params, labels) +% This function is used to plot the output paramaters of fitting functions, +% where you want to keep track of the value of a fit parameters vs run +% number. Here, a histogram is plotted of all the N solutions to see if +% they exhibit a Gaussian / Uniform distribution, which may give some +% information to the best solutions. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - params: (N x P) array of P fit parameters converged with +% N independent runs. For a system in which some +% parameters are common, you can define the params as a +% {1 x P} cell array, each of which has an (N x C) array +% of C common fit parameters with N independent runs. +% - labels: (1 x P) cell array that contains the labels of each fit +% parameter. +% +% OUT: +% - fig: MATLAB figure object with the histogram analysis plotted. + +%% Default parameters +if nargin < 2; labels = []; end +if isempty(labels); labels = []; end +% -- Initialising the plot parameters +pp = plot_props(); + +%% - 1 - INITIALISING VARIABLES +% -- Initialising the variables +P = size(params, 2); % number of independent parameters +N = size(params, 1); % number of independent runs +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'Statistical Analysis - Histogram of Fit Parameters'); +fig.Position(3) = (P./2)*pp.fig5x4(1); +fig.Position(4) = 0.7*pp.fig5x4(2); +%% - 2 - PLOTTING THE PARAMETERS VS N +for p = 1:P + subplot(1,P,p); hold on; + histogram(params(:,p), 'facecolor', pp.col.fit{p}); + % -- Formatting the figure +% axis padded; + gca_props(); + if ~isempty(labels); title(labels{p}, 'fontweight', 'bold'); end + ax = gca; ax.FontSize = 10; +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_params.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_params.m new file mode 100644 index 0000000..5f8b4f8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F005 - statistical analysis of fitting/view_stat_params.m @@ -0,0 +1,66 @@ +function fig = view_stat_params(params, labels) +% fig = view_stat_params(params, labels) +% This function is used to plot the output parameters of fitting functions, +% where you want to keep track of the value of a fit parameters vs run +% number. This can be used to check for any large deviations of the fit +% parameters and whether you should impose any constraints if some +% solutions are unphysical. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - params: (N x P) array of P fit parameters converged with +% N independent runs. For a system in which some +% parameters are common, you can define the params as a +% {1 x P} cell array, each of which has an (N x C) array +% of C common fit parameters with N independent runs. +% - labels: (1 x P) cell array that contains the labels of each fit +% parameter. +% +% OUT: +% - fig: MATLAB figure object with the fit parameter analysis plotted. + +%% Default parameters +if nargin < 2; labels = []; end +if isempty(labels); labels = []; end +% -- Initialising the plot parameters +pp = plot_props(); + +%% - 1 - INITIALISING VARIABLES +if iscell(params) + P = length(params); % number of independent parameters + N = size(params{1}, 1); % number of independent runs +else + P = size(params, 2); % number of independent parameters + N = size(params, 1); % number of independent runs +end +nruns = 1:N; % number of independent runs as a vector +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'Statistical Analysis - Parameters vs Run Number'); +fig.Position(3) = (P./2)*pp.fig5x4(1); +fig.Position(4) = 1.25*pp.fig5x4(2); + +%% - 2 - PLOTTING THE FIT PARAMETERS VS NUMBER OF RUNS +for p = 1:P + subplot(1,P,p); hold on; + % -- Plotting the outcome for the XPS fitting + if iscell(params) + C = size(params{p}, 2); % number of independent common fit parameters. + for c = 1:C + plot(params{p}(:,c), nruns, 'k.-', 'color', pp.col.fit{c}, 'markerfacecolor', pp.col.fit{c}, 'linewidth', 1.25); + errorbar(mean(params{p}(:,c)), mean(nruns(:)), 0, 0, 3*std(params{p}(:,c)), 3*std(params{p}(:,c)), 'ks-',... + 'color', [0 0 0], 'markerfacecolor', pp.col.fit{c}, 'markersize', 12, 'linewidth', 1.5); + end + % -- Plotting the outcome for the ARPES fitting + else + plot(params(:,p), nruns, 'k.-', 'color', pp.col.fit{p}, 'markerfacecolor', pp.col.fit{p}, 'linewidth', 1.25); + errorbar(mean(params(:,p)), mean(nruns(:)), 0, 0, 3*std(params(:,p)), 3*std(params(:,p)), 'ks-',... + 'color', [0 0 0], 'markerfacecolor', pp.col.fit{p}, 'markersize', 12, 'linewidth', 1.5); + end + % -- Formatting the figure +% axis padded; + gca_props(); + if ~isempty(labels); title(labels{p}, 'fontweight', 'bold'); end + ax = gca; ax.FontSize = 10; +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/create_arpes_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/create_arpes_data.m new file mode 100644 index 0000000..384ac88 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/create_arpes_data.m @@ -0,0 +1,26 @@ +function arpesStr = create_arpes_data() +% arpesStr = create_arpes_data() +% This function generates a template data structure used for +% analysing ARPES data. The fields can be filled in, after which the user +% can then use the data structure within all the processing / fitting +% tools. +% - Assigning file information +arpesStr = struct(); +arpesStr.FileName = ''; +arpesStr.H5file = ''; +arpesStr.TimeStamp = datetime; +arpesStr.Type = "Eb(k)"; +arpesStr.index = 1; +% - Assigning the meta data +arpesStr.meta = struct(); +% - Assinging experimental parameters +arpesStr.hv = []; +arpesStr.tltM = []; +arpesStr.tltE = []; +arpesStr.thtM = []; +arpesStr.Temp = []; +% - Assinging the main experimental variables +arpesStr.raw_data = []; +arpesStr.raw_tht = []; +arpesStr.raw_eb = []; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/create_pes_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/create_pes_data.m new file mode 100644 index 0000000..c2addcb --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/create_pes_data.m @@ -0,0 +1,15 @@ +function pesStr = create_pes_data() +% pesStr = create_pes_data() +% This function generates a template data structure used for +% analysing PES data. The fields can be filled in, after which the user +% can then use the data structure within all the processing / fitting +% tools. +pesStr = struct(); +pesStr.FileName = ''; +pesStr.H5file = ''; +pesStr.TimeStamp = datetime; +pesStr.Type = "PES"; +pesStr.hv = []; +pesStr.xdat = []; +pesStr.ydat = []; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_adress_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_adress_data.m new file mode 100644 index 0000000..23c53d6 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_adress_data.m @@ -0,0 +1,275 @@ +function dataStr = load_adress_data(FileName, PathName) +% dataStr = load_adress_data(FileName, PathName) +% This function loads in the HDF5 data files of ARPES data from +% the ADRESS beamline at the SLS. The output is a MATLAB +% data-structure that yields all the data and information. This function +% should be used to load in a single ADRESS data-file that is unprocessed +% or has been previously processed using PESTools. Last updated in +% October 2022, and includes electrostatic tilt extraction. +% +% REQ. FUNCTIONS: +% - [data, axes, note] = ReaderHDF5(fname); +% +% IN: +% - FileName: char of the input .h5 or .mat file-name. +% - PathName: char of the input .h5 or .mat directory path. +% +% OUT: +% dataStr - MATLAB data structure containing all fields below; +% .(FileName): string of the current filename of the data file. +% .(H5file): string of the raw .H5 filename of the data file. +% .(TimeStamp): time-stamp of when the file was created. +% .(Type): string "Eb(k)", "Eb(k,i)", "Eb(kx,ky)" or "Eb(kx,kz)". +% .(index): [1xN] vector of the total number of scans. +% .(meta): structure that contains all meta information. +% .(meta.info): [1xN] char array of scan information. +% .(meta.Epass): scalar of the Pass energy. +% .(meta.Pol): string of the photon polarisation used. +% .(meta.Slit): scalar of the beamline exit slit size. +% .(meta.Mode): string of the Analyzer angular mode used. +% .(meta.X): scalar of the manipulator X position. +% .(meta.Y): scalar of the manipulator Y position. +% .(meta.Z): scalar of the manipulator Z position. +% .(meta.dhv): scalar estimate of the beamline resolution. +% .(meta.deb): scalar of the Analyzer resolution. +% .(hv): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). Photon energy [eV]. +% .(tltM): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). Mechanical Tilt [degrees] +% .(tltE): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). Electrostatic Tilt [degrees]. +% .(thtM): scalar of the manipulator Theta angle. +% .(Temp): scalar of the sample temperature. +% .(raw_data): 2Data [nEnergy x nAngle] or 3Data [nEnergy x nAngle xnScan] data array. +% .(raw_tht): [1×nAngle] row vector of angles. +% .(raw_eb): [nEnergyx1] column vector of energy. + + +%% Default parameters +if nargin < 1; FileName = ''; end +if nargin < 2; PathName = ''; end +if isempty(FileName); FileName = ''; end +if isempty(PathName); PathName = ''; end +% - Display text +disp('Loading ADRESS data...') +% - Verifying inputs are characters +FileName = char(FileName); +PathName = char(PathName); + +%% 1 - Loading and reading in the HDF5 data file +dataStr = create_arpes_data(); +% - If no filename if defined, load in an empty data structure +if isempty(FileName); return; +% - Verify that a .h5 file has been parsed and load the variables +elseif string(FileName(end-2:end)) == ".h5" + %% 1.1 -- Extracting file information + FileInfo = dir(char(string(PathName) + string(FileName))); + TimeStamp = string(FileInfo.date); + %% 1.2 -- Extracting all of the data variables + [Data, Axes, Note] = ReaderHDF5(char(string(PathName) + string(FileName))); + Angle = Axes{1}; + Energy = (Axes{2})'; + if size(Axes,1)==3; Scan = Axes{3}; else Scan = []; end + if ndims(Data)==3; Data = double(permute(Data,[2 1 3])); else Data=double(Data'); end + % -- Identifying the type of scan that has been performed + if size(Scan, 1) == 0; Type = "Eb(k)"; % --- If no Scan parameter is defined, it must be an Eb(k) scan + elseif range(Scan) == 0; Type = "Eb(k,i)"; % --- If all Scan parameters are identical, it must be repeated Eb(k) scans + elseif max(Scan(:)) > 100; Type = "Eb(kx,kz)"; % --- If the maximum value of the Scan parameter is > 100, it must be Eb(kx,kz) + else; Type = "Eb(kx,ky)"; % --- Else the final type remaining is the Eb(kx,ky) scan + end + % -- Extracting the photon energy and mechanical tilt values + % --- For Eb(k) scans + if Type == "Eb(k)" || Type == "Eb(k,i)" + % -- Assigning the photon energy (hv) + tmpPos = strfind(Note,'hv ='); + % ---- Vanilla form hv = xxxx eV + for i = 0:1:3 + hv = str2double(Note(tmpPos+9:tmpPos+13-i)); + if ~isnan(hv); break; end + end + % ---- If there is a missing space + if isnan(hv) + for i = 0:1:3 + hv = str2double(Note(tmpPos+10:tmpPos+14-i)); + if ~isnan(hv); break; end + end + end + % ---- If there is a ones(x)* prefix to the hv value + if isnan(hv) + for i = 0:1:3 + hv = str2double(Note(tmpPos+18:tmpPos+24-i)); + if ~isnan(hv); break; end + end + end + % ---- If there is a ones(xx)* prefix to the hv value + if isnan(hv) + for i = 0:1:3 + hv = str2double(Note(tmpPos+19:tmpPos+23-i)); + if ~isnan(hv); break; end + end + end + if isnan(hv); hv = []; disp('hv in load_adress_data not assigned.'); end + % -- Assigning the mechanical tilt angle (Tilt) + tmpPos = strfind(Note, 'Tilt ='); + Tilt = str2double(Note(tmpPos+9:tmpPos+17)); + for i = 0:1:7 + Tilt = str2double(Note(tmpPos+9:tmpPos+17-i)); + if ~isnan(Tilt); break;end + end + if isnan(Tilt); Tilt = []; disp('Tilt in load_adress_data not assigned.'); end + % --- For Eb(kx,kz) or photon energy dependent scans + elseif Type == "Eb(kx,kz)" + % -- Assigning the photon energy (hv) as the scan parameter + hv = Scan; + % -- Assigning the tilt angle (Tilt) + tmpPos = strfind(Note, 'Tilt ='); + Tilt = str2double(Note(tmpPos+9:tmpPos+17)); + for i = 0:1:7 + Tilt = str2double(Note(tmpPos+9:tmpPos+17-i)); + if ~isnan(Tilt); break;end + end + if isnan(Tilt); Tilt = []; disp('Tilt in load_adress_data not assigned.'); end + elseif Type == "Eb(kx,ky)" + % -- Assigning the photon energy (hv) + tmpPos = strfind(Note,'hv ='); + % ---- Vanilla form hv = xxxx eV + for i = 0:1:3 + hv = str2double(Note(tmpPos+9:tmpPos+13-i)); + if ~isnan(hv); break; end + end + % ---- If there is a missing space + if isnan(hv) + for i = 0:1:3 + hv = str2double(Note(tmpPos+10:tmpPos+14-i)); + if ~isnan(hv); break; end + end + end + % ---- If there is a ones(x)* prefix to the hv value + if isnan(hv) + for i = 0:1:3 + hv = str2double(Note(tmpPos+18:tmpPos+24-i)); + if ~isnan(hv); break; end + end + end + % ---- If there is a ones(xx)* prefix to the hv value + if isnan(hv) + for i = 0:1:3 + hv = str2double(Note(tmpPos+19:tmpPos+23-i)); + if ~isnan(hv); break; end + end + end + if isnan(hv); hv = []; disp('hv in load_adress_data not assigned.'); end + % -- Assigning the tilt angle (Tilt) as the scan parameter + Tilt = Scan; + end + %% 1.3 -- Extracting the information variables from the Notes + % -- Pass energy (ep) and uncertainty (dE) evaluations + tmpPos = strfind(Note, 'Epass ='); + for i = 0:1:3 + Epass = str2double(Note(tmpPos+9:tmpPos+12-i)); + if ~isnan(Epass); break; end + end + if isnan(Epass); Epass = []; disp('Epass in load_adress_data not assigned.'); end + dHv = 75e-3; + dEnergy = 0.5*Epass/1000; + % -- Theta Manipulator (Theta) evaluation + tmpPos = strfind(Note, 'Theta ='); + for i = 0:1:7 + Theta = str2double(Note(tmpPos+9:tmpPos+17-i)); + if ~isnan(Theta); break; end + end + if isnan(Theta); Theta = []; disp('Theta in load_adress_data not assigned.'); end + % -- Temperature (Temp) evaluation + tmpPos = strfind(Note, 'Temp ='); + for i = 0:1:5 + Temp = str2double(Note(tmpPos+10:tmpPos+14-i)); + if ~isnan(Temp); break; end + end + % -- Deflection Angle (Electrostatic Tilt) evaluation + tmpPos = strfind(Note, 'ADef ='); + for i = 0:1:5 + ADef = str2double(Note(tmpPos+10:tmpPos+14-i)); + if ~isnan(ADef); break; end + end + % -- Polarisation evaluation + tmpPos = strfind(Note, 'Pol ='); + for i = 0:1:5 + Pol = string(Note(tmpPos+10:tmpPos+12-i)); + if contains(Pol,"LV"); Pol = "LV (p-pol)"; break; + elseif contains(Pol,"LH"); Pol = "LH (s-pol)"; break; + elseif contains(Pol,"C+"); Pol = "C+"; break; + elseif contains(Pol,"C-"); Pol = "C-"; break; + else; Pol = ""; + end + end + % -- Slit evaluation + tmpPos = strfind(Note, 'Slit = '); + for i = 0:1:5 + Slit = str2double(Note(tmpPos+10:tmpPos+14-i)); + if ~isnan(Slit); break; end + end + % -- Mode evaluation + tmpPos = strfind(Note, 'Mode = '); + for i = 0:1:5 + Mode = string(Note(tmpPos+10:tmpPos+13-i)); + if contains(Mode,"MAD"); Mode = "MAD"; break; + elseif contains(Mode,"MAM"); Mode = "MAM"; break; + elseif contains(Mode,"LAD"); Mode = "LAD"; break; + elseif contains(Mode,"WAM"); Mode = "WAM"; break; + else; Mode = ""; + end + end + % -- Manipulator Position evaluation + % --- X + tmpPos = strfind(Note, 'X = '); + for i = 0:1:8 + X = str2double(Note(tmpPos+10:tmpPos+20-i)); + if ~isnan(X); break; end + end + % --- Z + tmpPos = strfind(Note, 'Z = '); + for i = 0:1:8 + Z = str2double(Note(tmpPos+10:tmpPos+18-i)); + if ~isnan(Z); break; end + end + % --- Y + tmpPos = strfind(Note, 'Y = '); + for i = 0:1:6 + Y = str2double(Note(tmpPos+11:end-i)); + if ~isnan(Y); break; end + end + %% 1.4 - Assigning the data to the MATLAB structure + % - Assigning file information + dataStr.FileName = FileName(1:end-3); + dataStr.H5file = char(FileName); + dataStr.TimeStamp = TimeStamp; + dataStr.Type = Type; + dataStr.index = 1:size(Data, 3); + % - Assigning the meta data + dataStr.meta.info = Note; + dataStr.meta.Epass = Epass; + dataStr.meta.Pol = Pol; + dataStr.meta.Slit = Slit; + dataStr.meta.Mode = Mode; + dataStr.meta.X = X; + dataStr.meta.Y = Y; + dataStr.meta.Z = Z; + dataStr.meta.dhv = dHv; + dataStr.meta.deb = dEnergy; + % - Assinging experimental parameters + dataStr.hv = hv; + dataStr.tltM = Tilt; % Mechanical Tilt + dataStr.tltE = ADef; % Electrostatic Tilt + dataStr.thtM = Theta; + dataStr.Temp = Temp; + % - Assinging the main experimental variables + dataStr.raw_data = Data; + dataStr.raw_tht = Angle; + dataStr.raw_eb = Energy; + +%% 2 - Reading in the .mat data that has been processed before +elseif string(FileName(end-3:end)) == ".mat" + arpes_data = load(char(string(PathName) + string(FileName))); + dataStr = arpes_data.dataStr; + if isstruct(dataStr) && isfield(dataStr, 'FileName') + dataStr.FileName = FileName(1:end-4); + end +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_cassiopee_fs.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_cassiopee_fs.m new file mode 100644 index 0000000..e0172fb --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_cassiopee_fs.m @@ -0,0 +1,193 @@ +function dataStr = load_cassiopee_fs(PathName) +%% Default parameters +if nargin < 1; PathName = ''; end +% - Display text +disp('Loading SOLEIL data...') + +% - Verifying inputs are characters +PathName = char(PathName); +fileExt = '*.txt'; +dataStr = create_arpes_data(); + +% - If no filename if defined, load in an empty data structure +if isempty(PathName); return; +else + %% 0 - Move info files into info folder + % Define the info folder path + Info_Path = fullfile(string(PathName),'info'); + + % Create the destination directory if it does not exist + if ~exist(Info_Path, 'dir') + mkdir(Info_Path); + end + + % Get a list of all files in the source directory + fileList = dir(fullfile(string(PathName), fileExt)); + + % Loop through the file list and move files that match the pattern + for ii = 1:numel(fileList) + fileName = fileList(ii).name; + if ~isempty(regexp(fileName, '.*_\d+_i\.txt', 'once')) + movefile(fullfile(PathName, fileName), fullfile(Info_Path, fileName)); + end + end + + %% 1 - Loading and reading in the txt data file + % Define the regular expression pattern to match the numbers in the filenames + pattern = '(\d+)_ROI1_\.txt'; + + % Get a list of the files in the directory + file_list = dir(fullfile(string(PathName), fileExt)); + + % Extract the file numbers using regular expressions + file_nums = zeros(size(file_list)); + for i = 1:numel(file_list) + filename = file_list(i).name; + matches = regexp(filename, pattern, 'tokens'); + if ~isempty(matches) + file_nums(i) = str2double(matches{1}); + end + end + + % Sort the file list based on the extracted numbers + [sorted_nums, idx] = sort(file_nums); + sortedFileNames = file_list(idx); + + % Loop through the sorted file names and extract the theta values + data_cell = cell(length(sortedFileNames), 1); + + for i = 1:numel(sortedFileNames) + file_path = fullfile(string(PathName), sortedFileNames(i).name); + file_contents = fileread(file_path); + + data = readmatrix(file_path, 'Range', 'B46'); + data_cell{i} = data; + + deb_pattern = 'Energy Step=\s*(\S+)'; + deb_match = regexp(file_contents,deb_pattern,'tokens'); + deb = deb_match{1}{1}; + end + + dimension_1_scale_pattern = 'Dimension 1 scale=\s*([\d\. ]+)'; + dimension_1_scale_match = regexp(file_contents, dimension_1_scale_pattern, 'tokens'); + dimension_1_scale = str2num(dimension_1_scale_match{1}{1}); + + dimension_1_name_pattern = 'Dimension 1 name=\s*(\S+)'; + dimension_1_name_match = regexp(file_contents, dimension_1_name_pattern, 'tokens'); + dimension_1_name = dimension_1_name_match{1}{1}; + + dimension_2_name_pattern = 'Dimension 2 name=\s*(\S+)'; + dimension_2_name_match = regexp(file_contents, dimension_2_name_pattern, 'tokens'); + dimension_2_name = dimension_2_name_match{1}{1}; + + temperature_pattern = 'inputA=\s*([\d\. ]+)'; + temperature_match = regexp(file_contents, temperature_pattern, 'tokens'); + Temp = str2double(temperature_match{1}{1}); + + % Combine ARPES data + Data = cat(3, data_cell{:}); + + % Read the last file for the analyzer angle + fid = fopen(file_path, 'r'); + line_num = 0; + while ~feof(fid) + line_num = line_num + 1; + line = fgetl(fid); + if strncmp(line, 'Dimension 2 scale=', length('Dimension 2 scale=')) + % Found the line starting with "Dimension 2 scale=" + parts = strsplit(line, '='); + C = textscan(parts{2},'%f'); + % extract the array + Raw_tht = C{1}; + break; + end + end + fclose(fid); + + + %% Read info files + + % Define the regular expression pattern to match the numbers in the filenames + pattern = '(\d+)_i\.txt'; + + % Get a list of the files in the directory + file_list = dir(fullfile(string(Info_Path), fileExt)); + + % Extract the file numbers using regular expressions + file_nums = zeros(size(file_list)); + for i = 1:numel(file_list) + filename = file_list(i).name; + matches = regexp(filename, pattern, 'tokens'); + if ~isempty(matches) + file_nums(i) = str2double(matches{1}); + end + end + + % Sort the file list based on the extracted numbers + [sorted_nums, idx] = sort(file_nums); + sortedFileNames = file_list(idx); + + % Loop through the sorted file names and extract the theta values + theta_values = cell(numel(file_list), 1); + hv_values = cell(numel(file_list), 1); + + for i = 1:numel(sortedFileNames) + file_path = fullfile(Info_Path, sortedFileNames(i).name); + file_contents = fileread(file_path); + + theta_matches = regexp(file_contents, 'theta \(deg\) :[\t\s]*([\d.-]+)', 'tokens'); + hv_matches = regexp(file_contents, 'hv \(eV\) :[ \t]*([\d.]+)', 'tokens'); + + theta_values{i} = str2double(theta_matches{1}{1}); + hv_values{i} = str2double(hv_matches{1}{1}); + end + + % Read the last file for the tilt and beamline resolution + fid = fopen(file_path, 'r'); + line_num = 0; + tilt = []; + resolution = []; + + while ~feof(fid) + line_num = line_num + 1; + line = fgetl(fid); + + % search for "tilt (deg) :" + if strncmp(line, 'tilt (deg) :', length('tilt (deg) :')) + parts = strsplit(line, ':'); + tilt = str2double(parts{2}); + end + + % search for "Resolution (meV) :" + if strncmp(line, 'Resolution (meV) :', length('Resolution (meV) :')) + parts = strsplit(line, ':'); + resolution = str2double(parts{2}); + end + + % if both tilt and resolution are found, exit the loop + if ~isempty(tilt) && ~isempty(resolution) + break; + end + end + + %% Assemble data file + %meta info + dataStr.FileName = sortedFileNames(1).name; + %dataStr.H5file = ''; + dataStr.TimeStamp = string(sortedFileNames(1).date); + dataStr.Type = "Eb(kx,ky)"; + dataStr.index = 1:size(Data, 3); + dataStr.meta = struct(); + dataStr.raw_data = Data; + dataStr.raw_tht = transpose(Raw_tht); + dataStr.raw_eb = transpose(dimension_1_scale); + dataStr.deb = str2double(deb); + dataStr.hv = hv_values{1}; + dataStr.dhv = resolution; + dataStr.tltM = cell2mat(transpose(theta_values)); + %dataStr.tltE = []; + dataStr.thtM = tilt; + dataStr.Temp = Temp; + + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_cassiopee_kz.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_cassiopee_kz.m new file mode 100644 index 0000000..ca269b5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_cassiopee_kz.m @@ -0,0 +1,150 @@ +function dataStr = load_cassiopee_kz(PathName) +%% Default parameters +if nargin < 1; PathName = ''; end +% - Display text +disp('Loading SOLEIL data...') + +% - Verifying inputs are characters +PathName = char(PathName); +fileExt = '*.txt'; +dataStr = create_arpes_data(); + +% - If no filename if defined, load in an empty data structure +if isempty(PathName); return; +% - Verify that a .h5 file has been parsed and load the variables +else + %% 1 - Loading and reading in the txt data file + % Define the regular expression pattern to match the numbers in the filenames + pattern = '(\d+)_ROI1_\.txt'; + + % Get a list of the files in the directory + file_list = dir(fullfile(string(PathName), fileExt)); + + % Extract the file numbers using regular expressions + file_nums = zeros(size(file_list)); + for i = 1:numel(file_list) + filename = file_list(i).name; + matches = regexp(filename, pattern, 'tokens'); + if ~isempty(matches) + file_nums(i) = str2double(matches{1}); + end + end + + % Sort the file list based on the extracted numbers + [sorted_nums, idx] = sort(file_nums); + sortedFileNames = file_list(idx); + + % Loop through the sorted file names and extract the theta values + data_cell = cell(length(sortedFileNames), 1); + + for i = 1:numel(sortedFileNames) + file_path = fullfile(string(PathName), sortedFileNames(i).name); + file_contents = fileread(file_path); + + data = readmatrix(file_path, 'Range', 'B46'); + data_cell{i} = data; + + deb_pattern = 'Energy Step=\s*(\S+)'; + deb_match = regexp(file_contents,deb_pattern,'tokens'); + deb = deb_match{1}{1}; + end + + dimension_1_scale_pattern = 'Dimension 1 scale=\s*([\d\. ]+)'; + dimension_1_scale_match = regexp(file_contents, dimension_1_scale_pattern, 'tokens'); + dimension_1_scale = str2num(dimension_1_scale_match{1}{1}); + + dimension_1_name_pattern = 'Dimension 1 name=\s*(\S+)'; + dimension_1_name_match = regexp(file_contents, dimension_1_name_pattern, 'tokens'); + dimension_1_name = dimension_1_name_match{1}{1}; + + dimension_2_name_pattern = 'Dimension 2 name=\s*(\S+)'; + dimension_2_name_match = regexp(file_contents, dimension_2_name_pattern, 'tokens'); + dimension_2_name = dimension_2_name_match{1}{1}; + + temperature_pattern = 'inputA=\s*([\d\. ]+)'; + temperature_match = regexp(file_contents, temperature_pattern, 'tokens'); + Temp = str2double(temperature_match{1}{1}); + + % Concatenate the matrices + Data = cat(3, data_cell{:}); + + % Read the last file for the analyzer angle + fid = fopen(file_path, 'r'); + line_num = 0; + while ~feof(fid) + line_num = line_num + 1; + line = fgetl(fid); + if strncmp(line, 'Dimension 2 scale=', length('Dimension 2 scale=')) + % Found the line starting with "Dimension 2 scale=" + parts = strsplit(line, '='); + C = textscan(parts{2},'%f'); + % extract the array + Raw_tht = C{1}; + break; + end + end + fclose(fid); + + + %% Read info files + + % Define the info folder path + Info_Path = fullfile(string(PathName),'info'); + + % Define the regular expression pattern to match the numbers in the filenames + pattern = '(\d+)_i\.txt'; + + % Get a list of the files in the directory + file_list = dir(fullfile(string(Info_Path), fileExt)); + + % Extract the file numbers using regular expressions + file_nums = zeros(size(file_list)); + for i = 1:numel(file_list) + filename = file_list(i).name; + matches = regexp(filename, pattern, 'tokens'); + if ~isempty(matches) + file_nums(i) = str2double(matches{1}); + end + end + + % Sort the file list based on the extracted numbers + [sorted_nums, idx] = sort(file_nums); + sortedFileNames = file_list(idx); + + % Loop through the sorted file names and extract the theta values + theta_values = cell(numel(file_list), 1); + hv_values = cell(numel(file_list), 1); + + for i = 1:numel(sortedFileNames) + file_path = fullfile(Info_Path, sortedFileNames(i).name); + file_contents = fileread(file_path); + + theta_matches = regexp(file_contents, 'theta \(deg\) :[\t\s]*([\d.-]+)', 'tokens'); + hv_matches = regexp(file_contents, 'hv \(eV\) :[ \t]*([\d.]+)', 'tokens'); + + theta_values{i} = str2double(theta_matches{1}{1}); + hv_values{i} = str2double(hv_matches{1}{1}); + end + + + %% Assemble data file + %meta info + dataStr.FileName = sortedFileNames(1).name; + %dataStr.H5file = ''; + dataStr.TimeStamp = string(sortedFileNames(1).date); + dataStr.Type = "Eb(kx,kz)"; + dataStr.index = 1:size(Data, 3); + dataStr.meta = struct(); + dataStr.raw_data = Data; + dataStr.raw_tht = transpose(Raw_tht); + dataStr.raw_eb = transpose(dimension_1_scale); + dataStr.deb = str2double(deb); + dataStr.hv = transpose(cell2mat(hv_values)); + dataStr.dhv = []; + dataStr.tltM = theta_values{1}; + %dataStr.tltE = []; + %dataStr.thtM = []; + dataStr.Temp = Temp; + + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_pearl_data.asv b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_pearl_data.asv new file mode 100644 index 0000000..767b484 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_pearl_data.asv @@ -0,0 +1,282 @@ +function dataStr = load_pearl_data(FileName, PathName) +% dataStr = load_pearl_data(FileName, PathName) +% This function loads in the HDF5 data files of ARPES / XPS data from +% the PEARL beamline at the SLS. The output is a MATLAB +% data-structure that yields all the data and information. This function +% should be used to load in a single PEARL data-file that is unprocessed +% or has been previously processed using PESTools. Last updated in +% November 2022 +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - FileName: char of the input .h5 or .mat file-name. +% - PathName: char of the input .h5 or .mat directory path. +% +% OUT: +% dataStr - MATLAB data structure containing all fields below; +% .(FileName): string of the current filename of the data file. +% .(H5file): string of the raw .H5 filename of the data file. +% .(TimeStamp): time-stamp of when the file was created. +% .(Type): string "Eb(k)", "Eb(k,i)", "Eb(kx,ky)" or "Eb(kx,kz)". +% .(index): [1xN] vector of the total number of scans. +% .(meta): structure that contains all meta information. +% .(meta.general): structure with author / sample information. +% .(meta.logs): string array with acuisition logs. +% .(meta.Pol): string of the photon polarisation used. +% .(meta.Slit): scalar of the beamline exit slit size. +% .(meta.Mode): string of the Analyzer angular mode used. +% .(meta.X): scalar of the manipulator X position. +% .(meta.Y): scalar of the manipulator Y position. +% .(meta.Z): scalar of the manipulator Z position. +% .(meta.dhv): scalar estimate of the beamline resolution. +% .(meta.deb): scalar of the Analyzer resolution. +% .(hv): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). Photon energy [eV]. +% .(tltM): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). Mechanical Tilt [degrees] +% .(tltE): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). Electrostatic Tilt [degrees]. +% .(thtM): scalar of the manipulator Theta angle. +% .(Temp): scalar of the sample temperature. +% .(raw_data): 2Data [nEnergy x nAngle] or 3Data [nEnergy x nAngle xnScan] data array. +% .(raw_tht): [1×nAngle] row vector of angles. +% .(raw_eb): [nEnergyx1] column vector of energy. + +%% Default parameters +if nargin < 1; FileName = ''; end +if nargin < 2; PathName = ''; end +if isempty(FileName); FileName = ''; end +if isempty(PathName); PathName = ''; end +% - Display text +disp('Loading PEARL data...') +% - Verifying inputs are characters +FileName = char(FileName); +PathName = char(PathName); + +%% 1 - Loading and reading in the HDF5 data file +% - If no filename if defined, load in an empty data structure +if isempty(FileName); return; +% - Verify that a .h5 file has been parsed and load the variables +elseif string(FileName(end-2:end)) == ".h5" + %% 1.1 -- Extracting file information + FileInfo = dir(char(string(PathName) + string(FileName))); + TimeStamp = string(FileInfo.date); + %% 1.2 -- Extracting all of the data variables + initStr = struct(); + full_h5_file_name = char(string(PathName) + string(FileName)); + %% 1.2.1 -- Extracting all of the data variables - Regular '\scan1' Spectrum + Type = "Eb(k)"; + group_names = string({h5info(full_h5_file_name).Groups.Name}); + if group_names(1) == '/__DATA_TYPES__'; group_names(1) = []; end + % -- Filing through each group and extracting all the data + for i = 1:length(group_names) + % Validity check on group name + % ---- Ensuring the group name does not include prefix '/' + group_name = group_names(i); group_name = char(group_name); group_name = group_name(2:end); + % ---- Removing all spaces from the group name + group_name = strrep(group_name," ","_"); + % Extracting element names + element_names = string({h5info(full_h5_file_name, char(group_names(i)+"/")).Datasets.Name}); + % --- Filing through each element in the group + for j = 1:length(element_names) + % Validity check on element name + element_name = element_names(j); + % ---- Extracting the PEARL dataset + initStr.(group_name).(element_name) = h5read(full_h5_file_name, char(group_names(i)+"/"+element_names(j))); + end + % --- Extracting all the data attributes + if group_name == "scan1" + attr_names = string({h5info(full_h5_file_name, char("/scan1/attrs")).Datasets.Name}); + for j = 1:length(attr_names) + initStr.scan1.attrs.(attr_names(j)) = h5read(full_h5_file_name, char("/scan1/attrs"+"/"+attr_names(j))); + end + end + end + % Extracting all the scan attributes + general = initStr.general; + logs = initStr.logs.logs; + %% 1.2.2 -- Extracting all of the data variables - MultiRegionScan '\scan1' + if sum(contains(group_names, "/scan 1")) ~= 0 + % For custom 'MultiRegionScan' files + Type = "Eb(k,i)"; + group_names = string({h5info(full_h5_file_name, char("/scan 1")).Groups.Name}); + % -- Filing through each group and extracting all the data + for i = 1:length(group_names) + % ---- Ensuring the group name does not include prefix '/' + group_name = group_names(i); group_name = char(group_name); group_name = group_name(9:end); + % Extracting element names + element_names = string({h5info(full_h5_file_name, char(group_names(i)+"/")).Datasets.Name}); + % --- Filing through each element in the group + for j = 1:length(element_names) + initStr.scan_1.(group_name).(element_names(j)) = h5read(full_h5_file_name, char(group_names(i)+"/"+element_names(j))); + end + end + end + %% 1.2.3 -- Collecting all spectral data + spectra = struct(); + if isfield(initStr,'scan_1'); spectra = initStr.scan_1; Type = "Eb(k,i)"; + elseif isfield(initStr,'scan1'); spectra = initStr.scan1; Type = "Eb(k)"; + end + %% 1.3 -- Extracting all of the necessary variables + % --- Extracting region / type independent variables + % ----- Extracting experimental parameters & meta data + Pol = "LH (s-pol)"; + Slit = mean(spectra.attrs.ExitSlit); + Mode = spectra.attrs.LensMode(1); + hv = mean(spectra.attrs.MonoEnergy); + Temp = mean(spectra.attrs.ManipulatorTempB); + % ----- Assinging the main experimental variables + % ------ Angle + angle_start = spectra.attrs.ScientaSliceBegin(1); + angle_end = spectra.attrs.ScientaSliceEnd(1); + angle_num = spectra.attrs.ScientaNumSlices(1); + Angle = linspace(angle_start, angle_end, angle_num); + % -- For an XPSSPectrum + if Type == "Eb(k)" + % - Extracting experimental parameters & meta data + X = spectra.attrs.ManipulatorX; + Y = spectra.attrs.ManipulatorY; + Z = spectra.attrs.ManipulatorZ; + Tilt = spectra.attrs.ManipulatorTilt; + Theta = spectra.attrs.ManipulatorTheta; + Phi = spectra.attrs.ManipulatorPhi; + % - Assinging the main experimental variables + Epass = str2double(spectra.attrs.PassEnergy); + % -- Kinetic Energy + ek_start = spectra.attrs.ScientaChannelBegin(1); + ek_end = spectra.attrs.ScientaChannelEnd(1); + ek_step = spectra.attrs.StepSize(1); + kEnergy = ek_start : ek_step : ek_end; kEnergy = kEnergy'; + % -- Binding Energy + Energy = kEnergy - hv - 4.5; + % -- Data + Data = spectra.ScientaImage; + % -- Index + index = 1:size(Data,3); + % -- Assigning the data to the MATLAB structure + dataStr = struct(); + % - Assigning file information + dataStr.FileName = FileName(1:end-3); + dataStr.H5file = char(FileName); + dataStr.TimeStamp = TimeStamp; + dataStr.Type = Type; + dataStr.index = index; + % - Assigning the meta data + dataStr.meta.general = general; + dataStr.meta.logs = logs; + dataStr.meta.Epass = Epass; + dataStr.meta.Pol = Pol; + dataStr.meta.Slit = Slit; + dataStr.meta.Mode = Mode; + dataStr.meta.X = X; + dataStr.meta.Y = Y; + dataStr.meta.Z = Z; + % - Assinging experimental parameters + dataStr.hv = hv; + dataStr.phiM = Phi; + dataStr.thtM = Theta; + dataStr.tltM = Tilt; + dataStr.Temp = Temp; + % - Assinging the main experimental variables + dataStr.raw_data = Data; + dataStr.raw_tht = Angle; + dataStr.raw_eb = Energy; + % -- For a MultiRegionScan + elseif Type == "Eb(k,i)" + % --- Extracting region dependent variables + field_names = fieldnames(spectra,'-full'); + region_index = contains(field_names, 'region'); + region_names = field_names(region_index); + % --- If there is no region, it is a ManipulatorScan + if isempty(region_names) + manip_index = contains(field_names, 'Manipulator'); + manip_names = field_names(manip_index); + scan_name = manip_names{1}; + spectra + % - Extracting experimental parameters & meta data + if strcmp(scan_name, "ManipulatorZ"); + X = spectra.attrs.ManipulatorX; + Y = spectra.attrs.ManipulatorY; + Z = spectra.attrs.ManipulatorZ; + Tilt = spectra.attrs.ManipulatorTilt; + Theta = spectra.attrs.ManipulatorTheta; + Phi = spectra.attrs.ManipulatorPhi; + % - Assinging the main experimental variables + Epass = str2double(spectra.attrs.PassEnergy); + % -- Kinetic Energy + ek_start = spectra.attrs.ScientaChannelBegin(1); + ek_end = spectra.attrs.ScientaChannelEnd(1); + ek_step = spectra.attrs.StepSize(1); + kEnergy = ek_start : ek_step : ek_end; kEnergy = kEnergy'; + % -- Binding Energy + Energy = kEnergy - hv - 4.5; + % -- Data + Data = spectra.ScientaImage; + % -- Index + index = 1:size(Data,3); + + else + % --- Filing through each region and extracting spectrum + dataStr = {}; + for i = 1:length(region_names) + dataField = getfield(spectra, region_names{i}); + % - Extracting experimental parameters & meta data + X = dataField.PositionX; + Y = dataField.PositionY; + Z = dataField.PositionZ; + Tilt = dataField.PositionTilt; + Theta = dataField.PositionTheta; + Phi = dataField.PositionPhi; + % - Assinging the main experimental variables + Epass = dataField.ScientaPassEnergy; + % -- Kinetic Energy + ek_start = dataField.ScientaChannelBegin(1); + ek_end = dataField.ScientaChannelEnd(1); + ek_step = dataField.ScientaStepEnergy(1); + kEnergy = ek_start : ek_step : ek_end; kEnergy = kEnergy'; + % -- Binding Energy + Energy = kEnergy - hv - 4.5; + % -- Data + Data = dataField.ScientaImage; + Data = permute(Data, [2,3,1]); + % - Index + index = 1:size(Data,3); + % -- Assigning the data to the MATLAB structure + % - Assigning file information + dataStr{i}.FileName = FileName(1:end-3); + dataStr{i}.H5file = char(FileName); + dataStr{i}.TimeStamp = TimeStamp; + dataStr{i}.Type = Type; + dataStr{i}.index = index; + % - Assigning the meta data + dataStr{i}.meta.general = general; + dataStr{i}.meta.logs = logs; + dataStr{i}.meta.Epass = Epass; + dataStr{i}.meta.Pol = Pol; + dataStr{i}.meta.Slit = Slit; + dataStr{i}.meta.Mode = Mode; + dataStr{i}.meta.X = X; + dataStr{i}.meta.Y = Y; + dataStr{i}.meta.Z = Z; + % - Assinging experimental parameters + dataStr{i}.hv = hv; + dataStr{i}.phiM = Phi; + dataStr{i}.thtM = Theta; + dataStr{i}.tltM = Tilt; + dataStr{i}.Temp = Temp; + % - Assinging the main experimental variables + dataStr{i}.raw_data = Data; + dataStr{i}.raw_tht = Angle; + dataStr{i}.raw_eb = Energy; + end + end + + end + +%% 2 - Reading in the .mat data that has been processed before +elseif string(FileName(end-3:end)) == ".mat" + arpes_data = load(char(string(PathName) + string(FileName))); + initStr = arpes_data.pearlStr; + if isstruct(initStr) && isfield(initStr, 'FileName') + initStr.FileName = FileName(1:end-4); + end +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_pearl_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_pearl_data.m new file mode 100644 index 0000000..29b1c97 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_pearl_data.m @@ -0,0 +1,314 @@ +function dataStr = load_pearl_data(FileName, PathName) +% dataStr = load_pearl_data(FileName, PathName) +% This function loads in the HDF5 data files of ARPES / XPS data from +% the PEARL beamline at the SLS. The output is a MATLAB +% data-structure that yields all the data and information. This function +% should be used to load in a single PEARL data-file that is unprocessed +% or has been previously processed using PESTools. Last updated in +% November 2022 +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - FileName: char of the input .h5 or .mat file-name. +% - PathName: char of the input .h5 or .mat directory path. +% +% OUT: +% dataStr - MATLAB data structure containing all fields below; +% .(FileName): string of the current filename of the data file. +% .(H5file): string of the raw .H5 filename of the data file. +% .(TimeStamp): time-stamp of when the file was created. +% .(Type): string "Eb(k)", "Eb(k,i)", "Eb(kx,ky)" or "Eb(kx,kz)". +% .(index): [1xN] vector of the total number of scans. +% .(meta): structure that contains all meta information. +% .(meta.general): structure with author / sample information. +% .(meta.logs): string array with acuisition logs. +% .(meta.Pol): string of the photon polarisation used. +% .(meta.Slit): scalar of the beamline exit slit size. +% .(meta.Mode): string of the Analyzer angular mode used. +% .(meta.X): scalar of the manipulator X position. +% .(meta.Y): scalar of the manipulator Y position. +% .(meta.Z): scalar of the manipulator Z position. +% .(meta.dhv): scalar estimate of the beamline resolution. +% .(meta.deb): scalar of the Analyzer resolution. +% .(hv): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). Photon energy [eV]. +% .(tltM): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). Mechanical Tilt [degrees] +% .(tltE): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). Electrostatic Tilt [degrees]. +% .(thtM): scalar of the manipulator Theta angle. +% .(Temp): scalar of the sample temperature. +% .(raw_data): 2Data [nEnergy x nAngle] or 3Data [nEnergy x nAngle xnScan] data array. +% .(raw_tht): [1×nAngle] row vector of angles. +% .(raw_eb): [nEnergyx1] column vector of energy. + +%% Default parameters +if nargin < 1; FileName = ''; end +if nargin < 2; PathName = ''; end +if isempty(FileName); FileName = ''; end +if isempty(PathName); PathName = ''; end +% - Display text +disp('Loading PEARL data...') +% - Verifying inputs are characters +FileName = char(FileName); +PathName = char(PathName); + +%% 1 - Loading and reading in the HDF5 data file +% - If no filename if defined, load in an empty data structure +if isempty(FileName); return; +% - Verify that a .h5 file has been parsed and load the variables +elseif string(FileName(end-2:end)) == ".h5" + %% 1.1 -- Extracting file information + FileInfo = dir(char(string(PathName) + string(FileName))); + TimeStamp = string(FileInfo.date); + %% 1.2 -- Extracting all of the data variables + initStr = struct(); + full_h5_file_name = char(string(PathName) + string(FileName)); + %% 1.2.1 -- Extracting all of the data variables - Regular '\scan1' XPS Spectrum + Type = "Eb(k)"; + group_names = string({h5info(full_h5_file_name).Groups.Name}); + if group_names(1) == '/__DATA_TYPES__'; group_names(1) = []; end + % -- Filing through each group and extracting all the data + for i = 1:length(group_names) + % Validity check on group name + % ---- Ensuring the group name does not include prefix '/' + group_name = group_names(i); group_name = char(group_name); group_name = group_name(2:end); + % ---- Removing all spaces from the group name + group_name = strrep(group_name," ","_"); + % Extracting element names + element_names = string({h5info(full_h5_file_name, char(group_names(i)+"/")).Datasets.Name}); + % --- Filing through each element in the group + for j = 1:length(element_names) + % Validity check on element name + element_name = element_names(j); + % ---- Extracting the PEARL dataset + initStr.(group_name).(element_name) = h5read(full_h5_file_name, char(group_names(i)+"/"+element_names(j))); + end + % --- Extracting all the data attributes + if group_name == "scan1" + attr_names = string({h5info(full_h5_file_name, char("/scan1/attrs")).Datasets.Name}); + for j = 1:length(attr_names) + initStr.scan1.attrs.(attr_names(j)) = h5read(full_h5_file_name, char("/scan1/attrs"+"/"+attr_names(j))); + end + end + end + % Extracting all the scan attributes + general = initStr.general; + logs = initStr.logs.logs; + %% 1.2.2 -- Extracting all of the data variables - MultiRegionScan '\scan1' + if sum(contains(group_names, "/scan 1")) ~= 0 + % For custom 'MultiRegionScan' files + Type = "Eb(k,i)"; + group_names = string({h5info(full_h5_file_name, char("/scan 1")).Groups.Name}); + % -- Filing through each group and extracting all the data + for i = 1:length(group_names) + % ---- Ensuring the group name does not include prefix '/' + group_name = group_names(i); group_name = char(group_name); group_name = group_name(9:end); + % Extracting element names + element_names = string({h5info(full_h5_file_name, char(group_names(i)+"/")).Datasets.Name}); + % --- Filing through each element in the group + for j = 1:length(element_names) + initStr.scan_1.(group_name).(element_names(j)) = h5read(full_h5_file_name, char(group_names(i)+"/"+element_names(j))); + end + end + % initStr.scan_1 % FOR DEBUGGING + end + %% 1.2.3 -- Collecting all spectral data + spectra = struct(); + if isfield(initStr,'scan_1') + if isfield(initStr.scan_1,'Eph'); spectra = initStr.scan_1; Type = "Eb(k,hv)"; + else; spectra = initStr.scan_1; Type = "Eb(k,i)"; + end + elseif isfield(initStr,'scan1'); spectra = initStr.scan1; Type = "Eb(k)"; + end + %% 1.3 -- Extracting all of the necessary variables + % --- Extracting region / type independent variables + % ----- Extracting experimental parameters & meta data + Pol = "LH (s-pol)"; + Slit = mean(spectra.attrs.ExitSlit); + Mode = spectra.attrs.LensMode(1); + if Type == "Eb(k)" || Type == "Eb(k,i)"; hv = mean(spectra.attrs.MonoEnergy); else; hv = spectra.attrs.MonoEnergy; end + Temp = mean(spectra.attrs.ManipulatorTempB); + % ----- Assinging the main experimental variables + % ------ Angle + angle_start = spectra.attrs.ScientaSliceBegin(1); + angle_end = spectra.attrs.ScientaSliceEnd(1); + angle_num = spectra.attrs.ScientaNumSlices(1); + Angle = linspace(angle_start, angle_end, angle_num); + % -- For an XPSSPectrum + if Type == "Eb(k)" + % - Extracting experimental parameters & meta data + X = spectra.attrs.ManipulatorX; + Y = spectra.attrs.ManipulatorY; + Z = spectra.attrs.ManipulatorZ; + Tilt = spectra.attrs.ManipulatorTilt; + Theta = spectra.attrs.ManipulatorTheta; + Phi = spectra.attrs.ManipulatorPhi; + % - Assinging the main experimental variables + Epass = str2double(spectra.attrs.PassEnergy); + % -- Kinetic Energy + ek_start = spectra.attrs.ScientaChannelBegin(1); + ek_end = spectra.attrs.ScientaChannelEnd(1); + ek_step = spectra.attrs.StepSize(1); + kEnergy = ek_start : ek_step : ek_end; kEnergy = kEnergy'; + % -- Binding Energy + Energy = kEnergy - hv - 4.5; + % -- Data + Data = spectra.ScientaImage; + % -- Index + index = 1:size(Data,3); + % -- Assigning the data to the MATLAB structure + dataStr = struct(); + % - Assigning file information + dataStr.FileName = FileName(1:end-3); + dataStr.H5file = char(FileName); + dataStr.TimeStamp = TimeStamp; + dataStr.Type = Type; + dataStr.index = index; + % - Assigning the meta data + dataStr.meta.general = general; + dataStr.meta.logs = logs; + dataStr.meta.Epass = Epass; + dataStr.meta.Pol = Pol; + dataStr.meta.Slit = Slit; + dataStr.meta.Mode = Mode; + dataStr.meta.X = X; + dataStr.meta.Y = Y; + dataStr.meta.Z = Z; + % - Assinging experimental parameters + dataStr.hv = hv; + dataStr.phiM = Phi; + dataStr.thtM = Theta; + dataStr.tltM = Tilt; + dataStr.Temp = Temp; + % - Assinging the main experimental variables + dataStr.raw_data = Data; + dataStr.raw_tht = Angle; + dataStr.raw_eb = Energy; + % -- For a MultiRegionScan + elseif Type == "Eb(k,i)" + % --- Extracting region dependent variables + field_names = fieldnames(spectra,'-full'); + region_index = contains(field_names, 'region'); + region_names = field_names(region_index); + % Sorting regions into ascending order + filenum = cellfun(@(x)sscanf(x,'region%d'), region_names); % extract the numbers + [~,Sidx] = sort(filenum); % sort them, and get the sorting order + region_names = region_names(Sidx); % use to this sorting order to sort the filenames + % --- Filing through each region and extracting spectrum + dataStr = {}; + for i = 1:length(region_names) + dataField = getfield(spectra, region_names{i}); + % - Extracting experimental parameters & meta data + X = dataField.PositionX; + Y = dataField.PositionY; + Z = dataField.PositionZ; + Tilt = dataField.PositionTilt; + Theta = dataField.PositionTheta; + Phi = dataField.PositionPhi; + % - Assinging the main experimental variables + Epass = dataField.ScientaPassEnergy; + % -- Kinetic Energy + ek_start = dataField.ScientaChannelBegin(1); + ek_end = dataField.ScientaChannelEnd(1); + ek_step = dataField.ScientaStepEnergy(1); + kEnergy = ek_start : ek_step : ek_end; kEnergy = kEnergy'; + % -- Binding Energy + Energy = kEnergy - hv - 4.5; + % -- Data + Data = dataField.ScientaImage; + Data = permute(Data, [2,3,1]); + % - Index + index = 1:size(Data,3); + if index == 1; Type = "Eb(k)"; end + % -- Assigning the data to the MATLAB structure + % - Assigning file information + dataStr{i}.FileName = FileName(1:end-3); + dataStr{i}.H5file = char(FileName); + dataStr{i}.TimeStamp = TimeStamp; + dataStr{i}.Type = Type; + dataStr{i}.index = index; + % - Assigning the meta data + dataStr{i}.meta.general = general; + dataStr{i}.meta.logs = logs; + dataStr{i}.meta.region = region_names{i}; + dataStr{i}.meta.Epass = Epass; + dataStr{i}.meta.Pol = Pol; + dataStr{i}.meta.Slit = Slit; + dataStr{i}.meta.Mode = Mode; + dataStr{i}.meta.X = X; + dataStr{i}.meta.Y = Y; + dataStr{i}.meta.Z = Z; + % - Assinging experimental parameters + dataStr{i}.hv = hv; + dataStr{i}.phiM = Phi; + dataStr{i}.thtM = Theta; + dataStr{i}.tltM = Tilt; + dataStr{i}.Temp = Temp; + % - Assinging the main experimental variables + dataStr{i}.raw_data = Data; + dataStr{i}.raw_tht = Angle; + dataStr{i}.raw_eb = Energy; + end + % -- For a PhotonEnergy scan + elseif Type == "Eb(k,hv)" + % - Extracting experimental parameters & meta data + X = spectra.attrs.ManipulatorX; + Y = spectra.attrs.ManipulatorY; + Z = spectra.attrs.ManipulatorZ; + Tilt = spectra.attrs.ManipulatorTilt; + Theta = spectra.attrs.ManipulatorTheta; + Phi = spectra.attrs.ManipulatorPhi; + % - Assinging the main experimental variables + Epass = str2double(spectra.attrs.PassEnergy); + for i = 1:length(hv) + % -- Kinetic Energy + ek_start = spectra.attrs.ScientaChannelBegin(1); + ek_end = spectra.attrs.ScientaChannelEnd(1); + ek_step = spectra.attrs.StepSize(1); + kEnergy = ek_start : ek_step : ek_end; kEnergy = kEnergy'; + % -- Binding Energy + Energy(:,i) = kEnergy - hv(i) - 4.5; + end + % -- Data + Data = spectra.ScientaImage; + Data = permute(Data, [2,3,1]); + % -- Index + index = 1:size(Data,3); + % -- Assigning the data to the MATLAB structure + dataStr = struct(); + % - Assigning file information + dataStr.FileName = FileName(1:end-3); + dataStr.H5file = char(FileName); + dataStr.TimeStamp = TimeStamp; + dataStr.Type = Type; + dataStr.index = index; + % - Assigning the meta data + dataStr.meta.general = general; + dataStr.meta.logs = logs; + dataStr.meta.Epass = Epass; + dataStr.meta.Pol = Pol; + dataStr.meta.Slit = Slit; + dataStr.meta.Mode = Mode; + dataStr.meta.X = X; + dataStr.meta.Y = Y; + dataStr.meta.Z = Z; + % - Assinging experimental parameters + dataStr.hv = hv; + dataStr.phiM = Phi; + dataStr.thtM = Theta; + dataStr.tltM = Tilt; + dataStr.Temp = Temp; + % - Assinging the main experimental variables + dataStr.raw_data = Data; + dataStr.raw_tht = Angle; + dataStr.raw_eb = Energy; + end + +%% 2 - Reading in the .mat data that has been processed before +elseif string(FileName(end-3:end)) == ".mat" + arpes_data = load(char(string(PathName) + string(FileName))); + initStr = arpes_data.pearlStr; + if isstruct(initStr) && isfield(initStr, 'FileName') + initStr.FileName = FileName(1:end-4); + end +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_sis_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_sis_data.m new file mode 100644 index 0000000..f13eaf1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/load_sis_data.m @@ -0,0 +1,327 @@ +function dataStr = load_sis_data(FileName, PathName) +% dataStr = load_sis_data(FileName, PathName) +% This function loads in the HDF5 data files of ARPES data from +% the SIS beamline at the SLS. The output is a MATLAB +% data-structure that yields all the data and information. This function +% should be used to load in a single SIS data-file that is unprocessed +% or has been previously processed using PESTools. +% REQ. FUNCTIONS: +% - [data, axes, note] = ReaderHDF5(fname); +% - [DataXC,OffsE] = SumScanXC(Energy,Data,maxLagE[,WinE]); +% +% IN: +% - FileName: char of the input .h5 or .mat file-name. +% - PathName: char of the input .h5 or .mat directory path. +% +% OUT: +% dataStr - MATLAB data structure containing all fields below; +% .(FileName): string of the current filename of the data file. +% .(H5file): string of the raw .H5 filename of the data file. +% .(Type): string "Eb(k)", "Eb(k,i)", "Eb(kx,ky)" or "Eb(kx,kz)". +% .(raw_data): 2Data [nEnergy x nAngle] or 3Data [nEnergy x nAngle xnScan] data array. +% .(raw_tht): [1×nAngle] row vector of angles. +% .(raw_eb): [nEnergyx1] column vector of energy. +% .(hv): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). +% .(tltM): scalar or [1×nScan] row vector (if Scan parameter for 3Data data). +% .(thtM): scalar of the manipular Theta angle. +% .(Temp): scalar of the sample temperature. +% .(meta): structure with all measurement information. + +%% Default parameters +if nargin < 2; PathName = ''; end +if isempty(PathName); PathName = ''; end +disp('Loading in SIS data...') +% - Verifying input are characters +FileName = char(FileName); +PathName = char(PathName); + +%% 1 - Reading in the HDataF5 data +% - Verify that a .h5 file has been parsed and load the variables +if string(FileName(end-2:end)) == ".h5" + % -- Defining the MATLAB data-structure + dataStr = struct(); + dataStr.FileName = FileName(1:end-3); + dataStr.H5path = char(PathName); + dataStr.H5file = char(FileName); + H5full = char(string(PathName) + string(FileName)); + %% -- Extracting all of the data variables + datav_new = struct(); + datav_new.value = h5read(H5full,'/Electron Analyzer/Image Data'); + if ndims(datav_new.value) == 2 + size3 = size(datav_new.value); + xnum = size3(1);ynum=size3(2); + xaxis = h5readatt(H5full,'/Electron Analyzer/Image Data','Axis1.Scale'); + datav_new.y = xaxis(1):xaxis(2):xaxis(1)+(xnum-1)*xaxis(2); + yaxis = h5readatt(H5full,'/Electron Analyzer/Image Data','Axis0.Scale'); + datav_new.z = yaxis(1):yaxis(2):yaxis(1)+(ynum-1)*yaxis(2); + elseif ndims(datav_new.value) == 3 + size3 = size(datav_new.value); + xnum = size3(1);ynum=size3(3);znum=size3(2); + xaxis = h5readatt(H5full,'/Electron Analyzer/Image Data','Axis2.Scale'); + datav_new.x = xaxis(1):xaxis(2):xaxis(1)+(xnum-1)*xaxis(2); + yaxis = h5readatt(H5full,'/Electron Analyzer/Image Data','Axis0.Scale'); + datav_new.z = yaxis(1):yaxis(2):yaxis(1)+(ynum-1)*yaxis(2); + zaxis = h5readatt(H5full,'/Electron Analyzer/Image Data','Axis1.Scale'); + datav_new.y = zaxis(1):zaxis(2):zaxis(1)+(znum-1)*zaxis(2); + end + + %% -- Reading in all of the meta data + for meta = {h5info(H5full ,'/Electron Analyzer/').Datasets.Attributes.Name} + meta= meta(1); + if strcmp(meta{1},'Acquisition Mode') + datav_new.info.Aquisition_Mode= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Acquisition Mode'); + end + if strcmp(meta{1}, 'Intensity Units') + datav_new.info.Intensity_Units= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Intensity Units'); + end + if strcmp(meta{1}, 'Axis0.ScaleType') + datav_new.info.Axis0.ScaleType= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Axis0.ScaleType'); + end + if strcmp(meta{1}, 'Axis0.Scale') + datav_new.info.Axis0.Scale= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Axis0.Scale'); + end + if strcmp(meta{1}, 'Axis0.Description') + datav_new.info.Axis0.Description= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Axis0.Description'); + end + if strcmp(meta{1},'Axis0.Units') + datav_new.info.Axis0.Units= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Axis0.Units'); + end + if strcmp(meta{1},'Axis0.Mode') + datav_new.info.Axis0.Mode= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Axis0.Mode'); + end + if strcmp(meta{1}, 'Axis1.ScaleType') + datav_new.info.Axis1.ScaleType= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Axis1.ScaleType'); + end + if strcmp(meta{1}, 'Axis1.Scale') + datav_new.info.Axis1.Scale= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Axis1.Scale'); + end + if strcmp(meta{1}, 'Axis1.Description') + datav_new.info.Axis1.Description= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Axis1.Description'); + end + if strcmp(meta{1},'Axis1.Units') + datav_new.info.Axis1.Units= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Axis1.Units'); + end + if strcmp(meta{1},'Axis1.Mode') + datav_new.info.Axis1.Mode= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Axis1.Mode'); + end + if strcmp(meta{1},'Specified Number of Sweeps') + datav_new.info.Sweeps= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Specified Number of Sweeps'); + end + if strcmp(meta{1},'Dither Window (%)') + datav_new.info.Dither.Window= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Dither Window (%)'); + end + if strcmp(meta{1},'Dither Points') + datav_new.info.Dither.Points= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Dither Points'); + end + if strcmp(meta{1},'Lens Mode') + datav_new.info.Lens_Mode= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Lens Mode'); + end + if strcmp(meta{1},'Pass Energy (eV)') + datav_new.info.EPass= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Pass Energy (eV)'); + end + if strcmp(meta{1},'Energy Scale') + datav_new.info.Energy_Scale= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Energy Scale'); + end + if strcmp(meta{1},'Work Function (eV)') + datav_new.info.Work_Function= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Work Function (eV)'); + end + if strcmp(meta{1},'Dwell Time (ms)') + datav_new.info.Dwell_Time= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Dwell Time (ms)'); + end + if strcmp(meta{1},'Detector First X-Channel') + datav_new.info.Detector_First_X_Channel= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Detector First X-Channel'); + end + if strcmp(meta{1},'Detector Last X-Channel') + datav_new.info.Detector_Last_X_Channel= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Detector Last X-Channel'); + end + if strcmp(meta{1},'Detector First Y-Channel') + datav_new.info.Detector_First_Y_Channel= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Detector First Y-Channel'); + end + if strcmp(meta{1},'Detector Last Y-Channel') + datav_new.info.Detector_Last_Y_Channel= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Detector Last Y-Channel'); + end + if strcmp(meta{1},'Detector Slices') + datav_new.info.Detector_Slices= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Detector Slices'); + end + if strcmp(meta{1},'Detector ADC Mode') + datav_new.info.Detector_ADC_Mode= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Detector ADC Mode'); + end + if strcmp(meta{1},'Date Created') + datav_new.info.Creation_Date= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Date Created'); + end + if strcmp(meta{1},'Time Created') + datav_new.info.Creation_Time= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Time Created'); + end + if strcmp(meta{1},'Excitation Energy (eV)') + datav_new.info.Excitation_Energy= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Excitation Energy (eV)'); + end + if strcmp(meta{1},'Excitation Energy Read Device') + datav_new.info.Excitation_Energy_Readback= ... + h5readatt(H5full,'/Electron Analyzer/Image Data',... + 'Excitation Energy Read Device'); + end + end + for meta = {h5info(H5full ,'/').Attributes.Name} + meta = meta(1); + if strcmp(meta{1},'Comments') + datav_new.info.Comments= ... + h5readatt(H5full,'/',... + 'Comments'); + end + end + %% -- Reading in all of the instrumental data + try datav_new.info.ExitSlit=h5read(H5full,... + '/Other Instruments/Exit Slit'); catch ;end + try datav_new.info.FE_Vert_Width=h5read(H5full,... + '/Other Instruments/FE Vert. Width'); catch ;end + try datav_new.info.FE_Horiz_Width=h5read(H5full,... + '/Other Instruments/FE Horiz. Width'); catch ;end + try datav_new.info.Phi=h5read(H5full,... + '/Other Instruments/Phi'); catch ;end + try datav_new.info.Pressure_AC=h5read(H5full,... + '/Other Instruments/Pressure AC (ACMI)'); catch ;end + try datav_new.info.Pressure_TC=h5read(H5full,... + '/Other Instruments/Pressure TC (TCMP)'); catch ;end + try datav_new.info.Ring_Current=h5read(H5full,... + '/Other Instruments/Storage Ring Current'); catch ;end + try datav_new.info.Temperature_Cryo=h5read(H5full,... + '/Other Instruments/Temperature A (Cryostat)'); catch ;end + try datav_new.info.Temperature_Sample1=h5read(H5full,... + '/Other Instruments/Temperature B (Sample 1)'); catch ;end + try datav_new.info.Temperature_Head=h5read(H5full,... + '/Other Instruments/Temperature C (Head Mech)'); catch ;end + try datav_new.info.Temperature_Sample2=h5read(H5full,... + '/Other Instruments/Temperature D (Sample 2)'); catch ;end + try datav_new.info.Temperature_Boot1=h5read(H5full,... + '/Other Instruments/Temperature D2 (Boot 1)'); catch ;end + try datav_new.info.Temperature_Shield=h5read(H5full,... + '/Other Instruments/Temperature D3 (Shield)'); catch ;end + try datav_new.info.Temperature_Boot2=h5read(H5full,... + '/Other Instruments/Temperature D4 (Boot 2)'); catch ;end + try datav_new.info.Temperature_Cryopump=h5read(H5full,... + '/Other Instruments/Temperature D5 (Cryopump)'); catch ;end + try datav_new.info.Theta=h5read(H5full,... + '/Other Instruments/Theta'); catch ;end + try datav_new.info.Tilt=h5read(H5full,... + '/Other Instruments/Tilt'); catch ;end + try datav_new.info.X=h5read(H5full,... + '/Other Instruments/X'); catch ;end + try datav_new.info.Y=h5read(H5full,... + '/Other Instruments/Y'); catch ;end + try datav_new.info.Z=h5read(H5full,... + '/Other Instruments/Z'); catch ;end + try datav_new.info.hv=h5read(H5full,... + '/Other Instruments/hv'); catch ;end + + %% -- Creating a consistent data structure to be used + % Checking to see whether the Scan parameter is identical + if length(datav_new.info.Tilt) > 1 && all(datav_new.info.Tilt == datav_new.info.Tilt(1)) + index = 1:length(datav_new.info.Tilt); + datav_new.info.Tilt = datav_new.info.Tilt(1); + elseif length(datav_new.info.hv) > 1 && all(datav_new.info.hv == datav_new.info.hv(1)) + index = 1:length(datav_new.info.hv); + datav_new.info.hv = datav_new.info.hv(1); + elseif length(datav_new.info.Tilt) > 1 + index = 1:length(datav_new.info.Tilt); + elseif length(datav_new.info.hv) > 1 + index = 1:length(datav_new.info.hv); + else + index = 1; + end + % Extracting the type of scan that is performed + if length(datav_new.info.Tilt) > 1; dataStr.Type = "Eb(kx,ky)"; + elseif length(datav_new.info.hv) > 1; dataStr.Type = "Eb(kx,kz)"; + elseif length(index) > 1; dataStr.Type = "Eb(k,i)"; + else; dataStr.Type = "Eb(k)"; + end + % Squeezingthe data if the scan parameter is 1 unit + if size(datav_new.value, 1) == 1; datav_new.value = squeeze(datav_new.value); end + + % Assigning all data variables + dataStr.index = index; + dataStr.raw_data = datav_new.value; + dataStr.raw_tht = datav_new.y; + dataStr.raw_eb = datav_new.z; + dataStr.hv = datav_new.info.hv; + dataStr.tltM = datav_new.info.Tilt; + dataStr.thtM = datav_new.info.Theta; + dataStr.Temp = datav_new.info.Temperature_Sample1; + dataStr.meta = datav_new.info; + + % Validity checks on the data variables + if dataStr.index == 1; dataStr.raw_data = permute(dataStr.raw_data, [2 1]); + else; dataStr.raw_data = permute(dataStr.raw_data, [3 2 1]); + end + if size(dataStr.raw_eb, 2) > 1; dataStr.raw_eb = dataStr.raw_eb'; end + if size(dataStr.raw_tht, 1) > 1; dataStr.raw_tht = dataStr.raw_tht'; end + if size(dataStr.tltM, 1) > 1; dataStr.tltM = dataStr.tltM'; end + if size(dataStr.hv, 1) > 1; dataStr.hv = dataStr.hv'; end + +%% 2 - Reading in the .mat data that has been processed +elseif string(FileName(end-3:end)) == ".mat" + arpes_data = load(char(string(PathName) + string(FileName))); + dataStr = arpes_data.dataStr; + if isstruct(dataStr) && isfield(dataStr, 'FileName') + dataStr.FileName = FileName(1:end-4); + end +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/save_adress_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/save_adress_data.m new file mode 100644 index 0000000..381abe6 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F006 - data saveloaders/save_adress_data.m @@ -0,0 +1,44 @@ +function save_adress_data(dataStr, SaveFullName) +% save_adress_data(dataStr, SaveFullName, isoslice_args) +% This function save the ARPES data that has been processed using the +% PESTools package. The function saves the data as a MATLAB structure +% file, which can be loaded back in at any point of the processing / +% analysis stage. This function should only be used to save a single +% MATLAB structure (as a .mat file). +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - dataStr: MATLAB data structure containing all the ADRESS data. +% - SaveFullName: (if empty, it is prompted) string or char of the full path + filename to be saved. +% - isoslice_args: (if empty, it is ignored) 1x4 cell of {scanIndex, isoType, isoWin, remap} for quickly plotting a snapshot of the data. +% +% OUT: (none, only the file is saved) + +%% Default parameters +if nargin < 2; SaveFullName = ''; end +if isempty(SaveFullName); SaveFullName = ''; end +% -- Extract the initial file name +if isfield(dataStr, 'FileName'); FileName = dataStr.FileName; +else; FileName = ''; +end +%% 1 - User defined FileName and Path for the processed data +if isempty(SaveFullName) + filter = {'*.mat'}; + [save_filename, save_filepath] = uiputfile(filter, 'Save the data...', FileName); + save_fullfile = char(string(save_filepath) + string(save_filename)); + % - If Cancel is pressed, then return nothing + if isequal(save_filepath,0) || isequal(save_filename,0); return; end +else + save_fullfile = char(string(SaveFullName) + ".mat"); +end + +%% 2 - Executing the saving of the data +% wbar = waitbar(0.5,'Saving...'); +save(char(save_fullfile), 'dataStr', '-v7.3'); +disp('-> saved data : '); display(dataStr); +% close(wbar); + +%% Close wait-bar +% waitbar(1,'Save complete!'); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/SumScanMax.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/SumScanMax.m new file mode 100644 index 0000000..8969acf --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/SumScanMax.m @@ -0,0 +1,18 @@ +function OffsE = SumScanMax(Energy, Data) + +%% - 1 - Extracting the maximum positions +OffsE = []; +figure(); hold on; +for i = 1:size(Data,3) + % -- + dat = squeeze(Data(:,:,i)); + dat = sum(dat, 2); + dat = dat - min(dat(:)); + dat = dat ./ max(dat(:)); + [~, max_indx] = max(dat(:)); + OffsE(i) = Energy(max_indx); + DataMax = 0; + plot(Energy, dat, '-'); +end + +end diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/align_energy.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/align_energy.m new file mode 100644 index 0000000..e5f7725 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/align_energy.m @@ -0,0 +1,315 @@ +function [dataStr, dataStr_ref] = align_energy(dataStr, align_args, dataStr_ref, plot_result) +% [dataStr, dataStr_ref] = align_energy(dataStr, align_args, dataStr_ref, plot_result) +% - #1 - FIRST STEP IN PROCESSING ARPES DATA +% This is a function that will align the 'dataStr' ARPES data-structure +% to the Fermi-level, a peak, or reference VB or CB state. The energy +% alignment is done using various approaches that the user can select from, +% either using the 'dataStr' or a reference 'dataStr_ref' data file. (1) +% The 'align2ref' argument aligns to some peak or edge reference, (2) +% 'fit2ef' fits directly to the FDD edge of a reference, (3) 'fit2peak' +% fits directly to some peak feature. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - [EAlign, EF, Fail] = AlignEF(Data, ECorr [,eWin] [,dEWin] [,dESmooth] [,feat]); +% +% IN: +% - dataStr: data structure of the ARPES data. +% - align_args: {1×6} cell of {Type,Scans,eWin, dEWin, dESmooth, feat}. +% Type: "global" / "AlignEF" (same as "AlignEF") +% "align2ref" +% "align2ref-perchannel" +% "fit2ef" || "fit2ef-95%" (default 95% window size) +% "fit2ef-5%" +% "fit2ef-10%" +% "fit2ef-25%" +% "fit2ef-50%" +% "fit2ef-75%" +% "fit2peak" || "fit2peak-95%" (default 95% window size) +% "fit2peak-5%" +% "fit2peak-10%" +% "fit2peak-25%" +% "fit2peak-50%" +% "fit2peak-75%" +% "global shift via scan" +% "scans" +% "none" +% Scans: for "global" or "ref" it is empty []. For "scans", it defines the scan indices to perform alignment on. +% eWin: approximate EF position. Can be a single, constant value. If a vector, it linear interpolates estimates between [firstEF, endEF]. +% dEWin: can be empty []. Single, constant value that defines the width of the EF. +% dESmooth: can be empty []. Single, constant value that defines Gaussian pre-smoothing energy width. +% feat: either 'edge' or 'peak'. defines the feature to align as a 'peak' instead of the default Fermi 'edge'. +% - dataStr_ref: reference data structure used for Eb alignment. +% - plot_result: if 1, will plot figure of the alignment, otherwise it wont. +% +% OUT: +% dataStr - MATLAB data structure with new additional fields below; +% - .meta.align_args: {1×6} cell of input arguments of alignment. +% - .(eb_shifts): cell array that contains all of the Eb shifts applied to this data. +% - .(eb_ref_file): cell array that contains the name of Eb reference files used. +% - .(eb): aligned 2D or 3D array of energy. +% - .(tht): aligned 2D or 3D array of theta. +% dataStr_ref - MATLAB reference data structure with new additional fields below; +% - .meta.align_args: {1×6} cell of input arguments of alignment. +% - .(eb_shifts): cell array that contains all of the Eb shifts applied to this data. +% - .(raw_eb): aligned 2D array of energy. + +%% Default parameters +if nargin < 4; plot_result = 0; end +if nargin < 3; dataStr_ref = dataStr; end +if nargin < 2; align_args = {"global", [], 0, [], [], 'edge'}; end +if isempty(align_args); align_args = {"global", [], 0, [], [], 'edge'}; end +if isempty(dataStr_ref); dataStr_ref = dataStr; end +if isempty(plot_result); plot_result = 0; end +% - Extracting the fields to be used with most recent processing +[xField, yField, ~, dField] = find_data_fields(dataStr); +[xField_ref, yField_ref, ~, dField_ref] = find_data_fields(dataStr_ref); +% - Constants +eb_ref_file = dataStr_ref.FileName; +%% Validity checks on the input parameters +if length(align_args) ~= 6 + error('error: align_args is not a {1x6} cell - make sure you defined the align arguments correctly.'); +else + align_args{1} = lower(string(align_args{1})); + if isempty(align_args{2}) || ischar(align_args{2}) || isstring(align_args{2}); align_args{2} = []; end + if isempty(align_args{3}) || ischar(align_args{3}) || isstring(align_args{3}); align_args{3} = []; end + if isempty(align_args{4}) || ischar(align_args{4}) || isstring(align_args{4}); align_args{4} = []; end + if isempty(align_args{5}) || ischar(align_args{5}) || isstring(align_args{5}); align_args{5} = []; end + align_args{6} = char(lower(string(align_args{6}))); +end + +%% - 1 - Initialising the alignment parameters +% - Extracting alignment alignType parameters +alignType = align_args{1}; +scan_indxs = align_args{2}; +% - Extracting alignment parameters +eWin = align_args{3}; +dEWin = align_args{4}; +dESmooth = align_args{5}; +feat = align_args{6}; +% - Defining the scan indices over the energy alignment for-loop +if ~strcmpi(alignType,"scans") && ~strcmpi(alignType,"global shift via scan") + scan_indxs = 1:size(dataStr.(dField), 3); +else + minVal = 1; maxVal = size(dataStr.(dField), 3); + % - Checking max/min are not exceeded + scan_indxs(scan_indxs < minVal) = minVal; + scan_indxs(scan_indxs > maxVal) = maxVal; + % - Checking that there are not duplicate numbers + scan_indxs = unique(scan_indxs); +end +% - Defining the values of eWin and interpolating if necessary +if isempty(eWin); eWin = []; +elseif length(eWin) == 1; eWin = ones(length(scan_indxs)) .* eWin; +elseif length(eWin) > 1; eWin = linspace(eWin(1), eWin(2), length(scan_indxs)); +end + +%% - 2 - Executing binding energy alignment over all scans +% - Checking the align type is valid +if strcmpi(alignType,"global") || strcmpi(alignType,"AlignEF") ||strcmpi(alignType,"global shift via scan") || strcmpi(alignType,"scans")... + || strcmpi(alignType,"align2ref") || strcmpi(alignType,"align2ref-perchannel")... + || strcmpi(alignType,"fit2ef") || strcmpi(alignType,"fit2ef-5%") || strcmpi(alignType,"fit2ef-10%") || strcmpi(alignType,"fit2ef-25%")... + || strcmpi(alignType,"fit2ef-50%") || strcmpi(alignType,"fit2ef-75%") || strcmpi(alignType,"fit2ef-95%")... + || strcmpi(alignType,"fit2peak") || strcmpi(alignType,"fit2peak-5%") || strcmpi(alignType,"fit2peak-10%") || strcmpi(alignType,"fit2peak-25%")... + || strcmpi(alignType,"fit2peak-50%") || strcmpi(alignType,"fit2peak-75%") || strcmpi(alignType,"fit2peak-95%")... + || strcmpi(alignType,"none") +else + error('Error: Align type not recognised.'); +end + +%% - 3.1 - EXECUTING GLOBAL ENERGY ALIGNMENTS (filing through all scan indices) +if strcmpi(alignType,"global") || strcmpi(alignType,"AlignEF")... + || strcmpi(alignType,"align2ref") || strcmpi(alignType,"align2ref-perchannel")... + || strcmpi(alignType,"fit2ef") || strcmpi(alignType,"fit2ef-5%") || strcmpi(alignType,"fit2ef-10%") || strcmpi(alignType,"fit2ef-25%") || strcmpi(alignType,"fit2ef-50%") || strcmpi(alignType,"fit2ef-75%") || strcmpi(alignType,"fit2ef-95%")... + || strcmpi(alignType,"fit2peak") || strcmpi(alignType,"fit2peak-5%") || strcmpi(alignType,"fit2peak-10%") || strcmpi(alignType,"fit2peak-25%") || strcmpi(alignType,"fit2peak-50%") || strcmpi(alignType,"fit2peak-75%") || strcmpi(alignType,"fit2peak-95%") + % - Initialising variables + eb_shift_mat = []; + aligned_energy = []; + eWin_i = []; + % - Iterating through all scan indices + for i = scan_indxs + % -- For a single value of eWin to be used + if isempty(eWin) || length(eWin) == 1; eWin_i = eWin; + % -- For an eWin value at each scan between eWin(1) -> eWin(2) + else; eWin_i = eWin(i); + end + + % -- (A) IF ALIGNING GLOBALLY TO THE ARPES DATA DIRECTLY + if strcmpi(alignType,"global") || strcmpi(alignType,"AlignEF") + % --- If the alignment was previously performed, apply again + if string(yField) == "eb"; [~, eb_shift, ~] = AlignEF(dataStr.(dField)(:,:,i), dataStr.eb(:,1,i), eWin_i, dEWin, dESmooth, feat); + % --- If no alignment has been performed, do it for the first time + elseif string(yField) == "raw_eb"; [~, eb_shift, ~] = AlignEF(dataStr.(dField)(:,:,i), dataStr.raw_eb, eWin_i, dEWin, dESmooth, feat); + end + + % -- (B) IF ALIGNING GLOBALLY TO A REFERENCE DATA-SET + elseif strcmpi(alignType,"align2ref") + % --- If the scan index exceeds the reference data, cap it to the end + if i > size(dataStr_ref.(dField_ref), 3) + [~, eb_shift, ~] = AlignEF(dataStr_ref.(dField_ref)(:,:,end), dataStr_ref.(yField_ref), eWin_i, dEWin, dESmooth, feat); + else + [~, eb_shift, ~] = AlignEF(dataStr_ref.(dField_ref)(:,:,i), dataStr_ref.(yField_ref), eWin_i, dEWin, dESmooth, feat); + end + + % -- (C) IF ALIGNING GLOBALLY TO A REFERENCE DATA-SET, TO EACH INDIVIDUAL X-CHANNEL + elseif strcmpi(alignType,"align2ref-perchannel") + % --- Iterating through all the angle (or kx) channels + for ikx = 1:size(dataStr_ref.(dField_ref), 2) + % ---- Executing energy alignment for each channel + if i > size(dataStr_ref.(dField_ref), 3) + [~, eb_shift(ikx), ~] = AlignEF(dataStr_ref.(dField_ref)(:,ikx,end), dataStr_ref.(yField_ref), eWin_i, dEWin, dESmooth, feat); + else + [~, eb_shift(ikx), ~] = AlignEF(dataStr_ref.(dField_ref)(:,ikx,i), dataStr_ref.(yField_ref), eWin_i, dEWin, dESmooth, feat); + end + end + + % -- (D) IF FITTING TO THE FERMI-EDGE OF A REFERENCE DATA-SET + elseif contains(alignType,"fit2ef") + % --- Initialising variables + if strcmpi(alignType,"fit2ef") || strcmpi(alignType,"fit2ef-95%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.95*abs(range(dataStr_ref.(xField_ref)(:))); + elseif strcmpi(alignType,"fit2ef-25%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.25*abs(range(dataStr_ref.(xField_ref)(:))); + elseif strcmpi(alignType,"fit2ef-50%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.50*abs(range(dataStr_ref.(xField_ref)(:))); + elseif strcmpi(alignType,"fit2ef-75%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.75*abs(range(dataStr_ref.(xField_ref)(:))); + elseif strcmpi(alignType,"fit2ef-5%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.05*abs(range(dataStr_ref.(xField_ref)(:))); + elseif strcmpi(alignType,"fit2ef-10%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.10*abs(range(dataStr_ref.(xField_ref)(:))); + end + % ---- Executing energy alignment by fitting to FDD + if i > size(dataStr_ref.raw_data, 3) + [~,eb_shift] = fdd2fit_solver(dataStr_ref.(xField_ref), dataStr_ref.(yField_ref), dataStr_ref.(dField_ref)(:,:,end), angleWin, eWin_i+dEWin.*[-1,1], [], [], [], plot_result); + else + [~,eb_shift] = fdd2fit_solver(dataStr_ref.(xField_ref), dataStr_ref.(yField_ref), dataStr_ref.(dField_ref)(:,:,i), angleWin, eWin_i+dEWin.*[-1,1], [], [], [], plot_result); + end + + % -- (E) IF ALIGNING TO A PEAK FEATURE OF A REFERENCE DATA-SET + elseif contains(alignType,"fit2peak") + % --- Initialising variables + if strcmpi(alignType,"fit2peak") || strcmpi(alignType,"fit2peak-95%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.95*abs(range(dataStr_ref.(xField_ref)(:))); + elseif strcmpi(alignType,"fit2peak-25%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.25*abs(range(dataStr_ref.(xField_ref)(:))); + elseif strcmpi(alignType,"fit2peak-50%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.50*abs(range(dataStr_ref.(xField_ref)(:))); + elseif strcmpi(alignType,"fit2peak-75%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.75*abs(range(dataStr_ref.(xField_ref)(:))); + elseif strcmpi(alignType,"fit2peak-5%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.05*abs(range(dataStr_ref.(xField_ref)(:))); + elseif strcmpi(alignType,"fit2peak-10%"); angleWin = mean(dataStr_ref.(xField_ref)(:)) + [-1,1].*0.10*abs(range(dataStr_ref.(xField_ref)(:))); + end + % --- Extracting the peak position + [pesStr, ~] = pes_extract_data(dataStr_ref, {angleWin,1}, 0); + if isempty(eWin); [xVal, ~] = find_peak_loc(pesStr.xdat, pesStr.ydat, [], "spline", plot_result); + elseif isempty(dEWin); [xVal, ~] = find_peak_loc(pesStr.xdat, pesStr.ydat, [], "spline", plot_result); + else; [xVal, ~] = find_peak_loc(pesStr.xdat, pesStr.ydat, eWin + dEWin.*[-1, 1], "spline", plot_result); + end + eb_shift = xVal - eWin; + end + % - Appending all the aligned data vectors into a matrix + if isfield(dataStr, 'eb'); aligned_energy(:,:,i) = dataStr.eb(:,:,i) - eb_shift; + else; aligned_energy(:,1,i) = dataStr.raw_eb - eb_shift; + end + aligned_energy_ref(:,1,i) = dataStr_ref.raw_eb - eb_shift; + % - Appending all the energy shifts into a matrix + eb_shift_mat(i,:) = [i, eb_shift]; + end + % Assigning final variables to the data structure + EB = aligned_energy; + EB_REF = aligned_energy_ref; +end + +%% - 3.2 - EXECUTING SCAN SELECTED ENERGY ALIGNMENTS (filing through selected scan indices) +if strcmpi(alignType,"global shift via scan") || strcmpi(alignType,"scans") + if ~isfield(dataStr, 'eb'); error('Must run global alignment first.'); end + % (A) IF ALIGNING TO A SCAN INDEX AND THEN SHIFTING GLOBALLY FOR ALL SCANS BY A CONSTANT + if strcmpi(alignType,"global shift via scan") + % - Extracting the scan to make the alignment to + ebindx = scan_indxs(1); + % - Eb alignment over a single defined scan + [~, eb_shift, ~] = AlignEF(dataStr.(dField)(:,:,ebindx), dataStr.eb(:,1,ebindx), eWin(1), dEWin, dESmooth, feat); + % -- Applying the energy shift to the data globally + EB = dataStr.eb - eb_shift; + EB_REF = dataStr_ref.raw_eb - eb_shift; + % -- Appending all the energy shifts into a cell + eb_shift_mat = [ebindx, eb_shift]; + % (B) IF ALIGNING ONLY CERTAIN SCAN INDICES + elseif strcmpi(alignType,"scans") + ebindx = 0; + eWin_i = []; + for i = scan_indxs + ebindx = ebindx + 1; + % - For a single value of eWin to be used + if isempty(eWin) || length(eWin) == 1; eWin_i = eWin; + % - For an eWin value at each scan between eWin(1) -> eWin(2) + else; eWin_i = eWin(ebindx); + end + % - Eb alignment over defined scans + [~, eb_shift, ~] = AlignEF(dataStr.(dField)(:,:,i), dataStr.eb(:,1,i), eWin_i, dEWin, dESmooth, feat); + % -- Applying the energy shift to the data + EB(:,:,i) = dataStr.eb(:,:,i) - eb_shift; + % -- Appending all the energy shifts into a matrix + eb_shift_mat(i,:) = [i, eb_shift]; + end + EB_REF = dataStr_ref.raw_eb; + end +end + +%% - 3 - Remapping matrices into 2D or 3D consistent forms +% - 3.1 Remapping to 2D +% - Remapping the EB domain to be 2D +if size(EB,1) == 1 || size(EB,2) == 1; EB=repmat(EB,[1, size(dataStr.(dField),2)]); end +% - 3.2 Remapping to 3D +% - Remapping the EB domain to be 3D +if size(EB, 3) == 1; EB = repmat(EB,[1, 1, size(dataStr.(dField),3)]); end +% - 3.3 Remap the tht matrix +if ~isfield(dataStr, 'tht') + THT = dataStr.raw_tht; + % - 3.1 Remapping to 2D + % -- Remapping the THT / K domain to be 2D + if size(THT,1) == 1 || size(THT,2) == 1; THT=repmat(THT,[size(dataStr.(dField),1), 1]); end + % - 3.2 Remapping to 3D + % -- Remapping the THT / K domain to be 3D + if size(THT, 3) == 1; THT = repmat(THT,[1, 1, size(dataStr.(dField),3)]); end +elseif size(dataStr.tht, 1) == 1 + THT = dataStr.raw_tht; + % - 3.1 Remapping to 2D + % -- Remapping the THT / K domain to be 2D + if size(THT,1) == 1 || size(THT,2) == 1; THT=repmat(THT,[size(dataStr.(dField),1), 1]); end + % - 3.2 Remapping to 3D + % -- Remapping the THT / K domain to be 3D + if size(THT, 3) == 1; THT = repmat(THT,[1, 1, size(dataStr.(dField),3)]); end +else; THT = dataStr.tht; +end + +%% 4 - Appending the new data to the MATLAB structure +% - ARPES data +if ~isfield(dataStr.meta, 'align_args'); dataStr.meta.align_args = {}; end +dataStr.meta.align_args{end+1} = align_args; +if ~isfield(dataStr, 'eb_shifts'); dataStr.eb_shifts = {}; end +dataStr.eb_shifts{end+1} = eb_shift_mat; +if ~isfield(dataStr, 'eb_ref_file'); dataStr.eb_ref_file = {}; end +dataStr.eb_ref_file{end+1} = eb_ref_file; +dataStr.eb = EB; +dataStr.tht = THT; +% - Reference ARPES data +if ~isfield(dataStr_ref.meta, 'align_args'); dataStr_ref.meta.align_args = {}; end +dataStr_ref.meta.align_args{end+1} = align_args; +if ~isfield(dataStr_ref, 'eb_shifts'); dataStr_ref.eb_shifts = {}; end +dataStr_ref.eb_shifts{end+1} = eb_shift_mat; +dataStr_ref.raw_eb = EB_REF; + +%% -- For Debugging +if plot_result == 1 && ~contains(alignType,"fit2ef") + fig = figure(); + fig.Position(3) = 2*450; + fig.Position(4) = 350; + subplot(121); hold on; + ImData(dataStr_ref.raw_tht, dataStr_ref.raw_eb, dataStr_ref.raw_data(:,:,scan_indxs(1))); + line([-1e3, 1e3], [0, 0], 'color', 'c', 'linewidth', 1.5, 'linestyle', '-'); + line([-1e3, 1e3], [0, 0] + eb_shift_mat(2), 'color', 'c', 'linewidth', 0.5, 'linestyle', '--'); + img_props([], "tht"); + axis([min(dataStr_ref.raw_tht(:)), max(dataStr_ref.raw_tht(:)), min(dataStr_ref.raw_eb(:)), max(dataStr_ref.raw_eb(:))]); + colorbar; title('align_energy(): Reference', 'Interpreter', 'none'); + subplot(122); hold on; + ImData(dataStr.tht(:,:,scan_indxs(1)), dataStr.eb(:,:,scan_indxs(1)), dataStr.(dField)(:,:,scan_indxs(1))); + line([-1e3, 1e3], [0, 0], 'color', 'c', 'linewidth', 1.5, 'linestyle', '-'); + line([-1e3, 1e3], [0, 0] + eb_shift_mat(2), 'color', 'c', 'linewidth', 0.5, 'linestyle', '--'); + img_props([], "tht"); + axis([min(dataStr.tht(:)), max(dataStr.tht(:)), min(dataStr.eb(:)), max(dataStr.eb(:))]); + colorbar; title('align_energy(): Data', 'Interpreter', 'none'); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/bgrd_subtr_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/bgrd_subtr_data.m new file mode 100644 index 0000000..1d2980a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/bgrd_subtr_data.m @@ -0,0 +1,182 @@ +function dataStr = bgrd_subtr_data(dataStr, bsub_args, plot_result) +% dataStr = bgrd_subtr_data(dataStr, bsub_args, plot_result) +% - #2 - SECOND STEP IN PROCESSING ARPES DATA +% This is a function that will background subtract / normalise the ARPES data using several +% different approaches over a given window. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - DataC=SetContrast(Data,minFrac,maxFrac [,gamma]); +% +% IN: +% - dataStr: data structure of the ARPES data. +% - bsub_args: {1×5} cell of {bgrdType,bgrdWin,bgrdScale,bgrdSmooth,normType}. +% bgrdType: "AngleInt" +% "AngleInt-clip" +% "AngleInt-mean" +% "AngleInt-pctile" +% "AngleInt-mean-moving" +% "AngleInt-pctile-moving" +% "none" +% bgrdWin: EDC angle range to +% integrate over to extract ISubtr. +% bgrdScale: scale coefficient to subtract (Data - intScale * ISubtr). +% bgrdSmooth: single, constant value that determine presmoothing of data to extract background. +% normType: "max" +% "max-each" +% "mean-each" +% "none" +% - plot_result: if 1, will plot figure of the alignment, otherwise it wont. +% +% OUT: +% dataStr - MATLAB data structure with new additional fields below; +% - .meta.bsub_args: {1×5} cell of input arguments. +% - .(data): 2D or 3D array of the normalised data. + +%% Default parameters +if nargin < 3; plot_result = 0; end +if nargin < 2; bsub_args = {"AngleInt-clip", [], 0.25, 50, "max-each"}; end +if isempty(bsub_args); bsub_args = {"AngleInt-clip", [], 0.25, 50, "max-each"}; end +if isempty(plot_result); plot_result = 0; end +% - Extracting the fields to be used with most recent processing +[xField, yField, ~, dField] = find_data_fields(dataStr); +% - Do not compound background subtraction, so force dField to be = 'raw_data' +% dField = 'raw_data'; +%% Validity checks on the input parameters +if length(bsub_args) ~= 5 + error('error: bsub_args is not a {1x5} cell - make sure you defined the arguments correctly.'); +else + bsub_args{1} = lower(string(bsub_args{1})); + if isempty(bsub_args{2}) || ischar(bsub_args{2}) || isstring(bsub_args{2}); bsub_args{2} = mean(dataStr.(xField)(:)) + [-1,1].*0.95.*range(dataStr.(xField)(:)); end + if isempty(bsub_args{3}) || ischar(bsub_args{3}) || isstring(bsub_args{3}); bsub_args{3} = 0.25; end + if isempty(bsub_args{4}) || ischar(bsub_args{4}) || isstring(bsub_args{4}); bsub_args{4} = 50; end + bsub_args{5} = char(lower(string(bsub_args{5}))); +end + +%% - 1 - Initialising the normalisation parameters +% - Extracting normalisation parameters +bgrdType = bsub_args{1}; +bgrdWin = bsub_args{2}; +bgrdScale = bsub_args{3}; +bgrdSmooth = bsub_args{4}; +normType = bsub_args{5}; +% - Extracting the window of integration +Win = sort([bgrdWin(1), bgrdWin(2)]); + +%% - 2 - Background subtraction of the data over all scans +% - Checking the background type is valid +if strcmpi(bgrdType,"AngleInt") || strcmpi(bgrdType,"AngleInt-clip")... + || strcmpi(bgrdType,"AngleInt-mean") || strcmpi(bgrdType,"AngleInt-pctile")... + || strcmpi(bgrdType,"AngleInt-mean-moving") || strcmpi(bgrdType,"AngleInt-pctile-moving")... + || strcmpi(bgrdType,"none") +else + error('Error: bgrdType not recognised.'); +end +% - Checking the normalisation type is valid +if strcmpi(normType,"max") || strcmpi(normType,"max-each") || strcmpi(normType,"mean-each")... + || strcmpi(normType,"none")... + || strcmpi(normType,"sum-each") +else; error('Error: normType not recognised.'); +end +norm_data = []; +for i = 1:size(dataStr.(dField), 3) + %% 2.1 - Executing background subtraction + % (A) - Angle-integrated subtraction (subtracts angle-integrated spectrum) + if strcmpi(bgrdType,"AngleInt") + ISubtr = IntAngle(dataStr.(dField)(:,:,i), dataStr.(xField)(:,:,i), dataStr.(yField)(:,:,i), Win); + % - HWHM adjusted to suppress uneven sensitivity of the CCD channels + ISubtr = Gaco2(ISubtr, 0, bgrdSmooth); + % - Subtracting background + norm_data(:,:,i) = dataStr.(dField)(:,:,i) - bgrdScale * ISubtr; + % (B) - Angle-integrated subtraction (anything < 0 is equal to 0) + elseif strcmpi(bgrdType,"AngleInt-clip") + ISubtr = IntAngle(dataStr.(dField)(:,:,i), dataStr.(xField)(:,:,i), dataStr.(yField)(:,:,i), Win); + % - HWHM adjusted to suppress uneven sensitivity of the CCD channels + ISubtr = Gaco2(ISubtr, 0, bgrdSmooth); + % - Subtracting background + norm_data(:,:,i) = dataStr.(dField)(:,:,i) - bgrdScale * ISubtr; + % - Clipping all negativ values to zero + norm_data(norm_data < 0) = 0; + % (C) - Subtracting the mean value of the angle-integrated spectrum + elseif strcmpi(bgrdType,"AngleInt-mean") + ISubtr = IntAngle(dataStr.(dField)(:,:,i), dataStr.(xField)(:,:,i), dataStr.(yField)(:,:,i), Win); + % - Finding the mean value of the EDC + ISubtr = mean(ISubtr(:)); + % - Subtracting background + norm_data(:,:,i) = dataStr.(dField)(:,:,i) - bgrdScale * ISubtr; + % - Clipping all negative values to zero + norm_data(norm_data < 0) = 0; + % (D) - Subtracting a percentile value of the angle-integrated spectrum + elseif strcmpi(bgrdType,"AngleInt-pctile") + ISubtr = IntAngle(dataStr.(dField)(:,:,i), dataStr.(xField)(:,:,i), dataStr.(yField)(:,:,i), Win); + % - Finding the mean value of the EDC + ISubtr = mean(ISubtr(:)) + bgrdScale*range(ISubtr(:)); + % - Subtracting background + norm_data(:,:,i) = dataStr.(dField)(:,:,i) - ISubtr; + % - Clipping all negative values to zero + norm_data(norm_data < 0) = 0; + % (E) - Subtracting the mean value of all EDCs moving from left to right + elseif strcmpi(bgrdType,"AngleInt-mean-moving") + % - Filing through all EDCs to subtract the mean value of each EDC + for jj = 1:size(dataStr.(dField), 2) + ISubtr = mean(dataStr.(dField)(:,jj,i)); + norm_data(:,jj,i) = dataStr.(dField)(:,jj,i) - bgrdScale * ISubtr; + end + % - Clipping all negative evalues to zero + norm_data(norm_data < 0) = 0; + % (F) - Subtracting the percentile value of all EDCs moving from left to right + elseif strcmpi(bgrdType,"AngleInt-pctile-moving") + % - Filing through all EDCs to subtract the mean value of each EDC + for jj = 1:size(dataStr.(dField), 2) + ISubtr = mean(dataStr.(dField)(:,jj,i)) + bgrdScale*range(dataStr.(dField)(:,jj,i)); + norm_data(:,jj,i) = dataStr.(dField)(:,jj,i) - bgrdScale * ISubtr; + end + % - Clipping all negative values to zero + norm_data(norm_data < 0) = 0; + % (G) - No background subtraction + elseif bgrdType == "none" + ISubtr = 0; + norm_data(:,:,i) = dataStr.(dField)(:,:,i) - bgrdScale * ISubtr; + end + %% 2.2 - Renormalising the intensity + if strcmpi(normType,"max-each"); norm_data(:,:,i) = norm_data(:,:,i) / max(max(norm_data(:,:,i))); + elseif strcmpi(normType,"mean-each"); norm_data(:,:,i) = norm_data(:,:,i) / mean(mean(norm_data(:,:,i))); + elseif strcmpi(normType,"none"); norm_data(:,:,i) = norm_data(:,:,i) / 1; + elseif strcmpi(normType,"sum-each"); norm_data(:,:,i) = norm_data(:,:,i) / sum(sum(norm_data(:,:,i))); + end +end +% - Forcing maximum value across all scans to be unity if required +if strcmpi(normType,"max") || strcmpi(normType,"max-each") || strcmpi(normType,"sum-each") + norm_data = norm_data / max(norm_data(:)); +end + +%% 3 - Assigning to a data structure +dataStr.data = norm_data; +dataStr.data = dataStr.data - min(dataStr.data(:)); +% - Appending new data to the data object +dataStr.meta.bsub_args = bsub_args; +% - Setting NaN values to zero +dataStr.data(isnan(dataStr.data)) = 0; +% - Setting the contrast +for i = 1:size(dataStr.(dField), 3) + dataStr.data(:,:,i) = SetContrast(dataStr.data(:,:,i),0.05, 1.); +end + +%% -- For Debugging +if plot_result == 1 + fig = figure(); + fig.Position(3) = 2*450; + fig.Position(4) = 350; + subplot(121); hold on; + ImData(dataStr.tht(:,:,1), dataStr.eb(:,:,1), dataStr.raw_data(:,:,1)); + img_props([], "tht"); + axis([min(dataStr.raw_tht(:)), max(dataStr.raw_tht(:)), min(dataStr.raw_eb(:)), max(dataStr.raw_eb(:))]); + colorbar; title('bgrd_subtr_data(): Raw', 'Interpreter', 'none'); + subplot(122); hold on; + ImData(dataStr.(xField)(:,:,1), dataStr.(yField)(:,:,1), dataStr.data(:,:,1)); + img_props([], "tht"); + axis([min(dataStr.(xField)(:)), max(dataStr.(xField)(:)), min(dataStr.(yField)(:)), max(dataStr.(yField)(:))]); + colorbar; title('bgrd_subtr_data(): After', 'Interpreter', 'none'); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/bgrd_subtr_isoe.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/bgrd_subtr_isoe.m new file mode 100644 index 0000000..d9e63f0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/bgrd_subtr_isoe.m @@ -0,0 +1,123 @@ +function isoeStr = bgrd_subtr_isoe(isoeStr, bsub_args) +% isoeStr = bgrd_subtr_isoe(isoeStr, bsub_args) +% This function background subtracts isoe ARPES data, given a specific +% window [minKx, maxKx] over which to cut the isoe surface. The entire +% isoe surface is then divided by this region, to normalised the +% background to be uniform across all isoe scans. +% +% REQ. FUNCTIONS: +% - AA = Gaco2(A,hwX,hwY [,hsX] [,hsY]) +% - [XCut,DCut] = Cut(ACorr,ECorr,Data,xMode,Win) +% - DataC=SetContrast(Data,minFrac,maxFrac [,gamma]); +% +% IN: +% - isoeStr: data structure of the sliced Iso-E ARPES data. +% - bsub_args: 1x5 cell of {bgrdType (either "angle/kx-int (fixed edc)", "angle/kx-int (fixed mean)", "angle/kx-int (moving mean)", "none"), +% bgrdWin, bgrdScale, bgrdSmooth, +% normType (either "init max", "final max", "none")}. +% OUT: +% - isoeStr: output data structure after transformation. + +%% Default parameters +if nargin < 2; bsub_args = {"angle/kx-int (fixed mean)", [-0.65, -0.45], 0.25, 50, "none"}; end +if isempty(bsub_args); bsub_args = {"angle/kx-int (fixed mean)", [-0.65, -0.45], 0.25, 50, "none"}; end +% disp('IsoE Background Subtraction...') +% wbar = waitbar(0.5, 'Background Subtracting IsoE data...', 'Name', 'isoe_bgrd_sbtr'); + +%% - 1 - Initialising the normalisation parameters +% - Extracting normalisation parameters +bgrdType = bsub_args{1}; +bgrdWin = bsub_args{2}; +bgrdScale = bsub_args{3}; +bgrdSmooth = bsub_args{4}; +normType = bsub_args{5}; +% - Extracting the window of integration +Win = sort([bgrdWin(1), bgrdWin(2)]); +% - Extracting the initial data maximum +init_max = max(isoeStr.DSlice(:)); + +%% - 2 - Executing background subtraction +% - Extracting the EDC (vertical line profile) of the background +cutType = "EDC"; % Type of cut to make. Either "MDC" (horizontal) or "EDC" (vertical) +cutWin = Win; % Integration window of the cut to be made. +isocut_args = {[], cutType, cutWin}; +[cutStr, ~] = extract_isoCut(isoeStr, isocut_args, 0); +ISubtr = cutStr.DCut; +% (A) - Angle-integrated subtraction (subtracts angle-integrated spectrum) +if bgrdType == "angle/kx-int (fixed edc)" + % - HWHM adjusted to suppress uneven sensitivity of the CCD channels + ISubtr = Gaco2(ISubtr, 0, bgrdSmooth); + % - Subtracting background + isoeStr.DSlice = isoeStr.DSlice - bgrdScale .* ISubtr; + isoeStr.DSlice(isoeStr.DSlice < 0) = 0; + +% (B) - Fixed mean background subtraction (subtracts a fixed mean value over a non-dispersive region) +elseif bgrdType == "angle/kx-int (fixed mean)" + % - Finding the mean value of the EDC + ISubtr = mean(ISubtr(:)); + % - Subtracting background as the mean value of the EDC + isoeStr.DSlice = isoeStr.DSlice - bgrdScale * ISubtr; + isoeStr.DSlice(isoeStr.DSlice < 0) = 0; + +% (C) - Moving mean background subtraction (subtracts a the mean value of all EDCs over whole image) +elseif bgrdType == "angle/kx-int (moving mean)" + % - Filing through all EDCs to subtract the mean value of each EDC + for jj = 1:size(isoeStr.DSlice, 2) + ISubtr = mean(isoeStr.DSlice(:,jj)); + isoeStr.DSlice(:,jj) = isoeStr.DSlice(:,jj) - bgrdScale * ISubtr; + end + isoeStr.DSlice(isoeStr.DSlice < 0) = 0; + +elseif bgrdType == "AngleInt-Norm" + % - HWHM adjusted to suppress uneven sensitivity of the CCD channels + ISubtr = Gaco2(ISubtr, 0, bgrdSmooth); + % - Subtracting background + isoeStr.DSlice = isoeStr.DSlice - bgrdScale .* ISubtr; + isoeStr.DSlice(isoeStr.DSlice < 0) = 0; + ISliceE = isoeStr.DSlice; + ASliceE = isoeStr.XSlice; + % - integral intensity of scans over 90% of angular range + nA=size(ISliceE,2); n1=round(0.05*nA); n2=round(0.95*nA); + ISliceN=ISliceE(:,n1:n2); + ISliceN=sum(ISliceN,2)/(n2-n1+1); + % - normalization + ISliceN=ISliceE./repmat(ISliceN,1,nA); + isoeStr.DSlice = ISliceN; + isoeStr.DSlice(isoeStr.DSlice < 0) = 0; + +% (D) - BEST ONE, NORMALISES INCONSISTENCIES +elseif bgrdType == "Norm" + ISliceE = isoeStr.DSlice; + ASliceE = isoeStr.XSlice; + % - integral intensity of scans over 90% of angular range + nA=size(ISliceE,2); n1=round(0.05*nA); n2=round(0.95*nA); + ISliceN=ISliceE(:,n1:n2); + ISliceN=sum(ISliceN,2)/(n2-n1+1); + % - normalization + ISliceN=ISliceE./repmat(ISliceN,1,nA); + isoeStr.DSlice = ISliceN; + isoeStr.DSlice(isoeStr.DSlice < 0) = 0; +% (E) - No background subtraction +elseif bgrdType == "none" + ISubtr = 0; + isoeStr.DSlice = isoeStr.DSlice - bgrdScale * ISubtr; +end + +%% - 3 - Normalising to a given maximum +final_max = max(isoeStr.DSlice(:)); +% (A) - Normalise to the original maximum +if normType == "init max" + isoeStr.DSlice = (isoeStr.DSlice ./ final_max) .* init_max; +% (B) - Normalise to the current maximum +elseif normType == "final max" + isoeStr.DSlice = (isoeStr.DSlice ./ final_max); +% (C) - No background subtraction +elseif normType == "none" + isoeStr.DSlice = isoeStr.DSlice; +end +% - Setting NaN values to zero +isoeStr.DSlice = isoeStr.DSlice - min(isoeStr.DSlice(:)); +isoeStr.DSlice(isnan(isoeStr.DSlice)) = 0; +%% Close wait-bar +% close(wbar); +end diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/convert_to_k.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/convert_to_k.m new file mode 100644 index 0000000..027452f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/convert_to_k.m @@ -0,0 +1,131 @@ +function dataStr = convert_to_k(dataStr, kconv_args, plot_result) +% dataStr = convert_to_k(dataStr, kconv_args, plot_result) +% - #3 - THIRD STEP IN PROCESSING ARPES DATA +% This is a function that will convert the angles thtA into kx and the +% scan parameters into either ky (for tltM) or kz (for hv). Last updated in +% October 2022, and includes input for new X-ray incidence angle. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - surfNormX = SurfNormX(hv, eB_ref, kx_ref, thtM, thtA_ref) calculates the surface normal angle in the MP. +% - Kxx = Kxx(HV, Eb, thtM, ThtA, surfNormX) calculates k// in the MP. +% - Kyy = Kyy(HV, Eb, thtM, TltM, surfNormX) calculates k// in the MP. +% - Kzz = Kzz(HV, Eb, thtM, ThtA, TltM, v000, surfNormX) calculates kz along the surface normal. +% +% IN: +% - dataStr: data structure of the ARPES data. +% - kconv_args: {1×5} cell of {eB_ref, kx_ref, thtA_ref, v000, incAlpha}. +% eB_ref: single, constant value of the binding energy at the refernece point. +% kx_ref: single, constant value of the wave-vector value at the reference point. +% thtA_ref: single, constant value of the tht angle value at the reference point. +% v000: single, constant value of the inner potential. Tune to make sure spacing of Gamma points is correct. Default is 12.57. +% incAlpha: nominal X-ray incidence angle, for the present geometry equal to 9deg. If omitted, old geometry with 20deg implied. +% - plot_result: if 1, will plot figure of the alignment, otherwise it wont. +% OUT: +% dataStr - MATLAB data structure with new additional fields below; +% - .(surfNormX): double or vector of surface normal vector. +% - .(kx): 2D or 3D array of kx from the Theta angle. +% - .(ky): 2D or 3D array of kx from the Tilt angle. +% - .(kz): 2D or 3D array of kx from the Photon Energy. + +%% Default parameters +if nargin < 3; plot_result = 0; end +if nargin < 2; kconv_args = {0, 0, 0, 12.57, 20}; end +if isempty(kconv_args); kconv_args = {0, 0, 0, 12.57, 20}; end +if isempty(plot_result); plot_result = 0; end +%% Validity checks on the input parameters +if length(kconv_args) ~= 5 + error('error: kconv_args is not a {1x5} cell - make sure you defined the arguments correctly.'); +else + if isempty(kconv_args{1}) || ischar(kconv_args{2}) || isstring(kconv_args{3}); kconv_args{1} = 0; end + if isempty(kconv_args{2}) || ischar(kconv_args{2}) || isstring(kconv_args{2}); kconv_args{2} = 0; end + if isempty(kconv_args{3}) || ischar(kconv_args{3}) || isstring(kconv_args{3}); kconv_args{3} = 0; end + if isempty(kconv_args{4}) || ischar(kconv_args{4}) || isstring(kconv_args{4}); kconv_args{4} = 12.57; end + if isempty(kconv_args{5}) || ischar(kconv_args{5}) || isstring(kconv_args{5}); kconv_args{5} = 20; end +end + +%% - 1 - Initialising the k conversion parameters +dataStr.meta.kconv_args = kconv_args; +% - Extracting conversion parameters +eB_ref = kconv_args{1}; +kx_ref = kconv_args{2}; +thtA_ref = kconv_args{3}; +v000 = kconv_args{4}; +incAlpha = kconv_args{5}; +%% - 2 - Wave-vector conversions over all scans +if isnan(dataStr.tltE); dataStr.tltE = 0; end +% - 2.1 Wave-vector conversions for Eb(k) +if dataStr.Type == "Eb(k)" || dataStr.Type == "Eb(k,i)" + if length(thtA_ref) == 2; thtA_ref = thtA_ref(1); end + if length(dataStr.index) == 1 + dataStr.surfNormX = SurfNormX(dataStr.hv, eB_ref, kx_ref, dataStr.thtM, thtA_ref, incAlpha); + dataStr.kx = Kxx(dataStr.hv, dataStr.eb, dataStr.thtM, dataStr.tht, dataStr.surfNormX, incAlpha); + dataStr.ky = Kyy(dataStr.hv, dataStr.eb, dataStr.tht, dataStr.thtM, dataStr.tltM + dataStr.tltE, dataStr.surfNormX, incAlpha); + dataStr.kz = Kzz(dataStr.hv, dataStr.eb, dataStr.thtM, dataStr.tht, dataStr.tltM + dataStr.tltE, v000, dataStr.surfNormX, incAlpha); + else + for i = 1:length(dataStr.index) + dataStr.surfNormX = SurfNormX(dataStr.hv, eB_ref, kx_ref, dataStr.thtM, thtA_ref, incAlpha); + dataStr.kx(:,:,i) = Kxx(dataStr.hv, dataStr.eb(:,:,i), dataStr.thtM, dataStr.tht(:,:,i), dataStr.surfNormX, incAlpha); + dataStr.ky = Kyy(dataStr.hv, dataStr.eb(:,:,i), dataStr.tht(:,:,i), dataStr.thtM, dataStr.tltM + dataStr.tltE, dataStr.surfNormX, incAlpha); + dataStr.kz = Kzz(dataStr.hv, dataStr.eb(:,:,i), dataStr.thtM, dataStr.tht(:,:,i), dataStr.tltM + dataStr.tltE, v000, dataStr.surfNormX, incAlpha); + end + end + % Finding the mean value of ky and kz + dataStr.ky = mean(dataStr.ky(:)); + dataStr.kz = mean(dataStr.kz(:)); +% - 2.2 Wave-vector conversions for Eb(kx,ky) +elseif dataStr.Type == "Eb(kx,ky)" + if length(thtA_ref) == 2; thtA_ref = linspace(thtA_ref(1), thtA_ref(2), size(dataStr.tltM, 2)); + else; thtA_ref = ones(size(dataStr.tltM, 2))*thtA_ref(1); + end + % Mechanical Tilt Map + if size(dataStr.tltM, 2) > 1 + for i = 1:size(dataStr.tltM, 2) + dataStr.surfNormX(i) = SurfNormX(dataStr.hv, eB_ref, kx_ref, dataStr.thtM, thtA_ref(i), incAlpha); + dataStr.kx(:,:,i) = Kxx(dataStr.hv, dataStr.eb(:,:,i), dataStr.thtM, dataStr.tht(:,:,i), dataStr.surfNormX(i), incAlpha); + dataStr.ky(:,:,i) = Kyy(dataStr.hv, dataStr.eb(:,:,i), dataStr.tht(:,:,i), dataStr.thtM, dataStr.tltM(i) + dataStr.tltE, dataStr.surfNormX(i), incAlpha); + dataStr.kz(:,:,i) = Kzz(dataStr.hv, dataStr.eb(:,:,i), dataStr.thtM, dataStr.tht(:,:,i), dataStr.tltM(i) + dataStr.tltE, v000, dataStr.surfNormX(i), incAlpha); + end + % Electrostatic Tilt Map + else + for i = 1:size(dataStr.tltE, 2) + dataStr.surfNormX(i) = SurfNormX(dataStr.hv, eB_ref, kx_ref, dataStr.thtM, thtA_ref(i), incAlpha); + dataStr.kx(:,:,i) = Kxx(dataStr.hv, dataStr.eb(:,:,i), dataStr.thtM, dataStr.tht(:,:,i), dataStr.surfNormX(i), incAlpha); + dataStr.ky(:,:,i) = Kyy(dataStr.hv, dataStr.eb(:,:,i), dataStr.tht(:,:,i), dataStr.thtM, dataStr.tltM + dataStr.tltE(i), dataStr.surfNormX(i), incAlpha); + dataStr.kz(:,:,i) = Kzz(dataStr.hv, dataStr.eb(:,:,i), dataStr.thtM, dataStr.tht(:,:,i), dataStr.tltM + dataStr.tltE(i), v000, dataStr.surfNormX(i), incAlpha); + end + end + +% - 2.3 Wave-vector conversions for Eb(kx,kz) +elseif dataStr.Type == "Eb(kx,kz)" + if length(thtA_ref) == 2; thtA_ref = linspace(thtA_ref(1), thtA_ref(2), size(dataStr.hv, 2)); + else; thtA_ref = ones(size(dataStr.hv, 2))*thtA_ref(1); + end + for i = 1:size(dataStr.hv, 2) + dataStr.surfNormX(i) = SurfNormX(dataStr.hv(i), eB_ref, kx_ref, dataStr.thtM, thtA_ref(i), incAlpha); + dataStr.kx(:,:,i) = Kxx(dataStr.hv(i), dataStr.eb(:,:,i), dataStr.thtM, dataStr.tht(:,:,i), dataStr.surfNormX(i), incAlpha); + dataStr.ky(:,:,i) = Kyy(dataStr.hv(i), dataStr.eb(:,:,i), dataStr.tht(:,:,i), dataStr.thtM, dataStr.tltM + dataStr.tltE, dataStr.surfNormX(i), incAlpha); + dataStr.kz(:,:,i) = Kzz(dataStr.hv(i), dataStr.eb(:,:,i), dataStr.thtM, dataStr.tht(:,:,i), dataStr.tltM + dataStr.tltE, v000, dataStr.surfNormX(i), incAlpha); + end +end + +%% -- For Debugging +if plot_result == 1 + fig = figure(); + fig.Position(3) = 2*450; + fig.Position(4) = 350; + subplot(121); hold on; + ImData(dataStr.tht(:,:,1), dataStr.eb(:,:,1), dataStr.data(:,:,1)); + line([0, 0] + mean(thtA_ref(:)), [-1e3, 1e3], 'color', 'c', 'linewidth', 0.5, 'linestyle', '-'); + line([-1e3, 1e3], [0, 0] + eB_ref, 'color', 'c', 'linewidth', 0.5, 'linestyle', '-'); + img_props([], "tht"); + axis([min(dataStr.tht(:)), max(dataStr.tht(:)), min(dataStr.eb(:)), max(dataStr.eb(:))]); + colorbar; title('convert_to_k(): Before', 'Interpreter', 'none'); + subplot(122); hold on; + ImData(dataStr.kx(:,:,1), dataStr.eb(:,:,1), dataStr.data(:,:,1)); + img_props([], "kx"); + axis([min(dataStr.kx(:)), max(dataStr.kx(:)), min(dataStr.eb(:)), max(dataStr.eb(:))]); + colorbar; title('convert_to_k(): After', 'Interpreter', 'none'); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/data_crop3D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/data_crop3D.m new file mode 100644 index 0000000..0ef9323 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/data_crop3D.m @@ -0,0 +1,153 @@ +function dataStr = data_crop3D(dataStr, xField_lims, yField_lims, zField_lims) +% dataStr = crop_data(dataStr, xField_lims, yField_lims, zField_lims) +% This function crops the ARPES x-, y- and z-independent variables over +% a given range. The function crops the most recently processed data and +% ensures consistency across both the independent variables and data +% matrix. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% +% IN: +% - dataStr: loaded MATLAB data structure. +% - xField_lims: [1 x 2] row vector of xField ('raw_tht', 'tht', 'kx') crop limits. +% - yField_lims: [1 x 2] row vector of yField ('raw_eb', 'eb') crop limits. +% - zField_lims: [1 x 2] row vector of zField ('hv / tltM', 'kz / ky') crop limits. +% +% OUT: +% - dataStr: modified and cropped ARPES data structure. + +%% Default parameters +maxLim = 1e4; +if nargin < 2; xField_lims=[-1 1]*maxLim; yField_lims=[-1 1]*maxLim; zField_lims=[-1 1]*maxLim; end +if nargin < 3; yField_lims=[-1 1]*maxLim; zField_lims=[-1 1]*maxLim; end +if nargin < 4; zField_lims=[-1 1]*maxLim; end +if isempty(xField_lims); xField_lims=[-1 1]*maxLim; end +if isempty(yField_lims); yField_lims=[-1 1]*maxLim; end +if isempty(zField_lims); zField_lims=[-1 1]*maxLim; end +if length(xField_lims) < 2; xField_lims=[-1 1]*maxLim; end +if length(yField_lims) < 2; yField_lims=[-1 1]*maxLim; end +if length(zField_lims) < 2; zField_lims=[-1 1]*maxLim; end +% - Sorting the cropping limits in ascending order +xField_lims = sort(xField_lims); +yField_lims = sort(yField_lims); +zField_lims = sort(zField_lims); +% - Extracting the fields to be used with most recent processing +[xField, yField, zField, dField] = find_data_fields(dataStr); + +% disp('Data cropping...') +% wbar = waitbar(0.1, 'Extracting cropping indices...', 'Name', 'crop_data'); + +%% 1 - First determine the zField indices of the crop over scan parameter +if string(zField) == "hv" || string(zField) == "tltM" || string(zField) == "index" + [~, zIndxL] = min(abs(dataStr.(zField)(1,:) - zField_lims(1))); + [~, zIndxU] = min(abs(dataStr.(zField)(1,:) - zField_lims(2))); + zField_indx = [zIndxL zIndxU]; +else + thtIndx = ceil(size(dataStr.(dField), 2)/2); + ebIndx = ceil(size(dataStr.(dField), 1)/2); + [~, zIndxL] = min(abs(dataStr.(zField)(ebIndx,thtIndx,:) - zField_lims(1))); + [~, zIndxU] = min(abs(dataStr.(zField)(ebIndx,thtIndx,:) - zField_lims(2))); + zField_indx = [zIndxL zIndxU]; +end +%% 2 - Next determine the xField and yField indices across each scan +for i = 1:diff(zField_indx)+1 + z_index = i - 1 + min(zField_indx); +% waitbar(i/diff(zField_indx)+1, wbar, 'Extracting cropping indices...', 'Name', 'crop_data'); + %% 2.1 - xField cropping indices + if string(xField) == "raw_tht" + [~, xIndx_L] = min(abs(dataStr.(xField)(1,:) - xField_lims(1))); + [~, xIndx_U] = min(abs(dataStr.(xField)(1,:) - xField_lims(2))); + xField_indx{i} = [xIndx_L xIndx_U]; + else + ebIndx = ceil(size(dataStr.(dField), 1)/2); + [~, xIndx_L] = min(abs(dataStr.(xField)(ebIndx,:,z_index) - xField_lims(1))); + [~, xIndx_U] = min(abs(dataStr.(xField)(ebIndx,:,z_index) - xField_lims(2))); + xField_indx{i} = [xIndx_L xIndx_U]; + end + %% - 2.2 - yField cropping indices + if string(yField) == "raw_eb" + [~, yIndx_L] = min(abs(dataStr.(yField)(:,1) - yField_lims(1))); + [~, yIndx_U] = min(abs(dataStr.(yField)(:,1) - yField_lims(2))); + yField_indx{i} = [yIndx_L yIndx_U]; + else + thtIndx = ceil(size(dataStr.(dField), 2)/2); + [~, yIndx_L] = min(abs(dataStr.(yField)(:,thtIndx,z_index) - yField_lims(1))); + [~, yIndx_U] = min(abs(dataStr.(yField)(:,thtIndx,z_index) - yField_lims(2))); + yField_indx{i} = [yIndx_L yIndx_U]; + end +end +%% 3 - Validity check that the cropping indices for x- and y- are consistent +% x-field consistency checks +xField_diff = diff(cat(1, xField_indx{:}),[], 2); +for i = 1:length(xField_diff) +% waitbar(i/length(xField_diff), wbar, 'Validity checks on x-field indices...', 'Name', 'crop_data'); + if xField_diff(i) ~= min(xField_diff) + xField_indx{i}(1) = xField_indx{i}(1) - floor((min(xField_diff)-xField_diff(i))/2); + xField_indx{i}(2) = xField_indx{i}(2) + ceil((min(xField_diff)-xField_diff(i))/2); + end +end +%y-field consistency checks +yField_diff = diff(cat(1, yField_indx{:}),[], 2); +for i = 1:length(yField_diff) +% waitbar(i/length(yField_diff), wbar, 'Validity checks on y-field indices...', 'Name', 'crop_data'); + if yField_diff(i) ~= min(yField_diff) && yField_diff(i) > min(yField_diff) + yField_indx{i}(2) = yField_indx{i}(2) - abs(yField_diff(i) - min(yField_diff)); + elseif yField_diff(i) ~= min(yField_diff) && yField_diff(i)< min(yfield_diff) + yField_indx{i}(2) = yField_indx{i}(2) + abs(yField_diff(i) - min(yField_diff)); + end +end +%% 4 - Filing through each scan parameter and applying a subsequent crop to x and y variables +for i = 1:diff(zField_indx)+1 + z_index = i -1 + min(zField_indx); +% waitbar(i/diff(zField_indx)+1, wbar, 'Cropping ARPES data...', 'Name', 'crop_data'); + % - Applying cropping operations + if string(xField) == "kx" + crp_xField{i} = dataStr.(xField)(yField_indx{i}(1):yField_indx{i}(2), xField_indx{i}(1):xField_indx{i}(2), z_index); + crp_yField{i} = dataStr.(yField)(yField_indx{i}(1):yField_indx{i}(2), xField_indx{i}(1):xField_indx{i}(2), z_index); + crp_dField{i} = dataStr.(dField)(yField_indx{i}(1):yField_indx{i}(2), xField_indx{i}(1):xField_indx{i}(2), z_index); + if dataStr.Type == "Eb(k)"; crp_zField = dataStr.(zField)(1, zField_indx(1):zField_indx(2)); + elseif dataStr.Type == "Eb(kx,ky)" || dataStr.Type == "Eb(kx,kz)" || dataStr.Type == "Eb(k,i)"; crp_zField{i} = dataStr.(zField)(yField_indx{i}(1):yField_indx{i}(2), xField_indx{i}(1):xField_indx{i}(2), z_index); + end + % Cropping other fields for consistency + crp_thtField{i} = dataStr.tht(yField_indx{i}(1):yField_indx{i}(2), xField_indx{i}(1):xField_indx{i}(2), z_index); + elseif string(yField) == "eb" + crp_xField{i} = dataStr.(xField)(yField_indx{i}(1):yField_indx{i}(2), xField_indx{i}(1):xField_indx{i}(2), z_index); + crp_yField{i} = dataStr.(yField)(yField_indx{i}(1):yField_indx{i}(2), xField_indx{i}(1):xField_indx{i}(2), z_index); + if i == diff(zField_indx)+1; crp_zField = dataStr.(zField)(1, zField_indx(1):zField_indx(2)); end + crp_dField{i} = dataStr.(dField)(yField_indx{i}(1):yField_indx{i}(2), xField_indx{i}(1):xField_indx{i}(2), z_index); + elseif string(xField) == "raw_tht" + if i == diff(zField_indx)+1 + crp_xField = dataStr.(xField)(1, xField_indx{1}(1):xField_indx{i}(2)); + crp_yField = dataStr.(yField)(yField_indx{1}(1):yField_indx{i}(2), 1); + crp_zField = dataStr.(zField)(1, zField_indx(1):zField_indx(2)); + end + crp_dField{i} = dataStr.(dField)(yField_indx{i}(1):yField_indx{i}(2), xField_indx{i}(1):xField_indx{i}(2), z_index); + end +end +%% 5 - Converting cell arrays into 3D matrices of data +if iscell(crp_xField); crp_xField = cat(3, crp_xField{:}); +else; crp_xField = crp_xField; end +if iscell(crp_yField); crp_yField = cat(3, crp_yField{:}); +else; crp_yField = crp_yField; end +if iscell(crp_zField); crp_zField = cat(3, crp_zField{:}); +else; crp_zField = crp_zField; end +if iscell(crp_dField); crp_dField = cat(3, crp_dField{:}); +else; crp_dField = crp_dField; end +%% 6 - Assigning the cropped variables / data to new matrices +% - Assigning the first set of variables +dataStr.(xField) = []; dataStr.(yField) = []; dataStr.(zField) = []; dataStr.(dField) = []; +dataStr.(xField) = crp_xField; +dataStr.(yField) = crp_yField; +dataStr.(zField) = crp_zField; +dataStr.(dField) = crp_dField; +if exist('crp_thtField', 'var'); crp_thtField = cat(3, crp_thtField{:}); dataStr.tht = crp_thtField; end +% - Saving the crop to the meta data +dataStr.meta.crp_lims = []; +dataStr.meta.crp_lims = [xField_lims, yField_lims, zField_lims]; +dataStr.meta.crp_xIndx = xField_indx; +dataStr.meta.crp_yIndx = yField_indx; +dataStr.meta.crp_zIndx = zField_indx; +%% Close wait-bar +% close(wbar); +end diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/data_filter3D.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/data_filter3D.m new file mode 100644 index 0000000..331b7b5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/data_filter3D.m @@ -0,0 +1,59 @@ +function dataStr = data_filter3D(dataStr, filter_args) +% dataStr = filter_data(dataStr, filter_args) +% This function filters the 3D ARPES data given the filter arguments, which +% includes the filter type ("Gaco2", "GaussFlt2", "LaplaceFlt2", "CurvatureFlt2") and filter parameters. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - AA = Gaco2(A,hwX,hwY [,hsX] [,hsY]) +% - AA = GaussFlt2(Img,hwX,hwY,hsX,hsY) +% - AA = CurvatureFlt2(Img [,order] [,CX] [,CY]) +% - AA = LaplaceFlt2(Img [,y2xRatio] [,order]) +% +% IN: +% - dataStr loaded MATLAB data structure. +% - filter_args: 1x2 cell of {filter_type, [xFilterVal, yFilterVal]}. +% +% OUT: +% - dataStr modified and filtered ARPES data structure. + +%% Default parameters +if nargin < 2; filter_args = {"Gaco2", [1, 1]}; end +if isempty(filter_args); filter_args = {"Gaco2", [1, 1]}; end +% disp('Data filtering...') +% wbar = waitbar(0, 'Executing data filtering...', 'Name', 'data_filter3D'); + +%% 1 - Initialising the filter parameters +dataStr.meta.filter_args = filter_args; +% - Extracting the fields to be used with most recent processing +[~, ~, ~, dField] = find_data_fields(dataStr); +% - Extracting filter parameters +filter_type = filter_args{1}; +filter_val = filter_args{2}; +if length(filter_val) == 1; filter_val = [1, 1] .*filter_val; end + +%% 2 - Performing the filtering operation over all scans +for i = 1:size(dataStr.(dField), 3) +% waitbar(i/size(dataStr.(dField), 3), wbar, 'Filtering ARPES data...', 'Name', 'data_filter3D'); + if filter_type == "Gaco2" + filtered_data = Gaco2(dataStr.(dField)(:,:,i), filter_val(1), filter_val(2)); + elseif filter_type == "GaussFlt2" + filtered_data = GaussFlt2(dataStr.(dField)(:,:,i), filter_val(1), filter_val(2), 40, 40); + elseif filter_type == "LaplaceFlt2" + filtered_data = GaussFlt2(dataStr.(dField)(:,:,i), 5, 5, 40, 40); + filtered_data = SetContrast(filtered_data, 0.4, 0.999, 1.5); + filtered_data = LaplaceFlt2(filtered_data, filter_val(1)); + elseif filter_type == "CurvatureFlt2" + filtered_data = GaussFlt2(dataStr.(dField)(:,:,i), 100, 100, 500, 500); + filtered_data = SetContrast(filtered_data, 0.4, 0.999, 1.5); + filtered_data = CurvatureFlt2(filtered_data, '2D', filter_val(1), filter_val(2)); + filtered_data = GaussFlt2(filtered_data, 1, 1, 10, 10); + filtered_data = SetContrast(filtered_data, 0.2, 0.999); + end + dataStr.(dField)(:,:,i) = filtered_data; +end +%% 3 - Setting NaN values to zero +dataStr.(dField)(isnan(dataStr.(dField))) = 0; +%% Close wait-bar +% close(wbar); +end diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/delete_scans.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/delete_scans.m new file mode 100644 index 0000000..9c28efc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/delete_scans.m @@ -0,0 +1,64 @@ +function dataStr = delete_scans(dataStr, scancorr_args) +% dataStr = delete_scans(dataStr, scancorr_args) +% This function deletes a single or linear range of scans that contain +% anomalies. The given input is a vector of all the scan indices of the +% ARPES scans to be deleted. Function to delete a scan - *Eb(kx,ky) or +% Eb(kx,kz) scans only* +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% +% IN: +% - dataStr: loaded MATLAB data structure. +% - scancorr_args: 1x1 cell of {scan_indxs}. +% +% OUT: +% - dataStr: ARPES data structure after deleting desired scans. + +%% Default parameters +dataStr.meta.scancorr_args = scancorr_args; +% - Extracting the fields to be used with most recent processing +[xField, yField, zField, dField] = find_data_fields(dataStr); +% - Sorting the cropping limits in ascending order +scan_indxs = sort(scancorr_args{1}); +if length(scan_indxs) == 1; scan_indxs = [scan_indxs(1), scan_indxs(1)]; end + +% disp('Deleting ARPES scans...') +% wbar = waitbar(0.5, 'Deleting scans...', 'Name', 'delete_scans'); + +%% Validity check on input +minVal = 1; +maxVal = size(dataStr.(dField), 3); +% - Checking max/min are not exceeded +scan_indxs(scan_indxs < minVal) = minVal; +scan_indxs(scan_indxs > maxVal) = maxVal; +% - Checking that there are not duplicate numbers +scan_indxs = unique(scan_indxs); + +%% - 1 - EbAlign->Normalise->kConvert fields +if isfield(dataStr, 'kx') + dataStr.(xField)(:,:,scan_indxs) = []; + dataStr.tht(:,:,scan_indxs) = []; + dataStr.(yField)(:,:,scan_indxs) = []; + dataStr.(zField)(:,:,scan_indxs) = []; + dataStr.(dField)(:,:,scan_indxs) = []; +%% - 2 - EbAlign->Normalise fields +elseif isfield(dataStr, 'data') + dataStr.(xField)(:,:,scan_indxs) = []; + dataStr.(yField)(:,:,scan_indxs) = []; + dataStr.(zField)(scan_indxs) = []; + dataStr.(dField)(:,:,scan_indxs) = []; +%% - 3 - EbAlign fields +elseif isfield(dataStr, 'eb') + dataStr.(xField)(:,:,scan_indxs) = []; + dataStr.(yField)(:,:,scan_indxs) = []; + dataStr.(zField)(scan_indxs) = []; + dataStr.(dField)(:,:,scan_indxs) = []; +%% - 4 - Raw, unprocessed data fields +else + dataStr.(zField)(scan_indxs) = []; + dataStr.(dField)(:,:,scan_indxs) = []; +end +%% Close wait-bar +% close(wbar); +end diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoConts.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoConts.m new file mode 100644 index 0000000..6d4d9f8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoConts.m @@ -0,0 +1,272 @@ +function [contStr, fig] = extract_isoConts(dataStr, isocont_args, plot_results) +% [contStr, fig] = extract_isoConts(dataStr, isocont_args, plot_results) +% This function extracts and plots the iso-contours of a 2D ARPES image. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - [h=] ImData(X,Y,Z[,style]); +% - [DSlice,XSlice] = Slice(ACorr,ECorr,Data,xMode,Win) ; +% - [XR,YR,DataR] = Remap(XM,YM,Data); +% +% IN: +% - dataStr: data structure of the ARPES data. +% - isocont_args: 1x6 cell of {scanIndex, icPOI, icMinArea, icVal, icN, icSmooth}. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - contStr: new MATLAB data-structure. +% - fig: figure output. + +%% Default parameters +if nargin < 3; plot_results = 1; end +if nargin < 2; isocont_args = cell(1,6); plot_results = 1; end +if isempty(isocont_args); isocont_args = cell(1,6); end +if isempty(plot_results); plot_results = 1; end +pp = plot_props(); +fig = []; + +%% - 1 - Initialising input parameters +% - Extracting the input parameters +scanIndex = isocont_args{1}; if isempty(scanIndex); scanIndex = 1; end % Scan index to be cut +icPOI = isocont_args{2}; if isempty(icPOI); icPOI = [0, 15.04]; end % 1x2 vector of a given point of interest, aroudn which the contours are determined +icMinArea = isocont_args{3}; if isempty(icMinArea); icMinArea = 0.005; end % single, constant value that stores all contours above the minimum enclosed area +icVal = isocont_args{4}; if isempty(icVal); icVal = [0.05, 0.5]; end % single value or 1x2 vector that gives the normalised iso-countour value, or range [minVal, maxVal] +icN = isocont_args{5}; if isempty(icN); icN = 10; end % single, constant value that determines the total number of iso-contours to extract. For single icVal, this is ignored. +icSmooth = isocont_args{6}; if isempty(icSmooth); icSmooth = [1.5, 1.5]; end % Gaussian pre-smoothing parameters of the data prior to extracting the iso-contours +% - Extracting the x-axis, y-axis and data +if isfield(dataStr, 'IsoType') + scanIndex = 1; + xField = dataStr.xField; + if dataStr.IsoType == "IsoE" || dataStr.IsoType == "IsoK" + XDat = dataStr.XSlice; + YDat = dataStr.YSlice; + DDat = dataStr.DSlice; + elseif dataStr.IsoType == "Scan" + XDat = dataStr.XScan; + YDat = dataStr.YScan; + DDat = dataStr.DScan; + end +else + [xField, yField, ~, dField] = find_data_fields(dataStr); + if isfield(dataStr, 'kx') || isfield(dataStr, 'data') || isfield(dataStr, 'eb') + XDat = dataStr.(xField)(:,:,scanIndex); + YDat = dataStr.(yField)(:,:,scanIndex); + DDat = dataStr.(dField)(:,:,scanIndex); + else + XDat = dataStr.(xField); + YDat = dataStr.(yField); + DDat = dataStr.(dField)(:,:,scanIndex); + end +end +% - Creating a list of all contour values to file through +icVal = sort(icVal); +if length(icVal) == 1; icRange = icVal * max(DDat(:)); +else; icRange = linspace(icVal(1), icVal(2), icN) .* max(DDat(:)); +end + +%% - 2 - Extracting the Iso-Contours +DDat_raw = DDat; +% -- Gaussian pre-smooth the data if required +DDat = Gaco2(DDat, icSmooth(1), icSmooth(2)); +% -- Initialising variables +figTemp = figure(); set(figTemp, 'Visible', 'off'); +XCont = {}; +YCont = {}; +ACont = {}; +% -- Filing through all potential values of the iso-contours +for i = 1:length(icRange) + areaCont = []; + xCont = {}; + yCont = {}; + [CMatrix, ~] = contour(XDat, YDat, DDat, [1, 1]*icRange(i), 'linewidth', 2, 'linestyle', '-'); + % - Finding the areas contained within all contours + n = 0; ii = 1; + sz = size(CMatrix, 2); + if ~isempty(CMatrix) + nn(1) = CMatrix(2,1); + xx{1} = CMatrix(1,2:nn(1)+1); + yy{1} = CMatrix(2,2:nn(1)+1); + areaThresh(1) = polyarea(xx{1},yy{1}); + while n+nn(ii)+ii < sz + n = n + nn(ii); + ii = ii + 1; + nn(ii) = CMatrix(2,n+ii); + xx{ii} = CMatrix(1,n+ii+1:n+nn(ii)+ii); + yy{ii} = CMatrix(2,n+ii+1:n+nn(ii)+ii); + areaThresh(ii) = polyarea(xx{ii}, yy{ii}); + end + else + xx{1} = 0; + yy{1} = 0; + areaThresh = 0; + end + % -- Appling the limitations from the minimum area threshold + indx = find(areaThresh > icMinArea); + j = 1; + for n = indx + xCont{j} = xx{n}; + yCont{j} = yy{n}; + areaCont(j) = areaThresh(n); + j = j + 1; + end + areaThresh = sum(areaCont(:)); + + % -- Appling the limitations from the Point Of Interest + if ~isempty(icPOI) && length(icPOI) == 2 + POI_indx = []; + % - Finding the index for all contours that enclose the POI + for k = 1:length(xCont) + xLims = [min((xCont{k}(:))), max((xCont{k}(:)))]; + yLims = [min((yCont{k}(:))), max((yCont{k}(:)))]; + if icPOI(1) < xLims(2) && icPOI(1) > xLims(1) && icPOI(2) < yLims(2) && icPOI(2) > yLims(1) + POI_indx(end+1) = k; + end + end + % - Only keep the contours that enclose the POI + xCont = xCont(POI_indx); + yCont = yCont(POI_indx); + areaCont = areaCont(POI_indx); + end + + % -- Storing contours in a cell array + if ~isempty(xCont) || ~isempty(yCont) || ~isempty(areaCont) + XCont(end+1) = xCont; + YCont(end+1) = yCont; + ACont{end+1} = areaCont; + end +end +close(figTemp); + +%% - 3 - Extracting some statistics from the iso-contours +% -- Extracting estimates for the total size of the contours +x_length = []; +y_length = []; +areas = []; +for i = 1:length(XCont) + x_length(i) = range(XCont{i}); + y_length(i) = range(YCont{i}); + areas(i) = ACont{i}; +end +XMag = mean(x_length); +dXMag = 0.5 * range(x_length); +YMag = mean(y_length); +dYMag = 0.5 * range(y_length); +% -- Extracting estimates for the enclosed areas +mu_area = mean(areas); +err_area = 0.5 * range(areas); +% -- Extracting estimates for the electron number density (cm^-2) +mu_ne = 2 * (1/(2*pi))^2 * mu_area * (1e8)^2; +err_ne = 2 * (1/(2*pi))^2 * err_area * (1e8)^2; +% -- Defining the span of the contours as a single enclosed vector +XSpan = [XCont{1}, fliplr(XCont{end})]; +YSpan = [YCont{1}, fliplr(YCont{end})]; +% -- Defining the origin position of the iso-contours +X0 = mean(cell2mat(XCont)); +Y0 = mean(cell2mat(YCont)); + +%% 4.0 - Initialising the figure +if plot_results == 1 + fig = figure(); hold on; + fig.Position(1) = pp.figpos(1); + fig.Position(2) = pp.figpos(2); + fig.Position(3) = pp.fig5x4(1); + fig.Position(4) = pp.fig5x4(2); + %% 4.1 - Plotting the iamge with its iso-contours + % -- The plot depends on how far in the analysis + ImData(XDat, YDat, DDat_raw); + plot(icPOI(1), icPOI(2), 'mo', 'color', 'm', 'markerfacecolor', 'm'); + img_props([], string(xField)); + colbar_props(); + axis([min(XDat(:)), max(XDat(:)), min(YDat(:)), max(YDat(:))]); + % -- Adding title to the figure + title(sprintf(string(dataStr.FileName) + "; IsoCont"), 'interpreter', 'none', 'fontsize', 9); + axis equal; + axis([min(XDat(:)), max(XDat(:)), min(YDat(:)), max(YDat(:))]); + % - Initial formatting of the axis + ax = gca; + % -- Font properties + ax.FontName = 'Helvetica'; + ax.FontWeight = 'normal'; + ax.FontSize = 12; + % -- Tick properties + ax.TickLabelInterpreter = 'latex'; + ax.XMinorTick = 'off'; + ax.YMinorTick = 'off'; + ax.TickDir = 'in'; + ax.TickLength = [0.02 0.025]; + % -- Ruler properties + ax.XAxisLocation = 'bottom'; % 'bottom' | 'top' | 'origin' + ax.YAxisLocation = 'left'; % 'left' | 'right' | 'origin' + % -- Box Styling properties + ax.Color = [0, 0, 0]; + ax.LineWidth = 2.0; + ax.Box = 'on'; + ax.Layer = 'Top'; + %% 4.2 - Plotting the iso-contours + patch(XSpan, YSpan, [0 1 0], 'EdgeAlpha', 0, 'facealpha', 0.50); + isoCols = jet(length(XCont)); % Setting the color for each iso contour + for i = 1:length(XCont) + plot(XCont{i}, YCont{i}, 'color', isoCols(i,:), 'linewidth', 2, 'linestyle', '-'); + text(max(XCont{i}(:)), max(YCont{i}(:)), char(sprintf('%i', i)),... + 'horizontalalignment', 'center', 'fontsize', 14, 'color', isoCols(i,:)); + end + % -- Plotting the total span of the iso-contours + plot(X0+[-1,1].*0.5.*XMag(1), Y0.*[1,1], 'm-', 'linewidth', 1.5); + plot(X0.*[1,1], Y0+[-1,1].*0.5.*YMag(1), 'm-', 'linewidth', 1.5); + + %% 4.3 - Formatting the axis +% (A) -- If the data to be saved is an IsoSlice / IsoCut /IsoScan form + if isfield(dataStr, 'IsoType') + if dataStr.IsoType== "IsoE" + if dataStr.Type == "Eb(kx,ky)" + if dataStr.xField == "kx"; xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(kx,kz)" + if dataStr.xField == "kx"; xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + end + elseif dataStr.IsoType== "IsoK" + ylabel('$$ \bf E_B (eV) $$', 'Interpreter', 'latex'); + if dataStr.Type == "Eb(kx,ky)" + if dataStr.xField == "kx"; xlabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(kx,kz)" + if dataStr.xField == "kx"; xlabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + end +% (B) -- Else, for the usual ARPES data structure + else + img_props([], string(dataStr.xField)); + end + end +end + +%% 5 - Appending data to MATLAB data structure +contStr = struct(); +contStr.isocont_args = isocont_args; +contStr.xField = string(xField); +contStr.FileName = dataStr.FileName; +contStr.Type = dataStr.Type; +contStr.IsoType = "IsoCont"; +contStr.IsoVal = icRange; +contStr.IsoNum = length(XCont); +contStr.XCont = XCont; +contStr.YCont = YCont; +contStr.ACont = ACont; +% Appending vectors to plot range of contours as a patch +contStr.XSpan = XSpan; +contStr.YSpan = YSpan; +% Appending analysis of contours +contStr.X0 = X0; +contStr.Y0 = Y0; +contStr.XMag = [XMag, dXMag]; +contStr.YMag = [YMag, dYMag]; +contStr.XYAniso = [XMag./YMag, abs((XMag./YMag)*sqrt((dXMag/XMag)^2 + (dYMag/YMag)^2))]; +contStr.AreaMag = [mu_area, err_area]; +contStr.Ne = [mu_ne, err_ne]; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoCube.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoCube.m new file mode 100644 index 0000000..1611cb7 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoCube.m @@ -0,0 +1,143 @@ +function [cubeStr, fig] = extract_isoCube(dataStr, isocube_args, plot_results) +% [cubeStr, fig] = extract_isoCube(dataStr, isocube_args, plot_results) +% This function plots a 3D ARPES data data cube in the form +% of D(X, Y, Z). General function to view 3D ARPES data via a data cube +% approach +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - [h=] ImData(X,Y,Z[,style]) +% +% IN: +% - dataStr: data structure of the ARPES data. +% - isocube_args: 1x2 cell of {cLimMin, smoothVal}. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - cubeStr: new MATLAB data-structure. +% - fig: figure output. + + +%% Default parameters +if nargin < 3; plot_results = 1; end +if nargin < 2; isocube_args = cell(1,2); plot_results = 1; end +if isempty(isocube_args); isocube_args = cell(1,2); end +if isempty(plot_results); plot_results = 1; end +pp = plot_props(); +fig = []; +% - Extracting the fields to be used with most recent processing +[xField, yField, zField, dField] = find_data_fields(dataStr); + +%% - 1 - Initialising input parameters +cLimMin = isocube_args{1}; if isempty(cLimMin); cLimMin = 0.25; end % minimum threshold, below which the data points are transparent +smoothVal = isocube_args{2}; if isempty(smoothVal); smoothVal = 5; end % FWHM of a Gaussian smoothing operation on the 3D cube + +%% 1 - Initialising and permuting the variable / data arrays to be consistent in 3D +% - 1.1 - EbAlign->Normalise->kConvert fields +if isfield(dataStr, 'kx') + v = permute(dataStr.(dField), [3 2 1]); + x = permute(dataStr.(xField), [3 2 1]); + y = permute(dataStr.(yField), [3 2 1]); + z = permute(dataStr.(zField), [3 2 1]); +% - 1.2 - EbAlign->Normalise fields +elseif isfield(dataStr, 'data') + v = permute(dataStr.(dField), [3 2 1]); + x = permute(dataStr.(xField), [3 2 1]); + y = permute(dataStr.(yField), [3 2 1]); + % - Converting the scan variable into 3D + z = repmat(dataStr.(zField), [size(dataStr.(dField),1),1,size(dataStr.(dField),2)]); + z = permute(z, [2 3 1]); +% - 1.3 - EbAlign fields +elseif isfield(dataStr, 'eb') + v = permute(dataStr.(dField), [3 2 1]); + x = permute(dataStr.(xField), [3 2 1]); + y = permute(dataStr.(yField), [3 2 1]); + % - Converting the scan variable into 3D + z = repmat(dataStr.(zField), [size(dataStr.(dField),1),1,size(dataStr.(dField),2)]); + z = permute(z, [2 3 1]); +% - 1.4 - Raw, unprocessed data fields +else + v = permute(dataStr.(dField), [3 2 1]); + % - Converting the theta variable into 3D + x = repmat(dataStr.(xField), [size(dataStr.(dField),1),1,size(dataStr.(dField),3)]); + x = permute(x, [3 2 1]); + % - Converting the eb variable into 3D + y = repmat(dataStr.(yField), [1,size(dataStr.(dField),2),size(dataStr.(dField),3)]); + y = permute(y, [3 2 1]); + % - Converting the scan variable into 3D + z = repmat(dataStr.(zField), [size(dataStr.(dField),1),1,size(dataStr.(dField),2)]); + z = permute(z, [2 3 1]); +end + +%% 2 - Interpolating the data with a Gaussian if necessary +% - If necessary, smooth the data beforehand +v = smooth3(v, 'gaussian', smoothVal); + +%% 2.0 - Initialising the figure +if plot_results == 1 + fig = figure(); hold on; + fig.Position(1) = pp.figpos(1); + fig.Position(2) = pp.figpos(2); + fig.Position(3) = pp.fig5x4(1); + fig.Position(4) = pp.fig5x4(2); + % - For a 3D Eb(kx,ky) scan type + if dataStr.Type == "Eb(kx,ky)" + % -- Plotting the Eb(kx,ky) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Scan - Eb(kx,ky): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Scan - Eb(kx,ky): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Scan - Eb(kx,ky): A'); + else; set(fig, 'Name', 'Iso-Scan - Eb(kx,ky): Raw'); + end + % - For a 3D Eb(kx,kz) scan type + elseif dataStr.Type == "Eb(kx,kz)" + % -- Plotting the Eb(kx,kz) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Scan - Eb(kx,kz): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Scan - Eb(k): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Scan - Eb(kx,kz): A'); + else; set(fig, 'Name', 'Iso-Scan - Eb(kx,kz): Raw'); + end + end + % - Plotting the iso surfaces of the cube + p1L = patch(isocaps(z, x, y, v, cLimMin*max(v(:))), 'FaceColor', 'interp', 'EdgeColor', 'none'); + p2L = patch(isosurface(z, x, y, v, cLimMin*max(v(:))),'FaceColor', 'black', 'EdgeColor', 'none'); + isonormals(v, p2L); + % - Formatting the figure + img_props([], string(xField)); + colbar_props([0.925 0.80 0.020 0.125]); + % - View orientation + view([-65, 12]); + axis([min(z(:)), max(z(:)), min(x(:)), max(x(:)), min(y(:)), max(y(:))]); + % - Defining the axes properties + ax = gca; + ax.Color = [1, 1, 1]; + ax.XColor = [0 0 0]; + ax.YColor = [0 0 0]; + ax.ZColor = [0 0 0]; + ax.Box = 'on'; + ax.BoxStyle = 'full'; + ax.Layer = 'Top'; + % - Axis labels and limits + if dataStr.Type == "Eb(kx,ky)" + if isfield(dataStr, 'kx'); ylabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); xlabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; ylabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); xlabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(kx,kz)" + if isfield(dataStr, 'kx'); ylabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); xlabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; ylabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); xlabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + end + zlabel('$$ \bf E_B (eV) $$', 'Interpreter', 'latex'); +end + +%% 6 - Appending data to MATLAB data structure +cubeStr = struct(); +cubeStr.isocube_args = isocube_args; +cubeStr.xField = string(xField); +cubeStr.FileName = dataStr.FileName; +cubeStr.Type = dataStr.Type; +cubeStr.IsoType = "Cube"; +cubeStr.XCube = x; +cubeStr.YCube = y; +cubeStr.ZCube = z; +cubeStr.DCube = v; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoCut.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoCut.m new file mode 100644 index 0000000..9b5ccf4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoCut.m @@ -0,0 +1,224 @@ +function [cutStr, fig] = extract_isoCut(dataStr, isocut_args, plot_results) +% [cutStr, fig] = extract_isoCut(dataStr, isocut_args, plot_results) +% This function plots a EDC/MDC cut through the ARPES data in +% D(X,Y,cutIndx) into a single figure that includes the Eb(k) +% dispersion. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - [h=] ImData(X,Y,Z[,style]) +% - [XCut,DCut] = Cut(ACorr,ECorr,Data,xMode,Win) +% +% IN: +% - dataStr: data structure of the ARPES data. +% - isocut_args: 1x3 cell of {scanIndex, isoType, isoWin}. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - cutStr: new MATLAB data-structure. +% - fig: figure output. + +%% Default parameters +if nargin < 3; plot_results = 1; end +if nargin < 2; isocut_args = cell(1,3); plot_results = 1; end +if isempty(isocut_args); isocut_args = cell(1,3); end +if isempty(plot_results); plot_results = 1; end +pp = plot_props(); +fig = []; + +%% - 1 - Initialising input parameters +scanIndex = isocut_args{1}; if isempty(scanIndex); scanIndex = 1; end % Scan index to be cut +isoType = isocut_args{2}; if isempty(isoType); isoType = "EDC"; end % Type of cut to make. Either "MDC" (horizontal) or "EDC" (vertical) +isoWin = isocut_args{3}; if isempty(isoWin); isoWin = [-0.1, 0.1]; end % Integration window of the cut to be made. +% - Capping the window to the max/min of the ARPES data +if isempty(isoWin); Win = [-0.1, 0.1]; +else; Win = sort(isoWin); +end +% - Extracting the x-axis, y-axis and data +if isfield(dataStr, 'IsoType') + scanIndex = 1; + xField = dataStr.xField; + if dataStr.IsoType == "IsoE" || dataStr.IsoType == "IsoK" + XDat = dataStr.XSlice; + YDat = dataStr.YSlice; + DDat = dataStr.DSlice; + elseif dataStr.IsoType == "Scan" + XDat = dataStr.XScan; + YDat = dataStr.YScan; + DDat = dataStr.DScan; + end +else + [xField, yField, ~, dField] = find_data_fields(dataStr); + if isfield(dataStr, 'kx') || isfield(dataStr, 'data') || isfield(dataStr, 'eb') + XDat = dataStr.(xField)(:,:,scanIndex); + YDat = dataStr.(yField)(:,:,scanIndex); + DDat = dataStr.(dField)(:,:,scanIndex); + else + XDat = dataStr.(xField); + YDat = dataStr.(yField); + DDat = dataStr.(dField)(:,:,scanIndex); + end +end +% - Capping the window limits +step_size = 0.025; +if isoType == "MDC" + if Win(1) < min(YDat(:)); Win(1) = min(YDat(:)) + step_size; end + if Win(2) > max(YDat(:)); Win(2) = max(YDat(:)) - step_size; end +elseif isoType == "EDC" + if Win(1) < min(XDat(:)); Win(1) = min(XDat(:)) + step_size; end + if Win(2) > max(XDat(:)); Win(2) = max(XDat(:)) - step_size; end +end +%% 2 - Extracting the Iso cuts +if isoType == "MDC" + [XCut, DCut] = Cut(XDat, YDat, DDat, 'mdc', Win); +elseif isoType== "EDC" + [XCut, DCut] = Cut(XDat, YDat, DDat, 'edc', Win); +end + +%% 3.0 - Plotting the figure if required +if plot_results == 1 + fig = figure(); + fig.Position(1) = pp.figpos(1); + fig.Position(2) = pp.figpos(2); + if isoType == "MDC" + fig.Position(3) = pp.fig5x4(1); + fig.Position(4) = 1.5*pp.fig5x4(2); + subplot(3,1,2:3); hold on; + elseif isoType== "EDC" + fig.Position(3) = 1.5*pp.fig5x4(1); + fig.Position(4) = pp.fig5x4(2); + subplot(1,3,1:2); hold on; + end + % - For an Eb(k) scan type + if dataStr.Type == "Eb(k)" + % -- Plotting the Eb(k) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Cut - Eb(k): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Cut - Eb(k): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Cut - Eb(k): A'); + else; set(fig, 'Name', 'Iso-Cut - Eb(k): Raw'); + end + % - For a 3D Eb(kx,ky) scan type + elseif dataStr.Type == "Eb(kx,ky)" + % -- Plotting the Eb(kx,ky) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Cut - Eb(kx,ky): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Cut - Eb(kx,ky): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Cut - Eb(kx,ky): A'); + else; set(fig, 'Name', 'Iso-Cut - Eb(kx,ky): Raw'); + end + % - For a 3D Eb(kx,kz) scan type + elseif dataStr.Type == "Eb(kx,kz)" + % -- Plotting the Eb(kx,kz) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Cut - Eb(kx,kz): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Cut - Eb(kx,kz): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Cut - Eb(kx,kz): A'); + else; set(fig, 'Name', 'Iso-Cut - Eb(kx,kz): Raw'); + end + % - For a 3D Eb(k,i) scan type + elseif dataStr.Type == "Eb(k,i)" + % -- Plotting the Eb(kx,kz) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Cut - Eb(k,i): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Cut - Eb(k,i): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Cut - Eb(k,i): A'); + else; set(fig, 'Name', 'Iso-Cut - Eb(k,i): Raw'); + end + end + %% 3.1 - Plotting the Eb(k) at the scan value + % -- The plot depends on how far in the analysis + ImData(XDat, YDat, DDat); + img_props([], string(xField)); + axis([min(XDat(:)), max(XDat(:)),min(YDat(:)), max(YDat(:))]); + % -- Plotting an outline over the integrated sliced region + if isoType == "MDC" + colbar_props(); + patch([-1e3, 1e3, 1e3, -1e3, -1e3], [Win(1), Win(1), Win(2), Win(2), Win(1)],... + [0 1 0], 'linewidth', 1, 'facealpha', 0, 'edgecolor', [0 1 0]); + elseif isoType== "EDC" + colbar_props([0.05 0.125 0.025 0.175], 'left'); + patch([Win(1), Win(1), Win(2), Win(2), Win(1)],[-1e3, 1e3, 1e3, -1e3, -1e3],... + [0 1 0], 'linewidth', 1, 'facealpha', 0, 'edgecolor', [0 0 1]); + end + % -- Adding title to the figure + title(sprintf(string(dataStr.FileName) + "; scan %i", scanIndex), 'interpreter', 'none', 'fontsize', 9); +% (A) -- If the data to be saved is an IsoSlice / IsoCut /IsoScan form + if isfield(dataStr, 'IsoType') + if dataStr.IsoType== "IsoE" + if dataStr.Type == "Eb(kx,ky)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(kx,kz)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(k,i)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf Index $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf Index $$', 'Interpreter', 'latex'); ylabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + end + elseif dataStr.IsoType== "IsoK" + ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + if dataStr.Type == "Eb(kx,ky)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(kx,kz)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(k,i)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf Index $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf Index $$', 'Interpreter', 'latex'); + end + end +% (B) -- Else, for the usual ARPES data structure + else + img_props([], string(dataStr.xField)); + end + end + %% 3.2 - Plotting the Iso-Cut + if isoType == "MDC" + subplot(3,1,1); hold on; + plot(XCut, DCut, 'k.-', 'color', [0 1 0], 'LineWidth', 1.5); + gca_props(); + ax = gca; + ax.XAxisLocation = 'top'; % 'bottom' | 'top' | 'origin' + ax.YAxisLocation = 'left'; % 'left' | 'right' | 'origin' + % Axis labels and limits + if xField == "raw_tht" || xField == "tht" + xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); + elseif xField == "kx" + xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); + end + ylabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); + % - Plotting the x- and y-axes + xl = [min(XDat(:)), max(XDat(:))]; yl = ylim; + axis([xl(1), xl(2), yl(1), 1.05*yl(2)]); + elseif isoType == "EDC" + subplot(1,3,3); hold on; + plot(DCut, XCut, 'k.-', 'color', [0 0 1], 'LineWidth', 1.5); + gca_props(); + ax = gca; + ax.XAxisLocation = 'bottom'; % 'bottom' | 'top' | 'origin' + ax.YAxisLocation = 'right'; % 'left' | 'right' | 'origin' + % - Axis labels and limits + ylabel('$$ \bf E_{B} (eV) $$', 'Interpreter', 'latex'); + xlabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); + % - Plotting the x- and y-axes + xl = xlim; yl = [min(YDat(:)), max(YDat(:))]; + axis([xl(1), 1.05*xl(2), yl(1), yl(2)]); + end +end + +%% 4 - Appending data to MATLAB data structure +cutStr = struct(); +cutStr.isocut_args = isocut_args; +cutStr.xField = string(xField); +cutStr.FileName = dataStr.FileName; +cutStr.Type = dataStr.Type; +cutStr.IsoType = isoType; +cutStr.IsoVal = mean(Win); +cutStr.IsoWin = 0.5*range(Win); +cutStr.IsoNum = 1; +cutStr.XCut = XCut; +cutStr.DCut = DCut; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoCut_series.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoCut_series.m new file mode 100644 index 0000000..db9b642 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoCut_series.m @@ -0,0 +1,193 @@ +function [cutStrM, fig] = extract_isoCut_series(dataStr, isocut_args, plot_results) +% [cutStrM, fig] = extract_isoCut_series(dataStr, isocut_args, plot_results) +% This function plots a EDC/MDC cut through the ARPES data in +% D(X,Y,cutIndx) into a single figure that includes the Eb(k) +% dispersion. General function to view a series of cuts through ARPES +% data. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - [h=] ImData(X,Y,Z[,style]) +% - [XCut,DCut] = Cut(ACorr,ECorr,Data,xMode,Win) +% +% IN: +% - dataStr: data structure of the ARPES data. +% - isocut_args: 1x6 cell of {scanIndex, isocutType, isocutWin, isocutXLims, isocutYLims, isocutN}. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - cutStr: new MATLAB data-structure. +% - fig: figure output. + +%% Default parameters +if nargin < 3; plot_results = 1; end +if nargin < 2; isocut_args = cell(1,6); plot_results = 1; end +if isempty(isocut_args); isocut_args = cell(1,6); end +if isempty(plot_results); plot_results = 1; end +pp = plot_props(); +fig = []; + +%% - 1 - Initialising input parameters +% - Extracting the input parameters +scanIndex = isocut_args{1}; if isempty(scanIndex); scanIndex = 1; end % Scan index to be cut +isoType = isocut_args{2}; if isempty(isoType); isoType = "MDC"; end % Type of line profile to extract. "EDC" (vertical) or "MDC" (horizontal) +isoWin = isocut_args{3}; if isempty(isoWin); isoWin = 0.02; end % single, constant value of the integration window. +isoXLims = isocut_args{4}; if isempty(isoXLims); isoXLims = [-1, 1]*1e5; end % 1x2 vector which gives the x-axis limits of the train [minX, maxX] +isoYLims = isocut_args{5}; if isempty(isoYLims); isoYLims = [-1, 1]*1e5; end % 1x2 vector which gives the y-axis limits of the train [minY, maxY] +isoN = isocut_args{6}; if isempty(isoN); isoN = 10; end % single, constant value that determines the total number of line profiles to extract +% - Extracting the x-axis, y-axis and data +if isfield(dataStr, 'IsoType') + scanIndex = 1; + xField = dataStr.xField; + if dataStr.IsoType == "IsoE" || dataStr.IsoType == "IsoK" + XDat = dataStr.XSlice; + YDat = dataStr.YSlice; + DDat = dataStr.DSlice; + elseif dataStr.IsoType == "Scan" + XDat = dataStr.XScan; + YDat = dataStr.YScan; + DDat = dataStr.DScan; + end +else + [xField, yField, ~, dField] = find_data_fields(dataStr); + if isfield(dataStr, 'kx') || isfield(dataStr, 'data') || isfield(dataStr, 'eb') + XDat = dataStr.(xField)(:,:,scanIndex); + YDat = dataStr.(yField)(:,:,scanIndex); + DDat = dataStr.(dField)(:,:,scanIndex); + else + XDat = dataStr.(xField); + YDat = dataStr.(yField); + DDat = dataStr.(dField)(:,:,scanIndex); + end +end +% - Verifying the min/max values of the limits +isoXLims = sort(isoXLims); +isoYLims = sort(isoYLims); +step_size = 0.01; +if isoXLims(1) < min(XDat(:)) || isoXLims(1) > max(XDat(:)); isoXLims(1) = min(XDat(:)) + step_size; end +if isoXLims(2) < min(XDat(:)) || isoXLims(2) > max(XDat(:)); isoXLims(2) = max(XDat(:)) - step_size; end +if isoYLims(1) < min(YDat(:)) || isoYLims(1) > max(YDat(:)); isoYLims(1) = min(YDat(:)) + step_size; end +if isoYLims(2) < min(YDat(:)) || isoYLims(2) > max(YDat(:)); isoYLims(2) = max(YDat(:)) - step_size; end +% - Extracting the maximum number of line-profiles possible +[xx, yy, ~] = data_crop2D(XDat, YDat, DDat, isoXLims, isoYLims); +% - Extracting the central location for each Cut +if isoType == "MDC" + max_N = length(xx); + if isoN > max_N; isoN = max_N; end + isoVals = linspace(isoYLims(1), isoYLims(2), isoN); +elseif isoType == "EDC" + max_N = length(yy); + if isoN > max_N; isoN = max_N; end + isoVals = linspace(isoXLims(1), isoXLims(2), isoN); +end + +%% 2 - Extracting the sequence of all line profiles +for i = 1:length(isoVals) + % Extracting the cut + cut_window = isoVals(i) + [-1, 1] * isoWin; + [all_cuts{i}, ~] = extract_isoCut(dataStr, {scanIndex, isoType, cut_window}, 0); + % Cropping the cut to be consistent with limits + if isoType == "MDC" + [all_cuts{i}.XCut, ~, all_cuts{i}.DCut] = data_crop2D(all_cuts{i}.XCut, [], all_cuts{i}.DCut, isoXLims, []); + elseif isoType == "EDC" + [~, all_cuts{i}.XCut, all_cuts{i}.DCut] = data_crop2D([], all_cuts{i}.XCut, all_cuts{i}.DCut, [], isoYLims); + end +end + +%% 3.0 - Plotting the figure if required +if plot_results == 1 + fig = figure(); + fig.Position(3) = 2*pp.fig5x4(1); + fig.Position(4) = pp.fig5x4(2); + isoCols = jet(length(isoVals)); % Setting the color for each line profile + %% 3.1 - Plotting the ARPES data + subplot(1,2,1); hold on; + % -- The plot depends on how far in the analysis + ImData(XDat, YDat, DDat); + img_props([], string(xField)); + colbar_props([0.06 0.75 0.015 0.175], 'left'); + axis([min(XDat(:)), max(XDat(:)),min(YDat(:)), max(YDat(:))]); + % -- Plotting the value of each line cut + for i = 1:length(isoVals) + if isoType == "MDC" + patch(... + [isoXLims(1), isoXLims(2), isoXLims(2), isoXLims(1), isoXLims(1)],... + all_cuts{i}.IsoVal + [-all_cuts{i}.IsoWin, -all_cuts{i}.IsoWin(1), all_cuts{i}.IsoWin, all_cuts{i}.IsoWin, -all_cuts{i}.IsoWin],... + isoCols(i,:), 'linewidth', 1, 'facealpha', 0.35, 'edgecolor', 'none'); + plot(isoXLims, [1, 1]*all_cuts{i}.IsoVal, 'k-', 'color', isoCols(i,:)); + elseif isoType == "EDC" + patch(... + all_cuts{i}.IsoVal + [-all_cuts{i}.IsoWin, -all_cuts{i}.IsoWin, all_cuts{i}.IsoWin, all_cuts{i}.IsoWin, -all_cuts{i}.IsoWin],... + [isoYLims(1), isoYLims(2), isoYLims(2), isoYLims(1), isoYLims(1)],... + isoCols(i,:), 'linewidth', 1, 'facealpha', 0.35, 'edgecolor', 'none'); + plot([1, 1]*all_cuts{i}.IsoVal, isoYLims, 'k-', 'color', isoCols(i,:)); + end + end + % -- Plotting an outline over the area where the line cuts are taken + patch(... + [isoXLims(1), isoXLims(2), isoXLims(2), isoXLims(1), isoXLims(1)],... + [isoYLims(1), isoYLims(1), isoYLims(2), isoYLims(2), isoYLims(1)],... + [0 1 0], 'linewidth', 0.5, 'facealpha', 0, 'edgecolor', [0 1 0], 'linestyle', ':'); + % -- Adding title to the figure + title(sprintf(string(dataStr.FileName) + "; scan %i", scanIndex), 'interpreter', 'none', 'fontsize', 9); +% (A) -- If the data to be saved is an IsoSlice / IsoCut /IsoScan form + if isfield(dataStr, 'IsoType') + if dataStr.IsoType== "IsoE" + if dataStr.Type == "Eb(kx,ky)" + if dataStr.xField == "kx"; xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(kx,kz)" + if dataStr.xField == "kx"; xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + end + elseif dataStr.IsoType== "IsoK" + ylabel('$$ \bf E_B (eV) $$', 'Interpreter', 'latex'); + if dataStr.Type == "Eb(kx,ky)" + if dataStr.xField == "kx"; xlabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(kx,kz)" + if dataStr.xField == "kx"; xlabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + end +% (B) -- Else, for the usual ARPES data structure + else + img_props([], string(dataStr.xField)); + end + end + %% 3.2 - Plotting all of the line profiles + subplot(1,2,2); hold on; + for i = length(isoVals):-1:1 + x = all_cuts{i}.XCut; + d = all_cuts{i}.DCut + all_cuts{i}.IsoVal; + plot(x, d, 'k.-', 'color', isoCols(i,:), 'LineWidth', 1.5); + end + gca_props(); + if isoType == "MDC" + xlim(isoXLims); + elseif isoType == "EDC" + xlim(isoYLims); + end + ylabel('$$ \bf Intensity (arb.) $$', 'Interpreter', 'latex'); + +end + +%% 4 - Appending data to MATLAB data structure +cutStrM = struct(); +cutStrM.isocut_args = isocut_args; +cutStrM.xField = string(xField); +cutStrM.FileName = dataStr.FileName; +cutStrM.Type = dataStr.Type; +cutStrM.IsoType = isoType; +cutStrM.IsoVal = isoVals; +cutStrM.IsoWin = [-1, 1] * isoWin; +cutStrM.IsoNum = isoN; +for i = 1:cutStrM.IsoNum + cutStrM.XCut{i} = all_cuts{i}.XCut; + cutStrM.DCut{i} = all_cuts{i}.DCut; +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoScan.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoScan.m new file mode 100644 index 0000000..236eec8 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoScan.m @@ -0,0 +1,102 @@ +function [scanStr, fig] = extract_isoScan(dataStr, isoscan_args, plot_results) +% [scanStr, fig] = extract_isoScan(dataStr, isoscan_args, plot_results) +% This function plots the 2D ARPES spectrum in the form of D(X,Y), along +% with a consistent formatting. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - gca_properties(type) +% - [h=] ImData(X,Y,Z[,style]) +% +% IN: +% - dataStr: data structure of the ARPES data. +% - isoscan_args: 1x1 cell of {scanIndex}. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - scanStr: new MATLAB data-structure. +% - fig: figure output. + +%% Default parameters +if nargin < 3; plot_results = 1; end +if nargin < 2; isoscan_args = cell(1,1); plot_results = 1; end +if isempty(isoscan_args); isoscan_args = cell(1,1); end +if isempty(plot_results); plot_results = 1; end +pp = plot_props(); +fig = []; +% - Extracting the fields to be used with most recent processing +[xField, yField, ~, dField] = find_data_fields(dataStr); + +%% - 1 - Initialising input parameters +isoScan = isoscan_args{1}; if isempty(isoScan); isoScan = 1; end % Scan index to be cut + +%% 1 - Extract the 2D ARPES spectra +% -- The data depends on how far in the analysis +if isfield(dataStr, 'kx') + XScan = dataStr.(xField)(:,:,isoScan); + YScan = dataStr.(yField)(:,:,isoScan); + DScan = dataStr.(dField)(:,:,isoScan); +elseif isfield(dataStr, 'data') || isfield(dataStr, 'eb') + XScan = dataStr.(xField)(:,:,isoScan); + YScan = dataStr.(yField)(:,:,isoScan); + DScan = dataStr.(dField)(:,:,isoScan); +else + XScan = dataStr.(xField); + YScan = dataStr.(yField); + DScan = dataStr.(dField)(:,:,isoScan); +end + +%% 2.0 - Initialising the figure +if plot_results == 1 + fig = figure(); + fig.Position(1) = pp.figpos(1); + fig.Position(2) = pp.figpos(2); + fig.Position(3) = pp.fig5x4(1); + fig.Position(4) = pp.fig5x4(2); + % - For an Eb(k) scan type + if dataStr.Type == "Eb(k)" + % -- Plotting the Eb(k) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Scan - Eb(k): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Scan - Eb(k): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Scan - Eb(k): A'); + else; set(fig, 'Name', 'Iso-Scan - Eb(k): Raw'); + end + % - For a 3D Eb(kx,ky) scan type + elseif dataStr.Type == "Eb(kx,ky)" + % -- Plotting the Eb(kx,ky) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Scan - Eb(kx,ky): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Scan - Eb(kx,ky): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Scan - Eb(kx,ky): A'); + else; set(fig, 'Name', 'Iso-Scan - Eb(kx,ky): Raw'); + end + % - For a 3D Eb(kx,kz) scan type + elseif dataStr.Type == "Eb(kx,kz)" + % -- Plotting the Eb(kx,kz) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Scan - Eb(kx,kz): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Scan - Eb(k): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Scan - Eb(kx,kz): A'); + else; set(fig, 'Name', 'Iso-Scan - Eb(kx,kz): Raw'); + end + end + %% 2.1 - Plotting the 2D ARPES spectra + ImData(XScan, YScan, DScan); + img_props([], string(xField)); + colbar_props(); + % -- Adding title to the figure + title(sprintf(string(dataStr.FileName) + "; scan %i", isoScan), 'interpreter', 'none', 'fontsize', 12); + axis([min(XScan(:)), max(XScan(:)), min(YScan(:)), max(YScan(:))]); +end + + +%% 3 - Appending data to MATLAB data structure +scanStr = struct(); +scanStr.isoscan_args = isoscan_args; +scanStr.xField = string(xField); +scanStr.FileName = dataStr.FileName; +scanStr.Type = dataStr.Type; +scanStr.IsoType = "Scan"; +scanStr.IsoVal = isoScan; +scanStr.XScan = XScan; +scanStr.YScan = YScan; +scanStr.DScan = DScan; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoSlice.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoSlice.m new file mode 100644 index 0000000..04bfb1c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoSlice.m @@ -0,0 +1,241 @@ +function [sliceStr, fig] = extract_isoSlice(dataStr, isoslice_args, plot_results) +% [sliceStr, fig] = extract_isoSlice(dataStr, isoslice_args, plot_results) +% This function plots the 3D ARPES data that is in the form +% D(X,Y,Z) into a single figure that includes the Eb(k) dispersion +% and an IsoK or IsoE slice. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - [h=] ImData(X,Y,Z[,style]); +% - [DSlice,XSlice] = Slice(ACorr,ECorr,Data,xMode,Win) ; +% - [XR,YR,DataR] = Remap(XM,YM,Data); +% +% IN: +% - dataStr: data structure of the ARPES data. +% - isoslice_args: 1x4 cell of {scanIndex, isoType, isoWin, remap}. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - sliceStr: new MATLAB data-structure. +% - fig: figure output. + +%% Default parameters +if nargin < 3; plot_results = 1; end +if nargin < 2; isoslice_args = cell(1,4); plot_results = 1; end +if isempty(isoslice_args); isoslice_args = cell(1,4); end +if isempty(plot_results); plot_results = 1; end +pp = plot_props(); +fig = []; +% - Extracting the fields to be used with most recent processing +[xField, yField, zField, dField] = find_data_fields(dataStr); + +%% - 1 - Initialising input parameters +scanIndex = isoslice_args{1}; if isempty(scanIndex); scanIndex = 1; end % Scan index to be cut +isoType = isoslice_args{2}; if isempty(isoType); isoType = "IsoK"; end % Type of cut to make. Either "IsoE" (horizontal) or "IsoK" (vertical) +isoWin = isoslice_args{3}; if isempty(isoWin); isoWin = [-0.1, 0.1]; end % Integration window of the cut to be made. +remap = isoslice_args{4}; if isempty(remap); remap = 1; end % Remap the slice onto a square grid? 1 or 0 +% - Capping the window to the max/min of the ARPES data +if isempty(isoWin); Win = [-0.1, 0.1]; +else; Win = sort(isoWin); +end +step_size = 0.025; +if isoType == "IsoE" + if Win(1) < min(dataStr.(yField)(:)); Win(1) = min(dataStr.(yField)(:))+step_size; end + if Win(2) > max(dataStr.(yField)(:)); Win(2) = max(dataStr.(yField)(:))-step_size; end +elseif isoType == "IsoK" + if Win(1) < min(dataStr.(xField)(:)); Win(1) = min(dataStr.(xField)(:))+step_size; end + if Win(2) > max(dataStr.(xField)(:)); Win(2) = max(dataStr.(xField)(:))-step_size; end +end + +%% 1 - Extracting the Iso slices +if isoType == "IsoE" + [DSlice, XSlice] = Slice(dataStr.(xField), dataStr.(yField), dataStr.(dField), 'IsoE', Win); + % - Extracting the scan parameter variables + if isfield(dataStr, 'kx'); init = ceil(0.5*size(dataStr.(dField), 2)); YSlice = squeeze(dataStr.(zField)(init,:,:))'; + else; YSlice = squeeze(dataStr.(zField))'; YSlice = repmat(YSlice, [1, size(XSlice, 2)]); + end +elseif isoType== "IsoK" + [DSlice, YSlice] = Slice(dataStr.(xField), dataStr.(yField), dataStr.(dField), 'IsoK', Win); + % - Extracting the scan parameter variables + if isfield(dataStr, 'kx'); init = ceil(0.5*size(dataStr.(dField), 2)); XSlice = squeeze(dataStr.(zField)(:,init,:)); + else; XSlice = squeeze(dataStr.(zField))'; XSlice = repmat(XSlice, [1, size(YSlice, 1)])'; + end +end +% 1.1 - Extracing the Scan axis of the raw data +% - For a 3D Eb(kx,ky) scan type +if dataStr.Type == "Eb(kx,ky)"; scanAxis = dataStr.tltM; +% - For a 3D Eb(kx,kz) scan type +elseif dataStr.Type == "Eb(kx,kz)"; scanAxis = dataStr.hv; +% - For a 3D Eb(k,i) scan type +elseif dataStr.Type == "Eb(k,i)"; scanAxis = dataStr.index; +end +%% 2 - Re-mapping the Iso slices onto a square grid if required +if remap == 1 + [XSlice, YSlice, DSlice] = Remap(XSlice, YSlice, DSlice); + YSlice = YSlice'; +end +DSlice(isnan(DSlice)) = 0; + +%% 3.0 - Initialising the figure +if plot_results == 1 + fig = figure(); + fig.Position(1) = pp.figpos(1); + fig.Position(2) = pp.figpos(2); + fig.Position(3) = 2*pp.fig5x4(1); + fig.Position(4) = pp.fig5x4(2); + % - For an Eb(k) scan type + if dataStr.Type == "Eb(k)" + % -- Plotting the Eb(k) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Slice - Eb(k): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Slice - Eb(k): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Slice - Eb(k): A'); + else; set(fig, 'Name', 'Iso-Slice - Eb(k): Raw'); + end + % - For a 3D Eb(kx,ky) scan type + elseif dataStr.Type == "Eb(kx,ky)" + % -- Plotting the Eb(kx,ky) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Slice - Eb(kx,ky): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Slice - Eb(kx,ky): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Slice - Eb(kx,ky): A'); + else; set(fig, 'Name', 'Iso-Slice - Eb(kx,ky): Raw'); + end + % - For a 3D Eb(kx,kz) scan type + elseif dataStr.Type == "Eb(kx,kz)" + % -- Plotting the Eb(kx,kz) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Slice - Eb(kx,kz): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Slice - Eb(kx,kz): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Slice - Eb(kx,kz): A'); + else; set(fig, 'Name', 'Iso-Slice - Eb(kx,kz): Raw'); + end + % - For a 3D Eb(k,i) scan type + elseif dataStr.Type == "Eb(k,i)" + % -- Plotting the Eb(kx,kz) figure object + if isfield(dataStr, 'kx'); set(fig, 'Name', 'Iso-Slice - Eb(k,i): A, N, K'); + elseif isfield(dataStr, 'data'); set(fig, 'Name', 'Iso-Slice - Eb(k,i): A, N'); + elseif isfield(dataStr, 'eb'); set(fig, 'Name', 'Iso-Slice - Eb(k,i): A'); + else; set(fig, 'Name', 'Iso-Slice - Eb(k,i): Raw'); + end + end + %% 3.1 - Plotting the Eb(k) at the scan value + subplot(1,2,1); hold on; + % -- The plot depends on how far in the analysis + if isfield(dataStr, 'kx') + ImData(dataStr.(xField)(:,:,scanIndex), dataStr.(yField)(:,:,scanIndex), dataStr.(dField)(:,:,scanIndex)); + elseif isfield(dataStr, 'data') || isfield(dataStr, 'eb') + ImData(dataStr.(xField)(:,:,scanIndex), dataStr.(yField)(:,:,scanIndex), dataStr.(dField)(:,:,scanIndex)); + else + ImData(dataStr.(xField), dataStr.(yField), dataStr.(dField)(:,:,scanIndex)); + end + img_props([], string(xField)); + colbar_props([0.06 0.75 0.015 0.175], 'left'); + axis([min(dataStr.(xField)(:)), max(dataStr.(xField)(:)),min(dataStr.(yField)(:)), max(dataStr.(yField)(:))]); + % -- Plotting an outline over the integrated sliced region + if isoType == "IsoE" + patch([-1e3, 1e3, 1e3, -1e3, -1e3], [Win(1), Win(1), Win(2), Win(2), Win(1)],... + [0 1 0], 'linewidth', 1, 'facealpha', 0, 'edgecolor', [0 1 0]); + elseif isoType== "IsoK" + patch([Win(1), Win(1), Win(2), Win(2), Win(1)],[-1e3, 1e3, 1e3, -1e3, -1e3],... + [0 1 0], 'linewidth', 1, 'facealpha', 0, 'edgecolor', [0 1 0]); + end + % -- Adding title to the figure + title(sprintf(string(dataStr.FileName) + "; scan %i", scanIndex), 'interpreter', 'none', 'fontsize', 12); + %% 3.2 - Plotting the Iso-Slice + subplot(1,2,2); hold on; + % - Plotting the Iso slices + ImData(XSlice, YSlice, DSlice); + % - Formatting the figure + minC = min(DSlice(:)); maxC = max(DSlice(:)); + caxis([minC, maxC]); + axis([min(XSlice(:)), max(XSlice(:)), min(YSlice(:)), max(YSlice(:))]); + img_props([], string(xField)); + colbar_props([0.94 0.75 0.015 0.175], 'right'); + % - Re-labelling the axes depending on what slice is taken + if isoType== "IsoE" + if dataStr.Type == "Eb(kx,ky)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(kx,kz)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(k,i)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf Index $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf Index $$', 'Interpreter', 'latex'); ylabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + end + elseif isoType== "IsoK" + ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + if dataStr.Type == "Eb(kx,ky)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(kx,kz)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + elseif dataStr.Type == "Eb(k,i)" + if isfield(dataStr, 'kx'); xlabel('$$ \bf Index $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf Index $$', 'Interpreter', 'latex'); + end + end + end + % -- Adding title to the figure + title(sprintf("%s; [%.2f,%.2f]", isoType, Win(1),Win(2)), 'interpreter', 'none', 'fontsize', 12); + % - title(sprintf(string(dataStr.FileName) + "; %s; [%.2f,%.2f]", isoType, isoWin(1),isoWin(2)), 'interpreter', 'none', 'fontsize', 12); + + %% 3.3 - Extracting the curve formed by the Eb(k) scan slice being looked at + if isoType== "IsoE" + initIndx = floor(0.5*size(dataStr.(dField), 1)); + if isfield(dataStr, 'kx') + x_curve = squeeze(dataStr.(xField)(initIndx,:,scanIndex)); + y_curve = squeeze(dataStr.(zField)(initIndx,:,scanIndex)); + elseif isfield(dataStr, 'data') || isfield(dataStr, 'eb') + x_curve = squeeze(dataStr.(xField)(initIndx,:,scanIndex)); + y_curve = repmat(squeeze(dataStr.(zField)(scanIndex)), size(x_curve)); + else + x_curve = squeeze(dataStr.(xField)); + y_curve = repmat(squeeze(dataStr.(zField)(scanIndex)), size(x_curve)); + end + % - Fitting a 4th order polynomial to the slice curve + x_interp = linspace(min(x_curve(:))-1e2, max(x_curve(:))+1e2, 1e3); + y_interp = polyval(polyfit(x_curve,y_curve,4),x_interp); + elseif isoType== "IsoK" + initIndx = floor(0.5*size(dataStr.(dField), 2)); + if isfield(dataStr, 'kx') + y_curve = squeeze(dataStr.(yField)(:,initIndx,scanIndex)); + x_curve = squeeze(dataStr.(zField)(:,initIndx,scanIndex)); + x_interp = linspace(min(x_curve(:))-5, max(x_curve(:))+5, 1e3); + y_interp = polyval(polyfit(x_curve,y_curve,1),x_interp); + elseif isfield(dataStr, 'data') || isfield(dataStr, 'eb') + y_curve = squeeze(dataStr.(yField)(:,initIndx,scanIndex)); + x_curve = repmat(squeeze(dataStr.(zField)(scanIndex)), size(y_curve)); + x_interp = ones(size(x_curve))*mean(x_curve(:)); + y_interp = linspace(-1e3, 1e3, size(x_interp, 1)); + else + y_curve = squeeze(dataStr.(yField)); + x_curve = repmat(squeeze(dataStr.(zField)(scanIndex)), size(y_curve)); + x_interp = ones(size(x_curve))*mean(x_curve(:)); + y_interp = linspace(-1e3, 1e3, size(x_interp, 1)); + end + end + % Plotting the scan slice curve + plot(x_interp, y_interp, 'Color', [0 0 1], 'LineWidth', 1., 'Linestyle', '-'); +end + +%% 5 - Appending data to MATLAB data structure +sliceStr = struct(); +sliceStr.isoslice_args = isoslice_args; +sliceStr.ScanAxis = scanAxis; +sliceStr.xField = string(xField); +sliceStr.FileName = dataStr.FileName; +sliceStr.Type = dataStr.Type; +sliceStr.IsoType = isoType; +sliceStr.IsoWin = Win; +sliceStr.IsoVal = mean(Win); +sliceStr.IsoRan = 0.5*range(Win); +sliceStr.IsoNum = 1; +sliceStr.XSlice = XSlice; +sliceStr.YSlice = YSlice; +sliceStr.DSlice = DSlice; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoSlice_series.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoSlice_series.m new file mode 100644 index 0000000..ac600f4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_isoSlice_series.m @@ -0,0 +1,80 @@ +function [sliceStrM, fig] = extract_isoSlice_series(dataStr, isoslice_args, plot_results) +% [sliceStrM, fig] = extract_isoSlice_series(dataStr, isoslice_args, plot_results) +% This function plots a EDC/MDC cut through the ARPES data in +% D(X,Y,cutIndx) into a single figure that includes the Eb(k) +% dispersion. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - [h=] ImData(X,Y,Z[,style]) +% - [XCut,DCut] = Cut(ACorr,ECorr,Data,xMode,Win) +% +% IN: +% - dataStr: data structure of the ARPES data. +% - isoslice_args: 1x6 cell of {scanIndex, isoType, isoWin, isoLims, isoN, remap}. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - cutStr: new MATLAB data-structure. +% - fig: figure output. + +%% Default parameters +if nargin < 3; plot_results = 1; end +if nargin < 2; isoslice_args = cell(1,6); plot_results = 1; end +if isempty(isoslice_args); isoslice_args = cell(1,6); end +if isempty(plot_results); plot_results = 1; end +pp = plot_props(); +fig = []; +% - Extracting the fields to be used with most recent processing +[xField, yField, ~, ~] = find_data_fields(dataStr); + +%% - 1 - Initialising input parameters +% - Extracting the input parameters +scanIndex = isoslice_args{1}; if isempty(scanIndex); scanIndex = 1; end % Scan index to be cut +isoType = isoslice_args{2}; if isempty(isoType); isoType = "IsoE"; end % Type of slice to make: "IsoE" (horizontal) or "IsoK" (vertical) +isoWin = isoslice_args{3}; if isempty(isoWin); isoWin = 0.02; end % single, constant value of the integration window. +isoLims = isoslice_args{4}; if isempty(isoLims); isoLims = [-1, 1]*1e5; end % 1x2 vector which gives the window limits of the series [min, max] +isoN = isoslice_args{5}; if isempty(isoN); isoN = 10; end % single, constant value that determines the total number of slices to extract +remap = isoslice_args{6}; if isempty(remap); remap = 1; end % Remap the slice onto a square grid? 1 or 0 +% - Verifying the min/max values of the limits +isoLims = sort(isoLims); +step_size = 0.01; +if isoType == "IsoE" + if isoLims(1) < min(dataStr.(yField)(:)) || isoLims(1) > max(dataStr.(yField)(:)); isoLims(1) = min(dataStr.(yField)(:)) + step_size; end + if isoLims(2) < min(dataStr.(yField)(:)) || isoLims(2) > max(dataStr.(yField)(:)); isoLims(2) = max(dataStr.(yField)(:)) - step_size; end + XX = data_crop3D(dataStr, [], isoLims); + max_N = size(XX.(xField), 1); +elseif isoType == "IsoK" + if isoLims(1) < min(dataStr.(xField)(:)) || isoLims(1) > max(dataStr.(xField)(:)); isoLims(1) = min(dataStr.(xField)(:)) + step_size; end + if isoLims(2) < min(dataStr.(xField)(:)) || isoLims(2) > max(dataStr.(xField)(:)); isoLims(2) = max(dataStr.(xField)(:)) - step_size; end + XX = data_crop3D(dataStr, isoLims, []); + max_N = size(XX.(xField), 2); +end +% - Verifying the max value of the number of slices +if isoN > max_N; isoN = max_N; end +% - Extracting the central location for each Cut +isoVals = linspace(isoLims(1), isoLims(2), isoN); + +%% 2 - Extracting the sequence of all line profiles +for i = 1:length(isoVals) + slice_window = isoVals(i) + [-1, 1] * isoWin; + [all_slices{i}, ~] = extract_isoSlice(dataStr, {scanIndex, isoType, slice_window, remap}, plot_results); +end + +%% 4 - Appending data to MATLAB data structure +sliceStrM = struct(); +sliceStrM.isoslice_args = isoslice_args; +sliceStrM.xField = string(xField); +sliceStrM.FileName = dataStr.FileName; +sliceStrM.Type = dataStr.Type; +sliceStrM.IsoType = isoType; +sliceStrM.IsoVal = isoVals; +sliceStrM.IsoRan = isoWin; +sliceStrM.IsoNum = isoN; +for i = 1:length(isoVals) + sliceStrM.IsoWin = isoVals(i) + [-1, 1] * isoWin; + sliceStrM.XSlice{i} = all_slices{i}.XSlice; + sliceStrM.YSlice{i} = all_slices{i}.YSlice; + sliceStrM.DSlice{i} = all_slices{i}.DSlice; +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_kf.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_kf.m new file mode 100644 index 0000000..29a7aff --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/extract_kf.m @@ -0,0 +1,146 @@ +function kfStr = extract_kf(XCut, DCut, kF_args, plot_results) +% kfStr = extract_kf(XCut, DCut, kF_args, plot_results) +% This function determines the value of KF from an MDC cut using the +% gradient method. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - [h=] ImData(X,Y,Z[,style]) +% +% IN: +% - XCut: 1xN vector of the k domain. +% - DCut: 1xN vector of the spectral intensity. +% - kF_args: 1x3 cell of {kfType("none","spline","gauss","smooth","xps_solver"), dkSmoothType, dkSmoothVal}. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - cutStr: new MATLAB data-structure. +% - fig: figure output. + +%% Default parameters +if nargin < 4; plot_results = 1; end +if nargin < 3; kF_args = cell(1,3); plot_results = 1; end +if isempty(kF_args); kF_args = cell(1,3); end +if isempty(plot_results); plot_results = 1; end +pp = plot_props(); + +%% - 1 - Initialising input parameters +kfType = kF_args{1}; if isempty(kfType); kfType = "gradient"; end % kf extraction method +dkSmoothType = kF_args{2}; if isempty(dkSmoothType); dkSmoothType = "none"; end % MDC pre-smoothing method +dkSmoothVal = kF_args{3}; if isempty(dkSmoothVal); dkSmoothVal = 1.0; end % MDC pre-smoothing parameter + +%% - 2 - Preparing the MDC cuts +% - 2.1 - Extracting raw MDC cut +XCut0 = XCut; +DCut0 = DCut; +% - 2.2 - Smoothing the MDC cut +XCut1 = XCut; +if lower(dkSmoothType) == "none" + DCut1 = DCut0; +elseif lower(dkSmoothType) == "gaco2" + DCut1 = Gaco2(DCut0, dkSmoothVal, dkSmoothVal); +elseif lower(dkSmoothType) == "binomial" + coeff = ones(1, 24); + DCut1 = filter(coeff, dkSmoothVal, DCut0); +elseif lower(dkSmoothType) == "savitzky-golay" + DCut1 = sgolayfilt(DCut0, dkSmoothVal, 11); +end +% - 2.3 - Differentiating the MDC cut to find Kf inflexion points +% -- Finding first derivative +dx = abs(XCut0(1) - XCut0(2)); +DCut2 = diff(DCut1(:), 1) ./ dx; +XCut2 = 0.5*dx+XCut0(1:length(DCut2)); +if lower(dkSmoothType) == "None" + DCut2 = DCut2; +elseif lower(dkSmoothType) == "gaco2" + DCut2 = Gaco2(DCut2, dkSmoothVal, dkSmoothVal); +elseif lower(dkSmoothType) == "binomial" + coeff = ones(1, 24); + DCut2 = filter(coeff, dkSmoothVal, DCut2); +elseif lower(dkSmoothType) == "savitzky-golay" + DCut2 = sgolayfilt(DCut2, dkSmoothVal, 11); +end + +%% - 3 - Extracting kF from the MDC cut +% Extracting the index of the maxima +[~, ilhs] = max(DCut2(:)); +[~, irhs] = min(DCut2(:)); +% Extracting the first estimate of kF +kFlhs = XCut2(ilhs); +kFrhs = XCut2(irhs); +% Extracting a better estimate of kF +[kFlhs, ~] = find_peak_loc(XCut2, abs(DCut2), kFlhs+mean(diff(XCut2(:))).*[-2, 2], kfType, plot_results); +[kFrhs, ~] = find_peak_loc(XCut2, abs(DCut2), kFrhs+mean(diff(XCut2(:))).*[-2, 2], kfType, plot_results); + +%% - 4 - Plotting the result if required +if plot_results == 1 + % -- Initialising the figure + fig = figure(); set(fig, 'Name', 'kF Extraction'); + fig.Position(3) = pp.fig16x9(1); + fig.Position(4) = pp.fig16x9(2); + hold on; + % 4.1 - Plotting the MDC curves + % - Plotting raw MDC cut + plot(XCut0, DCut0, '.-', 'linewidth', 4, 'color', [0.5,0.5,0.5,0.5]); + % - Plotting smoothed MDC cut + plot(XCut1, DCut1, '-', 'linewidth', 2, 'color', [0,0,0]); + % - General figure formatting + ax = gca; + % Font properties + ax.FontName = 'Helvetica'; ax.FontWeight = 'normal'; ax.FontSize = 15; + % Tick properties + ax.TickLabelInterpreter = 'latex'; + ax.XMinorTick = 'off'; ax.YMinorTick = 'off'; + ax.TickDir = 'out'; + % Ruler properties + ax.XAxisLocation = 'bottom'; % 'bottom' | 'top' | 'origin' + ax.YAxisLocation = 'left'; % 'left' | 'right' | 'origin' + % Box Styling properties + ax.LineWidth = 1.0; + ax.Box = 'off'; ax.Layer = 'Top'; + % Axis labels and limits + xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf MDC $$ $$\bf intensity$$ $$\bf (arb.)$$', 'Interpreter', 'latex'); + xlim([min(XCut0(:)), max(XCut0(:))]); + ylim([0, 1.25*max(DCut0(:))]); + title("kF Extraction", 'interpreter', 'none', 'fontsize', 12); + + % 4.2 - Plotting the kf positions + line([1 1]*kFlhs, [0, 1.25*max(DCut0(:))], 'Color', [1 0 0], 'LineWidth', 2.5, 'Linestyle', '-'); + line([1 1]*kFrhs, [0, 1.25*max(DCut0(:))], 'Color', [1 0 0], 'LineWidth', 2.5, 'Linestyle', '-'); + + % 4.3 - Plotting the MDC derivatives + yyaxis right; + y2col = [0.91 0.41 0.17 0.8]; + ax.YColor = y2col; + % - Plotting the derivative of the two + plot(XCut2, DCut2, '-', 'linewidth', 2, 'color', y2col); + % - General formatting + ylim([min(DCut2(:)), max(DCut2(:))]); + ylabel('$$ \bf dy/dx (arb.) $$', 'Interpreter', 'latex'); + % -- - Adding a legend to the figure + h = zeros(3, 1); + h(1) = plot(NaN,NaN,'.-', 'linewidth', 5, 'color', [0.5,0.5,0.5,0.5]); + h(2) = plot(NaN,NaN,'-', 'linewidth', 5, 'color', [0,0,0]); + h(3) = plot(NaN,NaN,'-', 'linewidth', 5, 'color', [0.91 0.41 0.17]); + legend(h, {'$$ MDC_{data} $$','$$ MDC_{smooth} $$','$$ MDC_{kF}$$ '}, 'interpreter', 'latex'); +end + +%% 5 - Appending data to MATLAB data structure +kfStr = struct(); +kfStr.kF_args = kF_args; +% -- Raw MDC cut data +kfStr.XCut0 = XCut0; +kfStr.DCut0 = DCut0; +% -- Smoothed MDC cut data +kfStr.XCut1 = XCut1; +kfStr.DCut1 = DCut1; +% -- Final MDC cut data used to find kf +kfStr.XCut2 = XCut2; +kfStr.DCut2 = DCut2; +% -- kF properties +kfStr.kFlhs = kFlhs; +kfStr.kFrhs = kFrhs; +kfStr.KF = (kFrhs - kFlhs); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/find_Ef_ADRESS.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/find_Ef_ADRESS.m new file mode 100644 index 0000000..8011db5 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/find_Ef_ADRESS.m @@ -0,0 +1,82 @@ +function [fit1,Ef] = find_Ef_ADRESS(Angle,Energy,Data,Angle_window,E_window, plot_result) +% (OLD FUNCTION, NOT USED CURRENTLY) +% [fit1,Ef] = find_Ef_ADRESS(Angle,Energy,Data,Angle_window, E_window, plot_result) +% This function fits a Fermi-Dirac distribution function, multiplied by a +% linear function, to the Data. Energy range [Energy_low, Energy_high]. +% Angle range [Angle_low, Angle_high]. +% This function performs a single fit, after binning all the channels. +% Note: the length of E or graph (Energy scale) can take arbitrary values +% Channel range can also be set to 1. + +%% Default parameters +% -- Estimating the energy window if no entry is entered +if nargin < 6; plot_result = 1; end +if nargin < 5; E_window = []; end +if isempty(E_window) + data = squeeze(Data); + [~, EF, ~] = AlignEF(data, Energy, 0); + E_window = [EF-0.6 EF+0.6]; +end +% -- Estimating the angle window if no entry is entered +if nargin < 4; Angle_window = []; end +if isempty(Angle_window) + Angle_window = [min(Angle(:))+0.25, max(Angle(:))-0.25]; +end +%% - 1 - Initialising variables +% Extracting the angle window +Angle_low = min(Angle_window); +Angle_high = max(Angle_window); +if size(Angle, 1) ~= 1; Data = Data(Angle>Angle_low&AngleAngle_low&Angle1; E = E'; end +if size(graph_sum, 2) >1; graph_sum = graph_sum'; end + +%% - 4 - Executing the Fermi fit +% Defining the function +fermi_fit = fittype(@(e, a, b, c, d, x) e+(a*(x-b)+d)./(1+exp((x-b)/c))); +% Initial fit parameters +dgraph_sum = graph_sum(10:end)-graph_sum(1:end-9); +dgraph_sum = [graph_sum(1)*ones(1,9) dgraph_sum']; +Ef_guess_loc = find(dgraph_sum == min(dgraph_sum)); +Ef_guess_loc = Ef_guess_loc(1); +a_start = (graph_sum(Ef_guess_loc) - graph_sum(1))/(E(Ef_guess_loc) - E(1)); +b_start = E(Ef_guess_loc); +c_start = .1; +d_start = max(graph_sum); +e_start = min(graph_sum); +% Executing the fitting operation +[fit1,gof1,out1]=fit(E,graph_sum,fermi_fit,'start',[e_start a_start b_start c_start d_start]); +fit1para = coeffvalues(fit1); +Ef = fit1para(3); +yy=feval(fermi_fit,fit1para(1),fit1para(2),fit1para(3),fit1para(4),fit1para(5),E); +%% - 5 - Plotting the best fit FDD +if plot_result == 1 + fig = figure(); + fig.Position(3) = 1.0*400; + fig.Position(4) = 1.0*400; + hold on; + plot(E, graph_sum,'o', 'Color', 'r', 'markerfacecolor', 'r'); + plot(E, yy, 'k-', 'linewidth', 2.5, 'linestyle', '-'); + line([1, 1].*Ef, [min(yy(:)), max(yy(:))], 'color', 'b', 'linewidth', 1.5, 'linestyle', ':'); + % -- Formatting the figure + % axis padded; + gca_props(); grid on; + ylabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); + xlabel('$$ \bf E_B [eV] $$', 'Interpreter', 'latex'); + legend({'Data', 'Fit', 'Ef'}, 'location', 'best', 'interpreter', 'none'); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/find_data_fields.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/find_data_fields.m new file mode 100644 index 0000000..5eaf88c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/find_data_fields.m @@ -0,0 +1,54 @@ +% --- General function to find the stage of the processing +function [xField, yField, zField, dField] = find_data_fields(dataStr) +% [xField, yField, zField, dField] = find_data_fields(dataStr) +% This function determines the most recent processed +% fields of the ARPES data-structure so that the correct +% post-processing can be performed in any order. The +% fields can be used to explicitly call a field within dataStr +% by using dataStr.(xField) for example. +% +% REQ. FUNCTIONS: none +% +% IN: +% - dataStr loaded MATLAB data structure. +% +% OUT: +% - xField: char of the most recent x-field ('raw_tht', 'tht', 'kx') +% - yField: char of the most recent y-field ('raw_eb', 'eb') +% - zField: char of the most recent z-field ('hv / tltM', 'kz / ky') +% - dField: char of the most recent d-field ('raw_data', 'data') + +% 1 - EbAlign->Normalise->kConvert fields +if isfield(dataStr, 'kx') + xField = 'kx'; yField = 'eb'; dField = 'data'; + if dataStr.Type == "Eb(k)"; zField = 'hv'; + elseif dataStr.Type == "Eb(kx,ky)"; zField = 'ky'; + elseif dataStr.Type == "Eb(kx,kz)"; zField = 'kz'; + elseif dataStr.Type == "Eb(k,i)"; zField = 'index'; + end +% 2 - EbAlign->Normalise fields +elseif isfield(dataStr, 'data') + xField = 'tht'; yField = 'eb'; dField = 'data'; + if dataStr.Type == "Eb(k)"; zField = 'hv'; + elseif dataStr.Type == "Eb(kx,ky)"; zField = 'tltM'; + elseif dataStr.Type == "Eb(kx,kz)"; zField = 'hv'; + elseif dataStr.Type == "Eb(k,i)"; zField = 'index'; + end +% 3 - EbAlign fields +elseif isfield(dataStr, 'eb') + xField = 'tht'; yField = 'eb'; dField = 'raw_data'; + if dataStr.Type == "Eb(k)"; zField = 'hv'; + elseif dataStr.Type == "Eb(kx,ky)"; zField = 'tltM'; + elseif dataStr.Type == "Eb(kx,kz)"; zField = 'hv'; + elseif dataStr.Type == "Eb(k,i)"; zField = 'index'; + end +% 4 - Raw, unprocessed data fields +else + xField = 'raw_tht'; yField = 'raw_eb'; dField = 'raw_data'; + if dataStr.Type == "Eb(k)"; zField = 'hv'; + elseif dataStr.Type == "Eb(kx,ky)"; zField = 'tltM'; + elseif dataStr.Type == "Eb(kx,kz)"; zField = 'hv'; + elseif dataStr.Type == "Eb(k,i)"; zField = 'index'; + end +end +end diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/truncate_ADRESS_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/truncate_ADRESS_data.m new file mode 100644 index 0000000..651fe87 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/truncate_ADRESS_data.m @@ -0,0 +1,16 @@ +function [Angle_axis_truncated, Energy_axis_truncated, Data_truncated]=... + truncate_ADRESS_data(Angle, Energy, Data, Angle_window, Energy_window) +% truncates data and axis in range given by windows +% [Angle_axis_truncated, Energy_axis_truncated, Data_truncated]=truncate_ADRESS_data(Angle, Energy, Data, Angle_window, Energy_window) +Angle_low=min(Angle_window); +Angle_high=max(Angle_window); +E_low=min(Energy_window); +E_high=max(Energy_window); + +Energy_axis_truncated=Energy(Energy>E_low&EnergyAngle_low&Angle2 + Data_truncated=Data(Energy>E_low&EnergyAngle_low&AngleE_low&EnergyAngle_low&AngleNormalise->kConvert fields +if isfield(dataStr, 'kx') + % - Cross-correlating the ARPES data + Y = squeeze(dataStr.(yField)(:,tht_indx,scan_indxs(1))); + D = dataStr.(dField)(:,:,scan_indxs); + [DataXC, ~] = SumScanXC(Y, D, xcorr_dE); + DataXC(isnan(DataXC)) = 0; + dataStr.(dField) = []; dataStr.(dField) = DataXC; + % - Squeezing the variable arrays + dataStr.(xField) = squeeze(dataStr.(xField)(:,:,scan_indxs(1))); + if isfield(dataStr, 'tht'); dataStr.tht = squeeze(dataStr.tht(:,:,scan_indxs(1))); end + dataStr.(yField) = squeeze(dataStr.(yField)(:,:,scan_indxs(1))); + if string(zField) ~= "index"; dataStr.(zField) = squeeze(dataStr.(zField)(eb_indx,tht_indx,scan_indxs(1))); end + % - Converting the wave-vector into a single field + dataStr.ky = mean(dataStr.ky(:)); + dataStr.kz = mean(dataStr.kz(:)); +%% 3 - EbAlign->Normalise fields +elseif isfield(dataStr, 'data') + % - Cross-correlating the ARPES data + Y = squeeze(dataStr.(yField)(:,tht_indx,scan_indxs(1))); + D = dataStr.(dField)(:,:,scan_indxs); + [DataXC, ~] = SumScanXC(Y, D, xcorr_dE); + DataXC(isnan(DataXC)) = 0; + dataStr.(dField) = []; dataStr.(dField) = DataXC; + % - Squeezing the variable arrays + dataStr.(xField) = squeeze(dataStr.(xField)(:,:,scan_indxs(1))); + dataStr.(yField) = squeeze(dataStr.(yField)(:,:,scan_indxs(1))); + dataStr.(zField) = dataStr.(zField)(scan_indxs(1)); +%% 4 - EbAlign fields +elseif isfield(dataStr, 'eb') + % - Cross-correlating the ARPES data + Y = squeeze(dataStr.(yField)(:,tht_indx,scan_indxs(1))); + D = dataStr.(dField)(:,:,scan_indxs); + [DataXC, ~] = SumScanXC(Y, D, xcorr_dE); + DataXC(isnan(DataXC)) = 0; + dataStr.(dField) = []; dataStr.(dField) = DataXC; + % - Squeezing the variable arrays + dataStr.(xField) = squeeze(dataStr.(xField)(eb_indx,:,scan_indxs(1))); + dataStr.(yField) = squeeze(dataStr.(yField)(:,tht_indx,scan_indxs(1))); + dataStr.(zField) = dataStr.(zField)(scan_indxs(1)); +%% 5 - Raw, unprocessed data fields +else + % - Squeezing the variable arrays + dataStr.(zField) = dataStr.(zField)(scan_indxs(1)); + % - Cross-correlating the ARPES data + [DataXC, ~] = SumScanXC(dataStr.(yField), dataStr.(dField)(:,:,scan_indxs), xcorr_dE); + DataXC(isnan(DataXC)) = 0; + dataStr.(dField) = []; dataStr.(dField) = DataXC; +end +%% 6 - Setting the identifier to Eb(k) now after XCorr +dataStr.meta.scancorr_args = scancorr_args; +dataStr.Type = "Eb(k)"; +dataStr.tltM = mean(dataStr.tltM); +dataStr.hv = mean(dataStr.hv); + +end diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/xfrag_scans.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/xfrag_scans.m new file mode 100644 index 0000000..e22e720 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F010 - arpes data processing/xfrag_scans.m @@ -0,0 +1,53 @@ +function dataStr_frag = xfrag_scans(dataStr, scanfrag_args) +% dataStr_frag = xfrag_scans(dataStr, scanfrag_args) +% This function cross-fragments the scans over the defined +% scan index and converts it from a 3D data set, into a 2D +% Eb(k) dispersion. This is used to treat each independent scan as a +% seperate ARPES data set and can be used for fitting statistics. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% +% IN: +% - dataStr: data structure of the ARPES data. +% - scanfrag_args: 1x1 cell of {xfrag_n}. +% +% OUT: +% - dataStr_frag: 1xN cell array of all the ARPES fragmented scans + +%% Default parameters +if nargin < 2; scanfrag_args = cell(1,1); end +if isempty(scanfrag_args); scanfrag_args = cell(1,1); end + +%% 1 - Initialising input parameters +xfrag_n = scanfrag_args{1}; if isempty(xfrag_n); xfrag_n = 1; end +% - Extracting the fields to be used with most recent processing +[~, ~, zField, dField] = find_data_fields(dataStr); + +%% 2 - Fragmenting the scans +dataStr_frag = {}; +if dataStr.Type == "Eb(k,i)" + for i = 1:length(dataStr.(zField)) + dataStr_frag{i} = dataStr; + dataStr_frag{i}.Type = "Eb(k)"; + dataStr_frag{i}.(zField) = dataStr_frag{i}.index(i); + dataStr_frag{i}.(dField) = squeeze(dataStr_frag{i}.(dField)(:,:,i)); + end +elseif dataStr.Type == "Eb(kx,ky)" + for i = 1:length(dataStr.(zField)) + dataStr_frag{i} = dataStr; + dataStr_frag{i}.Type = "Eb(k)"; + dataStr_frag{i}.(zField) = dataStr_frag{i}.tltM(i); + dataStr_frag{i}.(dField) = squeeze(dataStr_frag{i}.(dField)(:,:,i)); + end +elseif dataStr.Type == "Eb(kx,kz)" + for i = 1:length(dataStr.(zField)) + dataStr_frag{i} = dataStr; + dataStr_frag{i}.Type = "Eb(k)"; + dataStr_frag{i}.(zField) = dataStr_frag{i}.hv(i); + dataStr_frag{i}.(dField) = squeeze(dataStr_frag{i}.(dField)(:,:,i)); + end +elseif dataStr.Type == "Eb(k)" + dataStr_frag{1} = dataStr; +end +end diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/save_arpes_image_series.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/save_arpes_image_series.m new file mode 100644 index 0000000..99c37e7 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/save_arpes_image_series.m @@ -0,0 +1,146 @@ +function save_arpes_image_series(dataStr, viewVideo_args) +% save_arpes_image_series(dataStr, viewVideo_args) +% This function plots the Eb(kx) ARPES image as a function +% of the scan parameter, with the addition of a zoomed-in area +% of interest as an image series. You can also use this function to save +% all the ARPES scan images as an image series, allowing you to browse +% through all the ARPES scan images easily. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - gca_properties(type) +% - [h=] ImData(X,Y,Z[,style]) +% +% IN: +% - dataStr: data structure of the ARPES data. +% - viewVideo_args: 1x7 cell of {zLims, xLims, yLims, interpolate, ROI, xLimsROI, yLimsROI}. +% +% OUT: +% - figure output. + +%% Default parameters +pp = plot_props(); +if nargin < 2; viewVideo_args = cell(1,7); end +if isempty(viewVideo_args); viewVideo_args = cell(1,7); end +% - Extracting the fields to be used with most recent processing +[xField, yField, zField, dField] = find_data_fields(dataStr); + +%% - 1 - Initialising the defined parameters +zLims = viewVideo_args{1}; if isempty(zLims); zLims = []; end +xLims = viewVideo_args{2}; if isempty(xLims); xLims = []; end +yLims = viewVideo_args{3}; if isempty(yLims); yLims = []; end +interpolate = viewVideo_args{4}; if isempty(interpolate); interpolate = 0; end +ROI = viewVideo_args{5}; if isempty(ROI); ROI = 0; end +xLimsROI = viewVideo_args{6}; if isempty(xLimsROI); xLimsROI = []; end +yLimsROI = viewVideo_args{7}; if isempty(yLimsROI); yLimsROI = []; end + +%% - 2 - Initialising the figure +% - Choosing where to save the data +filter = {'*.*'}; +[save_filename, save_filepath] = uiputfile(filter, 'Save the image series...', dataStr.FileName); +fName = string(string(save_filepath) + string(save_filename)); +% If Cancel is pressed, then return nothing +if isequal(save_filepath,0) || isequal(save_filename,0); return; end +% - Initialising the data structures +dataStr = data_crop3D(dataStr, [], [], zLims); +% - Initialising the frames +nFrames = size(dataStr.(dField), 3); + +%% - 3 - Running the Eb(k) vs scan parameter frame-by-frame +for f = 1:nFrames + fig = figure(); + fig.Position(3) = 1.25*pp.fig5x4(1); + fig.Position(4) = 1.25*pp.fig5x4(2); + % - Initialising variables + ifName = fName + "_" + string(f); + % - Extracting the scan parameter for the given frame + if dataStr.Type == "Eb(kx,ky)" + if isfield(dataStr, 'kx'); scanVal = sprintf('$$ \\bf ky_{%i} = %.3f \\AA^{-1}$$', f, dataStr.(zField)(1,1,f)); + else; scanVal = sprintf('$$ \\bf \\tau_{%i} = %.2f^{\\circ}$$', f, dataStr.(zField)(f)); + end + elseif dataStr.Type == "Eb(kx,kz)" + if isfield(dataStr, 'kx'); scanVal = sprintf('$$ \\bf kz_{%i} = %.3f \\AA^{-1}$$', f, dataStr.(zField)(1,1,f)); + else; scanVal = sprintf('$$ \\bf hv_{%i} = %.2f eV $$', f, dataStr.(zField)(f)); + end + elseif dataStr.Type == "Eb(k,i)" + scanVal = sprintf('$$ \\bf scan: [%i]$$', f); + end + % - Extracting the full data + if isfield(dataStr, 'kx') + xDat = dataStr.(xField)(:,:,f); + yDat = dataStr.(yField)(:,:,f); + dDat = dataStr.(dField)(:,:,f); + elseif isfield(dataStr, 'data') || isfield(dataStr, 'eb') + xDat = dataStr.(xField)(:,:,f); + yDat = dataStr.(yField)(:,:,f); + dDat = dataStr.(dField)(:,:,f); + else + xDat = dataStr.(xField); + yDat = dataStr.(yField); + dDat = dataStr.(dField)(:,:,f); + end + %% 2.1 - Plotting the full Eb(k) image first + hold on; + if interpolate == 1; ImData(xDat, yDat, dDat, 'interp'); + else; ImData(xDat, yDat, dDat); + end + % - 2.2 - Formatting the figure + minC = min(min(min(dataStr.(dField)(:,:,f)))); + maxC = max(max(max(dataStr.(dField)(:,:,f)))); + caxis([minC, maxC]); + axis([xLims, yLims]); + img_props([], string(xField)); + colbar_props(); + title(dataStr.FileName, 'interpreter', 'none', 'fontsize', 12); + % - 2.3 - Adding text for the scan parameter + annotation('textbox', [0.22 0.2 0.17 0.06], 'String',scanVal, 'FitBoxToText','on',... + 'color', [0 0 0], 'fontsize', 13, 'backgroundcolor', [1 1 1], 'facealpha', 0.80,... + 'linewidth', 2, 'horizontalalignment', 'center', 'verticalalignment', 'middle',... + 'interpreter', 'latex'); + %% 3 - Plot the ROI if required + if ROI == 1 + %% 3.1 - Plotting the region of interest that is zoomed in on + x = [xLimsROI(1), xLimsROI(2), xLimsROI(2), xLimsROI(1), xLimsROI(1)]; + y = [yLimsROI(1), yLimsROI(1), yLimsROI(2), yLimsROI(2), yLimsROI(1)] ; + plot(x, y, 'LineWidth', 1.5, 'Color', 'y', 'linestyle', '-'); + %% 3.2 - Plotting the cropped Eb(k) on top + % - Creating a new inset axes to the figure + if mean(xLimsROI) < 0; new_ax = axes('Position',[.67 .655 .25 .25]); + else; new_ax = axes('Position',[.12 .655 .25 .25]); + end + % Cropping the data + [xDat_roi, yDat_roi, dDat_roi] = data_crop2D(xDat, yDat, dDat, xLimsROI, yLimsROI); + % - Plotting the cropped ARPES data + if interpolate == 1; ImData(xDat_roi, yDat_roi, dDat_roi, 'interp'); + else; ImData(xDat_roi, yDat_roi, dDat_roi); + end + % - 3.3 - Formatting the figure + minC = min(dDat_roi(:)); + maxC = max(dDat_roi(:)); + caxis([minC, maxC]); + axis([min(xDat_roi(:)), max(xDat_roi(:)), min(yDat_roi(:)), max(yDat_roi(:))]); + img_props([], string(xField)); + xlabel(''); ylabel(''); + % Other properties + ax = gca; + ax.FontSize = 10; + ax.TickDir = 'both'; + ax.Color = [1 1 1]; + ax.LineWidth = 0.75; + ax.Box = 'on'; + ax.Layer = 'Top'; + new_ax.XColor = [1 1 1]; + new_ax.YColor = [1 1 1]; + pbaspect([1 1 1]); + if mean(xLimsROI) < 0 + new_ax.XAxisLocation = 'bottom'; + new_ax.YAxisLocation = 'left'; + else + new_ax.XAxisLocation = 'bottom'; + new_ax.YAxisLocation = 'right'; + end + end + %% SAVE THE FIGURE + print(char(ifName), '-dpng', '-r500'); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/view_arpes_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/view_arpes_data.m new file mode 100644 index 0000000..64087b0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/view_arpes_data.m @@ -0,0 +1,39 @@ +function fig = view_arpes_data(dataStr, isoslice_args) +% fig = view_arpes_data(dataStr, isoslice_args) +% Use this as the general function to view all ARPES data, both during +% and after the processing of the data. The function identifies whether +% the APRES data is in the form of D(X,Y) for 2D data, or D(X,Y,Z) for 3D +% data and plots different figures accordingly. The 2D figure takes the +% form of an image in a single figure, whereas the 3D figure +% is plotted has a plot of the 2D ARPES image and a slice along a +% particular dimension. This function ensures that the most recent +% processing is also shown in the figure, so you can use this before and +% after processing to see the changes you have made to the data. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - gca_properties(type) +% - [h=] ImData(X,Y,Z[,style]) +% - view_isoScan(dataStr, isoscan_args) +% - view_isoSlice(dataStr, isoslice_args) +% +% IN: +% - dataStr: data structure of the ARPES data. +% - isoslice_args: 1x4 cell of {scanIndex, isoType, isoWin, remap}. Not required for 2D data, but can be used for 3D data. +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% Default parameters +if nargin < 2; isoslice_args = []; end +if isempty(isoslice_args); isoslice_args = []; end + +%% 1 - Plotting ARPES data +% - For an Eb(k) scan type +if dataStr.Type == "Eb(k)" + [~, fig] = extract_isoScan(dataStr); +% - For a 3D Eb(kx,ky) scan type +elseif dataStr.Type == "Eb(kx,ky)" || dataStr.Type == "Eb(kx,kz)" || dataStr.Type == "Eb(k,i)" + [~, fig] = extract_isoSlice(dataStr, isoslice_args); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/view_arpes_data_series.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/view_arpes_data_series.m new file mode 100644 index 0000000..a158d4b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/view_arpes_data_series.m @@ -0,0 +1,84 @@ +function view_arpes_data_series(dataStr, caxLims) +% view_arpes_data_series(dataStr, caxLims) +% General function to view a series of all scans from 3D ARPES data. Make +% sure ONLY Eb(kx,ky) or Eb(kx,kz) data is used here. This function plots +% the ARPES data in the form of D(X,Y) for all the scan parameter values +% (tltM or hv) in the form of a downsampled image series. This function +% ensures that the most recent processing is shown in the figure. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - [h=] ImData(X,Y,Z[,style]) +% +% IN: +% - dataStr: data structure of the ARPES data. +% - caxLims: 1x2 vector in normalised units of the colorscale of each image. +% +% OUT: (none) + +%% Default parameters +if nargin < 2; caxLims = [0, 1]; end +if isempty(caxLims); caxLims = [0, 1]; end + +disp('-> view series of all scans...') +wbar = waitbar(0., 'Plotting a view series of all scans...', 'Name', 'view_data_series'); + +%% - 1 - Initialising plot parameters +pp = plot_props(); +% - Extracting the fields to be used with most recent processing +[xField, yField, zField, dField] = find_data_fields(dataStr); +% - Each series is an nRows x nCols sub-plot +nRows = 3; nCols = 3; + +%% - 2 - Down-sampling the form of the data +step_size = 2; +zMidIndx = ceil(size(dataStr.(dField), 3)/2); + +%% - 3 - Plotting a series of Eb(k) Images +% Filing through all the pages of the figures +for ipage=1:ceil(size(dataStr.(dField), 3)/nRows/nCols) + figure_cell{ipage} = figure(); orient tall; + set(figure_cell{ipage}, 'Position', [80, 80, pp.fig8x8(1), pp.fig8x8(2)], 'Name', dataStr.H5file); + % Filing through all the frames in a single figure + for iframe=1:nRows*nCols + % - Finding the n'th data object to be plotted + n = (ipage-1)*nRows*nCols+iframe; + waitbar(n/size(dataStr.(dField), 3), wbar, 'Plotting a view series of all scans...', 'Name', 'view_data_series'); + % - If n > number of plotting elements, break the statement + if n > size(dataStr.(dField), 3) + break; + else + % -- Plotting the n'th data object + subplot(nRows,nCols,iframe); + img_props([], string(xField)); + xlabel(''); ylabel(''); + % -- The plot depends on how far in the analysis + % - 2.1 - EbAlign->Normalise->kConvert fields + if isfield(dataStr, 'kx') + ImData(dataStr.(xField)(1:step_size:end,1:step_size:end,n), dataStr.(yField)(1:step_size:end,1:step_size:end,n), dataStr.(dField)(1:step_size:end,1:step_size:end,n)); + title(sprintf('scan = %.2f', dataStr.(zField)(zMidIndx,zMidIndx,n)), 'fontsize', 10); + % - 2.2 - EbAlign->Normalise fields + elseif isfield(dataStr, 'data') + ImData(dataStr.(xField)(1:step_size:end,1:step_size:end,n), dataStr.(yField)(1:step_size:end,1:step_size:end,n), dataStr.(dField)(1:step_size:end,1:step_size:end,n)); + title(sprintf('scan = %.2f', dataStr.(zField)(n)), 'fontsize', 10); + % - 2.3 - EbAlign fields + elseif isfield(dataStr, 'eb') + ImData(dataStr.(xField)(1:step_size:end,1:step_size:end,n), dataStr.(yField)(1:step_size:end,1:step_size:end,n), dataStr.(dField)(1:step_size:end,1:step_size:end,n)); + title(sprintf('scan = %.2f', dataStr.(zField)(n)), 'fontsize', 10); + % - 2.4 - Raw, unprocessed data fields + else + ImData(dataStr.(xField)(1:step_size:end), dataStr.(yField)(1:step_size:end), dataStr.(dField)(1:step_size:end,1:step_size:end,n)); + title(sprintf('scan = %.2f', dataStr.(zField)(n)), 'fontsize', 10); + end + % - 2.5 - Formatting the figure + minC = min(min(min(dataStr.(dField)(1:step_size:end,1:step_size:end,iframe)))); + maxC = max(max(max(dataStr.(dField)(1:step_size:end,1:step_size:end,iframe)))); + caxis([caxLims(1), caxLims(2)].*maxC); + + % -- Remove the colorbar for all plots, except the first one + if iframe == 1; colbar_props([0.925 0.80 0.020 0.125]); end + end + end +end +close(wbar); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/view_arpes_isoSlice.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/view_arpes_isoSlice.m new file mode 100644 index 0000000..a7781fa --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F011 - arpes data plotting/view_arpes_isoSlice.m @@ -0,0 +1,125 @@ +function fig = view_arpes_isoSlice(sliceStr, plot_args, bzOverlay, bz_args) +% fig = view_arpes_isoSlice(sliceStr, plot_args, bzOverlay, bz_args) +% This function can be used to plot a very nice, publication quality +% IsoE image, along with the BZ overlay. Use this as a general function +% to plot good IsoE images, where many plot arguments can be controlled. +% The input data should be a sliceStr, that comes directly from the +% 'extract_isoSlice()' function. +% +% REQ. FUNCTIONS: none +% +% IN: +% - sliceStr: data structure of the sliced Iso-E ARPES data. +% - plot_args: 1x10 cell of {cMap, xLims, yLims, cLims, axCol, axisOn, axisEqual, gridOn, bzOn, interpOn}; +% - bzOverlay: data structure of the sliced Iso-E ARPES data. +% - bz_args: 1x3 cell of {bz_offset [xShift,yShift], bz_col [1,1,1], bz_lwidth [1.5]} +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% Default parameters +if nargin < 4; bz_args = {[0, 0], [1 1 1], 1.5}; end +if nargin < 3; bzOverlay = []; bz_args = {[0, 0], [1 1 1], 1.5}; end +if nargin < 2; plot_args = cell(1,10); bzOverlay = []; bz_args = {[0, 0], [1 1 1], 1.5}; end +if isempty(bz_args); bz_args = {[0, 0], [1 1 1], 1.5}; end +if isempty(bzOverlay); bzOverlay = []; end +if isempty(plot_args); plot_args = cell(1,10); end + +%% - 1 - Initialising the parameters +% - Extracting the plot arguments +cMap = plot_args{1}; if isempty(cMap); cMap = "hot"; end % colormap +xLims = plot_args{2}; if isempty(xLims); xLims = [min(sliceStr.XSlice(:)), max(sliceStr.XSlice(:))]; end % x-axis limits +yLims = plot_args{3}; if isempty(yLims); yLims = [min(sliceStr.YSlice(:)), max(sliceStr.YSlice(:))]; end % y-axis limits +cLims = plot_args{4}; if isempty(cLims); cLims = [0, 1]; end % color limits +axCol = plot_args{5}; if isempty(axCol); axCol = [0, 0, 0]; end % x- and y-axis colors +axisOn = plot_args{6}; if isempty(axisOn); axisOn = 1; end % show axis lines? +axisEqual = plot_args{7}; if isempty(axisEqual); axisEqual = 0; end % plot the axis as equals +gridOn = plot_args{8}; if isempty(gridOn); gridOn = 1; end % show Grid? +bzOn = plot_args{9}; if isempty(bzOn); bzOn = 0; end % show BZ? +interpOn = plot_args{10}; if isempty(interpOn); interpOn = 0; end % interpolate the data? +% - Initialising the plot / figure properties +pp = plot_props(); +fig = figure(); hold on; +fig.Position(3) = pp.fig5x4(1); +fig.Position(4) = pp.fig5x4(2); + +%% - 2 - Plotting the iso-slices +% 2.1 - Plotting the Iso-Slice plot +if interpOn == 1; ImData(sliceStr.XSlice, sliceStr.YSlice, sliceStr.DSlice, 'interp'); +else; ImData(sliceStr.XSlice, sliceStr.YSlice, sliceStr.DSlice); +end + +% - Initial formatting of the axis +ax = gca; +% -- Font properties +ax.FontName = 'Helvetica'; +ax.FontWeight = 'normal'; +ax.FontSize = 12; +% -- Tick properties +ax.TickLabelInterpreter = 'latex'; +ax.XMinorTick = 'off'; +ax.YMinorTick = 'off'; +ax.TickDir = 'in'; +ax.TickLength = [0.02 0.025]; +ax.XColor = axCol; +ax.YColor = axCol; +% -- Ruler properties +ax.XAxisLocation = 'bottom'; % 'bottom' | 'top' | 'origin' +ax.YAxisLocation = 'left'; % 'left' | 'right' | 'origin' +% -- Box Styling properties +ax.Color = [0, 0, 0]; +ax.LineWidth = 2.0; +ax.Box = 'on'; +ax.Layer = 'Top'; +% -- Adding title +title(sprintf(string(sliceStr.FileName) +... + "; %s; [%.2f,%.2f]", sliceStr.IsoType, sliceStr.IsoWin(1), sliceStr.IsoWin(2)), 'interpreter', 'none', 'fontsize', 8); + +% - Initial formatting of the figure +fig.Color = [1 1 1]; +fig.InvertHardcopy = 'off'; + +% 2.2 - Plotting the Brilluoin zone overlayer +if bzOn == 1 && ~isempty(bzOverlay) + bzone_props(bzOverlay, bz_args); +end + +% 2.3 - Applying color and axes limits, grid- and axes-lines +if axisEqual == 1; axis equal; end +axis([xLims, yLims]); +maxC = max(sliceStr.DSlice(:)); +caxis([cLims(1), cLims(2)].*maxC); +if axisOn == 1 + line([0 0], [-1e5, 1e5], 'Color', axCol, 'LineWidth', 1, 'Linestyle', '--'); + line([-1e5, 1e5], [0 0], 'Color', axCol, 'LineWidth', 1, 'Linestyle', '--'); +end +if gridOn == 1; grid on; end + +% - Formatting the figure +colormap(cMap); +colbar_props(); +% - Re-labelling the axes depending on what slice is taken +if sliceStr.IsoType== "IsoE" + if sliceStr.Type == "Eb(kx,ky)" + if sliceStr.xField == "kx"; xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif sliceStr.Type == "Eb(kx,kz)" + if sliceStr.xField == "kx"; xlabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \theta (^{\circ}) $$', 'Interpreter', 'latex'); ylabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + end +elseif sliceStr.IsoType== "IsoK" + ylabel('$$ \bf E_B (eV) $$', 'Interpreter', 'latex'); + if sliceStr.Type == "Eb(kx,ky)" + if sliceStr.xField == "kx"; xlabel('$$ \bf k_y (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf \tau (^{\circ}) $$', 'Interpreter', 'latex'); + end + elseif sliceStr.Type == "Eb(kx,kz)" + if sliceStr.xField == "kx"; xlabel('$$ \bf k_z (\AA^{-1}) $$', 'Interpreter', 'latex'); + else; xlabel('$$ \bf hv (eV) $$', 'Interpreter', 'latex'); + end + end +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff1D fitting/arpes2boff1D_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff1D fitting/arpes2boff1D_solver.m new file mode 100644 index 0000000..9da9a4e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff1D fitting/arpes2boff1D_solver.m @@ -0,0 +1,339 @@ +function fitStr = arpes2boff1D_solver(arpesStr, modelFunc, cTYPE, iparams, bTYPE, ibgrnd, solve_type) +% fitStr = arpes2boff1D_solver(arpesStr, cTYPE, modelFunc, iparams, bTYPE, ibgrnd, solve_type) +% Function that is used to fit N-parabolic dispersions to an EDC cut +% through ARPES data based on a set of model functions (modelFunc) that +% contain the band offset vs subband energy. This allows the band offset +% to be determined by extracting the best fit to the subbands, +% constraining their energies to what is found in a theoretical model. +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - modelFunc: 1xN cell of functions that gives the band offset vs subband energy +% - cTYPE: 1xN vector of the type of curve to use for fitting. Default: "sGLA" ("pGLA", "DS") +% - iparams: 3 cells {x0}{lb}{ub} with 1x6 array: the model fit parameters [FDEF,FDT,FDW,BOFF,INT,FWHM] +% - bTYPE: string of the type of background to use for fitting. Default: "Poly" ("none", "Shir", "LinShir") +% - ibgrnd: 3 cells {x0}{lb}{ub} with 1x5 vectors: the background parameters: [LHS,RHS,ORD,LAM,DEL,BGR] +% - solve_type: String of either "fminunc", "fmincon", "lsqnonlin", "simulannealbnd" that sets the optimisation routine to use +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Default parameters +% - Default input parameters to use +if nargin < 6; solve_type = "lsqcurvefit"; end +if nargin < 5 + ibgrnd{1} = [... + mean(arpesStr.xdat(:)) - abs(0.25*range(arpesStr.xdat(:))),... + mean(arpesStr.xdat(:)) + abs(0.25*range(arpesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(arpesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(arpesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if nargin < 4; bTYPE = "Poly"; end +if isempty(solve_type); solve_type = "lsqcurvefit"; end +if isempty(ibgrnd) + ibgrnd{1} = [... + mean(arpesStr.xdat(:)) - abs(0.25*range(arpesStr.xdat(:))),... + mean(arpesStr.xdat(:)) + abs(0.25*range(arpesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(arpesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(arpesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if isempty(bTYPE); bTYPE = "Poly"; end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Total number of states to be fitted +nSTATES = length(cTYPE); +% -- Defining the initial conditions and limits of the optimisation method +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; +% -- Applying constraints on the parameters, based on the data +% --- parameters +if x0(2) < 0; x0(2) = 0; end % if FDT < 0, then make it 0 +if x0(3) < 0; x0(3) = 0; end % if FDW < 0, then make it 0 +if x0(5) < 0; x0(5) = 0; end % if MR < 0, then make it 0 +if x0(5) > 1; x0(5) = 1; end % if MR > 0, then make it 1 +% --- lower bounds +if lb(2) < 0; lb(2) = 0; end % if FDT < 0, then make it 0 +if lb(3) < 0; lb(3) = 0; end % if FDW < 0, then make it 0 +if lb(5) < 0; lb(5) = 0; end % if MR < 0, then make it 0 +if lb(5) > 1; lb(5) = 1; end % if MR > 0, then make it 1 +% --- upper bounds +if ub(2) < 0; ub(2) = 0; end % if FDT < 0, then make it 0 +if ub(3) < 0; ub(3) = 0; end % if FDW < 0, then make it 0 +if ub(5) < 0; ub(5) = 0; end % if MR < 0, then make it 0 +if ub(5) > 1; ub(5) = 1; end % if MR > 0, then make it 1 +for i = 1:nSTATES + % --- parameters + if x0(5+i) < 0; x0(5+i) = 0; end % if INT < 0, then make it 0 + if x0(8+i) < 0; x0(8+i) = 0; end % if FWHM < 0, then make it 0 + % --- lower bounds + if lb(5+i) < 0; lb(5+i) = 0; end % if INT < 0, then make it 0 + if lb(8+i) < 0; lb(8+i) = 0; end % if FWHM < 0, then make it 0 + % --- upper bounds + if ub(5+i) < 0; ub(5+i) = 0; end % if INT < 0, then make it 0 + if ub(8+i) < 0; ub(8+i) = 0; end % if FWHM < 0, then make it 0 +end +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - DEFINING THE EDC DATA AND FITTING ARGUMENTS +% -- Extracting the data to be fitted +[roi_xdat, roi_ydat, roi_bgrnd] = PESBackground(arpesStr.xdat, arpesStr.ydat, bTYPE, x0(end-2), x0(end-1), x0(end), ibgrnd{4}); +% -- Defining a structure that stores all relevant model and data variables +ARPESObj = arpesStr; +ARPESObj.nSTATES = nSTATES; +ARPESObj.roi_xdat = roi_xdat; +ARPESObj.roi_ydat = roi_ydat; +ARPESObj.roi_bgrnd = roi_bgrnd; +ARPESObj.roi_ydat_sbtr = ARPESObj.roi_ydat - ARPESObj.roi_bgrnd; +% -- Appending the input arguments to the global variable +ARPESObj.fit_args.solve_type = solve_type; +ARPESObj.fit_args.modelFunc = modelFunc; +ARPESObj.fit_args.cTYPE = cTYPE; +ARPESObj.fit_args.iparams = iparams; +ARPESObj.fit_args.bTYPE = bTYPE; +ARPESObj.fit_args.ibgrnd = ibgrnd; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 5e3; +FuncTol = 1e-7; % 1e-7; +StepTol = 1e-7; % 1e-7; +OptTol = 1e-7; % 1e-7; +ConTol = 1e-7; % 1e-7; +FinDiffRelStep = 1e-5; % 1e-5; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; +%% - 3.1 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR CURVE FITTING +if solve_type == "lsqcurvefit" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqcurvefit,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqcurvefit(@(x,roi_xdat) full_pes_function(x,roi_xdat,ARPESObj), x0, roi_xdat, roi_ydat, lb, ub, options); +%% - 3.2 - LOCAL SOLVER: UNBOUNDED LEAST SQUARES NONLINEAR REGRESSION FIT +elseif solve_type == "nlinfit" + % -- Defining the optimisation options for the simulated annealing method + options = statset(... + 'MaxFunEvals', MaxFunEvals,... + 'MaxIter', MaxIter,... + 'TolFun', FuncTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,R,J,CovB,MSE,ErrorModelInfo] = nlinfit(roi_xdat, roi_ydat, @(x,roi_xdat) full_pes_function(x,roi_xdat,ARPESObj), x0, options); +%% - 3.3 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,grad,hessian] = fminunc(@(x) minimize_function(x,ARPESObj), x0, options); +%% - 3.4 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,ARPESObj), x0, [], [], [], [], lb, ub, [], options); +%% - 3.5 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR LEAST SQUARES PROBLEMS +elseif solve_type == "lsqnonlin" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqnonlin,... + 'Algorithm', 'levenberg-marquardt',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqnonlin(@(x) minimize_function(x,ARPESObj), x0, lb, ub, options); +%% - 3.6 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,ARPESObj), x0, lb, ub, options); +end + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.modelFunc = modelFunc; +fitStr.cTYPE = cTYPE; +fitStr.iparams = iparams; +fitStr.bTYPE = bTYPE; +fitStr.ibgrnd = ibgrnd; +fitStr.nSTATES = length(cTYPE); +%% 4.2 - Storing the XPS data, background, model and minimisation variables +% -- Extracting the original data +fitStr.xdat = arpesStr.xdat; +fitStr.ydat = arpesStr.ydat; +% -- Extracting the X-DOMAIN and DATA +[fitStr.X, fitStr.D] = fit_data(params, ARPESObj); +% -- Extracting the MODEL +fitStr.M = fit_model(params, ARPESObj); +% -- Extracting the BACKGROUND +fitStr.B = fit_background(params, ARPESObj); +% -- Extracting the DATA - BACKGROUND +fitStr.DB = fitStr.D - fitStr.B; +fitStr.MB = fitStr.M + fitStr.B; +% -- Extracting the RESIDUALS (R = D - (M + B)) +fitStr.R = fitStr.D - (fitStr.M + fitStr.B); +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ = sum(fitStr.R.^2 ./ abs(fitStr.M + fitStr.B)); +fitStr.MINFUN = minimize_function(params, ARPESObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables for the PES background +fitStr.bPARAMS = params(end-2:end); +fitStr.LHS = fitStr.bPARAMS(1); +fitStr.RHS = fitStr.bPARAMS(2); +fitStr.BGR = fitStr.bPARAMS(3); +%% 4.4 - Storing the final fit parameters +fitStr.params = params; +fitStr.FDEF = params(1); % scalar of the FDD Fermi-Level position. +fitStr.FDT = params(2); % scalar of the FDD temperature. +fitStr.FDW = params(3); % scalar of the FDD Gaussian width after convolution. +fitStr.BOFF = params(4); % scalar of the band offset +fitStr.MR = params(5); % scalar of the Mixing Ratio: 0 for pure Gaussian, 1 is for pure Lorentzian. +fitStr.INT = params(6:6+fitStr.nSTATES-1); % scalar of the peak intensity of PE curve. +fitStr.FWHM = params(6+fitStr.nSTATES:6+2*fitStr.nSTATES-1); % scalar of the FWHM of the PE curve. +%% 4.4 - Storing the final fit variables of each PES curve component +fitStr.XX = linspace(min(fitStr.X(:)), max(fitStr.X(:)), 1e3)'; +fitStr.YY = zeros(size(fitStr.XX)); +for i = 1:fitStr.nSTATES + BE(i) = modelFunc{i}(fitStr.BOFF); + % --- Best fit components on new domain + fitStr.cYY(:,i) = PESCurve_FDD(fitStr.XX, fitStr.cTYPE(i),... + BE(i), fitStr.INT(i), fitStr.FWHM(i), fitStr.MR, 0, 0, 0, 0,... + fitStr.FDEF, fitStr.FDT, fitStr.FDW); + fitStr.YY = fitStr.YY + fitStr.cYY(:,i); + % --- Storing each curve parameter + fitStr.BE(i) = BE(i); + % --- Storing the curve area information + fitStr.AREA(i) = trapz(fitStr.XX, fitStr.cYY(:,i)); +end +% --- Storing the normalised area contribution for quantification +fitStr.AREA0 = fitStr.AREA ./ trapz(fitStr.XX, fitStr.YY); + +end + +%% DEFINING THE RESIDUAL MINIMISATION FUNCTION TO BE MINIMISED +function MINFUN = minimize_function(x, ARPESObj) + % - 1 - Extracting the DATA + [~, D] = fit_data(x, ARPESObj); + % - 2 - Extracting the MODEL + M = fit_model(x, ARPESObj); + % - 3 - Extracting the BACKGROUND + B = fit_background(x, ARPESObj); + % - 4 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - (M + B); + % - 5 - Extracting the CHI-SQUARED value to be minimised + MINFUN = sum(R.^2 ./ (M + B)); +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE XPS DATA TO BE FITTED +function [X, D] = fit_data(x, ARPESObj) + [X, D, ~] = PESBackground(ARPESObj.xdat, ARPESObj.ydat, ARPESObj.fit_args.bTYPE, x(end-2), x(end-1), x(end), ARPESObj.fit_args.ibgrnd{4}); + D(isnan(D)) = 0; + if size(D, 2) > 1; D = D'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES BACKGROUND +function B = fit_background(x, ARPESObj) + [~, ~, B] = PESBackground(ARPESObj.xdat, ARPESObj.ydat, ARPESObj.fit_args.bTYPE, x(end-2), x(end-1), x(end), ARPESObj.fit_args.ibgrnd{4}); + B(isnan(B)) = 0; + if size(B, 2) > 1; B = B'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES CURVE FIT +function M = fit_model(x, ARPESObj) + % -- Extracting + modelFunc = ARPESObj.fit_args.modelFunc; + cTYPE = ARPESObj.fit_args.cTYPE; + % -- Extracting the input variables for the fit + FDEF = x(1); % scalar of the FDD Fermi-Level position. + FDT = x(2); % scalar of the FDD temperature. + FDW = x(3); % scalar of the FDD Gaussian width after convolution. + BOFF = x(4); % scalar of the band offset + MR = x(5); % scalar of the Mixing Ratio: 0 for pure Gaussian, 1 is for pure Lorentzian. + INT = x(6:6+ARPESObj.nSTATES-1); % scalar of the peak intensity of PE curve. + FWHM = x(6+ARPESObj.nSTATES:6+2*ARPESObj.nSTATES-1); % scalar of the FWHM of the PE curve. + % - 1 - Extract the curve component for each state + M = zeros(size(ARPESObj.roi_xdat)); % XPS model data + for i = 1:ARPESObj.nSTATES + BE = modelFunc{i}(BOFF); + cYY(:,i) = PESCurve_FDD(ARPESObj.roi_xdat, cTYPE(i), BE, INT(i), FWHM(i), MR, 0, 0, 0, 0, FDEF, FDT, FDW); + M = M + cYY(:,i); + end + M(isnan(M)) = 0; + if size(M, 2) > 1; M = M'; end +end + +%% DEFINING THE FINAL FUNCTION THAT DESCRIBES THE PES CURVE TO BE FITTED +function MB = full_pes_function(x, xdat, ARPESObj) + % - 1 - Extract the curve component for each state + modelFunc = ARPESObj.fit_args.modelFunc; + cTYPE = ARPESObj.fit_args.cTYPE; + % -- Extracting the input variables for the fit + FDEF = x(1); % scalar of the FDD Fermi-Level position. + FDT = x(2); % scalar of the FDD temperature. + FDW = x(3); % scalar of the FDD Gaussian width after convolution. + BOFF = x(4); % scalar of the band offset + MR = x(5); % scalar of the Mixing Ratio: 0 for pure Gaussian, 1 is for pure Lorentzian. + INT = x(6:6+ARPESObj.nSTATES-1); % scalar of the peak intensity of PE curve. + FWHM = x(6+ARPESObj.nSTATES:6+2*ARPESObj.nSTATES-1); % scalar of the FWHM of the PE curve. + % - 1 - Extract the curve component for each state + M = zeros(size(ARPESObj.roi_xdat)); % XPS model data + for i = 1:ARPESObj.nSTATES + BE = modelFunc{i}(BOFF); + cYY(:,i) = PESCurve_FDD(xdat, cTYPE(i), BE, INT(i), FWHM(i), MR, 0, 0, 0, 0, FDEF, FDT, FDW); + M = M + cYY(:,i); + end + M(isnan(M)) = 0; + if size(M, 2) > 1; M = M'; end + % - 3 - Determine the background to be used + [B_xdat, ~, B] = PESBackground(xdat, ARPESObj.roi_ydat, ARPESObj.fit_args.bTYPE, x(end-2), x(end-1), x(end), ARPESObj.fit_args.ibgrnd{4}); + B = interp1(B_xdat, B, xdat); + % - 4 - Final output is the sum of the model and background + MB = M + B; + MB(isnan(MB)) = 0; if size(MB, 2) > 1; MB = MB'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff1D fitting/arpes2boff1D_view_fit.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff1D fitting/arpes2boff1D_view_fit.m new file mode 100644 index 0000000..3ce62d4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff1D fitting/arpes2boff1D_view_fit.m @@ -0,0 +1,85 @@ +function fig = arpes2boff1D_view_fit(fitStr) +% fig = arpes2boff1D_view_fit(fitStr) +% This function is used to plot the results of the curve fitting +% performed by 'fitStr = arpes2boff1D_solver(...)'. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - fitStr: MATLAB data-structure that contains all fit parameters / variables / information +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% Default parameters +% -- Initialising the plot parameters +pp = plot_props(); + +%% - 1 - FIGURE WITH BACKGROUND AND XPS FITS +%% - 1.1 - INITIALISING THE FIGURE +fig = figure(); set(fig, 'Name', 'PES Curve Fitting'); +fig.Position(3) = 2.5*pp.fig5x4(1); +fig.Position(4) = pp.fig5x4(2); +%% - 1.2 - PLOTTING THE RAW DATA AND BEST FIT BACKGROUND +subplot(121); hold on; +% -- Plotting the ROI, LHS and RHS analysis windows +ROI = [fitStr.X(1), fitStr.X(end)]; +LHS = ROI(1) + 0.05.*[-1,1].*range(fitStr.xdat(:)); +RHS = ROI(2) + 0.05.*[-1,1].*range(fitStr.xdat(:)); +hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e6, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); +hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting a vertical line to show the ROI +a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +a.Annotation.LegendInformation.IconDisplayStyle = 'off'; +b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting the 1D data +plot(fitStr.xdat, fitStr.ydat, 'b-', 'linewidth', 0.5); +plot(fitStr.X, fitStr.D, 'b-', 'linewidth', 2); +plot(fitStr.X, fitStr.B, 'r-', 'linewidth', 2); +plot(fitStr.X, fitStr.DB, 'k-', 'linewidth', 2); +gca_props(); title('Background Subtraction', 'interpreter', 'none', 'fontsize', 9); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); +% -- Determining the best limits for the plot +axLim_y = [fitStr.ydat; fitStr.DB]; +axis([min(fitStr.xdat(:)), max(fitStr.xdat(:)), min(axLim_y(:)), 1.1*max(axLim_y(:))]); +%% - 1.3 - PLOTTING THE RESIDUALS FOR THE BEST FIT TO THE DATA +subplot(4,2,8); hold on; +bar(fitStr.X, fitStr.R, 'facecolor', [0 0 0]); +gca_props(); grid on; +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +%% - 1.4 - PLOTTING THE BEST FIT CURVE COMPONENTS AND FINAL MODEL FIT +subplot(4,2,[2,4,6]); hold on; +% -- Plotting all of the curve components +for i = 1:fitStr.nSTATES + area(fitStr.XX, fitStr.cYY(:,i), 'FaceColor', pp.col.fit{i}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); + plot(fitStr.XX, fitStr.cYY(:,i), 'k-', 'linewidth', 0.25); +end +% -- Plotting the curve component energy locations +for i = 1:fitStr.nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + line([fitStr.BE(i), fitStr.BE(i)], [0, max(fitStr.cYY(:,i))],... + 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '-'); +end +% -- Plotting the experimental and fit spectra +plot(fitStr.X, fitStr.DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(fitStr.XX, fitStr.YY, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(fitStr.CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +if min(fitStr.DB(:)) < fitStr.YY; min_y_val = min(fitStr.DB(:)); +else; min_y_val = min(fitStr.YY(:)); +end +if min_y_val > 0; min_y_val = 0; end +axis([min(fitStr.X(:)), max(fitStr.X(:)), min_y_val, 1.10*max(fitStr.DB(:))]); +title("Best Fit PES Curves", 'interpreter', 'none', 'fontsize', 9); diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff1D fitting/arpes2boff1D_view_init.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff1D fitting/arpes2boff1D_view_init.m new file mode 100644 index 0000000..5455b58 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff1D fitting/arpes2boff1D_view_init.m @@ -0,0 +1,179 @@ +function fig = arpes2boff1D_view_init(arpesStr, modelFunc, cTYPE, iparams, bTYPE, ibgrnd) +% fig = arpes2boff1D_view_init(arpesStr, modelFunc, cTYPE, iparams, bTYPE, ibgrnd) +% This function is used to plot the initial curve fitting model prior to +% using the 'arpes2boff1D_solver()' algorithm. This is used as an informative +% plot that allows you to view and create a better initial guess of the +% model prior to running the fitting algorithm. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - modelFunc: 1xN cell of functions that gives the band offset vs subband energy +% - cTYPE: 1xN vector of the type of curve to use for fitting. Default: "sGLA" ("pGLA", "DS") +% - iparams: 3 cells {x0}{lb}{ub} with 1x6 array: the model fit parameters [FDEF,FDT,FDW,BOFF,INT,FWHM] +% - bTYPE: string of the type of background to use for fitting. Default: "Poly" ("none", "Poly", "Shir", "LinShir", "StepFDDGpL", "StepFDDGsL") +% - ibgrnd: 4 cells {x0}{lb}{ub}{args} with 1x3 vectors of the background parameters: x0=lb=ub=[LHS,RHS,BGR], or argument of the background type args = [] +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% Default parameters +% - Default input parameters to use +if nargin < 6 + ibgrnd{1} = [... + mean(arpesStr.xdat(:)) - abs(0.25*range(arpesStr.xdat(:))),... + mean(arpesStr.xdat(:)) + abs(0.25*range(arpesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(arpesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(arpesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if nargin < 5; bTYPE = "Poly"; end +if isempty(ibgrnd) + ibgrnd{1} = [... + mean(arpesStr.xdat(:)) - abs(0.25*range(arpesStr.xdat(:))),... + mean(arpesStr.xdat(:)) + abs(0.25*range(arpesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(arpesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(arpesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if isempty(bTYPE); bTYPE = "Poly"; end +% -- Consistency check and finding the total number of curves +if size(iparams{1}, 1) ~= size(iparams{2}, 1) || size(iparams{2}, 1) ~= size(iparams{3}, 1) + error('The input parameter cell array is not a consistent size - check iparams input!'); +end + +%% Initialising variables +% -- Extracting the total number of states to be fitted +nSTATES = length(cTYPE); +% -- Extracting the input variables for the fit +FDEF = iparams{1}(1); % scalar of the FDD Fermi-Level position. +FDT = iparams{1}(2); % scalar of the FDD temperature. +FDW = iparams{1}(3); % scalar of the FDD Gaussian width after convolution. +BOFF = iparams{1}(4); % scalar of the band offset +MR = iparams{1}(5); % scalar of the Mixing Ratio: 0 for pure Gaussian, 1 is for pure Lorentzian. +INT = iparams{1}(6:6+nSTATES-1); % scalar of the peak intensity of PE curve. +FWHM = iparams{1}(6+nSTATES:6+2*nSTATES-1); % scalar of the FWHM of the PE curve. +% -- Extracting the limits +lbINT = iparams{2}(6:6+nSTATES-1); +ubINT = iparams{3}(6:6+nSTATES-1); +lbBOFF = iparams{2}(4); +ubBOFF = iparams{3}(4); +% -- Validity check on the inputs +if MR < 0; MR = 0; end +if MR > 1; MR = 1; end +if FDT < 0; FDT = 0; end +if FDW < 0; FDW = 0; end +for i = 1:length(INT) + if INT(i) < 0; INT(i) = 0; end + if lbINT(i) < 0; lbINT(i) = 0; end + if ubINT(i) < 0; ubINT(i) = 0; end +end + +%% - 1 - Extracting all background subtraction data and information +% -- Extracting the background +[X, D, B] = PESBackground(arpesStr.xdat, arpesStr.ydat,... + bTYPE, ibgrnd{1}(1), ibgrnd{1}(2), ibgrnd{1}(3), ibgrnd{4}); + +%% - 2 - Extracting all model data and information +% -- Extracting the original XPS data +xdat = arpesStr.xdat; +ydat = arpesStr.ydat; +% -- Initialising the vectors to contain XPS data +DB = D - B; % Data after being background subtracted +M = zeros(size(X)); % XPS model data +% -- Filing through all curve components and extracting them seperately +cYY = []; BE = []; +for i = 1:nSTATES + BE(i) = modelFunc{i}(BOFF); + cYY(:,i) = PESCurve_FDD(X, cTYPE(i), BE(i), INT(i), FWHM(i), MR, 0, 0, 0, 0, FDEF, FDT, FDW); + M = M + cYY(:,i); + lbBE(i) = modelFunc{i}(lbBOFF); + ubBE(i) = modelFunc{i}(ubBOFF); +end + +%% - 3 - Determination of the residuals and chi-squared +R = M - (D - B); % Residuals +CHISQ = sum(R.^2 ./ abs(M)); % Chi-squared + +%% - 4 - Plotting the model to be used for fitting +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'Initial PES Curve Fitting'); +fig.Position(3) = 2.5*pp.fig5x4(1); +fig.Position(4) = pp.fig5x4(2); +%% - 4.1 - PLOTTING THE RAW DATA AND BEST FIT BACKGROUND +subplot(121); hold on; +% -- Plotting the ROI, LHS and RHS analysis windows +ROI = [X(1), X(end)]; +LHS = ROI(1) + 0.05.*[-1,1].*range(xdat(:)); +RHS = ROI(2) + 0.05.*[-1,1].*range(xdat(:)); +hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e6, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); +hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting a vertical line to show the ROI +a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +a.Annotation.LegendInformation.IconDisplayStyle = 'off'; +b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting the 1D data +plot(xdat, ydat, 'b-', 'linewidth', 0.5); +plot(X, D, 'b-', 'linewidth', 2); +plot(X, B, 'r-', 'linewidth', 2); +plot(X, DB, 'k-', 'linewidth', 2); +gca_props(); title('Background Subtraction', 'interpreter', 'none', 'fontsize', 9); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); +% -- Determining the best limits for the plot +axLim_y = [ydat; DB]; +axis([min(xdat(:)), max(xdat(:)), min(axLim_y(:)), 1.1*max(axLim_y(:))]); +%% - 4.2 - PLOTTING THE BEST FIT CURVE COMPONENTS AND FINAL MODEL FIT +subplot(4,2,[2,4,6]); hold on; +% -- Plotting all of the curve components +for i = 1:nSTATES + area(X, cYY(:,i), 'FaceColor', pp.col.fit{i}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); + plot(X, cYY(:,i), 'k-', 'linewidth', 0.25); +end +% -- Plotting the curve component energy locations +for i = 1:nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + line([1,1]*BE(i), [0, max(cYY(:,i))],... + 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '-'); +end +% -- Plotting the experimental and fit spectra +plot(X, DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(X, M, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +axis([min(X(:)), max(X(:)), min(DB(:)), 1.10*max(DB(:))]); +title("Initial Curves for Fitting", 'interpreter', 'none', 'fontsize', 9); +%% - 4.3 - PLOTTING THE RESIDUALS FOR THE BEST FIT TO THE DATA +subplot(4,2,8); hold on; +bar(X, R, 'facecolor', [0 0 0]); +gca_props(); grid on; +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + +%% - 5 - Plotting the uncertainties to allow for easier optimisation +subplot(4,2,[2,4,6]); hold on; +for i = 1:nSTATES + %% - 5.1 - Plotting the primary peak uncertainties + x_vals = [lbBE(i), lbBE(i), ubBE(i), ubBE(i), lbBE(i)]; + y_vals = [lbINT(i), ubINT(i), ubINT(i), lbINT(i), lbINT(i)]; + patch(x_vals, y_vals, pp.col.fit{i}, 'FaceAlpha', 0.65, 'EdgeAlpha', 0); + %% - 5.2 - Adding text to identify each peak index + text(max(x_vals), max(y_vals), string(i), 'interpreter', 'latex', 'fontsize', 14, 'color', 'k'); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff2D fitting/arpes2boff2D_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff2D fitting/arpes2boff2D_solver.m new file mode 100644 index 0000000..a3c737b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff2D fitting/arpes2boff2D_solver.m @@ -0,0 +1,259 @@ +function fitStr = arpes2boff2D_solver(arpesStr, modelFunc, cTYPE, iparams, ibgrnd, solve_type) +% fitStr = arpes2boff2D_solver(arpesStr, modelFunc, cTYPE, iparams, ibgrnd, solve_type) +% Function that is used to fit N-parabolic dispersions to ARPES data, by +% defining the energy/momentum minimum and gaussian broadening, and +% effective mass of each subband state. A Fermi-Dirac Distribution is +% also used with a linear background, for states that are close to the +% Fermi edge. Constrained so that the subband energies are given by a +% functional form modelFunc. +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - modelFunc: 1xN cell of functions that gives the band offset vs subband energy +% - cTYPE: 1xN vector of the type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - iparams: 3 cells {x0}{lb}{ub} with 1x6 array: the model fit parameters [INT,XLOC,YLOC,XFWHM,YFWHM,MSTAR] +% - ibgrnd: 3 cells {x0}{lb}{ub} with 1x6 vector of the background parameters: [FDEF,FDT,FDW,BGR,BIN,BCO] +% - solve_type: String of either "fminunc", "fmincon", "lsqnonlin", "simulannealbnd" that sets the optimisation routine to use +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Default parameters & validity checks +% - Default input parameters to use +if nargin < 6; solve_type = "fmincon"; end +if isempty(solve_type); solve_type = "fmincon"; end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Extracting the total number of states to be fitted +n = length(cTYPE); +% -- Defining the initial conditions and limits of the parameters +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; +% -- Applying constraints on the parameters, based on the data +for i = 1:n + % --- parameters + if x0(i+2*n-1) < 0; x0(i+2*n-1) = 0; end % if INT < 0, then make it 0 + if x0(i+3*n-1) < 0; x0(i+3*n-1) = 0; end % if XFWHM < 0, then make it 0 + if x0(i+4*n-1) < 0; x0(i+4*n-1) = 0; end % if YFWHM < 0, then make it 0 + % --- lower bounds + if lb(i+2*n-1) < 0; lb(i+2*n-1) = 0; end % if INT < 0, then make it 0 + if lb(i+3*n-1) < 0; lb(i+3*n-1) = 0; end % if XFWHM < 0, then make it 0 + if lb(i+4*n-1) < 0; lb(i+4*n-1) = 0; end % if YFWHM < 0, then make it 0 + % --- upper bounds + if ub(i+2*n-1) < 0; ub(i+2*n-1) = 0; end % if INT < 0, then make it 0 + if ub(i+3*n-1) < 0; ub(i+3*n-1) = 0; end % if XFWHM < 0, then make it 0 + if ub(i+4*n-1) < 0; ub(i+4*n-1) = 0; end % if YFWHM < 0, then make it 0 +end +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - DEFINING THE ARPES DATA AND FITTING ARGUMENTS +% -- Defining global variable that stores all relevant model and data variables +ARPESObj = struct(); +ARPESObj.arpesStr = arpesStr; +% -- Appending the input arguments to the global variable +ARPESObj.fit_args.solve_type = solve_type; +ARPESObj.fit_args.cTYPE = cTYPE; +ARPESObj.fit_args.modelFunc = modelFunc; +ARPESObj.fit_args.iparams = iparams; +ARPESObj.fit_args.ibgrnd = ibgrnd; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 1e4; +FuncTol = 1e-12; +StepTol = 1e-12; +OptTol = 1e-12; +ConTol = 1e-12; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; +%% - 3.1 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +if solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fminunc(@(x) minimize_function(x,ARPESObj), x0, options); +%% - 3.2 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,ARPESObj), x0, [], [], [], [], lb, ub, [], options); +%% - 3.3 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR LEAST SQUARES PROBLEMS +elseif solve_type == "lsqnonlin" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqnonlin,... + 'Algorithm', 'levenberg-marquardt',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqnonlin(@(x) minimize_function(x,ARPESObj), x0, lb, ub, options); +%% - 3.4 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,ARPESObj), x0, lb, ub, options); +end + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.modelFunc = modelFunc; +fitStr.iparams = iparams; +fitStr.ibgrnd = ibgrnd; +%% 4.2 - Storing the ARPES data, background, model and minimisation variables +[ARPES, MODEL] = extract_arpes_and_model(params, ARPESObj.arpesStr, cTYPE, modelFunc); +% -- Storing the domain and range +fitStr.kx = MODEL.kx; +fitStr.eb = MODEL.eb; +% -- x- and y-axis limits +fitStr.kx_lims = [min(fitStr.kx(:)), max(fitStr.kx(:))]; +fitStr.eb_lims = [min(fitStr.eb(:)), max(fitStr.eb(:))]; +% -- Extracting the DATA +fitStr.D = ARPES.data; +% -- Extracting the MODEL +fitStr.M = MODEL.data; +% -- Extracting the RESIDUALS (R = D - M) +fitStr.R = fitStr.D - fitStr.M; +fitStr.Rx = mean(fitStr.R, 1); % R in 1D along x +fitStr.Ry = mean(fitStr.R, 2); % R in 1D along y +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ2D = fitStr.R.^2 ./ abs(fitStr.M); +fitStr.CHISQx = mean(fitStr.CHISQ2D, 1); % CHISQ in 1D along x +fitStr.CHISQy = mean(fitStr.CHISQ2D, 2); % CHISQ in 1D along y +fitStr.CHISQ = sum(sum(fitStr.CHISQ2D)); +fitStr.MINFUN = minimize_function(params, ARPESObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables for the ARPES model fit +fitStr.params = params; +fitStr.nSTATES = length(cTYPE); +fitStr.cTYPE = cTYPE; +% - Extracting parabolic parameters +fitStr.BOFF = params(1); +fitStr.XLOC = params(2:2+n-1); +fitStr.YLOC = []; for i = 1:n; fitStr.YLOC(i) = modelFunc{i}(fitStr.BOFF); end +fitStr.INT = params(2+n:2+2*n-1); +fitStr.XFWHM = params(2+2*n:2+3*n-1); +fitStr.YFWHM = params(2+3*n:2+4*n-1); +fitStr.MSTAR = params(2+4*n:2+5*n-1); +fitStr.FDEF = params(end-5); +fitStr.FDT = params(end-4); +fitStr.FDW = params(end-3); +fitStr.BGR = params(end-2); +fitStr.BIN = params(end-1); +fitStr.BCO = params(end); +%% 4.4 - Storing the Eb(kx) dispersions +fitStr.nkx = linspace(fitStr.kx_lims(1), fitStr.kx_lims(2), 1e3); +fitStr.neb = {}; +for i = 1:n + fitStr.neb{i} = eb_calc(fitStr.nkx, fitStr.XLOC(i), fitStr.YLOC(i), fitStr.MSTAR(i)); +end +end + +%% DEFINING THE FUNCTION TO BE MINIMISED VIA GLOBAL OPTIMISATION METHODS +function MINFUN = minimize_function(x, ARPESObj) + [ARPES, MODEL] = extract_arpes_and_model(x, ARPESObj.arpesStr, ARPESObj.fit_args.cTYPE, ARPESObj.fit_args.modelFunc); + % - 1 - Extracting the DATA + D = ARPES.data; + % - 2 - Extracting the MODEL + M = MODEL.data; + % - 3 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - M; + % - 5 - Extracting the CHI-SQUARED value to be minimised + % MINFUN = std2(R.^2 ./ abs(M + B)); % This was found to yield the lowest value for R^2, rather than sum + MINFUN = sum(sum(R.^2 ./ abs(M))); % This is the chi-sqaured +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE ARPES AND MODEL DATA CONSISTENTLY +function [ARPES, MODEL] = extract_arpes_and_model(x, arpesStr, cTYPE, modelFunc) + % 1 - Initialising variables + n = length(cTYPE); + % - Extracting parabolic parameters + BOFF = x(1); % scalar of the band offset + XLOC = x(2:2+n-1); % scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion. + INT = x(2+n:2+2*n-1); % scalar of the peak intensity of 2D PE curve. + XFWHM = x(2+2*n:2+3*n-1); % scalar of the x-axis FWHM for each Gaussian (k-resolution) + YFWHM = x(2+3*n:2+4*n-1); % scalar of the y-axis FWHM for each Gaussian (Eb-resolution) + MSTAR = x(2+4*n:2+5*n-1); % scalar of the effective mass, which governs the curvature of the parabola. + % - Extracting the binding energy of each subband + YLOC = []; + for i = 1:n + YLOC(i) = modelFunc{i}(BOFF); % scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion. + end + % - Extracting background parameters + FDEF = x(end-5); % scalar of the FDD Fermi-Level position. + FDT = x(end-4); % scalar of the FDD temperature. + FDW = x(end-3); % scalar of the FDD Gaussian width after convolution. + BGR = x(end-2); % scalar of the gradient of the linear background. + BIN = x(end-1); % scalar of the y-intercept of the linear background. + BCO = x(end); % scalar of the constant background y-offset value. + % - Extracting the kx and eb limits + kx_lims = [min(arpesStr.kx(:)), max(arpesStr.kx(:))]; + eb_lims = [min(arpesStr.eb(:)), max(arpesStr.eb(:))]; + % 2 - Extracting the constructed MODEL data + KX = linspace(kx_lims(1), kx_lims(2), size(arpesStr.kx,2)); + EB = linspace(eb_lims(1), eb_lims(2), size(arpesStr.eb,1))'; + MODEL_DATA = ARPESCurve_FDDGpL(KX, EB, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO); +% MODEL_DATA = ARPESCurveNorm_FDDGpL(KX, EB, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO); + ARPES_DATA = arpesStr.data; + % - Removing any NaN values + MODEL_DATA(isnan(MODEL_DATA)) = 0; + ARPES_DATA(isnan(ARPES_DATA)) = 0; + % 3 - Defining the ARPES data structure + ARPES = struct(); + ARPES.kx = KX; + ARPES.kx_step = mean(diff(KX(:))); + ARPES.kx_lims = kx_lims; + ARPES.eb = EB; + ARPES.eb_step = mean(diff(EB(:))); + ARPES.eb_lims = eb_lims; + ARPES.data = ARPES_DATA; + % 4 - Defining the MODEL data structure + MODEL = struct(); + MODEL.kx = KX; + MODEL.kx_step = mean(diff(KX(:))); + MODEL.kx_lims = kx_lims; + MODEL.eb = EB; + MODEL.eb_step = mean(diff(EB(:))); + MODEL.eb_lims = eb_lims; + MODEL.data = MODEL_DATA; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff2D fitting/arpes2boff2D_view_fit.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff2D fitting/arpes2boff2D_view_fit.m new file mode 100644 index 0000000..f919548 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff2D fitting/arpes2boff2D_view_fit.m @@ -0,0 +1,135 @@ +function fig = arpes2boff2D_view_fit(fitStr) +% fig = arpes2boff2D_view_fit(fitStr) +% This function is used to plot the results of the curve fitting +% performed by 'fitStr = arpes2boff2D_solver(...)'. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - fitStr: MATLAB data-structure that contains all fit parameters / variables / information +% +% OUT: +% - fig: figure output + +%% Initialising input variables +% -- Defining the values of the EDC cut figures +win = abs(0.05*range(fitStr.kx(:))); +val1 = mean(fitStr.kx(:)); +val2 = mean(fitStr.kx(:)) - abs(0.10*range(fitStr.kx(:))); +val3 = mean(fitStr.kx(:)) + abs(0.10*range(fitStr.kx(:))); + +%% - 1 - PLOTTING THE FITTED DATA +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'arpes2nbola_view_fit()'); +fig.Position(3) = 4.*pp.fig5x4(1); +fig.Position(4) = 2.*pp.fig5x4(2); +%% - 1.1 - Plotting the MODEL data +axs(1) = subplot(3,7,[1,2,8,9]); hold on; +ImData(fitStr.kx, fitStr.eb, fitStr.M); +for i = 1:fitStr.nSTATES; plot(fitStr.nkx, fitStr.neb{i}, 'r:', 'linewidth', 3); end +img_props(); +xlabel(' $$ k_{//} [A^{-1}] $$', 'interpreter', 'latex'); +ylabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +axis([fitStr.kx_lims, fitStr.eb_lims]); axis square; +caxis([min(fitStr.M(:)), max(fitStr.M(:))]); +title('Best fit model data'); + +%% - 4.2 - Plotting the ARPES data +axs(2) = subplot(3,7,[3,4,10,11]); hold on; +ImData(fitStr.kx, fitStr.eb, fitStr.D); img_props(); +for i = 1:fitStr.nSTATES; plot(fitStr.nkx, fitStr.neb{i}, 'r:', 'linewidth', 3); end +xlabel(' $$ k_{//} [A^{-1}] $$', 'interpreter', 'latex'); +ylabel('', 'interpreter', 'latex'); +axis([fitStr.kx_lims, fitStr.eb_lims]); axis square; +title('ARPES data that is fitted'); +caxis([min(fitStr.D(:)), max(fitStr.D(:))]); +% -- Plotting the EDC cut lines +line([1 1].*val1, [-1e5, 1e5], 'Color', pp.col.fit{1}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); +line([1 1].*val2, [-1e5, 1e5], 'Color', pp.col.fit{2}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); +line([1 1].*val3, [-1e5, 1e5], 'Color', pp.col.fit{3}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); + +%% - 4.6.1 - LHS and RHS EDCs +axs(7) = subplot(3,7,[17,18]); hold on; +% -- Extracting the LHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.D, 'edc', val2 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.M, 'edc', val2 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{2}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Extracting the RHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.D, 'edc', val3 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.M, 'edc', val3 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{3}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +gca_props(); grid on; +xlabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); + +%% - 4.3 - Plotting the 2D residuals +axs(3) = subplot(3,7,[5,6,12,13]); hold on; +ImData(fitStr.kx, fitStr.eb, fitStr.CHISQ2D); img_props(); +axis([fitStr.kx_lims, fitStr.eb_lims]); +title('Chi-Squared'); +% -- Add annotation for the quality of fit +text(0.04, 0.94, "$$ \chi^2 = $$ " + string(fitStr.CHISQ),... + 'interpreter', 'latex', 'fontsize', 16, 'color', 'w', 'Units','normalized'); +% -- Make the colormap bipolar (negative values blue, positive is red) +colormap(axs(3),'jet'); +% -- Make the colormap bipolar (negative values blue, positive is red) +ylabel('', 'interpreter', 'latex'); +xlabel(''); + +%% - 4.4 - Plotting the 1D residuals along x +axs(4) = subplot(3,7,[19,20]); hold on; +bar(fitStr.kx, fitStr.CHISQx); +gca_props(); grid on; +xlabel(' $$ k_{//} [A^{-1}] $$', 'interpreter', 'latex'); +ylabel('$$ \bf \chi^2(x) $$', 'Interpreter', 'latex'); +xlim(fitStr.kx_lims); +ax = gca; ax.YAxisLocation = 'right'; + +%% - 4.5 - Plotting the 1D residuals along y +axs(5) = subplot(3,7,[7,14]); hold on; +barh(fitStr.eb, fitStr.CHISQy); +gca_props(); grid on; +ylabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +xlabel('$$ \bf \chi^2(y) $$', 'Interpreter', 'latex'); +ylim(fitStr.eb_lims); +ax = gca; ax.YAxisLocation = 'right'; + +%% - 4.6 - Plotting best fit EDCs +%% - 4.6.1 - Gamma EDCs +axs(6) = subplot(3,7,[15,16]); hold on; +% -- Extracting the EDCs +[ARPES_XCut, ARPES_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.D, 'edc', val1 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.M, 'edc', val1 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{1}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Plotting the sub-band energies +for i = 1:fitStr.nSTATES; line([1 1]*fitStr.YLOC(i), [-1e5, 1e5], 'Color', 'r', 'LineWidth', 2, 'Linestyle', ':'); end +gca_props(); grid on; +ylabel('$$ Intensity $$', 'Interpreter', 'latex'); +xlabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +axis([min(ARPES_XCut(:)), max(ARPES_XCut(:)), 0, 1.25*max(ARPES_DCut(:))]); +%% - 4.6.1 - LHS and RHS EDCs +axs(7) = subplot(3,7,[17,18]); hold on; +% -- Extracting the LHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.D, 'edc', val2 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.M, 'edc', val2 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{2}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Extracting the RHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.D, 'edc', val3 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.M, 'edc', val3 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k:', 'color', pp.col.fit{3}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k:', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +gca_props(); grid on; +xlabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +axis([min(ARPES_XCut(:)), max(ARPES_XCut(:)), 0, 1.25*max(ARPES_DCut(:))]); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff2D fitting/arpes2boff2D_view_init.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff2D fitting/arpes2boff2D_view_init.m new file mode 100644 index 0000000..bbb4d58 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2boff2D fitting/arpes2boff2D_view_init.m @@ -0,0 +1,215 @@ +function fig = arpes2boff2D_view_init(arpesStr, modelFunc, cTYPE, iparams, ibgrnd) +% fig = arpes2boff2D_view_init(arpesStr, modelFunc, cTYPE,iparams, ibgrnd) +% This function is used to plot the initial curve fitting model prior to +% using the 'arpes2boff2D_solver()' algorithm. This is used as an informative +% plot that allows you to view and create a better initial guess of the +% model prior to running the fitting algorithm. +% +% REQ. FUNCTIONS: none +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - modelFunc: 1xN cell of functions that gives the band offset vs subband energy +% - cTYPE: 1xN vector of the type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - iparams: 3 cells {x0}{lb}{ub} with 1x6 array: the model fit parameters [INT,XLOC,YLOC,XFWHM,YFWHM,MSTAR] +% - ibgrnd: 3 cells {x0}{lb}{ub} with 1x6 vector of the background parameters: [FDEF,FDT,FDW,BGR,BIN,BCO] +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Initialising variables +% -- Extracting the total number of states to be fitted +n = length(cTYPE); +% - Defining the initial conditions and limits of the parameters +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; +% - Making the ARPES and MODEL data consistent over a consistent domain +[ARPES, MODEL] = extract_arpes_and_model(x0, arpesStr, cTYPE, modelFunc); +% - Extracting the parabolic dispersions for each subband energy +sbn_kx = linspace(ARPES.kx_lims(1), ARPES.kx_lims(2), 1e3); +sbn_eb = {}; +XLOC = x0(2:2+n-1); +for i = 1:n; YLOC(i) = modelFunc{i}(x0(1)); end +MSTAR = x0(2+4*n:2+5*n-1); +for i = 1:length(YLOC) + sbn_eb{i} = eb_calc(sbn_kx, XLOC(i), YLOC(i), MSTAR(i)); +end + +%% - 1 - Determination of the residuals and chi-squared (the minimisation variable) +% - 1.1 - Extracting the DATA +D = ARPES.data; +% - 1.2 - Extracting the MODEL +M = MODEL.data; +% - 1.4 - Extracting the RESIDUALS +R = D - M; % residuals = data - model +Rx = mean(R, 1); % R in 1D along x +Ry = mean(R, 2); % R in 1D along y +% - 1.5 - Extracting the CHI-SQUARED value to be minimised +CHISQ2D = R.^2 ./ M; +CHISQxx = mean(CHISQ2D, 1); % CHISQ in 1D along x +CHISQyy = mean(CHISQ2D, 2); % CHISQ in 1D along y +% - 1.6 - Extracting the REDUCED CHI-SQUARED value including degrees of freedom +CHISQ = sum(sum(CHISQ2D)); + +%% - 2 - PLOTTING THE FINAL DATA COMPARED WITH MODEL AT BOFF = 0 eV +% -- Initialising the plot properties +win = abs(0.05*range(ARPES.kx(:))); +val1 = mean(ARPES.kx(:)); +val2 = mean(ARPES.kx(:)) - abs(0.10*range(ARPES.kx(:))); +val3 = mean(ARPES.kx(:)) + abs(0.10*range(ARPES.kx(:))); +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'Initial Model'); +fig.Position(3) = 4.*pp.fig5x4(1); +fig.Position(4) = 2.*pp.fig5x4(2); +%% - 2.1 - Plotting the model data +% -- Extracting the data matrix +data = M; +% -- Plotting the data +axs(1) = subplot(3,7,[1,2,8,9]); hold on; +ImData(MODEL.kx, MODEL.eb, data); +for i = 1:length(sbn_eb); plot(sbn_kx, sbn_eb{i}, 'r:', 'linewidth', 3); end +img_props(); +xlabel(' $$ k_{//} [A^{-1}] $$', 'interpreter', 'latex'); +ylabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +axis([MODEL.kx_lims, MODEL.eb_lims]); +caxis([min(data(:)), max(data(:))]); +axis square; +title('Initial model data'); + +%% - 2.2 - Plotting the ARPES data +axs(2) = subplot(3,7,[3,4,10,11]); hold on; +ImData(ARPES.kx, ARPES.eb, ARPES.data); img_props(); +for i = 1:length(sbn_eb); plot(sbn_kx, sbn_eb{i}, 'r:', 'linewidth', 3); end +xlabel(' $$ k_{//} [A^{-1}] $$', 'interpreter', 'latex'); +ylabel('', 'interpreter', 'latex'); +axis([ARPES.kx_lims, ARPES.eb_lims]); axis square; +caxis([min(ARPES.data(:)), max(ARPES.data(:))]); +title('ARPES data to be fitted'); +% -- Plotting the EDC cut lines +line([1 1].*val1, [-1e5, 1e5], 'Color', pp.col.fit{1}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); +line([1 1].*val2, [-1e5, 1e5], 'Color', pp.col.fit{2}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); +line([1 1].*val3, [-1e5, 1e5], 'Color', pp.col.fit{3}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); + +%% - 2.3 - Plotting the 2D residuals +axs(3) = subplot(3,7,[5,6,12,13]); hold on; +ImData(ARPES.kx, ARPES.eb, CHISQ2D); img_props(); +axis([ARPES.kx_lims, ARPES.eb_lims]); +title('Chi-Squared'); +% -- Add annotation for the quality of fit +text(0.04, 0.94, "$$ \chi^2 = $$ " + string(CHISQ),... + 'interpreter', 'latex', 'fontsize', 16, 'color', 'w', 'Units','normalized'); +% -- Make the colormap bipolar (negative values blue, positive is red) +colormap(axs(3),'jet'); +% -- Make the colormap bipolar (negative values blue, positive is red) +ylabel('', 'interpreter', 'latex'); +xlabel(''); + +%% - 2.4 - Plotting the 1D residuals along x +axs(4) = subplot(3,7,[19,20]); hold on; +bar(ARPES.kx, CHISQxx); +gca_props(); grid on; +xlabel(' $$ k_{//} [A^{-1}] $$', 'interpreter', 'latex'); +ylabel('$$ \bf \chi^2(x) $$', 'Interpreter', 'latex'); +xlim(ARPES.kx_lims); +ax = gca; ax.YAxisLocation = 'right'; + +%% - 2.5 - Plotting the 1D residuals along y +axs(5) = subplot(3,7,[7,14]); hold on; +barh(ARPES.eb, CHISQyy); +gca_props(); grid on; +ylabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +xlabel('$$ \bf \chi^2(y) $$', 'Interpreter', 'latex'); +ylim(ARPES.eb_lims); +ax = gca; ax.YAxisLocation = 'right'; + +%% - 2.6 - Plotting best fit EDCs +%% - 2.6.1 - Gamma EDCs +axs(6) = subplot(3,7,[15,16]); hold on; +% -- Extracting the EDCs +[ARPES_XCut, ARPES_DCut] = Cut(ARPES.kx, ARPES.eb, ARPES.data, 'edc', val1 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(MODEL.kx, MODEL.eb, MODEL.data, 'edc', val1 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{1}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Plotting the sub-band energies +for i = 1:length(YLOC); line([1 1]*YLOC(i), [-1e5, 1e5], 'Color', 'r', 'LineWidth', 2, 'Linestyle', ':'); end +gca_props(); grid on; +ylabel('$$ Intensity $$', 'Interpreter', 'latex'); +xlabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +axis([min(ARPES_XCut(:)), max(ARPES_XCut(:)), 0, 1.25*max(ARPES_DCut(:))]); +%% - 2.6.1 - LHS and RHS EDCs +axs(7) = subplot(3,7,[17,18]); hold on; +% -- Extracting the LHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(ARPES.kx, ARPES.eb, ARPES.data, 'edc', val2 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(MODEL.kx, MODEL.eb, MODEL.data, 'edc', val2 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{2}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Extracting the RHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(ARPES.kx, ARPES.eb, ARPES.data, 'edc', val3 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(MODEL.kx, MODEL.eb, MODEL.data, 'edc', val3 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{3}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +gca_props(); grid on; +xlabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +axis([min(ARPES_XCut(:)), max(ARPES_XCut(:)), 0, 1.25*max(ARPES_DCut(:))]); + +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE ARPES AND MODEL DATA CONSISTENTLY +function [ARPES, MODEL] = extract_arpes_and_model(x, arpesStr, cTYPE, modelFunc) + % 1 - Initialising variables + n = length(cTYPE); + % - Extracting parabolic parameters + BOFF = x(1); % scalar of the band offset + XLOC = x(2:2+n-1); % scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion. + INT = x(2+n:2+2*n-1); % scalar of the peak intensity of 2D PE curve. + XFWHM = x(2+2*n:2+3*n-1); % scalar of the x-axis FWHM for each Gaussian (k-resolution) + YFWHM = x(2+3*n:2+4*n-1); % scalar of the y-axis FWHM for each Gaussian (Eb-resolution) + MSTAR = x(2+4*n:2+5*n-1); % scalar of the effective mass, which governs the curvature of the parabola. + % - Extracting the binding energy of each subband + YLOC = []; + for i = 1:n + YLOC(i) = modelFunc{i}(BOFF); % scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion. + end + % - Extracting background parameters + FDEF = x(end-5); % scalar of the FDD Fermi-Level position. + FDT = x(end-4); % scalar of the FDD temperature. + FDW = x(end-3); % scalar of the FDD Gaussian width after convolution. + BGR = x(end-2); % scalar of the gradient of the linear background. + BIN = x(end-1); % scalar of the y-intercept of the linear background. + BCO = x(end); % scalar of the constant background y-offset value. + % - Extracting the kx and eb limits + kx_lims = [min(arpesStr.kx(:)), max(arpesStr.kx(:))]; + eb_lims = [min(arpesStr.eb(:)), max(arpesStr.eb(:))]; + % 2 - Extracting the constructed MODEL data + KX = linspace(kx_lims(1), kx_lims(2), size(arpesStr.kx,2)); + EB = linspace(eb_lims(1), eb_lims(2), size(arpesStr.eb,1))'; + MODEL_DATA = ARPESCurve_FDDGpL(KX, EB, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO); +% MODEL_DATA = ARPESCurveNorm_FDDGpL(KX, EB, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO); + ARPES_DATA = arpesStr.data; + % - Removing any NaN values + MODEL_DATA(isnan(MODEL_DATA)) = 0; + ARPES_DATA(isnan(ARPES_DATA)) = 0; + % 3 - Defining the ARPES data structure + ARPES = struct(); + ARPES.kx = KX; + ARPES.kx_step = mean(diff(KX(:))); + ARPES.kx_lims = kx_lims; + ARPES.eb = EB; + ARPES.eb_step = mean(diff(EB(:))); + ARPES.eb_lims = eb_lims; + ARPES.data = ARPES_DATA; + % 4 - Defining the MODEL data structure + MODEL = struct(); + MODEL.kx = KX; + MODEL.kx_step = mean(diff(KX(:))); + MODEL.kx_lims = kx_lims; + MODEL.eb = EB; + MODEL.eb_step = mean(diff(EB(:))); + MODEL.eb_lims = eb_lims; + MODEL.data = MODEL_DATA; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_parsolver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_parsolver.m new file mode 100644 index 0000000..5a60130 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_parsolver.m @@ -0,0 +1,313 @@ +function fitStr = arpes2model_parsolver(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims) +% fitStr = arpes2model_parsolver(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims) +% Function that runs a a Global Optimisation Algorithm based on Simulated +% Annealing to determine the best model fit to the input ARPES data and +% model (initial conditions and bounds). The temperature of the Simulated +% Annealing is set to walk a large span of the parameter space to ensure +% the global minimum is obtained. The minimisation function is based on +% minimising the value of chi-squared. Uses Parallel Processing. +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - modelStr: MATLAB data-structure that contains the initial model data. +% - iparams: 3 cells {x0}{lb}{ub} with [1×5] array: the model fit parameters [K0,KFWHM,EFWHM,MFP,BOFF,INT] +% - ibgrnd: 3 cells {x0}{lb}{ub} with [1×3] vector of the background parameters: [MX,MY,C] +% - solve_type: String of either "fminunc", "fmincon", "lsqnonlin", "simulannealbnd" that sets the optimisation routine to use +% - kx_lims: [1×2] vector of [minKx, maxKx], which defines the consistent kx fit window +% - eb_lims: [1×2] vector of [minEb, maxEb], which defines the consistent eb fit window +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Default parameters & validity checks +% - Default input parameters to use +if nargin < 7; eb_lims = mean(modelStr.eb(:)) + [-1,1].*0.95*range(modelStr.eb(:)); end +if nargin < 6; kx_lims = mean(modelStr.kx(:)) + [-1,1].*0.95*range(modelStr.kx(:)); end +if nargin < 5; solve_type = "fmincon"; end +if nargin < 4; ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1} - 0.01; ibgrnd{3} = ibgrnd{1} + 0.01; end +if isempty(eb_lims); eb_lims = mean(modelStr.eb(:)) + [-1,1].*0.95*range(modelStr.eb(:)); end +if isempty(kx_lims); kx_lims = mean(modelStr.eb(:)) + [-1,1].*0.95*range(modelStr.kx(:)); end +if isempty(solve_type); solve_type = "fmincon"; end +if isempty(ibgrnd); ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1}-0.01; ibgrnd{3} = ibgrnd{1}+0.01; end +% -- Validity check on the input variables +if kx_lims(1) < 0.95*min(modelStr.kx(:)); kx_lims(1) = 0.95*min(modelStr.kx(:)); end +if kx_lims(2) > 0.95*max(modelStr.kx(:)); kx_lims(2) = 0.95*max(modelStr.kx(:)); end +if eb_lims(1) < 0.95*min(modelStr.eb(:)); eb_lims(1) = 0.95*min(modelStr.eb(:)); end +if eb_lims(2) > 0.95*max(modelStr.eb(:)); eb_lims(2) = 0.95*max(modelStr.eb(:)); end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Defining the initial conditions and limits of the parameters +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; +% -- Applying constraints on the parameters, based on the data +% --- parameters +if x0(2) < 0; x0(2) = 0; end % if kxFWHM < 0, then make it 0 +if x0(3) < 0; x0(3) = 0; end % if ebFWHM < 0, then make it 0 +if x0(4) < min(modelStr.MFP(:)); x0(4) = min(modelStr.MFP(:)); end % if MFP < min available, then make it the min +if x0(4) > max(modelStr.MFP(:)); x0(4) = max(modelStr.MFP(:)); end % if MFP > max available, then make it the max +if x0(5) < min(modelStr.BOFF(:)); x0(5) = min(modelStr.BOFF(:)); end % if BOFF < min available, then make it the min +if x0(5) > max(modelStr.BOFF(:)); x0(5) = max(modelStr.BOFF(:)); end % if BOFF > max available, then make it the max +if x0(6) < 0; x0(6) = 0; end % if INT < 0, then make it 0 +% --- lower bounds +if lb(2) < 0; lb(2) = 0; end % if kxFWHM < 0, then make it 0 +if lb(3) < 0; lb(3) = 0; end % if ebFWHM < 0, then make it 0 +if lb(4) < min(modelStr.MFP(:)); lb(4) = min(modelStr.MFP(:)); end % if MFP < min available, then make it the min +if lb(4) > max(modelStr.MFP(:)); lb(4) = max(modelStr.MFP(:)); end % if MFP > max available, then make it the max +if lb(5) < min(modelStr.BOFF(:)); lb(5) = min(modelStr.BOFF(:)); end % if BOFF < min available, then make it the min +if lb(5) > max(modelStr.BOFF(:)); lb(5) = max(modelStr.BOFF(:)); end % if BOFF > max available, then make it the max +if lb(6) < 0; lb(6) = 0; end % if INT < 0, then make it 0 +% --- upper bounds +if ub(2) < 0; ub(2) = 0; end % if kxFWHM < 0, then make it 0 +if ub(3) < 0; ub(3) = 0; end % if ebFWHM < 0, then make it 0 +if ub(4) < min(modelStr.MFP(:)); ub(4) = min(modelStr.MFP(:)); end % if MFP < min available, then make it the min +if ub(4) > max(modelStr.MFP(:)); ub(4) = max(modelStr.MFP(:)); end % if MFP > max available, then make it the max +if ub(5) < min(modelStr.BOFF(:)); ub(5) = min(modelStr.BOFF(:)); end % if BOFF < min available, then make it the min +if ub(5) > max(modelStr.BOFF(:)); ub(5) = max(modelStr.BOFF(:)); end % if BOFF > max available, then make it the max +if ub(6) < 0; ub(6) = 0; end % if INT < 0, then make it 0 +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - DEFINING THE ARPES DATA AND FITTING ARGUMENTS +% -- Defining global variable that stores all relevant model and data variables +ARPESObj = struct(); +ARPESObj.arpesStr = arpesStr; +ARPESObj.modelStr = modelStr; +% -- Appending the input arguments to the global variable +ARPESObj.fit_args.solve_type = solve_type; +ARPESObj.fit_args.iparams = iparams; +ARPESObj.fit_args.ibgrnd = ibgrnd; +ARPESObj.fit_args.kx_lims = kx_lims; +ARPESObj.fit_args.eb_lims = eb_lims; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 1e4; +FuncTol = 1e-12; +StepTol = 1e-12; +OptTol = 1e-12; +ConTol = 1e-12; +FinDiffRelStep = 1e-5; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; +% -- Initialising parallel processing +nCPU_PCC_Work = 6; +nCPU_PSI_HPC_Merlin6 = 44; +myCluster = parcluster('local'); nCPU = myCluster.NumWorkers; +if isempty(gcp('nocreate')); poolobj = parpool('local', nCPU, 'IdleTimeout', Inf); end +%% - 3.1 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +if solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'UseParallel', true,... + 'Display', 'iter-detailed'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fminunc(@(x) minimize_function(x,ARPESObj), x0, options); +%% - 3.2 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol,... + 'UseParallel', true,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central',... + 'Display', 'iter-detailed'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,ARPESObj), x0, [], [], [], [], lb, ub, [], options); +%% - 3.3 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR LEAST SQUARES PROBLEMS +elseif solve_type == "lsqnonlin" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqnonlin,... + 'Algorithm', 'levenberg-marquardt',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqnonlin(@(x) minimize_function(x,ARPESObj), x0, lb, ub, options); +%% - 3.4 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol,... + 'UseParallel', true); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,ARPESObj), x0, lb, ub, options); +end +% -- Shutting down parallel processing +% delete(poolobj); + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.iparams = iparams; +fitStr.ibgrnd = ibgrnd; +%% 4.2 - Storing the ARPES data, background, model and minimisation variables +[ARPES, MODEL] = extract_arpes_and_model(params, ARPESObj.arpesStr, ARPESObj.modelStr, kx_lims, eb_lims); +% -- Storing the domain and range +fitStr.kx = MODEL.kx; +fitStr.eb = MODEL.eb; +% -- x- and y-axis limits +fitStr.kx_lims = [min(fitStr.kx(:)), max(fitStr.kx(:))]; +fitStr.eb_lims = [min(fitStr.eb(:)), max(fitStr.eb(:))]; +% -- Extracting the DATA +fitStr.D = fit_data(params, ARPES); +% -- Extracting the MODEL +fitStr.M = fit_model(params, MODEL); +% -- Extracting the BACKGROUND +fitStr.B = fit_background(params, MODEL); +% -- Extracting the DATA - BACKGROUND +fitStr.DB = fitStr.D - fitStr.B; +fitStr.MB = fitStr.M + fitStr.B; +% -- Extracting the RESIDUALS (R = D - (M + B)) +fitStr.R = fitStr.D - (fitStr.M + fitStr.B); +fitStr.Rx = mean(fitStr.R, 1); % R in 1D along x +fitStr.Ry = mean(fitStr.R, 2); % R in 1D along y +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ2D = fitStr.R.^2 ./ abs(fitStr.M + fitStr.B); +fitStr.CHISQx = mean(fitStr.CHISQ2D, 1); % CHISQ in 1D along x +fitStr.CHISQy = mean(fitStr.CHISQ2D, 2); % CHISQ in 1D along y +fitStr.CHISQ = sum(sum(fitStr.CHISQ2D)); +fitStr.MINFUN = minimize_function(params, ARPESObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables for the ARPES model fit +fitStr.params = params; +fitStr.K0 = params(1); +fitStr.KFWHM = params(2); +fitStr.EFWHM = params(3); +fitStr.MFP = params(4); +fitStr.BOFF = params(5); +fitStr.INT = params(6); +fitStr.MX = params(7); +fitStr.MY = params(8); +fitStr.C = params(9); +end + +%% DEFINING THE FUNCTION TO BE MINIMISED VIA GLOBAL OPTIMISATION METHODS +function MINFUN = minimize_function(x, ARPESObj) + [ARPES, MODEL] = extract_arpes_and_model(x, ARPESObj.arpesStr, ARPESObj.modelStr, ARPESObj.fit_args.kx_lims, ARPESObj.fit_args.eb_lims); + % - 1 - Extracting the DATA + D = fit_data(x, ARPES); + % - 2 - Extracting the MODEL + M = fit_model(x, MODEL); + % - 3 - Extracting the BACKGROUND + B = fit_background(x, MODEL); + % - 4 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - (M + B); + % - 5 - Extracting the CHI-SQUARED value to be minimised + % MINFUN = std2(R.^2 ./ abs(M + B)); % This was found to yield the lowest value for R^2, rather than sum + MINFUN = sum(sum(R.^2 ./ abs(M + B))); % This is the chi-sqaured +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE ARPES DATA TO BE FITTED +function D = fit_data(x, ARPES) + D = ARPES.data; + D(isnan(D)) = 0; +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE MODEL +function M = fit_model(x, MODEL) + % 1 - Initialising variables + kxFWHM = x(2); % scalar of kx-resolution (Gaussian FWHM of k-broadening) + ebFWHM = x(3); % scalar of eb-resolution (Gaussian FWHM of eb-broadening) + INT = x(6); % scalar of the intensity scaling factor + % 2 - Extracting the model curve based on the MFP and BOFF chosen + model_data = MODEL.data; + % 3 - Gaussian broadening the model in x- and y-dimensions + % -- Extracting the FWHM of the smoothing + kxFWHM = kxFWHM ./ abs(MODEL.kx_step); + ebFWHM = ebFWHM ./ abs(MODEL.eb_step); + % -- Gaussian smoothing + model_data = Gaco2(model_data, kxFWHM, ebFWHM); + % 4 - Intensity scaling + model_data = INT .* model_data; + % Assigning the final model + M = model_data; + M(isnan(M)) = 0; +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE PLANAR BACKGROUND +function B = fit_background(x, MODEL) + % 1 - Initialising variables + MX = x(end-2); % scalar of the x-gradient of the plane. + MY = x(end-1); % scalar of the y-gradient of the plane. + C = x(end); % scalar of the constant off-set of the plane. + % 2 - Creating a planar background to be subtracted + B = MX * MODEL.kx + MY * MODEL.eb + C; + B(isnan(B)) = 0; +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE ARPES AND MODEL DATA CONSISTENTLY +function [ARPES, MODEL] = extract_arpes_and_model(x, arpesStr, modelStr, kx_lims, eb_lims) + % 1 - Initialising variables + K0 = x(1); % scalar of kx-resolution (Gaussian FWHM of k-broadening) + MFP = x(4); % scalar of mean free path (associated with resolution of bands) + BOFF = x(5); % scalar of band-offset + % 2 - Cropping the ARPES data to extract dimensional size + [xDat_crop, yDat_crop, ~] = data_crop2D(arpesStr.kx, arpesStr.eb, arpesStr.data, kx_lims, eb_lims); + kx_length = size(xDat_crop,2); + eb_length = size(yDat_crop,1); + % 3 - Extracting the interpolated MODEL data + imodelStr = mstheory_interp(modelStr, BOFF, MFP); + % 4 - Making the ARPES and MODEL data have a consistent domain + KX = linspace(kx_lims(1), kx_lims(2), kx_length); + EB = linspace(eb_lims(1), eb_lims(2), eb_length)'; + ARPES_DATA = interpn(arpesStr.eb(:,1), arpesStr.kx(1,:)-K0, arpesStr.data, EB, KX); + MODEL_DATA = interpn(imodelStr.eb, imodelStr.kx, imodelStr.data, EB, KX); + % 5 - Data renormalisation + ARPES_DATA = ARPES_DATA - min(ARPES_DATA(:)); ARPES_DATA = ARPES_DATA ./ max(ARPES_DATA(:)); + MODEL_DATA = MODEL_DATA - min(MODEL_DATA(:)); MODEL_DATA = MODEL_DATA ./ max(MODEL_DATA(:)); + ARPES_DATA(isnan(ARPES_DATA)) = 0; + MODEL_DATA(isnan(MODEL_DATA)) = 0; + % 6 - Defining the ARPES data structure + ARPES.kx = KX; + ARPES.kx_step = mean(diff(KX(:))); + ARPES.kx_lims = kx_lims; + ARPES.eb = EB; + ARPES.eb_step = mean(diff(EB(:))); + ARPES.eb_lims = eb_lims; + ARPES.data = ARPES_DATA; + % 7 - Defining the MODEL data structure + MODEL.MFP = MFP; + MODEL.BOFF = BOFF; + MODEL.kx = KX; + MODEL.kx_step = mean(diff(KX(:))); + MODEL.kx_lims = kx_lims; + MODEL.eb = EB; + MODEL.eb_step = mean(diff(EB(:))); + MODEL.eb_lims = eb_lims; + MODEL.data = MODEL_DATA; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_parsolver_n_runs.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_parsolver_n_runs.m new file mode 100644 index 0000000..2e27fc4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_parsolver_n_runs.m @@ -0,0 +1,120 @@ +function [fitStr0, statStr] = arpes2model_parsolver_n_runs(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims, n_runs) +% [fitStr0, statStr] = arpes2model_parsolver_n_runs(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims, n_runs) +% Function that runs arpes2model_solver() N amount of independent times until +% convergence. The initial conditions are randomly sampled over the range +% of the input uncertainty. This allows the uncertainty in the best fit +% parameters to be determined by looking at the variance of the +% converged fit parameters. Uses Parallel Processing. +% +% REQ. FUNCTIONS: none +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - modelStr: MATLAB data-structure that contains the initial model data. +% - iparams: 3 cells {x0}{lb}{ub} with 1x5 array: the model fit parameters [K0,KFWHM,EFWHM,MFP,BOFF,INT] +% - ibgrnd: 3 cells {x0}{lb}{ub} with 1x3 vector of the background parameters: [MX,MY,C] +% - solve_type: String of either "fminunc", "fmincon", "lsqnonlin", "simulannealbnd" that sets the optimisation routine to use +% - kx_lims: [1x2] vector of [minKx, maxKx], which defines the consistent kx fit window +% - eb_lims: [1x2] vector of [minEb, maxEb], which defines the consistent eb fit window +% - n_runs: scalar value for the total number of independent runs +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information +% - statStr: MATLAB data-structure that contains all the statistical analysis + +%% Default parameters +% - Default input parameters to use +if nargin < 8; n_runs = 10; end +if nargin < 7; eb_lims = 0.95*[min(modelStr.eb(:)), max(modelStr.eb(:))]; end +if nargin < 6; kx_lims = 0.95*[min(modelStr.kx(:)), max(modelStr.kx(:))]; end +if nargin < 5; solve_type = "fmincon"; end +if nargin < 4; ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1} - 0.10; ibgrnd{3} = ibgrnd{1} + 0.10; end +if isempty(n_runs); n_runs = 10; end +if isempty(eb_lims); eb_lims = 0.95*[min(modelStr.eb(:)), max(modelStr.eb(:))]; end +if isempty(kx_lims); kx_lims = 0.95*[min(modelStr.kx(:)), max(modelStr.kx(:))]; end +if isempty(solve_type); solve_type = "fmincon"; end +if isempty(ibgrnd); ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1}-0.10; ibgrnd{3} = ibgrnd{1}+0.10; end +% - Total number of parameters +nParams = length(iparams{1}) + length(ibgrnd{1}); + +%% - 1 - Running the fitting algorithm N independent time for statistical analysis +% -- Initialising parallel processing +nCPU_PCC_Work = 6; +nCPU_PSI_HPC_Merlin6 = 44; +myCluster = parcluster('local'); nCPU = myCluster.NumWorkers; +if isempty(gcp('nocreate')); poolobj = parpool('local', nCPU, 'IdleTimeout', Inf); end +% -- Initialising variables +statStr = struct(); +statStr.n_runs = 1:n_runs; +fit = cell(n_runs,1); +params = zeros(n_runs, nParams); +CHISQ = zeros(n_runs,1); +% -- Running the fitting algorithm N independent times for analysis +parfor i = statStr.n_runs + if n_runs < 101; fprintf("Run %i / %i \n", i, n_runs); end + % --- Uniform sampling of the initial conditions + new_init_conds = iparams; + new_init_conds{1} = iparams{2} + (iparams{3}-iparams{2}) .* rand(size(iparams{2})); + % --- Executing the fit + fitStr = arpes2model_solver(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims); + % --- Storing the best fit parameters for statistical analysis + fit{i} = fitStr; + % --- Storing the best fit parameters for statistical analysis + params(i,:) = fit{i}.params'; + CHISQ(i) = fit{i}.CHISQ; +end +% -- Shutting down parallel processing +% delete(poolobj); +% -- Assigning variables +statStr.fit = fit; +statStr.params = params; +statStr.CHISQ = CHISQ; +% -- Storing the parameter labels +statStr.params_label = {'K0', 'KFWHM', 'EFWHM', 'MFP', 'BOFF', 'INT', 'MX', 'MY', 'C'}; + +%% - 2 - Storing the fit structure that has the smallest value of chi-squared +[~, nCHISQ] = min(statStr.CHISQ(:)); +fitStr0 = statStr.fit{nCHISQ}; + +%% - 3 - Extracting the best estimate for each one of the parameters and their standard deviation +% -- CHISQ +statStr.CHISQmu = mean(statStr.CHISQ); +statStr.CHISQerr = 3*std(statStr.CHISQ); +% -- K0 +statStr.K0 = statStr.params(:,1)'; +statStr.K0mu = mean(statStr.K0); +statStr.K0err = 3*std(statStr.K0); +% -- kx FWHM +statStr.KFWHM = statStr.params(:,2)'; +statStr.KFWHMmu = mean(statStr.KFWHM); +statStr.KFWHMerr = 3*std(statStr.KFWHM); +% -- eb FWHM +statStr.EFWHM = statStr.params(:,3)'; +statStr.EFWHMmu = mean(statStr.EFWHM); +statStr.EFWHMerr = 3*std(statStr.EFWHM); +% -- MFP +statStr.MFP = statStr.params(:,4)'; +statStr.MFPmu = mean(statStr.MFP); +statStr.MFPerr = 3*std(statStr.MFP); +% -- BOFF +statStr.BOFF = statStr.params(:,5)'; +statStr.BOFFmu = mean(statStr.BOFF); +statStr.BOFFerr = 3*std(statStr.BOFF); +% -- INT +statStr.INT = statStr.params(:,6)'; +statStr.INTmu = mean(statStr.INT); +statStr.INTerr = 3*std(statStr.INT); +% -- MX +statStr.MX = statStr.params(:,end-2)'; +statStr.MXmu = mean(statStr.MX); +statStr.MXerr = 3*std(statStr.MX); +% -- MY +statStr.MY = statStr.params(:,end-1)'; +statStr.MYmu = mean(statStr.MY); +statStr.MYerr = 3*std(statStr.MY); +% -- C +statStr.C = statStr.params(:,end)'; +statStr.Cmu = mean(statStr.C); +statStr.Cerr = 3*std(statStr.C); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_parsolver_p_prctiles.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_parsolver_p_prctiles.m new file mode 100644 index 0000000..f1cd578 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_parsolver_p_prctiles.m @@ -0,0 +1,104 @@ +function [fitStr0, statStr] = arpes2model_parsolver_p_prctiles(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims, n_runs, prc, p_runs) +% [fitStr0, statStr] = arpes2model_solver_p_prctiles(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims, n_runs, prc, p_runs) +% Function that runs arpes2model_solver() N amount of independent times until +% convergence. The initial conditions are randomly sampled over the range +% of the input uncertainty. This allows the uncertainty in the best fit +% parameters to be determined by looking at the variance of the +% converged fit parameters. Once it runs N independent times, it then +% isolates the percentile of optimal fits based on chi-squared between +% (0 < prc). The initial conditions and bounds are re-calculated as the +% mean and 3 sigma variation of the isolated fit parameters. It then +% re-runs the arpes2model_solver() N amount of independent times again, +% and repeats this process for 'p_runs' amount of times. Uses Parallel Processing. +% +% REQ. FUNCTIONS: none +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - modelStr: MATLAB data-structure that contains the initial model data. +% - iparams: 3 cells {x0}{lb}{ub} with 1x5 array: the modelStr fit parameters [K0,KFWHM,EFWHM,MFP,BOFF,INT] +% - ibgrnd: 3 cells {x0}{lb}{ub} with 1x3 vector of the background parameters: [MX,MY,C] +% - solve_type: String of either "fminunc", "fmincon", "lsqnonlin", "simulannealbnd" that sets the optimisation routine to use +% - kx_lims: [1x2] vector of [minKx, maxKx], which defines the consistent kx fit window +% - eb_lims: [1x2] vector of [minEb, maxEb], which defines the consistent eb fit window +% - n_runs: scalar value for the total number of independent runs +% - prc: scalar value between [0, 100] that thresholds all the fit parameters within a percentile, 0 < prc, of the chi-squared values. This allows you to isolate the best solutions for diagnostic testing. +% - p_runs: scalar value of the total number of percentile squeezes to perform. +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information +% - statStr: MATLAB data-structure that contains all the statistical analysis + +%% Default parameters +% - Default input parameters to use +if nargin < 10; p_runs = 2; end +if nargin < 9; prc = 10; end +if nargin < 8; n_runs = 10; end +if nargin < 7; eb_lims = 0.95*[min(modelStr.eb(:)), max(modelStr.eb(:))]; end +if nargin < 6; kx_lims = 0.95*[min(modelStr.kx(:)), max(modelStr.kx(:))]; end +if nargin < 5; solve_type = "fmincon"; end +if nargin < 4; ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1} - 0.10; ibgrnd{3} = ibgrnd{1} + 0.10; end +if isempty(p_runs); p_runs = 10; end +if isempty(prc); prc = 2; end +if isempty(n_runs); n_runs = 10; end +if isempty(eb_lims); eb_lims = 0.95*[min(modelStr.eb(:)), max(modelStr.eb(:))]; end +if isempty(kx_lims); kx_lims = 0.95*[min(modelStr.kx(:)), max(modelStr.kx(:))]; end +if isempty(solve_type); solve_type = "fmincon"; end +if isempty(ibgrnd); ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1}-0.10; ibgrnd{3} = ibgrnd{1}+0.10; end + +%% - 1 - INITIALISING VARIABLES +statStr = {}; + +%% - 2 - RUNNING RUNNING THROUGH THE PERCENTILE-CONVERGING FITTING METHOD +for p = 1:p_runs + % -- Using the arpes2model solver for n runs + [fitStr0, statStr{p}] = arpes2model_parsolver_n_runs(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims, n_runs); + % -- Extracting the percentile value/index for the best solutions + chisq_prctile = prctile(statStr{p}.CHISQ, prc); + prctile_indx = statStr{p}.CHISQ < chisq_prctile; + if isempty(prctile_indx) || sum(prctile_indx) == 0 || abs(statStr{p}.CHISQmu - chisq_prctile) < 0.02 + [~, prctile_indx] = min(statStr{p}.CHISQ(:)); + end + fitStr0.iter = p; + fitStr0.prc_exit = 0; + % -- If only a single value of chi-squared remains, this is the best solution + if length(prctile_indx) == 1 + fitStr0.prc_exit = 1; + break + % -- If there are multiple values, redefine the parameters and run again + else + % -- Recalculating the new best fit parameters and bounds + params = statStr{p}.params(prctile_indx,:); + mu_params = mean(params, 1); + std_params = 3.*std(params, 1); + % -- Defining the new best fit parameters + iparams = {}; + iparams{1} = mu_params(1:end-3); + iparams{2} = mu_params(1:end-3) - std_params(1:end-3); + iparams{3} = mu_params(1:end-3) + std_params(1:end-3); + % -- Defining the new best fit background parameters + ibgrnd = {}; + ibgrnd{1} = mu_params(end-2:end); + ibgrnd{2} = mu_params(end-2:end) - std_params(end-2:end); + ibgrnd{3} = mu_params(end-2:end) + std_params(end-2:end); + % -- Verifying that the bound limits are not identical + for i = 1:size(iparams{1}, 2) + if iparams{1}(i) == iparams{2}(i); iparams{2}(i) = iparams{1}(i) - 0.001; end + if iparams{1}(i) == iparams{3}(i); iparams{3}(i) = iparams{1}(i) + 0.001; end + end + for i = 1:size(ibgrnd{1}, 2) + if ibgrnd{1}(i) == ibgrnd{2}(i); ibgrnd{2}(i) = ibgrnd{1}(i) - 0.001; end + if ibgrnd{1}(i) == ibgrnd{3}(i); ibgrnd{3}(i) = ibgrnd{1}(i) + 0.001; end + end +% % -- Verifying that the bound limits are not too small +% for i = 1:size(iparams{1}, 2) +% if abs(iparams{1}(i) - iparams{2}(i)) < 0.001; iparams{2}(i) = iparams{1}(i) - 0.001; end +% if abs(iparams{1}(i) - iparams{3}(i)) < 0.001; iparams{3}(i) = iparams{1}(i) - 0.001; end +% end +% for i = 1:size(ibgrnd{1}, 2) +% if abs(ibgrnd{1}(i) - ibgrnd{2}(i)) < 0.001; ibgrnd{2}(i) = ibgrnd{1}(i) - 0.001; end +% if abs(ibgrnd{1}(i) - ibgrnd{3}(i)) < 0.001; ibgrnd{3}(i) = ibgrnd{1}(i) - 0.001; end +% end + end +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_solver.m new file mode 100644 index 0000000..d51c760 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_solver.m @@ -0,0 +1,322 @@ +function fitStr = arpes2model_solver(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims) +% fitStr = arpes2model_solver(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims) +% Function that runs a a Global Optimisation Algorithm based on Simulated +% Annealing to determine the best model fit to the input ARPES data and +% model (initial conditions and bounds). The temperature of the Simulated +% Annealing is set to walk a large span of the parameter space to ensure +% the global minimum is obtained. The minimisation function is based on +% minimising the value of chi-squared. +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - modelStr: MATLAB data-structure that contains the initial model data. +% - iparams: 3 cells {x0}{lb}{ub} with [1×5] array: the model fit parameters [K0,KFWHM,EFWHM,MFP,BOFF,INT] +% - ibgrnd: 3 cells {x0}{lb}{ub} with [1×3] vector of the background parameters: [MX,MY,C] +% - solve_type: String that sets the optimisation routine to use: +% "fminunc" +% "fmincon" +% "lsqnonlin" +% "simulannealbnd" +% - kx_lims: [1×2] vector of [minKx, maxKx], which defines the consistent kx fit window +% - eb_lims: [1×2] vector of [minEb, maxEb], which defines the consistent eb fit window +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Default parameters & validity checks +% - Default input parameters to use +if nargin < 7; eb_lims = mean(modelStr.eb(:)) + [-1,1].*0.95*range(modelStr.eb(:)); end +if nargin < 6; kx_lims = mean(modelStr.kx(:)) + [-1,1].*0.95*range(modelStr.kx(:)); end +if nargin < 5; solve_type = "fmincon"; end +if nargin < 4; ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1} - 0.01; ibgrnd{3} = ibgrnd{1} + 0.01; end +if isempty(eb_lims); eb_lims = mean(modelStr.eb(:)) + [-1,1].*0.95*range(modelStr.eb(:)); end +if isempty(kx_lims); kx_lims = mean(modelStr.eb(:)) + [-1,1].*0.95*range(modelStr.kx(:)); end +if isempty(solve_type); solve_type = "fmincon"; end +if isempty(ibgrnd); ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1}-0.01; ibgrnd{3} = ibgrnd{1}+0.01; end +% -- Validity check on the input variables +if kx_lims(1) < 0.95*min(modelStr.kx(:)); kx_lims(1) = 0.95*min(modelStr.kx(:)); end +if kx_lims(2) > 0.95*max(modelStr.kx(:)); kx_lims(2) = 0.95*max(modelStr.kx(:)); end +if eb_lims(1) < 0.95*min(modelStr.eb(:)); eb_lims(1) = 0.95*min(modelStr.eb(:)); end +if eb_lims(2) > 0.95*max(modelStr.eb(:)); eb_lims(2) = 0.95*max(modelStr.eb(:)); end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Defining the initial conditions and limits of the parameters +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; +% -- Applying constraints on the parameters, based on the data +% --- parameters +if x0(2) < 0; x0(2) = 0; end % if kxFWHM < 0, then make it 0 +if x0(3) < 0; x0(3) = 0; end % if ebFWHM < 0, then make it 0 +if x0(4) < min(modelStr.MFP(:)); x0(4) = min(modelStr.MFP(:)); end % if MFP < min available, then make it the min +if x0(4) > max(modelStr.MFP(:)); x0(4) = max(modelStr.MFP(:)); end % if MFP > max available, then make it the max +if x0(5) < min(modelStr.BOFF(:)); x0(5) = min(modelStr.BOFF(:)); end % if BOFF < min available, then make it the min +if x0(5) > max(modelStr.BOFF(:)); x0(5) = max(modelStr.BOFF(:)); end % if BOFF > max available, then make it the max +if x0(6) < 0; x0(6) = 0; end % if INT < 0, then make it 0 +% --- lower bounds +if lb(2) < 0; lb(2) = 0; end % if kxFWHM < 0, then make it 0 +if lb(3) < 0; lb(3) = 0; end % if ebFWHM < 0, then make it 0 +if lb(4) < min(modelStr.MFP(:)); lb(4) = min(modelStr.MFP(:)); end % if MFP < min available, then make it the min +if lb(4) > max(modelStr.MFP(:)); lb(4) = max(modelStr.MFP(:)); end % if MFP > max available, then make it the max +if lb(5) < min(modelStr.BOFF(:)); lb(5) = min(modelStr.BOFF(:)); end % if BOFF < min available, then make it the min +if lb(5) > max(modelStr.BOFF(:)); lb(5) = max(modelStr.BOFF(:)); end % if BOFF > max available, then make it the max +if lb(6) < 0; lb(6) = 0; end % if INT < 0, then make it 0 +% --- upper bounds +if ub(2) < 0; ub(2) = 0; end % if kxFWHM < 0, then make it 0 +if ub(3) < 0; ub(3) = 0; end % if ebFWHM < 0, then make it 0 +if ub(4) < min(modelStr.MFP(:)); ub(4) = min(modelStr.MFP(:)); end % if MFP < min available, then make it the min +if ub(4) > max(modelStr.MFP(:)); ub(4) = max(modelStr.MFP(:)); end % if MFP > max available, then make it the max +if ub(5) < min(modelStr.BOFF(:)); ub(5) = min(modelStr.BOFF(:)); end % if BOFF < min available, then make it the min +if ub(5) > max(modelStr.BOFF(:)); ub(5) = max(modelStr.BOFF(:)); end % if BOFF > max available, then make it the max +if ub(6) < 0; ub(6) = 0; end % if INT < 0, then make it 0 +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - DEFINING THE ARPES DATA AND FITTING ARGUMENTS +% -- Defining global variable that stores all relevant model and data variables +ARPESObj = struct(); +ARPESObj.arpesStr = arpesStr; +ARPESObj.modelStr = modelStr; +% -- Appending the input arguments to the global variable +ARPESObj.fit_args.solve_type = solve_type; +ARPESObj.fit_args.iparams = iparams; +ARPESObj.fit_args.ibgrnd = ibgrnd; +ARPESObj.fit_args.kx_lims = kx_lims; +ARPESObj.fit_args.eb_lims = eb_lims; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 1e4; +FuncTol = 1e-12; +StepTol = 1e-12; +OptTol = 1e-12; +ConTol = 1e-12; +FinDiffRelStep = 1e-5; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; +%% - 3.1 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +if solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,grad,hessian] = fminunc(@(x) minimize_function(x,ARPESObj), x0, options); +%% - 3.2 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,ARPESObj), x0, [], [], [], [], lb, ub, [], options); +%% - 3.3 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR LEAST SQUARES PROBLEMS +elseif solve_type == "lsqnonlin" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqnonlin,... + 'Algorithm', 'levenberg-marquardt',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqnonlin(@(x) minimize_function(x,ARPESObj), x0, lb, ub, options); +%% - 3.4 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,ARPESObj), x0, lb, ub, options); +end + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.iparams = iparams; +fitStr.ibgrnd = ibgrnd; +%% 4.2 - Storing the ARPES data, background, model and minimisation variables +[ARPES, MODEL] = extract_arpes_and_model(params, ARPESObj.arpesStr, ARPESObj.modelStr, kx_lims, eb_lims); +% -- Storing the domain and range +fitStr.kx = MODEL.kx; +fitStr.eb = MODEL.eb; +% -- x- and y-axis limits +fitStr.kx_lims = [min(fitStr.kx(:)), max(fitStr.kx(:))]; +fitStr.eb_lims = [min(fitStr.eb(:)), max(fitStr.eb(:))]; +% -- Extracting the DATA +fitStr.D = fit_data(params, ARPES); +% -- Extracting the MODEL +fitStr.M = fit_model(params, MODEL); +% -- Extracting the BACKGROUND +fitStr.B = fit_background(params, MODEL); +% -- Extracting the DATA - BACKGROUND +fitStr.DB = fitStr.D - fitStr.B; +fitStr.MB = fitStr.M + fitStr.B; +% -- Extracting the RESIDUALS (R = D - (M + B)) +fitStr.R = fitStr.D - (fitStr.M + fitStr.B); +fitStr.Rx = mean(fitStr.R, 1); % R in 1D along x +fitStr.Ry = mean(fitStr.R, 2); % R in 1D along y +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ2D = fitStr.R.^2 ./ abs(fitStr.M + fitStr.B); +fitStr.CHISQx = mean(fitStr.CHISQ2D, 1); % CHISQ in 1D along x +fitStr.CHISQy = mean(fitStr.CHISQ2D, 2); % CHISQ in 1D along y +fitStr.CHISQ = sum(sum(fitStr.CHISQ2D)); +fitStr.MINFUN = minimize_function(params, ARPESObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables for the ARPES model fit +fitStr.params = params; +fitStr.K0 = params(1); +fitStr.KFWHM = params(2); +fitStr.EFWHM = params(3); +fitStr.MFP = params(4); +fitStr.BOFF = params(5); +fitStr.INT = params(6); +fitStr.MX = params(7); +fitStr.MY = params(8); +fitStr.C = params(9); +end + +%% DEFINING THE FUNCTION TO BE MINIMISED VIA GLOBAL OPTIMISATION METHODS +function MINFUN = minimize_function(x, ARPESObj) + [ARPES, MODEL] = extract_arpes_and_model(x, ARPESObj.arpesStr, ARPESObj.modelStr, ARPESObj.fit_args.kx_lims, ARPESObj.fit_args.eb_lims); + % - 1 - Extracting the DATA + D = fit_data(x, ARPES); + % - 2 - Extracting the MODEL + M = fit_model(x, MODEL); + % - 3 - Extracting the BACKGROUND + B = fit_background(x, MODEL); + % - 4 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - (M + B); + % - 5 - Extracting the CHI-SQUARED value to be minimised + MINFUN = sum(sum(R.^2 ./ abs(M + B))); % This is the chi-sqaured +end + +%% DEFINING THE FUNCTION TO BE MINIMISED VIA GLOBAL OPTIMISATION METHODS +function MINFUN = minimize_function_std2(x, ARPESObj) + [ARPES, MODEL] = extract_arpes_and_model(x, ARPESObj.arpesStr, ARPESObj.modelStr, ARPESObj.fit_args.kx_lims, ARPESObj.fit_args.eb_lims); + % - 1 - Extracting the DATA + D = fit_data(x, ARPES); + % - 2 - Extracting the MODEL + M = fit_model(x, MODEL); + % - 3 - Extracting the BACKGROUND + B = fit_background(x, MODEL); + % - 4 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - (M + B); + % - 5 - Extracting the CHI-SQUARED value to be minimised + MINFUN = std2(R.^2 ./ abs(M + B)); % This was found to yield the lowest value for R^2, rather than sum +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE ARPES DATA TO BE FITTED +function D = fit_data(x, ARPES) + D = ARPES.data; + D(isnan(D)) = 0; +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE MODEL +function M = fit_model(x, MODEL) + % 1 - Initialising variables + kxFWHM = x(2); % scalar of kx-resolution (Gaussian FWHM of k-broadening) + ebFWHM = x(3); % scalar of eb-resolution (Gaussian FWHM of eb-broadening) + INT = x(6); % scalar of the intensity scaling factor + % -- Constraints + if kxFWHM < 0; kxFWHM = 0; end + if ebFWHM < 0; ebFWHM = 0; end + if INT < 0; INT = 0; end + % 2 - Extracting the model curve based on the MFP and BOFF chosen + model_data = MODEL.data; + % 3 - Gaussian broadening the model in x- and y-dimensions + % -- Extracting the FWHM of the smoothing + kxFWHM = kxFWHM ./ abs(MODEL.kx_step); + ebFWHM = ebFWHM ./ abs(MODEL.eb_step); + % -- Gaussian smoothing + model_data = Gaco2(model_data, kxFWHM, ebFWHM); + model_data = INT .* model_data; + % Assigning the final model + M = model_data; + M(isnan(M)) = 0; +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE PLANAR BACKGROUND +function B = fit_background(x, MODEL) + % 1 - Initialising variables + MX = x(end-2); % scalar of the x-gradient of the plane. + MY = x(end-1); % scalar of the y-gradient of the plane. + C = x(end); % scalar of the constant off-set of the plane. + % 2 - Creating a planar background to be subtracted + B = MX * MODEL.kx + MY * MODEL.eb + C; + B(isnan(B)) = 0; +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE ARPES AND MODEL DATA CONSISTENTLY +function [ARPES, MODEL] = extract_arpes_and_model(x, arpesStr, modelStr, kx_lims, eb_lims) + % 1 - Initialising variables + K0 = x(1); % scalar of kx-origin offset + MFP = x(4); % scalar of mean free path (associated with resolution of bands) + BOFF = x(5); % scalar of band-offset + % 2 - Cropping the ARPES data to extract dimensional size + [xDat_crop, yDat_crop, ~] = data_crop2D(arpesStr.kx, arpesStr.eb, arpesStr.data, kx_lims, eb_lims); + kx_length = size(xDat_crop,2); + eb_length = size(yDat_crop,1); + % 3 - Extracting the interpolated MODEL data + imodelStr = mstheory_interp_spectra(modelStr, BOFF, MFP); + % 4 - Making the ARPES and MODEL data have a consistent domain + KX = linspace(kx_lims(1), kx_lims(2), kx_length); + EB = linspace(eb_lims(1), eb_lims(2), eb_length)'; + ARPES_DATA = interpn(arpesStr.eb(:,1), arpesStr.kx(1,:)-K0, arpesStr.data, EB, KX); + MODEL_DATA = interpn(imodelStr.eb, imodelStr.kx, imodelStr.data, EB, KX); + % 5 - Data renormalisation + ARPES_DATA = ARPES_DATA - min(ARPES_DATA(:)); ARPES_DATA = ARPES_DATA ./ max(ARPES_DATA(:)); + MODEL_DATA = MODEL_DATA - min(MODEL_DATA(:)); MODEL_DATA = MODEL_DATA ./ max(MODEL_DATA(:)); + ARPES_DATA(isnan(ARPES_DATA)) = 0; + MODEL_DATA(isnan(MODEL_DATA)) = 0; + % 6 - Defining the ARPES data structure + ARPES.kx = KX; + ARPES.kx_step = mean(diff(KX(:))); + ARPES.kx_lims = kx_lims; + ARPES.eb = EB; + ARPES.eb_step = mean(diff(EB(:))); + ARPES.eb_lims = eb_lims; + ARPES.data = ARPES_DATA; + % 7 - Defining the MODEL data structure + MODEL.MFP = MFP; + MODEL.BOFF = BOFF; + MODEL.kx = KX; + MODEL.kx_step = mean(diff(KX(:))); + MODEL.kx_lims = kx_lims; + MODEL.eb = EB; + MODEL.eb_step = mean(diff(EB(:))); + MODEL.eb_lims = eb_lims; + MODEL.data = MODEL_DATA; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_solver_n_runs.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_solver_n_runs.m new file mode 100644 index 0000000..3a94231 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_solver_n_runs.m @@ -0,0 +1,114 @@ +function [fitStr0, statStr] = arpes2model_solver_n_runs(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims, n_runs) +% [fitStr0, statStr] = arpes2model_solver_n_runs(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims, n_runs) +% Function that runs arpes2model_solver() N amount of independent times until +% convergence. The initial conditions are randomly sampled over the range +% of the input uncertainty. This allows the uncertainty in the best fit +% parameters to be determined by looking at the variance of the +% converged fit parameters. +% +% REQ. FUNCTIONS: none +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - modelStr: MATLAB data-structure that contains the initial model data. +% - iparams: 3 cells {x0}{lb}{ub} with 1x5 array: the model fit parameters [K0,KFWHM,EFWHM,MFP,BOFF,INT] +% - ibgrnd: 3 cells {x0}{lb}{ub} with 1x3 vector of the background parameters: [MX,MY,C] +% - solve_type: String of either "fminunc", "fmincon", "lsqnonlin", "simulannealbnd" that sets the optimisation routine to use +% - kx_lims: [1x2] vector of [minKx, maxKx], which defines the consistent kx fit window +% - eb_lims: [1x2] vector of [minEb, maxEb], which defines the consistent eb fit window +% - n_runs: scalar value for the total number of independent runs +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information +% - statStr: MATLAB data-structure that contains all the statistical analysis + +%% Default parameters +% - Default input parameters to use +if nargin < 8; n_runs = 10; end +if nargin < 7; eb_lims = 0.95*[min(modelStr.eb(:)), max(modelStr.eb(:))]; end +if nargin < 6; kx_lims = 0.95*[min(modelStr.kx(:)), max(modelStr.kx(:))]; end +if nargin < 5; solve_type = "fmincon"; end +if nargin < 4; ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1} - 0.10; ibgrnd{3} = ibgrnd{1} + 0.10; end +if isempty(n_runs); n_runs = 10; end +if isempty(eb_lims); eb_lims = 0.95*[min(modelStr.eb(:)), max(modelStr.eb(:))]; end +if isempty(kx_lims); kx_lims = 0.95*[min(modelStr.kx(:)), max(modelStr.kx(:))]; end +if isempty(solve_type); solve_type = "fmincon"; end +if isempty(ibgrnd); ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1}-0.10; ibgrnd{3} = ibgrnd{1}+0.10; end +% - Total number of parameters +nParams = length(iparams{1}) + length(ibgrnd{1}); + +%% - 1 - Running the fitting algorithm N independent time for statistical analysis +statStr = struct(); +statStr.n_runs = 1:n_runs; +fit = cell(n_runs,1); +params = zeros(n_runs, nParams); +CHISQ = zeros(n_runs,1); +% -- Running the fitting algorithm for N independent times for analysis +for i = statStr.n_runs + fprintf("Run %i / %i \n", i, n_runs); + % --- Add perturbation on the initial conditions + new_init_conds = iparams; + new_init_conds{1} = iparams{2} + (iparams{3}-iparams{2}) .* rand(size(iparams{2})); + % --- Executing the fit + if i == 1; fitStr{1} = arpes2model_solver(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims); + else; fitStr{i} = arpes2model_solver(arpesStr, modelStr, new_init_conds, ibgrnd, solve_type, kx_lims, eb_lims); + end + % --- Storing the best fits for statistical analysis + fit{i} = fitStr{i}; + % --- Storing the best fit parameters for statistical analysis + params(i,:) = fit{i}.params'; + CHISQ(i) = fit{i}.CHISQ; +end +% -- Assigning variables +statStr.fit = fit; +statStr.params = params; +statStr.CHISQ = CHISQ; +% -- Storing the parameter labels +statStr.params_label = {'K0', 'KFWHM', 'EFWHM', 'MFP', 'BOFF', 'INT', 'MX', 'MY', 'C'}; + +%% - 2 - Storing the fit structure that has the smallest value of chi-squared +[~, nCHISQ] = min(statStr.CHISQ(:)); +fitStr0 = statStr.fit{nCHISQ}; + +%% - 3 - Extracting the best estimate for each one of the parameters and their standard deviation +% -- CHISQ +statStr.CHISQmu = mean(statStr.CHISQ); +statStr.CHISQerr = 3*std(statStr.CHISQ); +% -- K0 +statStr.K0 = statStr.params(:,1)'; +statStr.K0mu = mean(statStr.K0); +statStr.K0err = 3*std(statStr.K0); +% -- kx FWHM +statStr.KFWHM = statStr.params(:,2)'; +statStr.KFWHMmu = mean(statStr.KFWHM); +statStr.KFWHMerr = 3*std(statStr.KFWHM); +% -- eb FWHM +statStr.EFWHM = statStr.params(:,3)'; +statStr.EFWHMmu = mean(statStr.EFWHM); +statStr.EFWHMerr = 3*std(statStr.EFWHM); +% -- MFP +statStr.MFP = statStr.params(:,4)'; +statStr.MFPmu = mean(statStr.MFP); +statStr.MFPerr = 3*std(statStr.MFP); +% -- BOFF +statStr.BOFF = statStr.params(:,5)'; +statStr.BOFFmu = mean(statStr.BOFF); +statStr.BOFFerr = 3*std(statStr.BOFF); +% -- INT +statStr.INT = statStr.params(:,6)'; +statStr.INTmu = mean(statStr.INT); +statStr.INTerr = 3*std(statStr.INT); +% -- MX +statStr.MX = statStr.params(:,end-2)'; +statStr.MXmu = mean(statStr.MX); +statStr.MXerr = 3*std(statStr.MX); +% -- MY +statStr.MY = statStr.params(:,end-1)'; +statStr.MYmu = mean(statStr.MY); +statStr.MYerr = 3*std(statStr.MY); +% -- C +statStr.C = statStr.params(:,end)'; +statStr.Cmu = mean(statStr.C); +statStr.Cerr = 3*std(statStr.C); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_solver_p_prctiles.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_solver_p_prctiles.m new file mode 100644 index 0000000..2ad229c --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2model fitting/arpes2model_solver_p_prctiles.m @@ -0,0 +1,104 @@ +function [fitStr0, statStr] = arpes2model_solver_p_prctiles(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims, n_runs, prc, p_runs) +% [fitStr0, statStr] = arpes2model_solver_p_prctiles(modelStr, arpesStr, iparams, ibgrnd, solve_type, n_runs, prc, p_runs) +% Function that runs arpes2model_solver() N amount of independent times until +% convergence. The initial conditions are randomly sampled over the range +% of the input uncertainty. This allows the uncertainty in the best fit +% parameters to be determined by looking at the variance of the +% converged fit parameters. Once it runs N independent times, it then +% isolates the percentile of optimal fits based on chi-squared between +% (0 < prc). The initial conditions and bounds are re-calculated as the +% mean and 3 sigma variation of the isolated fit parameters. It then +% re-runs the arpes2model_solver() N amount of independent times again, +% and repeats this process for 'p_runs' amount of times. +% +% REQ. FUNCTIONS: none +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - modelStr: MATLAB data-structure that contains the initial model data. +% - iparams: 3 cells {x0}{lb}{ub} with 1x5 array: the modelStr fit parameters [K0,KFWHM,EFWHM,MFP,BOFF,INT] +% - ibgrnd: 3 cells {x0}{lb}{ub} with 1x3 vector of the background parameters: [MX,MY,C] +% - solve_type: String of either "fminunc", "fmincon", "lsqnonlin", "simulannealbnd" that sets the optimisation routine to use +% - kx_lims: [1x2] vector of [minKx, maxKx], which defines the consistent kx fit window +% - eb_lims: [1x2] vector of [minEb, maxEb], which defines the consistent eb fit window +% - n_runs: scalar value for the total number of independent runs +% - prc: scalar value between [0, 100] that thresholds all the fit parameters within a percentile, 0 < prc, of the chi-squared values. This allows you to isolate the best solutions for diagnostic testing. +% - p_runs: scalar value of the total number of percentile squeezes to perform. +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information +% - statStr: MATLAB data-structure that contains all the statistical analysis + +%% Default parameters +% - Default input parameters to use +if nargin < 10; p_runs = 2; end +if nargin < 9; prc = 10; end +if nargin < 8; n_runs = 10; end +if nargin < 7; eb_lims = 0.95*[min(modelStr.eb(:)), max(modelStr.eb(:))]; end +if nargin < 6; kx_lims = 0.95*[min(modelStr.kx(:)), max(modelStr.kx(:))]; end +if nargin < 5; solve_type = "fmincon"; end +if nargin < 4; ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1} - 0.10; ibgrnd{3} = ibgrnd{1} + 0.10; end +if isempty(p_runs); p_runs = 10; end +if isempty(prc); prc = 2; end +if isempty(n_runs); n_runs = 10; end +if isempty(eb_lims); eb_lims = 0.95*[min(modelStr.eb(:)), max(modelStr.eb(:))]; end +if isempty(kx_lims); kx_lims = 0.95*[min(modelStr.kx(:)), max(modelStr.kx(:))]; end +if isempty(solve_type); solve_type = "fmincon"; end +if isempty(ibgrnd); ibgrnd{1} = [0, 0, 0]; ibgrnd{2} = ibgrnd{1}-0.10; ibgrnd{3} = ibgrnd{1}+0.10; end + +%% - 1 - INITIALISING VARIABLES +statStr = {}; + +%% - 2 - RUNNING RUNNING THROUGH THE PERCENTILE-CONVERGING FITTING METHOD +for p = 1:p_runs + % -- Using the arpes2model solver for n runs + [fitStr0, statStr{p}] = arpes2model_solver_n_runs(arpesStr, modelStr, iparams, ibgrnd, solve_type, kx_lims, eb_lims, n_runs); + % -- Extracting the percentile value/index for the best solutions + chisq_prctile = prctile(statStr{p}.CHISQ, prc); + prctile_indx = statStr{p}.CHISQ 0.95*max(modelStr.kx(:)); kx_lims(2) = 0.95*max(modelStr.kx(:)); end +if eb_lims(1) < 0.95*min(modelStr.eb(:)); eb_lims(1) = 0.95*min(modelStr.eb(:)); end +if eb_lims(2) > 0.95*max(modelStr.eb(:)); eb_lims(2) = 0.95*max(modelStr.eb(:)); end + +%% Initialising variables +K0 = iparams{1}(1); % scalar of kx-shift of the ARPES data +MFP = iparams{1}(4); % scalar of mean free path (associated with resolution of bands) +BOFF = iparams{1}(5); % scalar of band-offset +% -- Defining the initial conditions and limits of the parameters +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; + +%% 1 - Making the ARPES and MODEL data consistent with the fitting window +[ARPES, MODEL] = extract_arpes_and_model(x0, arpesStr, modelStr, kx_lims, eb_lims); + +%% - 1 - Determination of the residuals and chi-squared (the minimisation variable) +% - 1.1 - Extracting the DATA +D = ARPES.data; +% - 1.2 - Extracting the MODEL +M = model(x0, MODEL); +% - 1.3 - Extracting the BACKGROUND +B = background(x0, MODEL); +% - 1.4 - Extracting the RESIDUALS +R = D - (M + B); % residuals = data - (model + background) +Rx = mean(R, 1); % R in 1D along x +Ry = mean(R, 2); % R in 1D along y +% - 1.5 - Extracting the CHI-SQUARED value to be minimised +CHISQ2D = R.^2 ./ (M + B); +CHISQxx = mean(CHISQ2D, 1); % CHISQ in 1D along x +CHISQyy = mean(CHISQ2D, 2); % CHISQ in 1D along y +% - 1.6 - Extracting the REDUCED CHI-SQUARED value including degrees of freedom +CHISQ = sum(sum(CHISQ2D)); + +%% - 2 - PLOTTING THE FINAL DATA COMPARED WITH MODEL AT BOFF = 0 eV +% -- Initialising the plot properties +win = 0.01; +val1 = 0; +val2 = 0.25*min(ARPES.kx(:)); +val3 = 0.25*max(ARPES.kx(:)); +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'ARPES2MODEL Fitting'); +fig.Position(3) = 4.*pp.fig5x4(1); +fig.Position(4) = 2.*pp.fig5x4(2); +%% - 2.1 - Plotting the model data +% -- Extracting the data matrix +data = M + B; +% -- Plotting the data +axs(1) = subplot(3,7,[1,2,8,9]); hold on; +ImData(MODEL.kx, MODEL.eb, data); +img_props(); +xlabel(' $$ k_{//} [A^{-1}] $$', 'interpreter', 'latex'); +ylabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +axis([MODEL.kx_lims, MODEL.eb_lims]); +caxis([min(data(:)), max(data(:))]); +text(0.04, 0.94, "$$ \Phi = $$" + string(round(MODEL.BOFF,3)) + " $$ eV $$",... + 'interpreter', 'latex', 'fontsize', 16, 'color', 'w', 'Units','normalized'); +axis square; +title('Initial model data'); + +%% - 2.2 - Plotting the ARPES data +axs(2) = subplot(3,7,[3,4,10,11]); hold on; +ImData(ARPES.kx, ARPES.eb, ARPES.data); img_props(); +xlabel(' $$ k_{//} [A^{-1}] $$', 'interpreter', 'latex'); +ylabel('', 'interpreter', 'latex'); +axis([ARPES.kx_lims, ARPES.eb_lims]); axis square; +caxis([min(ARPES.data(:)), max(ARPES.data(:))]); +title('ARPES data to be fitted'); +% -- Plotting the EDC cut lines +line([1 1].*val1, [-1e5, 1e5], 'Color', pp.col.fit{1}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); +line([1 1].*val2, [-1e5, 1e5], 'Color', pp.col.fit{2}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); +line([1 1].*val3, [-1e5, 1e5], 'Color', pp.col.fit{3}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); + +%% - 2.3 - Plotting the 2D residuals +axs(3) = subplot(3,7,[5,6,12,13]); hold on; +ImData(ARPES.kx, ARPES.eb, CHISQ2D); img_props(); +axis([ARPES.kx_lims, ARPES.eb_lims]); +title('Chi-Squared'); +% -- Add annotation for the quality of fit +text(0.04, 0.94, "$$ \chi^2 = $$ " + string(CHISQ),... + 'interpreter', 'latex', 'fontsize', 16, 'color', 'w', 'Units','normalized'); +% -- Make the colormap bipolar (negative values blue, positive is red) +colormap(axs(3),'jet'); +% -- Make the colormap bipolar (negative values blue, positive is red) +ylabel('', 'interpreter', 'latex'); +xlabel(''); + +%% - 2.4 - Plotting the 1D residuals along x +axs(4) = subplot(3,7,[19,20]); hold on; +bar(ARPES.kx, CHISQxx); +gca_props(); grid on; +xlabel(' $$ k_{//} [A^{-1}] $$', 'interpreter', 'latex'); +ylabel('$$ \bf \chi^2(x) $$', 'Interpreter', 'latex'); +xlim(ARPES.kx_lims); +ax = gca; ax.YAxisLocation = 'right'; + +%% - 2.5 - Plotting the 1D residuals along y +axs(5) = subplot(3,7,[7,14]); hold on; +barh(ARPES.eb, CHISQyy); +gca_props(); grid on; +ylabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +xlabel('$$ \bf \chi^2(y) $$', 'Interpreter', 'latex'); +ylim(ARPES.eb_lims); +ax = gca; ax.YAxisLocation = 'right'; + +%% - 2.6 - Plotting best fit EDCs +%% - 2.6.1 - Gamma EDCs +axs(6) = subplot(3,7,[15,16]); hold on; +% -- Extracting the EDCs +[ARPES_XCut, ARPES_DCut] = Cut(ARPES.kx, ARPES.eb, ARPES.data, 'edc', val1 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(MODEL.kx, MODEL.eb, (M + B), 'edc', val1 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{1}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +gca_props(); grid on; +ylabel('$$ Intensity $$', 'Interpreter', 'latex'); +xlabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +%% - 2.6.1 - LHS and RHS EDCs +axs(7) = subplot(3,7,[17,18]); hold on; +% -- Extracting the LHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(ARPES.kx, ARPES.eb, ARPES.data, 'edc', val2 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(MODEL.kx, MODEL.eb, (M + B), 'edc', val2 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{2}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Extracting the RHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(ARPES.kx, ARPES.eb, ARPES.data, 'edc', val3 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(MODEL.kx, MODEL.eb, (M + B), 'edc', val3 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{3}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +gca_props(); grid on; +xlabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); + +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE MODEL +function M = model(x, MODEL) + % 1 - Initialising variables + kxFWHM = x(2); % scalar of kx-resolution (Gaussian FWHM of k-broadening) + ebFWHM = x(3); % scalar of eb-resolution (Gaussian FWHM of eb-broadening) + MFP = x(4); % scalar of mean free path (associated with resolution of bands) + BOFF = x(5); % scalar of band-offset + INT = x(6); % scalar of the intensity scaling factor + % 2 - Extracting the model curve based on the MFP and BOFF chosen + model_data = MODEL.data; + % 3 - Gaussian broadening the model in x- and y-dimensions + % -- Extracting the FWHM of the smoothing + kxFWHM = kxFWHM ./ abs(MODEL.kx_step); + ebFWHM = ebFWHM ./ abs(MODEL.eb_step); + % -- Gaussian smoothing + model_data = Gaco2(model_data, kxFWHM, ebFWHM); + % 4 - Intensity scaling + model_data = INT .* model_data; + % Assigning the final model + M = model_data; + M(isnan(M)) = 0; +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE PLANAR BACKGROUND +function B = background(x, MODEL) + % 1 - Initialising variables + MX = x(end-2); % scalar of the x-gradient of the plane. + MY = x(end-1); % scalar of the y-gradient of the plane. + C = x(end); % scalar of the constant off-set of the plane. + % 2 - Creating a planar background to be subtracted + B = MX * MODEL.kx + MY * MODEL.eb + C; + B(isnan(B)) = 0; +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE ARPES AND MODEL DATA CONSISTENTLY +function [ARPES, MODEL] = extract_arpes_and_model(x, arpesStr, modelStr, kx_lims, eb_lims) + % 1 - Initialising variables + K0 = x(1); % scalar of kx-resolution (Gaussian FWHM of k-broadening) + MFP = x(4); % scalar of mean free path (associated with resolution of bands) + BOFF = x(5); % scalar of band-offset + % 2 - Cropping the ARPES data to extract dimensional size + [xDat_crop, yDat_crop, ~] = data_crop2D(arpesStr.kx, arpesStr.eb, arpesStr.data, kx_lims, eb_lims); + kx_length = size(xDat_crop,2); + eb_length = size(yDat_crop,1); + % 3 - Extracting the interpolated MODEL data + imodelStr = mstheory_interp_spectra(modelStr, BOFF, MFP); + % 4 - Making the ARPES and MODEL data have a consistent domain + KX = linspace(kx_lims(1), kx_lims(2), kx_length); + EB = linspace(eb_lims(1), eb_lims(2), eb_length)'; + ARPES_DATA = interpn(arpesStr.eb(:,1), arpesStr.kx(1,:)-K0, arpesStr.data, EB, KX); + MODEL_DATA = interpn(imodelStr.eb, imodelStr.kx, imodelStr.data, EB, KX); + % 5 - Data renormalisation + ARPES_DATA = ARPES_DATA - min(ARPES_DATA(:)); ARPES_DATA = ARPES_DATA ./ max(ARPES_DATA(:)); + MODEL_DATA = MODEL_DATA - min(MODEL_DATA(:)); MODEL_DATA = MODEL_DATA ./ max(MODEL_DATA(:)); + ARPES_DATA(isnan(ARPES_DATA)) = 0; + MODEL_DATA(isnan(MODEL_DATA)) = 0; + % 6 - Defining the ARPES data structure + ARPES.kx = KX; + ARPES.kx_step = mean(diff(KX(:))); + ARPES.kx_lims = kx_lims; + ARPES.eb = EB; + ARPES.eb_step = mean(diff(EB(:))); + ARPES.eb_lims = eb_lims; + ARPES.data = ARPES_DATA; + % 7 - Defining the MODEL data structure + MODEL.MFP = MFP; + MODEL.BOFF = BOFF; + MODEL.kx = KX; + MODEL.kx_step = mean(diff(KX(:))); + MODEL.kx_lims = kx_lims; + MODEL.eb = EB; + MODEL.eb_step = mean(diff(EB(:))); + MODEL.eb_lims = eb_lims; + MODEL.data = MODEL_DATA; +end diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2nbola fitting/arpes2nbola_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2nbola fitting/arpes2nbola_solver.m new file mode 100644 index 0000000..96ecdd0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2nbola fitting/arpes2nbola_solver.m @@ -0,0 +1,246 @@ +function fitStr = arpes2nbola_solver(arpesStr, cTYPE, iparams, ibgrnd, solve_type) +% fitStr = arpes2nbola_solver(arpesStr, cTYPE, iparams, ibgrnd, solve_type) +% Function that is used to fit N-parabolic dispersions to ARPES data, by +% defining the energy/momentum minimum and gaussian broadening, and +% effective mass of each subband state. A Fermi-Dirac Distribution is +% also used with a linear background, for states that are close to the +% Fermi edge. +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - cTYPE: 1xN vector of the type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - iparams: 3 cells {x0}{lb}{ub} with 1x6 array: the model fit parameters [INT,XLOC,YLOC,XFWHM,YFWHM,MSTAR] +% - ibgrnd: 3 cells {x0}{lb}{ub} with 1x6 vector of the background parameters: [FDEF,FDT,FDW,BGR,BIN,BCO] +% - solve_type: String of either "fminunc", "fmincon", "lsqnonlin", "simulannealbnd" that sets the optimisation routine to use +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Default parameters & validity checks +% - Default input parameters to use +if nargin < 5; solve_type = "fmincon"; end +if isempty(solve_type); solve_type = "fmincon"; end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Defining the initial conditions and limits of the parameters +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; +% -- Applying constraints on the parameters, based on the data +n = length(cTYPE); +for i = 1:n + % --- parameters + if x0(i) < 0; x0(i) = 0; end % if INT < 0, then make it 0 + if x0(i+3*n) < 0; x0(i+3*n) = 0; end % if XFWHM < 0, then make it 0 + if x0(i+4*n) < 0; x0(i+4*n) = 0; end % if YFWHM < 0, then make it 0 + % --- lower bounds + if lb(i) < 0; lb(i) = 0; end % if INT < 0, then make it 0 + if lb(i+3*n) < 0; lb(i+3*n) = 0; end % if XFWHM < 0, then make it 0 + if lb(i+4*n) < 0; lb(i+4*n) = 0; end % if YFWHM < 0, then make it 0 + % --- upper bounds + if ub(i) < 0; ub(i) = 0; end % if INT < 0, then make it 0 + if ub(i+3*n) < 0; ub(i+3*n) = 0; end % if XFWHM < 0, then make it 0 + if ub(i+4*n) < 0; ub(i+4*n) = 0; end % if YFWHM < 0, then make it 0 +end +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - DEFINING THE ARPES DATA AND FITTING ARGUMENTS +% -- Defining global variable that stores all relevant model and data variables +ARPESObj = struct(); +ARPESObj.arpesStr = arpesStr; +% -- Appending the input arguments to the global variable +ARPESObj.fit_args.solve_type = solve_type; +ARPESObj.fit_args.cTYPE = cTYPE; +ARPESObj.fit_args.iparams = iparams; +ARPESObj.fit_args.ibgrnd = ibgrnd; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 1e4; +FuncTol = 1e-12; +StepTol = 1e-12; +OptTol = 1e-12; +ConTol = 1e-12; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; +%% - 3.1 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +if solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fminunc(@(x) minimize_function(x,ARPESObj), x0, options); +%% - 3.2 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,ARPESObj), x0, [], [], [], [], lb, ub, [], options); +%% - 3.3 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR LEAST SQUARES PROBLEMS +elseif solve_type == "lsqnonlin" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqnonlin,... + 'Algorithm', 'levenberg-marquardt',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqnonlin(@(x) minimize_function(x,ARPESObj), x0, lb, ub, options); +%% - 3.4 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,ARPESObj), x0, lb, ub, options); +end + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.iparams = iparams; +fitStr.ibgrnd = ibgrnd; +%% 4.2 - Storing the ARPES data, background, model and minimisation variables +[ARPES, MODEL] = extract_arpes_and_model(params, ARPESObj.arpesStr, cTYPE); +% -- Storing the domain and range +fitStr.kx = MODEL.kx; +fitStr.eb = MODEL.eb; +% -- x- and y-axis limits +fitStr.kx_lims = [min(fitStr.kx(:)), max(fitStr.kx(:))]; +fitStr.eb_lims = [min(fitStr.eb(:)), max(fitStr.eb(:))]; +% -- Extracting the DATA +fitStr.D = ARPES.data; +% -- Extracting the MODEL +fitStr.M = MODEL.data; +% -- Extracting the RESIDUALS (R = D - M) +fitStr.R = fitStr.D - fitStr.M; +fitStr.Rx = mean(fitStr.R, 1); % R in 1D along x +fitStr.Ry = mean(fitStr.R, 2); % R in 1D along y +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ2D = fitStr.R.^2 ./ abs(fitStr.M); +fitStr.CHISQx = mean(fitStr.CHISQ2D, 1); % CHISQ in 1D along x +fitStr.CHISQy = mean(fitStr.CHISQ2D, 2); % CHISQ in 1D along y +fitStr.CHISQ = sum(sum(fitStr.CHISQ2D)); +fitStr.MINFUN = minimize_function(params, ARPESObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables for the ARPES model fit +fitStr.params = params; +fitStr.n = length(cTYPE); +fitStr.cTYPE = cTYPE; +fitStr.INT = params(1:n); +fitStr.XLOC = params(n+1:2*n); +fitStr.YLOC = params(2*n+1:3*n); +fitStr.XFWHM = params(3*n+1:4*n); +fitStr.YFWHM = params(4*n+1:5*n); +fitStr.MSTAR = params(5*n+1:6*n); +fitStr.FDEF = params(end-5); +fitStr.FDT = params(end-4); +fitStr.FDW = params(end-3); +fitStr.BGR = params(end-2); +fitStr.BIN = params(end-1); +fitStr.BCO = params(end); +%% 4.4 - Storing the Eb(kx) dispersions +fitStr.sbn_kx = linspace(fitStr.kx_lims(1), fitStr.kx_lims(2), 1e3); +fitStr.sbn_eb = {}; +for i = 1:fitStr.n + fitStr.sbn_eb{i} = eb_calc(fitStr.sbn_kx, fitStr.XLOC(i), fitStr.YLOC(i), fitStr.MSTAR(i)); +end +end + +%% DEFINING THE FUNCTION TO BE MINIMISED VIA GLOBAL OPTIMISATION METHODS +function MINFUN = minimize_function(x, ARPESObj) + [ARPES, MODEL] = extract_arpes_and_model(x, ARPESObj.arpesStr, ARPESObj.fit_args.cTYPE); + % - 1 - Extracting the DATA + D = ARPES.data; + % - 2 - Extracting the MODEL + M = MODEL.data; + % - 3 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - M; + % - 5 - Extracting the CHI-SQUARED value to be minimised + % MINFUN = std2(R.^2 ./ abs(M + B)); % This was found to yield the lowest value for R^2, rather than sum + MINFUN = sum(sum(R.^2 ./ abs(M))); % This is the chi-sqaured +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE ARPES AND MODEL DATA CONSISTENTLY +function [ARPES, MODEL] = extract_arpes_and_model(x, arpesStr, cTYPE) + % 1 - Initialising variables + n = length(cTYPE); + % - Extracting parabolic parameters + INT = x(1:n); % scalar of the peak intensity of 2D PE curve. + XLOC = x(n+1:2*n); % scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion. + YLOC = x(2*n+1:3*n); % scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion. + XFWHM = x(3*n+1:4*n); % scalar of the x-axis FWHM for each Gaussian (k-resolution) + YFWHM = x(4*n+1:5*n); % scalar of the y-axis FWHM for each Gaussian (Eb-resolution) + MSTAR = x(5*n+1:6*n); % scalar of the effective mass, which governs the curvature of the parabola. + % - Extracting background parameters + FDEF = x(end-5); % scalar of the FDD Fermi-Level position. + FDT = x(end-4); % scalar of the FDD temperature. + FDW = x(end-3); % scalar of the FDD Gaussian width after convolution. + BGR = x(end-2); % scalar of the gradient of the linear background. + BIN = x(end-1); % scalar of the y-intercept of the linear background. + BCO = x(end); % scalar of the constant background y-offset value. + % - Extracting the kx and eb limits + kx_lims = [min(arpesStr.kx(:)), max(arpesStr.kx(:))]; + eb_lims = [min(arpesStr.eb(:)), max(arpesStr.eb(:))]; + % 2 - Extracting the constructed MODEL data + KX = linspace(kx_lims(1), kx_lims(2), size(arpesStr.kx,2)); + EB = linspace(eb_lims(1), eb_lims(2), size(arpesStr.eb,1))'; + MODEL_DATA = ARPESCurve_FDDGpL(KX, EB, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO); + ARPES_DATA = arpesStr.data; + % - Removing any NaN values + MODEL_DATA(isnan(MODEL_DATA)) = 0; + ARPES_DATA(isnan(ARPES_DATA)) = 0; + % 3 - Defining the ARPES data structure + ARPES = struct(); + ARPES.kx = KX; + ARPES.kx_step = mean(diff(KX(:))); + ARPES.kx_lims = kx_lims; + ARPES.eb = EB; + ARPES.eb_step = mean(diff(EB(:))); + ARPES.eb_lims = eb_lims; + ARPES.data = ARPES_DATA; + % 4 - Defining the MODEL data structure + MODEL = struct(); + MODEL.kx = KX; + MODEL.kx_step = mean(diff(KX(:))); + MODEL.kx_lims = kx_lims; + MODEL.eb = EB; + MODEL.eb_step = mean(diff(EB(:))); + MODEL.eb_lims = eb_lims; + MODEL.data = MODEL_DATA; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2nbola fitting/arpes2nbola_view_fit.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2nbola fitting/arpes2nbola_view_fit.m new file mode 100644 index 0000000..b143bad --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2nbola fitting/arpes2nbola_view_fit.m @@ -0,0 +1,134 @@ +function fig = arpes2nbola_view_fit(fitStr) +% fig = arpes2nbola_view_fit(fitStr) +% This function is used to plot the results of the curve fitting +% performed by 'fitStr = arpes2nbola_solver(...)'. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - fitStr: MATLAB data-structure that contains all fit parameters / variables / information +% +% OUT: +% - fig: figure output + +%% Initialising input variables +% -- Defining the values of the EDC cut figures +win = abs(0.05*range(fitStr.kx(:))); +val1 = mean(fitStr.kx(:)); +val2 = mean(fitStr.kx(:)) - abs(0.10*range(fitStr.kx(:))); +val3 = mean(fitStr.kx(:)) + abs(0.10*range(fitStr.kx(:))); + +%% - 1 - PLOTTING THE FITTED DATA +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'arpes2nbola_view_fit()'); +fig.Position(3) = 4.*pp.fig5x4(1); +fig.Position(4) = 2.*pp.fig5x4(2); +%% - 1.1 - Plotting the MODEL data +axs(1) = subplot(3,7,[1,2,8,9]); hold on; +ImData(fitStr.kx, fitStr.eb, fitStr.M); +for i = 1:fitStr.n; plot(fitStr.sbn_kx, fitStr.sbn_eb{i}, 'r:', 'linewidth', 3); end +img_props(); +xlabel('$$ \bf k_{//} (\AA^{-1}) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +axis([fitStr.kx_lims, fitStr.eb_lims]); axis square; +caxis([min(fitStr.M(:)), max(fitStr.M(:))]); +title('Model Fit'); + +%% - 4.2 - Plotting the ARPES data +axs(2) = subplot(3,7,[3,4,10,11]); hold on; +ImData(fitStr.kx, fitStr.eb, fitStr.D); img_props(); +for i = 1:fitStr.n; plot(fitStr.sbn_kx, fitStr.sbn_eb{i}, 'r:', 'linewidth', 3); end +xlabel('$$ \bf k_{//} (\AA^{-1}) $$', 'Interpreter', 'latex'); +ylabel('', 'Interpreter', 'latex'); +axis([fitStr.kx_lims, fitStr.eb_lims]); axis square; +title('ARPES Data'); +caxis([min(fitStr.D(:)), max(fitStr.D(:))]); +% -- Plotting the EDC cut lines +line([1 1].*val1, [-1e5, 1e5], 'Color', pp.col.fit{1}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); +line([1 1].*val2, [-1e5, 1e5], 'Color', pp.col.fit{2}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); +line([1 1].*val3, [-1e5, 1e5], 'Color', pp.col.fit{3}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); + +%% - 4.6.1 - LHS and RHS EDCs +axs(7) = subplot(3,7,[17,18]); hold on; +% -- Extracting the LHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.D, 'edc', val2 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.M, 'edc', val2 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{2}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Extracting the RHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.D, 'edc', val3 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.M, 'edc', val3 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{3}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +gca_props(); grid on; +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + +%% - 4.3 - Plotting the 2D residuals +axs(3) = subplot(3,7,[5,6,12,13]); hold on; +ImData(fitStr.kx, fitStr.eb, fitStr.CHISQ2D); img_props(); +axis([fitStr.kx_lims, fitStr.eb_lims]); axis square; +title('Chi-Squared'); +% -- Add annotation for the quality of fit +text(0.04, 0.94, "$$ \chi^2 = $$ " + string(fitStr.CHISQ),... + 'interpreter', 'latex', 'fontsize', 16, 'color', 'w', 'Units','normalized'); +% -- Make the colormap bipolar (negative values blue, positive is red) +colormap(axs(3),'jet'); +ylabel(''); +xlabel(''); + +%% - 4.4 - Plotting the 1D residuals along x +axs(4) = subplot(3,7,[19,20]); hold on; +bar(fitStr.kx, fitStr.CHISQx); +gca_props(); grid on; +xlabel(' $$ k_{//} [A^{-1}] $$', 'interpreter', 'latex'); +ylabel('$$ \bf \chi^2(x) $$', 'Interpreter', 'latex'); +xlim(fitStr.kx_lims); +ax = gca; ax.YAxisLocation = 'right'; + +%% - 4.5 - Plotting the 1D residuals along y +axs(5) = subplot(3,7,[7,14]); hold on; +barh(fitStr.eb, fitStr.CHISQy); +gca_props(); grid on; +ylabel(' $$ E - E_F [eV] $$', 'interpreter', 'latex'); +xlabel('$$ \bf \chi^2(y) $$', 'Interpreter', 'latex'); +ylim(fitStr.eb_lims); +ax = gca; ax.YAxisLocation = 'right'; + +%% - 4.6 - Plotting best fit EDCs +%% - 4.6.1 - Gamma EDCs +axs(6) = subplot(3,7,[15,16]); hold on; +% -- Extracting the EDCs +[ARPES_XCut, ARPES_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.D, 'edc', val1 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.M, 'edc', val1 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{1}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Plotting the sub-band energies +for i = 1:fitStr.n; line([1 1]*fitStr.YLOC(i), [-1e5, 1e5], 'Color', 'r', 'LineWidth', 2, 'Linestyle', ':'); end +gca_props(); grid on; +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Int. (arb.) $$', 'Interpreter', 'latex'); +axis([min(ARPES_XCut(:)), max(ARPES_XCut(:)), 0, 1.25*max(ARPES_DCut(:))]); +%% - 4.6.1 - LHS and RHS EDCs +axs(7) = subplot(3,7,[17,18]); hold on; +% -- Extracting the LHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.D, 'edc', val2 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.M, 'edc', val2 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{2}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Extracting the RHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.D, 'edc', val3 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(fitStr.kx, fitStr.eb, fitStr.M, 'edc', val3 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k:', 'color', pp.col.fit{3}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k:', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +gca_props(); grid on; +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +axis([min(ARPES_XCut(:)), max(ARPES_XCut(:)), 0, 1.25*max(ARPES_DCut(:))]); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2nbola fitting/arpes2nbola_view_init.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2nbola fitting/arpes2nbola_view_init.m new file mode 100644 index 0000000..7cb46be --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/arpes2nbola fitting/arpes2nbola_view_init.m @@ -0,0 +1,206 @@ +function fig = arpes2nbola_view_init(arpesStr, cTYPE, iparams, ibgrnd) +% fig = arpes2nbola_view_init(arpesStr, cTYPE, iparams, ibgrnd) +% This function is used to plot the initial curve fitting model prior to +% using the 'arpes2nbola_solver()' algorithm. This is used as an informative +% plot that allows you to view and create a better initial guess of the +% model prior to running the fitting algorithm. +% +% REQ. FUNCTIONS: none +% +% IN: +% - arpesStr: MATLAB data-structure that contains the initial ARPES data. +% - cTYPE: 1xN vector of the type of curve to use for fitting. Default: "G2DA" ("G2D", "L2D") +% - iparams: 3 cells {x0}{lb}{ub} with 1x6 array: the model fit parameters [INT,XLOC,YLOC,XFWHM,YFWHM,MSTAR] +% - ibgrnd: 3 cells {x0}{lb}{ub} with 1x6 vector of the background parameters: [FDEF,FDT,FDW,BGR,BIN,BCO] +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Initialising variables +% - Defining the initial conditions and limits of the parameters +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; +% - Making the ARPES and MODEL data consistent over a consistent domain +[ARPES, MODEL] = extract_arpes_and_model(x0, arpesStr, cTYPE); +% - Extracting the parabolic dispersions for each subband energy +sbn_kx = linspace(ARPES.kx_lims(1), ARPES.kx_lims(2), 1e3); +sbn_eb = {}; +XLOC = iparams{1}(:,2); +YLOC = iparams{1}(:,3); +MSTAR = iparams{1}(:,6); +for i = 1:length(YLOC) + sbn_eb{i} = eb_calc(sbn_kx, XLOC(i), YLOC(i), MSTAR(i)); +end + +%% - 1 - Determination of the residuals and chi-squared (the minimisation variable) +% - 1.1 - Extracting the DATA +D = ARPES.data; +% - 1.2 - Extracting the MODEL +M = MODEL.data; +% - 1.4 - Extracting the RESIDUALS +R = D - M; % residuals = data - model +Rx = mean(R, 1); % R in 1D along x +Ry = mean(R, 2); % R in 1D along y +% - 1.5 - Extracting the CHI-SQUARED value to be minimised +CHISQ2D = R.^2 ./ M; +CHISQxx = mean(CHISQ2D, 1); % CHISQ in 1D along x +CHISQyy = mean(CHISQ2D, 2); % CHISQ in 1D along y +% - 1.6 - Extracting the REDUCED CHI-SQUARED value including degrees of freedom +CHISQ = sum(sum(CHISQ2D)); + +%% - 2 - PLOTTING THE FINAL DATA COMPARED WITH MODEL AT BOFF = 0 eV +% -- Initialising the plot properties +win = abs(0.05*range(ARPES.kx(:))); +val1 = mean(ARPES.kx(:)); +val2 = mean(ARPES.kx(:)) - abs(0.10*range(ARPES.kx(:))); +val3 = mean(ARPES.kx(:)) + abs(0.10*range(ARPES.kx(:))); +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'Initial Model'); +fig.Position(3) = 4.*pp.fig5x4(1); +fig.Position(4) = 2.*pp.fig5x4(2); +%% - 2.1 - Plotting the model data +% -- Extracting the data matrix +data = M; +% -- Plotting the data +axs(1) = subplot(3,7,[1,2,8,9]); hold on; +ImData(MODEL.kx, MODEL.eb, data); +for i = 1:length(sbn_eb); plot(sbn_kx, sbn_eb{i}, 'r:', 'linewidth', 3); end +img_props(); +xlabel('$$ \bf k_{//} (\AA^{-1}) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +axis([MODEL.kx_lims, MODEL.eb_lims]); +caxis([min(data(:)), max(data(:))]); +axis square; +title('Initial Model'); + +%% - 2.2 - Plotting the ARPES data +axs(2) = subplot(3,7,[3,4,10,11]); hold on; +ImData(ARPES.kx, ARPES.eb, ARPES.data); img_props(); +for i = 1:length(sbn_eb); plot(sbn_kx, sbn_eb{i}, 'r:', 'linewidth', 3); end +xlabel('$$ \bf k_{//} (\AA^{-1}) $$', 'Interpreter', 'latex'); +ylabel('', 'Interpreter', 'latex'); +axis([ARPES.kx_lims, ARPES.eb_lims]); axis square; +caxis([min(ARPES.data(:)), max(ARPES.data(:))]); +title('ARPES Data'); +% -- Plotting the EDC cut lines +line([1 1].*val1, [-1e5, 1e5], 'Color', pp.col.fit{1}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); +line([1 1].*val2, [-1e5, 1e5], 'Color', pp.col.fit{2}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); +line([1 1].*val3, [-1e5, 1e5], 'Color', pp.col.fit{3}, 'LineWidth', pp.llwidth, 'Linestyle', '-'); + +%% - 2.3 - Plotting the 2D residuals +axs(3) = subplot(3,7,[5,6,12,13]); hold on; +ImData(ARPES.kx, ARPES.eb, CHISQ2D); img_props(); +axis([ARPES.kx_lims, ARPES.eb_lims]); axis square; +title('Chi-Squared'); +% -- Add annotation for the quality of fit +text(0.04, 0.94, "$$ \chi^2 = $$ " + string(CHISQ),... + 'interpreter', 'latex', 'fontsize', 16, 'color', 'w', 'Units','normalized'); +% -- Make the colormap bipolar (negative values blue, positive is red) +colormap(axs(3),'jet'); +% -- Make the colormap bipolar (negative values blue, positive is red) +ylabel('', 'interpreter', 'latex'); +xlabel(''); + +%% - 2.4 - Plotting the 1D residuals along x +axs(4) = subplot(3,7,[19,20]); hold on; +bar(ARPES.kx, CHISQxx); +gca_props(); grid on; +xlabel('$$ \bf k_{//} (\AA^{-1}) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf \chi^2(x) $$', 'Interpreter', 'latex'); +xlim(ARPES.kx_lims); +ax = gca; ax.YAxisLocation = 'right'; + +%% - 2.5 - Plotting the 1D residuals along y +axs(5) = subplot(3,7,[7,14]); hold on; +barh(ARPES.eb, CHISQyy); +gca_props(); grid on; +ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +xlabel('$$ \bf \chi^2(y) $$', 'Interpreter', 'latex'); +ylim(ARPES.eb_lims); +ax = gca; ax.YAxisLocation = 'right'; + +%% - 2.6 - Plotting best fit EDCs +%% - 2.6.1 - Gamma EDCs +axs(6) = subplot(3,7,[15,16]); hold on; +% -- Extracting the EDCs +[ARPES_XCut, ARPES_DCut] = Cut(ARPES.kx, ARPES.eb, ARPES.data, 'edc', val1 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(MODEL.kx, MODEL.eb, MODEL.data, 'edc', val1 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{1}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Plotting the sub-band energies +for i = 1:length(YLOC); line([1 1]*YLOC(i), [-1e5, 1e5], 'Color', 'r', 'LineWidth', 2, 'Linestyle', ':'); end +gca_props(); grid on; +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Int. (arb.) $$', 'Interpreter', 'latex'); +axis([min(ARPES_XCut(:)), max(ARPES_XCut(:)), 0, 1.25*max(ARPES_DCut(:))]); +%% - 2.6.1 - LHS and RHS EDCs +axs(7) = subplot(3,7,[17,18]); hold on; +% -- Extracting the LHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(ARPES.kx, ARPES.eb, ARPES.data, 'edc', val2 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(MODEL.kx, MODEL.eb, MODEL.data, 'edc', val2 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{2}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Extracting the RHS EDCs +[ARPES_XCut, ARPES_DCut] = Cut(ARPES.kx, ARPES.eb, ARPES.data, 'edc', val3 + win*[-1, 1]); +[MODEL_XCut, MODEL_DCut] = Cut(MODEL.kx, MODEL.eb, MODEL.data, 'edc', val3 + win*[-1, 1]); +% -- Plotting the experimental and fit spectra +plot(ARPES_XCut, ARPES_DCut, 'k-', 'color', pp.col.fit{3}, 'linewidth', 2*pp.llwidth); +plot(MODEL_XCut, MODEL_DCut, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +gca_props(); grid on; +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +axis([min(ARPES_XCut(:)), max(ARPES_XCut(:)), 0, 1.25*max(ARPES_DCut(:))]); + +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE ARPES AND MODEL DATA CONSISTENTLY +function [ARPES, MODEL] = extract_arpes_and_model(x, arpesStr, cTYPE) + % 1 - Initialising variables + n = length(cTYPE); + % - Extracting parabolic parameters + INT = x(1:n); % scalar of the peak intensity of 2D PE curve. + XLOC = x(n+1:2*n); % scalar of the x-location of the min/max of the 2D parabolic ARPES dispersion. + YLOC = x(2*n+1:3*n); % scalar of the y-location of the min/max of the 2D parabolic ARPES dispersion. + XFWHM = x(3*n+1:4*n); % scalar of the x-axis FWHM for each Gaussian (k-resolution) + YFWHM = x(4*n+1:5*n); % scalar of the y-axis FWHM for each Gaussian (Eb-resolution) + MSTAR = x(5*n+1:6*n); % scalar of the effective mass, which governs the curvature of the parabola. + % - Extracting background parameters + FDEF = x(end-5); % scalar of the FDD Fermi-Level position. + FDT = x(end-4); % scalar of the FDD temperature. + FDW = x(end-3); % scalar of the FDD Gaussian width after convolution. + BGR = x(end-2); % scalar of the gradient of the linear background. + BIN = x(end-1); % scalar of the y-intercept of the linear background. + BCO = x(end); % scalar of the constant background y-offset value. + % - Extracting the kx and eb limits + kx_lims = [min(arpesStr.kx(:)), max(arpesStr.kx(:))]; + eb_lims = [min(arpesStr.eb(:)), max(arpesStr.eb(:))]; + % 2 - Extracting the constructed MODEL data + KX = linspace(kx_lims(1), kx_lims(2), size(arpesStr.kx,2)); + EB = linspace(eb_lims(1), eb_lims(2), size(arpesStr.eb,1))'; + MODEL_DATA = ARPESCurve_FDDGpL(KX, EB, cTYPE, INT, XLOC, YLOC, XFWHM, YFWHM, MSTAR, FDEF, FDT, FDW, BGR, BIN, BCO); + ARPES_DATA = arpesStr.data; + % - Removing any NaN values + MODEL_DATA(isnan(MODEL_DATA)) = 0; + ARPES_DATA(isnan(ARPES_DATA)) = 0; + % 3 - Defining the ARPES data structure + ARPES = struct(); + ARPES.kx = KX; + ARPES.kx_step = mean(diff(KX(:))); + ARPES.kx_lims = kx_lims; + ARPES.eb = EB; + ARPES.eb_step = mean(diff(EB(:))); + ARPES.eb_lims = eb_lims; + ARPES.data = ARPES_DATA; + % 4 - Defining the MODEL data structure + MODEL = struct(); + MODEL.kx = KX; + MODEL.kx_step = mean(diff(KX(:))); + MODEL.kx_lims = kx_lims; + MODEL.eb = EB; + MODEL.eb_step = mean(diff(EB(:))); + MODEL.eb_lims = eb_lims; + MODEL.data = MODEL_DATA; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/kz2model fitting/kz2model_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/kz2model fitting/kz2model_solver.m new file mode 100644 index 0000000..b9454f0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/kz2model fitting/kz2model_solver.m @@ -0,0 +1,268 @@ +function fitStr = kz2model_solver(xdat, ydat, cTYPE, iparams, solve_type) +% fitStr = kz2model_solver(xdat, ydat, cTYPE, iparams, solve_type) +% Function that runs a a Global Optimisation Algorithm based on Simulated +% Annealing to determine the best curve fit to the input XPS data and +% model (initial conditions and bounds). The temperature of the Simulated +% Annealing is set to walk a large span of the parameter space to ensure +% the global minimum is obtained. The minimisation function is based on +% minimising the standard deviation of the squared residuals. Although +% the "simulannealbnd()" algorithm is the best due to its global +% convergence, the option is here to also use "lsqcurvefit()" and +% "lsqnonlin()" for fast convergence to the XPS curve fits. Use this +% function to run the convergence algorithm only one. +% NOTE: use 'xps_solver_n_runs()' to run the algorithm N times, allowing +% for quantification of fit parameter uncertainties. +% +% IN: +% - xdat: 1xN vector that contains the domain of the line profile. +% - ydat: 1xN vector that contains the intensity data of the line profile. +% - cTYPE: string of the type of curves to use; "sGLA" ("pGLA", "sGL", "pGL", "G", "L", "DS"). +% - iparams: 3 cells {x0}{lb}{ub} with Nx8 arrays: the n'th peak parameters [KZ0,INT,MFP,DZ,MR,SKZ0,SINT,ASY,BGR] +% - solve_type: string of the optimisation algorithm to use; "lsqcurvefit" (very fast, good), "lsqnonlin" (fast, not good), "simulannealbnd" (slow, best). +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Default parameters +% - Default input parameters to use +if nargin < 5; solve_type = "lsqcurvefit"; end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Defining the initial conditions and limits of the optimisation method +x0 = iparams{1}(:); +lb = iparams{2}(:); +ub = iparams{3}(:); +% -- Defining the initial conditions and limits of the optimisation method +% --- parameters +if x0(2) < 0; x0(2) = 0; end % if INT < 0, then make it 0 +if x0(3) < 0; x0(3) = 0; end % if MFP FWHM < 0, then make it 0 +if x0(4) < 0; x0(4) = 0; end % if DZ FWHM < 0, then make it 0 +if x0(5) < 0; x0(5) = 0; end % if MR < 0, then make it 0 +if x0(5) > 1; x0(5) = 1; end % if MR > 1, then make it 1 +if x0(7) < 0; x0(7) = 0; end % if SINT < 0, then make it 0 +if x0(8) < 0; x0(8) = 0; end % if ASY < 0, then make it 0 +% --- lower bounds +if lb(2) < 0; lb(2) = 0; end % if INT < 0, then make it 0 +if lb(3) < 0; lb(3) = 0; end % if MFP FWHM < 0, then make it 0 +if lb(4) < 0; lb(4) = 0; end % if DZ FWHM < 0, then make it 0 +if lb(5) < 0; lb(5) = 0; end % if MR < 0, then make it 0 +if lb(5) > 1; lb(5) = 1; end % if MR > 1, then make it 1 +if lb(7) < 0; lb(7) = 0; end % if SINT < 0, then make it 0 +if lb(8) < 0; lb(8) = 0; end % if ASY < 0, then make it 0 +% --- lower bounds +if ub(2) < 0; ub(2) = 0; end % if INT < 0, then make it 0 +if ub(3) < 0; ub(3) = 0; end % if MFP FWHM < 0, then make it 0 +if ub(4) < 0; ub(4) = 0; end % if DZ FWHM < 0, then make it 0 +if ub(5) < 0; ub(5) = 0; end % if MR < 0, then make it 0 +if ub(5) > 1; ub(5) = 1; end % if MR > 1, then make it 1 +if ub(7) < 0; ub(7) = 0; end % if SINT < 0, then make it 0 +if ub(8) < 0; ub(8) = 0; end % if ASY < 0, then make it 0 +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - DEFINING THE XPS DATA AND FITTING ARGUMENTS +% -- Defining a structure that stores all relevant model and data variables +DataObj = struct(); +DataObj.xdat = xdat; +DataObj.ydat = ydat; +% -- Appending the input arguments to the global variable +DataObj.fit_args.solve_type = solve_type; +DataObj.fit_args.cTYPE = cTYPE; +DataObj.fit_args.iparams = iparams; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 5e3; +FuncTol = 1e-7; % 1e-7; +StepTol = 1e-7; % 1e-7; +OptTol = 1e-7; % 1e-7; +ConTol = 1e-7; % 1e-7; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; +%% - 3.1 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR CURVE FITTING +if solve_type == "lsqcurvefit" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqcurvefit,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqcurvefit(@(x,xdat) full_fit_function(x,xdat,DataObj), x0, xdat, ydat, lb, ub, options); +%% - 3.2 - LOCAL SOLVER: UNBOUNDED LEAST SQUARES NONLINEAR REGRESSION FIT +elseif solve_type == "nlinfit" + % -- Defining the optimisation options for the simulated annealing method + options = statset(... + 'MaxFunEvals', MaxFunEvals,... + 'MaxIter', MaxIter,... + 'TolFun', FuncTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,R,J,CovB,MSE,ErrorModelInfo] = nlinfit(roi_xdat, roi_int, @(x,xdat) full_fit_function(x,xdat,DataObj), x0, options); +%% - 3.3 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,grad,hessian] = fminunc(@(x) minimize_function(x,DataObj), x0, options); +%% - 3.4 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,DataObj), x0, [], [], [], [], lb, ub, [], options); +%% - 3.5 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR LEAST SQUARES PROBLEMS +elseif solve_type == "lsqnonlin" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqnonlin,... + 'Algorithm', 'levenberg-marquardt',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqnonlin(@(x) minimize_function(x,DataObj), x0, lb, ub, options); +%% - 3.6 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,DataObj), x0, lb, ub, options); +end + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.cTYPE = cTYPE; +fitStr.iparams = iparams; +%% 4.2 - Storing the XPS data, background, model and minimisation variables +% -- Extracting the original data +fitStr.xdat = xdat; +fitStr.ydat = ydat; +% -- Extracting the X-DOMAIN and DATA +[fitStr.X, fitStr.D] = fit_data(params, DataObj); +% -- Extracting the MODEL +[fitStr.M, fitStr.M0, fitStr.M1] = fit_model(params, DataObj); +% -- Extracting the BACKGROUND +fitStr.B = fit_background(params, DataObj); +% -- Extracting the DATA - BACKGROUND +fitStr.DB = fitStr.D - fitStr.B; +fitStr.MB = fitStr.M + fitStr.B; +% -- Extracting the RESIDUALS (R = D - (M + B)) +fitStr.R = fitStr.D - (fitStr.M + fitStr.B); +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ = sum(fitStr.R.^2 ./ abs(fitStr.M + fitStr.B)); +fitStr.MINFUN = minimize_function(params, DataObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables of each PES curve component +fitStr.XX = linspace(min(fitStr.X(:)), max(fitStr.X(:)), 1e3)'; +fitStr.YY0 = PESCurve(fitStr.XX, fitStr.cTYPE, params(1), params(2), 1./params(3), params(5), params(6), params(7), 0.0, params(8)); +fitStr.YY1 = PESCurve(fitStr.XX, fitStr.cTYPE, mean([params(1),params(1)+params(6)]), params(2), 1./params(4), params(5), 0.0, 0.0, 0.0, params(8)); +fitStr.YY1 = (fitStr.YY1 ./ max(fitStr.YY1(:)))*max(fitStr.YY0(:)); +fitStr.YY = full_fit_function(params, fitStr.XX, DataObj); +fitStr.params = params; +fitStr.KZ0 = params(1); +fitStr.INT = params(2); +fitStr.MFP = params(3); +fitStr.DZ = params(4); +fitStr.MR = params(5); +fitStr.SKZ0 = params(6); +fitStr.SINT = params(7); +fitStr.ASY = params(8); +fitStr.BGR = params(9); + +end + +%% DEFINING THE RESIDUAL MINIMISATION FUNCTION TO BE MINIMISED +function MINFUN = minimize_function(x, DataObj) + % - 1 - Extracting the DATA + [~, D] = fit_data(x, DataObj); + % - 2 - Extracting the MODEL + [M, ~, ~] = fit_model(x, DataObj); + % - 3 - Extracting the BACKGROUND + B = fit_background(x, DataObj); + % - 4 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - (M + B); + % - 5 - Extracting the CHI-SQUARED value to be minimised + MINFUN = sum(R.^2 ./ (M + B)); +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE DATA TO BE FITTED +function [X, D] = fit_data(x, DataObj) + X = DataObj.xdat; + D = DataObj.ydat; + D(isnan(D)) = 0; + if size(D, 2) > 1; D = D'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES BACKGROUND +function B = fit_background(x, DataObj) + B = DataObj.xdat.*0 + x(9); + B(isnan(B)) = 0; + if size(B, 2) > 1; B = B'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES CURVE FIT +function [M, M0, M1] = fit_model(x, DataObj) + % - 1 - Extract the curve with only MFP broadening + M0 = PESCurve(DataObj.xdat, DataObj.fit_args.cTYPE, x(1), x(2), 1./x(3), x(5), x(6), x(7), 0.0, x(8)); + M0(isnan(M0)) = 0; + if size(M0, 2) > 1; M0 = M0'; end + % - 2 - Extract the curve with only kz broadening + M1 = PESCurve(DataObj.xdat, DataObj.fit_args.cTYPE, x(1), x(2), 1./x(4), x(5), x(6), x(7), 0.0, x(8)); + M1(isnan(M1)) = 0; + if size(M1, 2) > 1; M1 = M1'; end + % - 3 - Extract the curve with MFP + KZ broadening + M = PESCurve(DataObj.xdat, DataObj.fit_args.cTYPE, x(1), x(2), (1./x(3)+1./x(4)), x(5), x(6), x(7), 0.0, x(8)); + M(isnan(M)) = 0; + if size(M, 2) > 1; M = M'; end +end + +%% DEFINING THE FINAL FUNCTION THAT DESCRIBES THE PES CURVE TO BE FITTED +function MB = full_fit_function(x, xdat, DataObj) + % - 1 - Extract the curve with MFP + KZ broadening + M = PESCurve(xdat, DataObj.fit_args.cTYPE, x(1), x(2), (1./x(3)+1./x(4)), x(5), x(6), x(7), 0.0, x(8)); + M(isnan(M)) = 0; + if size(M, 2) > 1; M = M'; end + % - 2 - Extracting the BACKGROUND + B = xdat.*0 + x(9); + B(isnan(B)) = 0; + if size(B, 2) > 1; B = B'; end + % - 3 - Extracting the FULL MODEL CURVE + MB = M + B; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/kz2model fitting/kz2model_view_fit.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/kz2model fitting/kz2model_view_fit.m new file mode 100644 index 0000000..bac5b9e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/kz2model fitting/kz2model_view_fit.m @@ -0,0 +1,66 @@ +function fig = kz2model_view_fit(fitStr) +% fig = kz2model_view_fit(fitStr) +% This function is used to plot the results of the curve fitting +% performed by 'fitStr = kz2model_solver(...)'. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - fitStr: MATLAB data-structure that contains all fit parameters / variables / information +% +% OUT: +% - fig: figure output + +%% - 1 - Extracting all model data and information +X = fitStr.xdat; % Original domain +D = fitStr.ydat; % Original data +M0 = fitStr.M0; % Model data (MFP) +M = fitStr.M; % Model data (MFP+KZ) +B = fitStr.B; % Background +DB = D - B; % Data after being background subtracted +XX = fitStr.XX; % Interpolated domain +YY0 = fitStr.YY0; % Interpolated MFP broadened spectrum +YY1 = fitStr.YY1; % Interpolated Kz broadened spectrum +YY = fitStr.YY; % Interpolated MFP + kz broadened spectrum +%% - 3 - Determination of the residuals and chi-squared +R = M - (D - B); % Residuals +CHISQ = sum(R.^2 ./ abs(M)); % Chi-squared + +%% - 4 - Plotting the model to be used for fitting +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'XPS Curve Fitting'); +fig.Position(3) = 1.5*pp.fig5x4(1); +fig.Position(4) = pp.fig5x4(2); +%% - 4.2 - PLOTTING THE BEST FIT CURVE COMPONENTS AND FINAL MODEL FIT +subplot(4,1,[1,2,3]); hold on; +% -- Plotting all of the curve components +area(XX, YY, 'FaceColor', pp.col.fit{2}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); +plot(XX, YY, 'k-', 'linewidth', 0.25); +area(XX, YY1, 'FaceColor', pp.col.fit{4}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); +plot(XX, YY1, 'k-', 'linewidth', 0.25); +area(XX, YY0, 'FaceColor', pp.col.fit{3}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); +plot(XX, YY0, 'k-', 'linewidth', 0.25); +% -- Plotting the curve component energy locations +line([fitStr.KZ0, fitStr.KZ0], [0, fitStr.INT], 'Color', [0 0 0], 'LineWidth', 2, 'Linestyle', '-'); +line(fitStr.KZ0+[fitStr.SKZ0, fitStr.SKZ0], [0, fitStr.INT*fitStr.SINT], 'Color', [0 0 0], 'LineWidth', 2, 'Linestyle', '-'); +% -- Plotting the experimental and fit spectra +plot(X, DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(XX, YY, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +axis([min(X(:)), max(X(:)), 0.0, 1.10*max(DB(:))]); +title("Best Fit Outcome", 'interpreter', 'none', 'fontsize', 9); +%% - 4.3 - PLOTTING THE RESIDUALS FOR THE BEST FIT TO THE DATA +subplot(4,1,4); hold on; +bar(X, R, 'facecolor', [0 0 0]); +gca_props(); grid on; +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +xlabel('$$ \bf k_z (A^{-1}) $$', 'Interpreter', 'latex'); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/kz2model fitting/kz2model_view_init.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/kz2model fitting/kz2model_view_init.m new file mode 100644 index 0000000..22c42fb --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/kz2model fitting/kz2model_view_init.m @@ -0,0 +1,77 @@ +function fig = kz2model_view_init(xdat, ydat, cTYPE, iparams) +% fig = kz2model_view_init(xdat, ydat, cTYPE, iparams) +% This function is used to plot the initial curve fitting model prior to +% using the 'kz2model_solver()' algorithm. This is used as an informative +% plot that allows you to view and create a better initial guess of the +% model prior to running the fitting algorithm. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - xdat: 1xN vector that contains the domain of the line profile. +% - ydat: 1xN vector that contains the intensity data of the line profile. +% - cTYPE: string of the type of curves to use; "sGLA" ("pGLA", "sGL", "pGL", "G", "L", "DS"). +% - iparams: 3 cells {x0}{lb}{ub} with Nx8 arrays: the n'th peak parameters [KZ0,INT,MFP,DZ,MR,SKZ0,SINT,ASY,BGR] +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% - 1 - Extracting all model data and information +X = xdat; % Original domain +D = ydat; % Original data +M0 = PESCurve(xdat, cTYPE, iparams{1}(1), iparams{1}(2), 1./iparams{1}(3), iparams{1}(5), iparams{1}(6), iparams{1}(7), 0.0, iparams{1}(8)); % Model data (MFP only) +M1 = PESCurve(xdat, cTYPE, mean([iparams{1}(1),iparams{1}(1)+iparams{1}(6)]), iparams{1}(2), 1./iparams{1}(4), iparams{1}(5), 0.0, 0.0, 0.0, iparams{1}(8)); % Model data (KZ only) +M = PESCurve(xdat, cTYPE, iparams{1}(1), iparams{1}(2), 1./iparams{1}(3)+1./iparams{1}(4), iparams{1}(5), iparams{1}(6), iparams{1}(7), 0.0, iparams{1}(8)); % Model data (MFP+KZ) +B = iparams{1}(9); % Background +DB = D - B; % Data after being background subtracted +%% - 3 - Determination of the residuals and chi-squared +R = M - (D - B); % Residuals +CHISQ = sum(R.^2 ./ abs(M)); % Chi-squared + +%% - 4 - Plotting the model to be used for fitting +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'XPS Curve Fitting'); +fig.Position(3) = 1.5*pp.fig5x4(1); +fig.Position(4) = pp.fig5x4(2); +%% - 4.2 - PLOTTING THE BEST FIT CURVE COMPONENTS AND FINAL MODEL FIT +subplot(4,1,[1,2,3]); hold on; +% -- Plotting all of the curve components +area(X, M, 'FaceColor', pp.col.fit{2}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); +plot(X, M, 'k-', 'linewidth', 0.25); +area(X, M0, 'FaceColor', pp.col.fit{3}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); +plot(X, M0, 'k-', 'linewidth', 0.25); +area(X, M1, 'FaceColor', pp.col.fit{4}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); +plot(X, M1, 'k-', 'linewidth', 0.25); +% -- Plotting the curve component energy locations +line([iparams{1}(1), iparams{1}(1)], [0, iparams{1}(2)], 'Color', [0 0 0], 'LineWidth', 2, 'Linestyle', '-'); +line(iparams{1}(1)+[iparams{1}(6), iparams{1}(6)], [0, iparams{1}(2)*iparams{1}(7)], 'Color', [0 0 0], 'LineWidth', 2, 'Linestyle', '-'); +% -- Plotting the experimental and fit spectra +plot(X, DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(X, M, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +axis([min(X(:)), max(X(:)), min(DB(:)), 1.10*max(DB(:))]); +title("Initial Curves for Fitting", 'interpreter', 'none', 'fontsize', 9); +%% - 4.3 - PLOTTING THE RESIDUALS FOR THE BEST FIT TO THE DATA +subplot(4,1,4); hold on; +bar(X, R, 'facecolor', [0 0 0]); +gca_props(); grid on; +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +xlabel('$$ \bf k_z (A^{-1}) $$', 'Interpreter', 'latex'); + +%% - 5 - Plotting the uncertainties to allow for easier optimisation +subplot(4,1,[1,2,3]); hold on; +%% - 5.1 - Plotting the primary peak uncertainties +lbBE = iparams{2}(1); ubBE = iparams{3}(1); +lbINT = iparams{2}(2); ubINT = iparams{3}(2); +x_vals = [lbBE, lbBE, ubBE, ubBE, lbBE]; +y_vals = [lbINT, ubINT, ubINT, lbINT, lbINT]; +patch(x_vals, y_vals, pp.col.fit{3}, 'FaceAlpha', 0.65, 'EdgeAlpha', 0); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/vb2le fitting/vb2le_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/vb2le fitting/vb2le_solver.m new file mode 100644 index 0000000..455b7d4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F012 - arpes data fitting/vb2le fitting/vb2le_solver.m @@ -0,0 +1,198 @@ +function fitStr = vb2le_solver(kx, eb, data, bgrnd_type, iparams, plot_results) +% ffitStr = vb2le_solver(kx, eb, data, bgrnd_type, iparams, plot_results) +% Function that fits to the valence band leading edge using a 1st order +% polynomial ('poly1') for the leading edge. The background can be +% defined also as a 1st order polynomial ('poly1') or a constant flat +% baseline ('flat'). The intersection between these two lines then +% determines the VBM position based on the Leading Edge (LE) method +% discussed in literature. +% +% IN: +% - kx: vector / array of the wave vector (x-domain) of the ARPES data. +% - eb: vector / array of the binding energy (y-domain) of the ARPES data. +% - data: NxM array of ARPES intensity. +% - bgrnd_type: String of either "poly0" (flat background), "poly1" (linear background), "none" (to the x-axis baseline) +% - iparams: 1x6 array: the model fit parameters [KWIN,EWIN_BGRND,EWIN_EDGE,dESmooth] +% - plot_results: Either 1 or 0; plots the fits if 1. +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Default parameters +if nargin < 6; plot_results = 1; end +if isempty(plot_results); plot_results = 1; end +if isempty(bgrnd_type); bgrnd_type = "poly0"; end + +%% - 1 - Initialising the fitting parameters +pp = plot_props(); +% - Extracting the VB fit parameters +KWIN = iparams{1}; if isempty(KWIN); KWIN = [-0.05, 0.05]; end % window of the EDC taken around the VBM position +EWIN_BGRND = iparams{2}; if isempty(EWIN_BGRND); EWIN_BGRND = [-0.25, 0.25]; end % window of the background region within the EDC cut +EWIN_EDGE = iparams{3}; if isempty(EWIN_EDGE); EWIN_EDGE = -0.75 + [-0.25, 0.25]; end % window of the VBM leading edge region within the EDC cut +dESmooth = iparams{4}; if isempty(dESmooth); dESmooth = 0; end % can be empty []. Single, constant value that defines Gaussian pre-smoothing energy width. +% - Validity check on the inputs +KWIN = sort(KWIN); +EWIN_BGRND = sort(EWIN_BGRND); +EWIN_EDGE = sort(EWIN_EDGE); +dESmooth = abs(dESmooth); +% - Capping the k-integration window to the min/max limits +if KWIN(1) < min(kx(:)); KWIN(1) = min(kx(:));end +if KWIN(2) > max(kx(:)); KWIN(2) = max(kx(:)); end + +%% - 2 - Extracting the EDC cut from the data +% - Extracting the full EDC cut through the VBM +[XCut, DCut] = Cut(kx, eb, data, 'edc', KWIN); +DCut = DCut ./ max(DCut(:)); +% - Smoothing the data if necessary +if dESmooth ~= 0; DCut = Gaco1(DCut, dESmooth); end +% - Extracting the region of the background +[~, lb_indx] = min(abs(XCut - EWIN_BGRND(1))); +[~, ub_indx] = min(abs(XCut - EWIN_BGRND(2))); +XCut_back = XCut(lb_indx:ub_indx); +DCut_back = DCut(lb_indx:ub_indx); +% - Extracting the region of the edge +[~, lb_indx] = min(abs(XCut - EWIN_EDGE(1))); +[~, ub_indx] = min(abs(XCut - EWIN_EDGE(2))); +XCut_edge = XCut(lb_indx:ub_indx); +DCut_edge = DCut(lb_indx:ub_indx); +XX = linspace(min(XCut(:)), max(XCut(:)), 1e3)'; + +%% - 3 - Fitting a linear equation to the leading edge +% -- Fitting the data +fit_edge = fit(XCut_edge, DCut_edge, 'poly1'); +% - Extracting confidence interval for each coefficient +fitci_edge = abs(0.5*range(confint(fit_edge))); +% - Evaluating the best fit lines over a consistent domain +DD_edge = fit_edge(XX); +% - Extracting confidence interval to be plotted as a patch +ci_edge = predint(fit_edge, XX, 0.95, 'observation', 'off'); +ciXX = [XX; flipud(XX)]; +ciDD_edge = [ci_edge(:,1); flipud(ci_edge(:,2))]; + +%% - 4 - Fitting a to the background +if bgrnd_type == "poly0" + % -- Fitting the data + fit_back.p1 = 0; + fit_back.p2 = mean(DCut_back(:)); + % - Extracting confidence interval for each coefficient + fitci_back = 3*std(DCut_back(:))*[1,1]; + % - Evaluating the best fit lines over a consistent domain + DD_back = zeros(size(XX))+fit_back.p2; + % - Extracting confidence interval to be plotted as a patch + ci_back = [DD_back-fitci_back, DD_back+fitci_back]; + ciXX = [XX; flipud(XX)]; + ciDD_back = [ci_back(:,1); flipud(ci_back(:,2))]; +elseif bgrnd_type == "poly1" + % -- Fitting the data + fit_back = fit(XCut_back, DCut_back, 'poly1'); + % - Extracting confidence interval for each coefficient + fitci_back = abs(0.5*range(confint(fit_back))); + % - Evaluating the best fit lines over a consistent domain + DD_back = fit_back(XX); + % - Extracting confidence interval to be plotted as a patch + ci_back = predint(fit_back, XX, 0.95, 'observation', 'off'); + ciXX = [XX; flipud(XX)]; + ciDD_back = [ci_back(:,1); flipud(ci_back(:,2))]; +elseif bgrnd_type == "none" + % -- Fitting the data + fit_back.p1 = 0; + fit_back.p2 = 0; + % - Extracting confidence interval for each coefficient + fitci_back = 3*std(0.*DCut_back(:))*[1,1]; + % - Evaluating the best fit lines over a consistent domain + DD_back = zeros(size(XX))+fit_back.p2; + % - Extracting confidence interval to be plotted as a patch + ci_back = [DD_back-fitci_back, DD_back+fitci_back]; + ciXX = [XX; flipud(XX)]; + ciDD_back = [ci_back(:,1); flipud(ci_back(:,2))]; +end + +%% - 5 - Finding the point of intersection and its uncertainty +% - Finding the mean value of the POI +a = fit_back.p1; +c = fit_back.p2; +b = fit_edge.p1; +d = fit_edge.p2; +coeff = (d-c)./(a-b); +X0 = round(coeff, 3); +Y0 = round(a.*coeff + c, 3); +% - Finding the uncertainty in the POI +A = fit_back.p1 + fitci_back(1); +C = fit_back.p2 - fitci_back(2); +B = fit_edge.p1 - fitci_edge(1); +D = fit_edge.p2 + fitci_edge(2); +coeff = (D-C)./(A-B); +dX0 = round(abs(X0 - (coeff)), 3); +dY0 = round(abs(Y0 - (A.*coeff + C)), 3); + +%% - 5 - Plotting the fitting result +if plot_results == 1 + % -- Initialising the figure + fig = figure(); + fig.Position(3) = 1.25*pp.fig5x4(1); + fig.Position(4) = 2.00*pp.fig5x4(2); + + % -- Plotting the ARPES data and the EDC cut location + subplot(2,1,1); hold on; + ImData(eb, kx, data); + patch([-1e3, 1e3, 1e3, -1e3, -1e3],[KWIN(1), KWIN(1), KWIN(2), KWIN(2), KWIN(1)],... + [0 1 0], 'linewidth', 1, 'facealpha', 0, 'edgecolor', [0 0 1]); + img_props(); + axis([min(eb(:)), max(eb(:)),min(kx(:)), max(kx(:))]); + xlabel('$$ \bf E_{B} (eV) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf k_x (\AA^{-1}) $$', 'Interpreter', 'latex'); + + % -- Plotting the EDC cut and the VB fitting to the leading edge + subplot(2,1,2); hold on; + % -- Plotting the full EDC cut first + plot(XCut, DCut, 'k.-', 'color', pp.col.fit{1}, 'LineWidth', 0.50); + % -- Plotting the fits to the EDC background + patch(ciXX, ciDD_back, pp.col.fit{2}, 'EdgeAlpha', 0, 'facealpha', 0.25); + plot(XCut_back, DCut_back, 'k.-', 'color', pp.col.fit{2}, 'LineWidth', 1.50); + plot(XX, DD_back, 'k:', 'color', pp.col.fit{2}, 'LineWidth', 1.50); + % -- Plotting the fits to the EDC leading edge + patch(ciXX, ciDD_edge, pp.col.fit{3}, 'EdgeAlpha', 0, 'facealpha', 0.25); + plot(XCut_edge, DCut_edge, 'g.-', 'color', pp.col.fit{3}, 'LineWidth', 1.50); + plot(XX, DD_edge, 'g:', 'color', pp.col.fit{3}, 'LineWidth', 1.50); + % -- Plotting the point of intersection + errorbar(X0, Y0, dY0, dY0, dX0, dX0, 'ko',... + 'markersize', 7, 'color', [0 0 0], 'markerfacecolor', [1 0 0]); + % -- Add text to show the POI + text(0.05, 0.90, "$$ E_{VBM} = (" + X0 + " \pm " + dX0 + ") eV $$",... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); + % -- Formatting the figure + gca_props(); + ax = gca; + ax.XAxisLocation = 'bottom'; % 'bottom' | 'top' | 'origin' + ax.YAxisLocation = 'left'; % 'left' | 'right' | 'origin' + % - Axis labels and limits + xlabel('$$ \bf E_{B} (eV) $$', 'Interpreter', 'latex'); + ylabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); + % - Plotting the x- and y-axes + axis([min(eb(:)), max(eb(:)), 0, 1.15]); +end + + +%% 6 - Appending data to MATLAB data structure +fitStr = struct(); +fitStr.vb_fit_args = iparams; +% - Appending all the EDC cuts taken +fitStr.XCut = XCut; +fitStr.DCut = DCut; +fitStr.XCut_back = XCut_back; +fitStr.DCut_back = DCut_back; +fitStr.XCut_edge = XCut_edge; +fitStr.DCut_edge = DCut_edge; +% - Appending the best fits to the background and edge +fitStr.fit_back = fit_back; +fitStr.fit_edge = fit_edge; +fitStr.XX = XX; +fitStr.DD_back = DD_back; +fitStr.DD_edge = DD_edge; +% - Appending the VBM position and its uncertainty +fitStr.VBM = X0; +fitStr.dVBM = dX0; +fitStr.VBM_int = Y0; +fitStr.dVBM_int = dY0; + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/nlayer_pes_model.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/nlayer_pes_model.m new file mode 100644 index 0000000..3c4f167 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/nlayer_pes_model.m @@ -0,0 +1,280 @@ +function pes_model = nlayer_pes_model(pes_hv, lyr_mat, lyr_cls, lyr_thick, theta, gamma, plot_result) +% pes_model = nlayer_pes_model(pes_hv, lyr_mat, lyr_cls, lyr_thick, theta, gamma, plot_result) +% Function that determines the total photoelectron intensity originating +% from N independent layers in a sample that consists of several +% different materials of a user-defined thickness. The core-level being +% probed is also defined, as well as the experimental geometry. +% -------------------------------------------------------------------- +% The model does the following: +% +% (1) Using the input photon energies, the electron kinetic energies +% are determined so that the attenuation length / inelastic-mean free +% path (IMFP) of electrons in each layer can be determined. +% Using: +% Ek = Ehv - Ebe - WF , +% Ek is the electron kinetic energy; Ehv is the input photon energy; +% Ebe is the binding energy of the electron, which is determined by +% in the Photoionisation Energy and Fluorescence Database (PIEFD) +% whose value depends on the input core-level defined; WF is the sample +% work function, which is determined by the Materials Properties +% Database (MPD), whose value depends on the layer material. +% +% (2) The total intensity of photoelectrons from each layer depends +% on several parameters, all of which can be determined; +% I = N * F +% where N is the number of atoms per unit volume, determined by: +% N = N_AVOGADRO * DENSITY / MOLECULAR WEIGHT. +% The density and molecular weight are both contained within the MPD +% for each material defined. +% F is the relative sensitivity factor, determined by: +% F = XSECT * ANG_CORR * IMFP * TRANS_CORR * exp(-C/IMFP) +% where XSECT is the photoionisation cross-section, determined within +% the Photoionisation Cross-Section and Asymmetry Database (PIXSAD). +% ANG_CORR is the angular correction factor (function of the +% ASYmmetry parameter and the ANGle between the incident x-rays and +% analyser), which is determined by; +% ANG_CORR = 1 + 0.5*ASY (1.5 * sin(ANG)^2 - 1). +% The IMFP is determined from the Tanuma et. al. TPP-2M formalism, +% defined within the 'imfp_tpp2m_mpd()' function, only the kinetic +% energy and material are required, which are known from the user +% inputs. +% TRANS_CORR is the transmission correction (function of the kinetic +% energy) and this is assumed to be 1 for this model. +% C is the correction for surface contamination, which is +% proportional to layer thickness, which we assume is equal to 0 for +% this model. +% Thus, the TOTAL intensity I0 of each layer can be determined using +% the formalism discussed here. +% +% (3) The Beer-Lambert law is used to model the attenuation of the +% photoelectron intensity as a function of depth. This model states +% that the photoelectron intensity decreases exponentially due to +% inelastic scattering, with a decay constant equal to the IMFP. +% Thus, for a bulk, single-layer system, the Beer-Lambert law states: +% I(z) = I0 * exp(-z / IMFP), +% which gives the photoelectron intensity, I, that emerges from a +% depth, z, within the sample. This is applied to each layer in the +% n-layered stack defined by the user, where I0 is determined from +% part (2), discussed above. The total integral intensity for each +% layer in the sample stack then gives the total emitted +% photoelectron intensity. +% +% (4) Once the integral intensites from each layer are determined, +% the final intensities are expressed in terms of a 'relative +% contribution'. Here, each layer intensity is normalised by the sum +% of all the intensities at each photon energy. +% -------------------------------------------------------------------- +% +% IN: +% - pes_hv: Nx1 column vector of the input photon energy. +% - lyr_mat: Mx1 cell-vector of the material for each layer in the stack; e.g. "Si", "SiO2", "Al2O3"... +% - lyr_cls: Mx1 cell-vector of the core-level probed for each layer in the stack; e.g. "Si(2p)", "Si(2s)", "Al(2p)"... +% - lyr_thick: Mx1 cell-vector of the thickness of each layer in the stack (in nano-metres) +% - theta: scalar of the angle between the emitted photoelectrons and the surface normal (degrees). +% - gamma: scalar of the angle between the incident x-rays and the analyser (degrees). +% +% OUT: +% - pes_model: data structure that contains all the pes model parameters and variables. + +%% Default parameters +% -- Defining the default parameters +if nargin < 7; plot_result = 1; end +if nargin < 6; gamma = 70; end +if nargin < 5; gamma = 70; theta = 0; end +if isempty(plot_result); plot_result = 1; end +if isempty(gamma); gamma = 80; end +if isempty(theta); theta = 0; end +if isempty(pes_hv); pes_hv = linspace(350, 1500, 1e4); end +% -- Extracting the total number of layers to be probed +Nlyrs = length(lyr_mat); +% -- Verify that the input layer variables are consistent i nsize +lyr_cls = lyr_cls(1:Nlyrs); +lyr_thick = lyr_thick(1:Nlyrs); + +%% 1 - Determination of the IMFP at all kinetic energy for each layer material +%% 1.1 - Defining the notation for core levels +% --- Defining in terms of orbital notation +cls_00 = {... + '1s',... + '2s', '2p',... + '3s', '3p', '3d',... + '4s', '4p', '4d', '4f',... + '5s', '5p', '5d', '5f',... + '6s', '6p', '6d',... + '7s',... + }; +% --- Defining in terms of IUPAC notation +cls_01 = {... + 'K',... % 1s + 'L1', 'L3',... % 2s, 2p + 'M1', 'M3', 'M5',... % 3s, 3p, 3d + 'N1', 'N3', 'N5', 'N7',... % 4s, 4p, 4d, 4f + 'O1', 'O3', 'O5', 'O7',... % 5s, 5p, 5d, 5f + 'P1', 'P3', 'P5',... % 6s, 6p, 6d + 'Q1',... % 7s + }; +%% 1.2 - Extracting the IMFP +for i = 1:Nlyrs + %% 1.2.1 - Extracting the binding energy for each layer material core-level + % (A) Determine the core-level being probed + lyr_elem{i} = lyr_cls{i}(1:end-4); % Corresponding element + lyr_elem_cls{i} = lyr_cls{i}(end-2:end-1); % Corresponding core-level + lyr_piefd{i} = get_piefd_props(lyr_elem{i}); % Extract properties from PIEFD + findx = find(contains(cls_00, string(lyr_elem_cls{i}))); % Find index of the core-level + if isempty(findx); findx = find(contains(cls_01, string(lyr_elem_cls{i}))); end + % (B) Extracting the core-level binding energy + cls_iupac = cls_01(findx); % Core-level in IUPAC notation + piefd_varnames = lyr_piefd{i}.Properties.VariableNames; + findx = strcmpi(piefd_varnames(:), "BE_" + string(cls_iupac)); + lyr_be{i} = lyr_piefd{i}{1,findx}; % Extracting the binding energy of the core-level + lyr_Z{i} = lyr_piefd{i}.ATOM_ZNUM; % Extracting the atomic Z number of the layer + %% 1.2.2 - Extracting the work function for each layer material + % (A) Extract the properties from the MPD + lyr_mpd{i} = get_mpd_props(lyr_mat{i}); + % (B) Extract the work function, density and atomic mass + lyr_WF{i} = lyr_mpd{i}.ELE_WFUNC; + lyr_density{i} = lyr_mpd{i}.DENSITY; + lyr_atmass{i} = lyr_mpd{i}.ATOM_MASS; + % -- Validity check - if the result is NaN, assume a value of zero + if isnan(lyr_WF{i}); lyr_WF{i} = 0; end + %% 1.2.3 - Determine the kinetic energy of photoelectrons for each layer material + pes_ke{i} = pes_hv - lyr_be{i} - lyr_WF{i}; + %% 1.2.4 - Determine the IMFP at all kinetic energies for each layer material + lyr_IMFP{i} = eimfp_tpp2m_mpd(pes_ke{i}, lyr_mat{i}); + % Ensuring the imfp is a row vector + if size(lyr_IMFP{i}, 1) > 1; lyr_IMFP{i} = lyr_IMFP{i}'; end + % Convert the IMFP into nm + lyr_IMFP{i} = 0.1 * lyr_IMFP{i}; +end +% - Determine the average Z number for all layers +lyr_avgZ = mean(cell2mat(lyr_Z(:))); + +%% 2 - Determine the maximum intensity I0 for each layer material +for i = 1:Nlyrs + %% 2.1 - Determine the total number of atoms per unit volume + Nav = 6.022e23; + lyr_N{i} = Nav.*(lyr_density{i} ./ lyr_atmass{i}); % number of atoms per unit volume + %% 2.2 - Extracting the photoionisation cross section + [~, lyr_sigma{i}, lyr_beta{i}] = get_pixsad_props(lyr_elem{i}, lyr_elem_cls{i}, pes_hv); % Extract properties from PIXSAD + % -- Validity check - if the result is NaN, assume a value of zero (or 2 for asymmetry) + if isnan(lyr_sigma{i}); lyr_sigma{i} = 0; end + if isnan(lyr_beta{i}); lyr_beta{i} = 2; end + %% 2.3 - Determine the adjusted asymmetry factor for solid materials + a = 0.781; b = 0.00514; c = 0.000031; + lyr_beta_adj{i} = lyr_beta{i} .* (a - b.*lyr_avgZ + c.*lyr_avgZ.^2); + %% 2.4 - Determine the angular correction factor using the asymmetry parameter + lyr_gamma{i} = 1 + 0.5.*lyr_beta_adj{i} .* (1.5.*(sin(deg2rad(gamma))).^2 - 1); + %% 2.5 - Determine other variables for I0 calculation + lyr_T{i} = 1; % Transmission correction + lyr_c{i} = 0; % Surface contamination correction + %% 2.6 - Determine the relative sensitivity factor F + lyr_F{i} = lyr_sigma{i}.*lyr_gamma{i}.*lyr_IMFP{i}.*lyr_T{i}.*exp(-lyr_c{i}./lyr_IMFP{i}); + %% 2.7 - Determine the value of I0 + lyr_I0{i} = lyr_N{i} .* lyr_F{i}; +end + +%% 3 - Use Beer-Lambert law to determine the total photoelectron intensity for each layer +% For one layer (Bulk) +if Nlyrs == 1 + % -- Extracting the layer intensities + lyr_ints{1} = lyr_I0{1} .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))); + % -- Normalising each curve in terms of its relative contribution + lyr_norm = lyr_ints{1}; + lyr_ints0{1} = lyr_ints{1} ./ lyr_norm; +% For two layers (S1 -> Bulk) +elseif Nlyrs == 2 + % -- Extracting the layer intensities + lyr_ints{1} = lyr_I0{1} .* (1 - exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta)))); + lyr_ints{2} = lyr_I0{2} .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))); + % -- Normalising each curve in terms of its relative contribution + lyr_norm = lyr_ints{1} + lyr_ints{2}; + lyr_ints0{1} = lyr_ints{1} ./ lyr_norm; + lyr_ints0{2} = lyr_ints{2} ./ lyr_norm; +% For three layers (S1 -> S2 -> Bulk) +elseif Nlyrs == 3 + % -- Extracting the layer intensities + lyr_ints{1} = lyr_I0{1} .* (1 - exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta)))); + lyr_ints{2} = lyr_I0{2} .* (1 - exp(-lyr_thick{2} ./ (lyr_IMFP{2} .* cos(theta)))) .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))); + lyr_ints{3} = lyr_I0{3} .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))).* exp(-lyr_thick{2} ./ (lyr_IMFP{2} .* cos(theta))); + % -- Normalising each curve in terms of its relative contribution + lyr_norm = lyr_ints{1} + lyr_ints{2} + lyr_ints{3}; + lyr_ints0{1} = lyr_ints{1} ./ lyr_norm; + lyr_ints0{2} = lyr_ints{2} ./ lyr_norm; + lyr_ints0{3} = lyr_ints{3} ./ lyr_norm; +% For four layers (S1 -> S2 -> S3 -> Bulk) +elseif Nlyrs == 4 + % -- Extracting the layer intensities + lyr_ints{1} = lyr_I0{1} .* (1 - exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta)))); + lyr_ints{2} = lyr_I0{2} .* (1 - exp(-lyr_thick{2} ./ (lyr_IMFP{2} .* cos(theta)))) .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))); + lyr_ints{3} = lyr_I0{3} .* (1 - exp(-lyr_thick{3} ./ (lyr_IMFP{3} .* cos(theta)))) .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))).* exp(-lyr_thick{2} ./ (lyr_IMFP{2} .* cos(theta))); + lyr_ints{4} = lyr_I0{4} .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))).* exp(-lyr_thick{2} ./ (lyr_IMFP{2} .* cos(theta))).* exp(-lyr_thick{3} ./ (lyr_IMFP{3} .* cos(theta))); + % -- Normalising each curve in terms of its relative contribution + lyr_norm = lyr_ints{1} + lyr_ints{2} + lyr_ints{3} + lyr_ints{4}; + lyr_ints0{1} = lyr_ints{1} ./ lyr_norm; + lyr_ints0{2} = lyr_ints{2} ./ lyr_norm; + lyr_ints0{3} = lyr_ints{3} ./ lyr_norm; + lyr_ints0{4} = lyr_ints{4} ./ lyr_norm; +% For five layers (S1 -> S2 -> S3 -> S4 -> Bulk) +elseif Nlyrs == 5 + % -- Extracting the layer intensities + lyr_ints{1} = lyr_I0{1} .* (1 - exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta)))); + lyr_ints{2} = lyr_I0{2} .* (1 - exp(-lyr_thick{2} ./ (lyr_IMFP{2} .* cos(theta)))) .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))); + lyr_ints{3} = lyr_I0{3} .* (1 - exp(-lyr_thick{3} ./ (lyr_IMFP{3} .* cos(theta)))) .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))).* exp(-lyr_thick{2} ./ (lyr_IMFP{2} .* cos(theta))); + lyr_ints{4} = lyr_I0{4} .* (1 - exp(-lyr_thick{4} ./ (lyr_IMFP{4} .* cos(theta)))) .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))).* exp(-lyr_thick{2} ./ (lyr_IMFP{2} .* cos(theta))).* exp(-lyr_thick{3} ./ (lyr_IMFP{3} .* cos(theta))); + lyr_ints{5} = lyr_I0{5} .* exp(-lyr_thick{1} ./ (lyr_IMFP{1} .* cos(theta))).* exp(-lyr_thick{2} ./ (lyr_IMFP{2} .* cos(theta))).* exp(-lyr_thick{3} ./ (lyr_IMFP{3} .* cos(theta))).* exp(-lyr_thick{4} ./ (lyr_IMFP{4} .* cos(theta))); + % -- Normalising each curve in terms of its relative contribution + lyr_norm = lyr_ints{1} + lyr_ints{2} + lyr_ints{3} + lyr_ints{4} + lyr_ints{5}; + lyr_ints0{1} = lyr_ints{1} ./ lyr_norm; + lyr_ints0{2} = lyr_ints{2} ./ lyr_norm; + lyr_ints0{3} = lyr_ints{3} ./ lyr_norm; + lyr_ints0{4} = lyr_ints{4} ./ lyr_norm; + lyr_ints0{5} = lyr_ints{5} ./ lyr_norm; +% For any higher order layer, return an error +else + msg = 'Toooooo many layers defined; only calculates a maximum of 5 layers = 4 (overlayers) + 1 (bulk).'; + error(msg) +end + +%% 4 - Creating a MATLAB data structure to store all of the results +% - Defining the structure +pes_model = struct(); +% - Defining the input arguments +pes_model.pes_hv = pes_hv; +pes_model.lyr_mat = lyr_mat; +pes_model.lyr_cls = lyr_cls; +pes_model.lyr_thick = lyr_thick; +pes_model.theta = theta; +pes_model.gamma = gamma; +% - Defining the material properties +pes_model.Nlyrs = Nlyrs; +pes_model.lyr_mpd = lyr_mpd; +pes_model.lyr_piefd = lyr_piefd; +% - Defining the properties for extracting the IMFP +pes_model.lyr_elem = lyr_elem; +pes_model.lyr_elem_cls = lyr_elem_cls; +pes_model.lyr_be = lyr_be; +pes_model.lyr_Z = lyr_Z; +pes_model.lyr_avgZ = lyr_avgZ; +pes_model.lyr_WF = lyr_WF; +pes_model.lyr_density = lyr_density; +pes_model.lyr_atmass = lyr_atmass; +pes_model.pes_ke = pes_ke; +pes_model.lyr_IMFP = lyr_IMFP; +% - Defining the properties for extracting value of I0 +pes_model.lyr_N = lyr_N; +pes_model.lyr_sigma = lyr_sigma; +pes_model.lyr_beta = lyr_beta; +pes_model.lyr_beta_adj = lyr_beta_adj; +pes_model.lyr_gamma = lyr_gamma; +pes_model.lyr_T = lyr_T; +pes_model.lyr_c = lyr_c; +pes_model.lyr_F = lyr_F; +pes_model.lyr_I0 = lyr_I0; +% - Defining the final intensities +pes_model.lyr_ints = lyr_ints; +pes_model.lyr_ints0 = lyr_ints0; + +%% 5 - Plotting the multilayer model stack and solutions +if plot_result == 1; view_nlayer_pes_model(pes_model); end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/overlayer_calc.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/overlayer_calc.m new file mode 100644 index 0000000..59b3776 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/overlayer_calc.m @@ -0,0 +1,25 @@ +function d_o = overlayer_calc(theta, C_m, imfp_m, I_m, C_o, imfp_o, I_o) +% d_o = overlayer_calc(C_m, imfp_m, I_m, C_o, imfp_o, I_o) +% Function that determines the thickness of a uniform oxide-film on an +% oxidised metal surface. This is calculated from the relative +% photoelectron intensity of the oxidic or the metallic component, with +% respect to that of the corresponding oxide or clean metal, respectively. +% This model assumes that the underlying metallic layer is an infinitely +% thick slab, with a uniform oxide layer of thickness d_o on top. +% +% IN: +% - theta: scalar of the photoelectron take-off angle. +% - C_m: scalar of the volume density of metal atoms in the metal [mole / cc]. +% - imfp_m: scalar of the imfp of electrons in the metal [nm]. +% - I_m: scalar of the total peak area of the metal photoelectron peak. +% - C_o: scalar of the volume density of metal atoms in the oxide [mole / cc]. +% - imfp_o: scalar of the imfp of electrons in the oxide [nm]. +% - I_o: scalar of the total peak area of the oxide photoelectron peak. +% +% OUT: +% - d_o: thickness of the oxide in nm. + +%% 1 : Determination of the oxide thickness +d_o = imfp_o .* sin(deg2rad(theta)) .* log(1 + (C_m.*imfp_m.*I_o) ./ (C_o.*imfp_o.*I_m)); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/view_nlayer_pes_model.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/view_nlayer_pes_model.m new file mode 100644 index 0000000..cd6b5f9 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/view_nlayer_pes_model.m @@ -0,0 +1,77 @@ +function fig = view_nlayer_pes_model(pes_model, lyr_cols) +% fig = view_nlayer_pes_model(pes_model) +% This function plots the solutions to the 'nlayer_pes_model()' function; +% the n-layered sample stack and the corresponding photoelectron +% contribution from each one of the layers. The user can input the colors +% for each one of the layers using the 'lyr_cols' argument; this is +% convenient when you want to color-match the schematic to your own +% drawings. +% +% IN: +% - pes_model: data structure that contains all the pes model parameters and variables (from 'nlayer_pes_model()'). +% - lyr_cols: Mx1 cell-vector of the [R,G,B] color of each independent layer. +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% Default parameters +% -- Extracting plot properties +pp = plot_props(); +% -- Defining the default parameters +if nargin < 2; lyr_cols = pp.col.fit; end +if isempty(lyr_cols); lyr_cols = pp.col.fit; end + +%% 1 - Plotting the the model solutions +fig = figure(); +fig.Position(3) = 2.50*500; +fig.Position(4) = 1.0*400; +%% 1.1 - Plotting the intensity profiles for each layer +subplot(121); hold on; +gca_props(0); +x_width = 5; +if pes_model.Nlyrs == 1 + y_cum = cell2mat(pes_model.lyr_thick); +else + y_cum = cumsum(cell2mat(pes_model.lyr_thick)); + y_cum(isinf(y_cum)) = y_cum(end-1) + 10; +end +% -- Plotting each layer from bottom-up +for i = pes_model.Nlyrs:-1:1 + patch([-1, -1, 1, 1, -1].*x_width, [0, y_cum(i), y_cum(i), 0, 0].*-1,... + lyr_cols{i}, 'edgecolor', [0 0 0]); +end +% -- Box Styling and Axis properties +ylabel('$$ \bf Depth\ From\ Surface\ [nm] $$', 'Interpreter', 'latex'); +title('Sample model stack'); +axis square; +axis([-x_width, x_width, -1*max(y_cum(:)), 0]); +% -- Adding text for each material type +for i = 1:pes_model.Nlyrs + if i == 1; y_loc = 0 - 0.5*(y_cum(i) - 0); + else; y_loc = -y_cum(i-1) - 0.5*(y_cum(i) - y_cum(i-1)); + end + if i == pes_model.Nlyrs + text(1.02*x_width, y_loc, "(B)"+string(pes_model.lyr_mat{i})+"["+string(pes_model.lyr_cls{i})+"]",... + 'color', 'k', 'horizontalalignment', 'left', 'verticalalignment', 'middle', 'FontWeight','bold', 'FontSize',11); + else + text(1.02*x_width, y_loc, sprintf("(S%i)",i)+string(pes_model.lyr_mat{i})+"["+string(pes_model.lyr_cls{i})+"]",... + 'color', 'k', 'horizontalalignment', 'left', 'verticalalignment', 'middle', 'FontWeight','bold', 'FontSize',11); + end +end +%% 4.2 - Plotting the intensity profiles for each layer +subplot(122); hold on; +for i = 1:pes_model.Nlyrs + plot(pes_model.pes_hv, pes_model.lyr_ints0{i}, 'k-', 'color', lyr_cols{i}, 'markerfacecolor', lyr_cols{i}, 'linewidth', 3.50); + max_vals(i) = max(pes_model.lyr_ints0{i}(:)); +end +legend(pes_model.lyr_mat, 'location', 'best'); +gca_props(0); +title('Photoelectron intensity contributions'); +xlabel('$$ \bf Photon\ energy\ [eV] $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Relative\ Contribution $$', 'Interpreter', 'latex'); +ylim([0, 1.05.*max(max_vals(:))]); +ax = gca; +ax.YAxisLocation = 'right'; + + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/view_nlayer_sample.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/view_nlayer_sample.m new file mode 100644 index 0000000..60cc399 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F020 - pes intensity modelling/view_nlayer_sample.m @@ -0,0 +1,61 @@ +function fig = view_nlayer_sample(lyr_mat, lyr_thick, lyr_cols) +% fig = view_nlayer_sample(lyr_mat, lyr_thick, lyr_cols) +% This function plots the solutions to the 'nlayer_pes_model()' function; +% the n-layered sample stack and the corresponding photoelectron +% contribution from each one of the layers. The user can input the colors +% for each one of the layers using the 'lyr_cols' argument; this is +% convenient when you want to color-match the schematic to your own +% drawings. +% +% IN: +% - lyr_mat: Mx1 cell-vector of the material for each layer in the stack; e.g. "Si", "SiO2", "Al2O3"... +% - lyr_thick: Mx1 cell-vector of the thickness of each layer in the stack (in nano-metres) +% - lyr_cols: Mx1 cell-vector of the [R,G,B] color of each independent layer. +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% Default parameters +% -- Extracting plot properties +pp = plot_props(); +% -- Defining the default parameters +if nargin < 3; lyr_cols = pp.col.fit; end +if isempty(lyr_cols); lyr_cols = pp.col.fit; end +% -- Extracting the total number of layers to be probed +Nlyrs = length(lyr_mat); + +%% 1 - Plotting the the material stack +fig= figure(); hold on; +gca_props(0); +x_width = 5; +if Nlyrs == 1 + y_cum = cell2mat(lyr_thick); +else + y_cum = cumsum(cell2mat(lyr_thick)); + y_cum(isinf(y_cum)) = y_cum(end-1) + 10; +end +% -- Plotting each layer from bottom-up +for i = Nlyrs:-1:1 + patch([-1, -1, 1, 1, -1].*x_width, [0, y_cum(i), y_cum(i), 0, 0].*-1,... + lyr_cols{i}, 'edgecolor', [0 0 0]); +end +% -- Box Styling and Axis properties +ylabel('$$ \bf Depth\ From\ Surface\ [nm] $$', 'Interpreter', 'latex'); +title('Sample model stack'); +axis square; +axis([-x_width, x_width, -1*max(y_cum(:)), 0]); +% -- Adding text for each material type +for i = 1:Nlyrs + if i == 1; y_loc = 0 - 0.5*(y_cum(i) - 0); + else; y_loc = -y_cum(i-1) - 0.5*(y_cum(i) - y_cum(i-1)); + end + if i == Nlyrs + text(1.02*x_width, y_loc, "(B)"+string(lyr_mat{i}),... + 'color', 'k', 'horizontalalignment', 'left', 'verticalalignment', 'middle', 'FontWeight','bold', 'FontSize',11); + else + text(1.02*x_width, y_loc, sprintf("(L%i)",i)+string(lyr_mat{i}),... + 'color', 'k', 'horizontalalignment', 'left', 'verticalalignment', 'middle', 'FontWeight','bold', 'FontSize',11); + end +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F021 - pes data processing/pes_extract_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F021 - pes data processing/pes_extract_data.m new file mode 100644 index 0000000..deb38ac --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F021 - pes data processing/pes_extract_data.m @@ -0,0 +1,151 @@ +function [pesStr, fig] = pes_extract_data(arpesStr, pes_args, plot_results) +% [pesStr, fig] = pes_extract_data(arpesStr, pes_args, plot_results) +% This function extracts an EDC cut through XPS data, allowing the +% angle-integrated XPS spectrum to be acquired. This is then used for all +% subsequent XPS analysis. The user can choose to make N cuts within a +% given window if desired. This is the function used to extract ADRESS +% data as XPS structure within the PESTools package. +% +% REQ. FUNCTIONS: +% - [xField, yField, zField, dField] = find_data_fields(dataStr); +% - [h=] ImData(X,Y,Z[,style]) +% - [XCut,DCut] = Cut(ACorr,ECorr,Data,xMode,Win) +% +% IN: +% - arpesStr: data structure of the ARPES data. +% - pes_args: 1x2 cell of {cutWin, cutN}; the integration window of the cut and total number of cuts. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - pesStr: new MATLAB data-structure for PES data, can be used with all 'pes analysis' functions. +% - fig: figure output. + +%% Default parameters +if nargin < 3; plot_results = 1; end +if nargin < 2; pes_args = cell(1,2); end +if isempty(pes_args) || length(pes_args) ~= 2; pes_args = cell(1,2); end +if isempty(plot_results); plot_results = 1; end +% - Extracting the fields to be used with most recent processing +[xField, yField, ~, dField] = find_data_fields(arpesStr); + +%% - 1 - Initialising input parameters +% - Extracting the input parameters +angleWin = pes_args{1}; if isempty(angleWin); angleWin = 0.95*[min(arpesStr.(xField)(:)), max(arpesStr.(xField)(:))]; end % Integration window of the cut to be made. +xpsN = pes_args{2}; if isempty(xpsN); xpsN = 1; end % single, constant value that determines the total number of line profiles to extract +% - Verifying the min/max values of the limits +Win = sort(angleWin); +step_size = 0.05; +if Win(1) < min(arpesStr.(xField)(:)); Win(1) = min(arpesStr.(xField)(:)) + step_size; end +if Win(2) > max(arpesStr.(xField)(:)); Win(2) = max(arpesStr.(xField)(:)) - step_size; end +% - Extracting the maximum number of line-profiles possible +[~, yy, ~] = data_crop2D(arpesStr.(xField), arpesStr.(yField), arpesStr.(dField), Win, []); +max_N = length(yy); if xpsN > max_N; xpsN = max_N; end +% - Extracting the central location for each Cut to be made +cutVals = linspace(Win(1), Win(2), xpsN+2); +if xpsN == 1; cutRange = 0.5*range(Win); +else; cutRange = 0.5*range(Win)./(xpsN+1); +end + +%% 2 - Extracting all of the angle-integrated cuts +for i = 1:xpsN + cutWin(i,:) = cutVals(i+1) + [-1, 1] * cutRange; + [XCut{i}, DCut{i}] = Cut(arpesStr.(xField), arpesStr.(yField), arpesStr.(dField), 'edc', cutWin(i,:)); +end + +%% 3 - Appending data to MATLAB data structure +if xpsN == 1 + pesStr = arpesStr; + pesStr.IsoType = "XPS"; + pesStr.pes_args = {angleWin, xpsN}; + pesStr.cutWin = cutWin(1,:); + pesStr.cutN = 1; + pesStr.xdat = XCut{1}; + pesStr.ydat = DCut{1}; +else + for i = 1:xpsN + pesStr{i} = arpesStr; + pesStr{i}.IsoType = "XPS"; + pesStr{i}.pes_args = {angleWin, xpsN}; + pesStr{i}.cutWin = cutWin(i,:); + pesStr{i}.cutN = i; + pesStr{i}.xdat = XCut{i}; + pesStr{i}.ydat = DCut{i}; + end +end + +%% 4.0 - Plotting the figure if required +fig = []; +if plot_results == 1 + % - Initialising the plot properties + pp = plot_props(); + fig = figure(); + fig.Position(3) = 1.5*pp.fig5x4(1); + fig.Position(4) = pp.fig5x4(2); + subplot(1,3,1:2); hold on; + % - For an Eb(k) scan type + if arpesStr.Type == "Eb(k)" + % -- Plotting the Eb(k) figure object + if isfield(arpesStr, 'kx'); set(fig, 'Name', 'Iso-Cut - Eb(k): A, N, K'); + elseif isfield(arpesStr, 'data'); set(fig, 'Name', 'Iso-Cut - Eb(k): A, N'); + elseif isfield(arpesStr, 'eb'); set(fig, 'Name', 'Iso-Cut - Eb(k): A'); + else; set(fig, 'Name', 'Iso-Cut - Eb(k): Raw'); + end + % - For a 3D Eb(kx,ky) scan type + elseif arpesStr.Type == "Eb(kx,ky)" + % -- Plotting the Eb(kx,ky) figure object + if isfield(arpesStr, 'kx'); set(fig, 'Name', 'Iso-Cut - Eb(kx,ky): A, N, K'); + elseif isfield(arpesStr, 'data'); set(fig, 'Name', 'Iso-Cut - Eb(kx,ky): A, N'); + elseif isfield(arpesStr, 'eb'); set(fig, 'Name', 'Iso-Cut - Eb(kx,ky): A'); + else; set(fig, 'Name', 'Iso-Cut - Eb(kx,ky): Raw'); + end + % - For a 3D Eb(kx,kz) scan type + elseif arpesStr.Type == "Eb(kx,kz)" + % -- Plotting the Eb(kx,kz) figure object + if isfield(arpesStr, 'kx'); set(fig, 'Name', 'Iso-Cut - Eb(kx,kz): A, N, K'); + elseif isfield(arpesStr, 'data'); set(fig, 'Name', 'Iso-Cut - Eb(k): A, N'); + elseif isfield(arpesStr, 'eb'); set(fig, 'Name', 'Iso-Cut - Eb(kx,kz): A'); + else; set(fig, 'Name', 'Iso-Cut - Eb(kx,kz): Raw'); + end + end + % - Defining the XPS plot colors + isoCols = jet(xpsN); + % - Defining the axes limits + xLims = [min(arpesStr.(xField)(:)), max(arpesStr.(xField)(:))]; + yLims = [min(arpesStr.(yField)(:)), max(arpesStr.(yField)(:))]; + %% 4.1 - Plotting the Eb(k) at the scan value + % -- The plot depends on how far in the analysis + ImData(arpesStr.(xField), arpesStr.(yField), arpesStr.(dField)); + img_props([], string(xField)); + axis([xLims, yLims]); + % -- Plotting an outline over the integrated sliced region + colbar_props([0.05 0.125 0.025 0.175], 'left'); + patch([Win(1), Win(1), Win(2), Win(2), Win(1)],[-1e3, 1e3, 1e3, -1e3, -1e3],... + [0 1 0], 'linewidth', 1, 'facealpha', 0, 'edgecolor', [0 0 1]); + % -- Plotting the value of each line cut + for i = 1:xpsN + patch(... + [cutWin(i,1), cutWin(i,1), cutWin(i,2), cutWin(i,2), cutWin(i,1)],... + [yLims(1), yLims(2), yLims(2), yLims(1), yLims(1)],... + isoCols(i,:), 'linewidth', 1, 'facealpha', 0.35, 'edgecolor', 'none'); + plot([1, 1]*mean(cutWin(i,:)), yLims, 'k-', 'color', isoCols(i,:)); + end + % -- Adding title to the figure + title(sprintf(string(arpesStr.FileName)), 'interpreter', 'none', 'fontsize', 9); + %% 4.2 - Plotting the Iso-Cut + subplot(1,3,3); hold on; + for i = 1:xpsN + plot(DCut{i}, XCut{i}, 'k.-', 'color', [0 0 1], 'LineWidth', 1.5, 'color', isoCols(i,:)); + end + gca_props(); + ax = gca; + ax.XAxisLocation = 'bottom'; % 'bottom' | 'top' | 'origin' + ax.YAxisLocation = 'right'; % 'left' | 'right' | 'origin' + % - Axis labels and limits + ylabel('$$ \bf E_{B} (eV) $$', 'Interpreter', 'latex'); + xlabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); + % - Plotting the x- and y-axes + xl = xlim; yl = [min(arpesStr.(yField)(:)), max(arpesStr.(yField)(:))]; + axis([xl(1), 1.05*xl(2), yl(1), yl(2)]); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F021 - pes data processing/pes_norm2peak.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F021 - pes data processing/pes_norm2peak.m new file mode 100644 index 0000000..5aa9f6d --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F021 - pes data processing/pes_norm2peak.m @@ -0,0 +1,74 @@ +function ydat_norm = pes_norm2peak(xdat, ydat, norm_args, plot_results) +% ydat_norm = pes_norm2peak(xdat, ydat, norm_args, plot_results) +% This function is used to normalise the XPS data, making the minimum +% intensity equal zero and the maximum intensity equal one. This is not +% necessary, but is useful when it comes to comparing qualitative changes +% to XPS spectra. By defining aprpropriate xpsnorm_args, you can +% normalise to a user-defined peak / position within the XPS data. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - xpsStr: data structure of the XPS data. +% - xpsnorm_args: 1x2 cell of {eWin, dEWin}. +% - plot_results: if 1, will plot figure of the results, otherwise it wont. +% +% OUT: +% - xpsStr: data structure of the XPS data. +% - fig: figure output. + +%% Default parameters +if nargin < 4; plot_results = 1; end +if nargin < 3; norm_args = cell(1,2); plot_results = 1; end +if isempty(norm_args); norm_args = cell(1,2); end +if isempty(plot_results); plot_results = 1; end + +%% 1 - Initialising input parameters +eWin = norm_args{1}; if isempty(eWin); eWin = mean(xdat(:)); dEWin = 0.5*abs(xdat(1)-xdat(end)); end % approximate Eb position of a peak in the spectrum to normalise to. +dEWin = norm_args{2}; if isempty(dEWin); dEWin = 0.5*abs(xdat(1)-xdat(end)); end % Single, constant value that defines the width of the approximate Eb position + +%% 2 - Normalising the XPS data +% -- Shifting the data so its minimum is zero +ydat_norm = ydat - min(ydat(:)); +% -- Extracting the indices over which to find the maximum +[~, lbIndx] = min(abs(xdat - (eWin - dEWin))); +[~, ubIndx] = min(abs(xdat - (eWin + dEWin))); +Indx = [lbIndx, ubIndx]; +% -- Finding the maximum peak value within this range +[maxVal, maxInd] = max(ydat_norm(Indx(1):Indx(2))); +peak_index = lbIndx + maxInd - 1; +if plot_results == 1 + sprintf(("xval = %.2f eV, yval = %.2f"), xdat(peak_index), ydat_norm(peak_index)) +end +% -- Normalising the XPS data +ydat_norm = ydat_norm ./ maxVal; + + +%% - 3 - Plotting normalisation figure +if plot_results == 1 + pp = plot_props(); + fig = figure(); set(fig, 'Name', 'XPS Data from ADRESS'); + fig.Position(3) = 1.25*pp.fig5x4(1); + fig.Position(4) = pp.fig5x4(2); + hold on; + % -- Plotting the XPS data pre-subtraction + plot(xdat, ydat, 'k-', 'linewidth', pp.llwidth); + % -- Plotting a line of the normalised peak window + h = line([1, 1]*eWin, [-1, 1]*5*max(ydat(:)), 'color', 'r', 'linestyle', '--', 'linewidth', 1.5); + h.Annotation.LegendInformation.IconDisplayStyle = 'off'; + h = line([1, 1]*eWin - dEWin, [-1, 1]*5*max(ydat(:)), 'color', 'r', 'linestyle', ':', 'linewidth', 1.5); + h.Annotation.LegendInformation.IconDisplayStyle = 'off'; + h = line([1, 1]*eWin + dEWin, [-1, 1]*5*max(ydat(:)), 'color', 'r', 'linestyle', ':', 'linewidth', 1.5); + h.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % - Formatting the figure + gca_props(); grid on; + axis([min(xdat(:)), max(xdat(:)),0, 1.25*max(ydat(:))]); + ylabel('$$ \bf Initial $$', 'Interpreter', 'latex'); + xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + % -- Plotting the XPS data after subtraction + yyaxis right; + plot(xdat, ydat_norm, '-', 'linewidth', pp.llwidth); + ylabel('$$ \bf Normalised $$', 'Interpreter', 'latex'); +end + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F021 - pes data processing/view_pes_data.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F021 - pes data processing/view_pes_data.m new file mode 100644 index 0000000..5d6d07f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F021 - pes data processing/view_pes_data.m @@ -0,0 +1,48 @@ +function fig = view_pes_data(pesStr) +% fig = view_pes_data(pesStr) +% This function plots the XPS data in the form of I(X). The +% input can either be a single XPS data structure, or a cell-array of XPS +% structures, each of which can be plotted and overlaid on top of one +% another. Use this as the general function to use to view all XPS data +% during the data processing / analysis stage. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - pesStr: data structure (or cell array of structures) of the XPS data. +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% - 1 - Plotting the XPS figure +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'XPS Data from ADRESS'); +fig.Position(3) = 1.25*pp.fig5x4(1); +fig.Position(4) = pp.fig5x4(2); +hold on; +% -- Filing through all potential XPS structures in a cell array +lgnd = {}; +if length(pesStr) == 1 && ~iscell(pesStr) + plot(pesStr.xdat, pesStr.ydat, 'k-', 'color', [0 0 1], 'linewidth', pp.llwidth); + axis([min(pesStr.xdat(:)), max(pesStr.xdat(:)),0, 1.15*max(pesStr.ydat(:))]); + lgnd{end+1} = string(pesStr.hv) + " eV"; + if isfield(pesStr, 'FileName'); title(sprintf(string(pesStr.FileName)), 'interpreter', 'none', 'fontsize', 9); end +else + cols = jet(length(pesStr)+2); + for i = 1:length(pesStr) + plot(pesStr{i}.xdat, pesStr{i}.ydat, 'k-', 'color', cols(i,:), 'linewidth', pp.llwidth); + lgnd{end+1} = string(pesStr{i}.hv) + " eV"; + max_ydat(i) = max(pesStr{i}.ydat(:)); + end + axis([min(pesStr{1}.xdat(:)), max(pesStr{1}.xdat(:)), 0, 1.15*max(max_ydat)]); + if isfield(pesStr, 'FileName'); title(sprintf(string(pesStr{1}.FileName)), 'interpreter', 'none', 'fontsize', 9); end +end +% - Formatting the figure +gca_props(); grid on; +% legend(lgnd,'Location','best'); +ylabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/fdd fitting/fdd2fit_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/fdd fitting/fdd2fit_solver.m new file mode 100644 index 0000000..7d430b9 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/fdd fitting/fdd2fit_solver.m @@ -0,0 +1,322 @@ +function [fitStr, Ef] = fdd2fit_solver(Angle, Energy, Data, AngleWin, EnergyWin, fddType, iparams, solve_type, plot_result) +% [fitStr, Ef] = fdd2fit_solver(Angle, Energy, Data, fddType, iparams, solve_type) +% Function that runs an optimisation algorithm to solve for the best fit +% to a Fermi-Dirac Distribution. The FDD function can be chosen for +% optimal fitting to the data. +% +% REQ. FUNCTIONS: none +% +% IN: +% - Angle: [1×nAngle] row vector of angles. +% - Energy: [nEnergyx1] column vector of energy. +% - Data: [nEnergy x nAngle] data array. +% - AngleWin: 1x2 vector of [minAngle, maxAngle] over which the fit is performed. Default: 95% of the full Angle window. +% - EnergyWin: 1x2 vector of [minEnergy, maxEnergy] over which the fit is performed. Default: 95% of the full Energy window. +% - fddType: string of the type of FDD curve to use for fitting. Default: "FDDGsL" ("FDD", "FDDG", "FDDGpL", "FDDGsL") +% - iparams: 3 cells {x0}{lb}{ub} with 1×7 vectors: defines the input parameters [fdd_ef,fdd_T,fdd_fwhm,lin_grad,lin_offset,const_bgrnd,fdd_scale] +% - solve_type: string of the optimisation algorithm to use; "lsqcurvefit" (very fast, good), "lsqnonlin" (fast, not good), "simulannealbnd" (slow, best). +% - plot_result: if True, will plot the result of the fitting. +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information +% - Ef: scalar value of the position of the Fermi-level. + +%% Default parameters +if nargin < 9; plot_result = 1; end +if isempty(plot_result); plot_result = 1; end +% - Solver parameters +if nargin < 8; solve_type = "lsqcurvefit"; end +if nargin < 6; fddType = "FDDGsL"; end +if isempty(solve_type); solve_type = "lsqcurvefit"; end +if isempty(fddType); fddType = "FDDGsL"; end +% -- Window parameters +if ~isempty(Angle) + if nargin < 4; AngleWin = mean(Angle(:)) + abs(0.475*range(Angle(:))).*[-1, 1]; end + if isempty(AngleWin); AngleWin = mean(Angle(:)) + abs(0.475*range(Angle(:))).*[-1, 1]; end +else; AngleWin = []; +end +if nargin < 5; EnergyWin = mean(Energy(:)) + abs(0.475*range(Energy(:))).*[-1, 1]; end +if isempty(EnergyWin); EnergyWin = mean(Energy(:)) + abs(0.475*range(Energy(:))).*[-1, 1]; end +% -- Fit variables +if nargin < 7 || isempty(iparams) + iparams{1} = [mean(EnergyWin(:)), 12, 0.30, 0.00, 0, mean(Data(:)), 1]; + iparams{2} = [min(EnergyWin(:)), 12, 0.00, -5.00, min(Energy(:)), -max(Data(:)), 0]; + iparams{3} = [max(EnergyWin(:)), 12, 2.00, 0.00, max(Energy(:)), max(Data(:)), max(Data(:))]; +end +% -- Consistency check and finding the total number of curves +if size(iparams{1}, 1) ~= size(iparams{2}, 1) || size(iparams{2}, 1) ~= size(iparams{3}, 1) + error('The input parameter cell array is not a consistent size - check iparams input!'); +end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Defining the initial conditions and limits of the optimisation method +x0 = [iparams{1}(:)]; +lb = [iparams{2}(:)]; +ub = [iparams{3}(:)]; +% -- Defining the initial conditions and limits of the optimisation method +% --- lower bounds +if lb(1) < min(EnergyWin(:)); lb(1) = min(EnergyWin(:)); end % if fdd_ef < 0, then make it 0 +if lb(2) < 0; lb(2) = 0; end % if fdd_T < 0, then make it 0 +if lb(3) < 0; lb(3) = 0; end % if fdd_fwhm < 0, then make it 0 +if lb(7) < 0; lb(7) = 0; end % if fdd_scale < 0, then make it 0 +% --- upper bounds +if ub(1) > max(EnergyWin(:)); ub(1) = max(EnergyWin(:)); end % if fdd_ef < 0, then make it 0 +if ub(4) > 0; ub(4) = 0; end % if lin_grad > 0, then make it 0 +% --- parameters +if x0(1) < lb(1); x0(1) = lb(1); elseif x0(1) > ub(1); x0(1) = ub(1); end +if x0(2) < lb(2); x0(2) = lb(2); elseif x0(2) > ub(2); x0(2) = ub(2); end +if x0(3) < lb(3); x0(3) = lb(3); elseif x0(3) > ub(3); x0(3) = ub(3); end +if x0(4) < lb(4); x0(4) = lb(4); elseif x0(4) > ub(4); x0(4) = ub(4); end +if x0(5) < lb(5); x0(5) = lb(5); elseif x0(5) > ub(5); x0(5) = ub(5); end +if x0(6) < lb(6); x0(6) = lb(6); elseif x0(6) > ub(6); x0(6) = ub(6); end +if x0(7) < lb(7); x0(7) = lb(7); elseif x0(7) > ub(7); x0(7) = ub(7); end +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - EXTRACTING THE FDD DATA +% -- Cross-correlating sum if necessary +if size(Data,3) > 1; [Data,~] = SumScanXC(Energy, Data); end +% -- Angle-Integrated sum if necessary +if ~isempty(Angle); [ydat, xdat] = IntAngle(Data, Angle, Energy, AngleWin); +else; xdat = Energy; ydat = Data; +end +% -- Ensuring data is in a column vector +if size(xdat, 2) > 1; xdat = xdat'; end +if size(ydat, 2) > 1; ydat = ydat'; end +% -- Normalising the data +ydat(isnan(ydat)) = 0; +ydat = ydat - min(ydat(:)); +ydat = ydat ./ max(ydat(:)); +% -- Extracting the data to be fitted +[roi_xdat, roi_ydat] = data_crop1D(xdat, ydat, EnergyWin); +% -- Defining a structure that stores all relevant model and data variables +FDDObj = struct(); +FDDObj.xdat = xdat; +FDDObj.ydat = ydat; +FDDObj.roi_xdat = roi_xdat; +FDDObj.roi_ydat = roi_ydat; +% -- Appending the input arguments to the global variable +FDDObj.fit_args.solve_type = solve_type; +FDDObj.fit_args.fddType = fddType; +FDDObj.fit_args.iparams = iparams; +FDDObj.fit_args.AngleWin = AngleWin; +FDDObj.fit_args.EnergyWin = EnergyWin; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 5e3; +FuncTol = 1e-7; % 1e-7; +StepTol = 1e-7; % 1e-7; +OptTol = 1e-7; % 1e-7; +ConTol = 1e-7; % 1e-7; +FinDiffRelStep = 1e-2; % 1e-5; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; +%% - 3.1 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR CURVE FITTING +if solve_type == "lsqcurvefit" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqcurvefit,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqcurvefit(@(x,roi_xdat) full_fdd_function(x,roi_xdat,FDDObj), x0, roi_xdat, roi_ydat, lb, ub, options); + +%% - 3.2 - LOCAL SOLVER: UNBOUNDED LEAST SQUARES NONLINEAR REGRESSION FIT +elseif solve_type == "nlinfit" + % -- Defining the optimisation options for the simulated annealing method + options = statset(... + 'MaxFunEvals', MaxFunEvals,... + 'MaxIter', MaxIter,... + 'TolFun', FuncTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,R,J,CovB,MSE,ErrorModelInfo] = nlinfit(roi_xdat, roi_ydat, @(x,roi_xdat) full_fdd_function(x,roi_xdat,FDDObj), x0, options); +%% - 3.3 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,grad,hessian] = fminunc(@(x) minimize_function(x,FDDObj), x0, options); + +%% - 3.4 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,FDDObj), x0, [], [], [], [], lb, ub, [], options); + + %% - 3.5 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR LEAST SQUARES PROBLEMS +elseif solve_type == "lsqnonlin" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqnonlin,... + 'Algorithm', 'levenberg-marquardt',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqnonlin(@(x) minimize_function(x,FDDObj), x0, lb, ub, options); +%% - 3.8 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,FDDObj), x0, lb, ub, options); +end + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.fddType = fddType; +fitStr.iparams = iparams; +fitStr.AngleWin = AngleWin; +fitStr.EnergyWin = EnergyWin; +%% 4.2 - Storing the XPS data, background, model and minimisation variables +% -- Extracting the original data +fitStr.xdat = xdat; +fitStr.ydat = ydat; +% -- Extracting the X-DOMAIN and DATA +[fitStr.X, fitStr.D] = fit_data(params, FDDObj); +% -- Extracting the MODEL +fitStr.M = fit_model(params, FDDObj); +% -- Extracting the RESIDUALS (R = D - (M + B)) +fitStr.R = fitStr.D - fitStr.M; +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ = sum(fitStr.R.^2 ./ abs(fitStr.M)); +fitStr.MINFUN = minimize_function(params, FDDObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables of each PES curve component +fitStr.XX = linspace(min(fitStr.X(:))-1, max(fitStr.X(:))+1, 1e3)'; +if fitStr.fddType == "FDD"; fitStr.YY = params(7).*FDD(fitStr.XX, params(1), params(2)); +elseif fitStr.fddType == "FDDG"; fitStr.YY = params(7).*FDDG(fitStr.XX, params(1), params(2), params(3), params(4)); +elseif fitStr.fddType == "FDDGpL"; fitStr.YY = params(7).*FDDGpL(fitStr.XX, params(1), params(2), params(3), params(4), params(5), params(6)); +elseif fitStr.fddType == "FDDGsL"; fitStr.YY = params(7).*FDDGsL(fitStr.XX, params(1), params(2), params(3), params(4), params(5), params(6)); +end +% --- Storing the best fit parameters +fitStr.params = params; +fitStr.EF = params(1); Ef = fitStr.EF; +fitStr.TEMP = params(2); +fitStr.FWHM = params(3); +fitStr.GRAD = params(4); +fitStr.OFFSET = params(5); +fitStr.BGRND = params(6); +fitStr.SCALE = params(7); + +%% - 5 - PLOTTING THE FIT IF REQUIRED +if plot_result == 1 + fig = figure(); + fig.Position(3) = 1.0*400; + fig.Position(4) = 1.0*400; + hold on; + % -- Plot the figure + plot(fitStr.xdat, fitStr.ydat, 'o', 'Color', [0.5 0.5 0.5], 'markerfacecolor', [0.5 0.5 0.5]); + plot(fitStr.X, fitStr.D,'o', 'Color', 'r', 'markerfacecolor', 'r'); + plot(fitStr.XX, fitStr.YY, 'k-', 'linewidth', 3.0, 'linestyle', '-'); + line([1, 1].*fitStr.EF, [-1e5, 1e5], 'color', 'b', 'linewidth', 1.5, 'linestyle', '-'); + a = line([0 0], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '--'); + b = line([-1e5, 1e5], [0 0], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '--'); + a.Annotation.LegendInformation.IconDisplayStyle = 'off'; + b.Annotation.LegendInformation.IconDisplayStyle = 'off'; + % -- Formatting the figure + gca_props(0); + title('fdd2fit_solver()', 'interpreter', 'none'); + ylabel('$$ \bf Intensity\ [arb.] $$', 'Interpreter', 'latex'); + xlabel('$$ \bf E_B\ [eV] $$', 'Interpreter', 'latex'); + legend({'', 'Data', 'Fit', 'Ef'}, 'location', 'northeast', 'interpreter', 'none'); + axis([... + min(fitStr.X(:)), ... + max(fitStr.X(:)), ... + min(fitStr.D(:)), ... + max(fitStr.D(:))]); + % -- Add annotation for the quality of fit + text(0.04, 0.35, "$$ \chi^2 = $$ " + string(fitStr.CHISQ), 'interpreter', 'latex', 'fontsize', 12, 'color', 'k', 'Units','normalized'); + text(0.04, 0.27, "$$ E_F = $$ " + string(round(fitStr.EF,3)) + " eV", 'interpreter', 'latex', 'fontsize', 12, 'color', 'k', 'Units','normalized'); + text(0.04, 0.19, "$$ \Delta E = $$ " + string(round(fitStr.FWHM,3)) + " eV", 'interpreter', 'latex', 'fontsize', 12, 'color', 'k', 'Units','normalized'); + % -- Printing data structure + Ef +end +end + +%% DEFINING THE RESIDUAL MINIMISATION FUNCTION TO BE MINIMISED +function MINFUN = minimize_function(x, FDDObj) + % - 1 - Extracting the DATA + [~, D] = fit_data(x, FDDObj); + % - 2 - Extracting the MODEL + M = fit_model(x, FDDObj); + % - 3 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - M; + % - 4 - Extracting the CHI-SQUARED value to be minimised + MINFUN = sum(R.^2 ./ abs(M)); +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE FDD DATA TO BE FITTED +function [X, D] = fit_data(x, FDDObj) + X = FDDObj.roi_xdat; + D = FDDObj.roi_ydat; + D(isnan(D)) = 0; if size(D, 2) > 1; D = D'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE FDD CURVE FIT +function M = fit_model(x, FDDObj) + if FDDObj.fit_args.fddType == "FDD"; M = FDD(FDDObj.roi_xdat, x(1), x(2)); + elseif FDDObj.fit_args.fddType == "FDDG"; M = FDDG(FDDObj.roi_xdat, x(1), x(2), x(3), x(4)); + elseif FDDObj.fit_args.fddType == "FDDGpL"; M = FDDGpL(FDDObj.roi_xdat, x(1), x(2), x(3), x(4), x(5), x(6)); + elseif FDDObj.fit_args.fddType == "FDDGsL"; M = FDDGsL(FDDObj.roi_xdat, x(1), x(2), x(3), x(4), x(5), x(6)); + end + M = x(7).*M; + M(isnan(M)) = 0; if size(M, 2) > 1; M = M'; end +end + +%% DEFINING THE FINAL FUNCTION THAT DESCRIBES THE FDD CURVE TO BE FITTED +function M = full_fdd_function(x, xdat, FDDObj) + if FDDObj.fit_args.fddType == "FDD"; M = FDD(xdat, x(1), x(2)); + elseif FDDObj.fit_args.fddType == "FDDG"; M = FDDG(xdat, x(1), x(2), x(3), x(4)); + elseif FDDObj.fit_args.fddType == "FDDGpL"; M = FDDGpL(xdat, x(1), x(2), x(3), x(4), x(5), x(6)); + elseif FDDObj.fit_args.fddType == "FDDGsL"; M = FDDGsL(xdat, x(1), x(2), x(3), x(4), x(5), x(6)); + end + M = x(7).*M; + M(isnan(M)) = 0; if size(M, 2) > 1; M = M'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2boff fitting/pes2boff_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2boff fitting/pes2boff_solver.m new file mode 100644 index 0000000..22a3e28 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2boff fitting/pes2boff_solver.m @@ -0,0 +1,372 @@ +function fitStr = pes2boff_solver(pesStr, modelStr, cTYPE, iparams, bTYPE, ibgrnd, solve_type) +% fitStr = pes2boff_solver(pesStr, modelStr, cTYPE, iparams, bTYPE, ibgrnd, solve_type) +% Function that runs an optimisation algorithm to solve for the best fit +% to the PES data using N curves that are integrated over a predefined +% potential profile that is defined by a particular model data structure and +% modulated by the mean free path. +% +% REQ. FUNCTIONS: none +% +% IN: +% - pesStr: data structure that contains the PES data. +% - modelStr: data structure that contains the model data. +% - cTYPE: 1xN vector of the type of curve to use for the nth state. +% - iparams: 3 cells {x0}{lb}{ub} with Nx8 arrays: the n'th peak parameters [BE,INT,FWHM,MR,LSE,LSI,LSW,ASY] +% - bTYPE: string of the type of background to use for fitting. Default: "Poly" ("none", "Poly", "Shir", "LinShir", "StepFDDGpL", "StepFDDGsL") +% - ibgrnd: 4 cells {x0}{lb}{ub}{args} with 1x3 vectors of the background parameters: x0=lb=ub=[LHS,RHS,BGR], or argument of the background type args = [] +% - solve_type: string of the optimisation algorithm to use; "lsqcurvefit" (very fast, good), "lsqnonlin" (fast, not good), "simulannealbnd" (slow, best). +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Default parameters +% - Default input parameters to use +if nargin < 6; solve_type = "lsqcurvefit"; end +if nargin < 5 + ibgrnd{1} = [... + mean(pesStr.xdat(:)) - abs(0.25*range(pesStr.xdat(:))),... + mean(pesStr.xdat(:)) + abs(0.25*range(pesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if nargin < 4; bTYPE = "Poly"; end +if isempty(solve_type); solve_type = "lsqcurvefit"; end +if isempty(ibgrnd) + ibgrnd{1} = [... + mean(pesStr.xdat(:)) - abs(0.25*range(pesStr.xdat(:))),... + mean(pesStr.xdat(:)) + abs(0.25*range(pesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if isempty(bTYPE); bTYPE = "Poly"; end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Total number of states to be fitted +nSTATES = length(cTYPE); +% -- Defining the initial conditions and limits of the optimisation method +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; +% -- Defining the initial conditions and limits of the optimisation method +for i = 1:nSTATES + indx = (2+i):nSTATES:(length(x0)-3); % +2 to account for MFP and BOFF + X0 = x0(indx); LB = lb(indx); UB = ub(indx); + % --- parameters + if X0(2) < 0; x0(indx(2)) = 0; end % if INT < 0, then make it 0 + if X0(3) < 0; x0(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if X0(4) < 0; x0(indx(4)) = 0; end % if MR < 0, then make it 0 + if X0(4) > 1; x0(indx(4)) = 1; end % if MR > 1, then make it 1 + if X0(6) < 0; x0(indx(6)) = 0; end % if LSI < 0, then make it 0 + if X0(7) < 0; x0(indx(7)) = 0; end % if LSW < 0, then make it 0 + if X0(8) < 0; x0(indx(8)) = 0; end % if ASY < 0, then make it 0 + % --- lower bounds + if LB(2) < 0; lb(indx(2)) = 0; end % if INT < 0, then make it 0 + if LB(3) < 0; lb(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if LB(4) < 0; lb(indx(4)) = 0; end % if MR < 0, then make it 0 + if LB(4) > 1; lb(indx(4)) = 1; end % if MR > 1, then make it 1 + if LB(6) < 0; lb(indx(6)) = 0; end % if LSI < 0, then make it 0 + if LB(7) < 0; lb(indx(7)) = 0; end % if LSW < 0, then make it 0 + if LB(8) < 0; lb(indx(8)) = 0; end % if ASY < 0, then make it 0 + % --- lower bounds + if UB(2) < 0; ub(indx(2)) = 0; end % if INT < 0, then make it 0 + if UB(3) < 0; ub(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if UB(4) < 0; ub(indx(4)) = 0; end % if MR < 0, then make it 0 + if UB(4) > 1; ub(indx(4)) = 1; end % if MR > 1, then make it 1 + if UB(6) < 0; ub(indx(6)) = 0; end % if LSI < 0, then make it 0 + if UB(7) < 0; ub(indx(7)) = 0; end % if LSW < 0, then make it 0 + if UB(8) < 0; ub(indx(8)) = 0; end % if ASY < 0, then make it 0 + % --- ensuring the fit window is within the domain + if x0(end-2) < min(pesStr.xdat(:)); x0(end-2) = min(pesStr.xdat(:)); end + if x0(end-1) > max(pesStr.xdat(:)); x0(end-1) = max(pesStr.xdat(:)); end +end +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - DEFINING THE XPS DATA AND FITTING ARGUMENTS +% -- Extracting the data to be fitted +[roi_xdat, roi_ydat, roi_bgrnd] = PESBackground(pesStr.xdat, pesStr.ydat, bTYPE, x0(end-2), x0(end-1), x0(end), ibgrnd{4}); +% -- Defining a structure that stores all relevant model and data variables +XPSObj = pesStr; +XPSObj.roi_xdat = roi_xdat; +XPSObj.roi_ydat = roi_ydat; +XPSObj.roi_bgrnd = roi_bgrnd; +XPSObj.roi_ydat_sbtr = XPSObj.roi_ydat - XPSObj.roi_bgrnd; +% -- Appending the input arguments to the global variable +XPSObj.fit_args.solve_type = solve_type; +XPSObj.fit_args.nSTATES = length(cTYPE); +XPSObj.fit_args.cTYPE = cTYPE; +XPSObj.fit_args.iparams = iparams; +XPSObj.fit_args.bTYPE = bTYPE; +XPSObj.fit_args.ibgrnd = ibgrnd; +XPSObj.modelStr = modelStr; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 5e3; +FuncTol = 1e-7; % 1e-7; +StepTol = 1e-7; % 1e-7; +OptTol = 1e-7; % 1e-7; +ConTol = 1e-7; % 1e-7; +FinDiffRelStep = 1e-5; % 1e-5; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; +%% - 3.1 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR CURVE FITTING +if solve_type == "lsqcurvefit" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqcurvefit,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqcurvefit(@(x,roi_xdat) full_pes_function(x,roi_xdat,XPSObj), x0, roi_xdat, roi_ydat, lb, ub, options); +%% - 3.2 - LOCAL SOLVER: UNBOUNDED LEAST SQUARES NONLINEAR REGRESSION FIT +elseif solve_type == "nlinfit" + % -- Defining the optimisation options for the simulated annealing method + options = statset(... + 'MaxFunEvals', MaxFunEvals,... + 'MaxIter', MaxIter,... + 'TolFun', FuncTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,R,J,CovB,MSE,ErrorModelInfo] = nlinfit(roi_xdat, roi_ydat, @(x,roi_xdat) full_pes_function(x,roi_xdat,XPSObj), x0, options); +%% - 3.3 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,grad,hessian] = fminunc(@(x) minimize_function(x,XPSObj), x0, options); +%% - 3.4 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,XPSObj), x0, [], [], [], [], lb, ub, [], options); +%% - 3.5 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR LEAST SQUARES PROBLEMS +elseif solve_type == "lsqnonlin" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqnonlin,... + 'Algorithm', 'levenberg-marquardt',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqnonlin(@(x) minimize_function(x,XPSObj), x0, lb, ub, options); +%% - 3.6 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,XPSObj), x0, lb, ub, options); +end + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.cTYPE = cTYPE; +fitStr.iparams = iparams; +fitStr.bTYPE = bTYPE; +fitStr.ibgrnd = ibgrnd; +fitStr.nSTATES = length(cTYPE); +%% 4.2 - Storing the XPS data, background, model and minimisation variables +% -- Extracting the original data +fitStr.xdat = pesStr.xdat; +fitStr.ydat = pesStr.ydat; +% -- Extracting the X-DOMAIN and DATA +[fitStr.X, fitStr.D] = fit_data(params, XPSObj); +% -- Extracting the MODEL +fitStr.M = fit_model(params, XPSObj); +% -- Extracting the BACKGROUND +fitStr.B = fit_background(params, XPSObj); +% -- Extracting the DATA - BACKGROUND +fitStr.DB = fitStr.D - fitStr.B; +fitStr.MB = fitStr.M + fitStr.B; +% -- Extracting the RESIDUALS (R = D - (M + B)) +fitStr.R = fitStr.D - (fitStr.M + fitStr.B); +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ = sum(fitStr.R.^2 ./ abs(fitStr.M + fitStr.B)); +fitStr.MINFUN = minimize_function(params, XPSObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables for the PES background +fitStr.bPARAMS = params(end-2:end); +fitStr.LHS = fitStr.bPARAMS(1); +fitStr.RHS = fitStr.bPARAMS(2); +fitStr.BGR = fitStr.bPARAMS(3); +%% 4.4 - Storing the final fit variables of each PES curve component +fitStr.MFP = params(1); +fitStr.BOFF = params(2); +fitStr.XX = linspace(min(fitStr.X(:)), max(fitStr.X(:)), 5e3)'; +fitStr.YY = zeros(size(fitStr.XX)); +% -- Storing the potential profile +imodelStr = mstheory_interp_spectra(modelStr, fitStr.BOFF, fitStr.MFP); +fitStr.ZPOT = linspace(min(imodelStr.ZPOT(:)), max(imodelStr.ZPOT(:)), 1e3); +fitStr.EPOT = interp1(imodelStr.ZPOT, imodelStr.EPOT, fitStr.ZPOT); +for i = 1:fitStr.nSTATES + % --- Best fit components on new domain + fitStr.cPARAMS(i,:) = params((2+i):fitStr.nSTATES:(end-3)); + [fitStr.cYY(:,i), fitStr.potYY(:,:,i)] = PESCurve_POT(fitStr.XX, fitStr.cTYPE(i),... + fitStr.cPARAMS(i,1), fitStr.cPARAMS(i,2), fitStr.cPARAMS(i,3),... + fitStr.cPARAMS(i,4), fitStr.cPARAMS(i,5), fitStr.cPARAMS(i,6),... + fitStr.cPARAMS(i,7), fitStr.cPARAMS(i,8),... + fitStr.MFP, fitStr.ZPOT, fitStr.EPOT); + fitStr.YY = fitStr.YY + fitStr.cYY(:,i); + % --- Storing each curve parameter + fitStr.DCL(i) = fitStr.cPARAMS(i,1); + fitStr.INT(i) = fitStr.cPARAMS(i,2); + fitStr.FWHM(i) = fitStr.cPARAMS(i,3); + fitStr.MR(i) = fitStr.cPARAMS(i,4); + fitStr.LSE(i) = fitStr.cPARAMS(i,5); + fitStr.LSI(i) = fitStr.cPARAMS(i,6); + fitStr.LSW(i) = fitStr.cPARAMS(i,7); + fitStr.ASY(i) = fitStr.cPARAMS(i,8); + % --- Storing energy information + fitStr.BE_Z0(i) = fitStr.DCL(i) - fitStr.BOFF; + [~,I] = max(fitStr.cYY(:,i)); fitStr.BE_MAX(i)= fitStr.XX(I); + % --- Storing the curve area information + fitStr.AREA(i) = trapz(fitStr.XX, fitStr.cYY(:,i)); +end +% --- Storing the normalised area contribution for quantification +fitStr.AREA0 = fitStr.AREA ./ trapz(fitStr.XX, fitStr.YY); +% - Extracting the total potential profile of all components +fitStr.potYY_tot = sum(fitStr.potYY, 3); +fitStr.potYY_comp = squeeze(sum(fitStr.potYY, 2)); +for i = 1:nSTATES + fitStr.potYY_comp(:,i) = fitStr.INT(i) .* (fitStr.potYY_comp(:,i) ./ max(fitStr.potYY_comp(:,i))); +end + +end + +%% DEFINING THE RESIDUAL MINIMISATION FUNCTION TO BE MINIMISED +function MINFUN = minimize_function(x, XPSObj) + % - 1 - Extracting the DATA + [~, D] = fit_data(x, XPSObj); + % - 2 - Extracting the MODEL + M = fit_model(x, XPSObj); + % - 3 - Extracting the BACKGROUND + B = fit_background(x, XPSObj); + % - 4 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - (M + B); + % - 5 - Extracting the CHI-SQUARED value to be minimised + MINFUN = sum(R.^2 ./ abs(M + B)); +% MINFUN = std(R.^2 ./ abs(M + B)); +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE XPS DATA TO BE FITTED +function [X, D] = fit_data(x, XPSObj) + [X, D, ~] = PESBackground(XPSObj.xdat, XPSObj.ydat, XPSObj.fit_args.bTYPE, x(end-2), x(end-1), x(end), XPSObj.fit_args.ibgrnd{4}); + D(isnan(D)) = 0; + if size(D, 2) > 1; D = D'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES BACKGROUND +function B = fit_background(x, XPSObj) + [~, ~, B] = PESBackground(XPSObj.xdat, XPSObj.ydat, XPSObj.fit_args.bTYPE, x(end-2), x(end-1), x(end), XPSObj.fit_args.ibgrnd{4}); + B(isnan(B)) = 0; + if size(B, 2) > 1; B = B'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES CURVE FIT +function M = fit_model(x, XPSObj) + % - 1 - Extracting the potential profile + imodelStr = mstheory_interp_spectra(XPSObj.modelStr, x(2), x(1)); + ZPOT = linspace(min(imodelStr.ZPOT(:)), max(imodelStr.ZPOT(:)), 1e3); + EPOT = interp1(imodelStr.ZPOT, imodelStr.EPOT, ZPOT); + % - 2 - Extract the curve component for each state + comp_int = {}; + for i = 1:XPSObj.fit_args.nSTATES + % -- Extracting the arguments for the component curve + pes_args = x((2+i):XPSObj.fit_args.nSTATES:(end-3)); + % -- Extracting the component intensities + comp_int{i} = PESCurve_POT(XPSObj.roi_xdat, XPSObj.fit_args.cTYPE(i),... + pes_args(1), pes_args(2), pes_args(3),... + pes_args(4), pes_args(5), pes_args(6),... + pes_args(7), pes_args(8),... + x(1), ZPOT, EPOT); + end + % - 3 - Sum up all of the curve components to get the final model PES curve + pes_int = zeros(size(XPSObj.roi_xdat)); + for i = 1:XPSObj.fit_args.nSTATES + pes_int = pes_int + comp_int{i}; + end + M = pes_int; + M(isnan(M)) = 0; + if size(M, 2) > 1; M = M'; end +end + +%% DEFINING THE FINAL FUNCTION THAT DESCRIBES THE PES CURVE TO BE FITTED +function MB = full_pes_function(x, xdat, XPSObj) + % - 1 - Extracting the potential profile + imodelStr = mstheory_interp_spectra(XPSObj.modelStr, x(2), x(1)); + ZPOT = linspace(min(imodelStr.ZPOT(:)), max(imodelStr.ZPOT(:)), 1e3); + EPOT = interp1(imodelStr.ZPOT, imodelStr.EPOT, ZPOT); + % - 2 - Extract the curve component for each state + comp_int = {}; + for i = 1:XPSObj.fit_args.nSTATES + % -- Extracting the arguments for the component curve + pes_args = x((2+i):XPSObj.fit_args.nSTATES:(end-3)); + % -- Extracting the component intensities + comp_int{i} = PESCurve_POT(xdat, XPSObj.fit_args.cTYPE(i),... + pes_args(1), pes_args(2), pes_args(3),... + pes_args(4), pes_args(5), pes_args(6),... + pes_args(7), pes_args(8),... + x(1), ZPOT, EPOT); + end + % - 3 - Sum up all of the curve components to get the final model PES curve + pes_int = zeros(size(xdat)); + for i = 1:XPSObj.fit_args.nSTATES + pes_int = pes_int + comp_int{i}; + end + M = pes_int; + % - 4 - Determine the background to be used + [B_xdat, ~, B] = PESBackground(xdat, XPSObj.roi_ydat, XPSObj.fit_args.bTYPE, x(end-2), x(end-1), x(end), XPSObj.fit_args.ibgrnd{4}); + B = interp1(B_xdat, B, xdat); + % - 5 - Final output is the sum of the model and background + MB = M + B; + MB(isnan(MB)) = 0; if size(MB, 2) > 1; MB = MB'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2boff fitting/pes2boff_view_fit.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2boff fitting/pes2boff_view_fit.m new file mode 100644 index 0000000..b98c2e9 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2boff fitting/pes2boff_view_fit.m @@ -0,0 +1,145 @@ +function fig = pes2boff_view_fit(fitStr) +% fig = pes2boff_view_fit(fitStr) +% This function is used to plot the final PES curve model AFTER curve +% fitting with the 'pes2boff_solver()'. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - fitStr: data structure that contains the PES fitting output of the corresponding solver. +% +% OUT: +% - fig: MATLAB figure object that summarises the fit. + +%% - 1 - Plotting the model to be used for fitting +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'PES Curve Fitting'); +fig.Position(1) = 100; +fig.Position(2) = 100; +fig.Position(3) = 2.5*pp.fig5x4(1); +fig.Position(4) = 2.5*pp.fig5x4(2); + +%% - 2.1 - PLOTTING THE RAW DATA AND BEST FIT BACKGROUND +subplot(221); hold on; +% -- Plotting the ROI, LHS and RHS analysis windows +ROI = [fitStr.X(1), fitStr.X(end)]; +LHS = ROI(1) + 0.05.*[-1,1].*range(fitStr.xdat(:)); +RHS = ROI(2) + 0.05.*[-1,1].*range(fitStr.xdat(:)); +hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e6, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); +hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting a vertical line to show the ROI +a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +a.Annotation.LegendInformation.IconDisplayStyle = 'off'; +b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting the 1D data +plot(fitStr.xdat, fitStr.ydat, 'b-', 'linewidth', 0.5); +plot(fitStr.X, fitStr.D, 'b-', 'linewidth', 2); +plot(fitStr.X, fitStr.B, 'r-', 'linewidth', 2); +plot(fitStr.X, fitStr.DB, 'k-', 'linewidth', 2); +gca_props(); title('Background Subtraction', 'interpreter', 'none', 'fontsize', 9); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); +% -- Determining the best limits for the plot +axLim_y = [fitStr.ydat; fitStr.DB]; +axis([min(fitStr.xdat(:)), max(fitStr.xdat(:)), min(axLim_y(:)), 1.1*max(axLim_y(:))]); + +%% - 2.2 - PLOTTING THE BEST FIT CURVE COMPONENTS AND FINAL MODEL FIT +subplot(8,2,[2,4,6]); hold on; +% -- Plotting all of the curve components +for i = 1:fitStr.nSTATES + area(fitStr.XX, fitStr.cYY(:,i), 'FaceColor', pp.col.fit{i}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); + plot(fitStr.XX, fitStr.cYY(:,i), 'k-', 'linewidth', 0.25); +end +% -- Plotting the curve component energy locations +for i = 1:fitStr.nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + % --- Plotting DCL + line([1,1]*fitStr.DCL(i), [0, max(fitStr.cYY(:,i))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '-'); + % --- Plotting BE_Z0 + line([1,1]*fitStr.BE_Z0(i), [0, max(fitStr.cYY(:,i))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', ':'); +end +% -- Plotting the experimental and fit spectra +plot(fitStr.X, fitStr.DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(fitStr.X, fitStr.M, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(fitStr.CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +axis([min(fitStr.X(:)), max(fitStr.X(:)), min(fitStr.DB(:)), 1.10*max(fitStr.DB(:))]); +title("Initial Model for Fitting", 'interpreter', 'none', 'fontsize', 9); + +%% - 2.3 - PLOTTING THE RESIDUALS FOR THE BEST FIT TO THE DATA +subplot(8,2,8); hold on; +bar(fitStr.X, fitStr.R, 'facecolor', [0 0 0]); +gca_props(); grid on; +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + +%% - 3 - PLOTTING THE POTENTIAL WELL, MODULATED BY THE MFP +subplot(8,2,[9,11,13,15]); hold on; +% --- Image of the curve series shifted by potential and scaled by MFP +ImData(fitStr.ZPOT, fitStr.XX, fitStr.potYY_tot); +% -- Plotting the curve component energy locations +for i = 1:fitStr.nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + % --- Plotting DCL + line([0, max(fitStr.ZPOT(:))], [1,1]*fitStr.DCL(i), 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', '-'); + % --- Plotting BE_Z0 + line([0, max(fitStr.ZPOT(:))], [1,1]*fitStr.BE_Z0(i), 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', ':'); +end +% --- Plotting the potential energy curves +plot(fitStr.ZPOT, fitStr.EPOT+fitStr.DCL(1), 'r-', 'linewidth', 2); +% --- Formatting the figure +img_props(); +subplot(8,2,[9,11,13,15]); hold on; +colormap jet; title('Model Potential : V(z)', 'Interpreter','none'); +axis square; +xlabel('$$ \bf z (nm) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +axis([0, max(fitStr.ZPOT(:)), min(fitStr.XX(:)), max(fitStr.XX(:))]); +% --- Adding text to quantify the band offset +BOFF = round(fitStr.BOFF, 3); +text(0.04, 0.92, "$$ \phi_{z=0} = $$ " + string(BOFF), 'interpreter', 'latex', 'fontsize', 14, 'color', 'w', 'Units','normalized'); + +%% - 4 - PLOTTING ALL THE INDIVIDUAL CURVES, SHIFTED BY THE POTENTIAL FOR N=1 +subplot(224); hold on; +% --- Plotting individual curves +cols = flipud(jet(length(fitStr.ZPOT)+2)); +for i = 1:length(fitStr.ZPOT) + plot(fitStr.XX, fitStr.potYY(:,i,1), 'k-', 'color', cols(i,:), 'linewidth', 0.5); +end +% --- Plotting the final curve +plot(fitStr.XX, fitStr.potYY_comp(:,1), 'k-', 'linewidth', 2); +% --- Formatting the figure +gca_props(); title('Integrated Curves : n = 1', 'Interpreter','none'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); +axis([min(fitStr.XX(:)), max(fitStr.XX(:)), 0, 1.1*max(fitStr.M(:))]); +% -- Plotting the curve component energy locations +lWidth = pp.llwidth; +% --- Plotting DCL +line([1,1]*fitStr.DCL(1), [0, max(fitStr.cYY(:,1))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '-'); +% --- Plotting BE_Z0 +line([1,1]*fitStr.BE_Z0(1), [0, max(fitStr.cYY(:,1))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', ':'); +% --- Plotting BE_MAX +[~,I] = max(fitStr.potYY_comp(:,1)); BE_MAX = fitStr.XX(I); +line([BE_MAX, BE_MAX], [0, max(fitStr.cYY(:,1))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '--'); +% --- Adding text to quantify all the shifts +DCL = round(fitStr.DCL(1), 3); +BE_Z0 = round(fitStr.BE_Z0(1), 3); +BE_MAX = round(fitStr.BE_MAX(1), 3); +text(0.04, 0.92, "$$ \Delta_{CL} = $$ " + string(DCL), 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); +text(0.04, 0.86, "$$ BE_{z=0} = $$ " + string(BE_Z0), 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); +text(0.04, 0.80, "$$ BE_{MAX} = $$ " + string(BE_MAX), 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2boff fitting/pes2boff_view_init.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2boff fitting/pes2boff_view_init.m new file mode 100644 index 0000000..792afa7 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2boff fitting/pes2boff_view_init.m @@ -0,0 +1,244 @@ +function fig = pes2boff_view_init(pesStr, modelStr, cTYPE, iparams, bTYPE, ibgrnd) +% fig = pes2boff_view_init(pesStr, modelStr, cTYPE, iparams, bTYPE, ibgrnd) +% This function is used to plot the initial, model XPS curve PRIOR to +% curve fitting with 'pes2boff_solver()'. The plot consists of 3 subplots; (1) The +% background that is determined from the fit; (2) A plot showing all of +% the fitted curve components, as well as the final model fit and +% experimental data; (3) A plot of the residuals, showing the quality of +% the experimental and model fit. This is used as an informative plot +% that allows you to view and create a better initial guess of the XPS +% model prior to running the fitting algorithm. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - pesStr: data structure that contains the PES data. +% - modelStr: data structure that contains the model data. +% - cTYPE: 1xN vector of the type of curve to use for the nth state. +% - iparams: 3 cells {x0}{lb}{ub} with Nx8 arrays: the n'th peak parameters [BE,INT,FWHM,MR,LSE,LSI,LSW,ASY] +% - bTYPE: string of the type of background to use for fitting. Default: "Poly" ("none", "Poly", "Shir", "LinShir", "StepFDDGpL", "StepFDDGsL") +% - ibgrnd: 4 cells {x0}{lb}{ub}{args} with 1x3 vectors of the background parameters: x0=lb=ub=[LHS,RHS,BGR], or argument of the background type args = [] +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% - 1 - Extracting all background subtraction data and information +% -- Extracting the background +[X, D, B] = PESBackground(pesStr.xdat, pesStr.ydat,... + bTYPE, ibgrnd{1}(1), ibgrnd{1}(2), ibgrnd{1}(3), ibgrnd{4}); + +%% - 2 - Extracting all of the input parameters +% -- Extracting the original XPS data +% xdat = linspace(min(pesStr.xdat(:)), max(pesStr.xdat(:)), 1e3); +% ydat = interp1(pesStr.xdat, pesStr.ydat, xdat); +xdat = pesStr.xdat; +ydat = pesStr.ydat; +% -- Extracting the total number of states to be fitted +nSTATES = length(cTYPE); +% -- Extracting all of the fit parameters +% -- Singular variables +MFP = iparams{1}(1); +BOFF = iparams{1}(2); +lbMFP = iparams{2}(1); ubMFP = iparams{3}(1); +lbBOFF = iparams{2}(2); ubBOFF = iparams{3}(2); +% -- Curve parameter variables +for i = 1:nSTATES + % --- Storing each curve parameter + DCL(i) = iparams{1}(i+2+0*nSTATES); + INT(i) = iparams{1}(i+2+1*nSTATES); + FWHM(i) = iparams{1}(i+2+2*nSTATES); + MR(i) = iparams{1}(i+2+3*nSTATES); + LSE(i) = iparams{1}(i+2+4*nSTATES); + LSI(i) = iparams{1}(i+2+5*nSTATES); + LSW(i) = iparams{1}(i+2+6*nSTATES); + ASY(i) = iparams{1}(i+2+7*nSTATES); + % --- Storing the constraints of each curve parameter + lbDCL(i) = iparams{2}(i+2+0*nSTATES); ubDCL(i) = iparams{3}(i+2+0*nSTATES); + lbINT(i) = iparams{2}(i+2+1*nSTATES); ubINT(i) = iparams{3}(i+2+1*nSTATES); + lbFWHM(i) = iparams{2}(i+2+2*nSTATES); ubFWHM(i) = iparams{3}(i+2+2*nSTATES); + lbMR(i) = iparams{2}(i+2+3*nSTATES); ubMR(i) = iparams{3}(i+2+3*nSTATES); + lbLSE(i) = iparams{2}(i+2+4*nSTATES); ubLSE(i) = iparams{3}(i+2+4*nSTATES); + lbLSI(i) = iparams{2}(i+2+5*nSTATES); ubLSI(i) = iparams{3}(i+2+5*nSTATES); + lbLSW(i) = iparams{2}(i+2+6*nSTATES); ubLSW(i) = iparams{3}(i+2+6*nSTATES); + lbASY(i) = iparams{2}(i+2+7*nSTATES); ubASY(i) = iparams{3}(i+2+7*nSTATES); + % --- Storing additional parameters + BE_Z0(i) = DCL(i) - BOFF; +end +% -- Extracting the model potential well based on the model and BOFF +imodelStr = mstheory_interp_spectra(modelStr, BOFF, MFP); +ZPOT = linspace(min(imodelStr.ZPOT(:)), max(imodelStr.ZPOT(:)), 1e3); +EPOT = interp1(imodelStr.ZPOT, imodelStr.EPOT, ZPOT); + +%% - 3 - Extracting all model data and information +% -- Initialising the vectors to contain XPS data +DB = D - B; % Data after being background subtracted +M = zeros(size(X)); % Initialising model data +% -- Filing through all curve components and extracting them seperately +cYY = []; potYY = []; +for i = 1:nSTATES + % --- Extracting curve profiles + [cYY(:,i), potYY(:,:,i)] = PESCurve_POT(X, cTYPE(i),... + DCL(i), INT(i), FWHM(i), MR(i), LSE(i), LSI(i), LSW(i), ASY(i),... + MFP, ZPOT, EPOT); + M = M + cYY(:,i); + % --- Storing additional parameters + [~,I] = max(cYY(:,i)); BE_MAX(i)= X(I); +end +% - Extracting the total potential profile of all components +potYY_tot = sum(potYY, 3); +potYY_comp = squeeze(sum(potYY, 2)); +for i = 1:nSTATES + potYY_comp(:,i) = INT(i) .* (potYY_comp(:,i) ./ max(potYY_comp(:,i))); +end + +%% - 3 - Determination of the residuals and chi-squared +R = M - (D - B); % Residuals +CHISQ = sum(R.^2 ./ abs(M + B)); % Chi-squared + +%% - 4 - Plotting the model to be used for fitting +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'PES Curve Fitting'); +fig.Position(1) = 100; +fig.Position(2) = 100; +fig.Position(3) = 2.5*pp.fig5x4(1); +fig.Position(4) = 2.5*pp.fig5x4(2); + +%% - 4.1 - PLOTTING THE RAW DATA AND BEST FIT BACKGROUND +subplot(221); hold on; +% -- Plotting the ROI, LHS and RHS analysis windows +ROI = [X(1), X(end)]; +LHS = ROI(1) + 0.05.*[-1,1].*range(xdat(:)); +RHS = ROI(2) + 0.05.*[-1,1].*range(xdat(:)); +hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e6, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); +hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting a vertical line to show the ROI +a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +a.Annotation.LegendInformation.IconDisplayStyle = 'off'; +b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting the 1D data +plot(xdat, ydat, 'b-', 'linewidth', 0.5); +plot(X, D, 'b-', 'linewidth', 2); +plot(X, B, 'r-', 'linewidth', 2); +plot(X, DB, 'k-', 'linewidth', 2); +gca_props(); title('Background Subtraction', 'interpreter', 'none', 'fontsize', 9); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); +% -- Determining the best limits for the plot +axLim_y = [ydat; DB]; +axis([min(xdat(:)), max(xdat(:)), min(axLim_y(:)), 1.1*max(axLim_y(:))]); + +%% - 4.2 - PLOTTING THE BEST FIT CURVE COMPONENTS AND FINAL MODEL FIT +subplot(8,2,[2,4,6]); hold on; +% -- Plotting all of the curve components +for i = 1:nSTATES + area(X, cYY(:,i), 'FaceColor', pp.col.fit{i}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); + plot(X, cYY(:,i), 'k-', 'linewidth', 0.25); +end +% -- Plotting the curve component energy locations +for i = 1:nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + % --- Plotting DCL + line([1, 1]*DCL(i), [0, max(cYY(:,i))], 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', '-'); + % --- Plotting BE + line([1, 1]*DCL(i)+EPOT(1), [0, max(cYY(:,i))], 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', ':'); +end +% -- Plotting the experimental and fit spectra +plot(X, DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(X, M, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +axis([min(X(:)), max(X(:)), min(DB(:)), 1.10*max(DB(:))]); +title("Initial Model for Fitting", 'interpreter', 'none', 'fontsize', 9); + +%% - 4.3 - PLOTTING THE RESIDUALS FOR THE BEST FIT TO THE DATA +subplot(8,2,8); hold on; +bar(X, R, 'facecolor', [0 0 0]); +gca_props(); grid on; +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + +%% - 5 - Plotting the uncertainties to allow for easier optimisation +subplot(8,2,[2,4,6]); hold on; +for i = 1:nSTATES + %% - 5.1 - Plotting the primary peak uncertainties + x_vals = [lbDCL(i), lbDCL(i), ubDCL(i), ubDCL(i), lbDCL(i)]; + y_vals = [lbINT(i), ubINT(i), ubINT(i), lbINT(i), lbINT(i)]; + patch(x_vals, y_vals, pp.col.fit{i}, 'FaceAlpha', 0.65, 'EdgeAlpha', 0); + %% - 5.2 - Adding text to identify each peak index + text(max(x_vals), max(y_vals), string(i), 'interpreter', 'latex', 'fontsize', 14, 'color', 'k'); + %% - 5.3 - Plotting the spin-orbit split (SOS) peak uncertainties + x_vals = DCL(i) + [lbLSE(i), lbLSE(i), ubLSE(i), ubLSE(i), lbLSE(i)]; + y_vals = [lbINT(i)*lbLSI(i), ubINT(i)*ubLSI(i), ubINT(i)*ubLSI(i), lbINT(i)*lbLSI(i), lbINT(i)*lbLSI(i)]; + patch(x_vals, y_vals, pp.col.fit{i}, 'FaceAlpha', 0.65, 'EdgeAlpha', 0); +end + +%% - 6 - PLOTTING THE POTENTIAL WELL, MODULATED BY THE MFP +subplot(8,2,[9,11,13,15]); hold on; +% --- Image of the curve series shifted by potential and scaled by MFP +ImData(ZPOT, X, potYY_tot); +% -- Plotting the curve component energy locations +for i = 1:nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + % --- Plotting DCL + line([0, max(ZPOT(:))], [DCL(i), DCL(i)], 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', '-'); + % --- Plotting BE + line([0, max(ZPOT(:))], [DCL(i), DCL(i)]+ EPOT(1), 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', ':'); +end +% --- Plotting the potential energy curves +plot(ZPOT, EPOT+DCL(1), 'r-', 'linewidth', 2); +% --- Formatting the figure +img_props(); +subplot(8,2,[9,11,13,15]); hold on; +colormap jet; title('Model Potential : V(z)', 'Interpreter','none'); +axis square; +xlabel('$$ \bf z (nm) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +axis([0, max(ZPOT(:)), min(X(:)), max(X(:))]); +% --- Adding text to quantify the band offset +BOFF = round(BOFF, 3); +text(0.04, 0.92, "$$ \phi_{z=0} = $$ " + string(BOFF) + " eV", 'interpreter', 'latex', 'fontsize', 14, 'color', 'w', 'Units','normalized'); + +%% - 7 - PLOTTING ALL THE INDIVIDUAL CURVES, SHIFTED BY THE POTENTIAL FOR N=1 +subplot(2,2,4); hold on; +% --- Plotting individual curves +cols = flipud(jet(length(ZPOT)+2)); +for i = 1:length(ZPOT) + plot(X, potYY(:,i,1), 'k-', 'color', cols(i,:), 'linewidth', 0.5); +end +% --- Plotting the final curve +plot(X, potYY_comp(:,1), 'k-', 'linewidth', 2); +% --- Formatting the figure +gca_props(); title('Integrated Curves : n = 1', 'Interpreter','none'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); +axis([min(X(:)), max(X(:)), 0, 1.1*max(M(:))]); +% -- Plotting the curve component energy locations +lWidth = pp.llwidth; +% --- Plotting DCL +line([1, 1]*DCL(1), [0, max(cYY(:,1))], 'Color', pp.col.fit{1}, 'LineWidth', lWidth, 'Linestyle', '-'); +% --- Plotting BE +line([1, 1]*DCL(1)+EPOT(1), [0, max(cYY(:,1))], 'Color', pp.col.fit{1}, 'LineWidth', lWidth, 'Linestyle', ':'); +% --- Plotting BE_MAX +[~,I] = max(potYY_comp(:,1)); BE_MAX = X(I); +line([BE_MAX, BE_MAX], [0, max(cYY(:,1))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '--'); +% --- Adding text to quantify all the shifts +DCL = round(DCL(1), 3); +BE_Z0 = round(BE_Z0(1), 3); +BE_MAX = round(BE_MAX(1), 3); +text(0.04, 0.92, "$$ \Delta_{CL} = $$ " + string(DCL) + " eV", 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); +text(0.04, 0.86, "$$ BE_{z=0} = $$ " + string(BE_Z0) + " eV", 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); +text(0.04, 0.80, "$$ BE_{MAX} = $$ " + string(BE_MAX) + " eV", 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_solver.m new file mode 100644 index 0000000..a4cfe2b --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_solver.m @@ -0,0 +1,376 @@ +function fitStr = pes2ncurve_solver(pesStr, cTYPE, iparams, bTYPE, ibgrnd, solve_type) +% fitStr = pes2ncurve_solver(pesStr, cTYPE, iparams, bTYPE, ibgrnd, solve_type) +% Function that runs an optimisation algorithm to solve for the best fit +% to the PES data using N curves. +% NOTE: use 'pes2ncurve_solver_n_runs()' to run the algorithm N times, allowing +% for quantification of fit parameter uncertainties. +% +% REQ. FUNCTIONS: none +% +% IN: +% - pesStr: data structure that contains the PES data. +% - cTYPE: 1×N vector of the type of curve to use for the nth state. +% - iparams: 3 cells {x0}{lb}{ub} with N×8 arrays: the n'th peak parameters [BE,INT,FWHM,MR,LSE,LSI,LSW,ASY] +% - bTYPE: string of the type of background to use for fitting. Default: "Poly" ("none", "Poly", "Shir", "LinShir", "StepFDDGpL", "StepFDDGsL") +% - ibgrnd: 4 cells {x0}{lb}{ub}{args} with 1x3 vectors of the background parameters: x0=lb=ub=[LHS,RHS,BGR], or argument of the background type args = [] +% - solve_type: string of the optimisation algorithm to use; "lsqcurvefit" (very fast, good), "lsqnonlin" (fast, not good), "simulannealbnd" (slow, best). +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Default parameters +% - Default input parameters to use +if nargin < 6; solve_type = "lsqcurvefit"; end +if nargin < 5 + ibgrnd{1} = [... + mean(pesStr.xdat(:)) - abs(0.25*range(pesStr.xdat(:))),... + mean(pesStr.xdat(:)) + abs(0.25*range(pesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if nargin < 4; bTYPE = "Poly"; end +if isempty(solve_type); solve_type = "lsqcurvefit"; end +if isempty(ibgrnd) + ibgrnd{1} = [... + mean(pesStr.xdat(:)) - abs(0.25*range(pesStr.xdat(:))),... + mean(pesStr.xdat(:)) + abs(0.25*range(pesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if isempty(bTYPE); bTYPE = "Poly"; end +% -- Consistency check and finding the total number of curves +if size(iparams{1}, 1) ~= size(iparams{2}, 1) || size(iparams{2}, 1) ~= size(iparams{3}, 1) + error('The input parameter cell array is not a consistent size - check iparams input!'); +end +% -- Validity check on input parameters +for i = 1:size(iparams{1}, 1) + if size(iparams{1}, 2) == 4 + % --- Set the ASY, LSE, LSI and LSW components to zero + iparams{1}(i,5) = 0; iparams{1}(i,6) = 0; iparams{1}(i,7) = 0; iparams{1}(i,8) = 0; + iparams{2}(i,5) = 0; iparams{2}(i,6) = 0; iparams{2}(i,7) = 0; iparams{2}(i,8) = 0; + iparams{3}(i,5) = 0; iparams{3}(i,6) = 0; iparams{3}(i,7) = 0; iparams{3}(i,8) = 0; + elseif size(iparams{1}, 2) == 5 + % --- Set the LSE, LSI and LSW components to zero + iparams{1}(i,6) = 0; iparams{1}(i,7) = 0; iparams{1}(i,8) = 0; + iparams{2}(i,6) = 0; iparams{2}(i,7) = 0; iparams{2}(i,8) = 0; + iparams{3}(i,6) = 0; iparams{3}(i,7) = 0; iparams{3}(i,8) = 0; + elseif size(iparams{1}, 2) == 6 + % --- Set the LSI and LSW components to zero + iparams{1}(i,7) = 0; iparams{1}(i,8) = 0; + iparams{2}(i,7) = 0; iparams{2}(i,8) = 0; + iparams{3}(i,7) = 0; iparams{3}(i,8) = 0; + elseif size(iparams{1}, 2) == 7 + % --- Set the LSW components to zero + iparams{1}(i,8) = 0; + iparams{2}(i,8) = 0; + iparams{3}(i,8) = 0; + elseif size(iparams{1}, 2) > 8 || size(iparams{1}, 2) < 4 + error('Not enough input arguments defined - check iparams input!'); + end +end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Total number of states to be fitted +nSTATES = length(cTYPE); +% -- Defining the initial conditions and limits of the optimisation method +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; +% -- Defining the initial conditions and limits of the optimisation method +for i = 1:nSTATES + indx = i:nSTATES:length(x0)-3; + X0 = x0(indx); LB = lb(indx); UB = ub(indx); + % --- parameters + if X0(2) < 0; x0(indx(2)) = 0; end % if INT < 0, then make it 0 + if X0(3) < 0; x0(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if X0(4) < 0; x0(indx(4)) = 0; end % if MR < 0, then make it 0 + if X0(4) > 1; x0(indx(4)) = 1; end % if MR > 1, then make it 1 + if X0(6) < 0; x0(indx(6)) = 0; end % if LSI < 0, then make it 0 + if X0(7) < 0; x0(indx(7)) = 0; end % if LSW < 0, then make it 0 + if X0(8) < 0; x0(indx(8)) = 0; end % if ASY < 0, then make it 0 + % --- lower bounds + if LB(2) < 0; lb(indx(2)) = 0; end % if INT < 0, then make it 0 + if LB(3) < 0; lb(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if LB(4) < 0; lb(indx(4)) = 0; end % if MR < 0, then make it 0 + if LB(4) > 1; lb(indx(4)) = 1; end % if MR > 1, then make it 1 + if LB(6) < 0; lb(indx(6)) = 0; end % if LSI < 0, then make it 0 + if LB(7) < 0; lb(indx(7)) = 0; end % if LSW < 0, then make it 0 + if LB(8) < 0; lb(indx(8)) = 0; end % if ASY < 0, then make it 0 + % --- lower bounds + if UB(2) < 0; ub(indx(2)) = 0; end % if INT < 0, then make it 0 + if UB(3) < 0; ub(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if UB(4) < 0; ub(indx(4)) = 0; end % if MR < 0, then make it 0 + if UB(4) > 1; ub(indx(4)) = 1; end % if MR > 1, then make it 1 + if UB(6) < 0; ub(indx(6)) = 0; end % if LSI < 0, then make it 0 + if UB(7) < 0; ub(indx(7)) = 0; end % if LSW < 0, then make it 0 + if UB(8) < 0; ub(indx(8)) = 0; end % if ASY < 0, then make it 0 + % --- ensuring the fit window is within the domain + if x0(end-2) < min(pesStr.xdat(:)); x0(end-2) = min(pesStr.xdat(:)); end + if x0(end-1) > max(pesStr.xdat(:)); x0(end-1) = max(pesStr.xdat(:)); end +end +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - DEFINING THE XPS DATA AND FITTING ARGUMENTS +% -- Extracting the data to be fitted +[roi_xdat, roi_ydat, roi_bgrnd] = PESBackground(pesStr.xdat, pesStr.ydat, bTYPE, x0(end-2), x0(end-1), x0(end), ibgrnd{4}); +% -- Defining a structure that stores all relevant model and data variables +XPSObj = pesStr; +XPSObj.roi_xdat = roi_xdat; +XPSObj.roi_ydat = roi_ydat; +XPSObj.roi_bgrnd = roi_bgrnd; +XPSObj.roi_ydat_sbtr = XPSObj.roi_ydat - XPSObj.roi_bgrnd; +% -- Appending the input arguments to the global variable +XPSObj.fit_args.solve_type = solve_type; +XPSObj.fit_args.nSTATES = length(cTYPE); +XPSObj.fit_args.cTYPE = cTYPE; +XPSObj.fit_args.iparams = iparams; +XPSObj.fit_args.bTYPE = bTYPE; +XPSObj.fit_args.ibgrnd = ibgrnd; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 5e3; +FuncTol = 1e-7; % 1e-7; +StepTol = 1e-7; % 1e-7; +OptTol = 1e-7; % 1e-7; +ConTol = 1e-7; % 1e-7; +FinDiffRelStep = 1e-5; % 1e-5; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; +%% - 3.1 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR CURVE FITTING +if solve_type == "lsqcurvefit" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqcurvefit,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqcurvefit(@(x,roi_xdat) full_pes_function(x,roi_xdat,XPSObj), x0, roi_xdat, roi_ydat, lb, ub, options); + +%% - 3.2 - LOCAL SOLVER: UNBOUNDED LEAST SQUARES NONLINEAR REGRESSION FIT +elseif solve_type == "nlinfit" + % -- Defining the optimisation options for the simulated annealing method + options = statset(... + 'MaxFunEvals', MaxFunEvals,... + 'MaxIter', MaxIter,... + 'TolFun', FuncTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,R,J,CovB,MSE,ErrorModelInfo] = nlinfit(roi_xdat, roi_ydat, @(x,roi_xdat) full_pes_function(x,roi_xdat,XPSObj), x0, options); +%% - 3.3 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,grad,hessian] = fminunc(@(x) minimize_function(x,XPSObj), x0, options); + +%% - 3.4 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,XPSObj), x0, [], [], [], [], lb, ub, [], options); + + %% - 3.5 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR LEAST SQUARES PROBLEMS +elseif solve_type == "lsqnonlin" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqnonlin,... + 'Algorithm', 'levenberg-marquardt',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqnonlin(@(x) minimize_function(x,XPSObj), x0, lb, ub, options); +%% - 3.8 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,XPSObj), x0, lb, ub, options); +end + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.cTYPE = cTYPE; +fitStr.iparams = iparams; +fitStr.bTYPE = bTYPE; +fitStr.ibgrnd = ibgrnd; +fitStr.nSTATES = length(cTYPE); +%% 4.2 - Storing the XPS data, background, model and minimisation variables +% -- Extracting the original data +fitStr.xdat = pesStr.xdat; +fitStr.ydat = pesStr.ydat; +% -- Extracting the X-DOMAIN and DATA +[fitStr.X, fitStr.D] = fit_data(params, XPSObj); +% -- Extracting the MODEL +fitStr.M = fit_model(params, XPSObj); +% -- Extracting the BACKGROUND +fitStr.B = fit_background(params, XPSObj); +% -- Extracting the DATA - BACKGROUND +fitStr.DB = fitStr.D - fitStr.B; +fitStr.MB = fitStr.M + fitStr.B; +% -- Extracting the RESIDUALS (R = D - (M + B)) +fitStr.R = fitStr.D - (fitStr.M + fitStr.B); +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ = sum(fitStr.R.^2 ./ abs(fitStr.M + fitStr.B)); +fitStr.MINFUN = minimize_function(params, XPSObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables for the PES background +fitStr.bPARAMS = params(end-2:end); +fitStr.LHS = fitStr.bPARAMS(1); +fitStr.RHS = fitStr.bPARAMS(2); +fitStr.BGR = fitStr.bPARAMS(3); +%% 4.4 - Storing the final fit variables of each PES curve component +fitStr.XX = linspace(min(fitStr.X(:)), max(fitStr.X(:)), 1e3)'; +fitStr.YY = zeros(size(fitStr.XX)); +for i = 1:fitStr.nSTATES + % --- Best fit components on new domain + fitStr.cPARAMS(i,:) = params(i:fitStr.nSTATES:end-3); + fitStr.cYY(:,i) = PESCurve(fitStr.XX, fitStr.cTYPE(i),... + fitStr.cPARAMS(i,1), fitStr.cPARAMS(i,2), fitStr.cPARAMS(i,3),... + fitStr.cPARAMS(i,4), fitStr.cPARAMS(i,5), fitStr.cPARAMS(i,6),... + fitStr.cPARAMS(i,7), fitStr.cPARAMS(i,8)); + fitStr.YY = fitStr.YY + fitStr.cYY(:,i); + % --- Storing each curve parameter + fitStr.BE(i) = fitStr.cPARAMS(i,1); + fitStr.INT(i) = fitStr.cPARAMS(i,2); + fitStr.FWHM(i) = fitStr.cPARAMS(i,3); + fitStr.MR(i) = fitStr.cPARAMS(i,4); + fitStr.LSE(i) = fitStr.cPARAMS(i,5); + fitStr.LSI(i) = fitStr.cPARAMS(i,6); + fitStr.LSW(i) = fitStr.cPARAMS(i,7); + fitStr.ASY(i) = fitStr.cPARAMS(i,8); + % --- Storing the curve area information + fitStr.AREA(i) = trapz(fitStr.XX, fitStr.cYY(:,i)); +end +% --- Storing the normalised area contribution for quantification +fitStr.AREA0 = fitStr.AREA ./ trapz(fitStr.XX, fitStr.YY); + +end + +%% DEFINING THE RESIDUAL MINIMISATION FUNCTION TO BE MINIMISED +function MINFUN = minimize_function(x, XPSObj) + % - 1 - Extracting the DATA + [~, D] = fit_data(x, XPSObj); + % - 2 - Extracting the MODEL + M = fit_model(x, XPSObj); + % - 3 - Extracting the BACKGROUND + B = fit_background(x, XPSObj); + % - 4 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - (M + B); + % - 5 - Extracting the CHI-SQUARED value to be minimised + MINFUN = sum(R.^2 ./ abs(M + B)); +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE XPS DATA TO BE FITTED +function [X, D] = fit_data(x, XPSObj) + [X, D, ~] = PESBackground(XPSObj.xdat, XPSObj.ydat, XPSObj.fit_args.bTYPE, x(end-2), x(end-1), x(end), XPSObj.fit_args.ibgrnd{4}); + D(isnan(D)) = 0; + if size(D, 2) > 1; D = D'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES BACKGROUND +function B = fit_background(x, XPSObj) + [~, ~, B] = PESBackground(XPSObj.xdat, XPSObj.ydat, XPSObj.fit_args.bTYPE, x(end-2), x(end-1), x(end), XPSObj.fit_args.ibgrnd{4}); + B(isnan(B)) = 0; + if size(B, 2) > 1; B = B'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES CURVE FIT +function M = fit_model(x, XPSObj) + % - 1 - Extract the curve component for each state + comp_int = {}; + for i = 1:XPSObj.fit_args.nSTATES + % -- Extracting the arguments for the component curve + pes_args = x(i:XPSObj.fit_args.nSTATES:end-3); + % -- Extracting the component intensities + comp_int{i} = PESCurve(XPSObj.roi_xdat, XPSObj.fit_args.cTYPE(i),... + pes_args(1), pes_args(2), pes_args(3),... + pes_args(4), pes_args(5), pes_args(6),... + pes_args(7), pes_args(8)); + end + % - 2 - Sum up all of the curve components to get the final model PES curve + pes_int = zeros(size(XPSObj.roi_xdat)); + for i = 1:XPSObj.fit_args.nSTATES + pes_int = pes_int + comp_int{i}; + end + M = pes_int; + M(isnan(M)) = 0; + if size(M, 2) > 1; M = M'; end +end + +%% DEFINING THE FINAL FUNCTION THAT DESCRIBES THE PES CURVE TO BE FITTED +function MB = full_pes_function(x, xdat, XPSObj) + % - 1 - Extract the curve component for each state + comp_int = {}; + for i = 1:XPSObj.fit_args.nSTATES + % -- Extracting the arguments for the component curve + pes_args = x(i:XPSObj.fit_args.nSTATES:end-3); + % -- Extracting the component intensities + comp_int{i} = PESCurve(xdat, XPSObj.fit_args.cTYPE(i),... + pes_args(1), pes_args(2), pes_args(3),... + pes_args(4), pes_args(5), pes_args(6),... + pes_args(7), pes_args(8)); + end + % - 2 - Sum up all of the curve components to get the final model PES curve + pes_int = zeros(size(xdat)); + for i = 1:XPSObj.fit_args.nSTATES + pes_int = pes_int + comp_int{i}; + end + M = pes_int; + % - 3 - Determine the background to be used + [B_xdat, ~, B] = PESBackground(xdat, XPSObj.roi_ydat, XPSObj.fit_args.bTYPE, x(end-2), x(end-1), x(end), XPSObj.fit_args.ibgrnd{4}); + B = interp1(B_xdat, B, xdat); + % - 4 - Final output is the sum of the model and background + MB = M + B; + MB(isnan(MB)) = 0; if size(MB, 2) > 1; MB = MB'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_solver_n_runs.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_solver_n_runs.m new file mode 100644 index 0000000..1b6984e --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_solver_n_runs.m @@ -0,0 +1,144 @@ +function [fitStr0, statStr] = pes2ncurve_solver_n_runs(pesStr, cTYPE, iparams, bTYPE, ibgrnd, solve_type, n_runs) +% [fitStr0, statStr] = pes2ncurve_solver_n_runs(pesStr, cTYPE, iPESCurves, bTYPE, iPESBgrnd, solve_type, n_runs) +% Function that runs 'xps_solver()' N amount of independent times until +% convergence. The initial conditions are randomly sampled over the range +% of the input uncertainty. This allows the uncertainty in the best fit +% parameters to be determined by looking at the variance of the +% converged fit parameters. It is advised to run this algorithm for AT +% LEAST N = 100, so good statistics can be obtained. Ideally, N = 1000 +% is optimal, but this can take a few hours, especially when using +% the 'simulannealbnd()' global optimisation method. +% +% REQ. FUNCTIONS: none +% +% IN: +% - pesStr: MATLAB data-structure that contains the XPS data. +% - cTYPE: 1×N vector of the type of curve to use for the nth state. +% - iPESCurves: 3 cells {x0}{lb}{ub} with Nx8 arrays: the n'th peak parameters [BE,INT,FWHM,MR,LSE,LSI,LSW,ASY] +% - bTYPE: string of the type of background to use for fitting. Default: "Poly" ("none", "Poly", "Shir", "LinShir", "StepFDDGpL", "StepFDDGsL") +% - iPESBgrnd: 3 cells {x0}{lb}{ub} with 1x5 vectors: the background parameters: [LHS,RHS,ORD,LAM,DEL,BGR] +% - solve_type: string of the optimisation algorithm to use; "lsqcurvefit" (very fast, good), "lsqnonlin" (fast, not good), "simulannealbnd" (slow, best). +% - n_runs: scalar value for the total number of independent runs +% +% OUT: +% - fitStr0: MATLAB data-structure that contains all the fit parameters / variables / information for the fit with minimum CHISQ value +% - statStr: MATLAB data-structure that contains all the statistical analysis + +%% Default parameters +% - Default input parameters to use +if nargin < 7; n_runs = 10; end +if nargin < 6; solve_type = "lsqcurvefit"; end +if nargin < 5 + ibgrnd{1} = [... + mean(pesStr.xdat(:)) - abs(0.25*range(pesStr.xdat(:))),... + mean(pesStr.xdat(:)) + abs(0.25*range(pesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if nargin < 4; bTYPE = "Poly"; end +if isempty(n_runs); n_runs = 10; end +if isempty(solve_type); solve_type = "lsqcurvefit"; end +if isempty(ibgrnd) + ibgrnd{1} = [... + mean(pesStr.xdat(:)) - abs(0.25*range(pesStr.xdat(:))),... + mean(pesStr.xdat(:)) + abs(0.25*range(pesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if isempty(bTYPE); bTYPE = "Poly"; end +% - Total number of states to be fitted +n_states = length(cTYPE); + +%% - 1 - Running the fitting algorithm N independent time for statistical analysis +statStr = struct(); +statStr.n_runs = 1:n_runs; +fit = cell(n_runs,1); +params = cell(11,1); +CHISQ = zeros(n_runs,1); +% - 1 - Running the fitting algorithm for N independent times for analysis +for i = statStr.n_runs + fprintf("Run %i / %i", i, n_runs); + % --- Add perturbation on the initial conditions + new_init_conds = iparams; + new_init_conds{1} = iparams{2} + (iparams{3}-iparams{2}) .* rand(size(iparams{2})); + % --- Executing the fit + if i == 1; fitStr{1} = pes2ncurve_solver(pesStr, cTYPE, iparams, bTYPE, ibgrnd, solve_type); + else; fitStr{i} = pes2ncurve_solver(pesStr, cTYPE, new_init_conds, bTYPE, ibgrnd, solve_type); + end + % --- Storing the best fits for statistical analysis + fit{i} = fitStr{i}; + % --- Storing the best fit parameters for statistical analysis + params{1}(i,:) = fit{i}.BE; + params{2}(i,:) = fit{i}.INT; + params{3}(i,:) = fit{i}.FWHM; + params{4}(i,:) = fit{i}.MR; + params{5}(i,:) = fit{i}.LSE; + params{6}(i,:) = fit{i}.LSI; + params{7}(i,:) = fit{i}.LSW; + params{8}(i,:) = fit{i}.ASY; + params{9}(i,:) = fit{i}.AREA0; + params{10}(i,:) = fit{i}.BGR; + params{11}(i,:) = fit{i}.CHISQ; + CHISQ(i) = fit{i}.CHISQ; +end +% -- Assigning variables +statStr.fit = fit; +statStr.params = params; +statStr.CHISQ = CHISQ; +% -- Storing the parameter labels +statStr.params_label = {'BE', 'INT', 'FWHM', 'MR', 'LSE', 'LSI', 'LSW', 'ASY', 'AREA0', 'BGR', 'CHISQ'}; + +%% - 2 - Storing the fit structure that has the smallest value of chi-squared +[~, nCHISQ] = min(statStr.CHISQ(:)); +fitStr0 = statStr.fit{nCHISQ}; + +%% - 3 - Extracting the best estimate for each one of the parameters and their standard deviation +% -- CHISQ +statStr.CHISQmu = mean(statStr.CHISQ); +statStr.CHISQerr = 3*std(statStr.CHISQ); +% -- Binding energy +statStr.BE = statStr.params{1}; +statStr.BEmu = mean(statStr.BE, 1); +statStr.BEerr = 3*std(statStr.BE, 1); +% -- Intensity +statStr.INT = statStr.params{2}; +statStr.INTmu = mean(statStr.INT, 1); +statStr.INTerr = 3*std(statStr.INT, 1); +% -- FWHM +statStr.FWHM = statStr.params{3}; +statStr.FWHMmu = mean(statStr.FWHM, 1); +statStr.FWHMerr = 3*std(statStr.FWHM, 1); +% -- MR +statStr.MR = statStr.params{4}; +statStr.MRmu = mean(statStr.MR, 1); +statStr.MRerr = 3*std(statStr.MR, 1); +% -- LSE +statStr.LSE = statStr.params{5}; +statStr.LSEmu = mean(statStr.LSE, 1); +statStr.LSEerr = 3*std(statStr.LSE, 1); +% -- LSI +statStr.LSI = statStr.params{6}; +statStr.LSImu = mean(statStr.LSI, 1); +statStr.LSIerr = 3*std(statStr.LSI, 1); +% -- LSW +statStr.LSW = statStr.params{7}; +statStr.LSWmu = mean(statStr.LSW, 1); +statStr.LSWerr = 3*std(statStr.LSW, 1); +% -- ASY +statStr.ASY = statStr.params{8}; +statStr.ASYmu = mean(statStr.ASY, 1); +statStr.ASYerr = 3*std(statStr.ASY, 1); +% -- AREA0 +statStr.AREA0 = statStr.params{9}; +statStr.AREA0mu = mean(statStr.AREA0, 1); +statStr.AREA0err = 3*std(statStr.AREA0, 1); +% -- BGR +statStr.BGR = statStr.params{10}; +statStr.BGRmu = mean(statStr.BGR, 1); +statStr.BGRerr = 3*std(statStr.BGR, 1); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_view_fit.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_view_fit.m new file mode 100644 index 0000000..7ea47bc --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_view_fit.m @@ -0,0 +1,87 @@ +function fig = pes2ncurve_view_fit(fitStr) +% fig = pes2ncurve_view_fit(fitStr) +% This function is used to plot the final PES curve model AFTER curve +% fitting with the 'pes2ncurve_solver()'. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - fitStr: data structure that contains the PES fitting output of the corresponding solver. +% +% OUT: +% - fig: MATLAB figure object that summarises the fit. + +%% Default parameters +% -- Initialising the plot parameters +pp = plot_props(); + +%% - 1 - FIGURE WITH BACKGROUND AND XPS FITS +%% - 1.1 - INITIALISING THE FIGURE +fig = figure(); set(fig, 'Name', 'PES Curve Fitting'); +fig.Position(3) = 2.5*pp.fig5x4(1); +fig.Position(4) = pp.fig5x4(2); +%% - 1.2 - PLOTTING THE RAW DATA AND BEST FIT BACKGROUND +subplot(121); hold on; +% -- Plotting the ROI, LHS and RHS analysis windows +ROI = [fitStr.X(1), fitStr.X(end)]; +LHS = ROI(1) + 0.05.*[-1,1].*range(fitStr.xdat(:)); +RHS = ROI(2) + 0.05.*[-1,1].*range(fitStr.xdat(:)); +hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e6, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); +hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting a vertical line to show the ROI +a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +a.Annotation.LegendInformation.IconDisplayStyle = 'off'; +b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting the 1D data +plot(fitStr.xdat, fitStr.ydat, 'b-', 'linewidth', 0.5); +plot(fitStr.X, fitStr.D, 'b-', 'linewidth', 2); +plot(fitStr.X, fitStr.B, 'r-', 'linewidth', 2); +plot(fitStr.X, fitStr.DB, 'k-', 'linewidth', 2); +gca_props(); title('Background Subtraction', 'interpreter', 'none', 'fontsize', 9); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); +% -- Determining the best limits for the plot +axLim_y = [fitStr.ydat; fitStr.DB]; +axis([min(fitStr.xdat(:)), max(fitStr.xdat(:)), min(axLim_y(:)), 1.1*max(axLim_y(:))]); +%% - 1.3 - PLOTTING THE RESIDUALS FOR THE BEST FIT TO THE DATA +subplot(4,2,8); hold on; +bar(fitStr.X, fitStr.R, 'facecolor', [0 0 0]); +gca_props(); +% grid on; +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +%% - 1.4 - PLOTTING THE BEST FIT CURVE COMPONENTS AND FINAL MODEL FIT +subplot(4,2,[2,4,6]); hold on; +% -- Plotting all of the curve components +for i = 1:fitStr.nSTATES + area(fitStr.XX, fitStr.cYY(:,i), 'FaceColor', pp.col.fit{i}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); + plot(fitStr.XX, fitStr.cYY(:,i), 'k-', 'linewidth', 0.25); +end +% -- Plotting the curve component energy locations +for i = 1:fitStr.nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + line([fitStr.cPARAMS(i,1), fitStr.cPARAMS(i,1)], [0, max(fitStr.cYY(:,i))],... + 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '-'); +end +% -- Plotting the experimental and fit spectra +plot(fitStr.X, fitStr.DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(fitStr.XX, fitStr.YY, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(fitStr.CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); +% grid on; +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +if min(fitStr.DB(:)) < fitStr.YY; min_y_val = min(fitStr.DB(:)); +else; min_y_val = min(fitStr.YY(:)); +end +if min_y_val > 0; min_y_val = 0; end +axis([min(fitStr.X(:)), max(fitStr.X(:)), min_y_val, 1.10*max(fitStr.DB(:))]); +title("Best Fit PES Curves", 'interpreter', 'none', 'fontsize', 9); diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_view_init.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_view_init.m new file mode 100644 index 0000000..f3ccb71 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2ncurve fitting/pes2ncurve_view_init.m @@ -0,0 +1,193 @@ +function fig = pes2ncurve_view_init(pesStr, cTYPE, iparams, bTYPE, ibgrnd) +% fig = pes2ncurve_view_init(pesStr, cTYPE, iparams, bTYPE, ibgrnd) +% This function is used to plot the initial, model XPS curve PRIOR to +% curve fitting with 'pes2ncurve_solver()'. The plot consists of 3 subplots; (1) The +% background that is determined from the fit; (2) A plot showing all of +% the fitted curve components, as well as the final model fit and +% experimental data; (3) A plot of the residuals, showing the quality of +% the experimental and model fit. This is used as an informative plot +% that allows you to view and create a better initial guess of the XPS +% model prior to running the fitting algorithm. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - pesStr: data structure that contains the PES data. +% - cTYPE: 1xN vector of the type of curve to use for the nth state. +% - iparams: 3 cells {x0}{lb}{ub} with Nx8 arrays: the n'th peak parameters [BE,INT,FWHM,MR,LSE,LSI,LSW,ASY] +% - bTYPE: string of the type of background to use for fitting. Default: "Poly" ("none", "Poly", "Shir", "LinShir", "StepFDDGpL", "StepFDDGsL") +% - ibgrnd: 4 cells {x0}{lb}{ub}{args} with 1x3 vectors of the background parameters: x0=lb=ub=[LHS,RHS,BGR], or argument of the background type args = [] +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% Default parameters +% - Default input parameters to use +if nargin < 5 + ibgrnd{1} = [... + mean(pesStr.xdat(:)) - abs(0.25*range(pesStr.xdat(:))),... + mean(pesStr.xdat(:)) + abs(0.25*range(pesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if nargin < 4; bTYPE = "Poly"; end +if isempty(ibgrnd) + ibgrnd{1} = [... + mean(pesStr.xdat(:)) - abs(0.25*range(pesStr.xdat(:))),... + mean(pesStr.xdat(:)) + abs(0.25*range(pesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if isempty(bTYPE); bTYPE = "Poly"; end +% -- Consistency check and finding the total number of curves +if size(iparams{1}, 1) ~= size(iparams{2}, 1) || size(iparams{2}, 1) ~= size(iparams{3}, 1) + error('The input parameter cell array is not a consistent size - check iparams input!'); +end +% -- Validity check on input parameters +for i = 1:size(iparams{1}, 1) + if size(iparams{1}, 2) == 4 + % --- Set the ASY, LSE, LSI and LSW components to zero + iparams{1}(i,5) = 0; iparams{1}(i,6) = 0; iparams{1}(i,7) = 0; iparams{1}(i,8) = 0; + iparams{2}(i,5) = 0; iparams{2}(i,6) = 0; iparams{2}(i,7) = 0; iparams{2}(i,8) = 0; + iparams{3}(i,5) = 0; iparams{3}(i,6) = 0; iparams{3}(i,7) = 0; iparams{3}(i,8) = 0; + elseif size(iparams{1}, 2) == 5 + % --- Set the LSE, LSI and LSW components to zero + iparams{1}(i,6) = 0; iparams{1}(i,7) = 0; iparams{1}(i,8) = 0; + iparams{2}(i,6) = 0; iparams{2}(i,7) = 0; iparams{2}(i,8) = 0; + iparams{3}(i,6) = 0; iparams{3}(i,7) = 0; iparams{3}(i,8) = 0; + elseif size(iparams{1}, 2) == 6 + % --- Set the LSI and LSW components to zero + iparams{1}(i,7) = 0; iparams{1}(i,8) = 0; + iparams{2}(i,7) = 0; iparams{2}(i,8) = 0; + iparams{3}(i,7) = 0; iparams{3}(i,8) = 0; + elseif size(iparams{1}, 2) == 7 + % --- Set the LSW components to zero + iparams{1}(i,8) = 0; + iparams{2}(i,8) = 0; + iparams{3}(i,8) = 0; + elseif size(iparams{1}, 2) > 8 || size(iparams{1}, 2) < 4 + error('Not enough input arguments defined - check iparams input!'); + end +end + +%% - 1 - Extracting all background subtraction data and information +% -- Extracting the background +[X, D, B] = PESBackground(pesStr.xdat, pesStr.ydat,... + bTYPE, ibgrnd{1}(1), ibgrnd{1}(2), ibgrnd{1}(3), ibgrnd{4}); + +%% - 2 - Extracting all model data and information +% -- Extracting the original XPS data +% xdat = linspace(min(pesStr.xdat(:)), max(pesStr.xdat(:)), 1e3); +% ydat = interp1(pesStr.xdat, pesStr.ydat, xdat); +xdat = pesStr.xdat; +ydat = pesStr.ydat; +% -- Extracting the total number of states to be fitted +nSTATES = length(cTYPE); +% -- Initialising the vectors to contain XPS data +DB = D - B; % Data after being background subtracted +M = zeros(size(X)); % XPS model data +% -- Filing through all curve components and extracting them seperately +cYY = []; +for i = 1:nSTATES + cYY(:,i) = PESCurve(X, cTYPE(i),... + iparams{1}(i,1), iparams{1}(i,2), iparams{1}(i,3),... + iparams{1}(i,4), iparams{1}(i,5), iparams{1}(i,6),... + iparams{1}(i,7), iparams{1}(i,8)); + M = M + cYY(:,i); +end + +%% - 3 - Determination of the residuals and chi-squared +R = M - (D - B); % Residuals +CHISQ = sum(R.^2 ./ abs(M + B)); % Chi-squared + +%% - 4 - Plotting the model to be used for fitting +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'Initial PES Curve Fitting'); +fig.Position(3) = 2.5*pp.fig5x4(1); +fig.Position(4) = pp.fig5x4(2); +%% - 4.1 - PLOTTING THE RAW DATA AND BEST FIT BACKGROUND +subplot(121); hold on; +% -- Plotting the ROI, LHS and RHS analysis windows +ROI = [X(1), X(end)]; +LHS = ROI(1) + 0.05.*[-1,1].*range(xdat(:)); +RHS = ROI(2) + 0.05.*[-1,1].*range(xdat(:)); +hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e6, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); +hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting a vertical line to show the ROI +a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +a.Annotation.LegendInformation.IconDisplayStyle = 'off'; +b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting the 1D data +plot(xdat, ydat, 'b-', 'linewidth', 0.5); +plot(X, D, 'b-', 'linewidth', 2); +plot(X, B, 'r-', 'linewidth', 2); +plot(X, DB, 'k-', 'linewidth', 2); +gca_props(); title('Background Subtraction', 'interpreter', 'none', 'fontsize', 9); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); +% -- Determining the best limits for the plot +axLim_y = [ydat; DB]; +axis([min(xdat(:)), max(xdat(:)), min(axLim_y(:)), 1.1*max(axLim_y(:))]); +%% - 4.2 - PLOTTING THE BEST FIT CURVE COMPONENTS AND FINAL MODEL FIT +subplot(4,2,[2,4,6]); hold on; +% -- Plotting all of the curve components +for i = 1:nSTATES + area(X, cYY(:,i), 'FaceColor', pp.col.fit{i}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); + plot(X, cYY(:,i), 'k-', 'linewidth', 0.25); +end +% -- Plotting the curve component energy locations +for i = 1:nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + line([iparams{1}(i,1), iparams{1}(i,1)], [0, max(cYY(:,i))],... + 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '-'); +end +% -- Plotting the experimental and fit spectra +plot(X, DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(X, M, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +axis([min(X(:)), max(X(:)), min(DB(:)), 1.10*max(DB(:))]); +title("Initial Curves for Fitting", 'interpreter', 'none', 'fontsize', 9); +%% - 4.3 - PLOTTING THE RESIDUALS FOR THE BEST FIT TO THE DATA +subplot(4,2,8); hold on; +bar(X, R, 'facecolor', [0 0 0]); +gca_props(); grid on; +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + +%% - 5 - Plotting the uncertainties to allow for easier optimisation +subplot(4,2,[2,4,6]); hold on; +for i = 1:nSTATES + %% - 5.1 - Plotting the primary peak uncertainties + lbBE = iparams{2}(i,1); ubBE = iparams{3}(i,1); + lbINT = iparams{2}(i,2); ubINT = iparams{3}(i,2); + x_vals = [lbBE, lbBE, ubBE, ubBE, lbBE]; + y_vals = [lbINT, ubINT, ubINT, lbINT, lbINT]; + patch(x_vals, y_vals, pp.col.fit{i}, 'FaceAlpha', 0.65, 'EdgeAlpha', 0); + %% - 5.2 - Adding text to identify each peak index + text(max(x_vals), max(y_vals), string(i), 'interpreter', 'latex', 'fontsize', 14, 'color', 'k'); + %% - 5.3 - Plotting the spin-orbit split (SOS) peak uncertainties + BE = iparams{1}(i,1); INT = iparams{1}(i,2); + lbLSE = iparams{2}(i,5); ubLSE = iparams{3}(i,5); + lbLSI = iparams{2}(i,6); ubLSI = iparams{3}(i,6); + x_vals = BE + [lbLSE, lbLSE, ubLSE, ubLSE, lbLSE]; + y_vals = [lbINT*lbLSI, ubINT*ubLSI, ubINT*ubLSI, lbINT*lbLSI, lbINT*lbLSI]; + patch(x_vals, y_vals, pp.col.fit{i}, 'FaceAlpha', 0.65, 'EdgeAlpha', 0); +end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2pot fitting/pes2pot_solver.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2pot fitting/pes2pot_solver.m new file mode 100644 index 0000000..c6711d0 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2pot fitting/pes2pot_solver.m @@ -0,0 +1,366 @@ +function fitStr = pes2pot_solver(pesStr, cTYPE, iparams, bTYPE, ibgrnd, solve_type, MFP, ZPOT, EPOT) +% fitStr = pes2pot_solver(pesStr, cTYPE, iparams, bTYPE, ibgrnd, solve_type, MFP, ZPOT, EPOT) +% Function that runs an optimisation algorithm to solve for the best fit +% to the PES data using N curves that are integrated over a predefined +% potential profile, modulated by the mean free path. +% +% REQ. FUNCTIONS: none +% +% IN: +% - pesStr: data structure that contains the PES data. +% - cTYPE: 1xN vector of the type of curve to use for the nth state. +% - iparams: 3 cells {x0}{lb}{ub} with Nx8 arrays: the n'th peak parameters [BE,INT,FWHM,MR,LSE,LSI,LSW,ASY] +% - bTYPE: string of the type of background to use for fitting. Default: "Poly" ("none", "Poly", "Shir", "LinShir", "StepFDDGpL", "StepFDDGsL") +% - ibgrnd: 4 cells {x0}{lb}{ub}{args} with 1x3 vectors of the background parameters: x0=lb=ub=[LHS,RHS,BGR], or argument of the background type args = [] +% - solve_type: string of the optimisation algorithm to use; "lsqcurvefit" (very fast, good), "lsqnonlin" (fast, not good), "simulannealbnd" (slow, best). +% - MFP: mean free path that will modulate the potential (nm). +% - ZPOT: 1xN vector of the z-axis of the potential (depth). +% - EPOT: 1xN vector of the energy-axis of the potential. +% +% OUT: +% - fitStr: MATLAB data-structure that contains all the fit parameters / variables / information + +%% Default parameters +% - Default input parameters to use +if nargin < 6; solve_type = "lsqcurvefit"; end +if nargin < 5 + ibgrnd{1} = [... + mean(pesStr.xdat(:)) - abs(0.25*range(pesStr.xdat(:))),... + mean(pesStr.xdat(:)) + abs(0.25*range(pesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if nargin < 4; bTYPE = "Poly"; end +if isempty(solve_type); solve_type = "lsqcurvefit"; end +if isempty(ibgrnd) + ibgrnd{1} = [... + mean(pesStr.xdat(:)) - abs(0.25*range(pesStr.xdat(:))),... + mean(pesStr.xdat(:)) + abs(0.25*range(pesStr.xdat(:))),... + 0]; + ibgrnd{2} = [0, 0, -abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{3} = [0, 0, +abs(0.05*range(pesStr.ydat(:)))]; + ibgrnd{4} = {1}; +end +if isempty(bTYPE); bTYPE = "Poly"; end + +%% - 1 - CONSTRAINING THE FIT PARAMETERS TO PHYSICAL VALUES +% -- Total number of states to be fitted +nSTATES = length(cTYPE); +% -- Defining the initial conditions and limits of the optimisation method +x0 = [iparams{1}(:); ibgrnd{1}(:)]; +lb = [iparams{2}(:); ibgrnd{2}(:)]; +ub = [iparams{3}(:); ibgrnd{3}(:)]; +% -- Defining the initial conditions and limits of the optimisation method +for i = 1:nSTATES + indx = i:nSTATES:length(x0)-3; + X0 = x0(indx); LB = lb(indx); UB = ub(indx); + % --- parameters + if X0(2) < 0; x0(indx(2)) = 0; end % if INT < 0, then make it 0 + if X0(3) < 0; x0(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if X0(4) < 0; x0(indx(4)) = 0; end % if MR < 0, then make it 0 + if X0(4) > 1; x0(indx(4)) = 1; end % if MR > 1, then make it 1 + if X0(6) < 0; x0(indx(6)) = 0; end % if LSI < 0, then make it 0 + if X0(7) < 0; x0(indx(7)) = 0; end % if LSW < 0, then make it 0 + if X0(8) < 0; x0(indx(8)) = 0; end % if ASY < 0, then make it 0 + % --- lower bounds + if LB(2) < 0; lb(indx(2)) = 0; end % if INT < 0, then make it 0 + if LB(3) < 0; lb(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if LB(4) < 0; lb(indx(4)) = 0; end % if MR < 0, then make it 0 + if LB(4) > 1; lb(indx(4)) = 1; end % if MR > 1, then make it 1 + if LB(6) < 0; lb(indx(6)) = 0; end % if LSI < 0, then make it 0 + if LB(7) < 0; lb(indx(7)) = 0; end % if LSW < 0, then make it 0 + if LB(8) < 0; lb(indx(8)) = 0; end % if ASY < 0, then make it 0 + % --- lower bounds + if UB(2) < 0; ub(indx(2)) = 0; end % if INT < 0, then make it 0 + if UB(3) < 0; ub(indx(3)) = 0; end % if FWHM < 0, then make it 0 + if UB(4) < 0; ub(indx(4)) = 0; end % if MR < 0, then make it 0 + if UB(4) > 1; ub(indx(4)) = 1; end % if MR > 1, then make it 1 + if UB(6) < 0; ub(indx(6)) = 0; end % if LSI < 0, then make it 0 + if UB(7) < 0; ub(indx(7)) = 0; end % if LSW < 0, then make it 0 + if UB(8) < 0; ub(indx(8)) = 0; end % if ASY < 0, then make it 0 + % --- ensuring the fit window is within the domain + if x0(end-2) < min(pesStr.xdat(:)); x0(end-2) = min(pesStr.xdat(:)); end + if x0(end-1) > max(pesStr.xdat(:)); x0(end-1) = max(pesStr.xdat(:)); end +end +% -- Determining the degrees of freedom for the fitting model +val = lb + (ub-lb); DoF = 0; +for i = 1:length(val); if val(i) ~= lb(i); DoF = DoF + 1; end; end + +%% - 2 - DEFINING THE XPS DATA AND FITTING ARGUMENTS +% -- Extracting the data to be fitted +[roi_xdat, roi_ydat, roi_bgrnd] = PESBackground(pesStr.xdat, pesStr.ydat, bTYPE, x0(end-2), x0(end-1), x0(end)); +% -- Defining a structure that stores all relevant model and data variables +XPSObj = pesStr; +XPSObj.roi_xdat = roi_xdat; +XPSObj.roi_ydat = roi_ydat; +XPSObj.roi_bgrnd = roi_bgrnd; +XPSObj.roi_ydat_sbtr = XPSObj.roi_ydat - XPSObj.roi_bgrnd; +% -- Appending the input arguments to the global variable +XPSObj.fit_args.solve_type = solve_type; +XPSObj.fit_args.nSTATES = length(cTYPE); +XPSObj.fit_args.cTYPE = cTYPE; +XPSObj.fit_args.iparams = iparams; +XPSObj.fit_args.bTYPE = bTYPE; +XPSObj.fit_args.ibgrnd = ibgrnd; +XPSObj.fit_args.MFP = MFP; +XPSObj.fit_args.ZPOT = ZPOT; +XPSObj.fit_args.EPOT = EPOT; + +%% - 3 - RUNNING THE SOLVER +% -- Local solver properties +MaxFunEvals = 1e5; +MaxIter = 5e3; +FuncTol = 1e-7; % 1e-7; +StepTol = 1e-7; % 1e-7; +OptTol = 1e-7; % 1e-7; +ConTol = 1e-7; % 1e-7; +FinDiffRelStep = 1e-5; % 1e-5; +% -- Simulated annealing properties +TempFcn = 'temperaturefast'; +InitTemp = 1e2; +ReannealInt = 1e2; +%% - 3.1 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR CURVE FITTING +if solve_type == "lsqcurvefit" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqcurvefit,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqcurvefit(@(x,roi_xdat) full_pes_function(x,roi_xdat,XPSObj), x0, roi_xdat, roi_ydat, lb, ub, options); +%% - 3.2 - LOCAL SOLVER: UNBOUNDED LEAST SQUARES NONLINEAR REGRESSION FIT +elseif solve_type == "nlinfit" + % -- Defining the optimisation options for the simulated annealing method + options = statset(... + 'MaxFunEvals', MaxFunEvals,... + 'MaxIter', MaxIter,... + 'TolFun', FuncTol); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,R,J,CovB,MSE,ErrorModelInfo] = nlinfit(roi_xdat, roi_ydat, @(x,roi_xdat) full_pes_function(x,roi_xdat,XPSObj), x0, options); +%% - 3.3 - LOCAL SOLVER: FIND MINIMUM OF UNBOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fminunc" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fminunc',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,grad,hessian] = fminunc(@(x) minimize_function(x,XPSObj), x0, options); +%% - 3.4 - LOCAL SOLVER: FIND MINIMUM OF BOUNDED MULTIVARIATE FUNCTION +elseif solve_type == "fmincon" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter,... + 'ConstraintTolerance', ConTol,... + 'FinDiffRelStep', FinDiffRelStep,... + 'FinDiffType', 'central'); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,fval,exitflag,output,lambda,grad,hessian] = fmincon(@(x) minimize_function(x,XPSObj), x0, [], [], [], [], lb, ub, [], options); +%% - 3.5 - LOCAL SOLVER: BOUNDED LEAST SQUARES FITTING METHOD FOR NON-LINEAR LEAST SQUARES PROBLEMS +elseif solve_type == "lsqnonlin" + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@lsqnonlin,... + 'Algorithm', 'levenberg-marquardt',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'FunctionTolerance', FuncTol,... + 'StepTolerance', StepTol,... + 'OptimalityTolerance', OptTol,... + 'MaxIterations', MaxIter); + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + [params,rnorm,resid,exitflag,output,lambda,jacobian] = lsqnonlin(@(x) minimize_function(x,XPSObj), x0, lb, ub, options); +%% - 3.6 - GLOBAL SOLVER: BOUNDED SIMULATED ANNEALING TO MINIMISE RESIDUALS +elseif solve_type == "simulannealbnd" + % -- Defining the optimisation options for the hybrid minimisation that takes place after convergence + hybridopts = optimoptions('fmincon',... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'OptimalityTolerance', OptTol,... + 'StepTolerance', StepTol,... + 'ConstraintTolerance', ConTol); + % -- Defining the optimisation options for the simulated annealing method + options = optimoptions(@simulannealbnd,... + 'TemperatureFcn', TempFcn,... + 'InitialTemperature', InitTemp,... + 'ReannealInterval', ReannealInt,... + 'MaxFunctionEvaluations', MaxFunEvals,... + 'MaxIterations', MaxIter,... + 'TolFun', FuncTol,... + 'FunctionTolerance', FuncTol,... + 'HybridFcn' , {'fmincon' , hybridopts}); + % to view annealing, add: + % 'PlotFcn',{@saplotbestf,@saplottemperature,@saplotf,@saplotstopping}, 'MaxIterations', 50, + % -- Run the simulated annealing method + % --- (1) Initially optimise all parameters + [params,fval,exitflag,output] = simulannealbnd(@(x) minimize_function(x,XPSObj), x0, lb, ub, options); +end + +%% - 4 - STORING THE FITS AS A MATLAB STRUCTURE +fitStr = struct(); +%% 4.1 - Storing the initial arguments +fitStr.solve_type = solve_type; +fitStr.cTYPE = cTYPE; +fitStr.iparams = iparams; +fitStr.bTYPE = bTYPE; +fitStr.ibgrnd = ibgrnd; +fitStr.nSTATES = length(cTYPE); +%% 4.2 - Storing the XPS data, background, model and minimisation variables +% -- Extracting the original data +fitStr.xdat = pesStr.xdat; +fitStr.ydat = pesStr.ydat; +% -- Extracting the X-DOMAIN and DATA +[fitStr.X, fitStr.D] = fit_data(params, XPSObj); +% -- Extracting the MODEL +fitStr.M = fit_model(params, XPSObj); +% -- Extracting the BACKGROUND +fitStr.B = fit_background(params, XPSObj); +% -- Extracting the DATA - BACKGROUND +fitStr.DB = fitStr.D - fitStr.B; +fitStr.MB = fitStr.M + fitStr.B; +% -- Extracting the RESIDUALS (R = D - (M + B)) +fitStr.R = fitStr.D - (fitStr.M + fitStr.B); +% -- Extracting the CHI-SQUARED value to be minimised +fitStr.CHISQ = sum(fitStr.R.^2 ./ abs(fitStr.M + fitStr.B)); +fitStr.MINFUN = minimize_function(params, XPSObj); +% -- Append the degrees of freedom +fitStr.DoF = DoF; +%% 4.3 - Storing the final fit variables for the PES background +fitStr.bPARAMS = params(end-2:end); +fitStr.LHS = fitStr.bPARAMS(1); +fitStr.RHS = fitStr.bPARAMS(2); +fitStr.BGR = fitStr.bPARAMS(3); +%% 4.4 - Storing the final fit variables of each PES curve component +fitStr.XX = linspace(min(fitStr.X(:)), max(fitStr.X(:)), 1e3)'; +fitStr.YY = zeros(size(fitStr.XX)); +for i = 1:fitStr.nSTATES + % --- Best fit components on new domain + fitStr.cPARAMS(i,:) = params(i:fitStr.nSTATES:end-3); + [fitStr.cYY(:,i), fitStr.potYY(:,:,i)] = PESCurve_POT(fitStr.XX, fitStr.cTYPE(i),... + fitStr.cPARAMS(i,1), fitStr.cPARAMS(i,2), fitStr.cPARAMS(i,3),... + fitStr.cPARAMS(i,4), fitStr.cPARAMS(i,5), fitStr.cPARAMS(i,6),... + fitStr.cPARAMS(i,7), fitStr.cPARAMS(i,8),... + XPSObj.fit_args.MFP, XPSObj.fit_args.ZPOT, XPSObj.fit_args.EPOT); + fitStr.YY = fitStr.YY + fitStr.cYY(:,i); + % --- Storing each curve parameter + fitStr.DCL(i) = fitStr.cPARAMS(i,1); + fitStr.INT(i) = fitStr.cPARAMS(i,2); + fitStr.FWHM(i) = fitStr.cPARAMS(i,3); + fitStr.MR(i) = fitStr.cPARAMS(i,4); + fitStr.LSE(i) = fitStr.cPARAMS(i,5); + fitStr.LSI(i) = fitStr.cPARAMS(i,6); + fitStr.LSW(i) = fitStr.cPARAMS(i,7); + fitStr.ASY(i) = fitStr.cPARAMS(i,8); + % --- Storing energy information + fitStr.BE_Z0(i) = fitStr.DCL(i)+EPOT(1); + [~,I] = max(fitStr.cYY(:,i)); fitStr.BE_MAX(i)= fitStr.XX(I); + % --- Storing the curve area information + fitStr.AREA(i) = trapz(fitStr.XX, fitStr.cYY(:,i)); +end +% --- Storing the normalised area contribution for quantification +fitStr.AREA0 = fitStr.AREA ./ trapz(fitStr.XX, fitStr.YY); +% - Extracting the total potential profile of all components +fitStr.potYY_tot = sum(fitStr.potYY, 3); +fitStr.potYY_comp = squeeze(sum(fitStr.potYY, 2)); +for i = 1:nSTATES + fitStr.potYY_comp(:,i) = fitStr.INT(i) .* (fitStr.potYY_comp(:,i) ./ max(fitStr.potYY_comp(:,i))); +end + +%% 4.5 - Storing the potential profile information +fitStr.BOFF = -1*EPOT(1); +fitStr.MFP = MFP; +fitStr.ZPOT = ZPOT; +fitStr.EPOT = EPOT; + +end + +%% DEFINING THE RESIDUAL MINIMISATION FUNCTION TO BE MINIMISED +function MINFUN = minimize_function(x, XPSObj) + % - 1 - Extracting the DATA + [~, D] = fit_data(x, XPSObj); + % - 2 - Extracting the MODEL + M = fit_model(x, XPSObj); + % - 3 - Extracting the BACKGROUND + B = fit_background(x, XPSObj); + % - 4 - Extracting the RESIDUALS (residuals = data - (model + background)) + R = D - (M + B); + % - 5 - Extracting the CHI-SQUARED value to be minimised + MINFUN = sum(R.^2 ./ abs(M + B)); +end + +%% DEFINING THE FUNCTION THAT EXTRACTS THE XPS DATA TO BE FITTED +function [X, D] = fit_data(x, XPSObj) + [X, D, ~] = PESBackground(XPSObj.xdat, XPSObj.ydat, XPSObj.fit_args.bTYPE, x(end-2), x(end-1), x(end)); + D(isnan(D)) = 0; + if size(D, 2) > 1; D = D'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES BACKGROUND +function B = fit_background(x, XPSObj) + [~, ~, B] = PESBackground(XPSObj.xdat, XPSObj.ydat, XPSObj.fit_args.bTYPE, x(end-2), x(end-1), x(end)); + B(isnan(B)) = 0; + if size(B, 2) > 1; B = B'; end +end + +%% DEFINING THE FUNCTION THAT DETERMINES THE TOTAL PES CURVE FIT +function M = fit_model(x, XPSObj) + % - 1 - Extract the curve component for each state + comp_int = {}; + for i = 1:XPSObj.fit_args.nSTATES + % -- Extracting the arguments for the component curve + pes_args = x(i:XPSObj.fit_args.nSTATES:end-3); + % -- Extracting the component intensities + comp_int{i} = PESCurve_POT(XPSObj.roi_xdat, XPSObj.fit_args.cTYPE(i),... + pes_args(1), pes_args(2), pes_args(3),... + pes_args(4), pes_args(5), pes_args(6),... + pes_args(7), pes_args(8),... + XPSObj.fit_args.MFP, XPSObj.fit_args.ZPOT, XPSObj.fit_args.EPOT); + end + % - 2 - Sum up all of the curve components to get the final model PES curve + pes_int = zeros(size(XPSObj.roi_xdat)); + for i = 1:XPSObj.fit_args.nSTATES + pes_int = pes_int + comp_int{i}; + end + M = pes_int; + M(isnan(M)) = 0; + if size(M, 2) > 1; M = M'; end +end + +%% DEFINING THE FINAL FUNCTION THAT DESCRIBES THE PES CURVE TO BE FITTED +function MB = full_pes_function(x, xdat, XPSObj) + % - 1 - Extract the curve component for each state + comp_int = {}; + for i = 1:XPSObj.fit_args.nSTATES + % -- Extracting the arguments for the component curve + pes_args = x(i:XPSObj.fit_args.nSTATES:end-3); + % -- Extracting the component intensities + comp_int{i} = PESCurve_POT(xdat, XPSObj.fit_args.cTYPE(i),... + pes_args(1), pes_args(2), pes_args(3),... + pes_args(4), pes_args(5), pes_args(6),... + pes_args(7), pes_args(8),... + XPSObj.fit_args.MFP, XPSObj.fit_args.ZPOT, XPSObj.fit_args.EPOT); + end + % - 2 - Sum up all of the curve components to get the final model PES curve + pes_int = zeros(size(xdat)); + for i = 1:XPSObj.fit_args.nSTATES + pes_int = pes_int + comp_int{i}; + end + M = pes_int; + % - 3 - Determine the background to be used + [B_xdat, ~, B] = PESBackground(xdat, XPSObj.roi_ydat, XPSObj.fit_args.bTYPE, x(end-2), x(end-1), x(end)); + B = interp1(B_xdat, B, xdat); + % - 4 - Final output is the sum of the model and background + MB = M + B; + MB(isnan(MB)) = 0; if size(MB, 2) > 1; MB = MB'; end +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2pot fitting/pes2pot_view_fit.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2pot fitting/pes2pot_view_fit.m new file mode 100644 index 0000000..90c93b4 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2pot fitting/pes2pot_view_fit.m @@ -0,0 +1,143 @@ +function fig = pes2pot_view_fit(fitStr) +% fig = pes2pot_view_fit(fitStr) +% This function is used to plot the final PES curve model AFTER curve +% fitting with the 'pes2pot_solver()'. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - fitStr: data structure that contains the PES fitting output of the corresponding solver. +% +% OUT: +% - fig: MATLAB figure object that summarises the fit. + +%% - 1 - Plotting the model to be used for fitting +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'PES Curve Fitting'); +fig.Position(1) = 100; +fig.Position(2) = 100; +fig.Position(3) = 2.5*pp.fig5x4(1); +fig.Position(4) = 2.5*pp.fig5x4(2); + +%% - 2.1 - PLOTTING THE RAW DATA AND BEST FIT BACKGROUND +subplot(221); hold on; +% -- Plotting the ROI, LHS and RHS analysis windows +ROI = [fitStr.X(1), fitStr.X(end)]; +LHS = ROI(1) + 0.05.*[-1,1].*range(fitStr.xdat(:)); +RHS = ROI(2) + 0.05.*[-1,1].*range(fitStr.xdat(:)); +hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e6, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); +hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting a vertical line to show the ROI +a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +a.Annotation.LegendInformation.IconDisplayStyle = 'off'; +b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting the 1D data +plot(fitStr.xdat, fitStr.ydat, 'b-', 'linewidth', 0.5); +plot(fitStr.X, fitStr.D, 'b-', 'linewidth', 2); +plot(fitStr.X, fitStr.B, 'r-', 'linewidth', 2); +plot(fitStr.X, fitStr.DB, 'k-', 'linewidth', 2); +gca_props(); title('Background Subtraction', 'interpreter', 'none', 'fontsize', 9); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); +% -- Determining the best limits for the plot +axLim_y = [fitStr.ydat; fitStr.DB]; +axis([min(fitStr.xdat(:)), max(fitStr.xdat(:)), min(axLim_y(:)), 1.1*max(axLim_y(:))]); + +%% - 2.2 - PLOTTING THE BEST FIT CURVE COMPONENTS AND FINAL MODEL FIT +subplot(8,2,[2,4,6]); hold on; +% -- Plotting all of the curve components +for i = 1:fitStr.nSTATES + area(fitStr.XX, fitStr.cYY(:,i), 'FaceColor', pp.col.fit{i}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); + plot(fitStr.XX, fitStr.cYY(:,i), 'k-', 'linewidth', 0.25); +end +% -- Plotting the curve component energy locations +for i = 1:fitStr.nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + % --- Plotting DCL + line([1,1]*fitStr.DCL(i), [0, max(fitStr.cYY(:,i))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '-'); + % --- Plotting BE_Z0 + line([1,1]*fitStr.BE_Z0(i), [0, max(fitStr.cYY(:,i))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', ':'); +end +% -- Plotting the experimental and fit spectra +plot(fitStr.X, fitStr.DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(fitStr.X, fitStr.M, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(fitStr.CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +axis([min(fitStr.X(:)), max(fitStr.X(:)), min(fitStr.DB(:)), 1.10*max(fitStr.DB(:))]); +title("Initial Model for Fitting", 'interpreter', 'none', 'fontsize', 9); + +%% - 2.3 - PLOTTING THE RESIDUALS FOR THE BEST FIT TO THE DATA +subplot(8,2,8); hold on; +bar(fitStr.X, fitStr.R, 'facecolor', [0 0 0]); +gca_props(); grid on; +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + +%% - 3 - PLOTTING THE POTENTIAL WELL, MODULATED BY THE MFP +subplot(223); hold on; +% --- Image of the curve series shifted by potential and scaled by MFP +ImData(fitStr.ZPOT, fitStr.XX, fitStr.potYY_tot); +% -- Plotting the curve component energy locations +for i = 1:fitStr.nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + % --- Plotting DCL + line([0, max(fitStr.ZPOT(:))], [1,1]*fitStr.DCL(i), 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', '-'); + % --- Plotting BE_Z0 + line([0, max(fitStr.ZPOT(:))], [1,1]*fitStr.BE_Z0(i), 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', ':'); +end +% --- Plotting the potential energy curves +plot(fitStr.ZPOT, fitStr.EPOT+fitStr.DCL(1), 'r-', 'linewidth', 2); +% --- Formatting the figure +img_props(); colormap jet; title('Model Potential : V(z)', 'Interpreter','none'); +axis square; +xlabel('$$ \bf z (nm) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +axis([0, max(fitStr.ZPOT(:)), min(fitStr.XX(:)), max(fitStr.XX(:))]); +% --- Adding text to quantify the band offset +BOFF = round(fitStr.BOFF, 3); +text(0.04, 0.92, "$$ \phi_{z=0} = $$ " + string(BOFF), 'interpreter', 'latex', 'fontsize', 14, 'color', 'w', 'Units','normalized'); + +%% - 4 - PLOTTING ALL THE INDIVIDUAL CURVES, SHIFTED BY THE POTENTIAL FOR N=1 +subplot(224); hold on; +% --- Plotting individual curves +cols = flipud(jet(length(fitStr.ZPOT)+2)); +for i = 1:length(fitStr.ZPOT) + plot(fitStr.XX, fitStr.potYY(:,i,1), 'k-', 'color', cols(i,:), 'linewidth', 0.5); +end +% --- Plotting the final curve +plot(fitStr.XX, fitStr.potYY_comp(:,1), 'k-', 'linewidth', 2); +% --- Formatting the figure +gca_props(); title('Integrated Curves : n = 1', 'Interpreter','none'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); +axis([min(fitStr.XX(:)), max(fitStr.XX(:)), 0, 1.1*max(fitStr.M(:))]); +% -- Plotting the curve component energy locations +lWidth = pp.llwidth; +% --- Plotting DCL +line([1,1]*fitStr.DCL(1), [0, max(fitStr.cYY(:,1))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '-'); +% --- Plotting BE_Z0 +line([1,1]*fitStr.BE_Z0(1), [0, max(fitStr.cYY(:,1))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', ':'); +% --- Plotting BE_MAX +[~,I] = max(fitStr.potYY_comp(:,1)); BE_MAX = fitStr.XX(I); +line([BE_MAX, BE_MAX], [0, max(fitStr.cYY(:,1))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '--'); +% --- Adding text to quantify all the shifts +DCL = round(fitStr.DCL(1), 3); +BE_Z0 = round(fitStr.BE_Z0(1), 3); +BE_MAX = round(fitStr.BE_MAX(1), 3); +text(0.04, 0.92, "$$ \Delta_{CL} = $$ " + string(DCL), 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); +text(0.04, 0.86, "$$ BE_{z=0} = $$ " + string(BE_Z0), 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); +text(0.04, 0.80, "$$ BE_{MAX} = $$ " + string(BE_MAX), 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2pot fitting/pes2pot_view_init.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2pot fitting/pes2pot_view_init.m new file mode 100644 index 0000000..5cd5b53 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F022 - pes data fitting/pes2pot fitting/pes2pot_view_init.m @@ -0,0 +1,226 @@ +function fig = pes2pot_view_init(pesStr, cTYPE, iparams, bTYPE, ibgrnd, MFP, ZPOT, EPOT) +% fig = pes2pot_view_init(pesStr, cTYPE, iparams, bTYPE, ibgrnd, MFP, ZPOT, EPOT) +% This function is used to plot the initial, model XPS curve PRIOR to +% curve fitting with 'pes2pot_solver()'. The plot consists of 3 subplots; (1) The +% background that is determined from the fit; (2) A plot showing all of +% the fitted curve components, as well as the final model fit and +% experimental data; (3) A plot of the residuals, showing the quality of +% the experimental and model fit. This is used as an informative plot +% that allows you to view and create a better initial guess of the XPS +% model prior to running the fitting algorithm. +% +% REQ. FUNCTIONS: (none) +% +% IN: +% - pesStr: data structure that contains the PES data. +% - cTYPE: 1xN vector of the type of curve to use for the nth state. +% - iparams: 3 cells {x0}{lb}{ub} with Nx8 arrays: the n'th peak parameters [BE,INT,FWHM,MR,LSE,LSI,LSW,ASY] +% - bTYPE: string of the type of background to use for fitting. Default: "Poly" ("none", "Poly", "Shir", "LinShir", "StepFDDGpL", "StepFDDGsL") +% - ibgrnd: 4 cells {x0}{lb}{ub}{args} with 1x3 vectors of the background parameters: x0=lb=ub=[LHS,RHS,BGR], or argument of the background type args = [] +% - MFP: mean free path that will modulate the potential (nm). +% - ZPOT: 1xN vector of the z-axis of the potential (depth). +% - EPOT: 1xN vector of the energy-axis of the potential. +% +% OUT: +% - fig: MATLAB figure object with the ARPES data plotted. + +%% - 1 - Extracting all background subtraction data and information +% -- Extracting the background +[X, D, B] = PESBackground(pesStr.xdat, pesStr.ydat,... + bTYPE, ibgrnd{1}(1), ibgrnd{1}(2), ibgrnd{1}(3), ibgrnd{4}); + +%% - 2 - Extracting all model data and information +% -- Extracting the original XPS data +% xdat = linspace(min(pesStr.xdat(:)), max(pesStr.xdat(:)), 1e3); +% ydat = interp1(pesStr.xdat, pesStr.ydat, xdat); +xdat = pesStr.xdat; +ydat = pesStr.ydat; +% -- Extracting the total number of states to be fitted +nSTATES = length(cTYPE); +BOFF = -1*EPOT(1); +% -- Initialising the vectors to contain XPS data +DB = D - B; % Data after being background subtracted +M = zeros(size(X)); % Initialising model data +% -- Filing through all curve components and extracting them seperately +cYY = []; potYY = []; +for i = 1:nSTATES + % --- Extracting curve profiles + [cYY(:,i), potYY(:,:,i)] = PESCurve_POT(X, cTYPE(i),... + iparams{1}(i,1), iparams{1}(i,2), iparams{1}(i,3),... + iparams{1}(i,4), iparams{1}(i,5), iparams{1}(i,6),... + iparams{1}(i,7), iparams{1}(i,8), MFP, ZPOT, EPOT); + M = M + cYY(:,i); + % --- Storing each curve parameter + DCL(i) = iparams{1}(i,1); + INT(i) = iparams{1}(i,2); + FWHM(i) = iparams{1}(i,3); + MR(i) = iparams{1}(i,4); + LSE(i) = iparams{1}(i,5); + LSI(i) = iparams{1}(i,6); + LSW(i) = iparams{1}(i,7); + ASY(i) = iparams{1}(i,8); + % --- Storing additional parameters + BE_Z0(i) = DCL(i) + EPOT(1); + [~,I] = max(cYY(:,i)); BE_MAX(i)= X(I); +end +% - Extracting the total potential profile of all components +potYY_tot = sum(potYY, 3); +potYY_comp = squeeze(sum(potYY, 2)); +for i = 1:nSTATES + potYY_comp(:,i) = INT(i) .* (potYY_comp(:,i) ./ max(potYY_comp(:,i))); +end + +%% - 3 - Determination of the residuals and chi-squared +R = M - (D - B); % Residuals +CHISQ = sum(R.^2 ./ abs(M+B)); % Chi-squared + +%% - 4 - Plotting the model to be used for fitting +% -- Initialising the plot properties +pp = plot_props(); +% -- Initialising the figure +fig = figure(); set(fig, 'Name', 'XPS Curve Fitting'); +fig.Position(1) = 100; +fig.Position(2) = 100; +fig.Position(3) = 2.5*pp.fig5x4(1); +fig.Position(4) = 2.5*pp.fig5x4(2); + +%% - 4.1 - PLOTTING THE RAW DATA AND BEST FIT BACKGROUND +subplot(221); hold on; +% -- Plotting the ROI, LHS and RHS analysis windows +ROI = [X(1), X(end)]; +LHS = ROI(1) + 0.05.*[-1,1].*range(xdat(:)); +RHS = ROI(2) + 0.05.*[-1,1].*range(xdat(:)); +hLHS = patch([LHS(1), LHS(1), LHS(2), LHS(2), LHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hLHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hRHS = patch([RHS(1), RHS(1), RHS(2), RHS(2), RHS(1)], [-1, 1, 1, -1, -1].*1e6, [0.6 0.6 0.2], 'facealpha', 0.4, 'edgecolor', 'none'); +hRHS.Annotation.LegendInformation.IconDisplayStyle = 'off'; +hMID = patch([ROI(1), ROI(1), ROI(2), ROI(2), ROI(1)], [-1, 1, 1, -1, -1].*1e6, [0.8 0.9 0.8], 'facealpha', 0.5, 'edgecolor', 'none'); +hMID.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting a vertical line to show the ROI +a = line([ROI(1) ROI(1)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +a.Annotation.LegendInformation.IconDisplayStyle = 'off'; +b = line([ROI(2) ROI(2)], [-1e5, 1e5], 'Color', [0 0 0], 'LineWidth', 1, 'Linestyle', '-'); +b.Annotation.LegendInformation.IconDisplayStyle = 'off'; +% -- Plotting the 1D data +plot(xdat, ydat, 'b-', 'linewidth', 0.5); +plot(X, D, 'b-', 'linewidth', 2); +plot(X, B, 'r-', 'linewidth', 2); +plot(X, DB, 'k-', 'linewidth', 2); +gca_props(); title('Background Subtraction', 'interpreter', 'none', 'fontsize', 9); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +legend({'Initial Data', 'ROI: Data', 'ROI: Background', 'ROI: Final'}, 'location', 'best', 'fontsize', 9); +% -- Determining the best limits for the plot +axLim_y = [ydat; DB]; +axis([min(xdat(:)), max(xdat(:)), min(axLim_y(:)), 1.1*max(axLim_y(:))]); + +%% - 4.2 - PLOTTING THE BEST FIT CURVE COMPONENTS AND FINAL MODEL FIT +subplot(8,2,[2,4,6]); hold on; +% -- Plotting all of the curve components +for i = 1:nSTATES + area(X, cYY(:,i), 'FaceColor', pp.col.fit{i}, 'FaceAlpha', pp.falpha, 'EdgeAlpha', 0); + plot(X, cYY(:,i), 'k-', 'linewidth', 0.25); +end +% -- Plotting the curve component energy locations +for i = 1:nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + % --- Plotting DCL + line([1, 1]*DCL(i), [0, max(cYY(:,i))], 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', '-'); + % --- Plotting BE + line([1, 1]*DCL(i)+EPOT(1), [0, max(cYY(:,i))], 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', ':'); +end +% -- Plotting the experimental and fit spectra +plot(X, DB, 'k-', 'color', pp.col.dat{1}, 'linewidth', 2*pp.llwidth); +plot(X, M, 'k-', 'Color', pp.col.dat{2}, 'linewidth', 2*pp.lwidth); +% -- Add annotation for the quality of fit +text(0.04, 0.90, "$$ \chi^2 = $$ " + string(CHISQ),... + 'interpreter', 'latex', 'fontsize', 14, 'color', 'k', 'Units','normalized'); +% - Formatting the figure +gca_props(); grid on; +ylabel('$$ \bf Intensity$$', 'Interpreter', 'latex'); +axis([min(X(:)), max(X(:)), min(DB(:)), 1.10*max(DB(:))]); +title("Initial Model for Fitting", 'interpreter', 'none', 'fontsize', 9); + +%% - 4.3 - PLOTTING THE RESIDUALS FOR THE BEST FIT TO THE DATA +subplot(8,2,8); hold on; +bar(X, R, 'facecolor', [0 0 0]); +gca_props(); grid on; +ylabel('$$ \bf Resid. $$', 'Interpreter', 'latex'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); + +%% - 5 - Plotting the uncertainties to allow for easier optimisation +subplot(8,2,[2,4,6]); hold on; +for i = 1:nSTATES + %% - 5.1 - Plotting the primary peak uncertainties + lbBE = iparams{2}(i,1); ubBE = iparams{3}(i,1); + lbINT = iparams{2}(i,2); ubINT = iparams{3}(i,2); + x_vals = [lbBE, lbBE, ubBE, ubBE, lbBE]; + y_vals = [lbINT, ubINT, ubINT, lbINT, lbINT]; + patch(x_vals, y_vals, pp.col.fit{i}, 'FaceAlpha', 0.65, 'EdgeAlpha', 0); + %% - 5.2 - Adding text to identify each peak index + text(max(x_vals), max(y_vals), string(i), 'interpreter', 'latex', 'fontsize', 14, 'color', 'k'); + %% - 5.3 - Plotting the spin-orbit split (SOS) peak uncertainties + DCL_mu = DCL(i); + lbLSE = iparams{2}(i,5); ubLSE = iparams{3}(i,5); + lbLSI = iparams{2}(i,6); ubLSI = iparams{3}(i,6); + x_vals = DCL_mu + [lbLSE, lbLSE, ubLSE, ubLSE, lbLSE]; + y_vals = [lbINT*lbLSI, ubINT*ubLSI, ubINT*ubLSI, lbINT*lbLSI, lbINT*lbLSI]; + patch(x_vals, y_vals, pp.col.fit{i}, 'FaceAlpha', 0.65, 'EdgeAlpha', 0); +end + +%% - 6 - PLOTTING THE POTENTIAL WELL, MODULATED BY THE MFP +subplot(223); hold on; +% --- Image of the curve series shifted by potential and scaled by MFP +ImData(ZPOT, X, potYY_tot); +% -- Plotting the curve component energy locations +for i = 1:nSTATES + if i == 1; lWidth = pp.llwidth; else; lWidth = pp.lwidth; end + % --- Plotting DCL + line([0, max(ZPOT(:))], [DCL(i), DCL(i)], 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', '-'); + % --- Plotting BE + line([0, max(ZPOT(:))], [DCL(i), DCL(i)]+ EPOT(1), 'Color', pp.col.fit{i}, 'LineWidth', lWidth, 'Linestyle', ':'); +end +% --- Plotting the potential energy curves +plot(ZPOT, EPOT+DCL(1), 'r-', 'linewidth', 2); +% --- Formatting the figure +img_props(); colormap jet; title('Model Potential : V(z)', 'Interpreter','none'); +axis square; +xlabel('$$ \bf z (nm) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +axis([0, max(ZPOT(:)), min(X(:)), max(X(:))]); +% --- Adding text to quantify the band offset +BOFF = round(BOFF, 3); +text(0.04, 0.92, "$$ \phi_{z=0} = $$ " + string(BOFF), 'interpreter', 'latex', 'fontsize', 14, 'color', 'w', 'Units','normalized'); + +%% - 7 - PLOTTING ALL THE INDIVIDUAL CURVES, SHIFTED BY THE POTENTIAL FOR N=1 +subplot(224); hold on; +% --- Plotting individual curves +cols = flipud(jet(length(ZPOT)+2)); +for i = 1:length(ZPOT) + plot(X, potYY(:,i,1), 'k-', 'color', cols(i,:), 'linewidth', 0.5); +end +% --- Plotting the final curve +plot(X, potYY_comp(:,1), 'k-', 'linewidth', 2); +% --- Formatting the figure +gca_props(); title('Integrated Curves : n = 1', 'Interpreter','none'); +xlabel('$$ \bf E_B - E_F (eV) $$', 'Interpreter', 'latex'); +ylabel('$$ \bf Intensity $$', 'Interpreter', 'latex'); +axis([min(X(:)), max(X(:)), 0, 1.1*max(M(:))]); +% -- Plotting the curve component energy locations +lWidth = pp.llwidth; +% --- Plotting DCL +line([1, 1]*DCL(1), [0, max(cYY(:,1))], 'Color', pp.col.fit{1}, 'LineWidth', lWidth, 'Linestyle', '-'); +% --- Plotting BE +line([1, 1]*DCL(1)+EPOT(1), [0, max(cYY(:,1))], 'Color', pp.col.fit{1}, 'LineWidth', lWidth, 'Linestyle', ':'); +% --- Plotting BE_MAX +[~,I] = max(potYY_comp(:,1)); BE_MAX = X(I); +line([BE_MAX, BE_MAX], [0, max(cYY(:,1))], 'Color', [0 0 0], 'LineWidth', lWidth, 'Linestyle', '--'); +% --- Adding text to quantify all the shifts +DCL = round(DCL(1), 3); +BE_Z0 = round(BE_Z0(1), 3); +BE_MAX = round(BE_MAX(1), 3); +text(0.04, 0.92, "$$ \Delta_{CL} = $$ " + string(DCL), 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); +text(0.04, 0.86, "$$ BE_{z=0} = $$ " + string(BE_Z0), 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); +text(0.04, 0.80, "$$ BE_{MAX} = $$ " + string(BE_MAX), 'interpreter', 'latex', 'fontsize', 13, 'color', 'k', 'Units','normalized'); + +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_cap.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_cap.m new file mode 100644 index 0000000..b623f4a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_cap.m @@ -0,0 +1,23 @@ +function capacitance = semi_eqn_cap(area, epsR, distance) +% capacitance = semi_eqn_cap(area, epsR, distance) +% Function that determines the capacitance of two parallel plates, with a +% dielectric material placed between them. The thickness and relative +% permittivity of the dieelctric can be defined by the user, as well as +% the cross sectional area of the capacitor plates. +% +% REQ. FUNCTIONS: +% - physics_constants(); +% +% IN: +% - capacitance: capacitance [Farads] +% +% OUT: +% - area: cross-sectional area between the capacitor plates [m^2] +% - epsR: relative permittivity of dielectric. +% - distance: distance between the plates of the capacitor [m]. + +%% Defining physical constants +pc = physics_constants(); +%% - 1 - Defining the capacitance equation +capacitance = pc.eps0*epsR*area/distance; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_cap2.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_cap2.m new file mode 100644 index 0000000..42349f7 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_cap2.m @@ -0,0 +1,25 @@ +function capacitance = semi_eqn_cap2(area, epsR_1, distance_1, epsR_2, distance_2) +% capacitance = semi_eqn_cap2(area, epsR_1, distance_1, epsR_2, distance_2) +% Function that determines the capacitance for two dielectric materials +% that are placed in series, between the capacitor plates. The user can +% define the relative perimittivity and thickness of each layer. The +% cross sectional area of the capacitor is constant for the two layers. +% +% REQ. FUNCTIONS: +% - physics_constants(); +% +% IN: +% - capacitance: capacitance [Farads] +% +% OUT: +% - area: cross-sectional area between the capacitor plates [m^2] +% - epsR_1: relative permittivity of dielectric layer 1. +% - distance_1: thickness of layer 1 between the capacitor plates [m]. +% - epsR_2: relative permittivity of dielectric layer 2. +% - distance_2: thickness of layer 2 between the capacitor plates [m]. + +%% Defining physical constants +pc = physics_constants(); +%% - 1 - Defining the capacitance equation +capacitance = ((epsR_1*epsR_2)/(epsR_1*distance_2+epsR_2*distance_1))*(pc.eps0*area); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_eb_calc.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_eb_calc.m new file mode 100644 index 0000000..c782a62 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_eb_calc.m @@ -0,0 +1,38 @@ +function eb = semi_eqn_eb_calc(k, k0, eb0, mstar) +% eb = eb_calc(k, k0, eb0, mstar) +% Function that evaluates the binding energy of a parabolic dispersion; +% k0, eb0 are the initial values at the base of the parabola and mstar +% defines the curvature of the parabolic disperison. +% +% REQ. FUNCTIONS: +% - physics_constants(); +% +% IN: +% - k: Nx1 vector that yields the wave-vector values [Ang^-1]. +% - k0: scalar of the initial wave-vector at eb = 0 eV [Ang^-1]. +% - eb0: scalar of the initial binding energy at k = 0 Ang^-1 [eV]. +% - mstar: scalar of the effective mass which defines the curvature of the parabola [mstar*me]. +% +% OUT: +% - eb: Nx1 vector that yields the binding energy values [eV]. + +%% Default parameters +if nargin < 4; mstar = 1; end +if nargin < 3; eb0 = 0; end +if nargin < 2; k0 = 0; end +if isempty(mstar); mstar = 1; end +if isempty(eb0); eb0 = 0; end +if isempty(k0); k0 = 0; end + +%% Defining physical constants +pc = physics_constants(); +%% - 1 - Determination of the output wave-vectors +% Ensuring eb is a column vector +if size(k, 2) > 1 && size(k, 1) == 1; k = k'; end +% Defining the physical constants +hbar = 4.135e-15; % Units of [eV s^−1] +% Calculating the binding energy values +eb = (3.8 / mstar) * (k - k0).^2 + eb0; +% If isnan, return zero +eb(isnan(eb)) = 0; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_leak.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_leak.m new file mode 100644 index 0000000..c3a058a --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/general equations/semi_eqn_leak.m @@ -0,0 +1,21 @@ +function current = semi_eqn_leak(voltage, area, distance, resistivity) +% current = semi_eqn_leak(voltage, area, distance, resistivity) +% Function that determines the leakage current between two parallel +% plates of a capacitor, through the intermediate dieelctric layer. +% +% REQ. FUNCTIONS: +% - physics_constants(); +% +% IN: +% - current: leakage current flowing through capacitor [A] +% +% OUT: +% - voltage: potential difference across the capacitor [V]. +% - area: cross-sectional area of the capacitor [m^2]. +% - distance: distance between the plates of the capacitor [m]. +% - resistivity: resistivity of the dielectric in the capacitor [Ohm m] +%% Defining physical constants +pc = physics_constants(); +%% - 1 - Defining the leakage current equation +current = voltage.*area./resistivity./distance; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/moscap model/moscap_characteristics.mlx b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/moscap model/moscap_characteristics.mlx new file mode 100644 index 0000000..12a46ee Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/moscap model/moscap_characteristics.mlx differ diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/moscap model/moscap_eqn_kf.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/moscap model/moscap_eqn_kf.m new file mode 100644 index 0000000..18b49f1 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/moscap model/moscap_eqn_kf.m @@ -0,0 +1,20 @@ +function kf = moscap_eqn_kf(ne, ni) +% kf = moscap_eqn_kf(ne, ni) +% +% REQ. FUNCTIONS: +% - physics_constants(); +% +% IN: +% - kf: Fermi wave-vector of the conduction electrons [Ang^-1] +% +% OUT: +% - ne: charge accumulated on the capacitor plates [cm^-2] +% - ni: initial charge on the capacitor plates [cm^-2] +%% Default parameters +if nargin < 2; ni = 0; end +if isempty(ni); ni = 0; end +%% Defining physical constants +pc = physics_constants(); +%% - 1 - Defining the Fermi wave-vector +kf = sqrt(2*pi*(ne + ni)*10000)*1e-10; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/moscap model/moscap_eqn_ne.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/moscap model/moscap_eqn_ne.m new file mode 100644 index 0000000..e5fb095 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/moscap model/moscap_eqn_ne.m @@ -0,0 +1,18 @@ +function ne = moscap_eqn_ne(voltage, epsR, distance) +% ne = moscap_eqn_ne(voltage, epsR, distance) +% +% REQ. FUNCTIONS: +% - physics_constants(); +% +% IN: +% - ne: charge accumulated on the capacitor plates [m^-2] +% +% OUT: +% - voltage: potential difference across the capacitor [V]. +% - epsR: relative permittivity of dielectric. +% - distance: distance between the plates of the capacitor [m]. +%% Defining physical constants +pc = physics_constants(); +%% - 1 - Defining the charge accumulation equation +ne = pc.eps0*epsR*voltage/distance/pc.e; +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_Ec02nd.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_Ec02nd.m new file mode 100644 index 0000000..5ab7b03 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_Ec02nd.m @@ -0,0 +1,32 @@ +function nd = semi_si_Ec02nd(Ec0) +% nd = semi_si_Ec02nd(Ec0) +% Function that determines the dopant concentration based on the CBM +% position relative to the Fermi-level. The data is taken from [1] using +% Phosphorous as the dopant. +% +% REFERENCE: +% [1] PV Lighthouse Solar Cell Simulator: https://www.pvlighthouse.com.au/bandgap +% +% +% REFERENCE: +% [1] PV Lighthouse Solar Cell Simulator: https://www.pvlighthouse.com.au/bandgap +% +% IN: +% - Ec0: N×1 column vector of CBM relative to EF [eV] +% +% OUT: +% - nd: N×1 column vector of the dopant concentration [cm-3] + +%% Default parameters +if nargin < 1; Ec0 = 0; end +if isempty(Ec0); Ec0 = 0; end +%% - 1 - Extracting the energy bands relative to EF vs dopant concentration +% - Importing the relevant data file +raw_dat = importdata('si_ebands_vs_nd.txt'); +nd_dat = raw_dat.data(:,1); % dopant concentration +Ec0_dat = raw_dat.data(:,2); % CBM energy (eV) +% - Linear interpolation of the data +nd_F = fit(Ec0_dat, nd_dat,'linearinterp'); +% - Extracting the dopant concentration +nd = nd_F(Ec0); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_Ev02nd.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_Ev02nd.m new file mode 100644 index 0000000..387063f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_Ev02nd.m @@ -0,0 +1,28 @@ +function nd = semi_si_Ev02nd(Ev0) +% nd = semi_si_Ev02nd(Ev0) +% Function that determines the dopant concentration based on the VBM +% position relative to the Fermi-level.The data is taken from [1] using +% Phosphorous as the dopant. +% +% REFERENCE: +% [1] PV Lighthouse Solar Cell Simulator: https://www.pvlighthouse.com.au/bandgap +% +% IN: +% - Ev0: N×1 column vector of VBM relative to EF [eV] +% +% OUT: +% - nd: N×1 column vector of the dopant concentration [cm-3] + +%% Default parameters +if nargin < 1; Ev0 = 0; end +if isempty(Ev0); Ev0 = 0; end +%% - 1 - Extracting the energy bands relative to EF vs dopant concentration +% - Importing the relevant data file +raw_dat = importdata('si_ebands_vs_nd.txt'); +nd_dat = raw_dat.data(:,1); % dopant concentration +Ec0_dat = raw_dat.data(:,2); % CBM energy (eV) +% - Linear interpolation of the data +nd_F = fit(Ec0_dat, nd_dat,'linearinterp'); +% - Extracting the dopant concentration +nd = nd_F(Ev0); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_nd2ebands.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_nd2ebands.m new file mode 100644 index 0000000..d9493cf --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_nd2ebands.m @@ -0,0 +1,34 @@ +function [Ec0, Ev0] = semi_si_nd2ebands(nd) +% [Ec0, Ev0] = semi_si_nd2ebands(nd) +% Function that determines the CBM / VBM energy for a given dopant +% concentration. The data is taken from [1] using Phosphorous as the +% dopant. The band gap narrowing has been implemented and the Fermi-level +% is located at 0 eV (i.e. the output values of the CBM / VBM are given +% relative to the Fermi-level). +% +% REFERENCE: +% [1] PV Lighthouse Solar Cell Simulator: https://www.pvlighthouse.com.au/bandgap +% +% IN: +% - nd: N×1 column vector of the dopant concentration [cm-3] +% +% OUT: +% - Ec0: N×1 column vector of CBM relative to EF [eV] +% - Ev0: N×1 column vector of VBM relative to EF [eV] + +%% Default parameters +if nargin < 1; nd = 0; end +if isempty(nd); nd = 0; end +%% - 1 - Extracting the energy bands relative to EF vs dopant concentration +% - Importing the relevant data file +raw_dat = importdata('si_ebands_vs_nd.txt'); +nd_dat = raw_dat.data(:,1); % dopant concentration +Ec0_dat = raw_dat.data(:,2); % CBM energy (eV) +Ev0_dat = raw_dat.data(:,2); % VBM energy (eV) +% - Linear interpolation of the data +Ec0_F = fit(nd_dat, Ec0_dat, 'linearinterp'); +Ev0_F = fit(nd_dat, Ev0_dat, 'linearinterp'); +% - Extracting the CBM and VBM values in eV +Ec0 = Ec0_F(nd); +Ev0 = Ev0_F(nd); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_nd2res.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_nd2res.m new file mode 100644 index 0000000..1591012 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_nd2res.m @@ -0,0 +1,28 @@ +function resistivity = semi_si_nd2res(nd) +% resistivity = semi_si_nd2res(nd) +% Function that determines the resistivity of a silicon sample, +% given dopant concentration only. The data is taken from [1] using +% Phosphorous as the dopant. +% +% REFERENCE: +% [1] PV Lighthouse Solar Cell Simulator: https://www.pvlighthouse.com.au/resistivity +% +% IN: +% - nd: N×1 column vector of the dopant concentration [cm-3]. +% +% OUT: +% - resistivity: N×1 column vector of the resistivity [Ohm cm]. + +%% Default parameters +if nargin < 1; nd = 1e10; end +if isempty(nd); nd = 1e10; end +%% - 1 - Extracting the energy bands relative to EF vs dopant concentration +% - Importing the relevant data file +raw_dat = importdata('si_nd_vs_res.txt'); +nd_dat = raw_dat.data(:,1); % dopant concentration +resistivity_dat = raw_dat.data(:,2); % resistivity +% - Linear interpolation of the data +resistivity_F = fit(nd_dat, resistivity_dat, 'linearinterp'); +% - Extracting the dopant concentration +resistivity = resistivity_F(nd); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_res2nd.m b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_res2nd.m new file mode 100644 index 0000000..97e463f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/semi_si_res2nd.m @@ -0,0 +1,28 @@ +function nd = semi_si_res2nd(resistivity) +% nd = semi_si_res2nd(resistivity) +% Function that determines the dopant concentration of a silicon sample, +% determined by the resistivity only. The data is taken from [1] using +% Phosphorous as the dopant. +% +% REFERENCE: +% [1] PV Lighthouse Solar Cell Simulator: https://www.pvlighthouse.com.au/resistivity +% +% IN: +% - resistivity: N×1 column vector of the resistivity [Ohm cm] +% +% OUT: +% - nd: N×1 column vector of the dopant concentration [cm-3] + +%% Default parameters +if nargin < 1; resistivity = 0; end +if isempty(resistivity); resistivity = 0; end +%% - 1 - Extracting the energy bands relative to EF vs dopant concentration +% - Importing the relevant data file +raw_dat = importdata('si_nd_vs_res.txt'); +nd_dat = raw_dat.data(:,1); % dopant concentration +resistivity_dat = raw_dat.data(:,2); % resistivity +% - Linear interpolation of the data +nd_F = fit(resistivity_dat, nd_dat,'linearinterp'); +% - Extracting the dopant concentration +nd = nd_F(resistivity); +end \ No newline at end of file diff --git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/si_ebands_vs_nd.txt b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/si_ebands_vs_nd.txt new file mode 100644 index 0000000..af57905 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/si_ebands_vs_nd.txt @@ -0,0 +1,503 @@ +Ï (cmâ»Â³) Ec0 (eV) Ev0 (eV) +0.000000E+00 5.640830E-01 -5.662280E-01 +1.000000E+12 4.441176E-01 -6.861484E-01 +1.037528E+12 4.431653E-01 -6.870998E-01 +1.076465E+12 4.422131E-01 -6.880512E-01 +1.116863E+12 4.412608E-01 -6.890026E-01 +1.158777E+12 4.403085E-01 -6.899540E-01 +1.202264E+12 4.393562E-01 -6.909054E-01 +1.247384E+12 4.384039E-01 -6.918568E-01 +1.294196E+12 4.374516E-01 -6.928081E-01 +1.342765E+12 4.364993E-01 -6.937595E-01 +1.393157E+12 4.355469E-01 -6.947109E-01 +1.445440E+12 4.345946E-01 -6.956622E-01 +1.499685E+12 4.336423E-01 -6.966135E-01 +1.555966E+12 4.326899E-01 -6.975648E-01 +1.614359E+12 4.317376E-01 -6.985162E-01 +1.674943E+12 4.307852E-01 -6.994674E-01 +1.737801E+12 4.298329E-01 -7.004187E-01 +1.803018E+12 4.288805E-01 -7.013700E-01 +1.870682E+12 4.279281E-01 -7.023212E-01 +1.940886E+12 4.269757E-01 -7.032724E-01 +2.013724E+12 4.260234E-01 -7.042237E-01 +2.089296E+12 4.250710E-01 -7.051748E-01 +2.167704E+12 4.241186E-01 -7.061260E-01 +2.249055E+12 4.231662E-01 -7.070772E-01 +2.333458E+12 4.222138E-01 -7.080283E-01 +2.421029E+12 4.212614E-01 -7.089794E-01 +2.511886E+12 4.203090E-01 -7.099305E-01 +2.606154E+12 4.193567E-01 -7.108816E-01 +2.703958E+12 4.184043E-01 -7.118326E-01 +2.805434E+12 4.174519E-01 -7.127836E-01 +2.910717E+12 4.164995E-01 -7.137346E-01 +3.019952E+12 4.155471E-01 -7.146856E-01 +3.133286E+12 4.145947E-01 -7.156365E-01 +3.250873E+12 4.136423E-01 -7.165875E-01 +3.372873E+12 4.126898E-01 -7.175384E-01 +3.499452E+12 4.117374E-01 -7.184892E-01 +3.630781E+12 4.107850E-01 -7.194401E-01 +3.767038E+12 4.098326E-01 -7.203909E-01 +3.908409E+12 4.088802E-01 -7.213417E-01 +4.055085E+12 4.079278E-01 -7.222924E-01 +4.207266E+12 4.069754E-01 -7.232431E-01 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--git a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/si_nd_vs_res.txt b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/si_nd_vs_res.txt new file mode 100644 index 0000000..09b4e10 --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/si_nd_vs_res.txt @@ -0,0 +1,502 @@ +N_Ph (cmâ»Â³) Ï (Ω cm) +1.000000E+12 4.414774E+03 +1.037528E+12 4.255157E+03 +1.076465E+12 4.101309E+03 +1.116863E+12 3.953022E+03 +1.158777E+12 3.810095E+03 +1.202264E+12 3.672335E+03 +1.247384E+12 3.539555E+03 +1.294196E+12 3.411575E+03 +1.342765E+12 3.288222E+03 +1.393157E+12 3.169328E+03 +1.445440E+12 3.054733E+03 +1.499685E+12 2.944282E+03 +1.555966E+12 2.837824E+03 +1.614359E+12 2.735215E+03 +1.674943E+12 2.636316E+03 +1.737801E+12 2.540993E+03 +1.803018E+12 2.449117E+03 +1.870682E+12 2.360564E+03 +1.940886E+12 2.275212E+03 +2.013724E+12 2.192947E+03 +2.089296E+12 2.113657E+03 +2.167704E+12 2.037233E+03 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a/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/silicon_energy_bands_data.xlsx b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/silicon_energy_bands_data.xlsx new file mode 100644 index 0000000..bb1011c Binary files /dev/null and b/Add-Ons/ADRESSTools_vEos/PESTools_PCC/F030 - semiconductor modelling/silicon/silicon_energy_bands_data.xlsx differ diff --git a/Add-Ons/ADRESSTools_vEos/README.md b/Add-Ons/ADRESSTools_vEos/README.md new file mode 100644 index 0000000..8075c4f --- /dev/null +++ b/Add-Ons/ADRESSTools_vEos/README.md @@ -0,0 +1,54 @@ +## Log of updates to ADRESSTools +**Eos - 10.04.2023:** +-> The Material Database is now an independent package that does not depend on the PESTools package. +-> New App available: IMFP determination via an app using 'IMFP_UI'. +-> New App available: PES binding energy spectrum, photoionisation cross-section and asymmetry app using 'PES_UI'. +-> Updated PEARL data-loader function. + +**Dionysus - 22.10.2022:** +-> Multiple bug fixes and improvement of PES / XPS analysis and curve fitting tools. +-> Improvement to figure aesthetics used in the codebase. +-> Updated GitHub Repo information and added several showcases of the functions available in ADRESSTools. +-> More generalised EF fitting function, allowing more accurate fits to the EF edge. +-> Updated angle -> wave-vector conversions to take into account new ADRESS geometry. + +**Cronus - 28.09.2022:** +-> Multiple bug fixes and improvement of PES / XPS analysis and curve fitting tools. +-> Updated Theory Data from Microsoft - all up-to-date now. +-> Added Physics Constants to Materials Database. +-> Uploaded MATools to 'Skyfall' version, with new ARPES geometry considered. + +**Basil - 21.02.2022:** +-> Multiple bug fixes and improvement of PES / XPS analysis and curve fitting tools. + +**Ajax - 24.11.2021:** Integration of PES / XPS analysis and curve fitting tools. + +**v2.1 - 17.07.2020:** Massive upgrade to all UI systems and added several new features for analysis. + +**v2.0 - 13.11.2019:** Further development of all UI's to make them all consistent; +-> When saving on the 'arpes_processor' UI, it will now automatically also save an info .txt file. +-> Added new method in 'kf_analysis' that will track states by measuring the full-width at half-maximum as a function of a scan parameter. This method allowed for kF to be tracked automatically using the algorithm, with the user only defining the region of interest. +-> Added feature in 'kf_analysis' that will plot a summary video showing the fits as a function of the scan parameter. +-> Merging to master. + +**v1.8 - 06.02.2019:** Further development of the 'arpes_statefitting' UI; + -> Added Voigt curve that can be fitted. + +**v1.7 - 18.12.2018:** Further development of the 'arpes_statefitting' UI; + -> Combined fit range and fit routine functions. + +**v1.6 - 06.12.2018:** Developed all UI's to be mutually consistent in forms. + +**v1.5 - 28.11.2018:** Developed the 'kf_analysis' UI. + +**v1.4 - 26.11.2018:** Developed the 'bz_navigation' UI. + +**v1.3 - 24.11.2018:** Developed the 'arpes_isoeanalysis' UI. + +**v1.2 - 10.11.2018:** Developed the 'arpes_statefitting' UI. + +**v1.1 - 05.11.2018:** Developed the 'arpes_processor' UI. + +**v1.0 - 10.10.2018:** Single GUI to perform all processing and analysis. + +## List of known bugs diff --git a/Add-Ons/Deconvolution/BoundGen.m b/Add-Ons/Deconvolution/BoundGen.m new file mode 100644 index 0000000..72715d6 --- /dev/null +++ b/Add-Ons/Deconvolution/BoundGen.m @@ -0,0 +1,101 @@ +function [ lb , ub , parvec0 ] = BoundGen( IG,x,y,np,bg,parvec0,mode ) +% Boundry generation. + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Background %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +if strcmp( bg , 'bg0' )==1 || size(IG,1) == 3 || strcmp( bg , 's' )==1 + bg0 = []; + lbg = []; + ubg = []; +elseif strcmp( bg , 'bg1' )==1 + % lbg = min([ 0 min(y) ]); % background can be negative + lbg = 0; % zero = min + ubg = max(y); + bg0 = parvec0(1); + parvec0 = parvec0(2:end); +elseif strcmp( bg , 'bg2' )==1 + lbg = [ 0 0 ]; + if y(1) == 0 + maxubg1 = y(find(y>0,1)); + else + maxubg1 = max([y(1) abs(y(1))]); + end + if y(end) == 0 + maxubg2 = y(find(y>0,1,'last')); + else + maxubg2 = max([y(end) abs(y(end))]); + end + ubg = [ maxubg1 maxubg2 ]; + bg0 = parvec0(1:2); + parvec0 = parvec0(3:end); +elseif strcmp( bg , 'bg3' )==1 + lbg = [ -max(y) -10^5 ]; % arbitrary large number + ubg = [ max(y) 10^5 ]; % arbitrary large number + bg0 = parvec0(1:2); + parvec0 = parvec0(3:end); +elseif size(IG,1) == 1 + bg0 = []; + lbg = []; + ubg = []; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Peaks %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +if strcmp(IG,'auto') == 1 || strcmp(IG,'full') == 1 + % Peak Suggestion %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + lpeaks = 0*parvec0; + upeaks = lpeaks; + scaleerrbound = 0.1; % deviation from original guess - scale + peakerrbound = 0.005; % deviation from original guess - position + depression = 4; % ratio of FWHM to range size + if mode == 1 % Voigt + for i=1:np % parveci = [a x0 nu sig] = [scale center shape(0lb' , 'VariableNames' , varArray ); + disp(T) +elseif strcmp( bg , 'bg1' )==1 + numbers = 1:length(parvec0); + nameArray = {}; + for i = 1:np + scaleStr = [ 'Peak # = ' num2str(i) par1 ]; + centerStr = [ 'Peak # = ' num2str(i) par2 ]; + shapeStr = [ 'Peak # = ' num2str(i) par3 ]; + widthStr = [ 'Peak # = ' num2str(i) par4 ]; + tempArray = { scaleStr , centerStr , shapeStr , widthStr }; + nameArray = [ nameArray tempArray ]; + end + bgstr = { 'Background Constant' }; + nameArray = [ bgstr nameArray ]; + T = table( nameArray' , numbers' , parvec0' , lb' , ub' , parameters' , parvec0'lb' , 'VariableNames' , varArray ); + disp(T) +elseif strcmp( bg , 'bg2' )==1 + numbers = 1:length(parvec0); + nameArray = {}; + for i = 1:np + scaleStr = [ 'Peak # = ' num2str(i) par1 ]; + centerStr = [ 'Peak # = ' num2str(i) par2 ]; + shapeStr = [ 'Peak # = ' num2str(i) par3 ]; + widthStr = [ 'Peak # = ' num2str(i) par4 ]; + tempArray = { scaleStr , centerStr , shapeStr , widthStr }; + nameArray = [ nameArray tempArray ]; + end + bgstr = { 'Constant at Beginning' 'Constant at End'}; + nameArray = [ bgstr nameArray ]; + T = table( nameArray' , numbers' , parvec0' , lb' , ub' , parameters' , parvec0'lb' , 'VariableNames' , varArray ); + disp(T) +elseif strcmp( bg , 'bg3' )==1 + numbers = 1:length(parvec0); + nameArray = {}; + for i = 1:np + scaleStr = [ 'Peak # = ' num2str(i) par1 ]; + centerStr = [ 'Peak # = ' num2str(i) par2 ]; + shapeStr = [ 'Peak # = ' num2str(i) par3 ]; + widthStr = [ 'Peak # = ' num2str(i) par4 ]; + tempArray = { scaleStr , centerStr , shapeStr , widthStr }; + nameArray = [ nameArray tempArray ]; + end + bgstr = { 'Constant at Beginning' 'Scale'}; + nameArray = [ bgstr nameArray ]; + T = table( nameArray' , numbers' , parvec0' , lb' , ub' , parameters' , parvec0'lb' , 'VariableNames' , varArray ); + disp(T) +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Changing Parameters %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Change using TXT %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +changecont = 1; +% Make Files for Changing % +while changecont == 1; + for i = 1:(np+1) + % Decide on Name % + if i == 1 + namechange = 'change_bg.txt'; + else + namechange = ['change_peak' num2str(i-1) '.txt']; + end + % Open File % + fileID=fopen(namechange,'wt'); + + % Print File % + if i == 1 + % Background files % + if strcmp( bg , 'bg0' )==1 || strcmp( bg , 's' )==1 + lbg = 0; + elseif strcmp( bg , 'bg1' )==1 + lbg = 1; + else + lbg = 2; + end + + for l = 1:lbg + fprintf(fileID,'%g\t%g\t%g\t%g\t\n',lb(l),parvec0(l),ub(l),parameters(l)); + end + else + % Peak files % + if strcmp( bg , 'bg0' )==1 || strcmp( bg , 's' )==1 + lbg = 0; + elseif strcmp( bg , 'bg1' )==1 + lbg = 1; + else + lbg = 2; + end + + for l = (4*i-7+lbg):(4*i-4+lbg) + fprintf(fileID,'%g\t%g\t%g\t%g\t\n',lb(l),parvec0(l),ub(l),parameters(l)); + end + end + + % Close % + fclose(fileID); + + % Backup % +% copyfile(namechange,['BU_' namechange]); + end + + fprintf('Change file now, close after finishing\n') + fprintf('Look at table for reference\n') + changecont = input('To stop changing input 0: '); +end + +% Read Files for Changing % +fclose('all'); +newpar = []; +for i = 1:(np+1) + % Decide on Name % + if i == 1 + namechange = 'change_bg.txt'; + else + namechange = ['change_peak' num2str(i-1) '.txt']; + end + % Open File % + fileID=fopen(namechange,'r'); + + % Read File % + newpar = [newpar;fscanf(fileID,'%f %f %f %f',[4 inf])']; + + % Close % + fclose(fileID); + + % Delete % + delete(namechange); +end + +lb = newpar(:,1)'; +parvec0 = newpar(:,2)'; +ub = newpar(:,3)'; +end \ No newline at end of file diff --git a/Add-Ons/Deconvolution/example, 4 peaks, dc.tif b/Add-Ons/Deconvolution/example, 4 peaks, dc.tif new file mode 100644 index 0000000..5c62486 Binary files /dev/null and b/Add-Ons/Deconvolution/example, 4 peaks, dc.tif differ diff --git a/Add-Ons/Deconvolution/example, 4 peaks, dcperfect.tif b/Add-Ons/Deconvolution/example, 4 peaks, dcperfect.tif new file mode 100644 index 0000000..a1f9923 Binary files /dev/null and b/Add-Ons/Deconvolution/example, 4 peaks, dcperfect.tif differ diff --git a/Add-Ons/Deconvolution/example, 4 peaks, original data.tif b/Add-Ons/Deconvolution/example, 4 peaks, original data.tif new file mode 100644 index 0000000..2b6b5e4 Binary files /dev/null and b/Add-Ons/Deconvolution/example, 4 peaks, original data.tif differ diff --git a/Add-Ons/Deconvolution/example, 4 peaks.txt b/Add-Ons/Deconvolution/example, 4 peaks.txt new file mode 100644 index 0000000..bb6dca4 --- /dev/null +++ b/Add-Ons/Deconvolution/example, 4 peaks.txt @@ -0,0 +1,300 @@ +0 7.21089209869789 +0.334448160535117 7.24895901150177 +0.668896321070234 7.28832266156970 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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +if V(1,1)>=V(end,1) % The data needs to be from smallest x to largest x. + V = flipud(V); +end + +% Range Selection %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +indmin=find(V(:,1)>=range(1),1); +indmax=find(V(:,1)>=range(2),1); +if isempty(indmin)==1; + indmin=1; +end +if isempty(indmax)==1; + indmax=length(V(:,1)); +end +x=V(indmin:indmax,1); +y=V(indmin:indmax,2); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Warning %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +if (2+4*np)*5 > length(y) % Thumb rule for goodness of fit. + disp('You should consider lowering the number of peaks, for better confidence values') +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Initial Guess %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +[ parvec0 ] = IGgen( IG,x,y,np,bg,mode ); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Bounds %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +[ lb , ub , parvec0 ] = BoundGen( IG,x,y,np,bg,parvec0,mode ); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Fitting %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +opts = optimset('Display','off','MaxIter',50000); + +if strcmp(IG,'full')==1 + % Full Fitting %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Initial Fit %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + funcfic = @( parvec,x )multiv( bg,parvec,x,y,mode ); + [parameters,resnorm,residual,exitflag,output,lambda,jacobian]=lsqcurvefit(funcfic,parvec0,x,y,lb,ub,opts); + yavg=mean(y); + r2=1-sum((y-funcfic( parameters,x )).^2)/sum((y-yavg).^2); + + % Initial Plot %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + plotter( x,y,bg,parameters,np,r2,range,residual,resnorm,name,IG,mode ); + + % Changing %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + changecheck = 0; + while changecheck == 0 + % Changing Parameters %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + [ lb , ub , parvec0 ] = changer( lb , ub , parvec0 , bg , np , parameters , mode ); + funcfic = @( parvec,x )multiv( bg,parvec,x,y,mode ); + [parameters,resnorm,residual,exitflag,output,lambda,jacobian]=lsqcurvefit(funcfic,parvec0,x,y,lb,ub,opts); + yavg=mean(y); + r2=1-sum((y-funcfic( parameters,x )).^2)/sum((y-yavg).^2); + plotter( x,y,bg,parameters,np,r2,range,residual,resnorm,name,IG,mode ); + + % Exit Check %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + changecheck = input('Input 0 to change something else, 1 to continue - '); + if changecheck == 1 + IG = []; + plotter( x,y,bg,parameters,np,r2,range,residual,resnorm,name,IG,mode ); + end + end +else + % Auto Fitting %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + funcfic = @( parvec,x )multiv( bg,parvec,x,y,mode ); + [parameters,resnorm,residual,exitflag,output,lambda,jacobian]=lsqcurvefit(funcfic,parvec0,x,y,lb,ub,opts); + yavg=mean(y); + r2=1-sum((y-funcfic( parameters,x )).^2)/sum((y-yavg).^2); + + % Plotting %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + plotter( x,y,bg,parameters,np,r2,range,residual,resnorm,name,IG,mode ); +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Calculating Confidence Intervals %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +conf = nlparci(parameters,residual,'jacobian',jacobian)'; +minConf = abs(parameters - conf(2,:)); +maxConf = abs(parameters - conf(1,:)); +conf = mean([minConf;maxConf]); +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Table %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Displays a table of the parameters +clc +fprintf('Range of peaks: from %g to %g.\n',range(1),range(2)) +fprintf('Number of peaks to fit = %g.\n',np) +if strcmp( bg , 'bg0' )==1 + fprintf('Background Constant = %g.\n',0) + redpar = parameters; + redconf = conf; +elseif strcmp( bg , 's' )==1 + fprintf('Shirley Background.\n') + redpar = parameters; + redconf = conf; +elseif strcmp( bg , 'bg1' )==1 + fprintf('Background Constant = %g ± %g.\n',parameters(1),conf(1)) + redpar = parameters(2:end); + redconf = conf(2:end); +elseif strcmp( bg , 'bg2' )==1 + fprintf('Background Constant 1 = %g ± %g.\n',parameters(1),conf(1)) + fprintf('Background Constant 2 = %g ± %g.\n',parameters(2),conf(2)) + redpar = parameters(3:end); + redconf = conf(3:end); +elseif strcmp( bg , 'bg3' )==1 + fprintf('Background Constant = %g ± %g.\n',parameters(1),conf(1)) + fprintf('Background Slope = %g ± %g.\n',parameters(2),conf(2)) + redpar = parameters(3:end); + redconf = conf(3:end); +end + +fprintf('R^2 = %g.\n',r2) + +if mode == 1 + fprintf('Peak #\t\tScale Factor\tPeak Center\t\tNu (0=Lorentz1 : the number of peaks to detect +% - 0 1 + w=max(eps,sin(2*pi*(0:(horizon-1))/2/(horizon-1))); + w=w/sum(w); + %V=conv(V(:),w(:),'same'); + V = real(ifft(fft(V(:),n+horizon).*fft(w(:),n+horizon))); + V = V(1+floor(horizon/2):end-ceil(horizon/2)); + end + + %find local maxima + tempMat(2:end,1) = V(1:end-1); + tempMat(:,2) = V(:); + tempMat(1:end-1,3) = V(2:end); + [~,posMax] =max(tempMat,[],2); + I = find(posMax==2); + I = I(:)'; + + %initialize buffer + newBuffer = zeros(size(buffer)); + + if is == 1 + % if first iteration, keep all local maxima + newBuffer(I) = Vorig(I); + else + old = find(buffer); + old = old(:)'; + + %Now, for each element of I, find the closest element in + %old along with its distance. The few nice lines below were + %written by Roger Stafford in a forum post available here: + %http://www.mathworks.fr/matlabcentral/newsreader/view_thread/243878 + nI = size(I,2); nOld = size(old,2); + [~,p] = sort([I,old]); + q = 1:nI+nOld; q(p) = q; + t = cumsum(p>nI); + r = 1:nOld; r(t(q(nI+1:nI+nOld))) = r; + s = t(q(1:nI)); + id = r(max(s,1)); + iu = r(min(s+1,nOld)); + [d,it] = min([abs(I-old(id));abs(old(iu)-I)]); + iOld = id+(it-1).*(iu-id); + + %done, now select only those that are sufficiently close + neighbours = iOld(dselect); +else + sorted = find(criterion>1E-3); + [~,order] = sort(criterion(sorted),'descend'); + peaks = sorted(order(1:min(length(sorted),select))); +end + +if display + %display + clf + plot(Vorig,'LineWidth',2); + hold on + plot(criterion*max(Vorig),'r'); + hold on + plot(peaks,Vorig(peaks),'ro','MarkerSize',10,'LineWidth',2) + grid on + title('Scale-space peak detection','FontSize',16); + legend('data','computed criterion','selected peaks'); +end +end + diff --git a/Add-Ons/Deconvolution/plotter.m b/Add-Ons/Deconvolution/plotter.m new file mode 100644 index 0000000..b65582f --- /dev/null +++ b/Add-Ons/Deconvolution/plotter.m @@ -0,0 +1,127 @@ +function [] = plotter( x,y,bg,parameters,np,r2,range,residual,resnorm,name,IG,mode ) +% Plots the fitted data and the residuals. +close all +h = figure; +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Main Plot %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +subplot(1,2,1) +plot(x,y); +title(name,'Interpreter','none') +hold all +grid on +% Plot Total Fit % +plot(x,multiv( bg,parameters,x,y,mode )) +% Plot Backgrund % +if strcmp( bg , 'bg0' )==1 + plot(x,x*0) + minyaxis = 0; +elseif strcmp( bg , 'bg1' )==1 + plot(x,multiv( bg,parameters(1),x,y,mode )) + minyaxis = 0; +elseif strcmp( bg , 'bg2' )==1 || strcmp( bg , 'bg3' )==1 + ybg = multiv( bg,[parameters(1) parameters(2)],x,y,mode ); + plot(x,ybg); + minyaxis = min(ybg)*1.1; +elseif strcmp( bg , 's' )==1 + [ mvx , sbg ] = multiv( bg,parameters,x,y,mode ); + plot(x,sbg); + minyaxis = 0; +end +% Plot peaks OVER background % +for i=1:np % parvec = [a x0 nu sig] = [scale center shape(01 + nu=1; + else + nu=parveci(3); + end + + %Voigt + f1=nu.*sqrt(log(2)./pi)*exp(-4.*log(2).*((x-x0)./(abs(sig))).^2)./abs(sig); + f2=(1-nu)./(pi.*abs(sig).*(1+4.*((x-x0)./(abs(sig))).^2)); + f3=nu.*sqrt(log(2)./pi)./abs(sig)+(1-nu)./(pi.*abs(sig)); + %f3=0.5; %if f3=0.5 a is the integral under the peak + + svx=a.*(f1+f2)./f3; + + %http://en.wikipedia.org/wiki/Voigt_profile + %http://www.casaxps.com/help_manual/line_shapes.htm + %http://sasfit.ingobressler.net/manual/Gaussian-Lorentzian_Cross_Product + %http://sasfit.ingobressler.net/manual/Gaussian-Lorentzian_Sum +elseif mode == 2 + % parveci = [a m zero sig] = [scale mode 'flip scale at zero' width] + a = parveci(1); + m = parveci(2); % mode + zero = parveci(3); + FWHM = parveci(4); + sig = fzero(@(sig)FWHMcalc( sig , FWHM , m , zero ),0.1); + x0 = log(zero-m) + sig^2; + + % Log normal + g = 1 / (sig*sqrt(2*pi)*exp(x0-(sig^2)/2)); + svx = (a./g).*lognpdf(zero-x,x0,sig); + + % http://en.wikipedia.org/wiki/Log-normal_distribution + % http://www.mathworks.com/help/stats/lognpdf.html +end + +end \ No newline at end of file diff --git a/Add-Ons/Deconvolution/writer.m b/Add-Ons/Deconvolution/writer.m new file mode 100644 index 0000000..c2af426 --- /dev/null +++ b/Add-Ons/Deconvolution/writer.m @@ -0,0 +1,98 @@ +function [ ] = writer( name,range,np,parameters,conf,r2,graphdata,bg,mode ) +% Writes data to file. + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Make File %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%(ignore warning) +mkdir('dc'); +fprintf('Ignore the error, if there is one\n') +timenum = clock; +timenum = round(timenum); +timename = ''; +for t = [ 1 2 3 6 5 4 ] + timename = [num2str( timenum( t ) ) '_' timename]; +end +fileID=fopen(['dc\dc_' name(1:end-4) '_' timename(1:end-1) '.txt'],'wt'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Write Tables %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% File Name %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +fprintf(fileID,['File name: ' name '\n']); +fprintf('Ignore the error, if there is one\n') +fprintf('\n') + +% Parameter Table %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +fprintf(fileID,'Range of peaks: from %g to %g.\n',range(1),range(2)); +fprintf(fileID,'Number of peaks to fit = %g.\n',np); +if strcmp( bg , 'bg0' )==1 + fprintf(fileID,'Background Constant = %g.\n',0); + redpar = parameters; + redconf = conf; +elseif strcmp( bg , 's' )==1 + fprintf('Shirley Background.\n') + redpar = parameters; + redconf = conf; +elseif strcmp( bg , 'bg1' )==1 + fprintf(fileID,'Background Constant = %g ± %g.\n',parameters(1),conf(1)); + redpar = parameters(2:end); + redconf = conf(2:end); +elseif strcmp( bg , 'bg2' )==1 + fprintf(fileID,'Background Constant 1 = %g ± %g.\n',parameters(1),conf(1)); + fprintf(fileID,'Background Constant 2 = %g ± %g.\n',parameters(2),conf(2)); + redpar = parameters(3:end); + redconf = conf(3:end); +elseif strcmp( bg , 'bg3' )==1 + fprintf(fileID,'Background Constant = %g ± %g.\n',parameters(1),conf(1)); + fprintf(fileID,'Background Slope = %g ± %g.\n',parameters(2),conf(2)); + redpar = parameters(3:end); + redconf = conf(3:end); +end +fprintf(fileID,'R^2 = %g.\n',r2); +if mode == 1 + fprintf(fileID,'Peak #\t\tScale Factor\tPeak Center\t\tNu (0=Lorentz0); + % X offset & spacing (documentation is obscure) + D.dx = D.waveHeader.sfA(1:D.Ndim); + D.x0 = D.waveHeader.sfB(1:D.Ndim); + D.x1 = nan; % D.x0+D.Nsam*D.dx; + fseek(fid, 64+320, 'bof'); + NN = D.Nsam*(1+double(CMPLX)); % if complex, read twice as many numbers + if isequal(0,datatype), % text data + % Number of bytes of wave data = wfmSize - (sizeof(WaveHeader5) - 4) + NN = D.binHeader.wfmSize-320; + D.y = fread(fid, NN, prec)'; + else, % numerical data + D.y = fread(fid, NN, prec); + end + if CMPLX, D.y = D.y(1:2:end) + i*D.y(2:2:end); end; % Re & Im values are interleaved + if ~isempty(D.y) && D.Ndim>1, + D.y = reshape(D.y, D.waveHeader.nDim(1:D.Ndim)); + end +end +D.WaveNotes = local_readNotes(fid, D.binHeader); +if isequal(0,datatype), % partition text data into lines using string indices stored @ eof + D = local_partition_text(fid, D); +end +fseek(fid,0,'eof'); +D.fileSize = ftell(fid); +fclose(fid); + + +%=============================== +function DV=local_igorTime2vec(it); +% igor time -> date vector a la Matlab +% The date/time is store as seconds since midnight, January 1, 1904. +Nsec_4year = 126230400; +idate_1988 = 21*uint32(Nsec_4year); % # seconds between 1-jan-1904 & 1-jan-1988 +it = double(it-idate_1988); % smaller numbers-> use ordinary numbers ("doubles") +M4 = floor(it/Nsec_4year); +YR = double(1988+4*M4); +it = double(it-M4*Nsec_4year); +last_it = it; +while 1, % subtract years as long as they fit + s = etime([YR+1 1 1 0 0 0], [YR 1 1 0 0 0]); + if it 2 + output_txt{end+1} = ['Z: ',num2str(pos(3),4)]; +end diff --git a/Add-Ons/NewCallbackwithT.m b/Add-Ons/NewCallbackwithT.m new file mode 100644 index 0000000..c973951 --- /dev/null +++ b/Add-Ons/NewCallbackwithT.m @@ -0,0 +1,18 @@ +function output_txt = myfunction(obj,event_obj) +% Display the position of the data cursor +% obj Currently not used (empty) +% event_obj Handle to event object +% output_txt Data cursor text string (string or cell array of strings). +% vapour pressure over ice: +% Marti, J., and K. Mauersberger, Geophys. Res.Lett., 20, 363?366, 1993. +% gives parameterization from 169 - 273K in Pa. (log10(p)= A1/T+B) +A_1 = -2663.5; +B_1 = 12.537; +pos = get(event_obj,'Position'); +output_txt = {['X: ',datestr(pos(1),0)],... + ['Y: ',num2str(pos(2),4)],... + ['T(over ice): ',num2str(A_1/(log10(pos(2)*100)-B_1)-273.15,3) ' °C']}; +% If there is a Z-coordinate in the position, display it as well +if length(pos) > 2 + output_txt{end+1} = ['Z: ',num2str(pos(3),4)]; +end diff --git a/Add-Ons/NewGuy012-spider_plot/README.md b/Add-Ons/NewGuy012-spider_plot/README.md new file mode 100644 index 0000000..2ce674b --- /dev/null +++ b/Add-Ons/NewGuy012-spider_plot/README.md @@ -0,0 +1,346 @@ +[![View spider_plot on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://www.mathworks.com/matlabcentral/fileexchange/59561-spider_plot) + +# spider_plot +Create a spider or radar plot with customizable individual axes. + +## Syntax: +**spider_plot(P)** + + +**spider_plot(P, Name, Value, ...)** + +## Input Arguments: +*(Required)* + +- **P** - The data points used to plot the spider chart. The rows are the groups of data and the columns are the data points. + The axes labels and axes limits are automatically generated if not specified. + [vector | matrix] + +## Name-Value Pair Arguments: +*(Optional)* + +- **AxesLabels** - Used to specify the label each of the axes. + [auto-generated (default) | cell of strings | 'none'] + +- **AxesInterval** - Used to change the number of intervals displayed between the webs. + [3 (default) | integer] + +- **AxesPrecision** - Used to change the precision level on the value displayed on the axes. + [1 (default) | integer | vector] + +- **AxesDisplay** - Used to change the number of axes in which the axes text are displayed. 'None' or 'one' can be used to simplify the plot appearance for normalized data. + ['all' (default) | 'none' | 'one'] + +- **AxesLimits** - Used to manually set the axes limits. A matrix of 2 x size(P, 2). The top row is the minimum axes limits and the bottow row is the maximum axes limits. + [auto-scaled (default) | matrix] + +- **FillOption** - Used to toggle color fill option. + ['off' (default) | 'on'] + +- **FillTransparency** - Used to set color fill transparency. + [0.1 (default) | scalar in range (0, 1)] + +- **Color** - Used to specify the line color, specified as an RGB triplet. The intensities must be in the range (0, 1). + [MATLAB colors (default) | RGB triplet | hexadecimal color code] + +- **LineStyle** - Used to change the line style of the plots. + ['-' (default) | '--' | ':' | '-.' | 'none' | cell array of character vectors] + +- **LineWidth** - Used to change the line width, where 1 point is 1/72 of an inch. + [0.5 (default) | positive value | vector] + +- **Marker** - Used to change the marker symbol of the plots. + ['o' (default) | '*' | 's' | 'd' | '+' | '.' | 'x' | '^' | 'v' | 'h' | 'none' | cell array of character vectors] + +- **MarkerSize** - Used to change the marker size, where 1 point is 1/72 of an inch. + [8 (default) | positive value | vector] + +- **AxesFont** - Used to change the font type of the values displayed on the axes. + [Helvetica (default) | supported font name] + +- **LabelFont** - Used to change the font type of the labels. + [Helvetica (default) | supported font name] + +- **AxesFontSize** - Used to change the font size of the values displayed on the axes. + [10 (default) | scalar value greater than zero] + +- **LabelFontSize** - Used to change the font size of the labels. + [10 (default) | scalar value greater than zero] + +- **Direction** - Used to change the direction of rotation of the plotted data and axis labels. + ['clockwise' (default) | 'counterclockwise'] + +- **AxesDirection** - Used to change the direction of axes. + ['normal' (default) | 'reverse' | cell array of character vectors] + +- **AxesLabelsOffset** - Used to adjust the position offset of the axes labels. + [0.1 (default) | positive value] + +- **AxesScaling** - Used to change the scaling of the axes. + ['linear' (default) | 'log' | cell array of character vectors] + +- **AxesColor** - Used to change the color of the spider axes. + [grey (default) | RGB triplet] + +- **AxesLabelsEdge** - Used to change the edge color of the axes labels. + [black (default) | RGB triplet | hexadecimal color code | 'none'] + +- **AxesOffset** - Used to change to axes offset from the origin. + [1 (default) | any integer less than the axes interval] + +## Examples: +### Example 1: Minimal number of arguments. All optional arguments are set to their default values. Axes labels and limits are automatically set. +```matlab +% Initialize data points +D1 = [5 3 9 1 2]; +D2 = [5 8 7 2 9]; +D3 = [8 2 1 4 6]; +P = [D1; D2; D3]; + +% Spider plot +spider_plot(P); + +% Legend settings +legend('D1', 'D2', 'D3', 'Location', 'southoutside'); +``` +

+ +

+ + +### Example 2: Manually setting the axes limits and axes precision. All other optional arguments are set to their default values. +```matlab +% Initialize data points +D1 = [5 3 9 1 2]; +D2 = [5 8 7 2 9]; +D3 = [8 2 1 4 6]; +P = [D1; D2; D3]; + +% Spider plot +spider_plot(P,... + 'AxesLimits', [1, 2, 1, 1, 1; 10, 8, 9, 5, 10],... % [min axes limits; max axes limits] + 'AxesPrecision', [0, 1, 1, 1, 1]); +``` +

+ +

+ + +### Example 3: Set fill option on. The fill transparency can be adjusted. +```matlab +% Initialize data points +D1 = [5 3 9 1 2]; +D2 = [5 8 7 2 9]; +D3 = [8 2 1 4 6]; +P = [D1; D2; D3]; + +% Spider plot +spider_plot(P,... + 'AxesLabels', {'S1', 'S2', 'S3', 'S4', 'S5'},... + 'AxesInterval', 2,... + 'FillOption', 'on',... + 'FillTransparency', 0.1); +``` +

+ +

+ + + ### Example 4: Maximum number of arguments. +```matlab +% Initialize data points +D1 = [5 3 9 1 2]; +D2 = [5 8 7 2 9]; +D3 = [8 2 1 4 6]; +P = [D1; D2; D3]; + +% Spider plot +spider_plot(P,... + 'AxesLabels', {'S1', 'S2', 'S3', 'S4', 'S5'},... + 'AxesInterval', 4,... + 'AxesPrecision', 0,... + 'AxesDisplay', 'one',... + 'AxesLimits', [1, 2, 1, 1, 1; 10, 8, 9, 5, 10],... + 'FillOption', 'on',... + 'FillTransparency', 0.2,... + 'Color', [1, 0, 0; 0, 1, 0; 0, 0, 1],... + 'LineStyle', {'--', '-', '--'},... + 'LineWidth', [1, 2, 3],... + 'Marker', {'o', 'd', 's'},... + 'MarkerSize', [8, 10, 12],... + 'AxesFont', 'Times New Roman',... + 'LabelFont', 'Times New Roman',... + 'AxesFontSize', 12,... + 'LabelFontSize', 10,... + 'Direction', 'clockwise',... + 'AxesDirection', {'reverse', 'normal', 'normal', 'normal', 'normal'},... + 'AxesLabelsOffset', 0.1,... + 'AxesScaling', 'linear',... + 'AxesColor', [0.6, 0.6, 0.6],... + 'AxesLabelsEdge', 'none',... + 'AxesOffset', 1); +``` +

+ +

+ + + ### Example 5: Excel-like radar charts. +```matlab +% Initialize data points +D1 = [5 0 3 4 4]; +D2 = [2 1 5 5 4]; +P = [D1; D2]; + +% Spider plot +spider_plot(P,... + 'AxesInterval', 5,... + 'AxesPrecision', 0,... + 'AxesDisplay', 'one',... + 'AxesLimits', [0, 0, 0, 0, 0; 5, 5, 5, 5, 5],... + 'FillOption', 'on',... + 'FillTransparency', 0.1,... + 'Color', [139, 0, 0; 240, 128, 128]/255,... + 'LineWidth', 4,... + 'Marker', 'none',... + 'AxesFontSize', 14,... + 'LabelFontSize', 10,... + 'AxesColor', [0.8, 0.8, 0.8],... + 'AxesLabelsEdge', 'none'); + +% Title and legend settings +title(sprintf('Excel-like Radar Chart'),... + 'FontSize', 14); +legend_str = {'D1', 'D2'}; +legend(legend_str, 'Location', 'southoutside'); +``` +

+ +

+ + + ### Example 6: Logarithimic scale on specified axes. Axes limits and axes intervals can be individually set as well. +```matlab +% Initialize data points +D1 = [5 3 9 1 1]; +D2 = [5 8 7 2 10]; +D3 = [8 2 1 4 100]; +P = [D1; D2; D3]; + +% Spider plot +spider_plot(P,... + 'AxesInterval', 2,... + 'AxesPrecision', 0,... + 'AxesFontSize', 10,... + 'AxesLabels', {'Linear Scale', 'Linear Scale', 'Linear Scale', 'Linear Scale', 'Logarithimic Scale'},... + 'AxesScaling', {'linear', 'linear', 'linear', 'linear', 'log'},... + 'AxesLimits', [1, 1, 1, 1, 1; 10, 10, 10, 10, 100]); + +% Legend properties +legend('D1', 'D2', 'D3', 'Location', 'northeast'); +``` +

+ +

+ + + ### Example 7: Spider plot with tiledlayout feature in R2019b. +```matlab +% Initialize data points +D1 = [5 3 9 1 2]; +D2 = [5 8 7 2 9]; +D3 = [8 2 1 4 6]; +P = [D1; D2; D3]; + +% Titled layout +t = tiledlayout(2, 2); + +% Tile 1 +nexttile; +spider_plot_R2019b(P,... + 'AxesInterval', 1,... + 'AxesPrecision', 0); + +% Tile 2 +nexttile; +spider_plot_R2019b(P,... + 'AxesInterval', 1,... + 'AxesPrecision', 0); + +% Tile 3 +nexttile(3, [1, 2]); +spider_plot_R2019b(P,... + 'AxesInterval', 1,... + 'AxesPrecision', 0); + +% Tile properties +t.TileSpacing = 'compact'; +t.Padding = 'compact'; +title(t, 'Spider Plots'); +``` +

+ +

+ + +## Author: +Moses Yoo, (jyoo at hatci dot com) +- 2020-12-01: Added support for adjust the axes offset from origin. + +- 2020-11-30: Allow for one data group without specified axes limits. + +- 2020-11-30: Added support for changing axes and label font type. + +- 2020-10-08: Adjust axes precision to be set to one or more axis. + +- 2020-09-30: Updated examples and added ability to reverse axes direction. + +- 2020-07-05: Added feature to change spider axes and axes labels edge color. + +- 2020-06-17: Allow logarithmic scale to be set to one or more axis. + +- 2020-03-26: Added feature to allow different line styles, line width, marker type, and marker sizes for the data groups. + +- 2020-02-17: Major revision in converting the function into a custom chart class. New feature introduced in R2019b. + +- 2020-02-12: Fixed condition and added error checking for when only one data group is plotted. + +- 2020-01-27: Corrected bug where only 7 entries were allowed in legend. + +- 2020-01-06: Added support for subplot and tiledlayout feature (tiledlayout introduced in R2019b). + +- 2019-11-27: Add option to change axes to logarithmic scale. + +- 2019-11-15: Add feature to customize the plot rotational direction and the offset position of the axis labels. + +- 2019-10-28: Major revision in implementing the new function argument validation feature introduced in R2019b. Replaced previous method of error checking and setting of default values. + +- 2019-10-23: Minor revision to set starting axes as the vertical line. Add customization option for font sizes and axes display. + +- 2019-10-16: Minor revision to add name-value pairs for customizing color, marker, and line settings. + +- 2019-10-08: Another major revision to convert to name-value pairs and add color fill option. + +- 2019-09-17: Major revision to improve speed, clarity, and functionality + +## Special Thanks: +Special thanks to the following people for their feature recommendations and suggested bug fixes. +- Gabriela Andrade +- Andrés Garcia +- Jiro Doke +- Alex Grenyer +- Tobias Kern +- Omar Hadri +- Zafar Ali +- Christophe Hurlin +- Sean de Wolski +- Roman +- Mariusz Sepczuk +- Mohamed Abubakr +- Maruis Mueller +- Nicolai +- Jingwei Too +- Cedric Jamet +- Richard Ruff + +[![View spider_plot on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://www.mathworks.com/matlabcentral/fileexchange/59561-spider_plot) diff --git a/Add-Ons/NewGuy012-spider_plot/license.txt b/Add-Ons/NewGuy012-spider_plot/license.txt new file mode 100644 index 0000000..68b8f85 --- /dev/null +++ b/Add-Ons/NewGuy012-spider_plot/license.txt @@ -0,0 +1,24 @@ +Copyright (c) 2020-2021, Moses +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are +met: + + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in + the documentation and/or other materials provided with the distribution + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE +LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +POSSIBILITY OF SUCH DAMAGE. diff --git a/Add-Ons/NewGuy012-spider_plot/screenshot/example1.PNG b/Add-Ons/NewGuy012-spider_plot/screenshot/example1.PNG new file mode 100644 index 0000000..324a91e Binary files /dev/null and b/Add-Ons/NewGuy012-spider_plot/screenshot/example1.PNG differ diff --git a/Add-Ons/NewGuy012-spider_plot/screenshot/example2.png b/Add-Ons/NewGuy012-spider_plot/screenshot/example2.png new file mode 100644 index 0000000..f0e77bc Binary files /dev/null and b/Add-Ons/NewGuy012-spider_plot/screenshot/example2.png differ diff --git a/Add-Ons/NewGuy012-spider_plot/screenshot/example3.PNG b/Add-Ons/NewGuy012-spider_plot/screenshot/example3.PNG new file mode 100644 index 0000000..637b909 Binary files /dev/null and b/Add-Ons/NewGuy012-spider_plot/screenshot/example3.PNG differ diff --git a/Add-Ons/NewGuy012-spider_plot/screenshot/example4.png b/Add-Ons/NewGuy012-spider_plot/screenshot/example4.png new file mode 100644 index 0000000..e58d0f6 Binary files /dev/null and b/Add-Ons/NewGuy012-spider_plot/screenshot/example4.png differ diff --git a/Add-Ons/NewGuy012-spider_plot/screenshot/example5.png b/Add-Ons/NewGuy012-spider_plot/screenshot/example5.png new file mode 100644 index 0000000..7805163 Binary files /dev/null and b/Add-Ons/NewGuy012-spider_plot/screenshot/example5.png differ diff --git a/Add-Ons/NewGuy012-spider_plot/screenshot/example6.png b/Add-Ons/NewGuy012-spider_plot/screenshot/example6.png new file mode 100644 index 0000000..3ca7ecc Binary files /dev/null and b/Add-Ons/NewGuy012-spider_plot/screenshot/example6.png differ diff --git a/Add-Ons/NewGuy012-spider_plot/screenshot/example7.PNG b/Add-Ons/NewGuy012-spider_plot/screenshot/example7.PNG new file mode 100644 index 0000000..6843dd8 Binary files /dev/null and b/Add-Ons/NewGuy012-spider_plot/screenshot/example7.PNG differ diff --git a/Add-Ons/NewGuy012-spider_plot/spider_plot_R2019b_examples.mlx b/Add-Ons/NewGuy012-spider_plot/spider_plot_R2019b_examples.mlx new file mode 100644 index 0000000..4c2c569 Binary files /dev/null and b/Add-Ons/NewGuy012-spider_plot/spider_plot_R2019b_examples.mlx differ diff --git a/Add-Ons/Sample.m b/Add-Ons/Sample.m new file mode 100644 index 0000000..285b56b --- /dev/null +++ b/Add-Ons/Sample.m @@ -0,0 +1,33 @@ +clc; +clear; +close all; + +% ========================================================================= +% ===== General figures =================================================== +% ========================================================================= + +Color = lines(7); +Color = Color([1,7,5,4],:); +Color(end+1,:) = [0.9,0.9,1] * 0.25; +I = [1,2,2,2,3,3,3,4,4,4,4,5,5,5]; +Size = [350,250,150,125,100]; +for i = 1:numel(I) + figure('Color','w'); + text(0,0,num2str(i),'HorizontalAlignment','Center','FontSize',Size(I(i)),'Color',Color(I(i),:)); + xlim([-1,1]); + ylim([-1,1]); + axis off; + set(gcf,'Color',(Color(I(i),:) + [1,1,1]) / 2,'MenuBar','none'); + set(gca,'XTick',[],'YTick',[]); +end + +% ========================================================================= +% ===== Distribute figures ================================================ +% ========================================================================= + +distFig('Pos','NW','Only',1,'Tight',true); +distFig('Pos','SW','Cols',3,'Only',(2:4),'Tight',true); +distFig('Pos','NE','Rows',2,'Only',5,'Tight',true); +distFig('Pos','NE','Rows',2,'Cols',2,'Only',[6,7],'Offset',2,'transpose',true,'Tight',true); +distFig('Pos','SE','Rows',2,'Cols',4,'Only',(8:11),'Tight',true); +distFig('Pos','SE','Rows',3,'Cols',2,'Not',(1:11),'Offset',3,'Tight',true); \ No newline at end of file diff --git a/Add-Ons/Sample.png b/Add-Ons/Sample.png new file mode 100644 index 0000000..5f469d4 Binary files /dev/null and b/Add-Ons/Sample.png differ diff --git a/Add-Ons/Tutorial_1_Basics.m b/Add-Ons/Tutorial_1_Basics.m new file mode 100644 index 0000000..ee18586 --- /dev/null +++ b/Add-Ons/Tutorial_1_Basics.m @@ -0,0 +1,145 @@ +clc; +clear; +close all; + +% ========================================================================= +% ===== Descriptions ====================================================== +% ========================================================================= + +Description = {... + 'This is a tutorial on how to use distFig. Hit enter in the workspace to continue to the next step and generate five figures.' + + 'By executing distFig(); with no arguments, the function will distribute all open and visible figures on the central screen. Hit enter to execute:' + 'Various arguments can be passed to the function to distribute the figures to different parts of the screen(s). Hit enter to distribute the figures in the western part of the screen by executing:' + 'Suppose you want to distribute the figures in five rows instead. Hit enter to execute:' + 'You can also distribute them in five columns instead. Hit enter to execute:' + 'You can also choose which figures to distribute. Hit enter to only distribute figure #1, #3 and #4 by executing:' + 'These can also be distributed in three rows by adding (''Rows'',3) to the function. Hit enter to execute:' + 'You can also choose to not distribute specific figures. Hit enter to distribute all but figure #5 by executing:' + 'Note how the figures are distributed in the columns at first, after which they restart in the next column in the top. Use (''Transpose'',true) to transpose the order, at which they are distributed. Hit enter to execute:' + + 'Suppose you only want to distriubute figure #1 to a specific place in the 2x2 pattern. Use input argument ''Offset'' to do so. We will use the eastern part of the screen for this. Hit enter to execute:' + 'Hit enter to offset it by 1 by executing:' + 'Hit enter to offset it by 2 by executing:' + 'Hit enter to offset it by 3 by executing:' + 'In order to do so, it is recommended to supply the number of column or rows, as the pattern will then be fixed. Otherwise the function will optimize the aspect ratio. This can be demonstrated by executing:' + 'Now figure #1 fills the whole area (''W''), but if all figures are distributed to this part of the screen, the pattern will change. Hit enter to execute:' + 'To demonstate the ''Offset'' feature again we add (''Offset'',1). Hit enter to execute:' + + 'Suppose you want to distribute figure #1 to the left and the remainding to the right. Do so by executing distFig two times using the ''Only'', ''Not'' and ''Offset'' arguments. Hit enter to execute:' + 'And the other way around by executing:' + + 'Get it? It might seem a little complicated, but it''ll catch on to you. If you have an external monitor you can distribute it by using ''Screen''. Hit enter to execute:' + 'You might have a warning now, if you don''t have an external monitor. You can also pass the direction of the monitor, if you have multiple external monitors.' + + 'Try and play around with the function by executing some of the used commands below:' + 'The function has other features as well, which are described in the function. To see a description of the various features execute:' + 'Please contact me, if you find any bugs/errors on AndersSSimonsen@GMail.com or write a comment on File Exchange. :)' + }; + +% ========================================================================= +% ===== Commands ========================================================== +% ========================================================================= + +Command = {... + {''} + + {'distFig();'} + {'distFig(''Pos'',''W'');'} + {'distFig(''Pos'',''W'',''Rows'',5);'} + {'distFig(''Pos'',''W'',''Columns'',5);'} + {'distFig(''Pos'',''W'',''Only'',[1,3,4]);'} + {'distFig(''Pos'',''W'',''Only'',[1,3,4],''Rows'',3);'} + {'distFig(''Pos'',''W'',''Not'',5);'} + {'distFig(''Pos'',''W'',''Not'',5,''Transpose'',true);'} + + {'distFig(''Pos'',''E'',''Only'',1,''Offset'',0,''Rows'',2,''Columns'',2);'} + {'distFig(''Pos'',''E'',''Only'',1,''Offset'',1,''Rows'',2,''Columns'',2);'} + {'distFig(''Pos'',''E'',''Only'',1,''Offset'',2,''Rows'',2,''Columns'',2);'} + {'distFig(''Pos'',''E'',''Only'',1,''Offset'',3,''Rows'',2,''Columns'',2);'} + {'distFig(''Pos'',''W'',''Only'',1);'} + {'distFig(''Pos'',''W'');'} + {'distFig(''Pos'',''W'',''Offset'',1);'} + + {'distFig(''Pos'',''W'',''Only'',1,''Columns'',2);','distFig(''Pos'',''W'',''Not'',1,''Rows'',4,''Columns'',2,''Offset'',4);'} + {'distFig(''Pos'',''W'',''Only'',1,''Rows'',2);','distFig(''Pos'',''W'',''Not'',1,''Rows'',2,''Columns'',4,''Offset'',4,''Transpose'',true);'} + + {'distFig(''Screen'',''External'');'} + {''} + + {'>>>ALL<<<'} + {'!help distFig'} + {''} + }; + +Trigger_All = numel(Command) - 2; +n = 0; +for i = 1:(Trigger_All - 1) + for j = 1:numel(Command{i}) + n = n + 1; + Command{Trigger_All}{n} = Command{i}{j}; + end +end + +% ========================================================================= +% ===== Steps ============================================================= +% ========================================================================= + +% ===== TextWidth ========================================================= +TextWidth = 60; + +for i = 1:numel(Description) + % ===== Description =================================================== + fprintf('===== Step %02.0f/%02.0f %s\n',i,numel(Description),repmat('=',1,TextWidth - 17)); + Str = ''; + while (1) + if (numel(Description{i}) >= TextWidth) + NewLine = regexp(Description{i}(1:TextWidth),'[ .]'); + Str = strcat(Str,Description{i}(1:NewLine(end)),'\n'); + Description{i}(1:NewLine(end) - 0) = []; + else + Str = strcat(Str,Description{i},'\n'); + break; + end + end + fprintf(Str); + + % ===== Command ======================================================= + if ~((isempty(Command{i}{1})) && (numel(Command{i}) == 1)) + for j = 1:numel(Command{i}) + if (numel(Command{i}{j}) ~= 0) + if (~strcmp(Command{i}{j}(1),'!')) + disp(sprintf('%s',Command{i}{j},Command{i}{j})); %#ok + else + disp(sprintf('%s',Command{i}{j}(2:end),Command{i}{j}(2:end))); %#ok + end + end + end + end + + % ===== Continue ====================================================== + input(''); + + % ===== Execute ======================================================= + if (~((isempty(Command{i}{1})) && (numel(Command{i}) == 1)) && (i ~= Trigger_All)) + for j = 1:numel(Command{i}) + if (numel(Command{i}{j}) ~= 0) + if (~strcmp(Command{i}{j}(1),'!')) + eval(sprintf(Command{i}{j})); + end + end + end + end + + % ===== Generate figures ============================================== + if (i == 1) + for j = 1:5 + figure('Color','w'); + text(0,0,num2str(j),'HorizontalAlignment','Center','FontSize',100,'Color',[0.9,0.9,1] * 0.25); + xlim([-1,1]); + ylim([-1,1]); + axis off; + set(gca,'XTick',[],'YTick',[]); + end + end +end \ No newline at end of file diff --git a/Add-Ons/Tutorial_2_Advanced.m b/Add-Ons/Tutorial_2_Advanced.m new file mode 100644 index 0000000..78b594d --- /dev/null +++ b/Add-Ons/Tutorial_2_Advanced.m @@ -0,0 +1,140 @@ +clc; +clear; +close all; + +% ========================================================================= +% ===== Descriptions ====================================================== +% ========================================================================= + +Description = {... + 'This is a tutorial on how to use some of the more advanced features of distFig. Hit enter in the workspace to continue to the next step and generate five figures.' + + 'Suppose you want to distribute the figures to the western part of the screen in two rows and two columns. Do so by executing:' + 'You can now only see figure #5 in the top left corner, which has been placed on top of figure #1. This is because the function restarts the pattern, when it runs out of space. The extra figure (#5) can be ignored by executing (We use the eastern part now):' + 'Note that you didn''t use the ''Only'' command, but instead you ignored the restart of the pattern. However, this can also be reproduced by executing either of the following, which do the same thing:' + + 'Suppose you want to distribute a figure so it spans the middle two rows in a four row pattern. This cannot be done by the standard features, but can be done with the ''Adjust'' command. This feature moves the whole pattern by a specified ammount. Move all figure to the north-western part by executing:' + 'Now, move the whole pattern by 100 pixels to the right and 200 pixels down by executing:' + 'Instead of moving them a specific number of pixels, you can use the same command with scalars from 0 to 1, which are realtive sizes of the selected monitor size. Move the whole pattern half a screen down by executing:' + 'The function detect automatically whether the input are integers or scalars. Now - returning to the case where one figure was supposed to span the middle two rows of a four row pattern. This can thus be done by executing:' + 'And let us position figure #2 and #3 on top and below figure #1 by executing the following two commands:' + 'Note how the ''Offset'' feature was used to position figure #3 by skipping the two rows, where figure #1 was placed.' + + 'distFig also features some minor function which are useful when positioning many figures (for instance 50). In such a case, it can be hard to see the actual figures due to the menu bar and the surrounding whitespace. The menu bars can be remove by executing:' + 'The whitespace can also be removed by making a tight fit around the figure. Do so by executing:' + + 'Now there is a lot more figure and a lot less crap. :)' + + 'The last feature of distFig is if you use Simulink. The figures from a Simulink model can be distributed by themself, along with the normal figures or completely ignored by executing one of the following:' + '(The above functions were not executed now) - try them out afterwards to see how our five figures are not distributed when executing the first one, where only Simulink figures are distributed.' + + 'Try and play around with the function by executing some of the used commands below:' + 'To see a description of the various features execute:' + 'Please contact me, if you find any bugs/errors on AndersSSimonsen@GMail.com or write a comment on File Exchange. :)' + }; + +% ========================================================================= +% ===== Commands ========================================================== +% ========================================================================= + +Command = {... + {''} + {'distFig(''Pos'',''W'',''Rows'',2,''Cols'',2'')'} + {'distFig(''Pos'',''E'',''Rows'',2,''Cols'',2'',''Extra'',''Ignore'')'} + {'distFig(''Pos'',''E'',''Rows'',2,''Cols'',2'',''Not'',5)','!distFig(''Pos'',''E'',''Rows'',2,''Cols'',2'',''Only'',[1,2,3,4])'} + + {'distFig(''Pos'',''NW'')'} + {'distFig(''Pos'',''NW'',''Adjust'',[100,-200])'} + {'distFig(''Pos'',''NW'',''Adjust'',[0,-0.5])'} + {'distFig(''Pos'',''E'',''Adjust'',[0,-0.25],''Only'',1,''Rows'',2)'} + {'distFig(''Pos'',''E'',''Only'',2,''Rows'',4)','distFig(''Pos'',''E'',''Only'',3,''Rows'',4,''Offset'',3)'} + {''} + + {'distFig(''Pos'',''W'',''Menu'',''none'')'} + {'distFig(''Pos'',''W'',''Tight'',true)'} + {''} + + {'!distFig(''Pos'',''W'',''Simulink'',''only'')','!distFig(''Pos'',''W'',''Simulink'',''include'')','!distFig(''Pos'',''W'',''Simulink'',''ignore'')'} + {''} + + {'>>>ALL<<<'} + {'!help distFig'} + {''} + }; + +Trigger_All = numel(Command) - 2; +n = 0; +for i = 1:(Trigger_All - 1) + for j = 1:numel(Command{i}) + n = n + 1; + Command{Trigger_All}{n} = Command{i}{j}; + end +end + +% ========================================================================= +% ===== Steps ============================================================= +% ========================================================================= + +% ===== TextWidth ========================================================= +TextWidth = 60; + +for i = 1:numel(Description) + % ===== Description =================================================== + fprintf('===== Step %02.0f/%02.0f %s\n',i,numel(Description),repmat('=',1,TextWidth - 17)); + Str = ''; + while (1) + if (numel(Description{i}) >= TextWidth) + NewLine = regexp(Description{i}(1:TextWidth),'[ .]'); + Str = strcat(Str,Description{i}(1:NewLine(end)),'\n'); + Description{i}(1:NewLine(end) - 0) = []; + else + Str = strcat(Str,Description{i},'\n'); + break; + end + end + fprintf(Str); + + % ===== Command ======================================================= + if ~((isempty(Command{i}{1})) && (numel(Command{i}) == 1)) + for j = 1:numel(Command{i}) + if (numel(Command{i}{j}) ~= 0) + if (~strcmp(Command{i}{j}(1),'!')) + disp(sprintf('%s',Command{i}{j},Command{i}{j})); %#ok + else + disp(sprintf('%s',Command{i}{j}(2:end),Command{i}{j}(2:end))); %#ok + end + end + end + end + + % ===== Continue ====================================================== + input(''); + + % ===== Execute ======================================================= + if (~((isempty(Command{i}{1})) && (numel(Command{i}) == 1)) && (i ~= Trigger_All)) + for j = 1:numel(Command{i}) + if (numel(Command{i}{j}) ~= 0) + if (~strcmp(Command{i}{j}(1),'!')) + eval(sprintf(Command{i}{j})); + end + end + end + end + + % ===== Generate figures ============================================== + if (i == 1) + for j = 1:5 + figure('Color','w'); + hold on; + plot(linspace(-1,1,100),sin(linspace(-1,1,100) * pi * j) * 0.25 + 0.75,'-','LineWidth',2); + plot(linspace(-1,1,100),-sin(linspace(-1,1,100) * pi * j) * 0.25 - 0.75,'-','LineWidth',2); + text(0,0,num2str(j),'HorizontalAlignment','Center','FontSize',100,'Color',[0.9,0.9,1] * 0.25,'BackGroundColor','w'); + hold off; + box on; + xlim([-1,1]); + ylim([-1,1]); + xlabel('XLabel'); + ylabel('YLabel'); + end + end +end \ No newline at end of file diff --git a/Add-Ons/arrow.m b/Add-Ons/arrow.m new file mode 100644 index 0000000..4c5c185 --- /dev/null +++ b/Add-Ons/arrow.m @@ -0,0 +1,1460 @@ +function [h,yy,zz] = arrow(varargin) +% ARROW Draw a line with an arrowhead. +% +% ARROW(Start,Stop) draws a line with an arrow from Start to Stop (points +% should be vectors of length 2 or 3, or matrices with 2 or 3 +% columns), and returns the graphics handle of the arrow(s). +% +% ARROW uses the mouse (click-drag) to create an arrow. +% +% ARROW DEMO & ARROW DEMO2 show 3-D & 2-D demos of the capabilities of ARROW. +% +% ARROW may be called with a normal argument list or a property-based list. +% ARROW(Start,Stop,Length,BaseAngle,TipAngle,Width,Page,CrossDir) is +% the full normal argument list, where all but the Start and Stop +% points are optional. If you need to specify a later argument (e.g., +% Page) but want default values of earlier ones (e.g., TipAngle), +% pass an empty matrix for the earlier ones (e.g., TipAngle=[]). +% +% ARROW('Property1',PropVal1,'Property2',PropVal2,...) creates arrows with the +% given properties, using default values for any unspecified or given as +% 'default' or NaN. Some properties used for line and patch objects are +% used in a modified fashion, others are passed directly to LINE, PATCH, +% or SET. For a detailed properties explanation, call ARROW PROPERTIES. +% +% Start The starting points. B +% Stop The end points. /|\ ^ +% Length Length of the arrowhead in pixels. /|||\ | +% BaseAngle Base angle in degrees (ADE). //|||\\ L| +% TipAngle Tip angle in degrees (ABC). ///|||\\\ e| +% Width Width of the base in pixels. ////|||\\\\ n| +% Page Use hardcopy proportions. /////|D|\\\\\ g| +% CrossDir Vector || to arrowhead plane. //// ||| \\\\ t| +% NormalDir Vector out of arrowhead plane. /// ||| \\\ h| +% Ends Which end has an arrowhead. //<----->|| \\ | +% ObjectHandles Vector of handles to update. / base ||| \ V +% E angle||<-------->C +% ARROW(H,'Prop1',PropVal1,...), where H is a |||tipangle +% vector of handles to previously-created arrows ||| +% and/or line objects, will update the previously- ||| +% created arrows according to the current view -->|A|<-- width +% and any specified properties, and will convert +% two-point line objects to corresponding arrows. ARROW(H) will update +% the arrows if the current view has changed. Root, figure, or axes +% handles included in H are replaced by all descendant Arrow objects. +% +% A property list can follow any specified normal argument list, e.g., +% ARROW([1 2 3],[0 0 0],36,'BaseAngle',60) creates an arrow from (1,2,3) to +% the origin, with an arrowhead of length 36 pixels and 60-degree base angle. +% +% Normally, an ARROW is a PATCH object, so any valid PATCH property/value pairs +% can be passed, e.g., ARROW(Start,Stop,'EdgeColor','r','FaceColor','g'). +% ARROW will use LINE objects when requested by ARROW(...,'Type','line') or, +% using LINE property/value pairs, ARROW(Start,Stop,'Type','line','Color','b'). +% +% The basic arguments or properties can generally be vectorized to create +% multiple arrows with the same call. This is done by passing a property +% with one row per arrow, or, if all arrows are to have the same property +% value, just one row may be specified. +% +% You may want to execute AXIS(AXIS) before calling ARROW so it doesn't change +% the axes on you; ARROW determines the sizes of arrow components BEFORE the +% arrow is plotted, so if ARROW changes axis limits, arrows may be malformed. +% +% This version of ARROW uses features of MATLAB 6.x and is incompatible with +% earlier MATLAB versions (ARROW for MATLAB 4.2c is available separately); +% some problems with perspective plots still exist. + +% Copyright (c)1995-2016, Dr. Erik A. Johnson , 5/25/2016 +% http://www.usc.edu/civil_eng/johnsone/ + +% Revision history: +% 5/25/16 EAJ Add documentation of 'Type','line' +% Add documentation of how to set color +% Add 'Color' property (which sets both 'EdgeColor' and 'FaceColor' for patch objects) +% 5/24/16 EAJ Remove 'EraseMode' in HG2 +% 7/16/14 EAJ R2014b HandleGraphics2 compatibility +% 7/14/14 EAJ 5/20/13 patch extension didn't work right in HG2 +% so break the arrow along its length instead +% 5/20/13 EAJ Extend patch line one more segment so EPS/PDF printed versions +% have nice rounded tips when the LineWidth is wider +% 2/06/13 EAJ Add ShortenLength property to shorten length if arrow is short +% 1/24/13 EAJ Remove some old comments. +% 5/20/09 EAJ Fix view direction in (3D) demo. +% 6/26/08 EAJ Replace eval('trycmd','catchcmd') with try, trycmd; catch, +% catchcmd; end; -- break's MATLAB 5 compatibility. +% 8/26/03 EAJ Eliminate OpenGL attempted fix since it didn't fix anyway. +% 11/15/02 EAJ Accomodate how MATLAB 6.5 handles NaN and logicals +% 7/28/02 EAJ Tried (but failed) work-around for MATLAB 6.x / OpenGL bug +% if zero 'Width' or not double-ended +% 11/10/99 EAJ Add logical() to eliminate zero index problem in MATLAB 5.3. +% 11/10/99 EAJ Corrected warning if axis limits changed on multiple axes. +% 11/10/99 EAJ Update e-mail address. +% 2/10/99 EAJ Some documentation updating. +% 2/24/98 EAJ Fixed bug if Start~=Stop but both colinear with viewpoint. +% 8/14/97 EAJ Added workaround for MATLAB 5.1 scalar logical transpose bug. +% 7/21/97 EAJ Fixed a few misc bugs. +% 7/14/97 EAJ Make arrow([],'Prop',...) do nothing (no old handles) +% 6/23/97 EAJ MATLAB 5 compatible version, release. +% 5/27/97 EAJ Added Line Arrows back in. Corrected a few bugs. +% 5/26/97 EAJ Changed missing Start/Stop to mouse-selected arrows. +% 5/19/97 EAJ MATLAB 5 compatible version, beta. +% 4/13/97 EAJ MATLAB 5 compatible version, alpha. +% 1/31/97 EAJ Fixed bug with multiple arrows and unspecified Z coords. +% 12/05/96 EAJ Fixed one more bug with log plots and NormalDir specified +% 10/24/96 EAJ Fixed bug with log plots and NormalDir specified +% 11/13/95 EAJ Corrected handling for 'reverse' axis directions +% 10/06/95 EAJ Corrected occasional conflict with SUBPLOT +% 4/24/95 EAJ A major rewrite. +% Fall 94 EAJ Original code. + +% Things to be done: +% - in the arrow_clicks section, prompt by printing to the screen so that +% the user knows what's going on; also make sure the figure is brought +% to the front. +% - segment parsing, computing, and plotting into separate subfunctions +% - change computing from Xform to Camera paradigms +% + this will help especially with 3-D perspective plots +% + if the WarpToFill section works right, remove warning code +% + when perpsective works properly, remove perspective warning code +% - add cell property values and struct property name/values (like get/set) +% - get rid of NaN as the "default" data label +% + perhaps change userdata to a struct and don't include (or leave +% empty) the values specified as default; or use a cell containing +% an empty matrix for a default value +% - add functionality of GET to retrieve current values of ARROW properties +% +% New list of things to be done: +% - rewrite as a graphics or class object that updates itself in real time +% (but have a 'Static' or 'DoNotUpdate' property to avoid updating) + +% Permission is granted to distribute ARROW with the toolboxes for the book +% "Solving Solid Mechanics Problems with MATLAB 5", by F. Golnaraghi et al. +% (Prentice Hall, 1999). + +% Permission is granted to Dr. Josef Bigun to distribute ARROW with his +% software to reproduce the figures in his image analysis text. + +% global variable initialization +persistent ARROW_PERSP_WARN ARROW_STRETCH_WARN ARROW_AXLIMITS ARROW_AX +if isempty(ARROW_PERSP_WARN ), ARROW_PERSP_WARN =1; end; +if isempty(ARROW_STRETCH_WARN), ARROW_STRETCH_WARN=1; end; + +% Handle callbacks +if (nargin>0 & isstr(varargin{1}) & strcmp(lower(varargin{1}),'callback')), + arrow_callback(varargin{2:end}); return; +end; + +% Are we doing the demo? +c = sprintf('\n'); +if (nargin==1 & isstr(varargin{1})), + arg1 = lower(varargin{1}); + if strncmp(arg1,'prop',4), arrow_props; + elseif strncmp(arg1,'demo',4) + clf reset + demo_info = arrow_demo; + if ~strncmp(arg1,'demo2',5), + hh=arrow_demo3(demo_info); + else, + hh=arrow_demo2(demo_info); + end; + if (nargout>=1), h=hh; end; + elseif strncmp(arg1,'fixlimits',3), + arrow_fixlimits(ARROW_AX,ARROW_AXLIMITS); + ARROW_AXLIMITS=[]; ARROW_AX=[]; + elseif strncmp(arg1,'help',4), + disp(help(mfilename)); + else, + error([upper(mfilename) ' got an unknown single-argument string ''' deblank(arg1) '''.']); + end; + return; +end; + +% Check # of arguments +if (nargout>3), error([upper(mfilename) ' produces at most 3 output arguments.']); end; + +% find first property number +firstprop = nargin+1; +for k=1:length(varargin), if ~isnumeric(varargin{k}) && ~all(ishandle(varargin{k})), firstprop=k; break; end; end; %eaj 5/24/16 for k=1:length(varargin), if ~isnumeric(varargin{k}), firstprop=k; break; end; end; +lastnumeric = firstprop-1; + +% check property list +if (firstprop<=nargin), + for k=firstprop:2:nargin, + curarg = varargin{k}; + if ~isstr(curarg) | sum(size(curarg)>1)>1, + error([upper(mfilename) ' requires that a property name be a single string.']); + end; + end; + if (rem(nargin-firstprop,2)~=1), + error([upper(mfilename) ' requires that the property ''' ... + varargin{nargin} ''' be paired with a property value.']); + end; +end; + +% default output +if (nargout>0), h=[]; end; +if (nargout>1), yy=[]; end; +if (nargout>2), zz=[]; end; + +% set values to empty matrices +start = []; +stop = []; +len = []; +baseangle = []; +tipangle = []; +wid = []; +page = []; +crossdir = []; +ends = []; +shorten = []; +ax = []; +oldh = []; +ispatch = []; +defstart = [NaN NaN NaN]; +defstop = [NaN NaN NaN]; +deflen = 16; +defbaseangle = 90; +deftipangle = 16; +defwid = 0; +defpage = 0; +defcrossdir = [NaN NaN NaN]; +defends = 1; +defshorten = 0; +defoldh = []; +defispatch = 1; + +% The 'Tag' we'll put on our arrows +ArrowTag = 'Arrow'; + +% check for oldstyle arguments +if (firstprop==2), + % assume arg1 is a set of handles + oldh = varargin{1}(:); + if isempty(oldh), return; end; +elseif (firstprop>9), + error([upper(mfilename) ' takes at most 8 non-property arguments.']); +elseif (firstprop>2), + {start,stop,len,baseangle,tipangle,wid,page,crossdir}; + args = [varargin(1:firstprop-1) cell(1,length(ans)-(firstprop-1))]; + [start,stop,len,baseangle,tipangle,wid,page,crossdir] = deal(args{:}); +end; + +% parse property pairs +extraprops={}; +for k=firstprop:2:nargin, + prop = varargin{k}; + val = varargin{k+1}; + prop = [lower(prop(:)') ' ']; + if strncmp(prop,'start' ,5), start = val; + elseif strncmp(prop,'stop' ,4), stop = val; + elseif strncmp(prop,'len' ,3), len = val(:); + elseif strncmp(prop,'base' ,4), baseangle = val(:); + elseif strncmp(prop,'tip' ,3), tipangle = val(:); + elseif strncmp(prop,'wid' ,3), wid = val(:); + elseif strncmp(prop,'page' ,4), page = val; + elseif strncmp(prop,'cross' ,5), crossdir = val; + elseif strncmp(prop,'norm' ,4), if (isstr(val)), crossdir=val; else, crossdir=val*sqrt(-1); end; + elseif strncmp(prop,'end' ,3), ends = val; + elseif strncmp(prop,'shorten',5), shorten = val; + elseif strncmp(prop,'object' ,6), oldh = val(:); + elseif strncmp(prop,'handle' ,6), oldh = val(:); + elseif strncmp(prop,'type' ,4), ispatch = val; + elseif strncmp(prop,'userd' ,5), %ignore it + else, + % make sure it is a valid patch or line property + try + get(0,['DefaultPatch' varargin{k}]); + catch + errstr = lasterr; + try + get(0,['DefaultLine' varargin{k}]); + catch + errstr(1:max(find(errstr==char(13)|errstr==char(10)))) = ''; + error([upper(mfilename) ' got ' errstr]); + end + end; + extraprops={extraprops{:},varargin{k},val}; + end; +end; + +% Check if we got 'default' values +start = arrow_defcheck(start ,defstart ,'Start' ); +stop = arrow_defcheck(stop ,defstop ,'Stop' ); +len = arrow_defcheck(len ,deflen ,'Length' ); +baseangle = arrow_defcheck(baseangle,defbaseangle,'BaseAngle' ); +tipangle = arrow_defcheck(tipangle ,deftipangle ,'TipAngle' ); +wid = arrow_defcheck(wid ,defwid ,'Width' ); +crossdir = arrow_defcheck(crossdir ,defcrossdir ,'CrossDir' ); +page = arrow_defcheck(page ,defpage ,'Page' ); +ends = arrow_defcheck(ends ,defends ,'' ); +shorten = arrow_defcheck(shorten ,defshorten ,'' ); +oldh = arrow_defcheck(oldh ,[] ,'ObjectHandles'); +ispatch = arrow_defcheck(ispatch ,defispatch ,'' ); + +% check transpose on arguments +[m,n]=size(start ); if any(m==[2 3])&(n==1|n>3), start = start'; end; +[m,n]=size(stop ); if any(m==[2 3])&(n==1|n>3), stop = stop'; end; +[m,n]=size(crossdir); if any(m==[2 3])&(n==1|n>3), crossdir = crossdir'; end; + +% convert strings to numbers +if ~isempty(ends) & isstr(ends), + endsorig = ends; + [m,n] = size(ends); + col = lower([ends(:,1:min(3,n)) ones(m,max(0,3-n))*' ']); + ends = NaN*ones(m,1); + oo = ones(1,m); + ii=find(all(col'==['non']'*oo)'); if ~isempty(ii), ends(ii)=ones(length(ii),1)*0; end; + ii=find(all(col'==['sto']'*oo)'); if ~isempty(ii), ends(ii)=ones(length(ii),1)*1; end; + ii=find(all(col'==['sta']'*oo)'); if ~isempty(ii), ends(ii)=ones(length(ii),1)*2; end; + ii=find(all(col'==['bot']'*oo)'); if ~isempty(ii), ends(ii)=ones(length(ii),1)*3; end; + if any(isnan(ends)), + ii = min(find(isnan(ends))); + error([upper(mfilename) ' does not recognize ''' deblank(endsorig(ii,:)) ''' as a valid ''Ends'' value.']); + end; +else, + ends = ends(:); +end; +if ~isempty(ispatch) & isstr(ispatch), + col = lower(ispatch(:,1)); + patchchar='p'; linechar='l'; defchar=' '; + mask = col~=patchchar & col~=linechar & col~=defchar; + if any(mask), + error([upper(mfilename) ' does not recognize ''' deblank(ispatch(min(find(mask)),:)) ''' as a valid ''Type'' value.']); + end; + ispatch = (col==patchchar)*1 + (col==linechar)*0 + (col==defchar)*defispatch; +else, + ispatch = ispatch(:); +end; +oldh = oldh(:); + +% check object handles +if ~all(ishandle(oldh)), error([upper(mfilename) ' got invalid object handles.']); end; + +% expand root, figure, and axes handles +if ~isempty(oldh), + ohtype = get(oldh,'Type'); + mask = strcmp(ohtype,'root') | strcmp(ohtype,'figure') | strcmp(ohtype,'axes'); + if any(mask), + oldh = num2cell(oldh); + for ii=find(mask)', + oldh(ii) = {findobj(oldh{ii},'Tag',ArrowTag)}; + end; + oldh = cat(1,oldh{:}); + if isempty(oldh), return; end; % no arrows to modify, so just leave + end; +end; + +% largest argument length +[mstart,junk]=size(start); [mstop,junk]=size(stop); [mcrossdir,junk]=size(crossdir); +argsizes = [length(oldh) mstart mstop ... + length(len) length(baseangle) length(tipangle) ... + length(wid) length(page) mcrossdir length(ends) length(shorten)]; +args=['length(ObjectHandle) '; ... + '#rows(Start) '; ... + '#rows(Stop) '; ... + 'length(Length) '; ... + 'length(BaseAngle) '; ... + 'length(TipAngle) '; ... + 'length(Width) '; ... + 'length(Page) '; ... + '#rows(CrossDir) '; ... + '#rows(Ends) '; ... + 'length(ShortenLength) ']; +if (any(imag(crossdir(:))~=0)), + args(9,:) = '#rows(NormalDir) '; +end; +if isempty(oldh), + narrows = max(argsizes); +else, + narrows = length(oldh); +end; +if (narrows<=0), narrows=1; end; + +% Check size of arguments +ii = find((argsizes~=0)&(argsizes~=1)&(argsizes~=narrows)); +if ~isempty(ii), + s = args(ii',:); + while ((size(s,2)>1)&((abs(s(:,size(s,2)))==0)|(abs(s(:,size(s,2)))==abs(' ')))), + s = s(:,1:size(s,2)-1); + end; + s = [ones(length(ii),1)*[upper(mfilename) ' requires that '] s ... + ones(length(ii),1)*[' equal the # of arrows (' num2str(narrows) ').' c]]; + s = s'; + s = s(:)'; + s = s(1:length(s)-1); + error(setstr(s)); +end; + +% check element length in Start, Stop, and CrossDir +if ~isempty(start), + [m,n] = size(start); + if (n==2), + start = [start NaN*ones(m,1)]; + elseif (n~=3), + error([upper(mfilename) ' requires 2- or 3-element Start points.']); + end; +end; +if ~isempty(stop), + [m,n] = size(stop); + if (n==2), + stop = [stop NaN*ones(m,1)]; + elseif (n~=3), + error([upper(mfilename) ' requires 2- or 3-element Stop points.']); + end; +end; +if ~isempty(crossdir), + [m,n] = size(crossdir); + if (n<3), + crossdir = [crossdir NaN*ones(m,3-n)]; + elseif (n~=3), + if (all(imag(crossdir(:))==0)), + error([upper(mfilename) ' requires 2- or 3-element CrossDir vectors.']); + else, + error([upper(mfilename) ' requires 2- or 3-element NormalDir vectors.']); + end; + end; +end; + +% fill empty arguments +if isempty(start ), start = [Inf Inf Inf]; end; +if isempty(stop ), stop = [Inf Inf Inf]; end; +if isempty(len ), len = Inf; end; +if isempty(baseangle ), baseangle = Inf; end; +if isempty(tipangle ), tipangle = Inf; end; +if isempty(wid ), wid = Inf; end; +if isempty(page ), page = Inf; end; +if isempty(crossdir ), crossdir = [Inf Inf Inf]; end; +if isempty(ends ), ends = Inf; end; +if isempty(shorten ), shorten = Inf; end; +if isempty(ispatch ), ispatch = Inf; end; + +% expand single-column arguments +o = ones(narrows,1); +if (size(start ,1)==1), start = o * start ; end; +if (size(stop ,1)==1), stop = o * stop ; end; +if (length(len )==1), len = o * len ; end; +if (length(baseangle )==1), baseangle = o * baseangle ; end; +if (length(tipangle )==1), tipangle = o * tipangle ; end; +if (length(wid )==1), wid = o * wid ; end; +if (length(page )==1), page = o * page ; end; +if (size(crossdir ,1)==1), crossdir = o * crossdir ; end; +if (length(ends )==1), ends = o * ends ; end; +if (length(shorten )==1), shorten = o * shorten ; end; +if (length(ispatch )==1), ispatch = o * ispatch ; end; +ax = repmat(gca,narrows,1); %eaj 7/16/14 ax=gca; if ~isnumeric(ax), ax=double(ax); end; ax=o*ax; + +% if we've got handles, get the defaults from the handles +if ~isempty(oldh), + for k=1:narrows, + oh = oldh(k); + ud = get(oh,'UserData'); + ax(k) = get(oh,'Parent'); %eaj 7/16/14 get(oh,'Parent'); if ~isnumeric(ans), double(ans); end; ax(k)=ans; + ohtype = get(oh,'Type'); + if strcmp(get(oh,'Tag'),ArrowTag), % if it's an arrow already + if isinf(ispatch(k)), ispatch(k)=strcmp(ohtype,'patch'); end; + % arrow UserData format: [start' stop' len base tip wid page crossdir' ends shorten] + start0 = ud(1:3); + stop0 = ud(4:6); + if (isinf(len(k))), len(k) = ud( 7); end; + if (isinf(baseangle(k))), baseangle(k) = ud( 8); end; + if (isinf(tipangle(k))), tipangle(k) = ud( 9); end; + if (isinf(wid(k))), wid(k) = ud(10); end; + if (isinf(page(k))), page(k) = ud(11); end; + if (isinf(crossdir(k,1))), crossdir(k,1) = ud(12); end; + if (isinf(crossdir(k,2))), crossdir(k,2) = ud(13); end; + if (isinf(crossdir(k,3))), crossdir(k,3) = ud(14); end; + if (isinf(ends(k))), ends(k) = ud(15); end; + if (isinf(shorten(k))), shorten(k) = ud(16); end; + elseif strcmp(ohtype,'line')|strcmp(ohtype,'patch'), % it's a non-arrow line or patch + convLineToPatch = 1; %set to make arrow patches when converting from lines. + if isinf(ispatch(k)), ispatch(k)=convLineToPatch|strcmp(ohtype,'patch'); end; + x=get(oh,'XData'); x=x(~isnan(x(:))); if isempty(x), x=NaN; end; + y=get(oh,'YData'); y=y(~isnan(y(:))); if isempty(y), y=NaN; end; + z=get(oh,'ZData'); z=z(~isnan(z(:))); if isempty(z), z=NaN; end; + start0 = [x(1) y(1) z(1) ]; + stop0 = [x(end) y(end) z(end)]; + else, + error([upper(mfilename) ' cannot convert ' ohtype ' objects.']); + end; + ii=find(isinf(start(k,:))); if ~isempty(ii), start(k,ii)=start0(ii); end; + ii=find(isinf(stop( k,:))); if ~isempty(ii), stop( k,ii)=stop0( ii); end; + end; +end; + +% convert Inf's to NaN's +start( isinf(start )) = NaN; +stop( isinf(stop )) = NaN; +len( isinf(len )) = NaN; +baseangle( isinf(baseangle)) = NaN; +tipangle( isinf(tipangle )) = NaN; +wid( isinf(wid )) = NaN; +page( isinf(page )) = NaN; +crossdir( isinf(crossdir )) = NaN; +ends( isinf(ends )) = NaN; +shorten( isinf(shorten )) = NaN; +ispatch( isinf(ispatch )) = NaN; + +% set up the UserData data (here so not corrupted by log10's and such) +ud = [start stop len baseangle tipangle wid page crossdir ends shorten]; + +% Set Page defaults +page = ~isnan(page) & trueornan(page); + +% Get axes limits, range, min; correct for aspect ratio and log scale +axm = zeros(3,narrows); +axr = zeros(3,narrows); +axrev = zeros(3,narrows); +ap = zeros(2,narrows); +xyzlog = zeros(3,narrows); +limmin = zeros(2,narrows); +limrange = zeros(2,narrows); +oldaxlims = zeros(6,narrows); +oneax = all(ax==ax(1)); +if (oneax), + T = zeros(4,4); + invT = zeros(4,4); +else, + T = zeros(16,narrows); + invT = zeros(16,narrows); +end; +axnotdone = true(size(ax)); +while (any(axnotdone)), + ii = find(axnotdone,1); + curax = ax(ii); + curpage = page(ii); + % get axes limits and aspect ratio + axl = [get(curax,'XLim'); get(curax,'YLim'); get(curax,'ZLim')]; + ax==curax; oldaxlims(:,ans)=repmat(reshape(axl',[],1),1,sum(ans)); + % get axes size in pixels (points) + u = get(curax,'Units'); + axposoldunits = get(curax,'Position'); + really_curpage = curpage & strcmp(u,'normalized'); + if (really_curpage), + curfig = get(curax,'Parent'); + pu = get(curfig,'PaperUnits'); + set(curfig,'PaperUnits','points'); + pp = get(curfig,'PaperPosition'); + set(curfig,'PaperUnits',pu); + set(curax,'Units','pixels'); + curapscreen = get(curax,'Position'); + set(curax,'Units','normalized'); + curap = pp.*get(curax,'Position'); + else, + set(curax,'Units','pixels'); + curapscreen = get(curax,'Position'); + curap = curapscreen; + end; + set(curax,'Units',u); + set(curax,'Position',axposoldunits); + % handle non-stretched axes position + str_stretch = { 'DataAspectRatioMode' ; ... + 'PlotBoxAspectRatioMode' ; ... + 'CameraViewAngleMode' }; + str_camera = { 'CameraPositionMode' ; ... + 'CameraTargetMode' ; ... + 'CameraViewAngleMode' ; ... + 'CameraUpVectorMode' }; + notstretched = strcmp(get(curax,str_stretch),'manual'); + manualcamera = strcmp(get(curax,str_camera),'manual'); + if ~arrow_WarpToFill(notstretched,manualcamera,curax), + % give a warning that this has not been thoroughly tested + if 0 & ARROW_STRETCH_WARN, + ARROW_STRETCH_WARN = 0; + strs = {str_stretch{1:2},str_camera{:}}; + strs = [char(ones(length(strs),1)*sprintf('\n ')) char(strs)]'; + warning([upper(mfilename) ' may not yet work quite right ' ... + 'if any of the following are ''manual'':' strs(:).']); + end; + % find the true pixel size of the actual axes + texttmp = text(axl(1,[1 2 2 1 1 2 2 1]), ... + axl(2,[1 1 2 2 1 1 2 2]), ... + axl(3,[1 1 1 1 2 2 2 2]),''); + set(texttmp,'Units','points'); + textpos = get(texttmp,'Position'); + delete(texttmp); + textpos = cat(1,textpos{:}); + textpos = max(textpos(:,1:2)) - min(textpos(:,1:2)); + % adjust the axes position + if (really_curpage), + % adjust to printed size + textpos = textpos * min(curap(3:4)./textpos); + curap = [curap(1:2)+(curap(3:4)-textpos)/2 textpos]; + else, + % adjust for pixel roundoff + textpos = textpos * min(curapscreen(3:4)./textpos); + curap = [curap(1:2)+(curap(3:4)-textpos)/2 textpos]; + end; + end; + if ARROW_PERSP_WARN & ~strcmp(get(curax,'Projection'),'orthographic'), + ARROW_PERSP_WARN = 0; + warning([upper(mfilename) ' does not yet work right for 3-D perspective projection.']); + end; + % adjust limits for log scale on axes + curxyzlog = strcmp(get(curax,{'XScale' 'YScale' 'ZScale'})','log'); + if (any(curxyzlog)), + ii = find([curxyzlog;curxyzlog]); + if (any(axl(ii)<=0)), + error([upper(mfilename) ' does not support non-positive limits on log-scaled axes.']); + else, + axl(ii) = log10(axl(ii)); + end; + end; + % correct for 'reverse' direction on axes; + curreverse = strcmp(get(curax,{'XDir' 'YDir' 'ZDir'})','reverse'); + ii = find(curreverse); + if ~isempty(ii), + axl(ii,[1 2])=-axl(ii,[2 1]); + end; + % compute the range of 2-D values + try, curT=get(curax,'Xform'); catch, num2cell(get(curax,'View')); curT=viewmtx(ans{:}); end; + lim = curT*[0 1 0 1 0 1 0 1;0 0 1 1 0 0 1 1;0 0 0 0 1 1 1 1;1 1 1 1 1 1 1 1]; + lim = lim(1:2,:)./([1;1]*lim(4,:)); + curlimmin = min(lim')'; + curlimrange = max(lim')' - curlimmin; + curinvT = inv(curT); + if (~oneax), + curT = curT.'; + curinvT = curinvT.'; + curT = curT(:); + curinvT = curinvT(:); + end; + % check which arrows to which cur corresponds + ii = find((ax==curax)&(page==curpage)); + oo = ones(1,length(ii)); + axr(:,ii) = diff(axl')' * oo; + axm(:,ii) = axl(:,1) * oo; + axrev(:,ii) = curreverse * oo; + ap(:,ii) = curap(3:4)' * oo; + xyzlog(:,ii) = curxyzlog * oo; + limmin(:,ii) = curlimmin * oo; + limrange(:,ii) = curlimrange * oo; + if (oneax), + T = curT; + invT = curinvT; + else, + T(:,ii) = curT * oo; + invT(:,ii) = curinvT * oo; + end; + axnotdone(ii) = zeros(1,length(ii)); +end; + +% correct for log scales +curxyzlog = xyzlog.'; +ii = find(curxyzlog(:)); +if ~isempty(ii), + start( ii) = real(log10(start( ii))); + stop( ii) = real(log10(stop( ii))); + if (all(imag(crossdir)==0)), % pulled (ii) subscript on crossdir, 12/5/96 eaj + crossdir(ii) = real(log10(crossdir(ii))); + end; +end; + +% correct for reverse directions +ii = find(axrev.'); +if ~isempty(ii), + start( ii) = -start( ii); + stop( ii) = -stop( ii); + crossdir(ii) = -crossdir(ii); +end; + +% transpose start/stop values +start = start.'; +stop = stop.'; + +% take care of defaults, page was done above +ii=find(isnan(start(:) )); if ~isempty(ii), start(ii) = axm(ii)+axr(ii)/2; end; +ii=find(isnan(stop(:) )); if ~isempty(ii), stop(ii) = axm(ii)+axr(ii)/2; end; +ii=find(isnan(crossdir(:) )); if ~isempty(ii), crossdir(ii) = zeros(length(ii),1); end; +ii=find(isnan(len )); if ~isempty(ii), len(ii) = ones(length(ii),1)*deflen; end; +ii=find(isnan(baseangle )); if ~isempty(ii), baseangle(ii) = ones(length(ii),1)*defbaseangle; end; +ii=find(isnan(tipangle )); if ~isempty(ii), tipangle(ii) = ones(length(ii),1)*deftipangle; end; +ii=find(isnan(wid )); if ~isempty(ii), wid(ii) = ones(length(ii),1)*defwid; end; +ii=find(isnan(ends )); if ~isempty(ii), ends(ii) = ones(length(ii),1)*defends; end; +ii=find(isnan(shorten )); if ~isempty(ii), shorten(ii) = ones(length(ii),1)*defshorten; end; + +% transpose rest of values +len = len.'; +baseangle = baseangle.'; +tipangle = tipangle.'; +wid = wid.'; +page = page.'; +crossdir = crossdir.'; +ends = ends.'; +shorten = shorten.'; +ax = ax.'; + +% given x, a 3xN matrix of points in 3-space; +% want to convert to X, the corresponding 4xN 2-space matrix +% +% tmp1=[(x-axm)./axr; ones(1,size(x,1))]; +% if (oneax), X=T*tmp1; +% else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=T.*tmp1; +% tmp2=zeros(4,4*N); tmp2(:)=tmp1(:); +% X=zeros(4,N); X(:)=sum(tmp2)'; end; +% X = X ./ (ones(4,1)*X(4,:)); + +% for all points with start==stop, start=stop-(verysmallvalue)*(up-direction); +ii = find(all(start==stop)); +if ~isempty(ii), + % find an arrowdir vertical on screen and perpendicular to viewer + % transform to 2-D + tmp1 = [(stop(:,ii)-axm(:,ii))./axr(:,ii);ones(1,length(ii))]; + if (oneax), twoD=T*tmp1; + else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=T(:,ii).*tmp1; + tmp2=zeros(4,4*length(ii)); tmp2(:)=tmp1(:); + twoD=zeros(4,length(ii)); twoD(:)=sum(tmp2)'; end; + twoD=twoD./(ones(4,1)*twoD(4,:)); + % move the start point down just slightly + tmp1 = twoD + [0;-1/1000;0;0]*(limrange(2,ii)./ap(2,ii)); + % transform back to 3-D + if (oneax), threeD=invT*tmp1; + else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=invT(:,ii).*tmp1; + tmp2=zeros(4,4*length(ii)); tmp2(:)=tmp1(:); + threeD=zeros(4,length(ii)); threeD(:)=sum(tmp2)'; end; + start(:,ii) = (threeD(1:3,:)./(ones(3,1)*threeD(4,:))).*axr(:,ii)+axm(:,ii); +end; + +% compute along-arrow points +% transform Start points + tmp1=[(start-axm)./axr;ones(1,narrows)]; + if (oneax), X0=T*tmp1; + else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=T.*tmp1; + tmp2=zeros(4,4*narrows); tmp2(:)=tmp1(:); + X0=zeros(4,narrows); X0(:)=sum(tmp2)'; end; + X0=X0./(ones(4,1)*X0(4,:)); +% transform Stop points + tmp1=[(stop-axm)./axr;ones(1,narrows)]; + if (oneax), Xf=T*tmp1; + else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=T.*tmp1; + tmp2=zeros(4,4*narrows); tmp2(:)=tmp1(:); + Xf=zeros(4,narrows); Xf(:)=sum(tmp2)'; end; + Xf=Xf./(ones(4,1)*Xf(4,:)); +% compute pixel distance between points + D = sqrt(sum(((Xf(1:2,:)-X0(1:2,:)).*(ap./limrange)).^2)); + D = D + (D==0); %eaj new 2/24/98 +% shorten the length if requested % added 2/6/2013 + numends = (ends==1) + (ends==2) + 2*(ends==3); + mask = shorten & D0 + ii = find(strcmpi(extraprops(1:2:end),'color')); %eaj 5/25/16 + ispatch = strcmp(get(H,'Type'),'patch'); + %eaj start 5/25/16 + while ~isempty(ii) && any(ispatch) + if ii>1, set(H,extraprops{1:2*ii-2}); end; + c = extraprops{2*ii}; + extraprops(1:2*ii) = []; + ii(1) = []; + if all(ispatch) || ischar(c)&&size(c,1)==1 || isnumeric(c)&&isequal(size(c),[1 3]) + set(H,'EdgeColor',c,'FaceColor',c) + elseif iscell(c) && numel(c)~=numel(H) + set(H(ispatch),'EdgeColor',c(ispatch),'FaceColor',c(ispatch)); + set(H(~ispatch),'Color',c(~ispatch)); + elseif isnumeric(c) && isequal(size(c),[numel(H) 3]) + set(H(ispatch),'EdgeColor',num2cell(c(ispatch,:),2),'FaceColor',num2cell(c(ispatch,:),2)); + set(H(~ispatch),'Color',num2cell(c(~ispatch,:),2)); + else + warning('ignoring unknown or invalid ''Color'' specification'); + end + end + if ~isempty(extraprops) + %eaj end 5/25/16 + set(H,extraprops{:}); + end %eaj 5/25/16 + end + % handle choosing arrow Start and/or Stop locations if unspecified + [H,oldaxlims,errstr] = arrow_clicks(H,ud,x,y,z,ax,oldaxlims); + if ~isempty(errstr), error([upper(mfilename) ' got ' errstr]); end; + % set the output + if (nargout>0), h=H; end; + % make sure the axis limits did not change + if isempty(oldaxlims), + ARROW_AXLIMITS = []; + ARROW_AX = []; + else, + lims = get(ax(:),{'XLim','YLim','ZLim'})'; + lims = reshape(cat(2,lims{:}),6,size(lims,2)); + mask = arrow_is2DXY(ax(:)); + oldaxlims(5:6,mask) = lims(5:6,mask); + % store them for possible restoring + mask = any(oldaxlims~=lims,1); ARROW_AX=ax(mask); ARROW_AXLIMITS=oldaxlims(:,mask); + if any(mask), + warning(arrow_warnlimits(ARROW_AX,narrows)); + end; + end; +else, + % don't create the patch, just return the data + h=x; + yy=y; + zz=z; +end; + + + +function out = arrow_defcheck(in,def,prop) +% check if we got 'default' values + out = in; + if ~isstr(in), return; end; + if size(in,1)==1 & strncmp(lower(in),'def',3), + out = def; + elseif ~isempty(prop), + error([upper(mfilename) ' does not recognize ''' in(:)' ''' as a valid ''' prop ''' string.']); + end; + + + +function [H,oldaxlims,errstr] = arrow_clicks(H,ud,x,y,z,ax,oldaxlims) +% handle choosing arrow Start and/or Stop locations if necessary + errstr = ''; + if isempty(H)|isempty(ud)|isempty(x), return; end; + % determine which (if any) need Start and/or Stop + needStart = all(isnan(ud(:,1:3)'))'; + needStop = all(isnan(ud(:,4:6)'))'; + mask = any(needStart|needStop); + if ~any(mask), return; end; + ud(~mask,:)=[]; ax(:,~mask)=[]; + x(:,~mask)=[]; y(:,~mask)=[]; z(:,~mask)=[]; + % make them invisible for the time being + set(H,'Visible','off'); + % save the current axes and limits modes; set to manual for the time being + oldAx = gca; + limModes=get(ax(:),{'XLimMode','YLimMode','ZLimMode'}); + set(ax(:),{'XLimMode','YLimMode','ZLimMode'},{'manual','manual','manual'}); + % loop over each arrow that requires attention + jj = find(mask); + for ii=1:length(jj), + h = H(jj(ii)); + axes(ax(ii)); + % figure out correct call + if needStart(ii), prop='Start'; else, prop='Stop'; end; + [wasInterrupted,errstr] = arrow_click(needStart(ii)&needStop(ii),h,prop,ax(ii)); + % handle errors and control-C + if wasInterrupted, + delete(H(jj(ii:end))); + H(jj(ii:end))=[]; + oldaxlims(jj(ii:end),:)=[]; + break; + end; + end; + % restore the axes and limit modes + axes(oldAx); + set(ax(:),{'XLimMode','YLimMode','ZLimMode'},limModes); + +function [wasInterrupted,errstr] = arrow_click(lockStart,H,prop,ax) +% handle the clicks for one arrow + fig = get(ax,'Parent'); + % save some things + oldFigProps = {'Pointer','WindowButtonMotionFcn','WindowButtonUpFcn'}; + oldFigValue = get(fig,oldFigProps); + oldArrowProps = {'EraseMode'}; + if ~isnumeric(fig), oldArrowProps={}; end %eaj 5/24/16 % only use in HG2 + oldArrowValue = get(H,oldArrowProps); + if isnumeric(fig), %eaj 5/24/16 + set(H,'EraseMode','background'); %because 'xor' makes shaft invisible unless Width>1 -- only use in HG2 + end %eaj 5/24/16 + global ARROW_CLICK_H ARROW_CLICK_PROP ARROW_CLICK_AX ARROW_CLICK_USE_Z + ARROW_CLICK_H=H; ARROW_CLICK_PROP=prop; ARROW_CLICK_AX=ax; + ARROW_CLICK_USE_Z=~arrow_is2DXY(ax)|~arrow_planarkids(ax); + set(fig,'Pointer','crosshair'); + % set up the WindowButtonMotion so we can see the arrow while moving around + set(fig,'WindowButtonUpFcn','set(gcf,''WindowButtonUpFcn'','''')', ... + 'WindowButtonMotionFcn',''); + if ~lockStart, + set(H,'Visible','on'); + set(fig,'WindowButtonMotionFcn',[mfilename '(''callback'',''motion'');']); + end; + % wait for the button to be pressed + [wasKeyPress,wasInterrupted,errstr] = arrow_wfbdown(fig); + % if we wanted to click-drag, set the Start point + if lockStart & ~wasInterrupted, + pt = arrow_point(ARROW_CLICK_AX,ARROW_CLICK_USE_Z); + feval(mfilename,H,'Start',pt,'Stop',pt); + set(H,'Visible','on'); + ARROW_CLICK_PROP='Stop'; + set(fig,'WindowButtonMotionFcn',[mfilename '(''callback'',''motion'');']); + % wait for the mouse button to be released + try + waitfor(fig,'WindowButtonUpFcn',''); + catch + errstr = lasterr; + wasInterrupted = 1; + end; + end; + if ~wasInterrupted, feval(mfilename,'callback','motion'); end; + % restore some things + set(gcf,oldFigProps,oldFigValue); + set(H,oldArrowProps,oldArrowValue); + +function arrow_callback(varargin) +% handle redrawing callbacks + if nargin==0, return; end; + str = varargin{1}; + if ~isstr(str), error([upper(mfilename) ' got an invalid Callback command.']); end; + s = lower(str); + if strcmp(s,'motion'), + % motion callback + global ARROW_CLICK_H ARROW_CLICK_PROP ARROW_CLICK_AX ARROW_CLICK_USE_Z + feval(mfilename,ARROW_CLICK_H,ARROW_CLICK_PROP,arrow_point(ARROW_CLICK_AX,ARROW_CLICK_USE_Z)); + drawnow; + else, + error([upper(mfilename) ' does not recognize ''' str(:).' ''' as a valid Callback option.']); + end; + +function out = arrow_point(ax,use_z) +% return the point on the given axes + if nargin==0, ax=gca; end; + if nargin<2, use_z=~arrow_is2DXY(ax)|~arrow_planarkids(ax); end; + out = get(ax,'CurrentPoint'); + out = out(1,:); + if ~use_z, out=out(1:2); end; + +function [wasKeyPress,wasInterrupted,errstr] = arrow_wfbdown(fig) +% wait for button down ignoring object ButtonDownFcn's + if nargin==0, fig=gcf; end; + errstr = ''; + % save ButtonDownFcn values + objs = findobj(fig); + buttonDownFcns = get(objs,'ButtonDownFcn'); + mask=~strcmp(buttonDownFcns,''); objs=objs(mask); buttonDownFcns=buttonDownFcns(mask); + set(objs,'ButtonDownFcn',''); + % save other figure values + figProps = {'KeyPressFcn','WindowButtonDownFcn'}; + figValue = get(fig,figProps); + % do the real work + set(fig,'KeyPressFcn','set(gcf,''KeyPressFcn'','''',''WindowButtonDownFcn'','''');', ... + 'WindowButtonDownFcn','set(gcf,''WindowButtonDownFcn'','''')'); + lasterr(''); + try + waitfor(fig,'WindowButtonDownFcn',''); + wasInterrupted = 0; + catch + wasInterrupted = 1; + end + wasKeyPress = ~wasInterrupted & strcmp(get(fig,'KeyPressFcn'),''); + if wasInterrupted, errstr=lasterr; end; + % restore ButtonDownFcn and other figure values + set(objs,'ButtonDownFcn',buttonDownFcns); + set(fig,figProps,figValue); + + + +function [out,is2D] = arrow_is2DXY(ax) +% check if axes are 2-D X-Y plots + % may not work for modified camera angles, etc. + out = false(size(ax)); % 2-D X-Y plots + is2D = out; % any 2-D plots + views = get(ax(:),{'View'}); + views = cat(1,views{:}); + out(:) = abs(views(:,2))==90; + is2D(:) = out(:) | all(rem(views',90)==0)'; + +function out = arrow_planarkids(ax) +% check if axes descendents all have empty ZData (lines,patches,surfaces) + out = true(size(ax)); + allkids = get(ax(:),{'Children'}); + for k=1:length(allkids), + kids = get([findobj(allkids{k},'flat','Type','line') + findobj(allkids{k},'flat','Type','patch') + findobj(allkids{k},'flat','Type','surface')],{'ZData'}); + for j=1:length(kids), + if ~isempty(kids{j}), out(k)=logical(0); break; end; + end; + end; + + + +function arrow_fixlimits(ax,lims) +% reset the axis limits as necessary + if isempty(ax) || isempty(lims), disp([upper(mfilename) ' does not remember any axis limits to reset.']); end; + for k=1:numel(ax), + if any(get(ax(k),'XLim')~=lims(1:2,k)'), set(ax(k),'XLim',lims(1:2,k)'); end; + if any(get(ax(k),'YLim')~=lims(3:4,k)'), set(ax(k),'YLim',lims(3:4,k)'); end; + if any(get(ax(k),'ZLim')~=lims(5:6,k)'), set(ax(k),'ZLim',lims(5:6,k)'); end; + end; + + + +function out = arrow_WarpToFill(notstretched,manualcamera,curax) +% check if we are in "WarpToFill" mode. + out = strcmp(get(curax,'WarpToFill'),'on'); + % 'WarpToFill' is undocumented, so may need to replace this by + % out = ~( any(notstretched) & any(manualcamera) ); + + + +function out = arrow_warnlimits(ax,narrows) +% create a warning message if we've changed the axis limits + msg = ''; + switch (numel(ax)) + case 1, msg=''; + case 2, msg='on two axes '; + otherwise, msg='on several axes '; + end; + msg = [upper(mfilename) ' changed the axis limits ' msg ... + 'when adding the arrow']; + if (narrows>1), msg=[msg 's']; end; + out = [msg '.' sprintf('\n') ' Call ' upper(mfilename) ... + ' FIXLIMITS to reset them now.']; + + + +function arrow_copyprops(fm,to) +% copy line properties to patches + props = {'EraseMode','LineStyle','LineWidth','Marker','MarkerSize',... + 'MarkerEdgeColor','MarkerFaceColor','ButtonDownFcn', ... + 'Clipping','DeleteFcn','BusyAction','HandleVisibility', ... + 'Selected','SelectionHighlight','Visible'}; + if ~isnumeric(findobj('Type','root')), props(strcmp(props,'EraseMode'))=[]; end; %eaj 5/24/16 + lineprops = {'Color', props{:}}; + patchprops = {'EdgeColor',props{:}}; + patch2props = {'FaceColor',patchprops{:}}; + fmpatch = strcmp(get(fm,'Type'),'patch'); + topatch = strcmp(get(to,'Type'),'patch'); + set(to( fmpatch& topatch),patch2props,get(fm( fmpatch& topatch),patch2props)); %p->p + set(to(~fmpatch&~topatch),lineprops, get(fm(~fmpatch&~topatch),lineprops )); %l->l + set(to( fmpatch&~topatch),lineprops, get(fm( fmpatch&~topatch),patchprops )); %p->l + set(to(~fmpatch& topatch),patchprops, get(fm(~fmpatch& topatch),lineprops) ,'FaceColor','none'); %l->p + + + +function arrow_props +% display further help info about ARROW properties + c = sprintf('\n'); + disp([c ... + 'ARROW Properties: Default values are given in [square brackets], and other' c ... + ' acceptable equivalent property names are in (parenthesis).' c c ... + ' Start The starting points. For N arrows, B' c ... + ' this should be a Nx2 or Nx3 matrix. /|\ ^' c ... + ' Stop The end points. For N arrows, this /|||\ |' c ... + ' should be a Nx2 or Nx3 matrix. //|||\\ L|' c ... + ' Length Length of the arrowhead (in pixels on ///|||\\\ e|' c ... + ' screen, points on a page). [16] (Len) ////|||\\\\ n|' c ... + ' BaseAngle Angle (degrees) of the base angle /////|D|\\\\\ g|' c ... + ' ADE. For a simple stick arrow, use //// ||| \\\\ t|' c ... + ' BaseAngle=TipAngle. [90] (Base) /// ||| \\\ h|' c ... + ' TipAngle Angle (degrees) of tip angle ABC. //<----->|| \\ |' c ... + ' [16] (Tip) / base ||| \ V' c ... + ' Width Width of the base in pixels. Not E angle ||<-------->C' c ... + ' the ''LineWidth'' prop. [0] (Wid) |||tipangle' c ... + ' Page If provided, non-empty, and not NaN, |||' c ... + ' this causes ARROW to use hardcopy |||' c ... + ' rather than onscreen proportions. A' c ... + ' This is important if screen aspect --> <-- width' c ... + ' ratio and hardcopy aspect ratio are ----CrossDir---->' c ... + ' vastly different. []' c... + ' CrossDir A vector giving the direction towards which the fletches' c ... + ' on the arrow should go. [computed such that it is perpen-' c ... + ' dicular to both the arrow direction and the view direction' c ... + ' (i.e., as if it was pasted on a normal 2-D graph)] (Note' c ... + ' that CrossDir is a vector. Also note that if an axis is' c ... + ' plotted on a log scale, then the corresponding component' c ... + ' of CrossDir must also be set appropriately, i.e., to 1 for' c ... + ' no change in that direction, >1 for a positive change, >0' c ... + ' and <1 for negative change.)' c ... + ' NormalDir A vector normal to the fletch direction (CrossDir is then' c ... + ' computed by the vector cross product [Line]x[NormalDir]). []' c ... + ' (Note that NormalDir is a vector. Unlike CrossDir,' c ... + ' NormalDir is used as is regardless of log-scaled axes.)' c ... + ' Ends Set which end has an arrowhead. Valid values are ''none'',' c ... + ' ''stop'', ''start'', and ''both''. [''stop''] (End)' c... + ' ShortenLength Shorten length of arrowhead(s) if line is too short' c ... + ' ObjectHandles Vector of handles to previously-created arrows to be' c ... + ' updated or line objects to be converted to arrows.' c ... + ' [] (Object,Handle)' c ... + ' Type ''patch'' creates the arrow with a PATCH object (the default)' c ... + ' and ''line'' creates it with a LINE object [''patch''].' c ... + ' Color For patch arrows (the default), set both ''FaceColor'' and' c ... + ' ''EdgeColor'' to the given value. For line arrows, set' c ... + ' the ''Color'' property to the given value.' c ... + ]); + + + +function out = arrow_demo + % demo + % create the data + [x,y,z] = peaks; + [ddd,out.iii]=max(z(:)); + out.axlim = [min(x(:)) max(x(:)) min(y(:)) max(y(:)) min(z(:)) max(z(:))]; + + % modify it by inserting some NaN's + [m,n] = size(z); + m = floor(m/2); + n = floor(n/2); + z(1:m,1:n) = NaN*ones(m,n); + + % graph it + clf('reset'); + out.hs=surf(x,y,z); + out.x=x; out.y=y; out.z=z; + xlabel('x'); ylabel('y'); + +function h = arrow_demo3(in) + % set the view + axlim = in.axlim; + axis(axlim); + zlabel('z'); + %set(in.hs,'FaceColor','interp'); + view(3); % view(viewmtx(-37.5,30,20)); + title(['Demo of the capabilities of the ARROW function in 3-D']); + + % Normal blue arrow + h1 = feval(mfilename,[axlim(1) axlim(4) 4],[-.8 1.2 4], ... + 'EdgeColor','b','FaceColor','b'); + + % Normal white arrow, clipped by the surface + h2 = feval(mfilename,axlim([1 4 6]),[0 2 4]); + t=text(-2.4,2.7,7.7,'arrow clipped by surf'); + + % Baseangle<90 + h3 = feval(mfilename,[3 .125 3.5],[1.375 0.125 3.5],30,50); + t2=text(3.1,.125,3.5,'local maximum'); + + % Baseangle<90, fill and edge colors different + h4 = feval(mfilename,axlim(1:2:5)*.5,[0 0 0],36,60,25, ... + 'EdgeColor','b','FaceColor','c'); + t3=text(axlim(1)*.5,axlim(3)*.5,axlim(5)*.5-.75,'origin'); + set(t3,'HorizontalAlignment','center'); + + % Baseangle>90, black fill + h5 = feval(mfilename,[-2.9 2.9 3],[-1.3 .4 3.2],30,120,[],6, ... + 'EdgeColor','r','FaceColor','k','LineWidth',2); + + % Baseangle>90, no fill + h6 = feval(mfilename,[-2.9 2.9 1.3],[-1.3 .4 1.5],30,120,[],6, ... + 'EdgeColor','r','FaceColor','none','LineWidth',2); + + % Stick arrow + h7 = feval(mfilename,[-1.6 -1.65 -6.5],[0 -1.65 -6.5],[],16,16); + t4=text(-1.5,-1.65,-7.25,'global mininum'); + set(t4,'HorizontalAlignment','center'); + + % Normal, black fill + h8 = feval(mfilename,[-1.4 0 -7.2],[-1.4 0 -3],'FaceColor','k'); + t5=text(-1.5,0,-7.75,'local minimum'); + set(t5,'HorizontalAlignment','center'); + + % Gray fill, crossdir specified, 'LineStyle' -- + h9 = feval(mfilename,[-3 2.2 -6],[-3 2.2 -.05],36,[],27,6,[],[0 -1 0], ... + 'EdgeColor','k','FaceColor',.75*[1 1 1],'LineStyle','--'); + + % a series of normal arrows, linearly spaced, crossdir specified + h10y=(0:4)'/3; + h10 = feval(mfilename,[-3*ones(size(h10y)) h10y -6.5*ones(size(h10y))], ... + [-3*ones(size(h10y)) h10y -.05*ones(size(h10y))], ... + 12,[],[],[],[],[0 -1 0]); + + % a series of normal arrows, linearly spaced + h11x=(1:.33:2.8)'; + h11 = feval(mfilename,[h11x -3*ones(size(h11x)) 6.5*ones(size(h11x))], ... + [h11x -3*ones(size(h11x)) -.05*ones(size(h11x))]); + + % series of magenta arrows, radially oriented, crossdir specified + h12x=2; h12y=-3; h12z=axlim(5)/2; h12xr=1; h12zr=h12z; ir=.15;or=.81; + h12t=(0:11)'/6*pi; + h12 = feval(mfilename, ... + [h12x+h12xr*cos(h12t)*ir h12y*ones(size(h12t)) ... + h12z+h12zr*sin(h12t)*ir],[h12x+h12xr*cos(h12t)*or ... + h12y*ones(size(h12t)) h12z+h12zr*sin(h12t)*or], ... + 10,[],[],[],[], ... + [-h12xr*sin(h12t) zeros(size(h12t)) h12zr*cos(h12t)],... + 'FaceColor','none','EdgeColor','m'); + + % series of normal arrows, tangentially oriented, crossdir specified + or13=.91; h13t=(0:.5:12)'/6*pi; + locs = [h12x+h12xr*cos(h13t)*or13 h12y*ones(size(h13t)) h12z+h12zr*sin(h13t)*or13]; + h13 = feval(mfilename,locs(1:end-1,:),locs(2:end,:),6); + + % arrow with no line ==> oriented downwards + h14 = feval(mfilename,[3 3 .100001],[3 3 .1],30); + t6=text(3,3,3.6,'no line'); set(t6,'HorizontalAlignment','center'); + + % arrow with arrowheads at both ends + h15 = feval(mfilename,[-.5 -3 -3],[1 -3 -3],'Ends','both','FaceColor','g', ... + 'Length',20,'Width',3,'CrossDir',[0 0 1],'TipAngle',25); + + h=[h1;h2;h3;h4;h5;h6;h7;h8;h9;h10;h11;h12;h13;h14;h15]; + +function h = arrow_demo2(in) + axlim = in.axlim; + dolog = 1; + if (dolog), set(in.hs,'YData',10.^get(in.hs,'YData')); end; + shading('interp'); + view(2); + title(['Demo of the capabilities of the ARROW function in 2-D']); + hold on; [C,H]=contour(in.x,in.y,in.z,20,'-'); hold off; + for k=H', + set(k,'ZData',(axlim(6)+1)*ones(size(get(k,'XData'))),'Color','k'); + if (dolog), set(k,'YData',10.^get(k,'YData')); end; + end; + if (dolog), axis([axlim(1:2) 10.^axlim(3:4)]); set(gca,'YScale','log'); + else, axis(axlim(1:4)); end; + + % Normal blue arrow + start = [axlim(1) axlim(4) axlim(6)+2]; + stop = [in.x(in.iii) in.y(in.iii) axlim(6)+2]; + if (dolog), start(:,2)=10.^start(:,2); stop(:,2)=10.^stop(:,2); end; + h1 = feval(mfilename,start,stop,'EdgeColor','b','FaceColor','b'); + + % three arrows with varying fill, width, and baseangle + start = [-3 -3 10; -3 -1.5 10; -1.5 -3 10]; + stop = [-.03 -.03 10; -.03 -1.5 10; -1.5 -.03 10]; + if (dolog), start(:,2)=10.^start(:,2); stop(:,2)=10.^stop(:,2); end; + h2 = feval(mfilename,start,stop,24,[90;60;120],[],[0;0;4],'Ends',str2mat('both','stop','stop')); + set(h2(2),'EdgeColor',[0 .35 0],'FaceColor',[0 .85 .85]); + set(h2(3),'EdgeColor','r','FaceColor',[1 .5 1]); + h=[h1;h2]; + +function out = trueornan(x) +if isempty(x), + out=x; +else, + out = isnan(x); + out(~out) = x(~out); +end; diff --git a/Add-Ons/autoArrangeFigures.m b/Add-Ons/autoArrangeFigures.m new file mode 100644 index 0000000..b393b15 --- /dev/null +++ b/Add-Ons/autoArrangeFigures.m @@ -0,0 +1,108 @@ +function autoArrangeFigures(NH, NW, monitor_id) +% INPUT : +% NH : number of grid of vertical direction +% NW : number of grid of horizontal direction +% OUTPUT : +% +% get every figures that are opened now and arrange them. +% +% autoArrangeFigures selects automatically Monitor1. +% If you are dual(or more than that) monitor user, I recommend to set wide +% monitor as Monitor1. +% +% if you want arrange automatically, type 'autoArrangeFigures(0,0)' or 'autoArrangeFigures()'. +% But maximum number of figures for automatic mode is 27. +% +% if you want specify grid for figures, give numbers for parameters. +% but if your grid size is smaller than required one for accommodating +% all figures, this function changes to automatic mode and if more +% figures are opend than maximum number, then it gives error. +% +% Notes +% + 2017.1.20 use monitor id(Adam Danz's idea) +% +% leejaejun, Koreatech, Korea Republic, 2014.12.13 +% jaejun0201@gmail.com + +if nargin < 2 + NH = 0; + NW = 0; + monitor_id = 1; +end + +task_bar_offset = [30 50]; + +%% +N_FIG = NH * NW; +if N_FIG == 0 + autoArrange = 1; +else + autoArrange = 0; +end +figHandle = sortFigureHandles(findobj('Type','figure')); +n_fig = size(figHandle,1); +if n_fig <= 0 + warning('figures are not found'); + return +end + +screen_sz = get(0,'MonitorPositions'); +screen_sz = screen_sz(monitor_id, :); +scn_w = screen_sz(3) - task_bar_offset(1); +scn_h = screen_sz(4) - task_bar_offset(2); +scn_w_begin = screen_sz(1) + task_bar_offset(1); +scn_h_begin = screen_sz(2) + task_bar_offset(2); + +if autoArrange==0 + if n_fig > N_FIG + autoArrange = 1; + warning('too many figures than you told. change to autoArrange'); + else + nh = NH; + nw = NW; + end +end + +if autoArrange == 1 + grid = [2 2 2 2 2 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4; + 3 3 3 3 3 3 3 3 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 7 7 7]'; + + if n_fig > length(grid) + warning('too many figures(maximum = %d)',length(grid)) + return + end + + if scn_w > scn_h + nh = grid(n_fig,1); + nw = grid(n_fig,2); + else + nh = grid(n_fig,2); + nw = grid(n_fig,1); + end +end + + +fig_width = scn_w/nw; +fig_height = scn_h/nh; + +fig_cnt = 1; +for i=1:1:nh + for k=1:1:nw + if fig_cnt>n_fig + return + end + fig_pos = [scn_w_begin+fig_width*(k-1) ... + scn_h_begin+scn_h-fig_height*i ... + fig_width ... + fig_height]; + set(figHandle(fig_cnt),'OuterPosition',fig_pos); + fig_cnt = fig_cnt + 1; + end +end + +end + +function figSorted = sortFigureHandles(figs) + [tmp, idx] = sort([figs.Number]); + figSorted = figs(idx); +end \ No newline at end of file diff --git a/Add-Ons/autoArrangeFigures_examples.m b/Add-Ons/autoArrangeFigures_examples.m new file mode 100644 index 0000000..c48c856 --- /dev/null +++ b/Add-Ons/autoArrangeFigures_examples.m @@ -0,0 +1,40 @@ +close all + +%% make 10 figures +for i=1:10 + figure() +end + +%% example 1. automatically arrange figures. +fprintf('press any key if you want to proceed\n') +pause +% autoArrangeFigures(0,0);s +autoArrangeFigures(); +%% example 2. put the size of grid1 +fprintf('press any key if you want to proceed\n') +pause +autoArrangeFigures(5,2,1); + +%% example 3. put the size of grid2 +fprintf('press any key if you want to proceed\n') +pause +autoArrangeFigures(3,3,1); + +%% make more figures over than the maximum number of figure +% totally 30 figures are now. +fprintf('press any key if you want to proceed\n') +pause +for i=1:20 + figure() +end + +%% example 4. I cannot arrange automatically if the number of figures are more than 27. + +fprintf('press any key if you want to proceed\n') +pause +autoArrangeFigures(0,0,1); + +%% example 5. You have to specify the size of grid. +fprintf('press any key if you want to proceed\n') +pause +autoArrangeFigures(6,5,1); \ No newline at end of file diff --git a/Add-Ons/brewermap.m b/Add-Ons/brewermap.m new file mode 100644 index 0000000..78411d6 --- /dev/null +++ b/Add-Ons/brewermap.m @@ -0,0 +1,540 @@ +function [map,num,typ] = brewermap(N,scheme) +% The complete selection of ColorBrewer colorschemes (RGB colormaps). +% +% (c) 2014 Stephen Cobeldick +% +% Returns any RGB colormap from the ColorBrewer colorschemes, especially +% intended for mapping and plots with attractive, distinguishable colors. +% +%%% Syntax (basic): +% map = brewermap(N,scheme); % Select colormap length, select any colorscheme. +% brewermap('plot') % View a figure showing all ColorBrewer colorschemes. +% schemes = brewermap('list')% Return a list of all ColorBrewer colorschemes. +% [map,num,typ] = brewermap(...); % The current colorscheme's number of nodes and type. +% +%%% Syntax (preselect colorscheme): +% old = brewermap(scheme); % Preselect any colorscheme, return the previous scheme. +% map = brewermap(N); % Use preselected scheme, select colormap length. +% map = brewermap; % Use preselected scheme, length same as current figure's colormap. +% +% See also CUBEHELIX RGBPLOT3 RGBPLOT COLORMAP COLORBAR PLOT PLOT3 SURF IMAGE AXES SET JET LBMAP PARULA +% +%% Color Schemes %% +% +% This product includes color specifications and designs developed by Cynthia Brewer. +% See the ColorBrewer website for further information about each colorscheme, +% colour-blind suitability, licensing, and citations: http://colorbrewer.org/ +% +% To reverse the colormap sequence simply prefix the string token with '*'. +% +% Each colorscheme is defined by a set of hand-picked RGB values (nodes). +% If is greater than the requested colorscheme's number of nodes then: +% * Sequential and Diverging schemes are interpolated to give a larger +% colormap. The interpolation is performed in the Lab colorspace. +% * Qualitative schemes are repeated to give a larger colormap. +% Else: +% * Exact values from the ColorBrewer sequences are returned for all colorschemes. +% +%%% Diverging +% +% Scheme|'BrBG'|'PRGn'|'PiYG'|'PuOr'|'RdBu'|'RdGy'|'RdYlBu'|'RdYlGn'|'Spectral'| +% ------|------|------|------|------|------|------|--------|--------|----------| +% Nodes | 11 | 11 | 11 | 11 | 11 | 11 | 11 | 11 | 11 | +% +%%% Qualitative +% +% Scheme|'Accent'|'Dark2'|'Paired'|'Pastel1'|'Pastel2'|'Set1'|'Set2'|'Set3'| +% ------|--------|-------|--------|---------|---------|------|------|------| +% Nodes | 8 | 8 | 12 | 9 | 8 | 9 | 8 | 12 | +% +%%% Sequential +% +% Scheme|'Blues'|'BuGn'|'BuPu'|'GnBu'|'Greens'|'Greys'|'OrRd'|'Oranges'|'PuBu'| +% ------|-------|------|------|------|--------|-------|------|---------|------| +% Nodes | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 | +% +% Scheme|'PuBuGn'|'PuRd'|'Purples'|'RdPu'|'Reds'|'YlGn'|'YlGnBu'|'YlOrBr'|'YlOrRd'| +% ------|--------|------|---------|------|------|------|--------|--------|--------| +% Nodes | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 | +% +%% Examples %% +% +%%% Plot a scheme's RGB values: +% rgbplot(brewermap(9,'Blues')) % standard +% rgbplot(brewermap(9,'*Blues')) % reversed +% +%%% View information about a colorscheme: +% [~,num,typ] = brewermap(0,'Paired') +% num = 12 +% typ = 'Qualitative' +% +%%% Multi-line plot using matrices: +% N = 6; +% axes('ColorOrder',brewermap(N,'Pastel2'),'NextPlot','replacechildren') +% X = linspace(0,pi*3,1000); +% Y = bsxfun(@(x,n)n*sin(x+2*n*pi/N), X(:), 1:N); +% plot(X,Y, 'linewidth',4) +% +%%% Multi-line plot in a loop: +% set(0,'DefaultAxesColorOrder',brewermap(NaN,'Accent')) +% N = 6; +% X = linspace(0,pi*3,1000); +% Y = bsxfun(@(x,n)n*sin(x+2*n*pi/N), X(:), 1:N); +% for n = 1:N +% plot(X(:),Y(:,n), 'linewidth',4); +% hold all +% end +% +%%% New colors for the COLORMAP example: +% load spine +% image(X) +% colormap(brewermap([],'YlGnBu')) +% +%%% New colors for the SURF example: +% [X,Y,Z] = peaks(30); +% surfc(X,Y,Z) +% colormap(brewermap([],'RdYlGn')) +% axis([-3,3,-3,3,-10,5]) +% +%%% New colors for the CONTOURCMAP example: +% brewermap('PuOr'); % preselect the colorscheme. +% load topo +% load coast +% figure +% worldmap(topo, topolegend) +% contourfm(topo, topolegend); +% contourcmap('brewermap', 'Colorbar','on', 'Location','horizontal',... +% 'TitleString','Contour Intervals in Meters'); +% plotm(lat, long, 'k') +% +%% Input and Output Arguments %% +% +%%% Inputs (*=default): +% N = NumericScalar, N>=0, an integer to specify the colormap length. +% = *[], same length as the current figure's colormap (see COLORMAP). +% = NaN, same length as the defining RGB nodes (useful for Line ColorOrder). +% = CharRowVector, to preselect a ColorBrewer colorscheme for later use. +% = 'plot', create a figure showing all of the ColorBrewer colorschemes. +% = 'list', return a cell array of strings listing all ColorBrewer colorschemes. +% scheme = CharRowVector, a ColorBrewer colorscheme name. +% = *none, uses the preselected colorscheme (must be set previously!). +% +%%% Outputs: +% map = NumericMatrix, size Nx3, a colormap of RGB values between 0 and 1. +% num = NumericScalar, the number of nodes defining the ColorBrewer colorscheme. +% typ = CharRowVector, the colorscheme type: 'Diverging'/'Qualitative'/'Sequential'. +% OR +% schemes = CellOfCharRowVectors, a list of every ColorBrewer colorscheme. +% +% [map,num,typ] = brewermap(*N,*scheme) +% OR +% schemes = brewermap('list') + +%% Input Wrangling %% +% +persistent raw tok isr idp +% +if isempty(raw) + raw = bmColors(); +end +% +msg = 'A colorscheme must be preselected before calling without a colorscheme name.'; +% +if nargin==0 % Current figure's colormap length and the preselected colorscheme. + assert(~isempty(idp),msg) + [map,num,typ] = bmSample([],isr,raw(idp)); +elseif nargin==2 % Input colormap length and colorscheme. + assert(isnumeric(N),'The first argument must be a scalar numeric, or empty.') + assert(ischar(scheme)&&isrow(scheme),'The second argument must be a 1xN char.') + tmp = strncmp('*',scheme,1); + [map,num,typ] = bmSample(N,tmp,raw(bmMatch(scheme,tmp,raw))); +elseif isnumeric(N) % Input colormap length and the preselected colorscheme. + assert(~isempty(idp),msg) + [map,num,typ] = bmSample(N,isr,raw(idp)); +else + assert(ischar(N)&&isrow(N),'The first argument must be a 1xN char or a scalar numeric.') + switch lower(N) + case 'plot' % Plot all colorschemes in a figure. + bmPlotFig(raw) + case 'list' % Return a list of all colorschemes. + map = {raw.str}; + typ = {raw.typ}; + num = [raw.num]; + otherwise % Store the preselected colorscheme token. + tmp = strncmp('*',N,1); + idp = bmMatch(N,tmp,raw); + typ = raw(idp).typ; + num = raw(idp).num; + % Only update persistent values if colorscheme name is okay: + isr = tmp; + map = tok; + tok = N; + end +end +% +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%brewermap +function idx = bmMatch(str,tmp,raw) +% Match the requested colorscheme name to names in the raw data structure. +str = str(1+tmp:end); +idx = strcmpi({raw.str},str); +assert(any(idx),'Colorscheme "%s" is not supported. Check the colorscheme list.',str) +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%bmMatch +function [map,num,typ] = bmSample(N,isr,raw) +% Pick a colorscheme, downsample/interpolate to the requested colormap length. +% +num = raw.num; +typ = raw.typ; +% +if isempty(N) + N = size(get(gcf,'colormap'),1); +elseif isscalar(N)&&isnan(N) + N = num; +else + assert(isscalar(N),'First argument must be a numeric scalar, or empty.') + assert(isreal(N),'Input must be a real numeric: %g+%gi',N,imag(N)) + assert(fix(N)==N&&N>=0,'Input must be positive integer: %g',N) +end +% +if N==0 + map = nan(0,3); + return +end +% +% downsample: +[idx,itp] = bmIndex(N,num,typ); +map = raw.rgb(idx,:)/255; +% interpolate: +if itp + M = [... + +3.2406255,-1.5372080,-0.4986286;... + -0.9689307,+1.8757561,+0.0415175;... + +0.0557101,-0.2040211,+1.0569959]; + wpt = [0.95047,1,1.08883]; % D65 + % + map = bmRGB2Lab(map,M,wpt); % optional + % + % Extrapolate a small amount at both ends: + %vec = linspace(0,num+1,N+2); + %map = interp1(1:num,map,vec(2:end-1),'linear','extrap'); + % Interpolation completely within ends: + map = interp1(1:num,map,linspace(1,num,N),'spline'); + % + map = bmLab2RGB(map,M,wpt); % optional +end +% reverse order: +if isr + map = map(end:-1:1,:); +end +% +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%bmSample +function rgb = bmGammaCor(rgb) +% Gamma correction of sRGB data. +idx = rgb <= 0.0031308; +rgb(idx) = 12.92 * rgb(idx); +rgb(~idx) = real(1.055 * rgb(~idx).^(1/2.4) - 0.055); +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%bmGammaCor +function rgb = bmGammaInv(rgb) +% Inverse gamma correction of sRGB data. +idx = rgb <= 0.04045; +rgb(idx) = rgb(idx) / 12.92; +rgb(~idx) = real(((rgb(~idx) + 0.055) / 1.055).^2.4); +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%bmGammaInv +function lab = bmRGB2Lab(rgb,M,wpt) % Nx3 <- Nx3 +% Convert a matrix of sRGB values to Lab. +% +%applycform(rgb,makecform('srgb2lab','AdaptedWhitePoint',wpt)) +% +% RGB2XYZ: +xyz = bmGammaInv(rgb) / M.'; +% Remember to include my license when copying my implementation. +% XYZ2Lab: +xyz = bsxfun(@rdivide,xyz,wpt); +idx = xyz>(6/29)^3; +F = idx.*(xyz.^(1/3)) + ~idx.*(xyz*(29/6)^2/3+4/29); +lab(:,2:3) = bsxfun(@times,[500,200],F(:,1:2)-F(:,2:3)); +lab(:,1) = 116*F(:,2) - 16; +% +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%bmRGB2Lab +function rgb = bmLab2RGB(lab,M,wpt) % Nx3 <- Nx3 +% Convert a matrix of Lab values to sRGB. +% +%applycform(lab,makecform('lab2srgb','AdaptedWhitePoint',wpt)) +% +% Lab2XYZ +tmp = bsxfun(@rdivide,lab(:,[2,1,3]),[500,Inf,-200]); +tmp = bsxfun(@plus,tmp,(lab(:,1)+16)/116); +idx = tmp>(6/29); +tmp = idx.*(tmp.^3) + ~idx.*(3*(6/29)^2*(tmp-4/29)); +xyz = bsxfun(@times,tmp,wpt); +% Remember to include my license when copying my implementation. +% XYZ2RGB +rgb = max(0,min(1, bmGammaCor(xyz * M.'))); +% +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%cbLab2RGB +function bmPlotFig(raw) +% Creates a figure showing all of the ColorBrewer colorschemes. +% +persistent cbh axh +% +xmx = max([raw.num]); +ymx = numel(raw); +% +if ishghandle(cbh) + figure(cbh); + delete(axh); +else + cbh = figure('HandleVisibility','callback', 'IntegerHandle','off',... + 'NumberTitle','off', 'Name',[mfilename,' Plot'],'Color','white',... + 'MenuBar','figure', 'Toolbar','none', 'Tag',mfilename); + set(cbh,'Units','pixels') + pos = get(cbh,'Position'); + pos(1:2) = pos(1:2) - 123; + pos(3:4) = max(pos(3:4),[842,532]); + set(cbh,'Position',pos) +end +% +axh = axes('Parent',cbh, 'Color','none',... + 'XTick',0:xmx, 'YTick',0.5:ymx, 'YTickLabel',{raw.str}, 'YDir','reverse'); +title(axh,['ColorBrewer Color Schemes (',mfilename,'.m)'], 'Interpreter','none') +xlabel(axh,'Scheme Nodes') +ylabel(axh,'Scheme Name') +axf = get(axh,'FontName'); +% +for y = 1:ymx + num = raw(y).num; + typ = raw(y).typ; + map = raw(y).rgb(bmIndex(num,num,typ),:)/255; % downsample + for x = 1:num + patch([x-1,x-1,x,x],[y-1,y,y,y-1],1, 'FaceColor',map(x,:), 'Parent',axh) + end + text(xmx+0.1,y-0.5,typ, 'Parent',axh, 'FontName',axf) +end +% +drawnow() +% +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%bmPlotFig +function [idx,itp] = bmIndex(N,num,typ) +% Ensure exactly the same colors as the online ColorBrewer colorschemes. +% +itp = N>num; +switch typ + case 'Qualitative' + itp = false; + idx = 1+mod(0:N-1,num); + case 'Diverging' + switch N + case 1 % extrapolated + idx = 8; + case 2 % extrapolated + idx = [4,12]; + case 3 + idx = [5,8,11]; + case 4 + idx = [3,6,10,13]; + case 5 + idx = [3,6,8,10,13]; + case 6 + idx = [2,5,7,9,11,14]; + case 7 + idx = [2,5,7,8,9,11,14]; + case 8 + idx = [2,4,6,7,9,10,12,14]; + case 9 + idx = [2,4,6,7,8,9,10,12,14]; + case 10 + idx = [1,2,4,6,7,9,10,12,14,15]; + otherwise + idx = [1,2,4,6,7,8,9,10,12,14,15]; + end + case 'Sequential' + switch N + case 1 % extrapolated + idx = 6; + case 2 % extrapolated + idx = [4,8]; + case 3 + idx = [3,6,9]; + case 4 + idx = [2,5,7,10]; + case 5 + idx = [2,5,7,9,11]; + case 6 + idx = [2,4,6,7,9,11]; + case 7 + idx = [2,4,6,7,8,10,12]; + case 8 + idx = [1,3,4,6,7,8,10,12]; + otherwise + idx = [1,3,4,6,7,8,10,11,13]; + end + otherwise + error('The colorscheme type "%s" is not recognized',typ) +end +% +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%bmIndex +function raw = bmColors() +% Return a structure of all colorschemes: name, scheme type, RGB values, number of nodes. +% Order: first sort by , then case-insensitive sort by : +raw(35).str = 'YlOrRd'; +raw(35).typ = 'Sequential'; +raw(35).rgb = [255,255,204;255,255,178;255,237,160;254,217,118;254,204,92;254,178,76;253,141,60;252,78,42;240,59,32;227,26,28;189,0,38;177,0,38;128,0,38]; +raw(34).str = 'YlOrBr'; +raw(34).typ = 'Sequential'; +raw(34).rgb = [255,255,229;255,255,212;255,247,188;254,227,145;254,217,142;254,196,79;254,153,41;236,112,20;217,95,14;204,76,2;153,52,4;140,45,4;102,37,6]; +raw(33).str = 'YlGnBu'; +raw(33).typ = 'Sequential'; +raw(33).rgb = [255,255,217;255,255,204;237,248,177;199,233,180;161,218,180;127,205,187;65,182,196;29,145,192;44,127,184;34,94,168;37,52,148;12,44,132;8,29,88]; +raw(32).str = 'YlGn'; +raw(32).typ = 'Sequential'; +raw(32).rgb = [255,255,229;255,255,204;247,252,185;217,240,163;194,230,153;173,221,142;120,198,121;65,171,93;49,163,84;35,132,67;0,104,55;0,90,50;0,69,41]; +raw(31).str = 'Reds'; +raw(31).typ = 'Sequential'; +raw(31).rgb = [255,245,240;254,229,217;254,224,210;252,187,161;252,174,145;252,146,114;251,106,74;239,59,44;222,45,38;203,24,29;165,15,21;153,0,13;103,0,13]; +raw(30).str = 'RdPu'; +raw(30).typ = 'Sequential'; +raw(30).rgb = [255,247,243;254,235,226;253,224,221;252,197,192;251,180,185;250,159,181;247,104,161;221,52,151;197,27,138;174,1,126;122,1,119;122,1,119;73,0,106]; +raw(29).str = 'Purples'; +raw(29).typ = 'Sequential'; +raw(29).rgb = [252,251,253;242,240,247;239,237,245;218,218,235;203,201,226;188,189,220;158,154,200;128,125,186;117,107,177;106,81,163;84,39,143;74,20,134;63,0,125]; +raw(28).str = 'PuRd'; +raw(28).typ = 'Sequential'; +raw(28).rgb = [247,244,249;241,238,246;231,225,239;212,185,218;215,181,216;201,148,199;223,101,176;231,41,138;221,28,119;206,18,86;152,0,67;145,0,63;103,0,31]; +raw(27).str = 'PuBuGn'; +raw(27).typ = 'Sequential'; +raw(27).rgb = [255,247,251;246,239,247;236,226,240;208,209,230;189,201,225;166,189,219;103,169,207;54,144,192;28,144,153;2,129,138;1,108,89;1,100,80;1,70,54]; +raw(26).str = 'PuBu'; +raw(26).typ = 'Sequential'; +raw(26).rgb = [255,247,251;241,238,246;236,231,242;208,209,230;189,201,225;166,189,219;116,169,207;54,144,192;43,140,190;5,112,176;4,90,141;3,78,123;2,56,88]; +raw(25).str = 'Oranges'; +raw(25).typ = 'Sequential'; +raw(25).rgb = [255,245,235;254,237,222;254,230,206;253,208,162;253,190,133;253,174,107;253,141,60;241,105,19;230,85,13;217,72,1;166,54,3;140,45,4;127,39,4]; +raw(24).str = 'OrRd'; +raw(24).typ = 'Sequential'; +raw(24).rgb = [255,247,236;254,240,217;254,232,200;253,212,158;253,204,138;253,187,132;252,141,89;239,101,72;227,74,51;215,48,31;179,0,0;153,0,0;127,0,0]; +raw(23).str = 'Greys'; +raw(23).typ = 'Sequential'; +raw(23).rgb = [255,255,255;247,247,247;240,240,240;217,217,217;204,204,204;189,189,189;150,150,150;115,115,115;99,99,99;82,82,82;37,37,37;37,37,37;0,0,0]; +raw(22).str = 'Greens'; +raw(22).typ = 'Sequential'; +raw(22).rgb = [247,252,245;237,248,233;229,245,224;199,233,192;186,228,179;161,217,155;116,196,118;65,171,93;49,163,84;35,139,69;0,109,44;0,90,50;0,68,27]; +raw(21).str = 'GnBu'; +raw(21).typ = 'Sequential'; +raw(21).rgb = [247,252,240;240,249,232;224,243,219;204,235,197;186,228,188;168,221,181;123,204,196;78,179,211;67,162,202;43,140,190;8,104,172;8,88,158;8,64,129]; +raw(20).str = 'BuPu'; +raw(20).typ = 'Sequential'; +raw(20).rgb = [247,252,253;237,248,251;224,236,244;191,211,230;179,205,227;158,188,218;140,150,198;140,107,177;136,86,167;136,65,157;129,15,124;110,1,107;77,0,75]; +raw(19).str = 'BuGn'; +raw(19).typ = 'Sequential'; +raw(19).rgb = [247,252,253;237,248,251;229,245,249;204,236,230;178,226,226;153,216,201;102,194,164;65,174,118;44,162,95;35,139,69;0,109,44;0,88,36;0,68,27]; +raw(18).str = 'Blues'; +raw(18).typ = 'Sequential'; +raw(18).rgb = [247,251,255;239,243,255;222,235,247;198,219,239;189,215,231;158,202,225;107,174,214;66,146,198;49,130,189;33,113,181;8,81,156;8,69,148;8,48,107]; +raw(17).str = 'Set3'; +raw(17).typ = 'Qualitative'; +raw(17).rgb = [141,211,199;255,255,179;190,186,218;251,128,114;128,177,211;253,180,98;179,222,105;252,205,229;217,217,217;188,128,189;204,235,197;255,237,111]; +raw(16).str = 'Set2'; +raw(16).typ = 'Qualitative'; +raw(16).rgb = [102,194,165;252,141,98;141,160,203;231,138,195;166,216,84;255,217,47;229,196,148;179,179,179]; +raw(15).str = 'Set1'; +raw(15).typ = 'Qualitative'; +raw(15).rgb = [228,26,28;55,126,184;77,175,74;152,78,163;255,127,0;255,255,51;166,86,40;247,129,191;153,153,153]; +raw(14).str = 'Pastel2'; +raw(14).typ = 'Qualitative'; +raw(14).rgb = [179,226,205;253,205,172;203,213,232;244,202,228;230,245,201;255,242,174;241,226,204;204,204,204]; +raw(13).str = 'Pastel1'; +raw(13).typ = 'Qualitative'; +raw(13).rgb = [251,180,174;179,205,227;204,235,197;222,203,228;254,217,166;255,255,204;229,216,189;253,218,236;242,242,242]; +raw(12).str = 'Paired'; +raw(12).typ = 'Qualitative'; +raw(12).rgb = [166,206,227;31,120,180;178,223,138;51,160,44;251,154,153;227,26,28;253,191,111;255,127,0;202,178,214;106,61,154;255,255,153;177,89,40]; +raw(11).str = 'Dark2'; +raw(11).typ = 'Qualitative'; +raw(11).rgb = [27,158,119;217,95,2;117,112,179;231,41,138;102,166,30;230,171,2;166,118,29;102,102,102]; +raw(10).str = 'Accent'; +raw(10).typ = 'Qualitative'; +raw(10).rgb = [127,201,127;190,174,212;253,192,134;255,255,153;56,108,176;240,2,127;191,91,23;102,102,102]; +raw(09).str = 'Spectral'; +raw(09).typ = 'Diverging'; +raw(09).rgb = [158,1,66;213,62,79;215,25,28;244,109,67;252,141,89;253,174,97;254,224,139;255,255,191;230,245,152;171,221,164;153,213,148;102,194,165;43,131,186;50,136,189;94,79,162]; +raw(08).str = 'RdYlGn'; +raw(08).typ = 'Diverging'; +raw(08).rgb = [165,0,38;215,48,39;215,25,28;244,109,67;252,141,89;253,174,97;254,224,139;255,255,191;217,239,139;166,217,106;145,207,96;102,189,99;26,150,65;26,152,80;0,104,55]; +raw(07).str = 'RdYlBu'; +raw(07).typ = 'Diverging'; +raw(07).rgb = [165,0,38;215,48,39;215,25,28;244,109,67;252,141,89;253,174,97;254,224,144;255,255,191;224,243,248;171,217,233;145,191,219;116,173,209;44,123,182;69,117,180;49,54,149]; +raw(06).str = 'RdGy'; +raw(06).typ = 'Diverging'; +raw(06).rgb = [103,0,31;178,24,43;202,0,32;214,96,77;239,138,98;244,165,130;253,219,199;255,255,255;224,224,224;186,186,186;153,153,153;135,135,135;64,64,64;77,77,77;26,26,26]; +raw(05).str = 'RdBu'; +raw(05).typ = 'Diverging'; +raw(05).rgb = [103,0,31;178,24,43;202,0,32;214,96,77;239,138,98;244,165,130;253,219,199;247,247,247;209,229,240;146,197,222;103,169,207;67,147,195;5,113,176;33,102,172;5,48,97]; +raw(04).str = 'PuOr'; +raw(04).typ = 'Diverging'; +raw(04).rgb = [127,59,8;179,88,6;230,97,1;224,130,20;241,163,64;253,184,99;254,224,182;247,247,247;216,218,235;178,171,210;153,142,195;128,115,172;94,60,153;84,39,136;45,0,75]; +raw(03).str = 'PRGn'; +raw(03).typ = 'Diverging'; +raw(03).rgb = [64,0,75;118,42,131;123,50,148;153,112,171;175,141,195;194,165,207;231,212,232;247,247,247;217,240,211;166,219,160;127,191,123;90,174,97;0,136,55;27,120,55;0,68,27]; +raw(02).str = 'PiYG'; +raw(02).typ = 'Diverging'; +raw(02).rgb = [142,1,82;197,27,125;208,28,139;222,119,174;233,163,201;241,182,218;253,224,239;247,247,247;230,245,208;184,225,134;161,215,106;127,188,65;77,172,38;77,146,33;39,100,25]; +raw(01).str = 'BrBG'; +raw(01).typ = 'Diverging'; +raw(01).rgb = [84,48,5;140,81,10;166,97,26;191,129,45;216,179,101;223,194,125;246,232,195;245,245,245;199,234,229;128,205,193;90,180,172;53,151,143;1,133,113;1,102,94;0,60,48]; +% number of nodes: +for k = 1:numel(raw) + switch raw(k).typ + case 'Diverging' + raw(k).num = 11; + case 'Qualitative' + raw(k).num = size(raw(k).rgb,1); + case 'Sequential' + raw(k).num = 9; + end +end +% +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%bmColors +% Code and Implementation: +% Copyright (c) 2014 Stephen Cobeldick +% Color Values Only: +% Copyright (c) 2002 Cynthia Brewer, Mark Harrower, and The Pennsylvania State University. +% +% Licensed under the Apache License, Version 2.0 (the "License"); +% you may not use this file except in compliance with the License. +% You may obtain a copy of the License at +% +% http://www.apache.org/licenses/LICENSE-2.0 +% +% Unless required by applicable law or agreed to in writing, software +% distributed under the License is distributed on an "AS IS" BASIS, +% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +% See the License for the specific language governing permissions and limitations under the License. +% +% Redistribution and use in source and binary forms, with or without +% modification, are permitted provided that the following conditions are met: +% +% 1. Redistributions as source code must retain the above copyright notice, this +% list of conditions and the following disclaimer. +% +% 2. The end-user documentation included with the redistribution, if any, must +% include the following acknowledgment: "This product includes color +% specifications and designs developed by Cynthia Brewer +% (http://colorbrewer.org/)." Alternately, this acknowledgment may appear in the +% software itself, if and wherever such third-party acknowledgments normally appear. +% +% 4. The name "ColorBrewer" must not be used to endorse or promote products +% derived from this software without prior written permission. For written +% permission, please contact Cynthia Brewer at cbrewer@psu.edu. +% +% 5. Products derived from this software may not be called "ColorBrewer", nor +% may "ColorBrewer" appear in their name, without prior written permission of Cynthia Brewer. +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%license \ No newline at end of file diff --git a/Add-Ons/brewermap_view.m b/Add-Ons/brewermap_view.m new file mode 100644 index 0000000..6066351 --- /dev/null +++ b/Add-Ons/brewermap_view.m @@ -0,0 +1,364 @@ +function [map,scheme] = brewermap_view(N,scheme) +% An interactive figure for ColorBrewer colormap selection. With demo! +% +% (c) 2014 Stephen Cobeldick +% +% View Cynthia Brewer's ColorBrewer colorschemes in a figure. +% +% * Two colorbars give the colorscheme in color and grayscale. +% * A button toggles between 3D-cube and 2D-lineplot of the RGB values. +% * A button toggles an endless cycle through the colorschemes. +% * A button reverses the colormap. +% * 35 buttons select any ColorBrewer colorscheme. +% * Text with the colorscheme's type (Diverging/Qualitative/Sequential) +% * Text with the colorscheme's number of nodes (defining colors). +% +%%% Syntax: +% brewermap_view +% brewermap_view(N) +% brewermap_view(N,scheme) +% brewermap_view([],...) +% brewermap_view({axes/figure handles},...) % see "Adjust External Colormaps" +% [map,scheme] = brewermap_view(...) +% +% Calling the function with an output argument blocks MATLAB execution until +% the figure is deleted: the final colormap and colorscheme are then returned. +% +% See also BREWERMAP CUBEHELIX RGBPLOT COLORMAP COLORMAPEDITOR COLORBAR UICONTROL ADDLISTENER +% +%% Adjust Colormaps of Other Figures or Axes %% +% +%%% Example: +% +% S = load('spine'); +% image(S.X) +% brewermap_view({gca}) +% +% Very useful! Simply provide a cell array of axes or figure handles when +% calling this function, and their colormaps will be updated in real-time: +% note that MATLAB versions <=2010 only support axes handles for this! +% +%% Input and Output Arguments %% +% +%%% Inputs (*=default): +% N = NumericScalar, an integer to define the colormap length. +% = *[], colormap length of one hundred and twenty-eight (128). +% = NaN, same length as the defining RGB nodes (useful for Line ColorOrder). +% = CellArray of axes/figure handles, to be updated by BREWERMAP_VIEW. +% scheme = CharRowVector, a ColorBrewer colorscheme name. +% +%%% Outputs (these block code execution until the figure is closed!): +% map = NumericMatrix, the colormap defined when the figure is closed. +% scheme = CharRowVector, the name of the colorscheme given in . +% +% [map,scheme] = brewermap_view(N,scheme) + +%% Input Wrangling %% +% +persistent ax2D ln2D ax3D pt3D txtH is2D cbAx cbIm pTxt pSld bEig bGrp bRev scm isr +% +new = isempty(ax2D)||~ishghandle(ax2D); +dfn = 128; +upb = false; +hgc = {}; +nmr = dfn; +% +% Parse colormap size: +if nargin==0 || isnumeric(N)&&isempty(N) + N = dfn; +elseif isnumeric(N) + assert(isscalar(N),'Input must be a scalar numeric. NUMEL: %d',numel(N)) + assert(isreal(N),'Input must be a real numeric: %g+%gi',N,imag(N)) + assert(isnan(N)||fix(N)==N&&N>0,'Input must be positive integer: %g',N) + N = double(N); +elseif iscell(N)&&numel(N) + hgc = N(:); + ish = all(1==cellfun('prodofsize',hgc)&cellfun(@ishghandle,hgc)); + assert(ish,'Input may be a cell array of axes handles or figure handles.') + nmr = [cellfun(@(h)size(colormap(h),1),hgc),dfn]; + N = nmr(1); +else + error('Input may be a numeric scalar/empty, or a cell array of handles.') +end +% +[mcs,mun,pyt] = brewermap('list'); +% +% Check BREWERMAP outputs: +ers = 'The function BREWERMAP returned an unexpected %s.'; +assert(all(35==[numel(mcs),numel(mun),numel(pyt)]),ers,'array size') +tmp = find(any(diff(+char(pyt)),2)); +assert(numel(tmp)==2&&all(tmp==[9;17]),ers,'scheme name sequence') +% +% Default pseudo-random colorscheme: +if nargin==0 || new + isr = false; + scm = mcs{1+mod(round(now*1e7),numel(mcs))}; +end +% Parse input colorscheme: +if nargin==2 + assert(ischar(scheme)&&isrow(scheme),'Second input must be a 1xN char vector.') + % Check if a reversed colormap was requested: + isr = strncmp(scheme,'*',1); + scm = scheme(1+isr:end); +end +% +if isnan(N) + N = mun(strcmpi(scm,mcs)); +end +% +%% Ensure Figure Exists %% +% +% LHS and RHS slider bounds/limits, and slider step sizes: +lbd = 1; +rbd = dfn; +stp = [1,10]; % [minor,major] +% +% Define the 3D cube axis order: +xyz = 'RGB'; % choose order +[~,xyz] = ismember(xyz,'RGB'); +% +if new % Create a new figure. + % + % Figure parameters: + M = 9; % buttons per column + gap = 0.01; % gaps + bth = 0.04; % demo height + btw = 0.10; % demo width + uih = 0.40; % height of UI control group + cbw = 0.23; % width of both colorbars + axh = 1-uih-2*gap; % axes height + wdt = 1-cbw-2*gap; % axes width + % + figH = figure('HandleVisibility','callback', 'Color','white',... + 'IntegerHandle','off', 'NumberTitle','off', 'Units','normalized',... + 'Name','ColorBrewer Interactive ColorScheme Selector',... + 'MenuBar','figure', 'Toolbar','none', 'Tag',mfilename); + % + % Add 2D lineplot: + ax2D = axes('Parent',figH, 'Position',[gap,uih+gap,wdt,axh], 'Box','on',... + 'ColorOrder',[1,0,0; 0,1,0; 0,0,1; 0.6,0.6,0.6], 'HitTest','off',... + 'Visible','off', 'XLim',[0,1], 'YLim',[0,1], 'XTick',[], 'YTick',[]); + ln2D = line([0,0,0,0;1,1,1,1],[0,0,0,0;1,1,1,1], 'Parent',ax2D,... + 'Visible','off', 'Linestyle','-', 'Marker','.'); + % + % Add 3D scatterplot: + ax3D = axes('Parent',figH, 'OuterPosition',[0,uih,wdt+2*gap,1-uih],... + 'Visible','on', 'XLim',[0,1], 'YLim',[0,1], 'ZLim',[0,1], 'HitTest','on'); + pt3D = patch('Parent',ax3D, 'XData',[0;1], 'YData',[0;1], 'ZData',[0;1],... + 'Visible','on', 'LineStyle','none', 'FaceColor','none', 'MarkerEdgeColor','none',... + 'Marker','o', 'MarkerFaceColor','flat', 'MarkerSize',10, 'FaceVertexCData',[1,1,0;1,0,1]); + view(ax3D,3); + grid(ax3D,'on') + lbl = {'Red','Green','Blue'}; + xlabel(ax3D,lbl{xyz(1)}) + ylabel(ax3D,lbl{xyz(2)}) + zlabel(ax3D,lbl{xyz(3)}) + % + % Add warning text: + txtH = text('Parent',ax2D, 'Units','normalized', 'Position',[1,1],... + 'HorizontalAlignment','right', 'VerticalAlignment','top', 'Color','k'); + % + % Add demo button: + demo = uicontrol(figH, 'Style','togglebutton', 'Units','normalized',... + 'Position',[gap,uih+gap+0*bth,btw,bth], 'String','Demo',... + 'Max',1, 'Min',0, 'Callback',@bmvDemo); %#ok + % Add 2D/3D button: + is2D = uicontrol(figH, 'Style','togglebutton', 'Units','normalized',... + 'Position',[gap,uih+gap+1*bth,btw,bth], 'String','2D / 3D',... + 'Max',1, 'Min',0, 'Callback',@bmv2D3D); + % Add reverse button: + bRev = uicontrol(figH, 'Style','togglebutton', 'Units','normalized',... + 'Position',[gap,uih+gap+2*bth,btw,bth], 'String','Reverse',... + 'Max',1, 'Min',0, 'Callback',@bmvRevM); + % + % Add colorbars: + C(1,1,:) = [1,1,1]; + cbAx(2) = axes('Parent',figH, 'Visible','off', 'Units','normalized',... + 'Position',[1-cbw/2,gap,cbw/2-gap,1-2*gap], 'YLim',[0.5,1.5],... + 'YDir','reverse', 'HitTest','off'); + cbAx(1) = axes('Parent',figH, 'Visible','off', 'Units','normalized',... + 'Position',[1-cbw/1,gap,cbw/2-gap,1-2*gap], 'YLim',[0.5,1.5],... + 'YDir','reverse', 'HitTest','off'); + cbIm(2) = image('Parent',cbAx(2), 'CData',C); + cbIm(1) = image('Parent',cbAx(1), 'CData',C); + % + % Add parameter slider, listener, and corresponding text: + sv = mean([lbd,rbd],2); + pTxt = uicontrol(figH,'Style','text', 'Units','normalized',... + 'Position',[gap,uih-bth,btw,bth], 'String','X'); + pSld = uicontrol(figH,'Style','slider', 'Units','normalized',... + 'Position',[gap,gap,btw,uih-bth], 'Min',lbd(1), 'Max',rbd(1),... + 'SliderStep',stp(1,:)/(rbd(1)-lbd(1)), 'Value',sv(1)); + addlistener(pSld, 'Value', 'PostSet',@bmvSldr); + % + % Add colorscheme button group: + bGrp = uibuttongroup('Parent',figH, 'BorderType','none', 'Units','normalized',... + 'BackgroundColor','white', 'Position',[2*gap+btw,gap,wdt-btw-gap,uih-gap]); + % Determine button locations: + Z = 1:numel(mcs); + Z = Z+(Z>17); + C = (ceil(Z/M)-1)/4; + R = (M-1-mod(Z-1,M))/M; + % Add colorscheme buttons to group: + for jj = numel(mcs):-1:1 + bEig(jj) = uicontrol('Parent',bGrp, 'Style','Toggle', 'String',mcs{jj},... + 'Unit','normalized', 'Position',[C(jj),R(jj),1/4,1/M]); + end + set(bGrp,'SelectionChangeFcn',@bmvChgS); + % +end +% +set(bGrp,'SelectedObject',bEig(strcmpi(scm,mcs))); +set(pSld,'Value',max(lbd,min(rbd,N))); +% +%% Nested Functions %% +% + function str = makeName() + str = '*'; + str = [str(isr),scm]; + end +% + function bmvUpDt() + % Update all graphics objects in the figure. + % + % Get ColorBrewer colormap and grayscale equivalent: + [map,num,typ] = brewermap(N,makeName()); + mag = map*[0.298936;0.587043;0.114021]; + % + % Update colorbar values: + set(cbAx, 'YLim', [0,abs(N)+(N==0)]+0.5); + set(cbIm(1), 'CData',reshape(map,[],1,3)) + set(cbIm(2), 'CData',repmat(mag,[1,1,3])) + % + % Update 2D line / 3D patch values: + if get(is2D, 'Value') % 2D + set(ln2D, 'XData',linspace(0,1,abs(N))); + set(ln2D,{'YData'},num2cell([map,mag],1).'); + else % 3D + set(pt3D,... + 'XData',map(:,xyz(1)),... + 'YData',map(:,xyz(2)),... + 'ZData',map(:,xyz(3)),... + 'FaceVertexCData',map) + end + % + % Update reverse button: + set(bRev, 'Value',isr) + % + % Update warning text: + str = {[typ,' '];sprintf('%d Nodes ',num)}; + set(txtH,'String',str); + % + % Update parameter value text: + set(pTxt(1), 'String',sprintf('N = %.0f',N)); + % + % Update external axes/figure: + nmr(1) = N; + for ii = find(cellfun(@ishghandle,hgc)) + colormap(hgc{ii},brewermap(nmr(ii),makeName())); + end + % + drawnow() + end +% + function bmv2D3D(h,~) + % Switch between 2D-line and 3D-cube representation. + % + if get(h,'Value') % 2D + set(ax3D, 'HitTest','off', 'Visible','off') + set(ax2D, 'HitTest','on', 'Visible','on') + set(pt3D, 'Visible','off') + set(ln2D, 'Visible','on') + else % 3D + set(ax2D, 'HitTest','off', 'Visible','off') + set(ax3D, 'HitTest','on', 'Visible','on') + set(ln2D, 'Visible','off') + set(pt3D, 'Visible','on') + end + % + bmvUpDt(); + end +% + function bmvChgS(~,e) + % Change the colorscheme. + % + scm = get(e.NewValue,'String'); + % + bmvUpDt() + end +% + function bmvRevM(h,~) + % Reverse the colormap. + % + isr = logical(get(h,'Value')); + % + bmvUpDt() + end +% + function bmvSldr(~,~) + % Update the slider position. + % + N = round(get(pSld,'Value')); + % + bmvUpDt() + end +% + function bmvDemo(h,~) + % Display all ColorBrewer colorschemes sequentially. + % + cnt = uint64(0); + while ishghandle(h)&&get(h,'Value') + cnt = cnt+1; + % + if mod(cnt,23)<1 + ids = 1+mod(find(strcmpi(scm,mcs)),numel(mcs)); + scm = mcs{ids}; + try %#ok + set(bGrp, 'SelectedObject',bEig(ids)); + end + end + % + if mod(cnt,69)<1 + isr = ~isr; + end + % + upb = (upb || N<=1) && N + set(pSld, 'Value',N) + end + % + % Faster/slower: + pause(0.1); + end + % + end +% +%% Initialize the Figure %% +% +bmvUpDt() +% +if nargout + waitfor(ax2D); + scheme = makeName(); +else + clear map +end +% +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%brewermap_view +% +% Copyright (c) 2014 Stephen Cobeldick +% +% Licensed under the Apache License, Version 2.0 (the "License"); +% you may not use this file except in compliance with the License. +% You may obtain a copy of the License at +% +% http://www.apache.org/licenses/LICENSE-2.0 +% +% Unless required by applicable law or agreed to in writing, software +% distributed under the License is distributed on an "AS IS" BASIS, +% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +% See the License for the specific language governing permissions and limitations under the License. +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%license \ No newline at end of file diff --git a/Add-Ons/distFig.m b/Add-Ons/distFig.m new file mode 100644 index 0000000..0876817 --- /dev/null +++ b/Add-Ons/distFig.m @@ -0,0 +1,831 @@ +function distFig(varargin) +% ===== Syntax ============================================================ +% distFig(...,'Screen',Value) +% distFig(...,'Position',Value) +% +% distFig(...,'Rows',Value) +% distFig(...,'Columns',Value) +% +% distFig(...,'Not',Value) +% distFig(...,'Only',Value) +% distFig(...,'Offset',Value) +% +% distFig(...,'Adjust',Value) +% distFig(...,'Extra',Value) +% distFig(...,'Menu',Value) +% distFig(...,'Transpose',Value) +% distFig(...,'Simulink',Value) +% distFig(...,'Tight',Value) +% distFig(...,'Scale',Value) +% distFig(...,'ScaleOrigin',Value) +% distFig(...,'FreezeSize',Value) +% distFig(...,'Order',Value) +% +% ===== Description ======================================================= +% distFig(...,'Screen',Value) assigns where the figures will be +% distributed. +% Synonyms for 'Screen' are 'Scr' and 'S'. Value can be: +% 'C' / 'Center' (Default) +% 'W' / 'West' / 'L' / 'Left' +% 'E' / 'East' / 'R' / 'Right' +% 'N' / 'North' / 'T' / 'Top' +% 'S' / 'South' / 'B' / 'Bottom' +% 'Main' / 'Primary' +% 'Ext' / 'External' / 'Secondary' +% +% distFig(...,'Position',Value) assigns in which part of the screen the +% figures will be distributed. +% Synonyms for 'Position' are 'Pos' and 'P'. Value can be: +% 'C' / 'Center' (Default) +% 'W' / 'West' / 'L' / 'Left' +% 'E' / 'East' / 'R' / 'Right' +% 'N' / 'North' / 'T' / 'Top' +% 'S' / 'South' / 'B' / 'Bottom' +% 'NW' +% 'NE' +% 'SW' +% 'SE' +% +% distFig(...,'Rows',Value) assigns how many rows the figures will be +% distributed on. +% Synonyms for 'Rows' are 'R'. Value can be: +% 1...n +% 'Auto' / -1 +% 'Auto' indicates that it automatically calculates the number of required +% rows. +% +% distFig(...,'Columns',Value) assigns how many rows the figures will be +% distributed on. +% Synonyms for 'Columns' are 'Cols' and 'C'. Value can be: +% 1...n +% 'Auto' / -1 +% 'Auto' indicates that it automatically calculates the number of required +% columns. +% +% distFig(...,'Not',Value) excludes specified figures from the distribution +% list. Value must be an array with the excluded figure numbers. The +% default value is []. The input argument 'gcf' (get current figure) can be +% used as well. +% +% distFig(...,'Only',Value) does only distribute specified figures. Value +% must be an array with the figure which will be distributed. The +% default value is []. The input argument 'gcf' (get current figure) can be +% used as well. +% +% distFig(...,'Offset',Value) can be used to shift all figures on the +% distribution list. Synonyms for 'Offset' is 'O'. Value must be an integer +% larger or equal to zero. The default offset value is 0. +% +% distFig(...,'Adjust',Value) can be used to adjust all figure positions. +% For instance, if all figures should be moved 20 pixels to the right, +% which is not possible with the other features, Value should be [20,0]. +% If Value is below 1, the scalars indicate the relative adjustment to the +% screen. If the selected monitor is [1920,1080] pixels, a Values of +% [0.25,-0.5] moves all figures with [480,540] pixels. +% Synonyms for 'Ajust' is 'A'. Value can be: +% [Integer,Integer] (In order to adjust by a specific ammount) +% [Scalar,Scalar]( < 1) (To adjust a relative ammount of the monitor size) +% The default value is [0,0]. +% +% distFig(...,'Extra',Value) is used to handle the extra figures, which +% might not fit into 'Rows' * 'Cols'. For instance, 5 figure are to be +% distributed on a 2x2 = 4 area. The fifth figure is then places on top of +% the first figure if 'Extra' is 'restart'. It can be ignored by setting +% 'Extra' to 'ignore', in which the fifth figure will not be distributed. +% +% distFig(...,'Menu',Value) can be used to modify the menu bar. +% Value can be: +% 'figure' +% 'none' +% +% distFig(...,'Transpose',Value) can be used to tranpose the order of +% distributing. The values must be logical and the default value is false. +% +% distFig(...,'Simulink',Value) can be used to handle simulink figures. +% Value can be: +% 'include' (Default) +% 'exclude' +% 'only' +% If value is true, simulink figures will be distributed along with the +% other figures. If value if 'exclude' simulink figures will be +% excluded from the distribution list. If value is 'only', only the +% simulink figures will be distributed and not the ordinary figures. +% +% distFig(...,'Tight',Value) can be used to stretch the figure to the +% border of the figure, so no unnecessary "whitespace" is present. +% Value must be logical and the default value if false. +% +% distFig(...,'Scale',Value) can be used to scale the figure matrix. Both +% horizontal and vertical scaling can be applied, but also similar scaling. +% Value is a single scalar for similar scaling, but is a 2x1 matrix for +% specific scaling in each direction. For instance, distFig('Scale',0.5) +% scales all figures by 50% relative to the upper left corner of the +% distribution area (Default Scale-origin). distFig('Scale',[0.8,0.4]) +% scales the figures by 80% and 40% in the horizontal and vertical +% directions respectivly relative to the default scale-origin. +% +% distFig(...,'ScaleOrigin',Value) can be used in combination with the +% 'Scale' option. Value is a 2x1 matrix with the origin. If these values +% are between 0 and 1 the relative monitor size is used, whereas larger +% values should be rounded indicating pixel values. For instance, +% distFig('Scale',0.5,'ScaleOrigin',[0.5,1]) scales the figures relative +% to the midpoint on the right hand side of the selected monitor. For a +% monitor with resolution 1920x1080, this would be equal to +% distFig('Scale',0.5,'ScaleOrigin',[1920,960]). +% The default scale origin is in the upper left corner of the distribution +% area. +% Synonyms for 'ScaleOrigin' are 'Origin', 'Orig' and 'Scaleorig'. +% +% distFig(...,'FreezeSize',Value) can be used to freeze the sizes of the +% figures before distribution. Currently, this function anchors the figures +% to the upper left corner of the original position, yet keeping the +% original size - it does not calculate new positions, so the figures may +% overlap. +% Synonym for 'FreezeSize' is 'Freeze'. +% +% distFig(...,'Order',Value) can be used to control the plotting order. For +% instance, distFig('Only',[5,6,7,8],'Order',[2,1,4,3]) will plot figure +% 5,6,7 and 8 in the order of 6,5,8 and 7. The ordering argument is thus +% related to the input of 'Only'. +% +% ===== Examples ========================================================== +% distFig(); +% This will distribute all open figures on the primary screen in two rows. +% +% distFig('Screen','Left','Position','Right','Only',[1,2,4]) +% This will only distribute figure 1, 2 and 4 on the right part of the left +% screen. +% +% distFig('Offset',2,'Not',[1,2]) +% This will distribute all figure but figure 1 and 2 in the same pattern as +% distFig(), but figure 1 and 2 will not be distributed, but instead there will +% be blank spots where they would have been distributed. +% +% ===== Note ============================================================== +% If you find any errors or bugs with this version please contact me on +% AndersSSimonsen@GMail.com or write a comment on file exchange - then I'll +% take a look at it. :) +% +% This function will only work in MATLAB 2014b and onwards due to the +% massive overhaul in the figure handle system - I will not support +% previous versions. + +% ========================================================================= +% ===== Version =========================================================== +% ========================================================================= + +% Anders Schou Simonsen, AndersSSimonsen@GMail.com +% Version 5.5 +% 31/03-2015 + +% ========================================================================= +% ===== Default values ==================================================== +% ========================================================================= + +Rows = -1; +Cols = -1; +Scr = 'C'; +Pos = 'C'; +Tight = false; +Menu = ''; +Transpose = false; +Extra = 'restart'; +Offset = 0; +Not = []; +Only = []; +Simulink = 'include'; +Adjust = [0,0]; +Scale = 1; +Scale_Orig = []; +FreezeSize = false; +Order = []; + +% ========================================================================= +% ===== Get inputs ======================================================== +% ========================================================================= + +if (mod(nargin,2) ~= 0) + error('Uneven number of inputs! Returning...'); +end + +for i = 1:2:nargin + if (ischar(varargin{i+1})) + varargin{i+1} = lower(varargin{i+1}); + end + switch lower(varargin{i}) + case {'scr','screen','s'} + % ============================================================= + Allow = { + 'C' 'c' 'center' 'main' 'primary' + 'W' 'w' 'west' 'l' 'left' + 'E' 'e' 'east' 'r' 'right' + 'N' 'n' 'north' 't' 'top' + 'S' 's' 'south' 'b' 'bottom' + 'Ext' 'ext' 'external' 'secondary' NaN + }; + Trigger = any(strcmp(Allow,varargin{i+1}),2); + if (~any(Trigger)) + warning('Input ''%s'' not recognized for ''%s''!',varargin{i+1},varargin{i}); + else + Scr = Allow{Trigger,1}; + end + case {'pos','position','p'} + % ============================================================= + Allow = { + 'C' 'c' 'center' NaN NaN + 'W' 'w' 'west' 'l' 'left' + 'E' 'e' 'east' 'r' 'right' + 'N' 'n' 'north' 't' 'top' + 'S' 's' 'south' 'b' 'bottom' + 'NW' 'nw' NaN NaN NaN + 'NE' 'ne' NaN NaN NaN + 'SW' 'sw' NaN NaN NaN + 'SE' 'se' NaN NaN NaN + }; + Trigger = any(strcmp(Allow,varargin{i+1}),2); + if (~any(Trigger)) + warning('Input ''%s'' not recognized for ''%s''!',varargin{i+1},varargin{i}); + else + Pos = Allow{Trigger,1}; + end + case {'rows','r'} + % ============================================================= + if (strcmp(varargin{i+1},'auto')) + Rows = -1; + else + if ~((isnumeric(varargin{i+1})) && (mod(varargin{i+1},1) == 0)) + warning('Input to ''%s'' must be a round numeric value!',varargin{i}); + else + Rows = varargin{i+1}; + end + end + case {'cols','columns','c'} + % ============================================================= + if (strcmp(varargin{i+1},'auto')) + Cols = -1; + else + if ~((isnumeric(varargin{i+1})) && (mod(varargin{i+1},1) == 0)) + warning('Input to ''%s'' must be a round numeric value!',varargin{i}); + else + Cols = varargin{i+1}; + end + end + case {'ext','extra'} + % ============================================================= + Allow = { + 'ignore' + 'restart' + }; + Trigger = any(strcmp(Allow,varargin{i+1}),2); + if (~any(Trigger)) + warning('Input ''%s'' not recognized for ''%s''!',varargin{i+1},varargin{i}); + else + Extra = Allow{Trigger,1}; + end + case {'menu','bar'} + % ============================================================= + Allow = { + 'figure' + 'none' + }; + Trigger = any(strcmp(Allow,varargin{i+1}),2); + if (~any(Trigger)) + warning('Input ''%s'' not recognized for ''%s''!',varargin{i+1},varargin{i}); + else + Menu = Allow{Trigger,1}; + end + case {'transpose'} + % ============================================================= + if (~islogical(varargin{i+1})) + warning('Input to ''%s'' must be logical!',varargin{i}); + else + Transpose = varargin{i+1}; + end + case {'offset','o'} + % ============================================================= + if ~((isnumeric(varargin{i+1})) && (mod(varargin{i+1},1) == 0)) + warning('Input to ''%s'' must be a round numeric value!',varargin{i}); + else + Offset = varargin{i+1}; + end + case {'adjust','a'} + % ============================================================= + if ~(isnumeric(varargin{i+1})) + warning('Input to ''%s'' must be numeric!',varargin{i}); + elseif (numel(varargin{i+1}) ~= 2) + warning('Input to ''%s'' must be a (1 x 2) matrix with integers or scalars less than one!',varargin{i}); + elseif (all(mod(varargin{i+1},1) == 0)) + Adjust = varargin{i+1}; + else + if (any(varargin{i+1} > 1)) + warning('Input to ''%s'' must be either integers or scalars less than one!',varargin{i}); + else + Adjust = varargin{i+1}; + end + end + case {'not'} + % ============================================================= + if ~((isnumeric(varargin{i+1}) && all(mod(varargin{i+1},1) == 0)) || isobject(varargin{i+1})) + warning('Input to ''%s'' must be round numeric values!',varargin{i}); + else + if (isobject(varargin{i+1})) + Not = get(varargin{i+1},'Number'); + if (iscell(Not)) + Not = cell2mat(Not); + end + else + Not = varargin{i+1}; + end + end + case {'only'} + % ============================================================= + if ~((isnumeric(varargin{i+1}) && all(mod(varargin{i+1},1) == 0)) || isobject(varargin{i+1})) + warning('Input to ''%s'' must be round numeric values!',varargin{i}); + else + if (isobject(varargin{i+1})) + Only = get(varargin{i+1},'Number'); + if (iscell(Only)) + Only = cell2mat(Only); + end + else + Only = varargin{i+1}; + end + end + case {'simu','simulink'} + % ============================================================= + Allow = { + 'include' NaN + 'exclude' 'ignore' + 'only' NaN + }; + Trigger = any(strcmp(Allow,varargin{i+1}),2); + if (~any(Trigger)) + warning('Input ''%s'' not recognized for ''%s''!',varargin{i+1},varargin{i}); + else + Simulink = Allow{Trigger,1}; + end + case {'tight'} + % ============================================================= + if (~islogical(varargin{i+1})) + warning('Input to ''%s'' must be logical!',varargin{i}); + else + Tight = varargin{i+1}; + end + case {'scale'} + % ============================================================= + if (~isnumeric(varargin{i+1}) || (numel(varargin{i+1}) > 2)) + warning('Input to ''%s'' must be one or two numeric values (x and y scale)!',varargin{i}); + else + Scale = varargin{i+1}; + end + case {'origin','orig','scaleorig','scaleorigin'} + % ============================================================= + if (~isnumeric(varargin{i+1}) || (numel(varargin{i+1}) ~= 2)) + warning('Input to ''%s'' must be two numeric values (x0 and y0)!',varargin{i}); + else + Scale_Orig = varargin{i+1}; + end + case {'freezesize','freeze'} + % ============================================================= + if (~islogical(varargin{i+1})) + warning('Input to ''%s'' must be logical!',varargin{i}); + else + FreezeSize = varargin{i+1}; + end + case {'order'} + % ============================================================= + if ~(isnumeric(varargin{i+1}) && all(mod(varargin{i+1},1) == 0)) + warning('Input to ''%s'' must be round numeric values!',varargin{i}); + else + Order = varargin{i+1}; + end + otherwise + % ============================================================= + fprintf('Input ''%s'' not recognized!',varargin{i}); + end +end + +% ========================================================================= +% ===== Constants ========================================================= +% ========================================================================= + +% ===== Limits ============================================================ +Limits = {... + 'C' [0,1] [0,1] + 'W' [0,0.5] [0,1] + 'E' [0.5,1] [0,1] + 'N' [0,1] [0.5,1] + 'NW' [0,0.5] [0.5,1] + 'NE' [0.5,1] [0.5,1] + 'S' [0,1] [0,0.5] + 'SW' [0,0.5] [0,0.5] + 'SE' [0.5,1] [0,0.5] + }; + +% ===== Screen angles ===================================================== +Screens = {... + (-pi * 1 / 4) (+pi * 1 / 4) 'E' + (-pi * 3 / 4) (-pi * 1 / 4) 'S' + (+pi * 1 / 4) (+pi * 3 / 4) 'N' + (+pi * 3 / 4) Inf 'W' + -Inf (-pi * 3 / 4) 'W' + }; + +% ===== Taskbar height ==================================================== +Taskbar_Height = 40; + +% ========================================================================= +% ===== Figure list ======================================================= +% ========================================================================= + +% ===== All figures ======================================================= +Fig_Object = findall(0,'type','figure'); +if (isempty(Fig_Object)) + fprintf('distFig: No figures to distribute!\n'); + return; +end + +% ===== Remove not visible figures ======================================== +Visible = arrayfun(@(n) (strcmp(get(Fig_Object(n),'Visible'),'on')),1:numel(Fig_Object)); +Fig_Object = Fig_Object(Visible); + +% ===== Include simulink figures ========================================== +Fig_Number = {Fig_Object.Number}; +Empty = arrayfun(@(n) (isempty(Fig_Number{n})),1:numel(Fig_Number)); +Fig_Number(Empty) = {0}; +Fig_Number = cell2mat(Fig_Number); +[~,Index] = sort(get(Fig_Object(Fig_Number == 0),'Name')); +Temp = find(Fig_Number == 0); +Fig_Number(Temp(Index)) = -(numel(Index):(-1):1); + +% ===== Logical distribution array ======================================== +Fig_Dist = true(1,numel(Fig_Object)); + +% ===== Simulink figures ================================================== +if strcmp(Simulink,'exclude') + Fig_Dist = (Fig_Number > 0); +end +if strcmp(Simulink,'only') + Fig_Dist = (Fig_Number < 0); +end + +% ===== Not =============================================================== +Fig_Dist(ismember(Fig_Number,Not)) = false; + +% ===== Only ============================================================== +if (~isempty(Only)) + Fig_Dist(~ismember(Fig_Number,Only)) = false; +end + +% ===== Number of figures ================================================= +nFig_Dist = sum(Fig_Dist); + +% ===== Return ============================================================ +if (nFig_Dist == 0) + return; +end + +% ========================================================================= +% ===== Monitor =========================================================== +% ========================================================================= + +% ===== Get monitor positions ============================================= +Monitors = get(0,'MonitorPositions'); +Monitors_Center = Monitors(:,1:2) + Monitors(:,3:4) / 2; +Monitors_Label = cell(size(Monitors,1),1); + +% ===== Center monitor ==================================================== +Temp = sum(abs(Monitors(:,1:2) - 1),2); +Trigger_C = find(Temp == min(Temp)); +Monitors_Label{Trigger_C} = 'C'; + +% ===== External monitors ================================================= +Dir = Monitors_Center - repmat(Monitors_Center(Trigger_C,:),size(Monitors_Center,1),1); +Theta = atan2(Dir(:,2),Dir(:,1)); +for i = 1:numel(Theta) + if (i ~= Trigger_C) + Monitors_Label{i} = Screens{(Theta(i) > [Screens{:,1}]) & (Theta(i) <= [Screens{:,2}]),3}; + end +end + +% ===== Select monitor ==================================================== +Monitor = Monitors(strcmp(Monitors_Label,Scr),:); +if (isempty(Monitor)) + if (strcmp(Scr,'Ext')) + if (size(Monitors,1) == 1) + warning('No external monitor could be found!'); + Monitor = Monitors(1,:); + else + Monitor = Monitors(find(~strcmp(Monitors_Label,'C'),1,'first'),:); + end + else + warning(['Screen ''%s'' could not be found! (Using ''C'' instead)\nThe following monitors were identified: %s.\n'... + 'If the function cannot find the monitor try and restart MATLAB - this will reset the monitor-matrix, which is being used by the function.'],... + Scr,sprintf('%s\b\b\b\b\b',sprintf('''%s'' and ',Monitors_Label{:}))); + Monitor = Monitors(strcmp(Monitors_Label,'C'),:); + if (isempty(Monitor)) + warning(['distFig cannot find matching monitors - using the first one!',... + '\nPlease report this problem to AndersSSimonsen@GMail.com, where you include this matrix:'],0); + disp(Monitors); + Monitor = Monitors(1,:); + end + end +end + +% ========================================================================= +% ===== Rows and columns ================================================== +% ========================================================================= + +Limit = Limits(strcmp(Limits(:,1),Pos),:); +if ((Rows == (-1)) && (Cols == (-1))) + AR_Ideal = 1.2; + AR_Mean = Inf; + for i = 1:50 + % ===== Exception ================================================= + if ((nFig_Dist + Offset) == 4) + Rows = 2; + Cols = 2; + break; + end + + % ===== Temporary rows and columns ================================ + Rows = i; + Cols = ceil((nFig_Dist + Offset) / Rows); + + % ===== Sizes ===================================================== + x = round(linspace(Limit{2}(1),Limit{2}(2),Cols + 1) * Monitor(3)) + 1; + y = round(linspace(Limit{3}(1),Limit{3}(2),Rows + 1) * (Monitor(4) - Taskbar_Height)) + Taskbar_Height + 1; + clear Size; + [Size(:,:,1),Size(:,:,2)] = meshgrid(diff(x),diff(y)); + + % ===== Output ==================================================== + AR_Mean_Prev = AR_Mean; + AR_Mean = mean(mean(Size(:,:,1) ./ Size(:,:,2))); + if (AR_Mean > AR_Ideal) + AR_Error = abs([AR_Ideal - AR_Mean_Prev,AR_Ideal - AR_Mean]); + if (AR_Error(1) < AR_Error(2)) + Rows = i - 1; + end + Cols = ceil((nFig_Dist + Offset) / Rows); + clear Size; + break; + end + end +elseif (Rows == (-1)) + Rows = ceil((nFig_Dist + Offset) / Cols); +elseif (Cols == (-1)) + Cols = ceil((nFig_Dist + Offset) / Rows); +end + +% ========================================================================= +% ===== Location matrix =================================================== +% ========================================================================= + +Sets = ceil(nFig_Dist / (Rows * Cols) + Offset); +Mat = nan(Rows,Cols,Sets); +if (Transpose) + Mat = permute(Mat,[2,1,3]); +end +if (isempty(Order)) + Order = (1:sum(Fig_Dist)); +end +Temp = sort(Fig_Number(Fig_Dist)); +if (max(Order) > numel(Temp)) + error('The ordering command is related to the input - not the actual figure numbers! Returning...'); +end +Mat((1:nFig_Dist) + Offset) = Temp(Order); +if (Transpose) + Mat = permute(Mat,[2,1,3]); +end +if (strcmp(Extra,'ignore')) + Sets = 1; +end + +% ========================================================================= +% ===== Position and size ================================================= +% ========================================================================= + +% ===== Grid ============================================================== +x = round(linspace(Limit{2}(1),Limit{2}(2),Cols + 1) * Monitor(3)) + 1; +y = round(linspace(Limit{3}(1),Limit{3}(2),Rows + 1) * (Monitor(4) - Taskbar_Height)) + Taskbar_Height + 1; + +% ===== Scale ============================================================= +if (isempty(Scale_Orig)) + Scale_Orig = [x(1),y(end)]; +end +if ((all(mod(Scale_Orig,1) == 0)) && (any(Scale_Orig > 1))) + ScaleOrig_Pixel = Scale_Orig; +else + ScaleOrig_Pixel = Monitor(3:4) .* Scale_Orig; +end +if (numel(Scale) == 1) + Scale(2) = Scale(1); +end +x = (x - ScaleOrig_Pixel(1)) * Scale(1) + ScaleOrig_Pixel(1); +y = (y - ScaleOrig_Pixel(2)) * Scale(2) + ScaleOrig_Pixel(2); + +% ===== Positon =========================================================== +[FPos(:,:,1),FPos(:,:,2)] = meshgrid(x(1:end-1),y(1:end-1)); +FPos(:,:,2) = flipud(FPos(:,:,2)); +FPos(:,:,1) = FPos(:,:,1) + Monitor(1) - 1; +FPos(:,:,2) = FPos(:,:,2) + Monitor(2) - 1; + +% ===== Size ============================================================== +[Size(:,:,1),Size(:,:,2)] = meshgrid(diff(x),diff(y)); + +% ===== Adjust ============================================================ +if (any(Adjust ~= 0)) + if (all(mod(Adjust,1) == 0)) + Adjust_Pixels = Adjust; + else + Adjust_Pixels = round(Adjust .* (Monitor(3:4) + [0,-Taskbar_Height])); + end +else + Adjust_Pixels = [0,0]; +end + +% ========================================================================= +% ===== Distribute figures ================================================ +% ========================================================================= + +for s = 1:Sets + for i = 1:size(Mat,1) + for j = 1:size(Mat,2) + if (~isnan(Mat(i,j,s))) + % ===== Position and figure =============================== + Pos_Temp = [squeeze(FPos(i,j,:))' + Adjust_Pixels,squeeze(Size(i,j,:))']; + gcf_Temp = Fig_Object(Fig_Number == Mat(i,j,s)); + gca_Temp = get(gcf_Temp,'CurrentAxes'); + + % ===== Freeze size ======================================= + if (FreezeSize) + Pos_Orig = get(gcf_Temp,'Position'); + Pos_Temp(2) = Pos_Temp(2) + Pos_Temp(4) - Pos_Orig(4); + Pos_Temp(3:4) = Pos_Orig(3:4); + end + + % ===== Focus figures to bring to front =================== + figure(gcf_Temp); + + % ===== Set units ========================================= + if (~isempty(Menu)) + set(gcf_Temp,'MenuBar',Menu); + end + if (Mat(i,j,s) < 0) + drawnow; + end + gca_Units_Prev = get(gca_Temp,'Units'); + gcf_Units_Prev = get(gcf_Temp,'Units'); + + % ===== Distribute figure ================================= + set(gca_Temp,'Units','normalized'); + set(gcf_Temp,'Units','pixels','OuterPosition',Pos_Temp); + set(gcf_Temp,'Units',gcf_Units_Prev); + + % ===== Apply tight ======================================= + if ((Tight) && (Mat(i,j,s) > 0)) + drawnow; + set(gca_Temp,'Position',[get(gca_Temp,'TightInset') * eye(4,2),1 - get(gca_Temp,'TightInset') * [1,0,1,0;0,1,0,1]']); + end + set(gca_Temp,'Units',gca_Units_Prev); + end + end + end +end + +% ========================================================================= +% ===== Check for new updates ============================================= +% ========================================================================= + +% This feature check for a new version of distFig. It is only an attempt, +% so it might not work without bugs. It can be disables by setting the +% variable below called "Update" to "false" or by deleting this whole +% section - this won't affect the rest of the function. +% +% It generates a .txt file called "distFig_Update.txt" located in the same +% folder as distFig.m, which holds the date for the last time the function +% checked for updates. In order to not check for updates all the time, the +% function only does this ONCE every 7 days (variable "Check_Interval"), +% and at max once for every started MATLAB session. Also, it uses appdata, +% so if you're using this as well, it might display messages multiple times +% within a session, if an update is available, if appdata is deleted. +% +% The update feature works by scanning the file exchange page for distFig +% for a string value called "datePublished", and compares it to the date of +% the current version (variable "Date_Current"). If these are not the same, +% a hyperlink will be shown to the function page on file exchange page. It +% thus depends on a very specific format, which might differ(?) from +% different languages - I'm not aware whether this is true, so please +% contact me on AndersSSimonsen@GMail.com if you find this to be true, so I +% can fix the feature. :) + +% ===== DISABLE THE UPDATE FEATURE BY SETTING THIS VALUE TO false ========= +Update = true; +% ===== DISABLE THE UPDATE FEATURE BY SETTING THIS VALUE TO false ========= + +if (Update) + try + % ===== Initialize ================================================ + Date_Current = [2015,03,31]; + Check_Interval = 7; + Check = false; + + % ===== Path of update file ======================================= + Path = mfilename('fullpath'); + Path = sprintf('%s\\distFig_Update.txt',Path(1:end-numel('\distFig'))); + + if (isempty(getappdata(0,'distFig_Update'))) + % ===== Set appdata =========================================== + setappdata(0,'distFig_Update',1); + + % ===== Read update file ====================================== + File_ID = fopen(Path,'r'); + Clock = clock; + Date_Today = Clock(1:3); + if (File_ID == (-1)) + % ===== Generate update file ============================== + File_ID = fopen(Path,'w'); + fprintf(File_ID,'%d %d %d',Date_Today(1),Date_Today(2),Date_Today(3)); + fclose(File_ID); + Check = true; + else + % ===== Read last date ==================================== + Data = textscan(File_ID,'%s','delimiter',''); + if (strcmp(Data{1},'DISABLE')) + Check = false; + else + Date_Last_Checked = cell2mat(textscan(Data{1}{1},'%f %f %f')); + + % ===== Write new date ================================ + File_ID = fopen(Path,'w'); + fprintf(File_ID,'%d %d %d',Date_Today(1),Date_Today(2),Date_Today(3)); + fclose(File_ID); + + % ===== Check for new updates? ======================== + Days_Elapsed = etime([Date_Today,zeros(1,3)],[Date_Last_Checked,zeros(1,3)]) / (60^2 * 24); + if (Days_Elapsed > Check_Interval) + Check = true; + end + end + end + + % ===== Check for updates ===================================== + if (Check) + % ===== Read File Exchange date =========================== + Data = urlread('http://se.mathworks.com/matlabcentral/fileexchange/37176-distribute-figures'); + Temp = Data((-1:100) + regexp(Data,'datePublished')); + Date_Online = cell2mat(textscan(Temp(26:end),'%f-%f-%f')); + + % ===== New update available? ============================= + if (~all(Date_Current == Date_Online)) + setappdata(0,'distFig_Update',2); + setappdata(0,'distFig_Online_Date',Date_Online); + end + end + end + + % ===== Message =================================================== + if (getappdata(0,'distFig_Update') == 2) + try + % ===== New version ======================================= + Date_Online = getappdata(0,'distFig_Online_Date'); + fprintf('New update available for distFig! '); + disp('Download here') + fprintf('\tCurrent version date:\t%02.0f-%02.0f-%02.0f\n',Date_Current(1),Date_Current(2),Date_Current(3)); + fprintf('\tOnline version date:\t%02.0f-%02.0f-%02.0f\n',Date_Online(1),Date_Online(2),Date_Online(3)); + + % ===== Postpone ========================================== + fprintf('Click here to postpone this message for %d days: ',Check_Interval); + Command = sprintf([... + 'setappdata(0,''distFig_Update'',1);',... + 'fprintf(''distFig update message postponed for %d days!\\n'');' + ],Check_Interval); + disp(sprintf('Postpone update message',Command)); %#ok + + % ===== Disable =========================================== + fprintf('Click here to disable the update feature forever: '); + Command = sprintf([... + 'File_ID = fopen(''%s'',''w'');',... + 'fprintf(File_ID,''DISABLE'');',... + 'fclose(File_ID);',... + 'setappdata(0,''distFig_Update'',1);',... + 'fprintf(''distFig update feature disabled!\\n'');' + ],Path); + disp(sprintf('Disable update feature',Command)); %#ok + catch + setappdata(0,'distFig_Update',1); + end + end + catch Error %#ok + % ===== Error handling ============================================ + try + Path_Error = [Path(1:end-numel([filesep 'distFig_Update.txt'])), [filesep 'distFig_Error.mat']]; + fprintf([ + 'There was an error in distFig when checking for updates.',... + '\nPlease report this to AndersSSimonsen@GMail.com by sending the error-file "distFig_Error.mat" located in %s. :)\n\n'],Path_Error); + AppData = getappdata(0); %#ok + save(Path_Error); + catch + end + end +end \ No newline at end of file diff --git a/Add-Ons/distFig.png b/Add-Ons/distFig.png new file mode 100644 index 0000000..da4efa3 Binary files /dev/null and b/Add-Ons/distFig.png differ diff --git a/Add-Ons/distFig_Error.mat b/Add-Ons/distFig_Error.mat new file mode 100644 index 0000000..6278527 Binary files /dev/null and b/Add-Ons/distFig_Error.mat differ diff --git a/Add-Ons/distFig_Update.txt b/Add-Ons/distFig_Update.txt new file mode 100644 index 0000000..8c9a77a --- /dev/null +++ b/Add-Ons/distFig_Update.txt @@ -0,0 +1 @@ +2023 5 9 \ No newline at end of file diff --git a/Add-Ons/distinguishable_colors.m b/Add-Ons/distinguishable_colors.m new file mode 100644 index 0000000..f9e9e25 --- /dev/null +++ b/Add-Ons/distinguishable_colors.m @@ -0,0 +1,152 @@ +function colors = distinguishable_colors(n_colors,bg,func) +% DISTINGUISHABLE_COLORS: pick colors that are maximally perceptually distinct +% +% When plotting a set of lines, you may want to distinguish them by color. +% By default, Matlab chooses a small set of colors and cycles among them, +% and so if you have more than a few lines there will be confusion about +% which line is which. To fix this problem, one would want to be able to +% pick a much larger set of distinct colors, where the number of colors +% equals or exceeds the number of lines you want to plot. Because our +% ability to distinguish among colors has limits, one should choose these +% colors to be "maximally perceptually distinguishable." +% +% This function generates a set of colors which are distinguishable +% by reference to the "Lab" color space, which more closely matches +% human color perception than RGB. Given an initial large list of possible +% colors, it iteratively chooses the entry in the list that is farthest (in +% Lab space) from all previously-chosen entries. While this "greedy" +% algorithm does not yield a global maximum, it is simple and efficient. +% Moreover, the sequence of colors is consistent no matter how many you +% request, which facilitates the users' ability to learn the color order +% and avoids major changes in the appearance of plots when adding or +% removing lines. +% +% Syntax: +% colors = distinguishable_colors(n_colors) +% Specify the number of colors you want as a scalar, n_colors. This will +% generate an n_colors-by-3 matrix, each row representing an RGB +% color triple. If you don't precisely know how many you will need in +% advance, there is no harm (other than execution time) in specifying +% slightly more than you think you will need. +% +% colors = distinguishable_colors(n_colors,bg) +% This syntax allows you to specify the background color, to make sure that +% your colors are also distinguishable from the background. Default value +% is white. bg may be specified as an RGB triple or as one of the standard +% "ColorSpec" strings. You can even specify multiple colors: +% bg = {'w','k'} +% or +% bg = [1 1 1; 0 0 0] +% will only produce colors that are distinguishable from both white and +% black. +% +% colors = distinguishable_colors(n_colors,bg,rgb2labfunc) +% By default, distinguishable_colors uses the image processing toolbox's +% color conversion functions makecform and applycform. Alternatively, you +% can supply your own color conversion function. +% +% Example: +% c = distinguishable_colors(25); +% figure +% image(reshape(c,[1 size(c)])) +% +% Example using the file exchange's 'colorspace': +% func = @(x) colorspace('RGB->Lab',x); +% c = distinguishable_colors(25,'w',func); + +% Copyright 2010-2011 by Timothy E. Holy + + % Parse the inputs + if (nargin < 2) + bg = [1 1 1]; % default white background + else + if iscell(bg) + % User specified a list of colors as a cell aray + bgc = bg; + for i = 1:length(bgc) + bgc{i} = parsecolor(bgc{i}); + end + bg = cat(1,bgc{:}); + else + % User specified a numeric array of colors (n-by-3) + bg = parsecolor(bg); + end + end + + % Generate a sizable number of RGB triples. This represents our space of + % possible choices. By starting in RGB space, we ensure that all of the + % colors can be generated by the monitor. + n_grid = 30; % number of grid divisions along each axis in RGB space + x = linspace(0,1,n_grid); + [R,G,B] = ndgrid(x,x,x); + rgb = [R(:) G(:) B(:)]; + if (n_colors > size(rgb,1)/3) + error('You can''t readily distinguish that many colors'); + end + + % Convert to Lab color space, which more closely represents human + % perception + if (nargin > 2) + lab = func(rgb); + bglab = func(bg); + else + C = makecform('srgb2lab'); + lab = applycform(rgb,C); + bglab = applycform(bg,C); + end + + % If the user specified multiple background colors, compute distances + % from the candidate colors to the background colors + mindist2 = inf(size(rgb,1),1); + for i = 1:size(bglab,1)-1 + dX = bsxfun(@minus,lab,bglab(i,:)); % displacement all colors from bg + dist2 = sum(dX.^2,2); % square distance + mindist2 = min(dist2,mindist2); % dist2 to closest previously-chosen color + end + + % Iteratively pick the color that maximizes the distance to the nearest + % already-picked color + colors = zeros(n_colors,3); + lastlab = bglab(end,:); % initialize by making the "previous" color equal to background + for i = 1:n_colors + dX = bsxfun(@minus,lab,lastlab); % displacement of last from all colors on list + dist2 = sum(dX.^2,2); % square distance + mindist2 = min(dist2,mindist2); % dist2 to closest previously-chosen color + [~,index] = max(mindist2); % find the entry farthest from all previously-chosen colors + colors(i,:) = rgb(index,:); % save for output + lastlab = lab(index,:); % prepare for next iteration + end +end + +function c = parsecolor(s) + if ischar(s) + c = colorstr2rgb(s); + elseif isnumeric(s) && size(s,2) == 3 + c = s; + else + error('MATLAB:InvalidColorSpec','Color specification cannot be parsed.'); + end +end + +function c = colorstr2rgb(c) + % Convert a color string to an RGB value. + % This is cribbed from Matlab's whitebg function. + % Why don't they make this a stand-alone function? + rgbspec = [1 0 0;0 1 0;0 0 1;1 1 1;0 1 1;1 0 1;1 1 0;0 0 0]; + cspec = 'rgbwcmyk'; + k = find(cspec==c(1)); + if isempty(k) + error('MATLAB:InvalidColorString','Unknown color string.'); + end + if k~=3 || length(c)==1, + c = rgbspec(k,:); + elseif length(c)>2, + if strcmpi(c(1:3),'bla') + c = [0 0 0]; + elseif strcmpi(c(1:3),'blu') + c = [0 0 1]; + else + error('MATLAB:UnknownColorString', 'Unknown color string.'); + end + end +end diff --git a/Add-Ons/grabit.m b/Add-Ons/grabit.m new file mode 100644 index 0000000..3e6829c --- /dev/null +++ b/Add-Ons/grabit.m @@ -0,0 +1,2067 @@ +function grabit(fname) + +%GRABIT Extracts data points from an image file. +% +% GRABIT starts a GUI program for extracting data from an image file. +% It is capable of reading in BMP, JPG, TIF, GIF, and PNG files (anything +% that is readable by IMREAD). Multiple data sets can be extracted from a +% single image file, and the data is saved as an n-by-2 matrix variable in +% the workspace. It can also be renamed and saved as a MAT file. +% +% Following steps should be taken: +% 1. Load the image file. +% 2. Calibrate axes dimensions. You will be prompted to select 4 points +% on the image. Zoom and pan enabled. +% 3. Grab points by clicking on points. Right-click to delete a point. +% Image can be zoomed and panned. +% 4. Multiple data sets will remain in memory so long as the GUI is open. +% Variables can be renamed, saved to file, or edited in Array Editor. +% +% Panning is achieved by clicking and dragging on the image. Double-click +% to center view. Right click and drag to zoom in and out. In addition, +% there are keyboard shortcuts for zooming: +% - zoom in +% - zoom out +% - reset view +% +% This code will also work for extracting data points from a tilted or a +% skewed image (even upside-down or mirrored). The calibration stage +% ensures that the imperfect orientation or quality of the image is +% accounted for. +% +% The types of files that will most likely work are BMP, JPG, TIF, GIF (up +% to 8-bit), and PNG files. Basically, any format supported by the IMREAD +% is accepted. +% +% GRABIT(FILENAME) will start the GUI program and open the image file +% FILENAME. +% +% Type GRABIT('-sample') to load a sample image. +% +% +% VERSIONS: +% v1.0 - first version +% v1.1 - use imshow instead of image (takes care of colormap) +% v1.5 - convert to a GUI version +% v1.6 - added functionality to open a file from the command window and +% embedded a sample image file to the function +% v1.6.1 - changed cross cursor to crosshair +% v1.6.2 - brought back 'image' in case the user doesn't have Image Toolbox +% v1.6.5 - fixed zoom problem in R14 +% v2.0 - major code change. added zoom feature during calibration. added +% panning feature. (March 3, 2006) +% v2.1 - store sample image as HEX to reduce file size. (March 6, 2006) +% v2.1.1 - animate view change and zooming for a better visual perception +% (March 11, 2006) +% v2.1.5 - added features: double-click to center view. right-click and +% drag to zoom. other minor code changes. (March 16, 2006) +% v2.2 - fixed loadImageFcn bug. (May 4, 2006) +% v2.3 - fixed bug to work with grayscale image (Jan, 2007) +% + +% Created in Matlab R13. Tested up to R2006b +% +% Copyright 2003 +% Jiro Doke +% +% To Do: Capability to deal with logarithmic axes +% + +%-------------------------------------------------------------------------- +% Initialize +%-------------------------------------------------------------------------- +sh = get(0, 'ShowHiddenHandles'); +set(0, 'ShowHiddenHandles', 'on'); + +% close existing windows +im = findobj('type', 'figure', 'tag', 'GrabitGUI'); +if ishandle(im) + close(im); +end + +set(0, 'ShowHiddenHandles', sh); + +% background colors +bgcolor1 = [.8, .8, .8]; +bgcolor2 = [ 1, 1, 1]; +bgcolor3 = [.7, .7, .7]; +bgcolor4 = [ 1, .5, .5]; + +%-------------------------------------------------------------------------- +% Custom cursor pointers +%-------------------------------------------------------------------------- +zoomPointer = [ + 2 2 2 2 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 1 1 1 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 2 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 NaN NaN NaN NaN 2 2 2 2 NaN NaN NaN NaN NaN + 2 1 2 NaN NaN 2 2 1 1 1 1 2 2 NaN NaN NaN + 2 1 2 NaN 2 1 1 2 2 2 2 1 1 2 NaN NaN + NaN 2 NaN NaN 2 1 2 2 1 1 2 2 1 2 NaN NaN + NaN NaN NaN 2 1 2 2 2 1 1 2 2 2 1 2 NaN + NaN NaN NaN 2 1 2 1 1 1 1 1 1 2 1 2 NaN + NaN NaN NaN 2 1 2 1 1 1 1 1 1 2 1 2 NaN + NaN NaN NaN 2 1 2 2 2 1 1 2 2 2 1 2 NaN + NaN NaN NaN NaN 2 1 2 2 1 1 2 2 1 2 NaN NaN + NaN NaN NaN NaN 2 1 1 2 2 2 2 1 1 1 2 NaN + NaN NaN NaN NaN NaN 2 2 1 1 1 1 2 1 1 1 2 + NaN NaN NaN NaN NaN NaN NaN 2 2 2 2 NaN 2 1 1 1 + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 2 1 2 + ]; + +zoomInOutPointer = [ + NaN NaN NaN 2 2 NaN NaN NaN NaN NaN NaN 1 1 1 NaN NaN + NaN NaN 2 1 1 2 NaN NaN NaN NaN 1 2 2 2 1 NaN + NaN 2 1 1 1 1 2 NaN NaN 1 2 2 1 2 2 1 + 2 1 1 1 1 1 1 2 NaN 1 2 1 1 1 2 1 + 2 1 2 1 1 2 1 2 NaN 1 2 2 1 2 2 1 + NaN 2 2 1 1 2 2 NaN NaN 1 1 2 2 2 1 NaN + NaN NaN 2 1 1 2 NaN NaN 1 1 1 1 1 1 NaN NaN + NaN NaN NaN 2 2 NaN NaN NaN 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN 2 2 NaN NaN NaN NaN NaN NaN 1 1 1 NaN NaN + NaN NaN 2 1 1 2 NaN NaN NaN NaN 1 2 2 2 1 NaN + NaN 2 2 1 1 2 2 NaN NaN 1 2 2 2 2 2 1 + 2 1 2 1 1 2 1 2 NaN 1 2 1 1 1 2 1 + 2 1 1 1 1 1 1 2 NaN 1 2 2 2 2 2 1 + NaN 2 1 1 1 1 2 NaN NaN 1 1 2 2 2 1 NaN + NaN NaN 2 1 1 2 NaN NaN 1 1 1 1 1 1 NaN NaN + NaN NaN NaN 2 2 NaN NaN NaN 1 1 NaN NaN NaN NaN NaN NaN + ]; + +% closed hand pointer (from Jérôme Briot) +closedHandPointer = [ + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN 2 2 NaN 2 2 NaN 2 2 NaN NaN NaN NaN + NaN NaN NaN 2 1 1 2 1 1 2 1 1 2 2 NaN NaN + NaN NaN 2 1 2 2 1 2 2 1 2 2 1 1 2 NaN + NaN NaN 2 1 2 2 2 2 2 2 2 2 1 2 1 2 + NaN NaN NaN 2 1 2 2 2 2 2 2 2 2 2 1 2 + NaN NaN 2 1 1 2 2 2 2 2 2 2 2 2 1 2 + NaN 2 1 2 2 2 2 2 2 2 2 2 2 2 1 2 + NaN 2 1 2 2 2 2 2 2 2 2 2 2 2 1 2 + NaN 2 1 2 2 2 2 2 2 2 2 2 2 1 2 NaN + NaN NaN 2 1 2 2 2 2 2 2 2 2 2 1 2 NaN + NaN NaN NaN 2 1 2 2 2 2 2 2 2 1 2 NaN NaN + NaN NaN NaN NaN 2 1 2 2 2 2 2 2 1 2 NaN NaN + NaN NaN NaN NaN 2 1 2 2 2 2 2 2 1 2 NaN NaN + ]; + +% X-axis Origin pointer +xoPointer = [ + 2 2 2 2 2 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 1 1 1 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 1 2 2 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 NaN 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 2 2 NaN NaN 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN 1 1 NaN NaN NaN 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN 1 1 1 NaN 1 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN 1 1 1 1 1 NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN NaN 1 1 1 NaN NaN NaN NaN 1 1 1 NaN + NaN NaN NaN NaN 1 1 1 1 1 NaN NaN 1 NaN NaN NaN 1 + NaN NaN NaN 1 1 1 NaN 1 1 1 NaN 1 NaN NaN NaN 1 + NaN NaN NaN 1 1 NaN NaN NaN 1 1 NaN 1 NaN NaN NaN 1 + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1 1 1 NaN + ]; + +% X-axis Max pointer +xmPointer = [ + 2 2 2 2 2 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 1 1 1 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 1 2 2 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 NaN 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 2 2 NaN NaN 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN 1 1 NaN NaN NaN 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN 1 1 1 NaN 1 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN 1 1 1 1 1 NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN NaN 1 1 1 NaN NaN NaN 1 NaN NaN NaN 1 + NaN NaN NaN NaN 1 1 1 1 1 NaN NaN 1 1 NaN 1 1 + NaN NaN NaN 1 1 1 NaN 1 1 1 NaN 1 NaN 1 NaN 1 + NaN NaN NaN 1 1 NaN NaN NaN 1 1 NaN 1 NaN NaN NaN 1 + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1 NaN NaN NaN 1 + ]; + +% Y-axis Origin pointer +yoPointer = [ + 2 2 2 2 2 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 1 1 1 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 1 2 2 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 NaN 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 2 2 NaN NaN 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN 1 1 NaN NaN NaN 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN 1 1 1 NaN NaN 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN 1 1 1 1 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN NaN 1 1 1 1 NaN NaN NaN 1 1 1 NaN + NaN NaN NaN NaN NaN 1 1 1 NaN NaN NaN 1 NaN NaN NaN 1 + NaN NaN NaN 1 1 1 1 1 NaN NaN NaN 1 NaN NaN NaN 1 + NaN NaN NaN 1 1 1 NaN NaN NaN NaN NaN 1 NaN NaN NaN 1 + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1 1 1 NaN + ]; + +% Y-axis Max pointer +ymPointer = [ + 2 2 2 2 2 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 1 1 1 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 1 2 2 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 1 2 NaN 2 1 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + 2 2 2 NaN NaN 2 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN + NaN NaN NaN 1 1 NaN NaN NaN 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN 1 1 1 NaN NaN 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN 1 1 1 1 1 1 NaN NaN NaN NaN NaN NaN + NaN NaN NaN NaN NaN 1 1 1 1 NaN NaN 1 NaN NaN NaN 1 + NaN NaN NaN NaN NaN 1 1 1 NaN NaN NaN 1 1 NaN 1 1 + NaN NaN NaN 1 1 1 1 1 NaN NaN NaN 1 NaN 1 NaN 1 + NaN NaN NaN 1 1 1 NaN NaN NaN NaN NaN 1 NaN NaN NaN 1 + NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1 NaN NaN NaN 1 + ]; + +% zoom button icon +zoomIcon = [ + 1 1 1 1 1 0 0 0 0 1 1 1 1 1 1 1 + 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 + 1 1 0 0 0 1 1 1 1 0 0 0 1 1 1 1 + 1 0 0 1 1 1 0 0 1 1 1 0 0 1 1 1 + 1 0 0 1 1 1 0 0 1 1 1 0 0 1 1 1 + 0 0 1 1 1 1 0 0 1 1 1 1 0 0 1 1 + 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 + 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 + 0 0 1 1 1 1 0 0 1 1 1 1 0 0 1 1 + 1 0 0 1 1 1 0 0 1 1 1 0 0 1 1 1 + 1 0 0 1 1 1 0 0 1 1 1 0 0 1 1 1 + 1 1 0 0 0 1 1 1 1 0 0 0 0 0 1 1 + 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 + 1 1 1 1 1 0 0 0 0 1 1 0 0 0 0 0 + 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 + 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 + ]; + +% create zoom icon (RGB matrix) +fgID = zoomIcon==0; +bgID = ~fgID; +zI1 = zeros([size(zoomIcon), 3]); +zI2 = zeros([size(zoomIcon), 3]); +for id = 1:3 + tmp = zoomIcon; + tmp(fgID) = 0; + tmp(bgID) = bgcolor3(id); + zI1(:,:,id) = tmp; + tmp(bgID) = bgcolor4(id); + zI2(:,:,id) = tmp; +end + +% get screen size in pixels +un = get(0, 'units'); +set(0, 'units', 'pixels'); +screenSize = get(0, 'ScreenSize'); +sW = screenSize(3); +sH = screenSize(4); +set(0, 'units', un); + +% figure width and height (in pixels) +fW = sW-200; +fH = sH-100; + +im = figure(... + 'units' , 'pixels', ... + 'position' , [100, 50, fW, fH], ... + 'backingstore' , 'off', ... + 'doublebuffer' , 'on', ... + 'name' , 'Grabit', ... + 'numbertitle' , 'off', ... + 'menubar' , 'none', ... + 'color' , bgcolor1, ... + 'pointer' , 'arrow', ... + 'visible' , 'off', ... + 'interruptible' , 'off', ... + 'busyaction' , 'cancel', ... + 'resizefcn' , @figResizeFcn, ... + 'windowbuttonupfcn' , @winBtnUpFcn, ... + 'keypressfcn' , @keyPressFcn, ... + 'deletefcn' , 'delete(timerfind(''name'', ''BtnUpTimer''));', ... + 'tag' , 'GrabitGUI', ... + 'defaultUicontrolUnits' , 'pixels', ... + 'defaultUicontrolBackgroundColor' , bgcolor3, ... + 'defaultUicontrolFontname' , 'Verdana', ... + 'defaultUicontrolFontUnits' , 'pixels', ... + 'defaultUicontrolFontsize' , 10, ... + 'defaultUicontrolInterruptible' , 'off', ... + 'defaultUicontrolBusyAction' , 'cancel', ... + 'defaultAxesFontName' , 'Verdana', ... + 'defaultAxesUnits' , 'pixels', ... + 'defaultAxesFontSize' , 8); + +panelW = 0.8*fW; +uicontrol(... + 'style' , 'frame', ... + 'position' , [10, fH-110, panelW, 100], ... + 'backgroundcolor' , bgcolor2); +uicontrol(... + 'style' , 'pushbutton', ... + 'string' , 'Load Image...', ... + 'callback' , {@loadImageFcn, []}, ... + 'position' , [15, fH-40, 200, 25], ... + 'tag' , 'LoadImageBtn'); +uicontrol(... + 'style' , 'edit', ... + 'backgroundcolor' , bgcolor2, ... + 'string' , '', ... + 'position' , [220, fH-40, panelW-215, 25], ... + 'horizontalalignment' , 'left', ... + 'enable' , 'inactive', ... + 'tag' , 'ImageFileLoc'); + +uicontrol(... + 'style' , 'frame', ... + 'position' , [15, fH-75, 3*(panelW-20)/4-5, 30], ... + 'backgroundcolor' , bgcolor2); +uicontrol(... + 'style' , 'togglebutton', ... + 'string' , 'Calibrate', ... + 'buttondownfcn' , @calibrateImageFcn, ... + 'position' , [20, fH-72, panelW/4-25, 25], ... + 'enable' , 'off', ... + 'tag' , 'CalibrateImageBtn'); +calibFrameX = panelW/4-5; +calibFrameW = panelW/2-10; +uicontrol(... + 'style' , 'text', ... + 'position' , [calibFrameX+5, fH-70, calibFrameW/8, 15], ... + 'string' , 'Xo:', ... + 'fontweight' , 'bold', ... + 'horizontalalignment' , 'right', ... + 'tooltipstring' , sprintf('Calibration:\nX-Axis Origin'), ... + 'backgroundcolor' , bgcolor2); +uicontrol(... + 'style' , 'text', ... + 'position' , [calibFrameX+5+calibFrameW/8, fH-70, calibFrameW/8, 15], ... + 'string' , ' NaN', ... + 'horizontalalignment' , 'left', ... + 'tag' , 'hXoValue', ... + 'tooltipstring' , sprintf('Calibration:\nX-Axis Origin'), ... + 'backgroundcolor' , bgcolor2); +uicontrol(... + 'style' , 'text', ... + 'position' , [calibFrameX+5+calibFrameW/4, fH-70, calibFrameW/8, 15], ... + 'string' , 'Xm:', ... + 'fontweight' , 'bold', ... + 'horizontalalignment' , 'right', ... + 'tooltipstring' , sprintf('Calibration:\nX-Axis Max'), ... + 'backgroundcolor' , bgcolor2); +uicontrol(... + 'style' , 'text', ... + 'position' , [calibFrameX+5+3*calibFrameW/8, fH-70, calibFrameW/8, 15], ... + 'string' , ' NaN', ... + 'horizontalalignment' , 'left', ... + 'tag' , 'hXmValue', ... + 'tooltipstring' , sprintf('Calibration:\nX-Axis Max'), ... + 'backgroundcolor' , bgcolor2); +uicontrol(... + 'style' , 'text', ... + 'position' , [calibFrameX+5+calibFrameW/2, fH-70, calibFrameW/8, 15], ... + 'string' , 'Yo:', ... + 'fontweight' , 'bold', ... + 'horizontalalignment' , 'right', ... + 'tooltipstring' , sprintf('Calibration:\nY-Axis Origin'), ... + 'backgroundcolor' , bgcolor2); +uicontrol(... + 'style' , 'text', ... + 'position' , [calibFrameX+5+5*calibFrameW/8, fH-70, calibFrameW/8, 15], ... + 'string' , ' NaN', ... + 'horizontalalignment' , 'left', ... + 'tag' , 'hYoValue', ... + 'tooltipstring' , sprintf('Calibration:\nY-Axis Origin'), ... + 'backgroundcolor' , bgcolor2); +uicontrol(... + 'style' , 'text', ... + 'position' , [calibFrameX+5+3*calibFrameW/4, fH-70, calibFrameW/8, 15], ... + 'string' , 'Ym:', ... + 'fontweight' , 'bold', ... + 'horizontalalignment' , 'right', ... + 'tooltipstring' , sprintf('Calibration:\nY-Axis Max'), ... + 'backgroundcolor' , bgcolor2); +uicontrol(... + 'style' , 'text', ... + 'position' , [calibFrameX+5+7*calibFrameW/8, fH-70, calibFrameW/8, 15], ... + 'string' , ' NaN', ... + 'horizontalalignment' , 'left', ... + 'tag' , 'hYmValue', ... + 'tooltipstring' , sprintf('Calibration:\nY-Axis Max'), ... + 'backgroundcolor' , bgcolor2); + +uicontrol(... + 'style' , 'togglebutton', ... + 'string' , 'Grab Points', ... + 'buttondownfcn' , @grabPointsFcn, ... + 'position' , [3*(panelW)/4, fH-72, panelW/4+5, 25], ... + 'enable' , 'off', ... + 'tag' , 'GrabPointsBtn'); +uicontrol(... + 'style' , 'togglebutton', ... + 'cdata' , zI1, ... + 'buttondownfcn' , @zoomBtnFcn, ... + 'position' , [15, fH-105, 25, 25], ... + 'enable' , 'inactive', ... + 'tag' , 'ZoomStateBtn'); +uicontrol(... + 'style' , 'pushbutton', ... + 'string' , 'Reset View ', ... + 'callback' , @resetViewFcn, ... + 'position' , [45, fH-105, 100, 25], ... + 'tag' , 'ResetViewBtn'); +uicontrol(... + 'style' , 'text', ... + 'position' , [150, fH-108, panelW-145, 31], ... + 'horizontalalignment' , 'center', ... + 'foregroundcolor' , [0 0 .5], ... + 'backgroundcolor' , bgcolor2, ... + 'fontsize' , 10, ... + 'string' , {'Click and drag to pan. Double-click to center. Right-click and drag to zoom.', ... + 'Keyboard Shortcuts: - zoom in, - zoom out, - reset view'}); + +rPanelX = 0.82 * fW; +rPanelW = fW - rPanelX - 10; +uicontrol(... + 'style' , 'listbox', ... + 'callback' , @selectVariableFcn, ... + 'position' , [rPanelX+10, 100, rPanelW-20, 0.6*fH], ... + 'backgroundcolor' , bgcolor2, ... + 'tooltipstring' , sprintf('Double-click to edit\nvariable in Array Editor'), ... + 'tag' , 'VariableList'); +uicontrol(... + 'style' , 'text', ... + 'string' , 'Data in Memory', ... + 'position' , [rPanelX+10, 0.6*fH+100, rPanelW-20, 20], ... + 'backgroundcolor' , bgcolor1, ... + 'fontweight' , 'bold'); +uicontrol(... + 'style' , 'pushbutton', ... + 'string' , 'Save to file as...', ... + 'position' , [rPanelX+10, 70, rPanelW-20, 25], ... + 'callback' , @variableManipulationFcn, ... + 'tooltipstring' , sprintf('Save variable as a MAT file or\nDouble-precision, tab-delimited TXT file'), ... + 'tag' , 'SaveAs'); +uicontrol(... + 'style' , 'pushbutton', ... + 'string' , 'Rename...', ... + 'position' , [rPanelX+10, 45, rPanelW-20, 25], ... + 'callback' , @variableManipulationFcn, ... + 'tooltipstring' , 'Rename variable in workspace', ... + 'tag' , 'Rename'); +uicontrol(... + 'style' , 'pushbutton', ... + 'string' , 'Delete...', ... + 'position' , [rPanelX+10, 20, rPanelW-20, 25], ... + 'callback' , @variableManipulationFcn, ... + 'tooltipstring' , 'Delete variable from workspace', ... + 'tag' , 'Delete'); + +axes(... + 'position' , [10, 10, 0.8*fW, fH-200], ... + 'visible' , 'on', ... + 'handlevisibility' , 'on', ... + 'box' , 'on', ... + 'drawmode' , 'fast', ... + 'xtick' , [], ... + 'ytick' , [], ... + 'interruptible' , 'off', ... + 'buttondownfcn' , @winBtnDownFcn, ... + 'tag' , 'ImageAxis'); +imAxRatio = (fH - 200) / (0.8 * fW); +title('', 'fontunits', 'pixels', 'fontsize', 24, 'color', 'red'); + +axes(... + 'position' , [rPanelX+20, 0.6*fH+150, rPanelW-30, 0.4*fH-190], ... + 'box' , 'on', ... + 'tag' , 'PreviewAxis'); + +uicontrol(... + 'style' , 'text', ... + 'string' , 'Preview Box', ... + 'fontweight' , 'bold', ... + 'position' , [rPanelX+20, fH-40, rPanelW-30, 25], ... + 'backgroundcolor' , bgcolor1); + +uicontrol(... + 'style' , 'edit', ... + 'backgroundcolor' , bgcolor4, ... + 'string' , 'Enter Value', ... + 'position' , [0 0 100 25], ... + 'horizontalalignment' , 'left', ... + 'visible' , 'off', ... + 'callback' , @coordinateEditFcn, ... + 'tag' , 'CoordinateEdit'); + +set(findobj(im, 'type', 'uicontrol'), 'units', 'normalized'); +set(findobj(im, 'type', 'axes'), 'units', 'normalized'); + +% create handles structure +handles = guihandles(im); +handles.zoomPointer = zoomPointer; +handles.zoomPointerHotSpot = [2 2]; +handles.zoomInOutPointer = zoomInOutPointer; +handles.zoomInOutPointerHotSpot = [9 9]; +handles.closedHandPointer = closedHandPointer; +handles.closedHandPointerHotSpot = [9 9]; +handles.xoPointer = xoPointer; +handles.xoPointerHotSpot = [2 2]; +handles.xmPointer = xmPointer; +handles.xmPointerHotSpot = [2 2]; +handles.yoPointer = yoPointer; +handles.yoPointerHotSpot = [2 2]; +handles.ymPointer = ymPointer; +handles.ymPointerHotSpot = [2 2]; +handles.zoomIconUp = zI1; +handles.zoomIconDown = zI2; +handles.curPointer = 'arrow'; +handles.curPointerData.CData = zoomPointer; +handles.curPointerData.HotSpot = [1 1]; +handles.state = 'normal'; +handles.bgcolor1 = bgcolor1; +handles.bgcolor2 = bgcolor2; +handles.bgcolor3 = bgcolor3; +handles.bgcolor4 = bgcolor4; +handles.imAxRatio = imAxRatio; +handles.I = []; +handles.map = []; +handles.savedVars = struct; +handles.isPanning = false; +handles.curTitle = ''; +handles.CurrentPointAxes = []; +handles.CurrentPointFig = []; +handles.timer = timer(... + 'Name', 'BtnUpTimer', ... + 'StartDelay', 0.2, ... + 'TimerFcn', {@btnUpTimerFcn, im}); + +guidata(im, handles); + +set(im, 'handlevisibility', 'callback'); + +if nargin == 1 && ischar(fname) + switch lower(fname) + case '-sample' + fname = createSampleImageFcn; + if ~isempty(fname) + loadImageFcn(handles.LoadImageBtn, [], fname); + try + pause(0.5); + delete(fname); + catch + errordlg(lasterr); + end + end + + otherwise + filename = which(fname); + if ~isempty(filename) + loadImageFcn(handles.LoadImageBtn, [], filename); + else + errordlg(sprintf('%s\nnot found.', fname)); + return; + end + end +end + +set(im, 'visible', 'on'); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% variableManipulationFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function variableManipulationFcn(varargin) +% This callback is called when one of the three buttons under the variable +% listbox is pressed. + +obj = varargin{1}; + +handles = guidata(obj); + +vars = fieldnames(handles.savedVars); +if isempty(vars) + return; +end +listboxVal = get(handles.VariableList, 'value'); +varName = vars{listboxVal}; +switch get(obj, 'Tag') + + case 'SaveAs' % save the variable as a .mat file + [fname, pname] = uiputfile(... + {'*.mat', 'MAT files (*.mat)'; ... + '*.txt', 'TXT files (*.txt)'}, ... + sprintf('Save ''%s'' as:', varName), ... + varName); + if ~isequal(fname, 0) && ~isequal(pname, 0) + saveDatFcn(pname, fname, handles.savedVars.(varName)) + end + + case 'Rename' % rename the variable in the base workspace + answer = inputdlg({sprintf('Rename ''%s'' as:', varName)}, ... + 'Rename...', 1, {varName}); + if ~isempty(answer) && ~strcmp(varName, answer{1}) + if ~(evalin('base', sprintf('exist(''%s'', ''var'')', answer{1}))) && ... + isempty(strmatch(answer{1}, vars, 'exact')) + newVarNames = vars; + newVarNames{listboxVal} = answer{1}; + for id = 1:length(vars) + tmp.(newVarNames{id}) = handles.savedVars.(vars{id}); + end + handles.savedVars = tmp; + showAllVarsFcn(handles); + set(handles.VariableList, 'value', listboxVal); + assignin('base', answer{1}, handles.savedVars.(answer{1})); + evalin('base', sprintf('clear %s;', varName)); + else + errordlg('That name is already in use.'); + return; + end + end + + case 'Delete' % delete the variable from the base workspace + btn = questdlg(sprintf('Delete ''%s'' from the workspace?', varName), ... + 'Delete from workspace...', 'Yes', 'No', 'No'); + switch btn + case 'Yes' + handles.savedVars = rmfield(handles.savedVars, varName); + showAllVarsFcn(handles); + evalin('base', sprintf('clear %s;', varName)); + case 'No' + end + +end + +guidata(obj, handles); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% saveDatFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function saveDatFcn(pname, fname, var) +% this function saves the variable to file + +[p, fname, ext] = fileparts(fname); +switch lower(ext) + case '.mat' + eval(sprintf('%s = var;', fname)); + save(fullfile(pname, [fname, ext]), fname, '-v6'); + case '.txt' + eval(sprintf('%s = var;', fname)); + save(fullfile(pname, [fname, ext]), fname, '-ascii', '-double', '-tabs'); + otherwise + errordlg('Unknown extension.'); +end + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% selectVariableFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function selectVariableFcn(varargin) +% this callback is called when a variable is selected from the variable +% listbox. When the variable is clicked, it will plot the data in the +% Preview Box above. If the variable is double-clicked, it will be opened +% in the Array Editor. It also ensures that the variable in the base +% workspace is the same copy as the variable stored in the GRABIT +% workspace. This means that if you change the contents of a variable in +% the base workspace (via other functions), then it will allow you to +% update the variable in the GRABIT workspace. + +obj = varargin{1}; + +handles = guidata(obj); + +sType = get(handles.GrabitGUI, 'SelectionType'); +switch sType + case {'normal', 'open'} % single or double click + vars = fieldnames(handles.savedVars); + if isempty(vars) + return; + end + listVal = get(obj, 'value'); + varName = vars{listVal}; + + % check to see if the stored var is the same as the var in the + % base workspace + if evalin('base', sprintf('exist(''%s'', ''var'')', varName)) + + % the copy in the base workspace must be a n-by-2 DOUBLE array + if strcmp(class(evalin('base', varName)), 'double') && ... + ndims(evalin('base', varName)) == 2 && ... + size(evalin('base', varName), 2) == 2 + + if ~isequal(evalin('base', varName), handles.savedVars.(varName)) + % may have been modified in the base workspace + btn = questdlg(sprintf('''%s'' may have been modified in the base workspace (e.g. Array Editor).\nUpdate the variable?', varName), ... + 'Modified Variable', 'Update Base Workspace', 'Update Grabit', 'Neither', 'Update Grabit'); + + switch btn + case 'Update Base Workspace' + assignin('base', varName, handles.savedVars.(varName)); + + case 'Update Grabit' + handles.savedVars.(varName) = evalin('base', varName); + showAllVarsFcn(handles); + set(obj, 'value', listVal); + + end + + end + + else + btn = questdlg(sprintf('''%s'' in the base workspace is different from the one in Grabit.\nUpdate the base workspace variable?', varName), ... + 'Wrong Variable', 'Update Base Workspace', 'Leave Untouched', 'Update Base Workspace'); + + switch btn + case 'Update Base Workspace' + assignin('base', varName, handles.savedVars.(varName)); + + end + + end + + else % the variable does not exist in base workspace, so make a copy + assignin('base', varName, handles.savedVars.(varName)); + end + + switch sType + case 'normal' % single click + axes(handles.PreviewAxis); + set(handles.PreviewLine, ... + 'xdata', handles.savedVars.(varName)(:, 1), ... + 'ydata', handles.savedVars.(varName)(:, 2)); + axis auto; + + case 'open' % double click + try + openvar(varName); + catch + errordlg(lasterr); + end + + end +end + +guidata(obj, handles); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% loadImageFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function loadImageFcn(varargin) +% this function loads an image file + +[obj, filename] = splitvar(varargin([1, 3])); + +handles = guidata(obj); + +if isempty(filename) + [fname, pathname] = uigetfile(... + {'*.bmp;*.jpg;*.jpeg;*.tif;*.tiff;*.gif;*.png', ... + 'Image Files (*.bmp, *.jpg, *.jpeg, *.tif, *.tiff, *.gif, *.png)'; + '*.bpm', 'BPM files (*.bpm)'; + '*.jpg;*jpeg', 'JPG files (*.jpg, *.jpeg)'; + '*.tif;*tiff', 'TIFF files (*.tif, *.tiff)'; + '*.gif', 'GIF files (*.gif)'; + '*.png', 'PNG files (*.png)'; + '*.*', 'All files (*.*)'}, 'Select an image file'); + if ischar(fname) + filename = fullfile(pathname, fname); + else + return; + end +end + +set(handles.ImageFileLoc, 'string', filename); + +try + %warning off; + [A, map] = imread(filename); + %warning on; +catch + errordlg(lasterr); + return; +end + +if ndims(A) == 3 %some TIFF files have wrong size matrices. + if size(A, 3)>3 + A = A(:, :, 1:3); + elseif size(A, 3)<3 + errordlg('This is a weird image file...possibly a bad TIFF file...'); + return; + end +end + +% Need this so that image shows up when not called by a CALLBACK +set(0, 'ShowHiddenHandles', 'on'); + +cla(handles.PreviewAxis); +handles.PreviewLine = line(NaN, NaN, ... + 'color' , 'blue', ... + 'linestyle' , '-', ... + 'marker' , '.', ... + 'tag' , 'PreviewLine', ... + 'parent' , handles.PreviewAxis); +axes(handles.ImageAxis); +cla(handles.ImageAxis); +NP = get(handles.GrabitGUI, 'nextplot'); % for compatibility with R14 + +if isempty(map) + imageInfo = imfinfo(filename); + if strcmpi(imageInfo.ColorType, 'grayscale') + colormap(gray(2^imageInfo.BitDepth)); + end +else + colormap(map); +end +iH = image(A); +set(iH, 'HitTest', 'off', 'EraseMode', 'normal'); +set(handles.ImageAxis, 'xtick', [], 'ytick', []); +axis equal; + +set(handles.GrabitGUI, 'nextplot', NP); +set(handles.ImageAxis, ... + 'drawmode' , 'fast', ... + 'tag' , 'ImageAxis', ... + 'handlevisibility', 'callback', ... + 'buttondownfcn' , @winBtnDownFcn); +set(get(handles.ImageAxis, 'title'), ... + 'string' , '', ... + 'fontunits' , 'pixels', ... + 'fontsize' , 24, ... + 'color' , 'red'); +handles.ImageLine = line(NaN, NaN, ... + 'color' , 'red', ... + 'linestyle' , 'none', ... + 'marker' , '.', ... + 'tag' , 'ImageLine', ... + 'hittest' , 'off'); +handles.CalibPtsH(:,1) = line(repmat(NaN, 2, 4), repmat(NaN, 2, 4)); +handles.CalibPtsH(:,2) = line(repmat(NaN, 2, 4), repmat(NaN, 2, 4)); +set(handles.CalibPtsH(:,1), ... + {'marker','color'}, {'o','r';'o','r';'o','b';'o','b'}, ... + 'markersize' , 10, ... + 'hittest' , 'off'); +set(handles.CalibPtsH(:,2), ... + {'marker','color'}, {'+','r';'x','r';'+','b';'x','b'}, ... + 'markersize' , 20, ... + 'hittest' , 'off'); + +% initialize image data +handles.I = A; +handles.map = map; +handles.CalibVals = []; +handles.CalibPts = [NaN, NaN, NaN, NaN]; +handles.CalibPtsIm = repmat(NaN, 4, 2); +handles.ImLimits = [get(handles.ImageAxis, 'xlim'); ... + get(handles.ImageAxis, 'ylim')]; + +set(handles.CalibrateImageBtn, ... + 'string', 'Calibrate', ... + 'enable', 'inactive', ... + 'value' , 0); +set(handles.GrabPointsBtn, ... + 'enable', 'off', ... + 'value' , 0); +set(handles.ZoomStateBtn, ... + 'enable', 'inactive', ... + 'value' , 0); +zoom off; + +set(0, 'ShowHiddenHandles', 'off'); + +guidata(obj, handles); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% calibrateImageFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function calibrateImageFcn(varargin) +% this function performs calibration of the image by prompting the user to +% select 4 points on the image as reference points. + +obj = varargin{1}; + +handles = guidata(obj); + +if isempty(handles.I) + set(obj, 'enable', 'off'); +else + switch get(obj, 'value') + case 0 % start calibration + set(obj, 'value', 1, 'backgroundcolor', handles.bgcolor4); + + handles.curPointer = 'custom'; + handles.curPointerData.CData = handles.xoPointer; + handles.curPointerData.HotSpot = handles.xoPointerHotSpot; + set(handles.GrabitGUI, ... + 'PointerShapeCData' , handles.curPointerData.CData, ... + 'PointerShapeHotSpot' , handles.curPointerData.HotSpot, ... + 'WindowButtonMotionFcn' , {@pointerFcn, handles, handles.curPointer}); + + set([handles.LoadImageBtn, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete], ... + 'enable', 'off'); + + set(handles.CalibPtsH, 'xdata', NaN, 'ydata', NaN); + handles.CalibVals = []; + handles.CalibPts = [NaN, NaN, NaN, NaN]; + handles.CalibPtsIm = repmat(NaN, 4, 2); + set([handles.hXoValue, handles.hXmValue, ... + handles.hYoValue, handles.hYmValue], ... + 'string', ' NaN'); + + % this is the first calibration point: X-Axis Origin + handles.curTitle = 'Click on the ORIGIN of x-axis'; + set(get(handles.ImageAxis, 'title'), ... + 'string', handles.curTitle); + + % change state to CALIBRATION + handles.state = 'calibration'; + + case 1 % stop (prematurely) calibration + set(obj, ... + 'value' , 0, ... + 'backgroundcolor' , handles.bgcolor3, ... + 'string' , 'Calibrate'); + handles.curTitle = ''; + set(get(handles.ImageAxis, 'title'), 'string', ''); + + handles.curPointer = 'arrow'; + set(handles.GrabitGUI, ... + 'WindowButtonMotionFcn' , {@pointerFcn, handles, handles.curPointer}); + + set([handles.LoadImageBtn, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete], ... + 'enable', 'on'); + + % calibration was prematurely stopped, so reset all values + set(handles.CalibPtsH, 'xdata', NaN, 'ydata', NaN); + handles.CalibVals = []; + handles.CalibPts = [NaN, NaN, NaN, NaN]; + handles.CalibPtsIm = repmat(NaN, 4, 2); + set([handles.hXoValue, handles.hXmValue, ... + handles.hYoValue, handles.hYmValue], ... + 'string', ' NaN'); + + set(handles.GrabPointsBtn, 'enable', 'off'); + set(handles.CoordinateEdit, 'visible', 'off'); + + % change state to NORMAL + handles.state = 'normal'; + end +end + +guidata(obj, handles); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% grabPointsFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function grabPointsFcn(varargin) +% this function is used to extract data points by prompting the user to +% select points on the image. + +obj = varargin{1}; + +handles = guidata(obj); + +switch get(obj, 'value') + case 0 % initiate point grabbing + calib = handles.CalibVals; + + axes(handles.ImageAxis); + set(handles.ImageAxis, ... + 'xlim', handles.ImLimits(1,:), ... + 'ylim', handles.ImLimits(2,:)); + set(handles.ImageLine, 'xdata', NaN, 'ydata', NaN); + handles.curTitle = {'Grab points by clicking on data points.', ... + ' or to delete previous point. to finish.'}; + set(get(handles.ImageAxis, 'title'), ... + 'string', handles.curTitle); + + set(handles.PreviewLine, 'xdata', NaN, 'ydata', NaN); + set(handles.PreviewAxis, ... + 'xlim', [min([calib.Xo calib.Xm]) max([calib.Xo calib.Xm])], ... + 'ylim', [min([calib.Yo calib.Ym]) max([calib.Yo calib.Ym])]); + + handles.ImDat = []; + handles.TrueDat = []; + + handles.curPointer = 'crosshair'; + set(handles.GrabitGUI, ... + 'WindowButtonMotionFcn', {@pointerFcn, handles, handles.curPointer}); + + set(obj, ... + 'value' , 1, ... + 'string' , 'Grabbing Points (0)', ... + 'backgroundcolor' , handles.bgcolor4); + set([handles.CalibrateImageBtn, ... + handles.LoadImageBtn, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete], ... + 'enable', 'off'); + + % change state to GRAB + handles.state = 'grab'; + + case 1 % finish point grabbing + set(obj, ... + 'value' , 0, ... + 'string' , 'Grab Points', ... + 'backgroundcolor' , handles.bgcolor1); + + handles.curTitle = ''; + set(get(handles.ImageAxis, 'title'), 'string', ''); + handles.curPointer = 'arrow'; + set(handles.GrabitGUI, 'WindowButtonMotionFcn', {@pointerFcn, handles, handles.curPointer}); + set(handles.CalibrateImageBtn, 'enable', 'inactive'); + set([handles.LoadImageBtn, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete], ... + 'enable', 'on'); + if ~isempty(handles.TrueDat) % some points were grabbed + varNames = fieldnames(handles.savedVars); + varNames{end + 1} = findNextVarNameFcn(varNames); + handles.savedVars.(varNames{end}) = handles.TrueDat; + assignin('base', varNames{end}, handles.savedVars.(varNames{end})); + showAllVarsFcn(handles); + end + + % change to NORMAL state + handles.state = 'normal'; +end + +guidata(obj, handles); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% showAllVarsFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function showAllVarsFcn(handles) +% this function shows all data set variables that exist in the GRABIT +% workspace in the variable listbox. + +varNames = fieldnames(handles.savedVars); + +if isempty(varNames) + listboxStr = {''}; +else + for id = 1:length(varNames) + [m, n] = size(handles.savedVars.(varNames{id})); + listboxStr{id} = sprintf('%s [%dx%d]', varNames{id}, m, n); + end +end + +set(handles.VariableList, 'string', listboxStr, 'value', length(listboxStr)); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% findNextVarNameFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function newVarName = findNextVarNameFcn(varNames) +% this helper function determines the next available variable name by +% checking the existing variable names in the base workspace and GRABIT +% workspace. + +wsVarNames = evalin('base', 'who'); +vars = unique([wsVarNames(:); varNames(:)]); +idx = 1; +while 1 + if isempty(strmatch(sprintf('Data%03d', idx), vars, 'exact')) + newVarName = sprintf('Data%03d', idx); + return; + else + idx = idx + 1; + end +end + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% zoomBtnFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function zoomBtnFcn(varargin) +% this function toggles the zoom state + +obj = varargin{1}; + +handles = guidata(obj); + +switch get(obj, 'value') + case 0 + set(obj, ... + 'value' , 1, ... + 'backgroundcolor', handles.bgcolor4, ... + 'cdata' , handles.zoomIconDown); + udata.titlestring = get(get(handles.ImageAxis, 'Title'), 'string'); + udata.btnstate = get([handles.LoadImageBtn, ... + handles.CalibrateImageBtn, ... + handles.GrabPointsBtn, ... + handles.VariableList, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete],'enable'); + udata.imgstate = get(handles.ImageAxis, 'ButtonDownFcn'); + udata.handlevisibility = get(handles.ImageAxis, 'handlevisibility'); + set(obj, 'userdata', udata); + + set(get(handles.ImageAxis, 'Title'), 'string', 'Zoom ON'); + set([handles.LoadImageBtn, ... + handles.CalibrateImageBtn, ... + handles.GrabPointsBtn, ... + handles.VariableList, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete], 'enable', 'off'); + set(handles.ImageAxis, 'ButtonDownFcn', ''); + zoom('on'); + handles.curPointerData.CData = get(handles.GrabitGUI, 'PointerShapeCData'); + handles.curPointerData.HotSpot = get(handles.GrabitGUI, 'PointerShapeHotSpot'); + set(handles.GrabitGUI, ... + 'PointerShapeCData' , handles.zoomPointer, ... + 'PointerShapeHotSpot' , handles.zoomPointerHotSpot, ... + 'WindowButtonMotionFcn' , {@pointerFcn, handles, 'custom'}, ... + 'keypressfcn' , ';'); % this prevents switching to command window + + % this seems necessary in some versions of Matlab + set(handles.ImageAxis, 'handlevisibility', 'on'); + + case 1 + set(obj, ... + 'value', 0, ... + 'backgroundcolor', handles.bgcolor3, ... + 'cdata', handles.zoomIconUp); + zoom('off'); + + %---------------------------------------------------------------------- + % If zoom created a compact view window, expand it to fill the whole + % axes. + %---------------------------------------------------------------------- + xl = get(handles.ImageAxis, 'xlim'); xrng = diff(xl); + yl = get(handles.ImageAxis, 'ylim'); yrng = diff(yl); + if abs(yrng/xrng - handles.imAxRatio) > .01 % wrong axes ratio + if yrng/xrng > handles.imAxRatio + xrng = yrng / handles.imAxRatio; + xl = mean(xl) + [-0.5, 0.5] * xrng; + else + yrng = xrng * handles.imAxRatio; + yl = mean(yl) + [-0.5, 0.5] * yrng; + end + set(handles.ImageAxis, 'xlim', xl, 'ylim', yl); + end + %---------------------------------------------------------------------- + + udata = get(obj, 'userdata'); + set(get(handles.ImageAxis, 'Title'), 'string', udata.titlestring); + set(handles.ImageAxis, 'handlevisibility', udata.handlevisibility); + set([handles.LoadImageBtn, ... + handles.CalibrateImageBtn, ... + handles.GrabPointsBtn, ... + handles.VariableList, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete], {'enable'}, udata.btnstate); + set(handles.ImageAxis, 'ButtonDownFcn', udata.imgstate); + set(handles.GrabitGUI, ... + 'PointerShapeCData' , handles.curPointerData.CData, ... + 'PointerShapeHotSpot' , handles.curPointerData.HotSpot, ... + 'WindowButtonMotionFcn' , {@pointerFcn, handles, handles.curPointer}, ... + 'keypressfcn' , @keyPressFcn); +end + +guidata(obj, handles); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% pointerFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function pointerFcn(varargin) +% this changes the pointer based on whether the cursor is in the image +% axes. + +[handles, ptr] = splitvar(varargin(3:4)); + +pt = get(handles.ImageAxis, 'CurrentPoint'); +xl = get(handles.ImageAxis, 'xlim'); +yl = get(handles.ImageAxis, 'ylim'); +if pt(1,1) > xl(1) && pt(1,1) < xl(2) && pt(1,2) > yl(1) && pt(1,2) < yl(2) + set(handles.GrabitGUI, 'pointer', ptr); +else + set(handles.GrabitGUI, 'pointer', 'arrow'); +end + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% figResize +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function figResizeFcn(varargin) +% this function makes sure the axis fills the whole axes extent + +obj = varargin{1}; + +handles = guidata(obj); + +axis(handles.ImageAxis, 'equal'); +handles.imAxRatio = diff(get(handles.ImageAxis, 'ylim')) / ... + diff(get(handles.ImageAxis, 'xlim')); +handles.ImLimits = [get(handles.ImageAxis, 'xlim'); ... + get(handles.ImageAxis, 'ylim')]; + +guidata(obj, handles); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% keyPressFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function keyPressFcn(varargin) +% this is for the keyboard shortcuts. During 'grab' mode, +% deletes the last point clicked and ends the 'grab' mode. + +obj = varargin{1}; + +handles = guidata(obj); + +if ~isempty(handles.I) + k = lower(get(obj, 'CurrentKey')); + + switch k + case 'a' % zoom in + xl = get(handles.ImageAxis, 'xlim'); xrng = diff(xl); + yl = get(handles.ImageAxis, 'ylim'); yrng = diff(yl); + + % prevent zooming in too much. + % set the limit to 64x zoom. + if xrng >= size(handles.I, 2)/64*2 + % animate zoom + for id = 0:0.2:1 + set(handles.ImageAxis, ... + 'xlim', xl + id * xrng / 4 * [1, -1], ... + 'ylim', yl + id * yrng / 4 * [1, -1]); + drawnow; + end + end + + case 'z' % zoom out + xl = get(handles.ImageAxis, 'xlim'); xrng = diff(xl); + yl = get(handles.ImageAxis, 'ylim'); yrng = diff(yl); + % animate zoom + for id = 0:0.2:1 + set(handles.ImageAxis, ... + 'xlim', xl + id * xrng / 2 * [-1, 1], ... + 'ylim', yl + id * yrng / 2 * [-1, 1]); + drawnow; + end + + case 'space' % reset view + resetViewFcn(handles.ResetViewBtn); + + case {'backspace', 'delete'} + + switch handles.state + case 'grab' + if ~handles.isPanning + + if isempty(handles.ImDat) + return; + else + handles.ImDat(end, :) = []; + handles.TrueDat(end, :) = []; + end + + set(handles.PreviewLine, ... + 'xdata', handles.TrueDat(:, 1), ... + 'ydata', handles.TrueDat(:, 2)); + set(handles.ImageLine, ... + 'xdata', handles.ImDat(:, 1), ... + 'ydata', handles.ImDat(:, 2)); + + set(handles.GrabPointsBtn, 'string', sprintf('Grabbing Points (%d)', size(handles.ImDat, 1))); + + guidata(obj, handles); + end + + end + + case {'return', 'enter'} + + switch handles.state + case 'grab' + grabPointsFcn(handles.GrabPointsBtn); + + end + + end +end + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% resetViewFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function resetViewFcn(varargin) +% this function resets the view + +obj = varargin{1}; + +handles = guidata(obj); + +if ~isempty(handles.I) + xl = get(handles.ImageAxis, 'xlim'); + yl = get(handles.ImageAxis, 'ylim'); + xd = (handles.ImLimits(1, :) - xl) / 10; + yd = (handles.ImLimits(2, :) - yl) / 10; + % animate zoom + for id = 0:10 + set(handles.ImageAxis, ... + 'xlim', xl + id * xd, ... + 'ylim', yl + id * yd); + drawnow; + end +end + +% take focus away +loseFocusFcn(handles) + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% loseFocusFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function loseFocusFcn(handles) +% attempt to take focus away by setting the ENABLE property to off and then +% back to the original setting + +settings = get([handles.LoadImageBtn, ... + handles.ResetViewBtn, ... + handles.VariableList, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete], ... + 'enable'); +set([handles.LoadImageBtn, ... + handles.ResetViewBtn, ... + handles.VariableList, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete], ... + 'enable', 'off'); +drawnow; +set([handles.LoadImageBtn, ... + handles.ResetViewBtn, ... + handles.VariableList, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete], ... + {'enable'}, settings); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% winBtnDownFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function winBtnDownFcn(varargin) +% this function is called when the mouse click initiates + +obj = varargin{1}; + +handles = guidata(obj); + +if strcmpi(get(handles.timer, 'Running'), 'on') || isempty(handles.I) + return; +end + +handles.CurrentPointAxes = get(handles.ImageAxis, 'CurrentPoint'); +handles.CurrentPointFig = get(handles.GrabitGUI, 'CurrentPoint'); + +switch get(handles.GrabitGUI, 'SelectionType') + case 'normal' + + set(handles.CoordinateEdit, 'visible', 'off'); + id = find(isnan(handles.CalibPts)); + if ~isempty(id) + set(handles.CalibPtsH(id(1),:), 'xdata', NaN, 'ydata', NaN); + end + + % first call winBtnMotionPauseFcn to prevent immediate click-n-drag + set(handles.GrabitGUI, ... + 'WindowButtonMotionFcn', ... + {@winBtnMotionPauseFcn, handles, handles.CurrentPointAxes(1,1:2), clock}); + + case 'alt' + + set(handles.CoordinateEdit, 'visible', 'off'); + id = find(isnan(handles.CalibPts)); + if ~isempty(id) + set(handles.CalibPtsH(id(1),:), 'xdata', NaN, 'ydata', NaN); + end + + xl = get(handles.ImageAxis, 'XLim');midX = (xl(1)+xl(2))/2; + yl = get(handles.ImageAxis, 'YLim');midY = (yl(1)+yl(2))/2; + figPos = get(handles.GrabitGUI, 'Position'); + handles.curTitle = get(get(handles.ImageAxis, 'title'), 'string'); + set(handles.GrabitGUI, ... + 'Pointer', 'custom', ... + 'PointerShapeCData' , handles.zoomInOutPointer, ... + 'PointerShapeHotSpot' , handles.zoomInOutPointerHotSpot, ... + 'WindowButtonMotionFcn' , {@zoomMotionFcn, handles, ... + get(handles.GrabitGUI, 'CurrentPoint'), ... + figPos(4), ... + size(handles.I, 2), ... + midX, ... + midY, ... + diff(xl)/2, ... + diff(yl)/2}); + + set(get(handles.ImageAxis, 'title'), 'string', 'Zooming...'); + +end + +guidata(obj, handles); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% zoomMotionFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function zoomMotionFcn(varargin) +% this performs the click-n-drag zooming function. The pointer location +% relative to the initial point determines the amount of zoom (in or out). + +[obj, handles, initPt, figHt, horizPx, midX, ... + midY, rngXhalf, rngYhalf] = splitvar(varargin([1, 3:end])); + +pt = get(obj, 'CurrentPoint'); + +% get relative pointer location (y-coord only). +% power law allows for the inverse to work: +% C^(x) * C^(-x) = 1 +% Choose C to get "appropriate" zoom factor +r = 30 ^ ((initPt(2) - pt(2)) / figHt); + +% make sure it doesn't zoom in too much. +% the limit is based on the size of the original image. +% set limit to 64x zoom. +if r < horizPx/64/rngXhalf/2 % stop zoom + set(get(handles.ImageAxis, 'title'), 'string', 'Max Zoom Reached'); + set(obj, ... + 'Pointer' , 'arrow', ... + 'WindowButtonMotionFcn' , ''); +else + set(handles.ImageAxis, ... + 'XLim', [midX - r * rngXhalf, midX + r * rngXhalf], ... + 'YLim', [midY - r * rngYhalf, midY + r * rngYhalf]); +end + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% winBtnMotionPauseFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function winBtnMotionPauseFcn(varargin) +% this prevents click-n-drag from happening for X seconds. This is useful +% because users may move the mouse as they are clicking. + +[obj, handles, xy, c] = splitvar(varargin([1, 3:end])); + +if etime(clock, c) > .15 % waits .15 seconds before dragging occurs + set(obj, ... + 'Pointer' , 'custom', ... + 'PointerShapeCData' , handles.closedHandPointer, ... + 'PointerShapeHotSpot' , handles.closedHandPointerHotSpot); + set(obj, 'WindowButtonMotionFcn', {@winBtnMotionFcn, handles.ImageAxis, xy}); + handles.curTitle = get(get(handles.ImageAxis, 'title'), 'string'); + set(get(handles.ImageAxis, 'title'), 'string', 'Panning...'); + handles.isPanning = true; + guidata(obj, handles); +end + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% winBtnMotionFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function winBtnMotionFcn(varargin) +% this function is called when click-n-drag (panning) is happening + +[axH, xy] = splitvar(varargin(3:4)); + +pt = get(axH, 'CurrentPoint'); +set(axH, ... + 'xlim', get(axH, 'xlim')+(xy(1)-pt(1,1)), ... + 'ylim', get(axH, 'ylim')+(xy(2)-pt(1,2))); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% winBtnUpFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function winBtnUpFcn(varargin) +% this is called when the mouse button is released. It initiates the button +% down timer object (see btnUpTimerFcn). This timer waits for 0.2 seconds +% before any action is taken. This is in order to detect a double click. If +% a double click is detected, the single click action is NOT executed. + +obj = varargin{1}; + +handles = guidata(obj); +if ~isempty(handles.I) % there is an image displayed + switch get(obj, 'SelectionType') + case 'normal' + if strcmpi(get(handles.timer, 'Running'), 'off') + + % start the timer which waits some time to see if double-clicking + % occurs + start(handles.timer); + + set(obj, ... + 'Pointer' , handles.curPointer, ... + 'PointerShapeCData' , handles.curPointerData.CData, ... + 'PointerShapeHotSpot' , handles.curPointerData.HotSpot, ... + 'WindowButtonMotionFcn' , {@pointerFcn, handles, handles.curPointer}); + + set(get(handles.ImageAxis, 'title'), 'string', handles.curTitle); + end + + case 'alt' + set(obj, ... + 'Pointer' , handles.curPointer, ... + 'PointerShapeCData' , handles.curPointerData.CData, ... + 'PointerShapeHotSpot' , handles.curPointerData.HotSpot, ... + 'WindowButtonMotionFcn' , {@pointerFcn, handles, handles.curPointer}); + + set(get(handles.ImageAxis, 'title'), 'string', handles.curTitle); + end +end + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% btnUpTimerFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function btnUpTimerFcn(varargin) + +figH = varargin{3}; + +handles = guidata(figH); + +switch get(handles.GrabitGUI, 'SelectionType') + case 'open' % double click + % this will center the view + + % get current units + un = get([0, handles.GrabitGUI, handles.ImageAxis], 'units'); + + set([0, handles.GrabitGUI, handles.ImageAxis], 'units', 'pixels'); + pt = get(0, 'PointerLocation'); + figPos = get(handles.GrabitGUI, 'Position'); + pt2 = pt - figPos(1:2); + axPos = get(handles.ImageAxis, 'position'); + + % check to see if pointer is inside the image axes + if pt2(1) > axPos(1) && pt2(1) < axPos(1)+axPos(3) && ... + pt2(2) > axPos(2) && pt2(2) < axPos(2)+axPos(4) + xl = get(handles.ImageAxis, 'xlim'); xrng = diff(xl); + yl = get(handles.ImageAxis, 'ylim'); yrng = diff(yl); + x = (pt2(1)-axPos(1))/axPos(3)*xrng+xl(1); + y = (axPos(2)+axPos(4)-pt2(2))/axPos(4)*yrng+yl(1); + + % animate (slide) to the new location. this may give a better + % visual perception of the view change + + % determine how fast to animate, depending on the location of the + % pointer + interval = ceil(norm((figPos(1:2)+axPos(1:2)+axPos(3:4)/2) - pt)/30); + + if interval + ld = (([x, y] - [xrng, yrng]/2) - [xl(1), yl(1)])/interval; + pd = ((figPos(1:2)+axPos(1:2)+axPos(3:4)/2) - pt)/interval; + else + % interval == 0, meaning it's the same point + ld = [0, 0]; + pd = [0, 0]; + end + + for id = 0:interval + set(handles.ImageAxis, ... + 'xlim', xl + id * ld(1), ... + 'ylim', yl + id * ld(2)); + + % center the pointer location + set(0, ... + 'PointerLocation', pt + id * pd); + drawnow; + end + end + + % reset UNITS + set([0, handles.GrabitGUI, handles.ImageAxis], {'units'}, un); + + case 'normal' % single click + + switch handles.state + case 'grab' + if ~handles.isPanning && ~isempty(handles.CurrentPointAxes) + calib = handles.CalibVals; + + X = handles.CurrentPointAxes(1, 1); + Y = handles.CurrentPointAxes(1, 2); + + % the point on the image + handles.ImDat(end + 1, :) = [X, Y]; + + % the true data point coordinates + handles.TrueDat(end + 1, :) = ([calib.Xo; calib.Yo] + ... + [calib.e1 calib.e2] \ [X - calib.Xxo; Y - calib.Yyo])'; + set(handles.PreviewLine, ... + 'xdata', handles.TrueDat(:, 1), ... + 'ydata', handles.TrueDat(:, 2)); + set(handles.ImageLine, ... + 'xdata', handles.ImDat(:, 1), ... + 'ydata', handles.ImDat(:, 2)); + + set(handles.GrabPointsBtn, 'string', sprintf('Grabbing Points (%d)', size(handles.ImDat, 1))); + + end + + case 'calibration' + if ~handles.isPanning && ~isempty(handles.CurrentPointAxes) + id = find(isnan(handles.CalibPts)); + pt = handles.CurrentPointAxes; + set(handles.CalibPtsH(id(1),:), 'xdata', pt(1,1), 'ydata', pt(1,2)); + handles.CalibPtsIm(id(1),:) = pt(1,1:2); + set(handles.CoordinateEdit, ... + 'units' , 'pixels', ... + 'position', [handles.CurrentPointFig+[5, 5], 100, 25], ... + 'visible' , 'on', ... + 'string' , 'Enter Value'); + end + + end +end + +handles.CurrentPointAxes = []; +handles.CurrentPointFig = []; +handles.isPanning = false; + +guidata(handles.GrabitGUI, handles); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% coordinateEditFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function coordinateEditFcn(varargin) +% this function is called when a value is entered in the edit box for +% calibration values + +obj = varargin{1}; + +handles = guidata(obj); + +strs = {'Click on the MAXIMUM value of x-axis', ... + 'Click on the ORIGIN of y-axis', ... + 'Click on the MAXIMUM value of y-axis', ... + ''}; +ptrs = {'xmPointer', 'yoPointer', 'ymPointer'}; +hs = {'hXoValue', 'hXmValue', 'hYoValue', 'hYmValue'}; + +val = str2double(get(obj, 'string')); +if ~isnan(val) + id = find(isnan(handles.CalibPts)); + if ~isempty(id) + handles.CalibPts(id(1)) = val; + set(handles.(hs{id(1)}), 'string', sprintf(' %g', val)); + set(obj, 'visible', 'off'); + handles.curTitle = strs{id(1)}; + set(get(handles.ImageAxis, 'title'), 'string', strs{id(1)}); + if id(1) == 4 % last calibration point + handles = calculateCalibrationFcn(handles); + else + handles.curPointerData.CData = handles.(ptrs{id(1)}); + handles.curPointerData.HotSpot = handles.([ptrs{id(1)} 'HotSpot']); + set(handles.GrabitGUI, ... + 'PointerShapeCData' , handles.curPointerData.CData, ... + 'PointerShapeHotSpot' , handles.curPointerData.HotSpot); + end + else + set(obj, 'string', ''); + end +else + set(obj, 'string', ''); +end + +guidata(handles.GrabitGUI, handles); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% calculateCalibrationFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function handles = calculateCalibrationFcn(handles) +% this function calculates the calibration values + +Xxo = handles.CalibPtsIm(1,1); +Yxo = handles.CalibPtsIm(1,2); +Xxm = handles.CalibPtsIm(2,1); +Yxm = handles.CalibPtsIm(2,2); +Xyo = handles.CalibPtsIm(3,1); +Yyo = handles.CalibPtsIm(3,2); +Xym = handles.CalibPtsIm(4,1); +Yym = handles.CalibPtsIm(4,2); + +v1 = [Xxm - Xxo; Yxm - Yxo]; +v2 = [Xym - Xyo; Yym - Yyo]; + +Xo = handles.CalibPts(1); +Xm = handles.CalibPts(2); +Yo = handles.CalibPts(3); +Ym = handles.CalibPts(4); + +Xlength = Xm - Xo; +Ylength = Ym - Yo; + +% the basis vectors in the MATLAB domain +e1 = v1 / Xlength; +e2 = v2 / Ylength; + +% rearrage axes +C = [e1 e2] \ [Xyo - Xxo; Yyo - Yxo]; +blahX = [Xxo; Yxo] + C(2) * e2; Xxo = blahX(1); Yxo = blahX(2); +blahY = [Xyo; Yyo] - C(1) * e1; Xyo = blahY(1); Yyo = blahY(2); + +calib.Xo = Xo; +calib.Xm = Xm; +calib.Yo = Yo; +calib.Ym = Ym; +calib.e1 = e1; +calib.e2 = e2; +calib.Xxo = Xxo; +calib.Yyo = Yyo; + +handles.CalibVals = calib; +set(handles.GrabPointsBtn, ... + 'enable', 'inactive'); +set(handles.CalibrateImageBtn, ... + 'value' , 0, ... + 'backgroundcolor' , handles.bgcolor3, ... + 'enable' , 'inactive', ... + 'string' , 'Re-Calibrate'); + +handles.state = 'normal'; + +handles.curPointer = 'arrow'; +set(handles.GrabitGUI , ... + 'WindowButtonMotionFcn' , {@pointerFcn, handles, handles.curPointer}); + +set([handles.LoadImageBtn, ... + handles.SaveAs, ... + handles.Rename, ... + handles.Delete], ... + 'enable', 'on'); + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% splitvar +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function varargout = splitvar(varargout) +% this function splits input arguments into individual variables. + + +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +% createSampleImageFcn +%-------------------------------------------------------------------------- +%-------------------------------------------------------------------------- +function fname = createSampleImageFcn +% this function creates a temporary image file in the temp directory by +% loading in a sample binary image data. + +str = [ + '4749463839611002CA01F70000000000800000008000808000000080800080008080C0' + 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']; + +% convert hex to dec +s = hex2dec(reshape(deblank(reshape(str', 1, [])), 2, [])'); + +fname = [tempname '.gif']; +fid = fopen(fname, 'w'); +if fid > 0 + fwrite(fid, s); + fclose(fid); +else + fname = ''; + errordlg('Error trying to create sample image.'); +end \ No newline at end of file diff --git a/Add-Ons/grabit/license.txt b/Add-Ons/grabit/license.txt new file mode 100644 index 0000000..cae4cd5 --- /dev/null +++ b/Add-Ons/grabit/license.txt @@ -0,0 +1,27 @@ +Copyright (c) 2016, The MathWorks, Inc. +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are +met: + + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in + the documentation and/or other materials provided with the distribution. + * In all cases, the software is, and all modifications and derivatives + of the software shall be, licensed to you solely for use in conjunction + with MathWorks products and service offerings. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE +LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +POSSIBILITY OF SUCH DAMAGE. diff --git a/Add-Ons/license.txt b/Add-Ons/license.txt new file mode 100644 index 0000000..ec26bf2 --- /dev/null +++ b/Add-Ons/license.txt @@ -0,0 +1,24 @@ +Copyright (c) 2015, Anders Simonsen +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are +met: + + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in + the documentation and/or other materials provided with the distribution + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE +LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +POSSIBILITY OF SUCH DAMAGE. diff --git a/Add-Ons/line_fewer_markers_v4/example.png b/Add-Ons/line_fewer_markers_v4/example.png new file mode 100644 index 0000000..17229b4 Binary files /dev/null and b/Add-Ons/line_fewer_markers_v4/example.png differ diff --git a/Add-Ons/line_fewer_markers_v4/example_.png b/Add-Ons/line_fewer_markers_v4/example_.png new file mode 100644 index 0000000..7b4167f Binary files /dev/null and b/Add-Ons/line_fewer_markers_v4/example_.png differ diff --git a/Add-Ons/line_fewer_markers_v4/line_fewer_markers.m b/Add-Ons/line_fewer_markers_v4/line_fewer_markers.m new file mode 100644 index 0000000..721fee2 --- /dev/null +++ b/Add-Ons/line_fewer_markers_v4/line_fewer_markers.m @@ -0,0 +1,245 @@ +% line_fewer_markers - line with controlled amount of markers and correct legend behaviour +% +% LINE_FEWER_MARKERS(X,Y,NUM_MARKERS) adds the line in vectors X and Y to the current axes +% with exactly NUM_MARKERS markers drawn. +% +% LINE_FEWER_MARKERS(X,Y,NUM_MARKERS,'PropertyName',PropertyValue,...) plots the data +% stored in the vectors X and Y. +% +% LINE_FEWER_MARKERS returns handles to LINE/MARKER objects. +% +% [H1,H2,H3] = LINE_FEWER_MARKERS(X,Y,NUM_MARKERS,'PropertyName',PropertyValue,...) +% performs the actions as above and returns the handles of all the plotted lines/markers. +% H1 = handle to the main marker(1 point); it may be put in array and used with legend +% H2 = handle to the continuous line (as in H2=plot()) +% H3 = handle to all other markers +% +% Property/Value pairs and descriptions: +% +% Spacing - 'x' : ordinary uniform along x +% - 'curve' : equal lengths along curve y(x) +% - 'logx' : to be used with logarithmic x scale +% +% LockOnMax - 0 : first marker on 1st data point +% - 1 : offset all markers such that one marker on first max of y(x) +% +% LegendLine - 'on' : default, reproduce linestyle also in legend +% - 'off' : shows only marker in legend +% +% LineSpec: same as for LINE: LineStyle,LineWidth,Marker,MarkerSize,MarkerFaceColor... +% +% +% Example: plot 3 curves with 9,9, and 15 markers each, using different input styles +% +% figure; hold on; +% t = 0:0.005:pi; +% line_fewer_markers(t*180/pi,cos(t) ,9, '--bs','spacing','curve'); +% line_fewer_markers(t*180/pi,sin(t) ,9, '-.ro','MarkerFaceColor','g', ... +% 'markersize',6,'linewidth',2); +% grey1 = [1 1 1]*0.5; +% line_fewer_markers(t*180/pi,sin(t).*cos(t) ,15, ':','marker','h','color',grey1, ... +% 'markerfacecolor',grey1,'linewidth',2,'LockOnMax',1); +% leg = legend('cos','sin','sin*cos','location','best'); +% +% Inspired by Ioannis Filippidis's answer: +% http://www.mathworks.com/matlabcentral/answers/2165-too-many-markers +% +% rev.4, Massimo Ciacci, October 17, 2014 +% +function [H1,H2,H3] = line_fewer_markers(x,y,num_Markers, varargin) + + +%% find marker spec in varargin and remove it; extract special params: LockOnMax,Spacing +if mod(length(varargin),2) + if ischar(varargin{1}) + linspec = varargin{1}; + extraArgs = varargin(2:end); + [varargInNoMk,varargInNoMkNoLn,lm,ms,mfc,LockOnMax,Spacing,LegendLine] = parseargsLineSpec(linspec,extraArgs); + else + error('odd sized [param | val] list, missing one param ?'); + end +else + [varargInNoMk,varargInNoMkNoLn,lm,ms,mfc,LockOnMax,Spacing,LegendLine] = parseargs(varargin{:}); +end + +%% input size check +if isvector(x) && isvector(y) + % make x,y row vectors + if iscolumn(x), x = x.'; end + if iscolumn(y), y = y.'; end +else + error('line_fewer_markers: input arguments must be 1D vectors'); +end + +% How the method works: plots 3 times: +% a) once only the line with all points with the style 'r--' and invisible handle, +% b) last time the markers, using fewer points with style 'ro' and again invisible handle. +% c) once with a visible handle, only the first point, using the complete style you specified (e.g. 'r--o') + +%% a) once only the line with all points with the style +H2 = line(x ,y ,varargInNoMk{:}); %no markers here +hasbehavior(H2,'legend',0); %prevent to appear in legends! + +%% b) last time the markers, using fewer points with style +if (strcmp(Spacing,'x') || strcmp(Spacing,'X')) + ti = round(linspace(1,length(x),num_Markers)); +elseif (strcmp(Spacing,'logx') || strcmp(Spacing,'log')) + xi = logspace(log10(x(2)),log10(x(end-1)),num_Markers); + ti = floor(interp1(x,(1:length(x)),xi)); +elseif (strcmp(Spacing,'curve') || strcmp(Spacing,'Curve')) + scaleY = 3/4; % 1/1 figure aspect ratio + yNrm = (y-min(y))./(max(y)-min(y))*scaleY; %NORMALIZE y scale in [0 1], height of display is prop to max(abs(y)) + xNrm = (x-min(x))./(max(x)-min(x)); %NORMALIZE x scale in [0 1] + + if (sum(isinf(yNrm))>0) || sum(isinf(x))>0 %spacing along curve not possible with infinites + ti = round(linspace(1,length(x),num_Markers)); + else + t = 1:length(x); + s = [0 cumsum(sqrt(diff(xNrm).^2+diff(yNrm).^2))];%measures length along the curve + si = (0:num_Markers-1)*s(end)/(num_Markers-1); %equally spaced lengths along the curve + si(end) = s(end); %fix last point to be within the curve + ti = round(interp1(s,t,si)); %find x index of markers + end +else + error('invalid spacing parameter'); +end +if LockOnMax + %set one ti on max if found + [Mv,idx] = max(y); idx=idx(1); + [mv,idxti] = min(abs(idx-ti)); + deltati = ti(idxti)-idx; + ti = max(1,min(ti-deltati,length(y))); +end +xi = x(ti); +yi = y(ti); +H3 = line(xi,yi,varargInNoMkNoLn{:},'Marker',lm,'MarkerSize',ms,'MarkerFaceColor',mfc,'LineStyle','none'); %plot markers only +hasbehavior(H3,'legend',0); %prevent to appear in legends! + +%% c) once with a visible handle, only the first point, using the complete style you specified +if strcmp(LegendLine,'on') + H1 = line(xi(1),yi(1),varargInNoMk{:},'Marker',lm,'MarkerSize',ms,'MarkerFaceColor',mfc); +else + H1 = line(xi(1),yi(1),varargInNoMk{:},'linestyle','none','Marker',lm,'MarkerSize',ms,'MarkerFaceColor',mfc); +end + + +%------------------------------------------------------------- +% PARSE FUNCTIONS +%------------------------------------------------------------- +% varargInNoMk = list of property pairs, marker specs removed +% varargInNoMkNoLn = list of property pairs, marker specs and line specs removed +function [varargInNoMk,varargInNoMkNoLn,lm,ms,mfc,LockOnMax,Spacing,LegendLine] = parseargs(varargin) +lm =[]; ms =[]; mfc=[]; LockOnMax=[]; Spacing=[]; LegendLine=[]; +varargInNoMk = {}; +varargInNoMkNoLn = {}; +arg_index = 1; +while arg_index <= length(varargin) + arg = varargin{arg_index}; + % extract special params and marker specs from arg list + if strcmp(arg,'marker') || strcmp(arg,'Marker') || strcmp(arg,'Mk') || strcmp(arg,'mk') + lm = varargin{arg_index+1}; + elseif strcmp(arg,'MarkerSize') || strcmp(arg,'markersize') || strcmp(arg,'Mks') || strcmp(arg,'mks') + ms = varargin{arg_index+1}; + elseif strcmp(arg,'MarkerFaceColor') || strcmp(arg,'markerfacecolor')||strcmp(arg,'MFC')||strcmp(arg,'mfc') + mfc = varargin{arg_index+1}; + elseif strcmp(arg,'LockOnMax') || strcmp(arg,'lockonmax') + LockOnMax = varargin{arg_index+1}; + elseif strcmp(arg,'Spacing') || strcmp(arg,'spacing') + Spacing = varargin{arg_index+1}; + elseif strcmp(arg,'LegendLine') || strcmp(arg,'legendline') + LegendLine = varargin{arg_index+1}; + else + % keep other params in arg list for line command + varargInNoMk = {varargInNoMk{:}, varargin{arg_index}, varargin{arg_index+1}}; + if ~strcmp(arg,'LineStyle') && ~strcmp(arg,'linestyle') + % exclude line params for marker only plot + varargInNoMkNoLn = {varargInNoMkNoLn{:}, varargin{arg_index}, varargin{arg_index+1}}; + end + end + arg_index = arg_index + 2; +end +%EXTRA DEFAULTS ARE SET HERE +if isempty(lm), lm = 'o' ; end +if isempty(ms), ms = 10 ; end +if isempty(mfc), mfc = 'none'; end +if isempty(LockOnMax), LockOnMax = 1 ; end +if isempty(Spacing), Spacing = 'x' ; end %%'x' -> marker delta-x constant; 'curve' : spacing constant along the curve length +if isempty(LegendLine), LegendLine = 'on' ; end + +%------------------------------------------------------------- +% Parse LineSpec string and other arguments +% varargInNoMk = list of property pairs, marker specs removed +% varargInNoMkNoLn = list of property pairs, marker specs and line specs removed +function [varargInNoMk,varargInNoMkNoLn,lm,ms,mfc,LockOnMax,Spacing,LegendLine] = parseargsLineSpec(linspec, extraArgs) +% b blue . point - solid +% g green o circle : dotted +% r red x x-mark -. dashdot +% c cyan + plus -- dashed +% m magenta * star (none) no line +% y yellow s square +% k black d diamond +% w white v triangle (down) +% ^ triangle (up) +% < triangle (left) +% > triangle (right) +% p pentagram +% h hexagram +varargInNoMk = {}; +varargInNoMkNoLn = {}; + +foundLine = false; +stringSearch = {'-.','--','-',':'}; +for ii=1:4 + if strfind(linspec, stringSearch{ii}) + foundLine = true; + ls = stringSearch{ii}; + linspec = setdiff(linspec,ls); + break + end +end +if foundLine + varargInNoMk = {varargInNoMk{:},'lineStyle',ls}; +else + varargInNoMk = {varargInNoMk{:},'lineStyle','-'}; +end + +if ~isempty(linspec) + foundCol = false; + stringSearch = {'b','g','r','c','m','y','k','w'}; + for ii=1:8 + if strfind(linspec, stringSearch{ii}) + foundCol = true; + colspec = stringSearch{ii}; + linspec = setdiff(linspec,colspec); + break + end + end + if foundCol + varargInNoMk = {varargInNoMk{:},'color',colspec}; + varargInNoMkNoLn = {varargInNoMkNoLn{:},'color',colspec}; + end +end + +if ~isempty(linspec) + foundMk = false; + stringSearch = {'.','o','x','+','*','s','d','v','^','<','>','p','h'}; + for ii=1:13 + if strfind(linspec, stringSearch{ii}) + foundMk = true; + mkspec = stringSearch{ii}; + break + end + end + if foundMk, lm = mkspec; else lm = 'none'; end +else + lm = 'none'; +end + + +[extraArgs1,unused,lm2,ms,mfc,LockOnMax,Spacing,LegendLine] = parseargs(extraArgs{:}); +if strcmp(lm,'none') && ~strcmp(lm2,'none') %if other marker specified in Property Pairs take that one + lm = lm2; +end +varargInNoMk = {varargInNoMk{:},extraArgs1{:}}; +varargInNoMkNoLn = {varargInNoMkNoLn{:},extraArgs1{:}}; + diff --git a/Add-Ons/line_fewer_markers_v4/test_lfm.m b/Add-Ons/line_fewer_markers_v4/test_lfm.m new file mode 100644 index 0000000..5211869 --- /dev/null +++ b/Add-Ons/line_fewer_markers_v4/test_lfm.m @@ -0,0 +1,24 @@ +clear all; close all; + +figure; hold on; set(gca,'FontSize',16); set(gca,'FontName','Times'); set(gcf,'Color',[1,1,1]); +xlabel('x');ylabel('y');title('a family plot with nice legend'); + +x = (1:1000); +xMid = (x(1)+2*x(end))/3; +parVals = [1 1.5 2 3]; + +num_Markers = 8; %<-------- +LineTypes = {'-.','-','--'}; +MarkerTypes = {'h','o','s','d','^','v','>','<','p'}; +colors = {'m','r','b',[1 1 1]*0.5}; +for ip=1:length(parVals) + col = colors{1+mod(ip,length(colors))}; + ls = LineTypes{1+mod(ip,length(LineTypes))}; + lm = MarkerTypes{1+mod(ip,length(MarkerTypes))}; + g = parVals(ip); + y = 1 + 1/g*abs(1e4./(xMid + (x-xMid/g).^(2-0.2*g))); % a function that changes with parameter g + legCell{ip} = ['fA, g=',num2str(g)]; %legend text + [p1,p2,p3] = line_fewer_markers(x,y,num_Markers,'color',col,'linestyle',ls, 'linewidth',2, 'marker', lm, 'markerfacecolor',col,'LockOnMax',1,'Spacing','curve','parent',gca); +end +lh = legend(legCell,'Location','NorthWest'); + diff --git a/Add-Ons/line_fewer_markers_v4/test_lfm_In_PlotYY.m b/Add-Ons/line_fewer_markers_v4/test_lfm_In_PlotYY.m new file mode 100644 index 0000000..2be4fad --- /dev/null +++ b/Add-Ons/line_fewer_markers_v4/test_lfm_In_PlotYY.m @@ -0,0 +1,15 @@ +clear all; close all; + +figure(10); hold on; set(gca,'FontSize',16); set(gca,'FontName','Times'); set(gcf,'Color',[1,1,1]); +x=(1:10); +y1=x.^2;y2=x.^3; + +f1 = @(x,y)line_fewer_markers(x,y,5,'ro'); +f2 = @(x,y)line_fewer_markers(x,y,8,'-.bs','Spacing','curve','markerfacecolor','g');%,'LegendLine','off'); +[yH,lh1,lh2] = plotyy(x,y1,x,y2,f1,f2) + +xlabel('x'); +ylabel(yH(1),'x^2') +ylabel(yH(2),'x^3') +legend([lh1,lh2],{'curve 1','curve 2'},'location','northwest') +set(gcf,'position',[100 100 900 600]); \ No newline at end of file diff --git a/Add-Ons/line_fewer_markers_v4/test_lfm_logScale.m b/Add-Ons/line_fewer_markers_v4/test_lfm_logScale.m new file mode 100644 index 0000000..8bac6b1 --- /dev/null +++ b/Add-Ons/line_fewer_markers_v4/test_lfm_logScale.m @@ -0,0 +1,19 @@ +clear all; close all; + +figure; hold on; grid on; +set(gca,'FontSize',16); set(gca,'FontName','Times'); set(gcf,'Color',[1,1,1]); +xlabel('f');ylabel('|H| [dB]'); + +f = logspace(log10(100),log10(10e6),100); +pS1= -2*pi*1e4; +pS2= -2*pi*1e5; +pS3= -2*pi*1e6; +G1 = -pS1./(pS1+2*pi*j*f); +G2 = -pS2./(pS2+2*pi*j*f); +G3 = -pS3./(pS3+2*pi*j*f); +h1=line_fewer_markers(f,20*log10(abs(G1)),8,'rs','spacing','logx','linewidth',2,'markerfacecolor','r') +h2=line_fewer_markers(f,20*log10(abs(G2)),8,'bp','spacing','logx','linewidth',2) +h3=line_fewer_markers(f,20*log10(abs(G3)),8,'mv','spacing','logx','linewidth',2,'markersize',6) +set(gca,'XScale','log') + +legend([h1,h2,h3],'G1','G2','G3','location','southwest'); diff --git a/Add-Ons/line_fewer_markers_v4/test_lfm_shortExample.m b/Add-Ons/line_fewer_markers_v4/test_lfm_shortExample.m new file mode 100644 index 0000000..32d2b7d --- /dev/null +++ b/Add-Ons/line_fewer_markers_v4/test_lfm_shortExample.m @@ -0,0 +1,10 @@ +clear all; close all; + +figure; hold on; set(gca,'FontSize',16); set(gca,'FontName','Times'); set(gcf,'Color',[1,1,1]); +xlabel('x');ylabel('y');title('a family plot with nice legend'); +t = 0:0.005:pi; +line_fewer_markers(t*180/pi,cos(t) ,9, '--bs','spacing','curve'); +line_fewer_markers(t*180/pi,sin(t) ,9, '-.ro','MFC','g','Mks',6,'linewidth',2); +grey1 = [1 1 1]*0.5; +line_fewer_markers(t*180/pi,sin(t).*cos(t) ,15, ':','Mk','p','color',grey1,'MFC',grey1,'linewidth',2,'LockOnMax',1); +leg = legend('cos','sin','sin*cos','location','best'); diff --git a/Add-Ons/line_fewer_markers_v4/test_lfm_shortExample_noLine.m b/Add-Ons/line_fewer_markers_v4/test_lfm_shortExample_noLine.m new file mode 100644 index 0000000..e407ed8 --- /dev/null +++ b/Add-Ons/line_fewer_markers_v4/test_lfm_shortExample_noLine.m @@ -0,0 +1,16 @@ +clear all; close all; + +figure; hold on; set(gca,'FontSize',16); set(gca,'FontName','Times'); set(gcf,'Color',[1,1,1]); +xlabel('x');ylabel('y');title('a family plot with nice legend'); +t = 0:0.005:pi; +grey1 = [1 1 1]*0.5; +% line_fewer_markers(t*180/pi,cos(t) ,9, '--bs','spacing','curve'); +% line_fewer_markers(t*180/pi,sin(t) ,9, '-.ro','MFC','g','Mks',6,'linewidth',2); +% line_fewer_markers(t*180/pi,sin(t).*cos(t) ,15, ':','Mk','p','color',grey1,'MFC',grey1,'linewidth',2,'LockOnMax',1); + +line_fewer_markers(t*180/pi,cos(t) ,9, '--bs','spacing','curve','LegendLine','off'); +line_fewer_markers(t*180/pi,sin(t) ,9, '-.ro','MFC','g','Mks',6,'linewidth',2,'LegendLine','off'); +line_fewer_markers(t*180/pi,sin(t).*cos(t) ,15, ':','Mk','p','color',grey1,'MFC',grey1,'linewidth',2,'LockOnMax',1,'LegendLine','off'); + + +leg = legend('cos','sin','sin*cos','location','best'); diff --git a/Add-Ons/matlab-openbis-master/LICENSE b/Add-Ons/matlab-openbis-master/LICENSE new file mode 100644 index 0000000..65c5ca8 --- /dev/null +++ b/Add-Ons/matlab-openbis-master/LICENSE @@ -0,0 +1,165 @@ + GNU LESSER GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + + This version of the GNU Lesser General Public License incorporates +the terms and conditions of version 3 of the GNU General Public +License, supplemented by the additional permissions listed below. + + 0. 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If the Library as you +received it does not specify a version number of the GNU Lesser +General Public License, you may choose any version of the GNU Lesser +General Public License ever published by the Free Software Foundation. + + If the Library as you received it specifies that a proxy can decide +whether future versions of the GNU Lesser General Public License shall +apply, that proxy's public statement of acceptance of any version is +permanent authorization for you to choose that version for the +Library. diff --git a/Add-Ons/matlab-openbis-master/OpenBis.m b/Add-Ons/matlab-openbis-master/OpenBis.m new file mode 100644 index 0000000..e37d216 --- /dev/null +++ b/Add-Ons/matlab-openbis-master/OpenBis.m @@ -0,0 +1,575 @@ +classdef OpenBis + % OpenBis High-level class for interacting with Python (pyBIS) Openbis objects + % This class creates a MATLAB OpenBis object that encapsulates the Python (pyBIS) Openbis object + % and provides methods for interacting with the Python (pyBIS) Openbis object. + % + % Usage: + % Construct the MATLAB OpenBis object like this: + % obi = OpenBis() + % This will ask for URL, user name and password to connect to openBIS server. + % These can also be provided as optional input arguments. + % + % Methods are generally called like this: + % spaces = obi.get_spaces() + % space = obi.get_space(code) + % + % Logout: + % obi.logout() + + + properties + pybis % Python Openbis object + end + + + methods + + %% Constructor method + function obj = OpenBis(varargin) + % OpenBis Constructor method for class OpenBis + % Creates the Python Openbis object and logs into the server + % Optional positional input arguments: + % url ... URL of the openBIS server (incl. port) + % user ... user name for openBIS + % pw ... password for openBIS + % Usage: + % obi = OpenBis() --> opens UI to enter URL, user name and password + % obi = OpenBis('server_url', 'user_name', 'user_password') + + if nargin > 0 + url = varargin{1}; + user = varargin{2}; + pw = varargin{3}; + else + [url, user, pw] = user_url_pw_inputdlg; + end + + o = py.pybis.Openbis(url, pyargs('verify_certificates', 0)); + o.login(user, pw, pyargs('save_token', 1)); + obj.pybis = o; + end + + function logout(obj) + %logout + % Log out of openBIS. + % Usage: + % obi.logout() + % + % After logout, the session token is no longer valid. + + obj.pybis.logout(); + end + + function tf= is_session_active(obj) + %is_session_active + % Check if the session token is still active. Returns true or false. + % Usage: + % true_false = obi.is_session_active() + + tf = obj.pybis.is_session_active(); + end + + function token = token(obj) + %token + % Returns the current session token. + % Usage: + % token = obi.token() + + token = char(obj.pybis.token); + end + + %% Masterdata methods + % this section defines Matlab equivalents of the following pyBIS methods: + % get_experiment_types + % get_sample_types + % get_material_types + % get_dataset_types + % get_terms + % get_tags + + function experiment_types = get_experiment_types(obj) + %get_experiment_types + % Return a table of all available experiment types. + % Usage: + % experiment_types = obi.get_experiment_types() + + experiment_types = obj.pybis.get_experiment_types(); + experiment_types = df_to_table(experiment_types.df); + end + + function sample_types = get_sample_types(obj) + %get_sample_types + % Return table of all available sample types. + % Usage: + % sample_types = obi.get_sample_types() + + sample_types = obj.pybis.get_sample_types(); + sample_types = df_to_table(sample_types.df); + end + + function material_types = get_material_types(obj) + %get_material_types + % Return table of all available material types. + % Usage: + % material_types = obi.get_material_types() + + material_types = obj.pybis.get_material_types(); + material_types = df_to_table(material_types.df); + end + + function dataset_types = get_dataset_types(obj) + %get_dataset_types + % Return table of all available dataset types. + % Usage: + % dataset_types = obi.get_dataset_types() + + dataset_types = obj.pybis.get_dataset_types(); + dataset_types = df_to_table(dataset_types.df); + end + + function terms = get_terms(obj) + %get_terms + % Return table of all available terms. + % Usage: + % terms = obi.get_terms() + + terms = obj.pybis.get_terms(); + terms = df_to_table(terms.df); + end + + function tags = get_tags(obj) + %get_tags + % Return table of all available tags. + % Usage: + % tags = obi.get_tags() + + tags = obj.pybis.get_tags(); + tags = df_to_table(tags.df); + end + + + %% Space methods + % this section defines Matlab equivalents of the following pyBIS methods: + % get_spaces + % get_space + % new_space + % space.delete + + function spaces = get_spaces(obj) + %get_spaces + % Return table of all available spaces. + % Usage: + % spaces = obi.get_spaces() + + spaces = obj.pybis.get_spaces(); + spaces = df_to_table(spaces.df); + end + + function space = get_space(obj, code) + %get_space + % Fetch space with matching space code and return the space object. + % An error is raised if a space with the code is not found on the server. + % Required input arguments: + % code ... space code + % Usage: + % space = obi.get_space('code') + + space = obj.pybis.get_space(code); + end + + function space = new_space(obj, code, description) + %new_space + % Create a new space with code and description and return the space object + % Required input arguments: + % code ... Space code + % description ... Space description + % Usage: + % space = obi.new_space('code', 'description') + + space = obj.pybis.new_space(pyargs('code', code, ... + 'description', description)); + space.save; + end + + function delete_space(obj, code, reason) + %delete_space + % Delete space with code and provide a reason for deletion + % Required input arguments: + % code ... Space code + % reason ... reason for deletion + % Usage: + % obi.delete_space('code', 'reason') + + space = obj.pybis.get_space(code); + space.delete(reason); + end + + + %% Project methods + % this section defines Matlab equivalents of the following pyBIS methods: + % get_projects + % get_project + % new_project + % project.delete + + function projects = get_projects(obj, space, code) + %get_projects + % Return table of matching projects. + % Input arguments: + % space ... space to fetch projects from + % project ... fetch projects matching code + % Usage: + % projects = obi.get_projects('space', 'code') + + projects = obj.pybis.get_projects(pyargs('space', space, 'code', code)); + projects = df_to_table(projects.df); + end + + function project = get_project(obj, id) + %get_project + % Fetch project with matching project id and return the project object. + % An error is raised if a project with the id is not found on the server. + % Required input arguments: + % id ... project id + % Usage: + % project = obi.get_project('id') + + project = obj.pybis.get_project(id); + end + + function project = new_project(obj, space, code, description) + %new_project + % Create a new project in space with code and description + % Return the project object + % Input arguments + % space ... Space code + % code ... Project code / id + % description ... Project description + % Usage: + % project = obi.new_project('space', 'code', 'description') + + space = obj.pybis.get_space(space); + project = space.new_project(pyargs('code', code, 'description', description)); + project.save(); + end + + function delete_project(obj, code, reason) + %delete_project + % Delete project with code and provide a reason for deletion + % Required input arguments: + % code ... Project code + % reason ... reason for deletion + % Usage: + % obi.delete_project('code', 'reason') + + project = obj.pybis.get_project(code); + project.delete(reason); + end + + + %% Experiment methods + % this section defines the following Matlab methods: + % get_experiments + % get_experiment + % new_experiment + + function experiments = get_experiments(obj, varargin) + %get_experiments + % Return table of matching experiments. + % Optional input arguments: + % space ... space to fetch experiments from + % type ... fetch experiments of specific type + % project ... project to fetch experiments from + % Usage: + % experiments = obi.get_experiments() + % experiments = obi.get_experiments('space', 'SPACE') + % experiments = obi.get_experiments('space', 'SPACE', 'type', 'UNKNOWN') + + space = ''; + type = ''; + project = ''; + + p = inputParser; + addRequired(p, 'obj'); + addParameter(p, 'space', space, @ischar); + addParameter(p, 'type', type, @ischar); + addParameter(p, 'project', project, @ischar); + parse(p, obj, varargin{:}); + a = p.Results; + + experiments = obj.pybis.get_experiments(pyargs('space', a.space, 'type', a.type, 'project', a.project)); + experiments = df_to_table(experiments.df); + end + + function experiment = get_experiment(obj, id) + %get_experiment + % Return experiment with identifier + % ID can be either the Space + Object code (e.g. /SPACE/123456789) or the PermID (e.g. 20181002164551373-1234) + % Usage: + % exp = obi.get_experiment('/SPACE/PROJECT/EXP') + % exp = obi.get_experiment('permID') + + experiment = obj.pybis.get_experiment(id); + end + + function experiment = new_experiment(obj, type, code, project) + %new_experiment + % Create a new experiment of specific type in a defined project + % Required input arguments: + % type ... new experiment type + % code ... new experiment code + % project ... project for new experiment ('SPACE/Project') + % Usage: + % experiment = obi.new_experiment('type', 'space', 'Space/Project') + + experiment = obj.pybis.new_experiment(pyargs('type', type, 'code', code, 'project', project)); + experiment.save(); + end + + + %% Object methods + % this section defines following Matlab methods related to openBIS objects / samples: + % get_object + % get_objects + % new_object + % delete_object + + function objects = get_objects(obj, varargin) + %get_objects + % Return a table of objects matching specified criteria + % Optional keyword arguments: + % id ... object identifier ('SPACE/PROJECT/') + % Usage: + % objects = obi.get_objects() + % objects = obi.get_objects('id', 'SPACE/') + + defaultId = ''; + + p = inputParser; + addRequired(p, 'obj'); + addParameter(p, 'id', defaultId, @ischar); + parse(p, obj, varargin{:}); + a = p.Results; + + objects = obj.pybis.get_objects(a.id); + objects = df_to_table(objects.df); + end + + function object = get_object(obj, id) + %get_object + % Return object (sample) corresponding to the id + % ID can be either the Space + Object code (e.g. /SPACE/123456789) or the PermID (e.g. 20181002164551373-1234) + % An error is raised if an object with the id is not found on the server. + % Required input arguments: + % id ... object id + % Usage: + % object = obi.get_object('id') + + object = obj.pybis.get_object(id); + end + + function object = new_object(obj, type, space, code) + %new_object + % Create a new object of type in space with code + % Return the object + % Input arguments + % type ... object type + % space ... Space code + % code ... object code + % Usage: + % object = obi.new_object('type', 'space', 'code') + + object = obj.pybis.new_object(pyargs('type', type, 'space', space, 'code', code)); + object.save(); + end + + function object = delete_object(obj, object, reason) + %delete_object + % Delete object and provide a reason for deletion + % Required input arguments: + % object ... object returned by get_object / new_object methods + % reason ... reason for deletion + % Usage: + % obi.delete_object(object, 'reason') + + object.delete(reason) + end + + + %% Dataset methods + % this section defines following Matlab methods: + % get_datasets + % get_dataset + % get_dataset_files + % dataset_download + % new_dataset + % new_dataset_container + + function datasets = get_datasets(obj, varargin) + %get_datasets + % Return table of matching datasets. + % Optional input arguments: + % code ... dataset code / permId + % type ... dataset type + % experiment ... datasets in experiment + % project ... datasets in project + % tags ... datasets with tags + % Usage: + % datasets = obi.get_datasets() + % datasets = obi.get_datasets('type', 'RAW_DATA') + % datasets = obi.get_datasets('experiment', '/SPACE/PROJECT/EXPERIMENT') + + defaultCode = ''; + defaultType = ''; + defaultExp = ''; + defaultProj = ''; + defaultTags = ''; + + p = inputParser; + addRequired(p, 'obj'); + addParameter(p, 'code', defaultCode, @ischar); + addParameter(p, 'type', defaultType, @ischar); + addParameter(p, 'experiment', defaultExp, @ischar); + addParameter(p, 'project', defaultProj, @ischar); + addParameter(p, 'tags', defaultTags, @ischar); + parse(p, obj, varargin{:}); + a = p.Results; + + datasets = obj.pybis.get_datasets(pyargs('code', a.code, 'type', a.type, 'experiment', a.experiment, ... + 'project', a.project, 'tags', a.tags)); + datasets = df_to_table(datasets.df); + end + + function dataset = get_dataset(obj, permid, varargin) + %get_dataset + % Get dataset with permId. An error is raised if a dataset with the id is not found on the server. + % Input arguments: + % permId ... dataset permId + % Usage: + % dataset = obi.get_dataset('permId') + + only_data = false; + + p = inputParser; + addRequired(p, 'obj'); + addRequired(p, 'permid', @ischar); + addOptional(p, 'only_data', only_data, @islogical); + parse(p, obj, permid, varargin{:}); + a = p.Results; + +% dataset = obj.pybis.get_dataset(pyargs('permid', a.permid, 'only_data', a.only_data)); + dataset = obj.pybis.get_dataset(a.permid); + end + + + function files = get_dataset_files(obj, dataset, varargin) + %get_dataset_files + % Get list of files in a dataset starting with start_folder. + % Input arguments: + % dataset ... dataset object returned by get_dataset + % start_folder ... starting folder for files (default: '/') + % Usage: + % files = obi.get_dataset_files(dataset) + + start_folder = '/'; + + p = inputParser; + addRequired(p, 'obj'); + addRequired(p, 'dataset'); + addOptional(p, 'start_folder', start_folder, @ischar); + parse(p, obj, dataset, varargin{:}); + a = p.Results; + + files = dataset.get_files(pyargs('start_folder', a.start_folder)); + files = df_to_table(files); + end + + function path_to_file = dataset_download(obj, dataset, files, varargin) + %dataset_download + % Download files in a dataset + % dataset ... dataset object returned by get_dataset + % files ... cell array of files + % destination ... folder to download to (default: data) + % wait_until_finished ... wait or download in the background (default: true) + % workers ... number of workers to use for download (default: 10) + % Usage: + % path_to_files = obi.dataset_download(dataset, {'file1', 'file2'}) + + destination = 'data'; + wait_until_finished = true; + workers = 10; + + p = inputParser; + addRequired(p, 'obj'); + addRequired(p, 'dataset'); + addRequired(p, 'files', @iscellstr); + addParameter(p, 'destination', destination, @ischar); + addParameter(p, 'wait_until_finished', wait_until_finished, @islogical); + addParameter(p, 'workers', workers, @isscalar); + + parse(p, obj, dataset, files, varargin{:}); + a = p.Results; + + dataset.download(pyargs('files', a.files, 'destination', a.destination, 'wait_until_finished', a.wait_until_finished, 'workers', int16(a.workers))); + + path_to_file = fullfile(a.destination, dataset.char, a.files); + + end + + function dataset = new_dataset(obj, type, object, file_list, varargin) + %new_dataset + % Create a new dataset with files + % type ... dataset type + % object ... object for dataset + % file_list ... list of files (cell string) to upload to new dataset + % properties ... structure with dataset properties (meta-data) + % Usage: + % dataset = obi.new_dataset('RAW_DATA', '/SPACE/PROJECT/OBJECT', {'file1', 'file2'}, 'properties', props) + + properties = struct; + + p = inputParser; + addRequired(p, 'obj'); + addRequired(p, 'type', @ischar); + addRequired(p, 'object', @ischar); + addRequired(p, 'file_list', @iscellstr); + addParameter(p, 'properties', properties, @isstruct); + + parse(p, obj, type, object, file_list, varargin{:}); + a = p.Results; + + dataset = obj.pybis.new_dataset(pyargs('type', a.type, 'sample', a.object, ... + 'files', a.file_list, 'props', a.properties)); + dataset.save(); + + end + + function dataset = new_dataset_container(obj, type, experiment, object) + %new_dataset_container + % Create a new dataset container + % type ... dataset container type + % experiment ... experiment for dataset container + % object ... object for dataset container + % Usage: + % dataset = obi.new_dataset_container('type', 'RAW_DATA', 'experiment', 'MY_EXP', 'object', 'MY_SAMPLE') + + p = inputParser; + addRequired(p, 'obj'); + addRequired(p, 'type', @ischar); + addRequired(p, 'experiment', @ischar); + addRequired(p, 'object', @ischar); + + parse(p, obj, type, experiment, object, file_list); + a = p.Results; + + dataset = obj.pybis.new_dataset(pyargs('type', a.type, 'experiment', a.experiment, 'sample', a.object, 'kind', 'CONTAINER')); + dataset.save(); + + end + + + end + +end + + diff --git a/Add-Ons/matlab-openbis-master/README.md b/Add-Ons/matlab-openbis-master/README.md new file mode 100644 index 0000000..7b43dea --- /dev/null +++ b/Add-Ons/matlab-openbis-master/README.md @@ -0,0 +1,7 @@ +# MATLAB toolbox for openBIS + +This repository provides a set of MATLAB functions that allow seemless integration between [MATLAB](https://mathworks.com/products/matlab.html) and the [openBIS](https://wiki-bsse.ethz.ch/display/bis/Home) data management system. The toolbox is written as a wrapper around the [pyBIS](https://sissource.ethz.ch/sispub/openbis/blob/master/pybis/src/python/README.md) Python API for openBIS. As MATLAB can call Python libraries directly (see https://ch.mathworks.com/help/matlab/call-python-libraries.html), all the functionality of pyBIS is directly available from within MATLAB. The main goal of the toolbox is to provide a more MATLABish way of accessing pyBIS fucntions. + +To get started, checkout the installation instructions in the repository's [Wiki](https://sissource.ethz.ch/hluetcke/matlab-openbis/wikis/home). A usage example is provided in the script [openbis_example.mlx](https://sissource.ethz.ch/hluetcke/matlab-openbis/blob/master/openbis_example.mlx) which can be run within the MATLAB Live Editor. Documentation is provided in the file [OpenBis.m](https://sissource.ethz.ch/hluetcke/matlab-openbis/blob/master/OpenBis.m). In the MATLAB Desktop UI, you can get the documentation by typing `doc OpenBis`. + +This repository is maintained by the [Scientific IT Services](https://sis.id.ethz.ch/) of [ETH Zurich](www.ethz.ch). diff --git a/Add-Ons/matlab-openbis-master/df_to_table.m b/Add-Ons/matlab-openbis-master/df_to_table.m new file mode 100644 index 0000000..7135acb --- /dev/null +++ b/Add-Ons/matlab-openbis-master/df_to_table.m @@ -0,0 +1,10 @@ +function [matlab_table] = df_to_table(df) +%df_to_table +% Returns a Matlab table for a Python dataframe + +csv_temp = sprintf('%s.csv', tempname); +df.to_csv(csv_temp); +matlab_table = readtable(csv_temp); +delete(csv_temp); + +end \ No newline at end of file diff --git a/Add-Ons/matlab-openbis-master/html/OpenBis.html b/Add-Ons/matlab-openbis-master/html/OpenBis.html new file mode 100644 index 0000000..29a410e --- /dev/null +++ b/Add-Ons/matlab-openbis-master/html/OpenBis.html @@ -0,0 +1,1155 @@ + + + + + OpenBis

Contents

classdef OpenBis
+    % OpenBis   High-level class for interacting with Python (pyBIS) Openbis objects
+    % This class creates a MATLAB OpenBis object that encapsulates the Python (pyBIS) Openbis object
+    % and provides methods for interacting with the Python (pyBIS) Openbis object.
+    %
+    % Usage:
+    % Construct the MATLAB OpenBis object like this:
+    % obi = OpenBis()
+    % This will ask for URL, user name and password to connect to openBIS server.
+    % These can also be provided as optional input arguments.
+    %
+    % Methods are generally called like this:
+    % spaces = obi.get_spaces()
+    % space = obi.get_space(code)
+    %
+    % Logout:
+    % obi.logout()
+
+
+    properties
+        pybis % Python Openbis object
+    end
+
+
+    methods
+

Constructor method

        function obj = OpenBis(varargin)
+            % OpenBis   Constructor method for class OpenBis
+            % Creates the Python Openbis object and logs into the server
+            % Optional positional input arguments:
+            % url ... URL of the openBIS server (incl. port)
+            % user ... user name for openBIS
+            % pw ... password for openBIS
+            % Usage:
+            % obi = OpenBis() --> opens UI to enter URL, user name and password
+            % obi = OpenBis('server_url', 'user_name', 'user_password')
+
+            if nargin > 0
+                url = varargin{1};
+                user = varargin{2};
+                pw = varargin{3};
+            else
+                [url, user, pw] = user_url_pw_inputdlg;
+            end
+
+            o = py.pybis.Openbis(url, pyargs('verify_certificates', 0));
+            o.login(user, pw, pyargs('save_token', 1));
+            obj.pybis = o;
+        end
+
+        function logout(obj)
+            %logout
+            % Log out of openBIS.
+            % Usage:
+            % obi.logout()
+            %
+            % After logout, the session token is no longer valid.
+
+            obj.pybis.logout();
+        end
+
+        function tf= is_session_active(obj)
+            %is_session_active
+            % Check if the session token is still active. Returns true or false.
+            % Usage:
+            % true_false = obi.is_session_active()
+
+            tf  = obj.pybis.is_session_active();
+        end
+
+        function token = token(obj)
+            %token
+            % Returns the current session token.
+            % Usage:
+            % token = obi.token()
+
+            token  = char(obj.pybis.token);
+        end
+

Masterdata methods

this section defines Matlab equivalents of the following pyBIS methods: get_experiment_types get_sample_types get_material_types get_dataset_types get_terms get_tags

        function experiment_types = get_experiment_types(obj)
+            %get_experiment_types
+            % Return a table of all available experiment types.
+            % Usage:
+            % experiment_types = obi.get_experiment_types()
+
+            experiment_types = obj.pybis.get_experiment_types();
+            experiment_types = df_to_table(experiment_types.df);
+        end
+
+        function sample_types = get_sample_types(obj)
+            %get_sample_types
+            % Return table of all available sample types.
+            % Usage:
+            % sample_types = obi.get_sample_types()
+
+            sample_types = obj.pybis.get_sample_types();
+            sample_types = df_to_table(sample_types.df);
+        end
+
+        function material_types = get_material_types(obj)
+            %get_material_types
+            % Return table of all available material types.
+            % Usage:
+            % material_types = obi.get_material_types()
+
+            material_types = obj.pybis.get_material_types();
+            material_types = df_to_table(material_types.df);
+        end
+
+        function dataset_types = get_dataset_types(obj)
+            %get_dataset_types
+            % Return table of all available dataset types.
+            % Usage:
+            % dataset_types = obi.get_dataset_types()
+
+            dataset_types = obj.pybis.get_dataset_types();
+            dataset_types = df_to_table(dataset_types.df);
+        end
+
+        function terms = get_terms(obj)
+            %get_terms
+            % Return table of all available terms.
+            % Usage:
+            % terms = obi.get_terms()
+
+            terms = obj.pybis.get_terms();
+            terms = df_to_table(terms.df);
+        end
+
+        function tags = get_tags(obj)
+            %get_tags
+            % Return table of all available tags.
+            % Usage:
+            % tags = obi.get_tags()
+
+            tags = obj.pybis.get_tags();
+            tags = df_to_table(tags.df);
+        end
+

Space methods

this section defines Matlab equivalents of the following pyBIS methods: get_spaces get_space new_space space.delete

        function spaces = get_spaces(obj)
+            %get_spaces
+            % Return table of all available spaces.
+            % Usage:
+            % spaces = obi.get_spaces()
+
+            spaces = obj.pybis.get_spaces();
+            spaces = df_to_table(spaces.df);
+        end
+
+        function space = get_space(obj, code)
+            %get_space
+            % Fetch space with matching space code and return the space object.
+            % An error is raised if a space with the code is not found on the server.
+            % Required input arguments:
+            % code ... space code
+            % Usage:
+            % space = obi.get_space('code')
+
+            space = obj.pybis.get_space(code);
+        end
+
+        function space = new_space(obj, code, description)
+            %new_space
+            % Create a new space with code and description and return the space object
+            % Required input arguments:
+            % code ... Space code
+            % description ... Space description
+            % Usage:
+            % space = obi.new_space('code', 'description')
+
+            space = obj.pybis.new_space(pyargs('code',  code, ...
+                'description', description));
+            space.save;
+        end
+
+        function delete_space(obj, code, reason)
+            %delete_space
+            % Delete space with code and provide a reason for deletion
+            % Required input arguments:
+            % code ... Space code
+            % reason ... reason for deletion
+            % Usage:
+            % obi.delete_space('code', 'reason')
+
+            space = obj.pybis.get_space(code);
+            space.delete(reason);
+        end
+

Project methods

this section defines Matlab equivalents of the following pyBIS methods: get_projects get_project new_project project.delete

        function projects = get_projects(obj, space, code)
+            %get_projects
+            % Return table of matching projects.
+            % Input arguments:
+            % space ... space to fetch projects from
+            % project ... fetch projects matching code
+            % Usage:
+            % projects = obi.get_projects('space', 'code')
+
+            projects = obj.pybis.get_projects(pyargs('space',  space, 'code', code));
+            projects = df_to_table(projects.df);
+        end
+
+        function project = get_project(obj, id)
+            %get_project
+            % Fetch project with matching project id and return the project object.
+            % An error is raised if a project with the id is not found on the server.
+            % Required input arguments:
+            % id ... project id
+            % Usage:
+            % project = obi.get_project('id')
+
+            project = obj.pybis.get_project(id);
+        end
+
+        function project = new_project(obj, space, code, description)
+            %new_project
+            % Create a new project in space with code and description
+            % Return the project object
+            % Input arguments
+            % space ... Space code
+            % code ... Project code / id
+            % description ... Project description
+            % Usage:
+            % project = obi.new_project('space', 'code', 'description')
+
+            space = obj.pybis.get_space(space);
+            project = space.new_project(pyargs('code', code,  'description', description));
+            project.save();
+        end
+
+        function delete_project(obj, code, reason)
+            %delete_project
+            % Delete project with code and provide a reason for deletion
+            % Required input arguments:
+            % code ... Project code
+            % reason ... reason for deletion
+            % Usage:
+            % obi.delete_project('code', 'reason')
+
+            project = obj.pybis.get_project(code);
+            project.delete(reason);
+        end
+

Experiment methods

this section defines the following Matlab methods: get_experiments get_experiment new_experiment

        function experiments = get_experiments(obj, varargin)
+            %get_experiments
+            % Return table of matching experiments.
+            % Optional input arguments:
+            % space ... space to fetch experiments from
+            % type ... fetch experiments of specific type
+            % project ... project to fetch experiments from
+            % Usage:
+            % experiments = obi.get_experiments()
+            % experiments = obi.get_experiments('space', 'SPACE')
+            % experiments = obi.get_experiments('space', 'SPACE', 'type', 'UNKNOWN')
+
+            space = '';
+            type = '';
+            project = '';
+
+            p = inputParser;
+            addRequired(p, 'obj');
+            addParameter(p, 'space', space, @ischar);
+            addParameter(p, 'type', type, @ischar);
+            addParameter(p, 'project', project, @ischar);
+            parse(p, obj, varargin{:});
+            a = p.Results;
+
+            experiments = obj.pybis.get_experiments(pyargs('space', a.space, 'type', a.type, 'project', a.project));
+            experiments = df_to_table(experiments.df);
+        end
+
+        function experiment = get_experiment(obj, id)
+            %get_experiment
+            % Return experiment with identifier
+            % ID can be either the Space + Object code (e.g. /SPACE/123456789) or the PermID (e.g. 20181002164551373-1234)
+            % Usage:
+            % exp = obi.get_experiment('/SPACE/PROJECT/EXP')
+            % exp = obi.get_experiment('permID')
+
+            experiment = obj.pybis.get_experiment(id);
+        end
+
+        function experiment = new_experiment(obj, type, code, project)
+            %new_experiment
+            % Create a new experiment of specific type in a defined project
+            % Required input arguments:
+            % type ... new experiment type
+            % code ... new experiment code
+            % project ... project for new experiment ('SPACE/Project')
+            % Usage:
+            % experiment = obi.new_experiment('type', 'space', 'Space/Project')
+
+            experiment = obj.pybis.new_experiment(pyargs('type', type, 'code', code, 'project', project));
+            experiment.save();
+        end
+

Object methods

this section defines following Matlab methods related to openBIS objects / samples: get_object get_objects new_object delete_object

        function objects = get_objects(obj, varargin)
+            %get_objects
+            % Return a table of objects matching specified criteria
+            % Optional keyword arguments:
+            % id ... object identifier ('SPACE/PROJECT/')
+            % Usage:
+            % objects = obi.get_objects()
+            % objects = obi.get_objects('id', 'SPACE/')
+
+            defaultId = '';
+
+            p = inputParser;
+            addRequired(p, 'obj');
+            addParameter(p, 'id', defaultId, @ischar);
+            parse(p, obj, varargin{:});
+            a = p.Results;
+
+            objects = obj.pybis.get_objects(a.id);
+            objects = df_to_table(objects.df);
+        end
+
+        function object = get_object(obj, id)
+            %get_object
+            % Return object (sample) corresponding to the id
+            % ID can be either the Space + Object code (e.g. /SPACE/123456789) or the PermID (e.g. 20181002164551373-1234)
+            % An error is raised if an object with the id is not found on the server.
+            % Required input arguments:
+            % id ... object id
+            % Usage:
+            % object = obi.get_object('id')
+
+            object = obj.pybis.get_object(id);
+        end
+
+        function object = new_object(obj, type, space, code)
+            %new_object
+            % Create a new object of type in space with code
+            % Return the object
+            % Input arguments
+            % type ... object type
+            % space ... Space code
+            % code ... object code
+            % Usage:
+            % object = obi.new_object('type', 'space', 'code')
+
+            object = obj.pybis.new_object(pyargs('type', type, 'space', space, 'code', code));
+            object.save();
+        end
+
+        function object = delete_object(obj, object, reason)
+            %delete_object
+            % Delete object and provide a reason for deletion
+            % Required input arguments:
+            % object ... object returned by get_object / new_object methods
+            % reason ... reason for deletion
+            % Usage:
+            % obi.delete_object(object, 'reason')
+
+            object.delete(reason)
+        end
+

Dataset methods

this section defines following Matlab methods: get_datasets get_dataset get_dataset_files dataset_download new_dataset new_dataset_container

        function datasets = get_datasets(obj, varargin)
+            %get_datasets
+            % Return table of matching datasets.
+            % Optional input arguments:
+            % code ... dataset code / permId
+            % type ... dataset type
+            % experiment ... datasets in experiment
+            % project ... datasets in project
+            % tags ... datasets with tags
+            % Usage:
+            % datasets = obi.get_datasets()
+            % datasets = obi.get_datasets('type', 'RAW_DATA')
+            % datasets = obi.get_datasets('experiment', '/SPACE/PROJECT/EXPERIMENT')
+
+            defaultCode = '';
+            defaultType = '';
+            defaultExp = '';
+            defaultProj = '';
+            defaultTags = '';
+
+            p = inputParser;
+            addRequired(p, 'obj');
+            addParameter(p, 'code', defaultCode, @ischar);
+            addParameter(p, 'type', defaultType, @ischar);
+            addParameter(p, 'experiment', defaultExp, @ischar);
+            addParameter(p, 'project', defaultProj, @ischar);
+            addParameter(p, 'tags', defaultTags, @ischar);
+            parse(p, obj, varargin{:});
+            a = p.Results;
+
+            datasets = obj.pybis.get_datasets(pyargs('code', a.code, 'type', a.type, 'experiment', a.experiment, ...
+                'project', a.project, 'tags', a.tags));
+            datasets = df_to_table(datasets.df);
+        end
+
+        function dataset = get_dataset(obj, permid, varargin)
+            %get_dataset
+            % Get dataset with permId. An error is raised if a dataset with the id is not found on the server.
+            % Input arguments:
+            % permId ... dataset permId
+            % Usage:
+            % dataset = obi.get_dataset('permId')
+
+            only_data = false;
+
+            p = inputParser;
+            addRequired(p, 'obj');
+            addRequired(p, 'permid', @ischar);
+            addOptional(p, 'only_data', only_data, @islogical);
+            parse(p, obj, permid, varargin{:});
+            a = p.Results;
+
+%             dataset = obj.pybis.get_dataset(pyargs('permid', a.permid, 'only_data', a.only_data));
+            dataset = obj.pybis.get_dataset(a.permid);
+        end
+
+
+        function files = get_dataset_files(obj, dataset, varargin)
+            %get_dataset_files
+            % Get list of files in a dataset starting with start_folder.
+            % Input arguments:
+            % dataset ... dataset object returned by get_dataset
+            % start_folder ... starting folder for files (default: '/')
+            % Usage:
+            % files = obi.get_dataset_files(dataset)
+
+            start_folder = '/';
+
+            p = inputParser;
+            addRequired(p, 'obj');
+            addRequired(p, 'dataset');
+            addOptional(p, 'start_folder', start_folder, @ischar);
+            parse(p, obj, dataset, varargin{:});
+            a = p.Results;
+
+            files = dataset.get_files(pyargs('start_folder', a.start_folder));
+            files = df_to_table(files);
+        end
+
+        function path_to_file = dataset_download(obj, dataset, files, varargin)
+            %dataset_download
+            % Download files in a dataset
+            % dataset ... dataset object returned by get_dataset
+            % files ... cell array of files
+            % destination ... folder to download to (default: data)
+            % wait_until_finished ... wait or download in the background (default: true)
+            % workers ... number of workers to use for download (default: 10)
+            % Usage:
+            % path_to_files = obi.dataset_download(dataset, {'file1', 'file2'})
+
+            destination = 'data';
+            wait_until_finished = true;
+            workers = 10;
+
+            p = inputParser;
+            addRequired(p, 'obj');
+            addRequired(p, 'dataset');
+            addRequired(p, 'files', @iscellstr);
+            addParameter(p, 'destination', destination, @ischar);
+            addParameter(p, 'wait_until_finished', wait_until_finished, @islogical);
+            addParameter(p, 'workers', workers, @isscalar);
+
+            parse(p, obj, dataset, files, varargin{:});
+            a = p.Results;
+
+            dataset.download(pyargs('files', a.files, 'destination', a.destination, 'wait_until_finished', a.wait_until_finished, 'workers', int16(a.workers)));
+
+            path_to_file = fullfile(a.destination, dataset.char, a.files);
+
+        end
+
+        function dataset = new_dataset(obj, type, experiment, object, file_list)
+            %new_dataset
+            % Create a new dataset with files
+            % type ... dataset type
+            % experiment ... experiment for dataset
+            % object ... object for dataset
+            % file_list ... list of files (cell string) to upload to new dataset
+            % Usage:
+            % dataset = obi.new_dataset('type', 'RAW_DATA', 'experiment', 'MY_EXP', 'object', 'MY_SAMPLE', 'file_list', {'file1', 'file2'})
+
+            p = inputParser;
+            addRequired(p, 'obj');
+            addRequired(p, 'type', @ischar);
+            addRequired(p, 'experiment', @ischar);
+            addRequired(p, 'object', @ischar);
+            addRequired(p, 'file_list', @iscellstr);
+
+            parse(p, obj, type, experiment, object, file_list);
+            a = p.Results;
+
+            dataset = obj.pybis.new_dataset(pyargs('type', a.type, 'experiment', a.experiment, 'sample', a.object, 'files', a.file_list));
+            dataset.save();
+
+        end
+
+        function dataset = new_dataset_container(obj, type, experiment, object)
+            %new_dataset_container
+            % Create a new dataset container
+            % type ... dataset container type
+            % experiment ... experiment for dataset container
+            % object ... object for dataset container
+            % Usage:
+            % dataset = obi.new_dataset_container('type', 'RAW_DATA', 'experiment', 'MY_EXP', 'object', 'MY_SAMPLE')
+
+            p = inputParser;
+            addRequired(p, 'obj');
+            addRequired(p, 'type', @ischar);
+            addRequired(p, 'experiment', @ischar);
+            addRequired(p, 'object', @ischar);
+
+            parse(p, obj, type, experiment, object, file_list);
+            a = p.Results;
+
+            dataset = obj.pybis.new_dataset(pyargs('type', a.type, 'experiment', a.experiment, 'sample', a.object, 'kind', 'CONTAINER'));
+            dataset.save();
+
+        end
+
    end
+
+end
+


Published with MATLAB® R2018a

\ No newline at end of file diff --git a/Add-Ons/matlab-openbis-master/html/df_to_table.html b/Add-Ons/matlab-openbis-master/html/df_to_table.html new file mode 100644 index 0000000..195fd76 --- /dev/null +++ b/Add-Ons/matlab-openbis-master/html/df_to_table.html @@ -0,0 +1,92 @@ + + + + + df_to_table
function [matlab_table] = df_to_table(df)
+%df_to_table
+%   Returns a Matlab table for a Python dataframe
+
+csv_temp = sprintf('%s.csv', tempname);
+df.to_csv(csv_temp);
+matlab_table = readtable(csv_temp);
+delete(csv_temp);
+
+end
+


Published with MATLAB® R2018a

\ No newline at end of file diff --git a/Add-Ons/matlab-openbis-master/html/passwordEntryDialog.html b/Add-Ons/matlab-openbis-master/html/passwordEntryDialog.html new file mode 100644 index 0000000..66f9f1a --- /dev/null +++ b/Add-Ons/matlab-openbis-master/html/passwordEntryDialog.html @@ -0,0 +1,826 @@ + + + + + passwordEntryDialog

Contents

function [Password, UserName] = passwordEntryDialog(varargin)
+
% PASSWORDENTRYDIALOG
+% [Password, UserName] = passwordEntryDialog(varargin)
+%
+% Create a password entry dialog for entering a password that is visibly
+% hidden.  Java must be enabled for this function to work properly.
+%
+% It has only been tested on the Windows platform in R2008a.  It should
+% work in R2007a or later.
+%
+% The password box is created using the Java Swing component
+% JPasswordField.
+%
+% Optional Input Arguments
+% ------------------------
+%
+% 'enterUserName'       DEFAULT: false
+% Display the user name entry box.  The user name entered must be at least
+% one character or an error dialog is displayed.
+%
+% 'DefaultUserName'     DEFAULT: ''
+% String value of user name to populate in User Name box upon creation.
+%
+% 'ValidatePassword'    DEFAULT: false
+% Display dialog box to reenter password for validation purposes.
+%
+% 'CheckPasswordLength' DEFAULT: true
+% Check the password length to ensure it meets the specified criteria.
+%
+% 'PasswordLengthMin'   DEFAULT: 2
+% Minimum password length allowed.
+%
+% 'PasswordLengthMax'   DEFAULT: 8
+% Maximum password length allowed.
+%
+% 'WindowName'          DEFAULT: 'Login'
+% Title of the password entry window.
+%
+% Examples
+% --------
+%
+% Create a password dialog box with the default options.
+% -----------------------------------------------------------------------
+% [Password] = passwordEntryDialog;
+%
+% Create a user name and password entry dialog box without password
+% verification.
+% -----------------------------------------------------------------------
+% [Password, UserName] = passwordEntryDialog('enterUserName', true)
+%
+% Create a user name and password entry dialog box without password
+% verification.  Set the user name to 'jdoe' upon startup.
+% -----------------------------------------------------------------------
+% [Password, UserName] = passwordEntryDialog('enterUserName', true,...
+%      'DefaultUserName', 'jdoe')
+%
+% Create a password dialog box with password validation
+% -----------------------------------------------------------------------
+% [Password] = passwordEntryDialog('ValidatePassword', true);
+%
+% Create a user name and password entry dialog box with password
+% verification.
+% -----------------------------------------------------------------------
+% [Password, UserName] = passwordEntryDialog('enterUserName', true,...
+%      'ValidatePassword', true)
+%
+% Check the length of the password to be between 5 and 8 characters
+% -----------------------------------------------------------------------
+% [Password, UserName] = passwordEntryDialog('CheckPasswordLength', true,...
+%      'PasswordLengthMin', 5,...
+%      'PasswordLengthMax', 8)
+%
+% -----------------------------------------------------------------------
+% Copyright (C) 2007-2008, Jesse B. Lai
+%
+% This program is free software: you can redistribute it and/or modify
+% it under the terms of the GNU Lesser General Public License as published
+% by the Free Software Foundation, either version 3 of the License, or
+% (at your option) any later version.
+%
+% This program is distributed in the hope that it will be useful,
+% but WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+% GNU Lesser General Public License for more details.
+%
+% You should have received a copy of the GNU Lesser General Public License
+% along with this program.  If not, see <http://www.gnu.org/licenses/>
+

History

The history of this program is outlined in this section.

20080616 - JBL - 0.0.2 Started 20080612

Updated to remove requirement for uicomponent function written by Yair Altman. Now, the Java components are created manually and the undocumented feature javacomponent is used.

A focus issue was worked out by using the drawnow command in a couple of places to allow the objects to be focused properly upon startup.

20080427 - JBL - 0.0.1 Started 20080425.

Initial version. Uses Java to create the password entry box. An edit box was initially attemped with the Java frame, but was occasionally getting Java exceptions when trying to query the 'SelectionStart' and 'SelectionEnd' properties.

Basic options of entering user name and password with options for password validation.

ToDo: Maybe add valid string input argument to only allow certain characters.

Program Information

% ProgramName = 'passwordEntryDialog';
+% ProgramVersion = '0.0.2';
+% svnRevision = '$Revision: 184 $';
+% svnRevision = getSVNRevision(svnRevision);
+% ProgramVersion = [ProgramVersion, '.' ,svnRevision];
+%
+% LastChangedDate = '$LastChangedDate: 2008-06-16 09:08:17 -0600 (Mon, 16 Jun 2008) $';
+% ProgramDate = getSVNDate(LastChangedDate);
+

Check for Existance of Java

if ~usejava('swing')
+   error('passwordEntryDialog: Java is required for this program to run.');
+end
+

Parse Input Arguments

Input arguments are parsed with the MATLAB inputParser class.

% Create input parser object
+ProgramOptionsParser = inputParser;
+ProgramOptionsParser.KeepUnmatched = true;
+
+ProgramOptionsParser.addParamValue('enterUserName', false, @(x) islogical(x) || isnumeric(x));
+ProgramOptionsParser.addParamValue('DefaultUserName', '', @ischar);
+ProgramOptionsParser.addParamValue('ValidatePassword', false, @(x) islogical(x) || isnumeric(x));
+ProgramOptionsParser.addParamValue('CheckPasswordLength', true, @(x) islogical(x) || isnumeric(x));
+ProgramOptionsParser.addParamValue('PasswordLengthMin', 2, @isnumeric);
+ProgramOptionsParser.addParamValue('PasswordLengthMax', 8, @isnumeric);
+ProgramOptionsParser.addParamValue('WindowName', 'Login', @ischar);
+
+% Parse Input Arguments
+try
+    ProgramOptionsParser.parse(varargin{:});
+catch Error
+    ProgramOptionsParser.parse;
+    if strcmpi(Error.identifier, 'MATLAB:InputParser:ArgumentFailedValidation')
+        error(Error.identifier, Error.message);
+    end;
+end;
+
+ProgramOptions = ProgramOptionsParser.Results;
+
+% Validate password length options
+if ProgramOptions.CheckPasswordLength
+    if ProgramOptions.PasswordLengthMax < ProgramOptions.PasswordLengthMin
+        error('MATLAB:InputParser:ArgumentFailedValidation', 'PasswordLengthMax must be greater than PasswordLengthMin');
+    end;
+end;
+

Determine GUI Size and Position

Center the GUI on the screen.

set(0,'Units','pixels')
+Screen = get(0,'screensize');
+
+PositionGUI = [0 0 300 50];
+if ProgramOptions.enterUserName
+    PositionGUI = PositionGUI + [0 0 0 50];
+end;
+if ProgramOptions.ValidatePassword
+    PositionGUI = PositionGUI + [0 0 0 50];
+    OffsetBottom = 43;
+else
+    OffsetBottom = 0;
+end;
+
+PositionGUI = [Screen(3:4)/2-PositionGUI(3:4)/2 PositionGUI(3:4)];
+PositionLeft = 10;
+BoxWidth = 200;
+

Create the GUI

BackgroundColor = get(0,'DefaultUicontrolBackgroundcolor');
+handles.figure1 = figure('Menubar','none', ...
+    'Units','Pixels', ...
+    'Resize','off', ...
+    'NumberTitle','off', ...
+    'Name',ProgramOptions.WindowName, ...
+    'Position',PositionGUI, ...
+    'Color', BackgroundColor, ...
+    'WindowStyle','modal');
+
+% Create Password Validation Entry Box
+if ProgramOptions.ValidatePassword
+    handles.java_PasswordValidate = javax.swing.JPasswordField();
+    handles.java_PasswordValidate.setFocusable(true);
+    [handles.java_PasswordValidate, handles.edit_PasswordValidate] = javacomponent(handles.java_PasswordValidate, [], handles.figure1);
+
+    set(handles.edit_PasswordValidate, ...
+        'Parent', handles.figure1, ...
+        'Tag', 'edit_PasswordValidate', ...
+        'Units', 'Pixels', ...
+        'Position',[PositionLeft 10 BoxWidth 23]);
+
+    handles.text_LabelPasswordValidate = uicontrol('Parent',handles.figure1, ...
+        'Tag', 'text_LabelPassword', ...
+        'Style','Text', ...
+        'Units','Pixels',...
+        'Position',[PositionLeft 33 BoxWidth 16], ...
+        'FontSize',10, ...
+        'String','Reenter password:',...
+        'HorizontalAlignment', 'Left');
+end;
+
+% Create Password Entry Box
+handles.java_Password = javax.swing.JPasswordField();
+[handles.java_Password, handles.edit_Password] = javacomponent(handles.java_Password, [PositionLeft 10+OffsetBottom BoxWidth 23], handles.figure1);
+handles.java_Password.setFocusable(true);
+
+set(handles.edit_Password, ...
+    'Parent', handles.figure1, ...
+    'Tag', 'edit_Password', ...
+    'Units', 'Pixels', ...
+    'Position',[PositionLeft 10+OffsetBottom BoxWidth 23]);
+drawnow;    % This drawnow is required to allow the focus to work
+
+handles.text_LabelPassword = uicontrol('Parent',handles.figure1, ...
+    'Tag', 'text_LabelPassword', ...
+    'Style','Text', ...
+    'Units','Pixels',...
+    'Position',[PositionLeft 33+OffsetBottom BoxWidth 16], ...
+    'FontSize',10, ...
+    'String','Key:',...
+    'HorizontalAlignment', 'Left');
+
+% Create OK Pushbutton
+handles.pushbutton_OK = uicontrol('Parent',handles.figure1, ...
+    'Tag', 'pushbutton_OK', ...
+    'Style','Pushbutton', ...
+    'Units','Pixels',...
+    'Position',[PositionLeft+BoxWidth+5 10 30 23], ...
+    'FontSize',10, ...
+    'String','OK',...
+    'HorizontalAlignment', 'Center');
+
+% Create Cancel Pushbutton
+handles.pushbutton_Cancel = uicontrol('Parent',handles.figure1, ...
+    'Tag', 'pushbutton_Cancel', ...
+    'Style','Pushbutton', ...
+    'Units','Pixels',...
+    'Position',[PositionLeft+BoxWidth+30+7 10 50 23], ...
+    'FontSize',10, ...
+    'String','Cancel',...
+    'HorizontalAlignment', 'Center');
+
+% Create User Name Edit Box
+if ProgramOptions.enterUserName
+    handles.java_UserName = javax.swing.JTextField();
+    handles.java_UserName.setFocusable(true);
+    [handles.java_UserName, handles.edit_UserName] = javacomponent(handles.java_UserName, [], handles.figure1);
+
+    set(handles.edit_UserName, ...
+        'Parent', handles.figure1, ...
+        'Tag', 'edit_UserName', ...
+        'Units', 'Pixels', ...
+        'Position',[PositionLeft 53+OffsetBottom 200 23]);
+    set(handles.java_UserName, 'Text', ProgramOptions.DefaultUserName);
+    drawnow;    % This drawnow is required to allow the focus to work
+
+    handles.text_LabelUserName = uicontrol('Parent',handles.figure1, ...
+        'Tag', 'text_LabelUserName', ...
+        'Style','Text', ...
+        'Units','Pixels',...
+        'Position',[PositionLeft 76+OffsetBottom 200 16], ...
+        'FontSize',10, ...
+        'String','User name:',...
+        'HorizontalAlignment', 'Left');
+
+    %uicontrol(handles.edit_UserName);
+    %set(handles.figure1,'CurrentObject',handles.java_UserName)
+    handles.java_UserName.requestFocus;     % Get focus
+    drawnow;
+else
+    handles.java_Password.requestFocus;     % Get focus
+    drawnow;
+end;
+

Setup Callbacks for Objects

Adds the callback functions for the objects in the GUI

set(handles.pushbutton_OK,     'Callback', {@pushbutton_OK_Callback, handles, ProgramOptions}, 'KeyPressFcn', {@pushbutton_KeyPressFcn, handles, ProgramOptions});
+set(handles.pushbutton_Cancel, 'Callback', {@pushbutton_Cancel_Callback, handles, ProgramOptions}, 'KeyPressFcn', {@pushbutton_KeyPressFcn, handles, ProgramOptions});
+set(handles.java_Password, 'ActionPerformedCallback', {@pushbutton_OK_Callback, handles, ProgramOptions});
+
+if ProgramOptions.ValidatePassword
+    if ProgramOptions.enterUserName
+        ObjectNext = handles.java_UserName;
+    else
+        ObjectNext = handles.java_Password;
+    end;
+    set(handles.java_PasswordValidate, 'ActionPerformedCallback', {@pushbutton_OK_Callback, handles, ProgramOptions}, 'NextFocusableComponent', ObjectNext);
+    set(handles.java_Password, 'NextFocusableComponent', handles.java_PasswordValidate);
+elseif ProgramOptions.enterUserName
+    set(handles.java_Password, 'NextFocusableComponent', handles.java_UserName);
+end;
+
+if ProgramOptions.enterUserName
+    set(handles.java_UserName, 'ActionPerformedCallback', {@pushbutton_OK_Callback, handles, ProgramOptions}, 'NextFocusableComponent', handles.java_Password);
+end;
+
+setappdata(handles.figure1, 'isCanceled', false);
+

Wait for Completion

% Wait for the user to complete entry.
+drawnow;
+uiwait(handles.figure1);
+

Get current information

User either closed the window or pressed cancel or OK.

isCanceled = ~ishandle(handles.figure1) || getappdata(handles.figure1, 'isCanceled');
+if isCanceled
+    if ishandle(handles.figure1)
+        delete(handles.figure1);
+    end;
+    Password = -1;
+    UserName = '';
+    return;
+end;
+
+Password = handles.java_Password.Password';
+if ProgramOptions.enterUserName
+    UserName = strtrim(get(handles.java_UserName, 'Text'));
+else
+    UserName = '';
+end;
+delete(handles.figure1);
+

DEFINE FUNCTIONS

The subfunctions required by this program are in the following section.

function pushbutton_KeyPressFcn(hObject, eventdata, handles, ProgramOptions)
+
+switch eventdata.Key
+    case 'return'
+        Callback = get(hObject, 'Callback');
+        feval(Callback{1}, hObject, '', Callback{2:end});
+end;
+
+function pushbutton_OK_Callback(hObject, eventdata, handles, ProgramOptions)
+if ProgramOptions.enterUserName
+    % Check if username is blank
+    UserName = strtrim(get(handles.java_UserName, 'Text'));
+    if isempty(UserName)
+        strMessage = 'Username is blank';
+        %disp(strMessage)
+        hError = errordlg(strMessage, 'passwordEntryDialog');
+        uiwait(hError);
+        return;
+    end;
+end;
+
+if ProgramOptions.CheckPasswordLength
+    %Password = handles.edit_Password.Password';
+    Password = handles.java_Password.Password';
+    if length(Password) < ProgramOptions.PasswordLengthMin || length(Password) > ProgramOptions.PasswordLengthMax
+        strMessage = sprintf('Password must be between %d and %d characters', ...
+            ProgramOptions.PasswordLengthMin, ...
+            ProgramOptions.PasswordLengthMax);
+        %disp(strMessage);
+        hError = errordlg(strMessage, 'passwordEntryDialog');
+        uiwait(hError);
+        if ProgramOptions.ValidatePassword
+            set(handles.java_PasswordValidate,'Text', '');
+        end;
+        handles.java_Password.requestFocus
+        return;
+    end;
+end;
+
+if ProgramOptions.ValidatePassword
+    % Check if passwords match
+    if ~isequal(handles.java_Password.Password, handles.java_PasswordValidate.Password)
+        strMessage = 'Passwords do not match.  Please try again';
+        %disp(strMessage);
+        hError=errordlg(strMessage, 'passwordEntryDialog','modal');
+        uiwait(hError);
+        set(handles.java_Password,'Text', '');
+        set(handles.java_PasswordValidate,'Text', '');
+
+        handles.java_Password.requestFocus
+        return;
+    end;
+end;
+uiresume(handles.figure1);
+
+function pushbutton_Cancel_Callback(hObject, eventdata, handles, ProgramOptions)
+setappdata(handles.figure1, 'isCanceled', true);
+uiresume(handles.figure1);
+


Published with MATLAB® R2018a

\ No newline at end of file diff --git a/Add-Ons/matlab-openbis-master/html/user_url_pw_inputdlg.html b/Add-Ons/matlab-openbis-master/html/user_url_pw_inputdlg.html new file mode 100644 index 0000000..3b58ecf --- /dev/null +++ b/Add-Ons/matlab-openbis-master/html/user_url_pw_inputdlg.html @@ -0,0 +1,102 @@ + + + + + user_url_pw_inputdlg
function [url, user, pw] = user_url_pw_inputdlg
+%user_url_pw_inputdlg
+%   Return the URL, user name and password for the openBIS server
+
+prompt = {'openBIS URL:', 'openBIS user:'};
+title = 'openBIS connection details';
+definput = {'https://XYZ.ethz.ch/openbis:8443', ''};
+answer = inputdlg(prompt, title, 1, definput);
+
+url = answer{1};
+user = answer{2};
+
+pw = passwordEntryDialog('CheckPasswordLength',0);
+
+end
+


Published with MATLAB® R2018a

\ No newline at end of file diff --git a/Add-Ons/matlab-openbis-master/openbis_example.mlx b/Add-Ons/matlab-openbis-master/openbis_example.mlx new file mode 100644 index 0000000..e9dd707 Binary files /dev/null and b/Add-Ons/matlab-openbis-master/openbis_example.mlx differ diff --git a/Add-Ons/matlab-openbis-master/passcode.m b/Add-Ons/matlab-openbis-master/passcode.m new file mode 100644 index 0000000..f27efc2 --- /dev/null +++ b/Add-Ons/matlab-openbis-master/passcode.m @@ -0,0 +1,74 @@ +function pass = passcode +%PASSCODE password input dialog box. +% passcode creates a modal dialog box that returns user password input. +% Given characters are substituted with '*'-Signs like in usual password dialogs. +% +% usage: +% password = PASSCODE +% +% Adapted from https://www.mathworks.com/matlabcentral/fileexchange/6590-passcode +% Version: v1.2 (03-Mar-2008) +% Author: Elmar Tarajan [MCommander@gmx.de] + + +ScreenSize = get(0,'ScreenSize'); +hfig = figure('Menubar','none', ... + 'Units','Pixels', ... + 'Resize','off', ... + 'NumberTitle','off', ... + 'Name',['password required'], ... + 'Position',[ (ScreenSize(3:4)-[300 75])/2 300 75], ... + 'Color',[0.8 0.8 0.8], ... + 'WindowStyle','modal'); +hedit = uicontrol('Parent',hfig, ... + 'Style','Edit', ... + 'Enable','inactive', ... + 'Units','Pixels','Position',[49 28 202 22], ... + 'FontSize',15, ... + 'String',[], ... + 'BackGroundColor',[0.7 0.7 0.7]); +hpass = uicontrol('Parent',hfig, ... + 'Style','Text', ... + 'Tag','password', ... + 'Units','Pixels','Position',[51 30 198 18], ... + 'FontSize',15, ... + 'BackGroundColor',[1 1 1]); +hwarn = uicontrol('Parent',hfig, ... + 'Style','Text', ... + 'Tag','error', ... + 'Units','Pixels','Position',[50 2 200 20], ... + 'FontSize',8, ... + 'String','character not allowed',... + 'Visible','off',... + 'ForeGroundColor',[1 0 0], ... + 'BackGroundColor',[0.8 0.8 0.8]); + +set(hfig,'KeyPressFcn',{@keypress_Callback,hedit,hpass,hwarn}, ... + 'CloseRequestFcn','uiresume') + +uiwait +pass = get(hpass,'userdata'); +delete(hfig) + + +function keypress_Callback(~,data,~,hpass,~) + +pass = get(hpass,'userdata'); + +switch data.Key + case 'backspace' + pass = pass(1:end-1); + case 'return' + uiresume + return + otherwise + try + pass = [pass data.Character]; + catch + disp('Some error occured during password entry!') + end +end + +set(hpass,'userdata',pass) +set(hpass,'String',char('*'*sign(pass))) + diff --git a/Add-Ons/matlab-openbis-master/passwordEntryDialog.m b/Add-Ons/matlab-openbis-master/passwordEntryDialog.m new file mode 100644 index 0000000..84a761a --- /dev/null +++ b/Add-Ons/matlab-openbis-master/passwordEntryDialog.m @@ -0,0 +1,406 @@ +function [Password, UserName] = passwordEntryDialog(varargin) +% PASSWORDENTRYDIALOG +% [Password, UserName] = passwordEntryDialog(varargin) +% +% Create a password entry dialog for entering a password that is visibly +% hidden. Java must be enabled for this function to work properly. +% +% It has only been tested on the Windows platform in R2008a. It should +% work in R2007a or later. +% +% The password box is created using the Java Swing component +% JPasswordField. +% +% Optional Input Arguments +% ------------------------ +% +% 'enterUserName' DEFAULT: false +% Display the user name entry box. The user name entered must be at least +% one character or an error dialog is displayed. +% +% 'DefaultUserName' DEFAULT: '' +% String value of user name to populate in User Name box upon creation. +% +% 'ValidatePassword' DEFAULT: false +% Display dialog box to reenter password for validation purposes. +% +% 'CheckPasswordLength' DEFAULT: true +% Check the password length to ensure it meets the specified criteria. +% +% 'PasswordLengthMin' DEFAULT: 2 +% Minimum password length allowed. +% +% 'PasswordLengthMax' DEFAULT: 8 +% Maximum password length allowed. +% +% 'WindowName' DEFAULT: 'Login' +% Title of the password entry window. +% +% Examples +% -------- +% +% Create a password dialog box with the default options. +% ----------------------------------------------------------------------- +% [Password] = passwordEntryDialog; +% +% Create a user name and password entry dialog box without password +% verification. +% ----------------------------------------------------------------------- +% [Password, UserName] = passwordEntryDialog('enterUserName', true) +% +% Create a user name and password entry dialog box without password +% verification. Set the user name to 'jdoe' upon startup. +% ----------------------------------------------------------------------- +% [Password, UserName] = passwordEntryDialog('enterUserName', true,... +% 'DefaultUserName', 'jdoe') +% +% Create a password dialog box with password validation +% ----------------------------------------------------------------------- +% [Password] = passwordEntryDialog('ValidatePassword', true); +% +% Create a user name and password entry dialog box with password +% verification. +% ----------------------------------------------------------------------- +% [Password, UserName] = passwordEntryDialog('enterUserName', true,... +% 'ValidatePassword', true) +% +% Check the length of the password to be between 5 and 8 characters +% ----------------------------------------------------------------------- +% [Password, UserName] = passwordEntryDialog('CheckPasswordLength', true,... +% 'PasswordLengthMin', 5,... +% 'PasswordLengthMax', 8) +% +% ----------------------------------------------------------------------- +% Copyright (C) 2007-2008, Jesse B. Lai +% +% This program is free software: you can redistribute it and/or modify +% it under the terms of the GNU Lesser General Public License as published +% by the Free Software Foundation, either version 3 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU Lesser General Public License for more details. +% +% You should have received a copy of the GNU Lesser General Public License +% along with this program. If not, see + +%% History +% The history of this program is outlined in this section. +% +% 20080616 - JBL - 0.0.2 +% Started 20080612 +% +% Updated to remove requirement for uicomponent function written by Yair +% Altman. Now, the Java components are created manually and the +% undocumented feature javacomponent is used. +% +% A focus issue was worked out by using the drawnow command in a couple of +% places to allow the objects to be focused properly upon startup. +% +% 20080427 - JBL - 0.0.1 +% Started 20080425. +% +% Initial version. Uses Java to create the password entry box. An edit +% box was initially attemped with the Java frame, but was occasionally +% getting Java exceptions when trying to query the 'SelectionStart' and +% 'SelectionEnd' properties. +% +% Basic options of entering user name and password with options for +% password validation. +% +% ToDo: Maybe add valid string input argument to only allow certain +% characters. + +%% Program Information + +% ProgramName = 'passwordEntryDialog'; +% ProgramVersion = '0.0.2'; +% svnRevision = '$Revision: 184 $'; +% svnRevision = getSVNRevision(svnRevision); +% ProgramVersion = [ProgramVersion, '.' ,svnRevision]; +% +% LastChangedDate = '$LastChangedDate: 2008-06-16 09:08:17 -0600 (Mon, 16 Jun 2008) $'; +% ProgramDate = getSVNDate(LastChangedDate); + +%% Check for Existance of Java +if ~usejava('swing') + error('passwordEntryDialog: Java is required for this program to run.'); +end + +%% Parse Input Arguments +% Input arguments are parsed with the MATLAB inputParser class. + +% Create input parser object +ProgramOptionsParser = inputParser; +ProgramOptionsParser.KeepUnmatched = true; + +ProgramOptionsParser.addParamValue('enterUserName', false, @(x) islogical(x) || isnumeric(x)); +ProgramOptionsParser.addParamValue('DefaultUserName', '', @ischar); +ProgramOptionsParser.addParamValue('ValidatePassword', false, @(x) islogical(x) || isnumeric(x)); +ProgramOptionsParser.addParamValue('CheckPasswordLength', true, @(x) islogical(x) || isnumeric(x)); +ProgramOptionsParser.addParamValue('PasswordLengthMin', 2, @isnumeric); +ProgramOptionsParser.addParamValue('PasswordLengthMax', 8, @isnumeric); +ProgramOptionsParser.addParamValue('WindowName', 'Login', @ischar); + +% Parse Input Arguments +try + ProgramOptionsParser.parse(varargin{:}); +catch Error + ProgramOptionsParser.parse; + if strcmpi(Error.identifier, 'MATLAB:InputParser:ArgumentFailedValidation') + error(Error.identifier, Error.message); + end; +end; + +ProgramOptions = ProgramOptionsParser.Results; + +% Validate password length options +if ProgramOptions.CheckPasswordLength + if ProgramOptions.PasswordLengthMax < ProgramOptions.PasswordLengthMin + error('MATLAB:InputParser:ArgumentFailedValidation', 'PasswordLengthMax must be greater than PasswordLengthMin'); + end; +end; + +%% Determine GUI Size and Position +% Center the GUI on the screen. + +set(0,'Units','pixels') +Screen = get(0,'screensize'); + +PositionGUI = [0 0 300 50]; +if ProgramOptions.enterUserName + PositionGUI = PositionGUI + [0 0 0 50]; +end; +if ProgramOptions.ValidatePassword + PositionGUI = PositionGUI + [0 0 0 50]; + OffsetBottom = 43; +else + OffsetBottom = 0; +end; + +PositionGUI = [Screen(3:4)/2-PositionGUI(3:4)/2 PositionGUI(3:4)]; +PositionLeft = 10; +BoxWidth = 200; + +%% Create the GUI + +BackgroundColor = get(0,'DefaultUicontrolBackgroundcolor'); +handles.figure1 = figure('Menubar','none', ... + 'Units','Pixels', ... + 'Resize','off', ... + 'NumberTitle','off', ... + 'Name',ProgramOptions.WindowName, ... + 'Position',PositionGUI, ... + 'Color', BackgroundColor, ... + 'WindowStyle','modal'); + +% Create Password Validation Entry Box +if ProgramOptions.ValidatePassword + handles.java_PasswordValidate = javax.swing.JPasswordField(); + handles.java_PasswordValidate.setFocusable(true); + [handles.java_PasswordValidate, handles.edit_PasswordValidate] = javacomponent(handles.java_PasswordValidate, [], handles.figure1); + + set(handles.edit_PasswordValidate, ... + 'Parent', handles.figure1, ... + 'Tag', 'edit_PasswordValidate', ... + 'Units', 'Pixels', ... + 'Position',[PositionLeft 10 BoxWidth 23]); + + handles.text_LabelPasswordValidate = uicontrol('Parent',handles.figure1, ... + 'Tag', 'text_LabelPassword', ... + 'Style','Text', ... + 'Units','Pixels',... + 'Position',[PositionLeft 33 BoxWidth 16], ... + 'FontSize',10, ... + 'String','Reenter password:',... + 'HorizontalAlignment', 'Left'); +end; + +% Create Password Entry Box +handles.java_Password = javax.swing.JPasswordField(); +[handles.java_Password, handles.edit_Password] = javacomponent(handles.java_Password, [PositionLeft 10+OffsetBottom BoxWidth 23], handles.figure1); +handles.java_Password.setFocusable(true); + +set(handles.edit_Password, ... + 'Parent', handles.figure1, ... + 'Tag', 'edit_Password', ... + 'Units', 'Pixels', ... + 'Position',[PositionLeft 10+OffsetBottom BoxWidth 23]); +drawnow; % This drawnow is required to allow the focus to work + +handles.text_LabelPassword = uicontrol('Parent',handles.figure1, ... + 'Tag', 'text_LabelPassword', ... + 'Style','Text', ... + 'Units','Pixels',... + 'Position',[PositionLeft 33+OffsetBottom BoxWidth 16], ... + 'FontSize',10, ... + 'String','Key:',... + 'HorizontalAlignment', 'Left'); + +% Create OK Pushbutton +handles.pushbutton_OK = uicontrol('Parent',handles.figure1, ... + 'Tag', 'pushbutton_OK', ... + 'Style','Pushbutton', ... + 'Units','Pixels',... + 'Position',[PositionLeft+BoxWidth+5 10 30 23], ... + 'FontSize',10, ... + 'String','OK',... + 'HorizontalAlignment', 'Center'); + +% Create Cancel Pushbutton +handles.pushbutton_Cancel = uicontrol('Parent',handles.figure1, ... + 'Tag', 'pushbutton_Cancel', ... + 'Style','Pushbutton', ... + 'Units','Pixels',... + 'Position',[PositionLeft+BoxWidth+30+7 10 50 23], ... + 'FontSize',10, ... + 'String','Cancel',... + 'HorizontalAlignment', 'Center'); + +% Create User Name Edit Box +if ProgramOptions.enterUserName + handles.java_UserName = javax.swing.JTextField(); + handles.java_UserName.setFocusable(true); + [handles.java_UserName, handles.edit_UserName] = javacomponent(handles.java_UserName, [], handles.figure1); + + set(handles.edit_UserName, ... + 'Parent', handles.figure1, ... + 'Tag', 'edit_UserName', ... + 'Units', 'Pixels', ... + 'Position',[PositionLeft 53+OffsetBottom 200 23]); + set(handles.java_UserName, 'Text', ProgramOptions.DefaultUserName); + drawnow; % This drawnow is required to allow the focus to work + + handles.text_LabelUserName = uicontrol('Parent',handles.figure1, ... + 'Tag', 'text_LabelUserName', ... + 'Style','Text', ... + 'Units','Pixels',... + 'Position',[PositionLeft 76+OffsetBottom 200 16], ... + 'FontSize',10, ... + 'String','User name:',... + 'HorizontalAlignment', 'Left'); + + %uicontrol(handles.edit_UserName); + %set(handles.figure1,'CurrentObject',handles.java_UserName) + handles.java_UserName.requestFocus; % Get focus + drawnow; +else + handles.java_Password.requestFocus; % Get focus + drawnow; +end; + +%% Setup Callbacks for Objects +% Adds the callback functions for the objects in the GUI + +set(handles.pushbutton_OK, 'Callback', {@pushbutton_OK_Callback, handles, ProgramOptions}, 'KeyPressFcn', {@pushbutton_KeyPressFcn, handles, ProgramOptions}); +set(handles.pushbutton_Cancel, 'Callback', {@pushbutton_Cancel_Callback, handles, ProgramOptions}, 'KeyPressFcn', {@pushbutton_KeyPressFcn, handles, ProgramOptions}); +set(handles.java_Password, 'ActionPerformedCallback', {@pushbutton_OK_Callback, handles, ProgramOptions}); + +if ProgramOptions.ValidatePassword + if ProgramOptions.enterUserName + ObjectNext = handles.java_UserName; + else + ObjectNext = handles.java_Password; + end; + set(handles.java_PasswordValidate, 'ActionPerformedCallback', {@pushbutton_OK_Callback, handles, ProgramOptions}, 'NextFocusableComponent', ObjectNext); + set(handles.java_Password, 'NextFocusableComponent', handles.java_PasswordValidate); +elseif ProgramOptions.enterUserName + set(handles.java_Password, 'NextFocusableComponent', handles.java_UserName); +end; + +if ProgramOptions.enterUserName + set(handles.java_UserName, 'ActionPerformedCallback', {@pushbutton_OK_Callback, handles, ProgramOptions}, 'NextFocusableComponent', handles.java_Password); +end; + +setappdata(handles.figure1, 'isCanceled', false); + +%% Wait for Completion + +% Wait for the user to complete entry. +drawnow; +uiwait(handles.figure1); + +%% Get current information +% User either closed the window or pressed cancel or OK. + +isCanceled = ~ishandle(handles.figure1) || getappdata(handles.figure1, 'isCanceled'); +if isCanceled + if ishandle(handles.figure1) + delete(handles.figure1); + end; + Password = -1; + UserName = ''; + return; +end; + +Password = handles.java_Password.Password'; +if ProgramOptions.enterUserName + UserName = strtrim(get(handles.java_UserName, 'Text')); +else + UserName = ''; +end; +delete(handles.figure1); + +%% DEFINE FUNCTIONS +% The subfunctions required by this program are in the following section. + +function pushbutton_KeyPressFcn(hObject, eventdata, handles, ProgramOptions) + +switch eventdata.Key + case 'return' + Callback = get(hObject, 'Callback'); + feval(Callback{1}, hObject, '', Callback{2:end}); +end; + +function pushbutton_OK_Callback(hObject, eventdata, handles, ProgramOptions) +if ProgramOptions.enterUserName + % Check if username is blank + UserName = strtrim(get(handles.java_UserName, 'Text')); + if isempty(UserName) + strMessage = 'Username is blank'; + %disp(strMessage) + hError = errordlg(strMessage, 'passwordEntryDialog'); + uiwait(hError); + return; + end; +end; + +if ProgramOptions.CheckPasswordLength + %Password = handles.edit_Password.Password'; + Password = handles.java_Password.Password'; + if length(Password) < ProgramOptions.PasswordLengthMin || length(Password) > ProgramOptions.PasswordLengthMax + strMessage = sprintf('Password must be between %d and %d characters', ... + ProgramOptions.PasswordLengthMin, ... + ProgramOptions.PasswordLengthMax); + %disp(strMessage); + hError = errordlg(strMessage, 'passwordEntryDialog'); + uiwait(hError); + if ProgramOptions.ValidatePassword + set(handles.java_PasswordValidate,'Text', ''); + end; + handles.java_Password.requestFocus + return; + end; +end; + +if ProgramOptions.ValidatePassword + % Check if passwords match + if ~isequal(handles.java_Password.Password, handles.java_PasswordValidate.Password) + strMessage = 'Passwords do not match. Please try again'; + %disp(strMessage); + hError=errordlg(strMessage, 'passwordEntryDialog','modal'); + uiwait(hError); + set(handles.java_Password,'Text', ''); + set(handles.java_PasswordValidate,'Text', ''); + + handles.java_Password.requestFocus + return; + end; +end; +uiresume(handles.figure1); + +function pushbutton_Cancel_Callback(hObject, eventdata, handles, ProgramOptions) +setappdata(handles.figure1, 'isCanceled', true); +uiresume(handles.figure1); \ No newline at end of file diff --git a/Add-Ons/matlab-openbis-master/pybis_example.ipynb b/Add-Ons/matlab-openbis-master/pybis_example.ipynb new file mode 100644 index 0000000..04e58a2 --- /dev/null +++ b/Add-Ons/matlab-openbis-master/pybis_example.ipynb @@ -0,0 +1,485 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from pybis import Openbis\n", + "import getpass\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Connecting to openBIS" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o = Openbis('https://openbis-tst.ethz.ch/openbis:8443', verify_certificates=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "username = 'h'\n", + "pw = getpass.getpass()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.login(username, pw, save_token=True) # saves the session token in ~/.pybis/example.com.token\n", + "del pw" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.token" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.is_session_active()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_datastores()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Masterdata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_experiment_types()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_sample_types()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_sample_type('PLATE')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_material_types()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_dataset_types()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_terms()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Samples / objects" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_sample_types()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "obj = o.new_object(type='UNKNOWN', space='MATLAB_TEST', code='12345')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "obj.save()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sample = o.get_sample('/MATLAB_TEST/911922')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sample.delete('just a test')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### List and get datasets" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "datasets = o.get_datasets(type='HISTOLOGY')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "counter = 0\n", + "for ds in datasets:\n", + " print(ds)\n", + " counter += 1\n", + " if counter > 10:\n", + " break" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ds = o.get_dataset('20101105142049776-6512')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ds.get_files(start_folder='original')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Experiments / collections" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_experiments(\n", + " project='TEST_PROJECT',\n", + " space='MATLAB_TEST'\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "experiment = o.get_experiment('/MATLAB_TEST/TEST_PROJECT/E1300')\n", + "experiment" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "experiment.props" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "experiment = o.new_experiment(type='UNKNOWN', code='EXP123456', project='/SIS_HLUETCKE/DEMO')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "experiment.save()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "project = o.new_project('SIS_HLUETCKE', 'test_project', 'boring project')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "project.save()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_objects('SIS_HLUETCKE/')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Download and import files" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ds.download(files='', destination='data', wait_until_finished=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.imshow(plt.imread('data/20101105142920015-6525/original/441_x40001.tif'))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_experiment_types()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_dataset_types()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.get_projects(space='MATLAB_TEST', code=None)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "project = o.new_project(space='MATLAB_TEST', code='ANOTHER_TEST', description='TGIF')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "project.save()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "project.delete('just a test')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Create a new dataset" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "file_list = [\n", + " '/Users/Henry/Data/temp/file1.dat',\n", + " '/Users/Henry/Data/temp/file2.dat',\n", + " '/Users/Henry/Data/temp/file3.dat'\n", + "]\n", + "file_list" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ds_new = o.new_dataset(type='ANALYZED_DATA', experiment='/HLUETCKE/DEMO/DEMO_EXP_1', sample='/HLUETCKE/DEMO/S43', files=file_list)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ds_new.save()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Logout" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "o.logout()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [default]", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Add-Ons/matlab-openbis-master/user_url_pw_inputdlg.m b/Add-Ons/matlab-openbis-master/user_url_pw_inputdlg.m new file mode 100644 index 0000000..80d294a --- /dev/null +++ b/Add-Ons/matlab-openbis-master/user_url_pw_inputdlg.m @@ -0,0 +1,15 @@ +function [url, user, pw] = user_url_pw_inputdlg +%user_url_pw_inputdlg +% Return the URL, user name and password for the openBIS server + +prompt = {'openBIS URL:', 'openBIS user:'}; +title = 'openBIS connection details'; +definput = {'https://XYZ.ethz.ch/openbis:8443', ''}; +answer = inputdlg(prompt, title, 1, definput); + +url = answer{1}; +user = answer{2}; + +pw = passwordEntryDialog('CheckPasswordLength',0); + +end \ No newline at end of file diff --git a/Add-Ons/mbar2molecPerCcm.m b/Add-Ons/mbar2molecPerCcm.m new file mode 100644 index 0000000..2ca9f52 --- /dev/null +++ b/Add-Ons/mbar2molecPerCcm.m @@ -0,0 +1,14 @@ +function gasPhaseConc = mbar2molecPerCcm(partialPressure, temperature) +%mbar2molecPerCcm converts partial pressure in mbar to concentration in +%molecules per cm3 +% +% * temperature is in K +% * partial pressure is in mbar +% * gasPhaseConc is in molec/cm3 + +R = 8.314472; % J/(K mol), gas constant +N_A = 6.02205E23; % molec/mole, Avogadro's number + +gasPhaseConc = partialPressure .* 100 .* N_A ./R ./temperature ./ 1E6; % in molec/cm3 +end + diff --git a/Add-Ons/readIBWbinheader.m b/Add-Ons/readIBWbinheader.m new file mode 100644 index 0000000..2654772 --- /dev/null +++ b/Add-Ons/readIBWbinheader.m @@ -0,0 +1,52 @@ +function H = readIBWbinheader(FFN); +% readIBWbinheader - read BinHeader segment of Igor IBW file +% H = readIBWbinheader('foo') reads BinHeader of file Foo.ibw +% IBW version 2,5 only +MAXDIMS = 4; + +fid = fopen(FFN,'r'); +H.version = fread(fid,1,'int16'); +switch H.version, + case 2, % typedef struct BinHeader2 { + H.wfmSize = fread(fid,1,'uint32'); % long wfmSize; // The size of the WaveHeader2 data structure plus the wave data plus 16 bytes of padding. + H.noteSize = fread(fid,1,'uint32'); % long noteSize; // The size of the note text. + H.pictSize = fread(fid,1,'uint32'); % long pictSize; // Reserved. Write zero. Ignore on read. + H.checksum = fread(fid,1,'int16'); % short checksum; // Checksum over this header and the wave header. + case 5, + H.checksum = fread(fid,1,'short'); + H.wfmSize = fread(fid,1,'long'); % The size of the WaveHeader5 data structure plus the wave data. + H.formulaSize = fread(fid,1,'long'); % The size of the dependency formula, if any. + H.noteSize = fread(fid,1,'long'); % The size of the note text. + H.dataEUnitsSize = fread(fid,1,'long'); % The size of optional extended data units. + H.dimEUnitsSize = fread(fid,MAXDIMS,'long'); % The size of optional extended dimension units. + H.dimLabelsSize = fread(fid,MAXDIMS,'long'); % The size of optional dimension labels. + H.sIndicesSize = fread(fid,1,'long'); ; % The size of string indicies if this is a text wave. + H.optionsSize1 = fread(fid,1,'long'); ; % Reserved. Write zero. Ignore on read. + H.optionsSize2 = fread(fid,1,'long'); ; % Reserved. Write zero. Ignore on read. + otherwise, +end % switch H.Version +fclose(fid); + +if ~ismember(H.version,[2 5]), + error(['Cannot read version ' num2str(H.version) ' IBW files - only versions 2,5 are okay.']); +end +%==FROM IgorBin.h ===================== +% #define MAXDIMS 4 +% +% typedef struct BinHeader5 { +% short version; // Version number for backwards compatibility. +% short checksum; // Checksum over this header and the wave header. +% long wfmSize; // The size of the WaveHeader5 data structure plus the wave data. +% long formulaSize; // The size of the dependency formula, if any. +% long noteSize; // The size of the note text. +% long dataEUnitsSize; // The size of optional extended data units. +% long dimEUnitsSize[MAXDIMS]; // The size of optional extended dimension units. +% long dimLabelsSize[MAXDIMS]; // The size of optional dimension labels. +% long sIndicesSize; // The size of string indicies if this is a text wave. +% long optionsSize1; // Reserved. Write zero. Ignore on read. +% long optionsSize2; // Reserved. Write zero. Ignore on read. +% } BinHeader5; + + + + diff --git a/Add-Ons/readIBWheaders.m b/Add-Ons/readIBWheaders.m new file mode 100644 index 0000000..75f10df --- /dev/null +++ b/Add-Ons/readIBWheaders.m @@ -0,0 +1,250 @@ +function [BH, H, FFN] = readIBWheaders(FFN); +% readIBWheaders - read BinHeader & WaveHeader segments of Igor IBW file +% [BH, WH, FFN] = readIBWheaders('foo') reads BinHeader & WaveHeader of +% file Foo.ibw - Versions 2 and 5 only. FFN is full filename. + +% % 1 byte char +% % 2 bytes short +% % 4 bytes int, long, float, Handle, any kind of pointer +% % 8 bytes double +MAXDIMS = 4; +MAX_WAVE_NAME2 = 18; % Maximum length of wave name in version 1 and 2 files. Does not include the trailing null. +MAX_WAVE_NAME5 = 31; % Maximum length of wave name in version 5 files. Does not include the trailing null. +MAX_UNIT_CHARS = 3; + + +BH = readIBWbinheader(FFN); +fid = fopen(FFN,'r'); +switch BH.version + case 2, + % The version 2 file has the following general layout. + % BinHeader2 structure: 16 bytes + % WaveHeader2 structure excluding wData field; 110 bytes + % Wave data: Variable size + fseek(fid,16,'bof'); % start of wave header of IBW vs 2; % struct WaveHeader2 { + H.type = fread(fid,1, 'uint16'); % short type; % See types (e.g. NT_FP64) above. Zero for text waves. + H.WaveHeader2 = fread(fid,1, 'uint32'); % struct WaveHeader2 **next; // Used in memory only. Write zero. Ignore on read. + H.bname = local_char(fread(fid, MAX_WAVE_NAME2+2, 'char')); % char bname[MAX_WAVE_NAME2+2]; // Name of wave plus trailing null. + H.whVersion = fread(fid,1, 'uint16'); % short whVersion; // Write 0. Ignore on read. + H.srcFldr = fread(fid,1, 'uint16'); % short srcFldr; // Used in memory only. Write zero. Ignore on read. + H.fileName = fread(fid,1, 'uint32'); % Handle fileName; // Used in memory only. Write zero. Ignore on read. + % + H.dataUnits = local_char(fread(fid, MAX_UNIT_CHARS+1, 'char')); % char dataUnits[MAX_UNIT_CHARS+1]; // Natural data units go here - null if none. + H.xUnits = local_char(fread(fid, MAX_UNIT_CHARS+1, 'char')); % char xUnits[MAX_UNIT_CHARS+1]; // Natural x-axis units go here - null if none. + % + H.npnts = fread(fid,1, 'uint32'); % long npnts; // Number of data points in wave. + % + H.aModified = fread(fid,1, 'uint16'); % short aModified; // Used in memory only. Write zero. Ignore on read. + H.hsA = fread(fid,1, 'double'); % double hsA,hsB; // X value for point p = hsA*p + hsB + H.hsB = fread(fid,1, 'double'); % double hsA,hsB; // X value for point p = hsA*p + hsB + % + H.wModified = fread(fid,1, 'uint16'); % short wModified; // Used in memory only. Write zero. Ignore on read. + H.swModified = fread(fid,1, 'uint16'); % short swModified; // Used in memory only. Write zero. Ignore on read. + H.fsValid = fread(fid,1, 'uint16'); % short fsValid; // True if full scale values have meaning. + H.topFullScale = fread(fid,1, 'double'); % double topFullScale,botFullScale; // The min full scale value for wave. + H.botFullScale = fread(fid,1, 'double'); % double topFullScale,botFullScale; // The min full scale value for wave. + % + H.useBits = fread(fid,1, 'char'); % char useBits; // Used in memory only. Write zero. Ignore on read. + H.kindBits = fread(fid,1, 'char'); % char kindBits; // Reserved. Write zero. Ignore on read. + H.formula = fread(fid,1, 'uint32'); % void **formula; // Used in memory only. Write zero. Ignore on read. + H.depID = fread(fid,1, 'uint32'); % long depID; // Used in memory only. Write zero. Ignore on read. + H.creationDate = fread(fid,1, '*uint32'); % unsigned long creationDate; // DateTime of creation. Not used in version 1 files. + H.platform = fread(fid,1, 'uint8'); % unsigned char platform; // 0=unspecified, 1=Macintosh, 2=Windows; Added for Igor Pro 5.5. +% dummy = fread(fid,1, 'uint8'); % align + H.wUnused = fread(fid,1, 'uint8'); % char wUnused[1]; // Reserved. Write zero. Ignore on read. + % + H.modDate = fread(fid,1, '*uint32'); % unsigned long modDate; // DateTime of last modification. + H.waveNoteH = fread(fid,1, 'uint32'); % Handle waveNoteH; // Used in memory only. Write zero. Ignore on read. + % + H.wData = fread(fid,4, 'single').'; % float wData[4]; // The start of the array of waveform data. + case 5, + % The version 5 file has the following general layout. + % BinHeader5 structure: 64 bytes + % WaveHeader5 structure excluding wData field: 320 bytes + % Wave data: Variable size + fseek(fid,64,'bof'); % start of wave header of IBW vs 5 + % + H.next = fread(fid,1, 'int32'); % link to next wave in linked list. + % + H.creationDate = fread(fid,1, 'uint32'); % DateTime of creation. + H.modDate = fread(fid,1, 'uint32'); % DateTime of creation. + % + H.npnts = fread(fid,1, 'int32'); % Total number of points (multiply dimensions up to first zero). + H.type = fread(fid,1, 'uint16'); % See types (e.g. NT_FP64) above. Zero for text waves. + H.dLock = fread(fid, 1, 'int16'); % Reserved. Write zero. Ignore on read. + % + H.whpad1 = fread(fid, 6, 'char').'; % Reserved. Write zero. Ignore on read. + H.whVersion = fread(fid, 1, 'int16'); % Write 1. Ignore on read. + H.bname = local_char(fread(fid, MAX_WAVE_NAME5+1, 'char')); % Name of wave plus trailing null. + H.whpad2 = fread(fid, 1, 'int32'); % long Reserved. Write zero. Ignore on read. + H.dFolder = fread(fid, 1, 'int32'); % ptr Used in memory only. Write zero. Ignore on read. + + % % Dimensioning info. [0] == rows, [1] == cols etc + H.nDim = fread(fid, MAXDIMS, 'int32').'; % long nDim[MAXDIMS] Number of of items in a dimension -- 0 means no data. + H.sfA = fread(fid, MAXDIMS, 'double').'; % double sfA[MAXDIMS]; Index value for element e of dimension d = sfA[d]*e + sfB[d]. + H.sfB = fread(fid, MAXDIMS, 'double').'; % double sfB[MAXDIMS];% double sfB[MAXDIMS]; + % % + % % % SI units + H.dataUnits = local_char(fread(fid, MAX_UNIT_CHARS+1, 'char')); % char dataUnits[MAX_UNIT_CHARS+1]; % Natural data units go here - null if none. + H.dimUnits = fread(fid, MAXDIMS*(MAX_UNIT_CHARS+1), '*char').'; % % char dimUnits[MAXDIMS][MAX_UNIT_CHARS+1]; % Natural dimension units go here - null if none. + % % + H.fsValid = fread(fid, 1, 'uint16'); % % short fsValid; % TRUE if full scale values have meaning. + H.whpad3 = fread(fid, 1, 'int16'); % % short whpad3; % Reserved. Write zero. Ignore on read. + H.topFullScale = fread(fid, 1, 'double'); + H.botFullScale = fread(fid, 1, 'double'); % % double topFullScale,botFullScale; % The max and max full scale value for wave. + % % + H.dataEUnits = fread(fid, 1, 'int32'); % % Handle dataEUnits; % Used in memory only. Write zero. Ignore on read. + H.dimEUnits = fread(fid, MAXDIMS, 'int32').'; % % Handle dimEUnits[MAXDIMS]; % Used in memory only. Write zero. Ignore on read. + H.dimLabels = fread(fid, MAXDIMS, 'int32').'; % % Handle dimLabels[MAXDIMS]; % Used in memory only. Write zero. Ignore on read. + % % + H.waveNoteH = fread(fid, 1, 'int32'); % % Handle waveNoteH; % Used in memory only. Write zero. Ignore on read. + % % + H.platform = fread(fid, 1, 'uint8'); % % unsigned char platform; % 0=unspecified, 1=Macintosh, 2=Windows; Added for Igor Pro 5. + H.skip_junk________ = fread(fid,80,'char').'; + % H. = fread(fid, 1, ''); + % % unsigned char spare[3]; + % H. = fread(fid, 1, ''); + % % + % H. = fread(fid, 1, ''); + % % long whUnused[13]; % Reserved. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % + % H. = fread(fid, 1, ''); + % % long vRefNum, dirID; % Used in memory only. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % + % H. = fread(fid, 1, ''); + % % % The following stuff is considered private to Igor. + % H. = fread(fid, 1, ''); + % % + % H. = fread(fid, 1, ''); + % % short aModified; % Used in memory only. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % short wModified; % Used in memory only. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % short swModified; % Used in memory only. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % + % H. = fread(fid, 1, ''); + % % char useBits; % Used in memory only. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % char kindBits; % Reserved. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % void **formula; % Used in memory only. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % long depID; % Used in memory only. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % + % H. = fread(fid, 1, ''); + % % short whpad4; % Reserved. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % short srcFldr; % Used in memory only. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % Handle fileName; % Used in memory only. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % + % H. = fread(fid, 1, ''); + % % long **sIndices; % Used in memory only. Write zero. Ignore on read. + % H. = fread(fid, 1, ''); + % % + H.wData = fread(fid, 1, 'single'); + % % float wData[1]; % The start of the array of data. Must be 64 bit aligned. + % H. = fread(fid, 1, ''); + % }; +end % switch BH.version +H.EOH_pos = ftell(fid); + + + + +fclose(fid); + +%==FROM IgorBin.h ===================== +% #define MAXDIMS 4 + +% % #define MAX_WAVE_NAME5 31 // Maximum length of wave name in version 5 files. Does not include the trailing null. +% % #define MAX_UNIT_CHARS 3 + +% % #define NT_CMPLX 1 % Complex numbers. +% % #define NT_FP32 2 % 32 bit fp numbers. +% % #define NT_FP64 4 % 64 bit fp numbers. +% % #define NT_I8 8 % 8 bit signed integer. Requires Igor Pro 2.0 or later. +% % #define NT_I16 0x10 % 16 bit integer numbers. Requires Igor Pro 2.0 or later. +% % #define NT_I32 0x20 % 32 bit integer numbers. Requires Igor Pro 2.0 or later. +% % #define NT_UNSIGNED 0x40 % Makes above signed integers unsigned. Requires Igor Pro 3.0 or later. +% +% struct WaveHeader5 { +% struct WaveHeader5 **next; % link to next wave in linked list. +% +% unsigned long creationDate; % DateTime of creation. +% unsigned long modDate; % DateTime of last modification. +% +% long npnts; % Total number of points (multiply dimensions up to first zero). +% short type; % See types (e.g. NT_FP64) above. Zero for text waves. +% short dLock; % Reserved. Write zero. Ignore on read. +% +% char whpad1[6]; % Reserved. Write zero. Ignore on read. +% short whVersion; % Write 1. Ignore on read. +% char bname[MAX_WAVE_NAME5+1]; % Name of wave plus trailing null. +% long whpad2; % Reserved. Write zero. Ignore on read. +% struct DataFolder **dFolder; % Used in memory only. Write zero. Ignore on read. +% +% % Dimensioning info. [0] == rows, [1] == cols etc +% long nDim[MAXDIMS]; % Number of of items in a dimension -- 0 means no data. +% double sfA[MAXDIMS]; % Index value for element e of dimension d = sfA[d]*e + sfB[d]. +% double sfB[MAXDIMS]; +% +% % SI units +% char dataUnits[MAX_UNIT_CHARS+1]; % Natural data units go here - null if none. +% char dimUnits[MAXDIMS][MAX_UNIT_CHARS+1]; % Natural dimension units go here - null if none. +% +% short fsValid; % TRUE if full scale values have meaning. +% short whpad3; % Reserved. Write zero. Ignore on read. +% double topFullScale,botFullScale; % The max and max full scale value for wave. +% +% Handle dataEUnits; % Used in memory only. Write zero. Ignore on read. +% Handle dimEUnits[MAXDIMS]; % Used in memory only. Write zero. Ignore on read. +% Handle dimLabels[MAXDIMS]; % Used in memory only. Write zero. Ignore on read. +% +% Handle waveNoteH; % Used in memory only. Write zero. Ignore on read. +% +% unsigned char platform; % 0=unspecified, 1=Macintosh, 2=Windows; Added for Igor Pro 5.5. +% unsigned char spare[3]; +% +% long whUnused[13]; % Reserved. Write zero. Ignore on read. +% +% long vRefNum, dirID; % Used in memory only. Write zero. Ignore on read. +% +% % The following stuff is considered private to Igor. +% +% short aModified; % Used in memory only. Write zero. Ignore on read. +% short wModified; % Used in memory only. Write zero. Ignore on read. +% short swModified; % Used in memory only. Write zero. Ignore on read. +% +% char useBits; % Used in memory only. Write zero. Ignore on read. +% char kindBits; % Reserved. Write zero. Ignore on read. +% void **formula; % Used in memory only. Write zero. Ignore on read. +% long depID; % Used in memory only. Write zero. Ignore on read. +% +% short whpad4; % Reserved. Write zero. Ignore on read. +% short srcFldr; % Used in memory only. Write zero. Ignore on read. +% Handle fileName; % Used in memory only. Write zero. Ignore on read. +% +% long **sIndices; % Used in memory only. Write zero. Ignore on read. +% +% float wData[1]; % The start of the array of data. Must be 64 bit aligned. +% }; + +function s=local_char(S); +% null-terminated string -> char string +S = S(:).'; +S = S(S~=0); +s=char(S); + + + + + + + + diff --git a/Add-Ons/rsquare.m b/Add-Ons/rsquare.m new file mode 100644 index 0000000..7a82f29 --- /dev/null +++ b/Add-Ons/rsquare.m @@ -0,0 +1,74 @@ +function [r2 rmse] = rsquare(y,f,varargin) +% Compute coefficient of determination of data fit model and RMSE +% +% [r2 rmse] = rsquare(y,f) +% [r2 rmse] = rsquare(y,f,c) +% +% RSQUARE computes the coefficient of determination (R-square) value from +% actual data Y and model data F. The code uses a general version of +% R-square, based on comparing the variability of the estimation errors +% with the variability of the original values. RSQUARE also outputs the +% root mean squared error (RMSE) for the user's convenience. +% +% Note: RSQUARE ignores comparisons involving NaN values. +% +% INPUTS +% Y : Actual data +% F : Model fit +% +% OPTION +% C : Constant term in model +% R-square may be a questionable measure of fit when no +% constant term is included in the model. +% [DEFAULT] TRUE : Use traditional R-square computation +% FALSE : Uses alternate R-square computation for model +% without constant term [R2 = 1 - NORM(Y-F)/NORM(Y)] +% +% OUTPUT +% R2 : Coefficient of determination +% RMSE : Root mean squared error +% +% EXAMPLE +% x = 0:0.1:10; +% y = 2.*x + 1 + randn(size(x)); +% p = polyfit(x,y,1); +% f = polyval(p,x); +% [r2 rmse] = rsquare(y,f); +% figure; plot(x,y,'b-'); +% hold on; plot(x,f,'r-'); +% title(strcat(['R2 = ' num2str(r2) '; RMSE = ' num2str(rmse)])) +% +% Jered R Wells +% 11/17/11 +% jered [dot] wells [at] duke [dot] edu +% +% v1.2 (02/14/2012) +% +% Thanks to John D'Errico for useful comments and insight which has helped +% to improve this code. His code POLYFITN was consulted in the inclusion of +% the C-option (REF. File ID: #34765). + +if isempty(varargin); c = true; +elseif length(varargin)>1; error 'Too many input arguments'; +elseif ~islogical(varargin{1}); error 'C must be logical (TRUE||FALSE)' +else c = varargin{1}; +end + +% Compare inputs +if ~all(size(y)==size(f)); error 'Y and F must be the same size'; end + +% Check for NaN +tmp = ~or(isnan(y),isnan(f)); +y = y(tmp); +f = f(tmp); + +if c; r2 = max(0,1 - sum((y(:)-f(:)).^2)/sum((y(:)-mean(y(:))).^2)); +else r2 = 1 - sum((y(:)-f(:)).^2)/sum((y(:)).^2); + if r2<0 + % http://web.maths.unsw.edu.au/~adelle/Garvan/Assays/GoodnessOfFit.html + warning('Consider adding a constant term to your model') %#ok + r2 = 0; + end +end + +rmse = sqrt(mean((y(:) - f(:)).^2)); \ No newline at end of file diff --git a/Add-Ons/spider_plot.m b/Add-Ons/spider_plot.m new file mode 100644 index 0000000..97a9ba8 --- /dev/null +++ b/Add-Ons/spider_plot.m @@ -0,0 +1,916 @@ +function spider_plot(P, varargin) +%spider_plot Create a spider or radar plot with individual axes. +% +% Syntax: +% spider_plot(P) +% spider_plot(P, Name, Value, ...) +% +% Input Arguments: +% (Required) +% P - The data points used to plot the spider chart. The +% rows are the groups of data and the columns are the +% data points. The axes labels and axes limits are +% automatically generated if not specified. +% [vector | matrix] +% +% Name-Value Pair Arguments: +% (Optional) +% AxesLabels - Used to specify the label each of the axes. +% [auto-generated (default) | cell array of character vectors | 'none'] +% +% AxesInterval - Used to change the number of intervals displayed +% between the webs. +% [3 (default) | integer] +% +% AxesPrecision - Used to change the precision level on the value +% displayed on the axes. +% [1 (default) | integer | vector] +% +% AxesDisplay - Used to change the number of axes in which the +% axes text are displayed. 'None' or 'one' can be used +% to simplify the plot appearance for normalized data. +% ['all' (default) | 'none' | 'one'] +% +% AxesLimits - Used to manually set the axes limits. A matrix of +% 2 x size(P, 2). The top row is the minimum axes +% limits and the bottow row is the maximum axes limits. +% [auto-scaled (default) | matrix] +% +% FillOption - Used to toggle color fill option. +% ['off' (default) | 'on'] +% +% FillTransparency - Used to set color fill transparency. +% [0.1 (default) | scalar in range (0, 1)] +% +% Color - Used to specify the line color, specified as an RGB +% triplet. The intensities must be in the range (0, 1). +% [MATLAB colors (default) | RGB triplet | hexadecimal color code] +% +% LineStyle - Used to change the line style of the plots. +% ['-' (default) | '--' | ':' | '-.' | 'none' | cell array of character vectors] +% +% LineWidth - Used to change the line width, where 1 point is +% 1/72 of an inch. +% [0.5 (default) | positive value | vector] +% +% Marker - Used to change the marker symbol of the plots. +% ['o' (default) | 'none' | '*' | 's' | 'd' | ... | cell array of character vectors] +% +% MarkerSize - Used to change the marker size, where 1 point is +% 1/72 of an inch. +% [8 (default) | positive value | vector] +% +% AxesFont - Used to change the font type of the values +% displayed on the axes. +% [Helvetica (default) | supported font name] +% +% LabelFont - Used to change the font type of the labels. +% [Helvetica (default) | supported font name] +% +% AxesFontSize - Used to change the font size of the values +% displayed on the axes. +% [10 (default) | scalar value greater than zero] +% +% LabelFontSize - Used to change the font size of the labels. +% [10 (default) | scalar value greater than zero] +% +% Direction - Used to change the direction of rotation of the +% plotted data and axis labels. +% ['clockwise' (default) | 'counterclockwise'] +% +% AxesDirection - Used to change the direction of axes. +% ['normal' (default) | 'reverse' | cell array of character vectors] +% +% AxesLabelsOffset - Used to adjust the position offset of the axes +% labels. +% [0.1 (default) | positive value] +% +% AxesScaling - Used to change the scaling of the axes. +% ['linear' (default) | 'log' | cell array of character vectors] +% +% AxesColor - Used to change the color of the spider axes. +% [grey (default) | RGB triplet | hexadecimal color code] +% +% AxesLabelsEdge - Used to change the edge color of the axes labels. +% [black (default) | RGB triplet | hexadecimal color code | 'none'] +% +% AxesOffset - Used to change to axes offset from the origin. +% [1 (default) | any integer less than the axes interval] +% +% Examples: +% % Example 1: Minimal number of arguments. All non-specified, optional +% arguments are set to their default values. Axes labels +% and limits are automatically generated and set. +% +% D1 = [5 3 9 1 2]; +% D2 = [5 8 7 2 9]; +% D3 = [8 2 1 4 6]; +% P = [D1; D2; D3]; +% spider_plot(P); +% legend('D1', 'D2', 'D3', 'Location', 'southoutside'); +% +% % Example 2: Manually setting the axes limits and axes precision. +% All non-specified, optional arguments are set to their +% default values. +% +% D1 = [5 3 9 1 2]; +% D2 = [5 8 7 2 9]; +% D3 = [8 2 1 4 6]; +% P = [D1; D2; D3]; +% spider_plot(P,... +% 'AxesLimits', [1, 2, 1, 1, 1; 10, 8, 9, 5, 10],... % [min axes limits; max axes limits] +% 'AxesPrecision', [0, 1, 1, 1, 1]); +% +% % Example 3: Set fill option on. The fill transparency can be adjusted. +% +% D1 = [5 3 9 1 2]; +% D2 = [5 8 7 2 9]; +% D3 = [8 2 1 4 6]; +% P = [D1; D2; D3]; +% spider_plot(P,... +% 'AxesLabels', {'S1', 'S2', 'S3', 'S4', 'S5'},... +% 'AxesInterval', 2,... +% 'FillOption', 'on',... +% 'FillTransparency', 0.1); +% +% % Example 4: Maximum number of arguments. +% +% D1 = [5 3 9 1 2]; +% D2 = [5 8 7 2 9]; +% D3 = [8 2 1 4 6]; +% P = [D1; D2; D3]; +% spider_plot(P,... +% 'AxesLabels', {'S1', 'S2', 'S3', 'S4', 'S5'},... +% 'AxesInterval', 4,... +% 'AxesPrecision', 0,... +% 'AxesDisplay', 'one',... +% 'AxesLimits', [1, 2, 1, 1, 1; 10, 8, 9, 5, 10],... +% 'FillOption', 'on',... +% 'FillTransparency', 0.2,... +% 'Color', [1, 0, 0; 0, 1, 0; 0, 0, 1],... +% 'LineStyle', {'--', '-', '--'},... +% 'LineWidth', [1, 2, 3],... +% 'Marker', {'o', 'd', 's'},... +% 'MarkerSize', [8, 10, 12],... +% 'AxesFont', 'Times New Roman',... +% 'LabelFont', 'Times New Roman',... +% 'AxesFontSize', 12,... +% 'LabelFontSize', 10,... +% 'Direction', 'clockwise',... +% 'AxesDirection', {'reverse', 'normal', 'normal', 'normal', 'normal'},... +% 'AxesLabelsOffset', 0.1,... +% 'AxesScaling', 'linear',... +% 'AxesColor', [0.6, 0.6, 0.6],... +% 'AxesLabelsEdge', 'none',... +% 'AxesOffset', 1); +% +% % Example 5: Excel-like radar charts. +% +% D1 = [5 0 3 4 4]; +% D2 = [2 1 5 5 4]; +% P = [D1; D2]; +% spider_plot(P,... +% 'AxesInterval', 5,... +% 'AxesPrecision', 0,... +% 'AxesDisplay', 'one',... +% 'AxesLimits', [0, 0, 0, 0, 0; 5, 5, 5, 5, 5],... +% 'FillOption', 'on',... +% 'FillTransparency', 0.1,... +% 'Color', [139, 0, 0; 240, 128, 128]/255,... +% 'LineWidth', 4,... +% 'Marker', 'none',... +% 'AxesFontSize', 14,... +% 'LabelFontSize', 10,... +% 'AxesColor', [0.8, 0.8, 0.8],... +% 'AxesLabelsEdge', 'none'); +% title('Excel-like Radar Chart',... +% 'FontSize', 14); +% legend_str = {'D1', 'D2'}; +% legend(legend_str, 'Location', 'southoutside'); +% +% % Example 6: Logarithimic scale on specified axes. Axes limits and axes +% intervals can be individually set as well. +% +% D1 = [5 3 9 1 1]; +% D2 = [5 8 7 2 10]; +% D3 = [8 2 1 4 100]; +% P = [D1; D2; D3]; +% spider_plot(P,... +% 'AxesInterval', 2,... +% 'AxesPrecision', 0,... +% 'AxesFontSize', 10,... +% 'AxesLabels', {'Linear Scale', 'Linear Scale', 'Linear Scale', 'Linear Scale', 'Logarithimic Scale'},... +% 'AxesScaling', {'linear', 'linear', 'linear', 'linear', 'log'},... +% 'AxesLimits', [1, 1, 1, 1, 1; 10, 10, 10, 10, 100]); +% legend('D1', 'D2', 'D3', 'Location', 'northeast'); +% +% % Example 7: Spider plot with subplot feature. +% +% D1 = [5 3 9 1 2]; +% D2 = [5 8 7 2 9]; +% D3 = [8 2 1 4 6]; +% P = [D1; D2; D3]; +% subplot(1, 2, 1) +% spider_plot(P,... +% 'AxesInterval', 1,... +% 'AxesPrecision', 0); +% subplot(1, 2, 2) +% spider_plot(P,... +% 'AxesInterval', 1,... +% 'AxesPrecision', 0); +% +% Author: +% Moses Yoo, (jyoo at hatci dot com) +% 2020-12-01: Added support for adjust the axes offset from origin. +% 2020-11-30: Allow for one data group without specified axes limits. +% 2020-11-30: Added support for changing axes and label font type. +% 2020-11-06: Fix bug in reverse axes direction feature. +% 2020-10-08: Adjust axes precision to be set to one or more axis. +% 2020-09-30: Updated examples and added ability to reverse axes direction. +% 2020-07-05: Added feature to change spider axes and axes labels edge color. +% 2020-06-17: Allow logarithmic scale to be set to one or more axis. +% 2020-03-26: Added feature to allow different line styles, line width, +% marker type, and marker sizes for the data groups. +% 2020-02-12: Fixed condition and added error checking for when only one +% data group is plotted. +% 2020-01-27: Corrected bug where only 7 entries were allowed in legend. +% 2020-01-06: Added support for subplot feature. +% 2019-11-27: Add option to change axes to logarithmic scale. +% 2019-11-15: Add feature to customize the plot rotational direction and +% the offset position of the axis labels. +% 2019-10-23: Minor revision to set starting axes as the vertical line. +% Add customization option for font sizes and axes display. +% 2019-10-16: Minor revision to add name-value pairs for customizing +% color, marker, and line settings. +% 2019-10-08: Another major revision to convert to name-value pairs and +% add color fill option. +% 2019-09-17: Major revision to improve speed, clarity, and functionality +% +% Special Thanks: +% Special thanks to Gabriela Andrade, Andrés Garcia, Alex Grenyer, +% Tobias Kern, Zafar Ali, Christophe Hurlin, Roman, Mariusz Sepczuk, +% Mohamed Abubakr, Nicolai, Jingwei Too, Cedric Jamet & Richard Ruff +% for their feature recommendations and suggested bug fixes. + +%%% Data Properties %%% +% Point properties +[num_data_groups, num_data_points] = size(P); + +% Number of optional arguments +numvarargs = length(varargin); + +% Check for even number of name-value pair argments +if mod(numvarargs, 2) == 1 + error('Error: Please check name-value pair arguments'); +end + +% Create default labels +axes_labels = cell(1, num_data_points); + +% Iterate through number of data points +for ii = 1:num_data_points + % Default axes labels + axes_labels{ii} = sprintf('Label %i', ii); +end + +% Default arguments +axes_interval = 3; +axes_precision = 1; +axes_display = 'all'; +axes_limits = []; +fill_option = 'off'; +fill_transparency = 0.2; +colors = lines(num_data_groups); +line_style = '-'; +line_width = 2; +marker_type = 'o'; +marker_size = 8; +axes_font = 'Helvetica'; +label_font = 'Helvetica'; +axes_font_size = 10; +label_font_size = 10; +direction = 'clockwise'; +axes_direction = 'normal'; +axes_labels_offset = 0.1; +axes_scaling = 'linear'; +axes_color = [0.6, 0.6, 0.6]; +axes_labels_edge = 'k'; +axes_offset = 1; + +% Check if optional arguments were specified +if numvarargs > 1 + % Initialze name-value arguments + name_arguments = varargin(1:2:end); + value_arguments = varargin(2:2:end); + + % Iterate through name-value arguments + for ii = 1:length(name_arguments) + % Set value arguments depending on name + switch lower(name_arguments{ii}) + case 'axeslabels' + axes_labels = value_arguments{ii}; + case 'axesinterval' + axes_interval = value_arguments{ii}; + case 'axesprecision' + axes_precision = value_arguments{ii}; + case 'axesdisplay' + axes_display = value_arguments{ii}; + case 'axeslimits' + axes_limits = value_arguments{ii}; + case 'filloption' + fill_option = value_arguments{ii}; + case 'filltransparency' + fill_transparency = value_arguments{ii}; + case 'color' + colors = value_arguments{ii}; + case 'linestyle' + line_style = value_arguments{ii}; + case 'linewidth' + line_width = value_arguments{ii}; + case 'marker' + marker_type = value_arguments{ii}; + case 'markersize' + marker_size = value_arguments{ii}; + case 'axesfont' + axes_font = value_arguments{ii}; + case 'labelfont' + label_font = value_arguments{ii}; + case 'axesfontsize' + axes_font_size = value_arguments{ii}; + case 'labelfontsize' + label_font_size = value_arguments{ii}; + case 'direction' + direction = value_arguments{ii}; + case 'axesdirection' + axes_direction = value_arguments{ii}; + case 'axeslabelsoffset' + axes_labels_offset = value_arguments{ii}; + case 'axesscaling' + axes_scaling = value_arguments{ii}; + case 'axescolor' + axes_color = value_arguments{ii}; + case 'axeslabelsedge' + axes_labels_edge = value_arguments{ii}; + case 'axesoffset' + axes_offset = value_arguments{ii}; + otherwise + error('Error: Please enter in a valid name-value pair.'); + end + end + +end + +%%% Error Check %%% +% Check if axes labels is a cell +if iscell(axes_labels) + % Check if the axes labels are the same number as the number of points + if length(axes_labels) ~= num_data_points + error('Error: Please make sure the number of labels is the same as the number of points.'); + end +else + % Check if valid char entry + if ~contains(axes_labels, 'none') + error('Error: Please enter in valid labels or "none" to remove labels.'); + end +end + +% Check if axes limits is not empty +if ~isempty(axes_limits) + % Check if the axes limits same length as the number of points + if size(axes_limits, 1) ~= 2 || size(axes_limits, 2) ~= num_data_points + error('Error: Please make sure the min and max axes limits match the number of data points.'); + end + + % Lower and upper limits + lower_limits = axes_limits(1, :); + upper_limits = axes_limits(2, :); + + % Difference in upper and lower limits + diff_limits = upper_limits - lower_limits; + + % Check to make sure upper limit is greater than lower limit + if any(diff_limits < 0) + error('Error: Please make sure max axes limits are greater than the min axes limits.'); + end + + % Check the range of axes limits + if any(diff_limits == 0) + error('Error: Please make sure the min and max axes limits are different.'); + end +end + +% Check if axes precision is numeric +if isnumeric(axes_precision) + % Check is length is one + if length(axes_precision) == 1 + % Repeat array to number of data points + axes_precision = repmat(axes_precision, num_data_points, 1); + elseif length(axes_precision) ~= num_data_points + error('Error: Please specify the same number of axes precision as number of data points.'); + end +else + error('Error: Please make sure the axes precision is a numeric value.'); +end + +% Check if axes properties are an integer +if floor(axes_interval) ~= axes_interval || any(floor(axes_precision) ~= axes_precision) + error('Error: Please enter in an integer for the axes properties.'); +end + +% Check if axes properties are positive +if axes_interval < 1 || any(axes_precision < 0) + error('Error: Please enter a positive value for the axes properties.'); +end + +% Check if axes display is valid char entry +if ~ismember(axes_display, {'all', 'none', 'one'}) + error('Error: Invalid axes display entry. Please enter in "all", "none", or "one" to set axes text.'); +end + +% Check if not a valid fill option arguement +if ~ismember(fill_option, {'off', 'on'}) + error('Error: Please enter either "off" or "on" for fill option.'); +end + +% Check if fill transparency is valid +if fill_transparency < 0 || fill_transparency > 1 + error('Error: Please enter a transparency value between [0, 1].'); +end + +% Check if font size is greater than zero +if axes_font_size <= 0 || label_font_size <= 0 + error('Error: Please enter a font size greater than zero.'); +end + +% Check if direction is valid char entry +if ~ismember(direction, {'counterclockwise', 'clockwise'}) + error('Error: Invalid direction entry. Please enter in "counterclockwise" or "clockwise" to set direction of rotation.'); +end + +% Check if axes direction is valid char entry +if ~ismember(axes_direction, {'normal', 'reverse'}) + error('Error: Invalid axes direction entry. Please enter in "normal" or "reverse" to set axes direction.'); +end + +% Check if axes labels offset is positive +if axes_labels_offset < 0 + error('Error: Please enter a positive for the axes labels offset.'); +end + +% Check if axes scaling is valid +if any(~ismember(axes_scaling, {'linear', 'log'})) + error('Error: Invalid axes scaling entry. Please enter in "linear" or "log" to set axes scaling.'); +end + +% Check if axes offset is valid +if floor(axes_offset)~=axes_offset || axes_offset < 0 || axes_offset > axes_interval + error('Error: Invalid axes offset entry. Please enter in an integer value that is between [0, axes_interval].'); +end + +% Check if axes scaling is a cell +if iscell(axes_scaling) + % Check is length is one + if length(axes_scaling) == 1 + % Repeat array to number of data groups + axes_scaling = repmat(axes_scaling, num_data_points, 1); + elseif length(axes_scaling) ~= num_data_points + error('Error: Please specify the same number of axes scaling as number of data points.'); + end +else + % Repeat array to number of data groups + axes_scaling = repmat({axes_scaling}, num_data_points, 1); +end + +% Check if line style is a char +if ischar(line_style) + % Convert to cell array of char + line_style = cellstr(line_style); + + % Repeat cell to number of data groups + line_style = repmat(line_style, num_data_groups, 1); +elseif iscellstr(line_style) + % Check is length is one + if length(line_style) == 1 + % Repeat cell to number of data groups + line_style = repmat(line_style, num_data_groups, 1); + elseif length(line_style) ~= num_data_groups + error('Error: Please specify the same number of line styles as number of data groups.'); + end +else + error('Error: Please make sure the line style is a char or a cell array of char.'); +end + +% Check if line width is numeric +if isnumeric(line_width) + % Check is length is one + if length(line_width) == 1 + % Repeat array to number of data groups + line_width = repmat(line_width, num_data_groups, 1); + elseif length(line_width) ~= num_data_groups + error('Error: Please specify the same number of line width as number of data groups.'); + end +else + error('Error: Please make sure the line width is a numeric value.'); +end + +% Check if marker type is a char +if ischar(marker_type) + % Convert to cell array of char + marker_type = cellstr(marker_type); + + % Repeat cell to number of data groups + marker_type = repmat(marker_type, num_data_groups, 1); +elseif iscellstr(marker_type) + % Check is length is one + if length(marker_type) == 1 + % Repeat cell to number of data groups + marker_type = repmat(marker_type, num_data_groups, 1); + elseif length(marker_type) ~= num_data_groups + error('Error: Please specify the same number of line styles as number of data groups.'); + end +else + error('Error: Please make sure the line style is a char or a cell array of char.'); +end + +% Check if line width is numeric +if isnumeric(marker_size) + if length(marker_size) == 1 + % Repeat array to number of data groups + marker_size = repmat(marker_size, num_data_groups, 1); + elseif length(marker_size) ~= num_data_groups + error('Error: Please specify the same number of line width as number of data groups.'); + end +else + error('Error: Please make sure the line width is numeric.'); +end + +% Check if axes direction is a cell +if iscell(axes_direction) + % Check is length is one + if length(axes_direction) == 1 + % Repeat array to number of data groups + axes_direction = repmat(axes_direction, num_data_points, 1); + elseif length(axes_direction) ~= num_data_points + error('Error: Please specify the same number of axes direction as number of data points.'); + end +else + % Repeat array to number of data groups + axes_direction = repmat({axes_direction}, num_data_points, 1); +end + +%%% Axes Scaling Properties %%% +% Check axes scaling option +log_index = strcmp(axes_scaling, 'log'); + +% If any log scaling is specified +if any(log_index) + % Initialize copy + P_log = P(:, log_index); + + % Logarithm of base 10, account for numbers less than 1 + P_log = sign(P_log) .* log10(abs(P_log)); + + % Minimum and maximun log limits + min_limit = min(min(fix(P_log))); + max_limit = max(max(ceil(P_log))); + recommended_axes_interval = max_limit - min_limit; + + % Warning message + warning('For the log scale values, recommended axes limit is [%i, %i] with an axes interval of %i.',... + 10^min_limit, 10^max_limit, recommended_axes_interval); + + % Replace original + P(:, log_index) = P_log; +end + +%%% Figure Properties %%% +% Grab current figure +fig = gcf; + +% Set figure background +fig.Color = 'white'; + +% Reset axes +cla reset; + +% Current axes handle +ax = gca; + +% Axis limits +hold on; +axis square; +axis([-1, 1, -1, 1] * 1.3); + +% Axis properties +ax.XTickLabel = []; +ax.YTickLabel = []; +ax.XColor = 'none'; +ax.YColor = 'none'; + +% Polar increments +theta_increment = 2*pi/num_data_points; +full_interval = axes_interval + 1; +rho_offset = axes_offset/full_interval; + +%%% Scale Data %%% +% Pre-allocation +P_scaled = zeros(size(P)); +axes_range = zeros(3, num_data_points); + +% Check axes scaling option +axes_direction_index = strcmp(axes_direction, 'reverse'); + +% Iterate through number of data points +for ii = 1:num_data_points + % Check for one data group and no axes limits + if num_data_groups == 1 && isempty(axes_limits) + % Group of points + group_points = P(:, :); + else + % Group of points + group_points = P(:, ii); + end + + % Check for log axes scaling option + if log_index(ii) + % Minimum and maximun log limits + min_value = min(fix(group_points)); + max_value = max(ceil(group_points)); + else + % Automatically the range of each group + min_value = min(group_points); + max_value = max(group_points); + end + + % Range of min and max values + range = max_value - min_value; + + % Check if axes_limits is not empty + if ~isempty(axes_limits) + % Check for log axes scaling option + if log_index(ii) + % Logarithm of base 10, account for numbers less than 1 + axes_limits(:, ii) = sign(axes_limits(:, ii)) .* log10(abs(axes_limits(:, ii))); %#ok + end + + % Manually set the range of each group + min_value = axes_limits(1, ii); + max_value = axes_limits(2, ii); + range = max_value - min_value; + + % Check if the axes limits are within range of points + if min_value > min(group_points) || max_value < max(group_points) + error('Error: Please make the manually specified axes limits are within range of the data points.'); + end + end + + % Scale points to range from [0, 1] + P_scaled(:, ii) = ((P(:, ii) - min_value) / range); + + % If reverse axes direction is specified + if axes_direction_index(ii) + % Store to array + axes_range(:, ii) = [max_value; min_value; range]; + P_scaled(:, ii) = -(P_scaled(:, ii) - 1); + else + % Store to array + axes_range(:, ii) = [min_value; max_value; range]; + end + + % Add offset of [rho_offset] and scaling factor of [1 - rho_offset] + P_scaled(:, ii) = P_scaled(:, ii) * (1 - rho_offset) + rho_offset; +end + +%%% Polar Axes %%% +% Polar coordinates +rho_increment = 1/full_interval; +rho = 0:rho_increment:1; + +% Check rotational direction +switch direction + case 'counterclockwise' + % Shift by pi/2 to set starting axis the vertical line + theta = (0:theta_increment:2*pi) + (pi/2); + case 'clockwise' + % Shift by pi/2 to set starting axis the vertical line + theta = (0:-theta_increment:-2*pi) + (pi/2); +end + +% Remainder after using a modulus of 2*pi +theta = mod(theta, 2*pi); + +% Iterate through each theta +for ii = 1:length(theta)-1 + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta(ii), rho); + + % Plot webs + h = plot(x_axes, y_axes,... + 'LineWidth', 1.5,... + 'Color', axes_color); + + % Turn off legend annotation + h.Annotation.LegendInformation.IconDisplayStyle = 'off'; +end + +% Iterate through each rho +for ii = 2:length(rho) + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta, rho(ii)); + + % Plot axes + h = plot(x_axes, y_axes,... + 'Color', axes_color); + + % Turn off legend annotation + h.Annotation.LegendInformation.IconDisplayStyle = 'off'; +end + +% Set end index depending on axes display argument +switch axes_display + case 'all' + theta_end_index = length(theta)-1; + case 'one' + theta_end_index = 1; + case 'none' + theta_end_index = 0; +end + +% Rho start index and offset interval +rho_start_index = axes_offset+1; +offset_interval = full_interval - axes_offset; + +% Iterate through each theta +for ii = 1:theta_end_index + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta(ii), rho); + + % Iterate through points on isocurve + for jj = rho_start_index:length(rho) + % Axes increment range + min_value = axes_range(1, ii); + range = axes_range(3, ii); + + % If reverse axes direction is specified + if axes_direction_index(ii) + % Axes increment value + axes_value = min_value - (range/offset_interval) * (jj-rho_start_index); + else + % Axes increment value + axes_value = min_value + (range/offset_interval) * (jj-rho_start_index); + end + + % Check for log axes scaling option + if log_index(ii) + % Exponent to the tenth power + axes_value = 10^axes_value; + end + + % Display axes text + text_str = sprintf(sprintf('%%.%if', axes_precision(ii)), axes_value); + text(x_axes(jj), y_axes(jj), text_str,... + 'Units', 'Data',... + 'Color', 'k',... + 'FontName', axes_font,... + 'FontSize', axes_font_size,... + 'HorizontalAlignment', 'center',... + 'VerticalAlignment', 'middle'); + end +end + +%%% Plot %%% +% Iterate through number of data groups +for ii = 1:num_data_groups + % Convert polar to cartesian coordinates + [x_points, y_points] = pol2cart(theta(1:end-1), P_scaled(ii, :)); + + % Make points circular + x_circular = [x_points, x_points(1)]; + y_circular = [y_points, y_points(1)]; + + % Plot data points + plot(x_circular, y_circular,... + 'LineStyle', line_style{ii},... + 'Marker', marker_type{ii},... + 'Color', colors(ii, :),... + 'LineWidth', line_width(ii),... + 'MarkerSize', marker_size(ii),... + 'MarkerFaceColor', colors(ii, :)); + + % Check if fill option is toggled on + if strcmp(fill_option, 'on') + % Fill area within polygon + h = patch(x_circular, y_circular, colors(ii, :),... + 'EdgeColor', 'none',... + 'FaceAlpha', fill_transparency); + + % Turn off legend annotation + h.Annotation.LegendInformation.IconDisplayStyle = 'off'; + end +end + +% Find object handles +text_handles = findobj(ax.Children,... + 'Type', 'Text'); +patch_handles = findobj(ax.Children,... + 'Type', 'Patch'); +isocurve_handles = findobj(ax.Children,... + 'Color', axes_color,... + '-and', 'Type', 'Line'); +plot_handles = findobj(ax.Children, '-not',... + 'Color', axes_color,... + '-and', 'Type', 'Line'); + +% Manually set the stack order +uistack(text_handles, 'bottom'); +uistack(plot_handles, 'bottom'); +uistack(patch_handles, 'bottom'); +uistack(isocurve_handles, 'bottom'); + +%%% Labels %%% +% Check labels argument +if ~strcmp(axes_labels, 'none') + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta, rho(end)); + + % Iterate through number of data points + for ii = 1:length(axes_labels) + % Angle of point in radians + theta_point = theta(ii); + + % Find out which quadrant the point is in + if theta_point == 0 + quadrant = 0; + elseif theta_point == pi/2 + quadrant = 1.5; + elseif theta_point == pi + quadrant = 2.5; + elseif theta_point == 3*pi/2 + quadrant = 3.5; + elseif theta_point == 2*pi + quadrant = 0; + elseif theta_point > 0 && theta_point < pi/2 + quadrant = 1; + elseif theta_point > pi/2 && theta_point < pi + quadrant = 2; + elseif theta_point > pi && theta_point < 3*pi/2 + quadrant = 3; + elseif theta_point > 3*pi/2 && theta_point < 2*pi + quadrant = 4; + end + + % Adjust label alignment depending on quadrant + switch quadrant + case 0 + horz_align = 'left'; + vert_align = 'middle'; + x_pos = axes_labels_offset; + y_pos = 0; + case 1 + horz_align = 'left'; + vert_align = 'bottom'; + x_pos = axes_labels_offset; + y_pos = axes_labels_offset; + case 1.5 + horz_align = 'center'; + vert_align = 'bottom'; + x_pos = 0; + y_pos = axes_labels_offset; + case 2 + horz_align = 'right'; + vert_align = 'bottom'; + x_pos = -axes_labels_offset; + y_pos = axes_labels_offset; + case 2.5 + horz_align = 'right'; + vert_align = 'middle'; + x_pos = -axes_labels_offset; + y_pos = 0; + case 3 + horz_align = 'right'; + vert_align = 'top'; + x_pos = -axes_labels_offset; + y_pos = -axes_labels_offset; + case 3.5 + horz_align = 'center'; + vert_align = 'top'; + x_pos = 0; + y_pos = -axes_labels_offset; + case 4 + horz_align = 'left'; + vert_align = 'top'; + x_pos = axes_labels_offset; + y_pos = -axes_labels_offset; + end + + % Display text label + text(x_axes(ii)+x_pos, y_axes(ii)+y_pos, axes_labels{ii},... + 'Units', 'Data',... + 'HorizontalAlignment', horz_align,... + 'VerticalAlignment', vert_align,... + 'EdgeColor', axes_labels_edge,... + 'BackgroundColor', 'w',... + 'FontName', label_font,... + 'FontSize', label_font_size); + end +end \ No newline at end of file diff --git a/Add-Ons/spider_plot_R2019b.m b/Add-Ons/spider_plot_R2019b.m new file mode 100644 index 0000000..5e353c6 --- /dev/null +++ b/Add-Ons/spider_plot_R2019b.m @@ -0,0 +1,822 @@ +function spider_plot_R2019b(P, options) +%spider_plot_R2019b Create a spider or radar plot with individual axes. +% +% Syntax: +% spider_plot_R2019b(P) +% spider_plot_R2019b(P, Name, Value, ...) +% +% Input Arguments: +% (Required) +% P - The data points used to plot the spider chart. The +% rows are the groups of data and the columns are the +% data points. The axes labels and axes limits are +% automatically generated if not specified. +% [vector | matrix] +% +% Name-Value Pair Arguments: +% (Optional) +% AxesLabels - Used to specify the label each of the axes. +% [auto-generated (default) | cell array of character vectors | 'none'] +% +% AxesInterval - Used to change the number of intervals displayed +% between the webs. +% [3 (default) | integer] +% +% AxesPrecision - Used to change the precision level on the value +% displayed on the axes. +% [1 (default) | integer | vector] +% +% AxesDisplay - Used to change the number of axes in which the +% axes text are displayed. 'None' or 'one' can be used +% to simplify the plot appearance for normalized data. +% ['all' (default) | 'none' | 'one'] +% +% AxesLimits - Used to manually set the axes limits. A matrix of +% 2 x size(P, 2). The top row is the minimum axes +% limits and the bottow row is the maximum axes limits. +% [auto-scaled (default) | matrix] +% +% FillOption - Used to toggle color fill option. +% ['off' (default) | 'on'] +% +% FillTransparency - Used to set color fill transparency. +% [0.1 (default) | scalar in range (0, 1)] +% +% Color - Used to specify the line color, specified as an RGB +% triplet. The intensities must be in the range (0, 1). +% [MATLAB colors (default) | RGB triplet] +% +% LineStyle - Used to change the line style of the plots. +% ['-' (default) | '--' | ':' | '-.' | 'none' | cell array of character vectors] +% +% LineWidth - Used to change the line width, where 1 point is +% 1/72 of an inch. +% [0.5 (default) | positive value | vector] +% +% Marker - Used to change the options.Marker symbol of the plots. +% ['o' (default) | 'none' | '*' | 's' | 'd' | ... | cell array of character vectors] +% +% MarkerSize - Used to change the options.Marker size, where 1 point is +% 1/72 of an inch. +% [8 (default) | positive value | vector] +% +% AxesFont - Used to change the font type of the values +% displayed on the axes. +% [Helvetica (default) | supported font name] +% +% LabelFont - Used to change the font type of the labels. +% [Helvetica (default) | supported font name] +% +% AxesFontSize - Used to change the font size of the values +% displayed on the axes. +% [10 (default) | scalar value greater than zero] +% +% LabelFontSize - Used to change the font size of the labels. +% [10 (default) | scalar value greater than zero] +% +% Direction - Used to change the direction of rotation of the +% plotted data and axis labels. +% ['clockwise' (default) | 'counterclockwise'] +% +% AxesDirection - Used to change the direction of axes. +% ['normal' (default) | 'reverse' | cell array of character vectors] +% +% AxesLabelsOffset - Used to adjust the position offset of the axes +% labels. +% [0.1 (default) | positive value] +% +% AxesScaling - Used to change the scaling of the axes. +% ['linear' (default) | 'log' | cell array of character vectors] +% +% AxesColor - Used to change the color of the spider axes. +% [grey (default) | RGB triplet | hexadecimal color code] +% +% AxesLabelsEdge - Used to change the edge color of the axes labels. +% [black (default) | RGB triplet | hexadecimal color code | 'none'] +% +% AxesOffset - Used to change to axes offset from the origin. +% [1 (default) | any integer less than the axes interval] +% +% Examples: +% % Example 1: Minimal number of arguments. All non-specified, optional +% arguments are set to their default values. Axes labels +% and limits are automatically generated and set. +% +% D1 = [5 3 9 1 2]; +% D2 = [5 8 7 2 9]; +% D3 = [8 2 1 4 6]; +% P = [D1; D2; D3]; +% spider_plot_R2019b(P); +% legend('D1', 'D2', 'D3', 'Location', 'southoutside'); +% +% % Example 2: Manually setting the axes limits and axes precision. +% All non-specified, optional arguments are set to their +% default values. +% +% D1 = [5 3 9 1 2]; +% D2 = [5 8 7 2 9]; +% D3 = [8 2 1 4 6]; +% P = [D1; D2; D3]; +% spider_plot_R2019b(P,... +% 'AxesLimits', [1, 2, 1, 1, 1; 10, 8, 9, 5, 10],... % [min axes limits; max axes limits] +% 'AxesPrecision', [0, 1, 1, 1, 1]); +% +% % Example 3: Set fill option on. The fill transparency can be adjusted. +% +% D1 = [5 3 9 1 2]; +% D2 = [5 8 7 2 9]; +% D3 = [8 2 1 4 6]; +% P = [D1; D2; D3]; +% spider_plot_R2019b(P,... +% 'AxesLabels', {'S1', 'S2', 'S3', 'S4', 'S5'},... +% 'AxesInterval', 2,... +% 'FillOption', 'on',... +% 'FillTransparency', 0.1); +% +% % Example 4: Maximum number of arguments. +% +% D1 = [5 3 9 1 2]; +% D2 = [5 8 7 2 9]; +% D3 = [8 2 1 4 6]; +% P = [D1; D2; D3]; +% spider_plot_R2019b(P,... +% 'AxesLabels', {'S1', 'S2', 'S3', 'S4', 'S5'},... +% 'AxesInterval', 4,... +% 'AxesPrecision', 0,... +% 'AxesDisplay', 'one',... +% 'AxesLimits', [1, 2, 1, 1, 1; 10, 8, 9, 5, 10],... +% 'FillOption', 'on',... +% 'FillTransparency', 0.2,... +% 'Color', [1, 0, 0; 0, 1, 0; 0, 0, 1],... +% 'LineStyle', {'--', '-', '--'},... +% 'LineWidth', [1, 2, 3],... +% 'Marker', {'o', 'd', 's'},... +% 'MarkerSize', [8, 10, 12],... +% 'AxesFont', 'Times New Roman',... +% 'LabelFont', 'Times New Roman',... +% 'AxesFontSize', 12,... +% 'LabelFontSize', 10,... +% 'Direction', 'clockwise',... +% 'AxesDirection', {'reverse', 'normal', 'normal', 'normal', 'normal'},... +% 'AxesLabelsOffset', 0.1,... +% 'AxesScaling', 'linear',... +% 'AxesColor', [0.6, 0.6, 0.6],... +% 'AxesLabelsEdge', 'none',... +% 'AxesOffset', 1); +% +% % Example 5: Excel-like radar charts. +% +% D1 = [5 0 3 4 4]; +% D2 = [2 1 5 5 4]; +% P = [D1; D2]; +% spider_plot_R2019b(P,... +% 'AxesInterval', 5,... +% 'AxesPrecision', 0,... +% 'AxesDisplay', 'one',... +% 'AxesLimits', [0, 0, 0, 0, 0; 5, 5, 5, 5, 5],... +% 'FillOption', 'on',... +% 'FillTransparency', 0.1,... +% 'Color', [139, 0, 0; 240, 128, 128]/255,... +% 'LineWidth', 4,... +% 'Marker', 'none',... +% 'AxesFontSize', 14,... +% 'LabelFontSize', 10,... +% 'AxesColor', [0.8, 0.8, 0.8],... +% 'AxesLabelsEdge', 'none'); +% title('Excel-like Radar Chart',... +% 'FontSize', 14); +% legend_str = {'D1', 'D2'}; +% legend(legend_str, 'Location', 'southoutside'); +% +% % Example 6: Logarithimic scale on specified axes. Axes limits and axes +% intervals can be individually set as well. +% +% D1 = [5 3 9 1 1]; +% D2 = [5 8 7 2 10]; +% D3 = [8 2 1 4 100]; +% P = [D1; D2; D3]; +% spider_plot_R2019b(P,... +% 'AxesInterval', 2,... +% 'AxesPrecision', 0,... +% 'AxesFontSize', 10,... +% 'AxesLabels', {'Linear Scale', 'Linear Scale', 'Linear Scale', 'Linear Scale', 'Logarithimic Scale'},... +% 'AxesScaling', {'linear', 'linear', 'linear', 'linear', 'log'},... +% 'AxesLimits', [1, 1, 1, 1, 1; 10, 10, 10, 10, 100]); +% legend('D1', 'D2', 'D3', 'Location', 'northeast'); +% +% % Example 7: Spider plot with tiledlayout feature in R2019b. +% +% D1 = [5 3 9 1 2]; +% D2 = [5 8 7 2 9]; +% D3 = [8 2 1 4 6]; +% P = [D1; D2; D3]; +% t = tiledlayout(2, 2); +% nexttile; +% spider_plot_R2019b(P,... +% 'AxesInterval', 1,... +% 'AxesPrecision', 0); +% nexttile; +% spider_plot_R2019b(P,... +% 'AxesInterval', 1,... +% 'AxesPrecision', 0); +% nexttile(3, [1, 2]); +% spider_plot_R2019b(P,... +% 'AxesInterval', 1,... +% 'AxesPrecision', 0); +% t.TileSpacing = 'compact'; +% t.Padding = 'compact'; +% title(t, 'Spider Plots'); +% +% Author: +% Moses Yoo, (jyoo at hatci dot com) +% 2020-12-01: Added support for adjust the axes offset from origin. +% 2020-11-30: Allow for one data group without specified axes limits. +% 2020-11-30: Added support for changing axes and label font type. +% 2020-11-06: Fix bug in reverse axes direction feature. +% 2020-10-08: Adjust axes precision to be set to one or more axis. +% 2020-09-30: -Updated examples. +% -Added feature to change spider axes and axes labels edge color. +% -Allow logarithmic scale to be set to one or more axis. +% -Added feature to allow different line styles, line width, +% marker type, and marker sizes for the data groups. +% -Allow ability to reverse axes direction. +% 2020-02-12: Fixed condition and added error checking for when only one +% data group is plotted. +% 2020-01-27: Corrected bug where only 7 entries were allowed in legend. +% 2020-01-06: Added support for tiledlayout feature introduced in R2019b. +% 2019-11-27: Add option to change axes to logarithmic scale. +% 2019-11-15: Add feature to customize the plot rotational direction and +% the offset position of the axis labels. +% 2019-10-28: Major revision in implementing the new function argument +% validation feature introduced in R2019b. Replaced previous +% method of error checking and setting of default values. +% 2019-10-23: Minor revision to set starting axes as the vertical line. +% Add customization option for font sizes and axes display. +% 2019-10-16: Minor revision to add name-value pairs for customizing +% color, Marker, and line settings. +% 2019-10-08: Another major revision to convert to name-value pairs and +% add color fill option. +% 2019-09-17: Major revision to improve speed, clarity, and functionality +% +% Special Thanks: +% Special thanks to Gabriela Andrade, Andrés Garcia, Jiro Doke, +% Alex Grenyer, Omar Hadri, Zafar Ali, Christophe Hurlin, Roman, +% Mariusz Sepczuk, Mohamed Abubakr, Nicolai, Jingwei Too, +% Cedric Jamet & Richard Ruff for their feature recommendations +% and suggested bug fixes. + +%%% Argument Validation %%% +arguments + P (:, :) double + options.AxesLabels {validateAxesLabels(options.AxesLabels, P)} = cellstr("Label " + (1:size(P, 2))) + options.AxesInterval (1, 1) double {mustBeInteger, mustBePositive} = 3 + options.AxesPrecision (:, :) double {mustBeInteger, mustBeNonnegative} = 1 + options.AxesDisplay char {mustBeMember(options.AxesDisplay, {'all', 'none', 'one'})} = 'all' + options.AxesLimits double {validateAxesLimits(options.AxesLimits, P)} = [] + options.FillOption char {mustBeMember(options.FillOption, {'off', 'on'})} = 'off' + options.FillTransparency (1, 1) double {mustBeGreaterThanOrEqual(options.FillTransparency, 0), mustBeLessThanOrEqual(options.FillTransparency, 1)} = 0.1 + options.Color = get(groot,'defaultAxesColorOrder') + options.LineStyle = '-' + options.LineWidth (:, :) double {mustBePositive} = 2 + options.Marker = 'o' + options.MarkerSize (:, :) double {mustBePositive} = 8 + options.AxesFont char = 'Helvetica' + options.LabelFont char = 'Helvetica' + options.AxesFontSize (1, 1) double {mustBePositive} = 10 + options.LabelFontSize (1, 1) double {mustBePositive} = 10 + options.Direction char {mustBeMember(options.Direction, {'counterclockwise', 'clockwise'})} = 'clockwise' + options.AxesDirection = 'normal' + options.AxesLabelsOffset (1, 1) double {mustBeNonnegative} = 0.1 + options.AxesScaling = 'linear' + options.AxesColor = [0.6, 0.6, 0.6] + options.AxesLabelsEdge = 'k' + options.AxesOffset (1, 1) double {mustBeNonnegative, mustBeInteger} = 1 +end + +%%% Data Properties %%% +% Point properties +[num_data_groups, num_data_points] = size(P); + +%%% Validate Properties %%% +% Check if axes offset is valid +if options.AxesOffset > options.AxesInterval + error('Error: Invalid axes offset entry. Please enter in an integer value that is between [0, axes_interval].'); +end + +%%% Validate Axes Precision +% Check if axes precision is numeric +if isnumeric(options.AxesPrecision) + % Check is length is one + if length(options.AxesPrecision) == 1 + % Repeat array to number of data points + options.AxesPrecision = repmat(options.AxesPrecision, num_data_points, 1); + elseif length(options.AxesPrecision) ~= num_data_points + error('Error: Please specify the same number of axes precision as number of data points.'); + end +else + error('Error: Please make sure the axes precision is a numeric value.'); +end + +%%% Validate Line Style +% Check if line style is a char +if ischar(options.LineStyle) + % Convert to cell array of char + options.LineStyle = cellstr(options.LineStyle); + + % Repeat cell to number of data groups + options.LineStyle = repmat(options.LineStyle, num_data_groups, 1); +elseif iscellstr(options.LineStyle) %#ok<*ISCLSTR> + % Check is length is one + if length(options.LineStyle) == 1 + % Repeat cell to number of data groups + options.LineStyle = repmat(options.LineStyle, num_data_groups, 1); + elseif length(options.LineStyle) ~= num_data_groups + error('Error: Please specify the same number of line styles as number of data groups.'); + end +else + error('Error: Please make sure the line style is a char or a cell array of char.'); +end + +%%% Validate Line Width +% Check if line width is numeric +if isnumeric(options.LineWidth) + % Check is length is one + if length(options.LineWidth) == 1 + % Repeat array to number of data groups + options.LineWidth = repmat(options.LineWidth, num_data_groups, 1); + elseif length(options.LineWidth) ~= num_data_groups + error('Error: Please specify the same number of line width as number of data groups.'); + end +else + error('Error: Please make sure the line width is a numeric value.'); +end + +%%% Validate Marker +% Check if marker type is a char +if ischar(options.Marker) + % Convert to cell array of char + options.Marker = cellstr(options.Marker); + + % Repeat cell to number of data groups + options.Marker = repmat(options.Marker, num_data_groups, 1); +elseif iscellstr(options.Marker) + % Check is length is one + if length(options.Marker) == 1 + % Repeat cell to number of data groups + options.Marker = repmat(options.Marker, num_data_groups, 1); + elseif length(options.Marker) ~= num_data_groups + error('Error: Please specify the same number of line styles as number of data groups.'); + end +else + error('Error: Please make sure the line style is a char or a cell array of char.'); +end + +%%% Validate Marker Size +% Check if line width is numeric +if isnumeric(options.MarkerSize) + if length(options.MarkerSize) == 1 + % Repeat array to number of data groups + options.MarkerSize = repmat(options.MarkerSize, num_data_groups, 1); + elseif length(options.MarkerSize) ~= num_data_groups + error('Error: Please specify the same number of line width as number of data groups.'); + end +else + error('Error: Please make sure the line width is numeric.'); +end + +%%% Validate Axes Scaling +% Check if axes scaling is valid +if any(~ismember(options.AxesScaling, {'linear', 'log'})) + error('Error: Invalid axes scaling entry. Please enter in "linear" or "log" to set axes scaling.'); +end + +% Check if axes scaling is a cell +if iscell(options.AxesScaling) + % Check is length is one + if length(options.AxesScaling) == 1 + % Repeat array to number of data groups + options.AxesScaling = repmat(options.AxesScaling, num_data_points, 1); + elseif length(options.AxesScaling) ~= num_data_points + error('Error: Please specify the same number of axes scaling as number of data points.'); + end +else + % Repeat array to number of data groups + options.AxesScaling = repmat({options.AxesScaling}, num_data_points, 1); +end + +%%% Validate Axes Direction +% Check if axes direction is a cell +if iscell(options.AxesDirection) + % Check is length is one + if length(options.AxesDirection) == 1 + % Repeat array to number of data groups + options.AxesDirection = repmat(options.AxesDirection, num_data_points, 1); + elseif length(options.AxesDirection) ~= num_data_points + error('Error: Please specify the same number of axes direction as number of data points.'); + end +else + % Repeat array to number of data groups + options.AxesDirection = repmat({options.AxesDirection}, num_data_points, 1); +end + +%%% Axes Scaling Properties %%% +% Check axes scaling option +log_index = strcmp(options.AxesScaling, 'log'); + +% If any log scaling is specified +if any(log_index) + % Initialize copy + P_log = P(:, log_index); + + % Logarithm of base 10, account for numbers less than 1 + P_log = sign(P_log) .* log10(abs(P_log)); + + % Minimum and maximun log limits + min_limit = min(min(fix(P_log))); + max_limit = max(max(ceil(P_log))); + recommended_axes_interval = max_limit - min_limit; + + % Warning message + warning('For the log scale values, recommended axes limit is [%i, %i] with an axes interval of %i.',... + 10^min_limit, 10^max_limit, recommended_axes_interval); + + % Replace original + P(:, log_index) = P_log; +end + +%%% Figure Properties %%% +% Grab current figure +fig = gcf; + +% Set figure background +fig.Color = 'white'; + +% Reset axes +cla reset; + +% Current axes handle +ax = gca; + +% Axis limits +hold on; +axis square; +axis([-1, 1, -1, 1] * 1.3); + +% Axis properties +ax.XTickLabel = []; +ax.YTickLabel = []; +ax.XColor = 'none'; +ax.YColor = 'none'; + +% Polar increments +theta_increment = 2*pi/num_data_points; +full_interval = options.AxesInterval+1; +rho_offset = options.AxesOffset/full_interval; + +%%% Scale Data %%% +% Pre-allocation +P_scaled = zeros(size(P)); +axes_range = zeros(3, num_data_points); + +% Check axes scaling option +axes_direction_index = strcmp(options.AxesDirection, 'reverse'); + +% Iterate through number of data points +for ii = 1:num_data_points + % Check for one data group and no axes limits + if num_data_groups == 1 && isempty(options.AxesLimits) + % Group of points + group_points = P(:, :); + else + % Group of points + group_points = P(:, ii); + end + + % Check for log axes scaling option + if log_index(ii) + % Minimum and maximun log limits + min_value = min(fix(group_points)); + max_value = max(ceil(group_points)); + else + % Automatically the range of each group + min_value = min(group_points); + max_value = max(group_points); + end + + % Range of min and max values + range = max_value - min_value; + + % Check if options.AxesLimits is not empty + if ~isempty(options.AxesLimits) + % Check for log axes scaling option + if log_index(ii) + % Logarithm of base 10, account for numbers less than 1 + options.AxesLimits(:, ii) = sign(options.AxesLimits(:, ii)) .* log10(abs(options.AxesLimits(:, ii))); + end + + % Manually set the range of each group + min_value = options.AxesLimits(1, ii); + max_value = options.AxesLimits(2, ii); + range = max_value - min_value; + + % Check if the axes limits are within range of points + if min_value > min(group_points) || max_value < max(group_points) + error('Error: Please make the manually specified axes limits are within range of the data points.'); + end + end + + % Scale points to range from [0, 1] + P_scaled(:, ii) = ((P(:, ii) - min_value) / range); + + % If reverse axes direction is specified + if axes_direction_index(ii) + % Store to array + axes_range(:, ii) = [max_value; min_value; range]; + P_scaled(:, ii) = -(P_scaled(:, ii) - 1); + else + % Store to array + axes_range(:, ii) = [min_value; max_value; range]; + end + + % Add offset of [rho_offset] and scaling factor of [1 - rho_offset] + P_scaled(:, ii) = P_scaled(:, ii) * (1 - rho_offset) + rho_offset; +end + +%%% Polar Axes %%% +% Polar coordinates +rho_increment = 1/full_interval; +rho = 0:rho_increment:1; + +% Check specified direction of rotation +switch options.Direction + case 'counterclockwise' + % Shift by pi/2 to set starting axis the vertical line + theta = (0:theta_increment:2*pi) + (pi/2); + case 'clockwise' + % Shift by pi/2 to set starting axis the vertical line + theta = (0:-theta_increment:-2*pi) + (pi/2); +end + +% Remainder after using a modulus of 2*pi +theta = mod(theta, 2*pi); + +% Iterate through each theta +for ii = 1:length(theta)-1 + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta(ii), rho); + + % Plot webs + h = plot(x_axes, y_axes,... + 'LineWidth', 1.5,... + 'Color', options.AxesColor); + + % Turn off legend annotation + h.Annotation.LegendInformation.IconDisplayStyle = 'off'; +end + +% Iterate through each rho +for ii = 2:length(rho) + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta, rho(ii)); + + % Plot axes + h = plot(x_axes, y_axes,... + 'Color', options.AxesColor); + + % Turn off legend annotation + h.Annotation.LegendInformation.IconDisplayStyle = 'off'; +end + +% Set end index depending on axes display argument +switch options.AxesDisplay + case 'all' + theta_end_index = length(theta)-1; + case 'one' + theta_end_index = 1; + case 'none' + theta_end_index = 0; +end + +% Rho start index and offset interval +rho_start_index = options.AxesOffset+1; +offset_interval = full_interval - options.AxesOffset; + +% Iterate through each theta +for ii = 1:theta_end_index + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta(ii), rho); + + % Iterate through points on isocurve + for jj = rho_start_index:length(rho) + % Axes increment range + min_value = axes_range(1, ii); + range = axes_range(3, ii); + + % If reverse axes direction is specified + if axes_direction_index(ii) + % Axes increment value + axes_value = min_value - (range/offset_interval) * (jj-rho_start_index); + else + % Axes increment value + axes_value = min_value + (range/offset_interval) * (jj-rho_start_index); + end + + % Check for log axes scaling option + if log_index(ii) + % Exponent to the tenth power + axes_value = 10^axes_value; + end + + % Display axes text + text_str = sprintf(sprintf('%%.%if', options.AxesPrecision(ii)), axes_value); + text(x_axes(jj), y_axes(jj), text_str,... + 'Units', 'Data',... + 'Color', 'k',... + 'FontName', options.AxesFont,... + 'FontSize', options.AxesFontSize,... + 'HorizontalAlignment', 'center',... + 'VerticalAlignment', 'middle'); + end +end + +%%% Plot %%% +% Iterate through number of data groups +for ii = 1:num_data_groups + % Convert polar to cartesian coordinates + [x_points, y_points] = pol2cart(theta(1:end-1), P_scaled(ii, :)); + + % Make points circular + x_circular = [x_points, x_points(1)]; + y_circular = [y_points, y_points(1)]; + + % Plot data points + plot(x_circular, y_circular,... + 'LineStyle', options.LineStyle{ii},... + 'Marker', options.Marker{ii},... + 'Color', options.Color(ii, :),... + 'LineWidth', options.LineWidth(ii),... + 'MarkerSize', options.MarkerSize(ii),... + 'MarkerFaceColor', options.Color(ii, :)); + + % Check if fill option is toggled on + if strcmp(options.FillOption, 'on') + % Fill area within polygon + h = patch(x_circular, y_circular, options.Color(ii, :),... + 'EdgeColor', 'none',... + 'FaceAlpha', options.FillTransparency); + + % Turn off legend annotation + h.Annotation.LegendInformation.IconDisplayStyle = 'off'; + end +end + +% Get object type of children +children_type = get(fig.Children, 'Type'); + +% Check if children is titled layout +if strcmp(children_type, 'titledlayout') + % Set handle to axes children + obj = ax.Children; +else + % Set handle to axes + obj = ax; +end + +% Find object handles +text_handles = findobj(obj.Children,... + 'Type', 'Text'); +patch_handles = findobj(obj.Children,... + 'Type', 'Patch'); +isocurve_handles = findobj(obj.Children,... + 'Color', options.AxesColor,... + '-and', 'Type', 'Line'); +plot_handles = findobj(obj.Children, '-not',... + 'Color', options.AxesColor,... + '-and', 'Type', 'Line'); + +% Manually set the stack order +uistack(text_handles, 'bottom'); +uistack(plot_handles, 'bottom'); +uistack(patch_handles, 'bottom'); +uistack(isocurve_handles, 'bottom'); + +%%% Labels %%% +% Check labels argument +if ~strcmp(options.AxesLabels, 'none') + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta, rho(end)); + + % Iterate through number of data points + for ii = 1:length(options.AxesLabels) + % Angle of point in radians + theta_point = theta(ii); + + % Find out which quadrant the point is in + if theta_point == 0 + quadrant = 0; + elseif theta_point == pi/2 + quadrant = 1.5; + elseif theta_point == pi + quadrant = 2.5; + elseif theta_point == 3*pi/2 + quadrant = 3.5; + elseif theta_point == 2*pi + quadrant = 0; + elseif theta_point > 0 && theta_point < pi/2 + quadrant = 1; + elseif theta_point > pi/2 && theta_point < pi + quadrant = 2; + elseif theta_point > pi && theta_point < 3*pi/2 + quadrant = 3; + elseif theta_point > 3*pi/2 && theta_point < 2*pi + quadrant = 4; + end + + % Adjust label alignment depending on quadrant + switch quadrant + case 0 + horz_align = 'left'; + vert_align = 'middle'; + x_pos = options.AxesLabelsOffset; + y_pos = 0; + case 1 + horz_align = 'left'; + vert_align = 'bottom'; + x_pos = options.AxesLabelsOffset; + y_pos = options.AxesLabelsOffset; + case 1.5 + horz_align = 'center'; + vert_align = 'bottom'; + x_pos = 0; + y_pos = options.AxesLabelsOffset; + case 2 + horz_align = 'right'; + vert_align = 'bottom'; + x_pos = -options.AxesLabelsOffset; + y_pos = options.AxesLabelsOffset; + case 2.5 + horz_align = 'right'; + vert_align = 'middle'; + x_pos = -options.AxesLabelsOffset; + y_pos = 0; + case 3 + horz_align = 'right'; + vert_align = 'top'; + x_pos = -options.AxesLabelsOffset; + y_pos = -options.AxesLabelsOffset; + case 3.5 + horz_align = 'center'; + vert_align = 'top'; + x_pos = 0; + y_pos = -options.AxesLabelsOffset; + case 4 + horz_align = 'left'; + vert_align = 'top'; + x_pos = options.AxesLabelsOffset; + y_pos = -options.AxesLabelsOffset; + end + + % Display text label + text(x_axes(ii)+x_pos, y_axes(ii)+y_pos, options.AxesLabels{ii},... + 'Units', 'Data',... + 'HorizontalAlignment', horz_align,... + 'VerticalAlignment', vert_align,... + 'EdgeColor', options.AxesLabelsEdge,... + 'BackgroundColor', 'w',... + 'FontName', options.LabelFont,... + 'FontSize', options.LabelFontSize); + end +end +end + +%%% Custom Validation Functions %%% +% Validate axes labels +function validateAxesLabels(axes_labels, P) +if ~isequal(axes_labels, 'none') + validateattributes(axes_labels, {'cell'}, {'size', [1, size(P, 2)]}, mfilename, 'axes_labels') +end +end + +% Validate axes limits +function validateAxesLimits(axes_limits, P) +if ~isempty(axes_limits) + validateattributes(axes_limits, {'double'}, {'size', [2, size(P, 2)]}, mfilename, 'axes_limits') + + % Lower and upper limits + lower_limits = axes_limits(1, :); + upper_limits = axes_limits(2, :); + + % Difference in upper and lower limits + diff_limits = upper_limits - lower_limits; + + % Check to make sure upper limit is greater than lower limit + if any(diff_limits < 0) + error('Error: Please make sure max axes limits are greater than the min axes limits.'); + end + + % Check the range of axes limits + if any(diff_limits == 0) + error('Error: Please make sure the min and max axes limits are different.'); + end +end +end \ No newline at end of file diff --git a/Add-Ons/spider_plot_R2019b_examples.mlx b/Add-Ons/spider_plot_R2019b_examples.mlx new file mode 100644 index 0000000..69aaafa Binary files /dev/null and b/Add-Ons/spider_plot_R2019b_examples.mlx differ diff --git a/Add-Ons/spider_plot_class.m b/Add-Ons/spider_plot_class.m new file mode 100644 index 0000000..a536219 --- /dev/null +++ b/Add-Ons/spider_plot_class.m @@ -0,0 +1,1279 @@ +classdef spider_plot_class < matlab.graphics.chartcontainer.ChartContainer & ... + matlab.graphics.chartcontainer.mixin.Legend + %spider_plot_class Create a spider or radar plot with individual axes. + % + % Syntax: + % s = spider_plot_class(P) + % s = spider_plot_class(P, Name, Value, ...) + % s = spider_plot_class(parent, ___) + % + % Input Arguments: + % (Required) + % P - The data points used to plot the spider chart. The + % rows are the groups of data and the columns are the + % data points. The axes labels and axes limits are + % automatically generated if not specified. + % [vector | matrix] + % + % Name-Value Pair Arguments: + % (Optional) + % AxesLabels - Used to specify the label each of the axes. + % [auto-generated (default) | array of strings | 'none'] + % + % AxesInterval - Used to change the number of intervals displayed + % between the webs. + % [3 (default) | integer] + % + % AxesPrecision - Used to change the precision level on the value + % displayed on the axes. + % [1 (default) | integer | vector] + % + % AxesDisplay - Used to change the number of axes in which the + % axes text are displayed. 'None' or 'one' can be used + % to simplify the plot appearance for normalized data. + % ['all' (default) | 'none' | 'one'] + % + % AxesLimits - Used to manually set the axes limits. A matrix of + % 2 x size(P, 2). The top row is the minimum axes + % limits and the bottow row is the maximum axes limits. + % [auto-scaled (default) | matrix] + % + % FillOption - Used to toggle color fill option. + % ['off' (default) | 'on'] + % + % FillTransparency - Used to set color fill transparency. + % [0.1 (default) | scalar in range (0, 1)] + % + % Color - Used to specify the line color, specified as an RGB + % triplet. The intensities must be in the range (0, 1). + % [MATLAB Color (default) | RGB triplet] + % + % LineStyle - Used to change the line style of the plots. + % ['-' (default) | '--' | ':' | '-.' | 'none'] + % + % LineWidth - Used to change the line width, where 1 point is + % 1/72 of an inch. + % [0.5 (default) | positive value] + % + % Marker - Used to change the options.Marker symbol of the plots. + % ['o' (default) | 'none' | '*' | 's' | 'd' | ...] + % + % MarkerSize - Used to change the options.Marker size, where 1 point is + % 1/72 of an inch. + % [8 (default) | positive value] + % + % AxesFont - Used to change the font type of the values + % displayed on the axes. + % [Helvetica (default) | supported font name] + % + % LabelFont - Used to change the font type of the labels. + % [Helvetica (default) | supported font name] + % + % AxesFontSize - Used to change the font size of the values + % displayed on the axes. + % [10 (default) | scalar value greater than zero] + % + % LabelFontSize - Used to change the font size of the labels. + % [10 (default) | scalar value greater than zero] + % + % Direction - Used to change the direction of rotation of the + % plotted data and axis labels. + % ['clockwise' (default) | 'counterclockwise'] + % + % AxesDirection - Used to change the direction of axes. + % ['normal' (default) | 'reverse' | cell array of character vectors] + % + % AxesLabelsOffset - Used to adjust the position offset of the axes + % labels. + % [0.1 (default) | positive value] + % + % AxesScaling - Used to change the scaling of the axes. + % ['linear' (default) | 'log' | cell array of character vectors] + % + % AxesColor - Used to change the color of the spider axes. + % [grey (default) | RGB triplet | hexadecimal color code] + % + % AxesLabelsEdge - Used to change the edge color of the axes labels. + % [black (default) | RGB triplet | hexadecimal color code | 'none'] + % + % LegendLabels - Used to add the labels to the legend. + % [cell array of character vectors] + % + % LegendHandle - Used to customize legend settings. + % [legend handle object] + % + % AxesOffset - Used to change to axes offset from the origin. + % [1 (default) | any integer less than the axes interval] + % + % Output Arguments: + % (Optional) + % s - Returns a chart class object. These are unique + % identifiers, which you can use to query and + % modify properties of the spider chart. + % [chart class object] + % + % Examples: + % % Example 1: Minimal number of arguments. All non-specified, optional + % arguments are set to their default values. Axes labels + % and limits are automatically generated and set. + % + % D1 = [5 3 9 1 2]; + % D2 = [5 8 7 2 9]; + % D3 = [8 2 1 4 6]; + % P = [D1; D2; D3]; + % if exist('s', 'var') + % delete(s); + % end + % s = spider_plot_class(P); + % s.LegendLabels = {'D1', 'D2', 'D3'}; + % s.LegendHandle.Location = 'southoutside'; + % + % % Example 2: Manually setting the axes limits and axes precision. + % All non-specified, optional arguments are set to their + % default values. + % + % D1 = [5 3 9 1 2]; + % D2 = [5 8 7 2 9]; + % D3 = [8 2 1 4 6]; + % P = [D1; D2; D3]; + % if exist('s', 'var') + % delete(s); + % end + % s = spider_plot_class(P); + % s.AxesLimits = [1, 2, 1, 1, 1; 10, 8, 9, 5, 10]; % [min axes limits; max axes limits] + % s.AxesPrecision = [0, 1, 1, 1, 1]; + % + % % Example 3: Set fill option on. The fill transparency can be adjusted. + % + % D1 = [5 3 9 1 2]; + % D2 = [5 8 7 2 9]; + % D3 = [8 2 1 4 6]; + % P = [D1; D2; D3]; + % if exist('s', 'var') + % delete(s); + % end + % s = spider_plot_class(P); + % s.AxesLabels = {'S1', 'S2', 'S3', 'S4', 'S5'}; + % s.AxesInterval = 2; + % s.FillOption = 'on'; + % s.FillTransparency = 0.1; + % + % % Example 4: Maximum number of arguments. + % + % D1 = [5 3 9 1 2]; + % D2 = [5 8 7 2 9]; + % D3 = [8 2 1 4 6]; + % P = [D1; D2; D3]; + % if exist('s', 'var') + % delete(s); + % end + % s = spider_plot_class(P); + % s.AxesLabels = {'S1', 'S2', 'S3', 'S4', 'S5'}; + % s.AxesInterval = 4; + % s.AxesPrecision = 0; + % s.AxesDisplay = 'one'; + % s.AxesLimits = [1, 2, 1, 1, 1; 10, 8, 9, 5, 10]; + % s.FillOption = 'on'; + % s.FillTransparency = 0.2; + % s.Color = [1, 0, 0; 0, 1, 0; 0, 0, 1]; + % s.LineStyle = '--'; + % s.LineWidth = 3; + % s.Marker = 'd'; + % s.MarkerSize = 10; + % s.AxesFont = 'Times New Roman'; + % s.LabelFont = 'Times New Roman'; + % s.AxesFontSize = 12; + % s.LabelFontSize = 10; + % s.Direction = 'clockwise'; + % s.AxesDirection = {'reverse', 'normal', 'normal', 'normal', 'normal'}; + % s.AxesLabelsOffset = 0; + % s.AxesScaling = 'linear'; + % s.AxesOffset = 1; + % s.LegendLabels = {'D1', 'D2', 'D3'}; + % s.LegendHandle.Location = 'northeastoutside'; + % + % % Example 5: Excel-like radar charts. + % + % D1 = [5 0 3 4 4]; + % D2 = [2 1 5 5 4]; + % P = [D1; D2]; + % if exist('s', 'var') + % delete(s); + % end + % s = spider_plot_class(P); + % s.AxesInterval = 5; + % s.AxesPrecision = 0; + % s.AxesDisplay = 'one'; + % s.AxesLimits = [0, 0, 0, 0, 0; 5, 5, 5, 5, 5]; + % s.FillOption = 'on'; + % s.FillTransparency = 0.1; + % s.Color = [139, 0, 0; 240, 128, 128]/255; + % s.LineWidth = 4; + % s.Marker = 'none'; + % s.AxesFontSize = 14; + % s.LabelFontSize = 10; + % title('Excel-like Radar Chart',... + % 'FontSize', 14); + % s.LegendLabels = {'D1', 'D2'}; + % + % % Example 6: Logarithimic scale on all axes. Axes limits and axes + % intervals are automatically set to factors of 10. + % + % D1 = [5 3 9 1 1]; + % D2 = [5 8 7 2 10]; + % D3 = [8 2 1 4 100]; + % P = [D1; D2; D3]; + % if exist('s', 'var') + % delete(s); + % end + % s = spider_plot_class(P); + % s.AxesInterval = 2; + % s.AxesPrecision = 0; + % s.AxesFontSize = 10; + % s.AxesLabels = {'Linear Scale', 'Linear Scale', 'Linear Scale', 'Linear Scale', 'Logarithimic Scale'}; + % s.AxesScaling = {'linear', 'linear', 'linear', 'linear', 'log'}; + % s.AxesLimits = [1, 1, 1, 1, 1; 10, 10, 10, 10, 100]; + % s.LegendLabels = {'D1', 'D2', 'D3'}; + % + % Author: + % Moses Yoo, (jyoo at hatci dot com) + % 2020-12-01: Added support for adjust the axes offset from origin. + % 2020-11-30: Allow for one data group without specified axes limits. + % 2020-11-30: Added support for changing axes and label font type. + % 2020-11-06: Fix bug in reverse axes direction feature. + % 2020-10-08: Adjust axes precision to be set to one or more axis. + % 2020-10-01: Fix legend feature with inherited legend class. + % 2020-09-30: -Fix axes limit bug. Updated examples. + % -Added feature to change spider axes and axes labels edge color. + % -Allow logarithmic scale to be set to one or more axis. + % -Added feature to allow different line styles, line width, + % marker type, and marker sizes for the data groups. + % -Allow ability to reverse axes direction. + % 2020-02-17: Major revision in converting the function into a custom + % chart class. New feature introduced in R2019b. + % 2020-02-12: Fixed condition and added error checking for when only one + % data group is plotted. + % 2020-01-27: Corrected bug where only 7 entries were allowed in legend. + % 2020-01-06: Added support for tiledlayout feature introduced in R2019b. + % 2019-11-27: Add option to change axes to logarithmic scale. + % 2019-11-15: Add feature to customize the plot rotational direction and + % the offset position of the axis labels. + % 2019-10-28: Major revision in implementing the new function argument + % validation feature introduced in R2019b. Replaced previous + % method of error checking and setting of default values. + % 2019-10-23: Minor revision to set starting axes as the vertical line. + % Add customization option for font sizes and axes display. + % 2019-10-16: Minor revision to add name-value pairs for customizing + % color, Marker, and line settings. + % 2019-10-08: Another major revision to convert to name-value pairs and + % add color fill option. + % 2019-09-17: Major revision to improve speed, clarity, and functionality + % + % Special Thanks: + % Special thanks to Gabriela Andrade, Andrés Garcia, Alex Grenyer, + % Omar Hadri, Zafar Ali, Christophe Hurlin, Roman, Mariusz Sepczuk, + % Mohamed Abubakr, Maruis Mueller, Nicolai, Jingwei Too, + % Cedric Jamet & Richard Ruff for their feature recommendations + % and bug finds. A huge thanks to Jiro Doke and Sean de Wolski for + % demonstrating the implementation of argument validation and custom chart + % class introduced in R2019b. + + %%% Public, SetObservable Properties %%% + properties(Access = public, SetObservable) + % Property validation and defaults + P (:, :) double + AxesLabels cell % Axes labels + LegendLabels cell % Legend labels + LegendHandle % Lengend handle + AxesInterval (1, 1) double {mustBeInteger, mustBePositive} = 3 % Number of axes grid lines + AxesPrecision (:, :) double {mustBeInteger, mustBeNonnegative} = 1 % Tick precision + AxesDisplay char {mustBeMember(AxesDisplay, {'all', 'none', 'one'})} = 'all' % Number of tick label groups shown on axes + AxesLimits double = [] % Axes limits + FillOption matlab.lang.OnOffSwitchState = 'off' % Whether to shade data + FillTransparency (1, 1) double {mustBeGreaterThanOrEqual(FillTransparency, 0), mustBeLessThanOrEqual(FillTransparency, 1)} % Shading alpha + Color = get(groot,'defaultAxesColorOrder') % Color order + LineStyle = '-' % Data line style + LineWidth (:, :) double {mustBePositive} = 2 % Data line width + Marker = 'o' % Data marker + MarkerSize (:, :) double {mustBePositive} = 8 % Data marker size + AxesFont char ='Helvetica' % Axes tick font type + LabelFont char = 'Helvetica' % Label font type + AxesFontSize (1, 1) double {mustBePositive} = 10 % Axes tick font size + LabelFontSize (1, 1) double {mustBePositive} = 10 % Label font size + Direction char {mustBeMember(Direction, {'counterclockwise', 'clockwise'})} = 'clockwise' + AxesDirection = 'normal' + AxesLabelsOffset (1, 1) double {mustBeNonnegative} = 0.1 % Offset position of axes labels + AxesScaling = 'linear' % Scaling of axes + AxesColor = [0.6, 0.6, 0.6] % Axes color + AxesLabelsEdge = 'k' % Axes label color + AxesOffset (1, 1) double {mustBeNonnegative, mustBeInteger} = 1 % Axes offset + end + + %%% Private, NonCopyable, Transient Properties %%% + properties(Access = private, NonCopyable, Transient) + % Data line object + DataLines = gobjects(0) + + % Background web object + ThetaAxesLines = gobjects(0) + RhoAxesLines = gobjects(0) + + % Fill shade object + FillPatches = gobjects(0) + + % Web axes tick values + AxesValues = []; + + % Axes label object + AxesTextLabels = gobjects(0) + AxesTickLabels = gobjects(0) + + % Initialize toggle state + InitializeToggle = true; + end + + %%% Protected, Dependent, Hidden Properties %%% + properties(Access = protected, Dependent, Hidden) + NumDataGroups + NumDataPoints + end + + methods + %%% Constructor Methods %%% + function obj = spider_plot_class(parentOrP, varargin) + % Validate number of input arguments + narginchk(1, inf); + + % Check if first argument is a graphic object or data + if isa(parentOrP, 'matlab.graphics.Graphics') + % spider_plot_class(parent, P, Name, Value, ...) + args = [{parentOrP, 'P'}, varargin]; + else + % spider_plot_class(P, Name, Value, ...) + args = [{'P', parentOrP}, varargin]; + end + + % Call superclass constructor method + obj@matlab.graphics.chartcontainer.ChartContainer(args{:}); + end + + %%% Set Methods %%% + function set.P(obj, value) + % Set property + obj.P = value; + + % Toggle re-initialize to true if P was changed + obj.InitializeToggle = true; %#ok<*MCSUP> + end + + function set.AxesLabels(obj, value) + % Validate axes labels + validateAxesLabels(value, obj.P); + + % Set property + obj.AxesLabels = value; + + % Toggle re-initialize to true if AxesLabels was changed + obj.InitializeToggle = true; + end + + function set.LegendLabels(obj, value) + % Validate legend labels + validateLegendLabels(value, obj.P); + + % Set property + obj.LegendLabels = value; + obj.LegendVisible = 'on'; + + % Set legend handle + obj.LegendHandle = getLegend(obj); + + % Toggle re-initialize to true iLegendLabels was changed + obj.InitializeToggle = true; + end + + function set.AxesInterval(obj, value) + % Set property + obj.AxesInterval = value; + + % Toggle re-initialize to true if AxesInterval was changed + obj.InitializeToggle = true; + end + + function set.AxesPrecision(obj, value) + % Set property + obj.AxesPrecision = value; + + % Toggle re-initialize to true if AxesPrecision was changed + obj.InitializeToggle = true; + end + + function set.AxesDisplay(obj, value) + % Set property + obj.AxesDisplay = value; + + % Toggle re-initialize to true if AxesDisplay was changed + obj.InitializeToggle = true; + end + + function set.AxesLimits(obj, value) + % Set property + obj.AxesLimits = value; + + % Toggle re-initialize to true if AxesLimits was changed + obj.InitializeToggle = true; + end + + function set.FillOption(obj, value) + % Set property + obj.FillOption = value; + + % Toggle re-initialize to true if FillOption was changed + obj.InitializeToggle = true; + end + + function set.FillTransparency(obj, value) + % Set property + obj.FillTransparency = value; + + % Toggle re-initialize to true if FillTransparency was changed + obj.InitializeToggle = true; + end + + function set.Color(obj, value) + % Set property + obj.Color = value; + + % Toggle re-initialize to true if Color was changed + obj.InitializeToggle = true; + end + + function set.LineStyle(obj, value) + % Set property + obj.LineStyle = value; + + % Toggle re-initialize to true if LineStyle was changed + obj.InitializeToggle = true; + end + + function set.LineWidth(obj, value) + % Set property + obj.LineWidth = value; + + % Toggle re-initialize to true if LineWidth was changed + obj.InitializeToggle = true; + end + + function set.Marker(obj, value) + % Set property + obj.Marker = value; + + % Toggle re-initialize to true if Marker was changed + obj.InitializeToggle = true; + end + + function set.MarkerSize(obj, value) + % Set property + obj.MarkerSize = value; + + % Toggle re-initialize to true if MarkerSize was changed + obj.InitializeToggle = true; + end + + function set.AxesFont(obj, value) + % Set property + obj.AxesFont = value; + + % Toggle re-initialize to true if AxesFont was changed + obj.InitializeToggle = true; + end + + function set.LabelFont(obj, value) + % Set property + obj.LabelFont = value; + + % Toggle re-initialize to true if LabelFont was changed + obj.InitializeToggle = true; + end + + function set.AxesFontSize(obj, value) + % Set property + obj.AxesFontSize = value; + + % Toggle re-initialize to true if AxesFontSize was changed + obj.InitializeToggle = true; + end + + function set.LabelFontSize(obj, value) + % Set property + obj.LabelFontSize = value; + + % Toggle re-initialize to true if LabelFontSize was changed + obj.InitializeToggle = true; + end + + function set.Direction(obj, value) + % Set property + obj.Direction = value; + + % Toggle re-initialize to true if Direction was changed + obj.InitializeToggle = true; + end + + function set.AxesDirection(obj, value) + % Set property + obj.AxesDirection = value; + + % Toggle re-initialize to true if Direction was changed + obj.InitializeToggle = true; + end + + function set.AxesLabelsOffset(obj, value) + % Set property + obj.AxesLabelsOffset = value; + + % Toggle re-initialize to true if AxesLabelsOffset was changed + obj.InitializeToggle = true; + end + + function set.AxesScaling(obj, value) + % Set property + obj.AxesScaling = value; + + % Toggle re-initialize to true if AxesScaling was changed + obj.InitializeToggle = true; + end + + function set.AxesColor(obj, value) + % Set property + obj.AxesColor = value; + + % Toggle re-initialize to true if AxesColor was changed + obj.InitializeToggle = true; + end + + function set.AxesLabelsEdge(obj, value) + % Set property + obj.AxesLabelsEdge = value; + + % Toggle re-initialize to true if AxesLabelsEdge was changed + obj.InitializeToggle = true; + end + + function set.AxesOffset(obj, value) + % Set property + obj.AxesOffset = value; + + % Toggle re-initialize to true if AxesOffset was changed + obj.InitializeToggle = true; + end + + %%% Get Methods %%% + function num_data_points = get.NumDataPoints(obj) + % Get number of data points + num_data_points = size(obj.P, 2); + end + + function num_data_groups = get.NumDataGroups(obj) + % Get number of data groups + num_data_groups = size(obj.P, 1); + end + + function axes_labels = get.AxesLabels(obj) + % Check if value is empty + if isempty(obj.AxesLabels) + % Set axes labels + axes_labels = cellstr("Label " + (1:obj.NumDataPoints)); + else + % Keep axes labels + axes_labels = obj.AxesLabels; + end + end + + function legend_labels = get.LegendLabels(obj) + % Check if value is empty + if isempty(obj.LegendLabels) + % Set legend labels + legend_labels = cellstr("Data " + (1:obj.NumDataGroups)); + else + % Keep legend labels + legend_labels = obj.LegendLabels; + end + end + + function color = get.Color(obj) + % Check if value is empty + if isempty(obj.Color) + % Set color order + color = lines(obj.NumDataGroups); + else + % Keep color order + color = obj.Color; + end + end + + function axes_limits = get.AxesLimits(obj) + % Validate axes limits + validateAxesLimits(obj.AxesLimits, obj.P); + + % Get property + axes_limits = obj.AxesLimits; + end + + function axes_precision = get.AxesPrecision(obj) + % Check if axes precision is numeric + if isnumeric(obj.AxesPrecision) + % Check is length is one + if length(obj.AxesPrecision) == 1 + % Repeat array to number of data points + obj.AxesPrecision = repmat(obj.AxesPrecision, obj.NumDataPoints, 1); + elseif length(obj.AxesPrecision) ~= obj.NumDataPoints + error('Error: Please specify the same number of axes precision as number of data points.'); + end + else + error('Error: Please make sure the axes precision is a numeric value.'); + end + + % Get property + axes_precision = obj.AxesPrecision; + end + + function axes_scaling = get.AxesScaling(obj) + % Check if axes scaling is valid + if any(~ismember(obj.AxesScaling, {'linear', 'log'})) + error('Error: Invalid axes scaling entry. Please enter in "linear" or "log" to set axes scaling.'); + end + + % Check if axes scaling is a cell + if iscell(obj.AxesScaling) + % Check is length is one + if length(obj.AxesScaling) == 1 + % Repeat array to number of data groups + obj.AxesScaling = repmat(obj.AxesScaling, obj.NumDataPoints, 1); + elseif length(obj.AxesScaling) ~= obj.NumDataPoints + error('Error: Please specify the same number of axes scaling as number of data points.'); + end + else + % Repeat array to number of data groups + obj.AxesScaling = repmat({obj.AxesScaling}, obj.NumDataPoints, 1); + end + + % Get property + axes_scaling = obj.AxesScaling; + end + + function line_style = get.LineStyle(obj) + % Check if line style is a char + if ischar(obj.LineStyle) + % Convert to cell array of char + obj.LineStyle = cellstr(obj.LineStyle); + + % Repeat cell to number of data groups + obj.LineStyle = repmat(obj.LineStyle, obj.NumDataGroups, 1); + elseif iscellstr(obj.LineStyle) %#ok<*ISCLSTR> + % Check is length is one + if length(obj.LineStyle) == 1 + % Repeat cell to number of data groups + obj.LineStyle = repmat(obj.LineStyle, obj.NumDataGroups, 1); + elseif length(obj.LineStyle) ~= obj.NumDataGroups + error('Error: Please specify the same number of line styles as number of data groups.'); + end + else + error('Error: Please make sure the line style is a char or a cell array of char.'); + end + + % Get property + line_style = obj.LineStyle; + end + + function line_width = get.LineWidth(obj) + % Check if line width is numeric + if isnumeric(obj.LineWidth) + % Check is length is one + if length(obj.LineWidth) == 1 + % Repeat array to number of data groups + obj.LineWidth = repmat(obj.LineWidth, obj.NumDataGroups, 1); + elseif length(obj.LineWidth) ~= obj.NumDataGroups + error('Error: Please specify the same number of line width as number of data groups.'); + end + else + error('Error: Please make sure the line width is a numeric value.'); + end + + % Get property + line_width = obj.LineWidth; + end + + function marker_style = get.Marker(obj) + % Check if marker type is a char + if ischar(obj.Marker) + % Convert to cell array of char + obj.Marker = cellstr(obj.Marker); + + % Repeat cell to number of data groups + obj.Marker = repmat(obj.Marker, obj.NumDataGroups, 1); + elseif iscellstr(obj.Marker) + % Check is length is one + if length(obj.Marker) == 1 + % Repeat cell to number of data groups + obj.Marker = repmat(obj.Marker, obj.NumDataGroups, 1); + elseif length(obj.Marker) ~= obj.NumDataGroups + error('Error: Please specify the same number of line styles as number of data groups.'); + end + else + error('Error: Please make sure the line style is a char or a cell array of char.'); + end + + % Get property + marker_style = obj.Marker; + end + + function marker_size = get.MarkerSize(obj) + % Check if line width is numeric + if isnumeric(obj.MarkerSize) + if length(obj.MarkerSize) == 1 + % Repeat array to number of data groups + obj.MarkerSize = repmat(obj.MarkerSize, obj.NumDataGroups, 1); + elseif length(obj.MarkerSize) ~= obj.NumDataGroups + error('Error: Please specify the same number of line width as number of data groups.'); + end + else + error('Error: Please make sure the line width is numeric.'); + end + + % Get property + marker_size = obj.MarkerSize; + end + + function axes_direction = get.AxesDirection(obj) + % Check if axes direction is a cell + if iscell(obj.AxesDirection) + % Check is length is one + if length(obj.AxesDirection) == 1 + % Repeat array to number of data groups + obj.AxesDirection = repmat(obj.AxesDirection, obj.NumDataPoints, 1); + elseif length(obj.AxesDirection) ~= obj.NumDataPoints + error('Error: Please specify the same number of axes direction as number of data points.'); + end + else + % Repeat array to number of data groups + obj.AxesDirection = repmat({obj.AxesDirection}, obj.NumDataPoints, 1); + end + + % Get property + axes_direction = obj.AxesDirection; + end + + function axes_offset = get.AxesOffset(obj) + % Check if axes offset is valid + if obj.AxesOffset > obj.AxesInterval + error('Error: Invalid axes offset entry. Please enter in an integer value that is between [0, axes_interval].'); + end + + % Get property + axes_offset = obj.AxesOffset; + end + end + + methods (Access = public) + function title(obj, title_text, varargin) + % Get axes and title handles + ax = getAxes(obj); + tlt = ax.Title; + + % Set title string + tlt.String = title_text; + + % Initialze name-value arguments + name_arguments = varargin(1:2:end); + value_arguments = varargin(2:2:end); + + % Iterate through name-value arguments + for ii = 1:length(name_arguments) + % Set name value pair + name = name_arguments{ii}; + value = value_arguments{ii}; + tlt.(name) = value; + end + end + end + + methods (Access = protected) + %%% Setup Methods %%% + function setup(obj) + % Figure properties + fig = gcf; + fig.Color = 'w'; + + % Axis properties + ax = getAxes(obj); + hold(ax, 'on'); + axis(ax, 'square'); + axis(ax, 'off'); + axis(ax, [-1, 1, -1, 1] * 1.3); + end + + %%% Update Methods %%% + function update(obj) + % Check re-initialize toggle + if obj.InitializeToggle + % Reset graphic objects + reset_objects(obj); + initialize(obj); + + % Set initialize toggle to false + obj.InitializeToggle = false; + end + + % Update plot appearance + update_plot(obj); + end + + function reset_objects(obj) + % Delete old objects + delete(obj.DataLines) + delete(obj.ThetaAxesLines) + delete(obj.RhoAxesLines) + delete(obj.FillPatches) + delete(obj.AxesTextLabels) + delete(obj.AxesTickLabels) + + % Reset object with empty objects + obj.DataLines = gobjects(0); + obj.ThetaAxesLines = gobjects(0); + obj.RhoAxesLines = gobjects(0); + obj.FillPatches = gobjects(0); + obj.AxesValues = []; + obj.AxesTextLabels = gobjects(0); + obj.AxesTickLabels = gobjects(0); + end + + function initialize(obj) + % Selected data + P_selected = obj.P; + + % Check axes scaling option + log_index = strcmp(obj.AxesScaling, 'log'); + + % If any log scaling is specified + if any(log_index) + % Initialize copy + P_log = P_selected(:, log_index); + + % Logarithm of base 10, account for numbers less than 1 + P_log = sign(P_log) .* log10(abs(P_log)); + + % Minimum and maximun log limits + min_limit = min(min(fix(P_log))); + max_limit = max(max(ceil(P_log))); + recommended_axes_interval = max_limit - min_limit; + + % Warning message + warning('For the log scale values, recommended axes limit is [%i, %i] with an axes interval of %i.',... + 10^min_limit, 10^max_limit, recommended_axes_interval); + + % Replace original + P_selected(:, log_index) = P_log; + end + + % Axes handles + ax = getAxes(obj); + + % Polar increments + theta_increment = 2*pi/obj.NumDataPoints; + full_interval = obj.AxesInterval+1; + rho_offset = obj.AxesOffset/full_interval; + + %%% Scale Data %%% + % Pre-allocation + P_scaled = zeros(size(P_selected)); + axes_range = zeros(3, obj.NumDataPoints); + + % Check axes scaling option + axes_direction_index = strcmp(obj.AxesDirection, 'reverse'); + + % Iterate through number of data points + for ii = 1:obj.NumDataPoints + % Check for one data group and no axes limits + if obj.NumDataGroups == 1 && isempty(obj.AxesLimits) + % Group of points + group_points = P_selected(:, :); + else + % Group of points + group_points = P_selected(:, ii); + end + + % Check for log axes scaling option + if log_index(ii) + % Minimum and maximun log limits + min_value = min(fix(group_points)); + max_value = max(ceil(group_points)); + else + % Automatically the range of each group + min_value = min(group_points); + max_value = max(group_points); + end + + % Range of min and max values + range = max_value - min_value; + + % Check if axes_limits is not empty + if ~isempty(obj.AxesLimits) + % Check for log axes scaling option + if log_index(ii) + % Logarithm of base 10, account for numbers less than 1 + obj.AxesLimits(:, ii) = sign(obj.AxesLimits(:, ii)) .* log10(abs(obj.AxesLimits(:, ii))); + end + + % Manually set the range of each group + min_value = obj.AxesLimits(1, ii); + max_value = obj.AxesLimits(2, ii); + range = max_value - min_value; + + % Check if the axes limits are within range of points + if min_value > min(group_points) || max_value < max(group_points) + error('Error: Please make the manually specified axes limits are within range of the data points.'); + end + end + + % Scale points to range from [0, 1] + P_scaled(:, ii) = ((P_selected(:, ii) - min_value) / range); + + % If reverse axes direction is specified + if axes_direction_index(ii) + % Store to array + axes_range(:, ii) = [max_value; min_value; range]; + P_scaled(:, ii) = -(P_scaled(:, ii) - 1); + else + % Store to array + axes_range(:, ii) = [min_value; max_value; range]; + end + + % Add offset of [rho_offset] and scaling factor of [1 - rho_offset] + P_scaled(:, ii) = P_scaled(:, ii) * (1 - rho_offset) + rho_offset; + end + + %%% Polar Axes %%% + % Polar coordinates + rho_increment = 1/full_interval; + rho = 0:rho_increment:1; + + % Check specified direction of rotation + switch obj.Direction + case 'counterclockwise' + % Shift by pi/2 to set starting axis the vertical line + theta = (0:theta_increment:2*pi) + (pi/2); + case 'clockwise' + % Shift by pi/2 to set starting axis the vertical line + theta = (0:-theta_increment:-2*pi) + (pi/2); + end + + % Remainder after using a modulus of 2*pi + theta = mod(theta, 2*pi); + + % Iterate through each theta + for ii = 1:length(theta)-1 + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta(ii), rho); + + % Plot + obj.ThetaAxesLines(ii) = line(ax, x_axes, y_axes,... + 'LineWidth', 1.5, ... + 'Color', obj.AxesColor,... + 'HandleVisibility', 'off'); + end + + % Iterate through each rho + for ii = 2:length(rho) + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta, rho(ii)); + + % Plot + obj.RhoAxesLines(ii-1) = line(ax, x_axes, y_axes,... + 'Color', obj.AxesColor,... + 'HandleVisibility', 'off'); + end + + % Set end index depending on axes display argument + switch obj.AxesDisplay + case 'all' + theta_end_index = length(theta)-1; + case 'one' + theta_end_index = 1; + case 'none' + theta_end_index = 0; + end + + % Rho start index and offset interval + rho_start_index = obj.AxesOffset+1; + offset_interval = full_interval - obj.AxesOffset; + + %%% Plot %%% + % Initialize data children + for ii = 1:obj.NumDataGroups + obj.FillPatches(ii) = patch(nan, nan, nan,... + 'Parent', ax,... + 'EdgeColor', 'none',... + 'HandleVisibility', 'off'); + obj.DataLines(ii) = line(nan, nan,... + 'Parent', ax); + end + + % Iterate through number of data groups + for ii = 1:obj.NumDataGroups + % Convert polar to cartesian coordinates + [x_points, y_points] = pol2cart(theta(1:end-1), P_scaled(ii, :)); + + % Make points circular + x_circular = [x_points, x_points(1)]; + y_circular = [y_points, y_points(1)]; + + % Plot data points + obj.DataLines(ii).XData = x_circular; + obj.DataLines(ii).YData = y_circular; + + % Check if fill option is toggled on + obj.FillPatches(ii).XData = x_circular; + obj.FillPatches(ii).YData = y_circular; + end + + %%% Labels %%% + % Iterate through number of data points + for ii = 1:obj.NumDataPoints + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta, rho(end)); + + % Angle of point in radians + [horz_align, vert_align, x_pos, y_pos] = obj.quadrant_position(theta(ii)); + + % Display text label + obj.AxesTextLabels(ii) = text(ax, x_axes(ii)+x_pos, y_axes(ii)+y_pos, '',... + 'Units', 'Data',... + 'HorizontalAlignment', horz_align,... + 'VerticalAlignment', vert_align,... + 'EdgeColor', obj.AxesLabelsEdge,... + 'BackgroundColor', 'w',... + 'FontName', obj.LabelFont,... + 'FontSize', obj.LabelFontSize,... + 'Visible', 'off'); + end + + % Iterate through each theta + for ii = 1:theta_end_index + % Convert polar to cartesian coordinates + [x_axes, y_axes] = pol2cart(theta(ii), rho); + + % Iterate through points on isocurve + for jj = rho_start_index:length(rho) + % Axes increment value + min_value = axes_range(1, ii); + range = axes_range(3, ii); + + % If reverse axes direction is specified + if axes_direction_index(ii) + % Axes increment value + axes_value = min_value - (range/offset_interval) * (jj-rho_start_index); + else + % Axes increment value + axes_value = min_value + (range/offset_interval) * (jj-rho_start_index); + end + + % Check for log axes scaling option + if log_index(ii) + % Exponent to the tenth power + axes_value = 10^axes_value; + end + + % Display axes text + obj.AxesValues(ii, jj) = axes_value; + obj.AxesTickLabels(ii, jj) = text(ax, x_axes(jj), y_axes(jj), '',... + 'Units', 'Data',... + 'Color', 'k',... + 'FontName', obj.AxesFont,... + 'FontSize', obj.AxesFontSize,... + 'HorizontalAlignment', 'center',... + 'VerticalAlignment', 'middle',... + 'Visible', 'off'); + end + end + + % Keep only valid entries + obj.AxesValues = obj.AxesValues(:, rho_start_index:end); + obj.AxesTickLabels = obj.AxesTickLabels(:, rho_start_index:end); + end + + function update_plot(obj) + % Iterate through patch objects + for ii = 1:numel(obj.FillPatches) + % Check fill option argument + if obj.FillOption + % Fill in patch with specified color and transparency + obj.FillPatches(ii).FaceColor = obj.Color(ii, :); + obj.FillPatches(ii).FaceAlpha = obj.FillTransparency; + else + % Set no patch color + obj.FillPatches(ii).FaceColor = 'none'; + end + end + + % Iterate through data line objects + for ii = 1:numel(obj.DataLines) + % Set line settings + obj.DataLines(ii).LineStyle = obj.LineStyle{ii}; + obj.DataLines(ii).Marker = obj.Marker{ii}; + obj.DataLines(ii).Color = obj.Color(ii, :); + obj.DataLines(ii).LineWidth = obj.LineWidth(ii); + obj.DataLines(ii).MarkerSize = obj.MarkerSize(ii); + obj.DataLines(ii).MarkerFaceColor = obj.Color(ii, :); + obj.DataLines(ii).DisplayName = obj.LegendLabels{ii}; + end + + % Check axes display argument + if isequal(obj.AxesLabels, 'none') + % Set axes text labels to invisible + set(obj.AxesTextLabels, 'Visible', 'off') + else + % Set axes text labels to visible + set(obj.AxesTextLabels, 'Visible', 'on') + + % Iterate through number of data points + for ii = 1:obj.NumDataPoints + % Display text label + obj.AxesTextLabels(ii).String = obj.AxesLabels{ii}; + obj.AxesTextLabels(ii).FontName = obj.LabelFont; + obj.AxesTextLabels(ii).FontSize = obj.LabelFontSize; + obj.AxesTextLabels(ii).EdgeColor = obj.AxesLabelsEdge; + end + end + + % Check axes precision argument + if isequal(obj.AxesPrecision, 'none') + % Set axes tick label invisible + set(obj.AxesTickLabels, 'Visible', 'off') + else + % Set axes tick label visible + set(obj.AxesTickLabels, 'Visible', 'on') + + % Iterate through axes values rows + for ii = 1:size(obj.AxesValues, 1) + % Iterate through axes values columns + for jj = 1:size(obj.AxesValues, 2) + % Display and set axes tick label settings + text_str = sprintf(sprintf('%%.%if', obj.AxesPrecision(ii)), obj.AxesValues(ii, jj)); + obj.AxesTickLabels(ii, jj).String = text_str; + obj.AxesTickLabels(ii, jj).FontName= obj.AxesFont; + obj.AxesTickLabels(ii, jj).FontSize = obj.AxesFontSize; + end + end + end + end + + function [horz_align, vert_align, x_pos, y_pos] = quadrant_position(obj, theta_point) + % Find out which quadrant the point is in + if theta_point == 0 + quadrant = 0; + elseif theta_point == pi/2 + quadrant = 1.5; + elseif theta_point == pi + quadrant = 2.5; + elseif theta_point == 3*pi/2 + quadrant = 3.5; + elseif theta_point == 2*pi + quadrant = 0; + elseif theta_point > 0 && theta_point < pi/2 + quadrant = 1; + elseif theta_point > pi/2 && theta_point < pi + quadrant = 2; + elseif theta_point > pi && theta_point < 3*pi/2 + quadrant = 3; + elseif theta_point > 3*pi/2 && theta_point < 2*pi + quadrant = 4; + end + + % Adjust label alignment depending on quadrant + switch quadrant + case 0 + horz_align = 'left'; + vert_align = 'middle'; + x_pos = obj.AxesLabelsOffset; + y_pos = 0; + case 1 + horz_align = 'left'; + vert_align = 'bottom'; + x_pos = obj.AxesLabelsOffset; + y_pos = obj.AxesLabelsOffset; + case 1.5 + horz_align = 'center'; + vert_align = 'bottom'; + x_pos = 0; + y_pos = obj.AxesLabelsOffset; + case 2 + horz_align = 'right'; + vert_align = 'bottom'; + x_pos = -obj.AxesLabelsOffset; + y_pos = obj.AxesLabelsOffset; + case 2.5 + horz_align = 'right'; + vert_align = 'middle'; + x_pos = -obj.AxesLabelsOffset; + y_pos = 0; + case 3 + horz_align = 'right'; + vert_align = 'top'; + x_pos = -obj.AxesLabelsOffset; + y_pos = -obj.AxesLabelsOffset; + case 3.5 + horz_align = 'center'; + vert_align = 'top'; + x_pos = 0; + y_pos = -obj.AxesLabelsOffset; + case 4 + horz_align = 'left'; + vert_align = 'top'; + x_pos = obj.AxesLabelsOffset; + y_pos = -obj.AxesLabelsOffset; + end + end + + end + +end + +%%% Custom Validation Functions %%% +% Validate axes labels +function validateAxesLabels(axes_labels, P) +if ~isequal(axes_labels, 'none') + validateattributes(axes_labels, {'cell'}, {'size', [1, size(P, 2)]}, mfilename, 'axes_labels') +end +end + +% Validate legend labels +function validateLegendLabels(legend_labels, P) +if ~isequal(legend_labels, 'none') + validateattributes(legend_labels, {'cell'}, {'size', [1, size(P, 1)]}, mfilename, 'legend_labels') +end +end + +% Validate axes limits +function validateAxesLimits(axes_limits, P) +if ~isempty(axes_limits) + validateattributes(axes_limits, {'double'}, {'size', [2, size(P, 2)]}, mfilename, 'axes_limits') + + % Lower and upper limits + lower_limits = axes_limits(1, :); + upper_limits = axes_limits(2, :); + + % Difference in upper and lower limits + diff_limits = upper_limits - lower_limits; + + % Check to make sure upper limit is greater than lower limit + if any(diff_limits < 0) + error('Error: Please make sure max axes limits are greater than the min axes limits.'); + end + + % Check the range of axes limits + if any(diff_limits == 0) + error('Error: Please make sure the min and max axes limits are different.'); + end +end +end \ No newline at end of file diff --git a/Add-Ons/spider_plot_class_examples.mlx b/Add-Ons/spider_plot_class_examples.mlx new file mode 100644 index 0000000..6433a59 Binary files /dev/null and b/Add-Ons/spider_plot_class_examples.mlx differ diff --git a/Add-Ons/spider_plot_examples.mlx b/Add-Ons/spider_plot_examples.mlx new file mode 100644 index 0000000..956151d Binary files /dev/null and b/Add-Ons/spider_plot_examples.mlx differ diff --git a/nappIce/HowTo/Bildschirmfoto 2019-05-08 um 09.58.47.png b/nappIce/HowTo/Bildschirmfoto 2019-05-08 um 09.58.47.png new file mode 100644 index 0000000..3d6e5c1 Binary files /dev/null and b/nappIce/HowTo/Bildschirmfoto 2019-05-08 um 09.58.47.png differ diff --git a/nappIce/HowTo/Bildschirmfoto 2022-03-23 um 08.19.22.png b/nappIce/HowTo/Bildschirmfoto 2022-03-23 um 08.19.22.png new file mode 100644 index 0000000..3074d2f Binary files /dev/null and b/nappIce/HowTo/Bildschirmfoto 2022-03-23 um 08.19.22.png differ diff --git a/nappIce/HowTo/Bildschirmfoto 2022-03-23 um 11.14.44.png b/nappIce/HowTo/Bildschirmfoto 2022-03-23 um 11.14.44.png new file mode 100644 index 0000000..1f758f4 Binary files /dev/null and b/nappIce/HowTo/Bildschirmfoto 2022-03-23 um 11.14.44.png differ diff --git a/nappIce/HowTo/Bildschirmfoto 2022-03-24 um 07.17.54.png b/nappIce/HowTo/Bildschirmfoto 2022-03-24 um 07.17.54.png new file mode 100644 index 0000000..25c8400 Binary files /dev/null and b/nappIce/HowTo/Bildschirmfoto 2022-03-24 um 07.17.54.png differ diff --git a/nappIce/HowTo/TMpnappIceHowToData.mat b/nappIce/HowTo/TMpnappIceHowToData.mat new file mode 100644 index 0000000..0d7c7f2 Binary files /dev/null and b/nappIce/HowTo/TMpnappIceHowToData.mat differ diff --git a/nappIce/HowTo/html/nappIceHowTo.html b/nappIce/HowTo/html/nappIceHowTo.html new file mode 100644 index 0000000..87b62bd --- /dev/null +++ b/nappIce/HowTo/html/nappIceHowTo.html @@ -0,0 +1,1828 @@ + + + + + How to analyse ISS XPS and NEXAFS data using Matlab

How to analyse ISS XPS and NEXAFS data using Matlab

Contents

Introduction: Concept

NEXAFS and XPS data from beam times is imported into a MATLAB table. The table allows to add meta data such as sample temperature, cell pressure, or Scienta settings (pass energy, etc). Further, data from several beam times can be imported and then filtered - for example to process all gas-phase CO2 PE from the last 5 years; or all ice NEXAFS at -10° to -12°C. Functions and the table are organised such that one can always go back to raw data to re-do the analysis or continue with processed data.

The basic idea is that a set of MATLAB functions that import the data of different format and from various sources and that can be used to perform basic XPS and NEXAFS data processing are used, shared, and developed by all group members. This requires common data formats and naming. The scripts/live scripts/functions that are used to call the common MATLAB functions are written, stored, named individually by each user.

+ +

Introduction: Function calls

Most functions need the MATLAB data table as input. The output can be stored in the same data table adding data to the original data table, or in a new one - thus creating a copy. Some functions such as those used for plotting do not write data.

InputTable = nappFunctionAbc(InputTable);
+

This command runs the function nappFunctionAbc on the data table InputTable and writes the results into the same table (with the name InputTable.

The InputTable may hold different data types such as XPS data, NEXAFS, and pictures. Mostly, the functions require one and the same data type as input. The InputTable needs to be filtered when passed to a function (see below). Exceptions from this are the nappGenerateSpectra and nappPlot functions that can be called with some limitations with mixed data as input (including pictures, that are ignored).

OutputTable = nappFunctionAbc(InputTable);
+

This command runs the same function on the data in the table InputTable and writes the results into the data table _OutputTable which is a full copy of InputTable plus the results of the function nappFunctionAbc.

Most functions allow to set a number of optional input parameters, some require additional mandatory input. Please check the documentation of each function for further help:

help nappFunctionAbc
+

The mandatory input comes first in each function call. In the following example the data of the InputTable is passed to the function as well as the variables x and y. The optional function input is given just like in any MATLAB function using parameter descriptions: 'option',setting. Setting can be a text string in quotes, or a variable (array, logical, table, date number, etc). Most common are:

OutputTable = nappFunctionAbc(InputTable,x,y,'tableSelection',tmpDataSelection,'...
+'tableVariable','TableVariable', energyScale','kinetic','mode','mean');
+
  • 'tableSelection': allows to filter the table and run the function only on selected table lines. tmpDataSelection is a logical array, see section Work with data: Filter table in this document.
  • 'tableVariable': allows to choose the data of the data table that the function should work with. See Introduction: Data structure section in this document.
  • 'energyScale': allows to use kinetic or binding energy scale to plot or perform calculation.
  • 'mode': allows to select options for functions such as using mean or sum for calculations, etc.
  • 'showFigures': allows to view or view not figures and function output.

Please consult the help files of each function for a complete list of options.

Introduction: Data structure

It starts with importing the multi-dimensional IgorPro files that the SES software saves or with the h5 file structure that is saved for the NEXAFS data.

  • Upon import of the SES data, region iterations are averaged and counts are normalised to 1 s.
  • NEXAFS data...

The data are then saved in a data table, each file in one row and the data in columns. Columns are called table variables in MATLAB and in the nappFunctions. The data columns are:

  • image: PE data: Intensity in counts-per-second vs. kinetic energy and sequence iteration. Functions that work with image data, overwrite this column.
  • imageRoh: a copy of image at the time of data import.
  • spectrum_countsPerSecond and spectrum_counts: Hold the spectra that are computed from the image. These data columns are modified by nappFunctions that work with spectrum data.
  • spectrumRoh_countsPerSecond and spectrumRoh_counts: a copy of the spectrum data at time of generation.

In other words, the data in the columns spectrum_countsPerSecond, spectrum_counts, image always hold the processed data and are modified by each function call. The Roh data allows to go back and re-do the processing. Next to this the data table stores analyser settings such as scientaEkin and sample parameters such as temperature and pressure. View the data table in the data viewer or command window of MATLAB to see all columns. This data structure allows to process all data and then still plot images, unprocessed data, or processed data of selected experiments.

ToDo

  • add code for intensity vs. time plotting
  • add code for average and plot iterations.
  • get rid of peakfind and replace by gauss fitting
  • use gauss fitting function within functions?
  • Tidy html output, and get Yanisha's feedback
  • Add section on how to modify figures after plotting
  • add section on how to access data in table
  • add section on how to merge data tables
  • Work on code and add section how to remove XPS from NEXAFS
  • Work on code and add section on I0 including 2nd order light
  • Add code to add combined spectra to data table as row.
  • Update help files for NEXAFS functions and NEXAFS options in general functions.
  • Set-up folders for Yanisha

Prepare: Initialise MATLAB

You need to have access to the folder holding the functions and helper files. These are shared via switch drive.

Add the paths to the initializeMatlab function at the end of this script This function needs to be added to the end of each of your scripts or live scripts. Below is an example.

function [myColorMap, PsiFarbe] = initializeMatlab
+%initializeMatlab Sets NappIce specific settings
+%   Adds Napp files to path and defines file locations for mac, windows,
+%   and Matlab online (which runs on unix)
% change working directory
+path = matlab.desktop.editor.getActiveFilename;
+[filepath,~,~] = fileparts(path);
+cd(filepath);
% The fitting routines writes quite a lot of feedback and warnings. I shut them off.
+warning('off','all')
+warning off backtrace
+warning off verbose
% Functions and helper files path:
+if ismac
+   % add Napp files to path
+   addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/Add-Ons');
+   addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/nappIce');
+elseif ispc
+   % add Napp files to path
+   addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/Add-Ons');
+   addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/nappIce');
+elseif isunix
+   % add Napp files to path
+   addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/Add-Ons');
+   addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/nappIce');
+end
% Color maps
+myColorMap.red     = colormap(autumn(7));
+myColorMap.blue    = colormap(winter(7));
% define PSI cooperate identity colours
+PsiFarbe.hellgrau       = [226 226 226]/255;
+PsiFarbe.mittelgrau     = [184 184 184]/255;
+PsiFarbe.dunkelgrau     = [78 78 77]/255;
+PsiFarbe.blaugrau       = [236 236 243]/255; % This is actually not a PSI colour
+PsiFarbe.gelb           = [239 200 37]/255;
+PsiFarbe.hellorange     = [227 164 31]/255;
+PsiFarbe.dunkelorange   = [207 92 22]/255;
+PsiFarbe.hellrot            = [164 36 23]/255;
+PsiFarbe.dunkelbraun    = [114 85 65]/255;
+PsiFarbe.hellbraun      = [127 119 47]/255;
+PsiFarbe.mittelgruen      = [135 150 59]/255;
+PsiFarbe.hellgruen      = [195 214 47]/255;
+PsiFarbe.dunkelgruen    = [72 130 33]/255;
+PsiFarbe.dunkelrot        = [104 47 86]/255;
+PsiFarbe.dunkelblau     = [37 65 108]/255;
+PsiFarbe.mittelgruenblau = [61 164 168]/255;
+PsiFarbe.hellblau         = [58 162 190]/255;
+PsiFarbe.mittelblau       = [50 118 158]/255;
end

The path might be different on your computer depending how you have set up SwitchDrive:

addpath('C:\Users\bletry_c\switchdrive\PSI_Matlab\nappIce');
+addpath('C:\Users\bletry_c\switchdrive\PSI_Matlab\Add-Ons');
+

then run the initialiseMatlab function:

clearvars
+[myColorMap, PsiFarbe] = initializeMatlab;
+close all
+clc
+

Prepare: ISS data structure and path to local copy of ISS data

Data needs to be organised in beam time folders that can be located on the Napp drive or locally on your computer. The data folder naming and structure within the beam time folder (orange on figure) is strict and there must not be any subfolders in the data folders:

+ +

  • NEXAFS holds *.h5 XAS data
  • Photos holds *.bmp pictures
  • Pressure holds the *.dat LabView files
  • SES holds the *.ibw PE data.
  • To run the scripts, there needs to be at least ONE *.ibw file in the SES folder

beam time folder location

  • The beam time folder can be a subfolder of any number of folders.
  • The beam time folder needs to have the same name, same subfolders, and folders above (path) locally and on the NAPP drive. This can be set by the user when calling the import function. As standard, we use "year:YYYY_MM__monthIssIceNapp"
  • on Napp drive: the beam time folder (and folders above) needs to be within the "SC Data" folder
  • locally: the beam time folder (and folders above) needs to be within your "MATLAB home folder:NAPP:SC Data" folder

The see all import options (few examples given below) check out the nappFileList.m help (this works for all nappIce functions):

help nappFileList.m
+

Helper functions

  • Napp_p_ice(T_current) states and plots the vapour pressure of ice between 200-270 K
  • Napp_p_RH(T_current,RH) calculates the partial pressure of water for a given temperature and relative humidity.
  • Napp_RH_p(T_current,partial_pressure_water) calculates the relative humidity for a given temperature and water pressure.

Import ISS data: Complete beam time folder

FileList = nappFileList('2022/2022_02__FebIssIceNapp');
+

This will create a new data table "FileList" overwriting any previous versions of this list with data imported from the local copy of the beam time folder with the name "2022_02__FebIssIceNapp" being a subfolder of the folder "2022".

data read from mat file
+

Import ISS data: Error messages

If you get a message like this in the command window

There appears to be no file in the SES folder. Add at least one file first.
+I quit now

and MATLAB quits running the script, please check that there is at least a *.ibw file in the SES folder

If you instead get a message like this

There is something wrong with the path. Check for typo and that the drives are mounted
+I quit now

and MATLAB quits running the script, please check

  • that there are no typos in the path names
  • that the drives are mounted.

Import ISS data: Add data to existing data table

This will import data from the beam time folder "2021/2021_08__AugIssIceNapp" on the NAPP drive adding the data to the data table "FileList" in the MATLAB workspace

FileList = nappFileList('2021/2021_08__AugIssIceNapp',FileList,'mode','nappDrive');
+

Import ISS data: Add new SES or NEXAFS files from local beam time folder

Using the mode 'localNew' the content of the beam time folder will be compared to that of the FileList in the workspace and only those files not yet imported will be processed. This is a little faster and preserves any changes to the FileList. To prevent data failure of running SES measurements, this only works on the local copy of the beam time folder

FileList = nappFileList('2022/2022_02__FebIssIceNapp',FileList,'mode','localNew');
+

Import ISS data: Choose files manually

This will open a windows file explorer window where you can choose as many data files to be imported as you want. In this example, a new FileList is written, overwriting any previous versions in the workspace.

FileList = nappFileList('2022/2022_02__FebIssIceNapp','mode','nappDrivePick');
+

+ +

Work with data: Excel

The nappFileList.m function also writes a csv file to the beam time folder. Open it as xlsx and use Excels formatting and filtering tools to work with your data set. So, the xlsx file is edited manually and might contain additional information that you have added such as slit settings, comments, type of sample, scope of the measurement, etc. The csv file it automatically generated and might thus be frequently be over-written. Use copy/paste to update the xlsx file with new data, formatting will be automatically applied to new data then.

+ +

Work with data: Add photon energy to table (XPS)

ISS beamline does not log settings of SES data. Photon energy, which is needed to calculate the binding energy later, needs to be added manually. This will read the FileList table and add the photon energy "1000" to the SES data with file numbers 1,8 to 12, and 26 acquired in February (month "2") of the year "2022"). Note, this is only adding to XPS data, NEXAFS data are not touched:

FileList = addPhotonEnergy(FileList,[1,8:12,26],1000,2,2022);
+

Work with data: Add sample description

Sample description to label figures and for filtering data can be added. It does not make sense to use temperature or pressure, as these data are written to the table anyway. It does make sense to use standard phrases to enable filtering all beam time data. This code example follow the same input structure as the addPhotonEnergy function. This function works on both NEXAFS and XPS data. One may limit and select either one specifically by adding either 'NEXAFS' or 'XPS' strings as last input parameter. This is optional, if not specified function runs on both data types:

FileList = addSampleNotes(FileList,[1,8:11],'Sample holder',2,2022,'XPS');
+FileList = addSampleNotes(FileList,[1,8:11],'Sample holder',2,2022,'NEXAFS');
+FileList = addSampleNotes(FileList,[2:7,35:36,56:60],'Ice with N2',2,2022);
+FileList = addSampleNotes(FileList,73:76,'H2O gas-phase',2,2022);
+FileList = addSampleNotes(FileList,73,'H2O gas-phase  (bad data)',2,2022);
+

Work with data: Filter table

An advantage of the data table is filtering. This works with standard MATLAB functions using logical operations. Main motivation of filtering is to work with selected subset of data which for example can be processed with the same settings, fitted with the same constrains, or shall be plotted in one graph for comparison.

Further, the InputTable may hold different data types such as XPS data, NEXAFS, and pictures. Mostly, the functions require one and the same data type as input. Therefore, the InputTable needs to be filtered when passed to most functions. Exceptions from this are the nappGenerateSpectra and nappPlot functions that can be called with some limitations in the settings with mixed data as input (including pictures, that are ignored).

The first example filter CO2 gas-phase C1s PE data that is not "(bad data)" and has a pass energy of 50 eV. In the second example, we pick a C1s or O1s PE data from the SES file #77 from February 2022. Any table column can be used for filtering. "&" means AND "|" is OR.

tmpDataSelection1 = matches(FileList.sample,'CO2 gas-phase') ...
+    & ~contains(FileList.sample,'(bad data)')...
+    & contains(FileList.name,'C1s')...
+    & FileList.scientaPassEnergy_eV == 50 ;
+
tmpDataSelection2 = (contains(FileList.name,'077_C1s') | contains(FileList.name,'077_O1s')) ...
+        (month(FileList.lastModifiedDatenum) == 2) &...
+        (year(FileList.lastModifiedDatenum) == 2022);
+

Work with data: Display filtered table and selected columns

MATLAB tables allow to address the columns by name. To display only the rows that match the filter criteria and only specific columns, code like the examples below can be used:

disp(FileList(tmpDataSelection1,{'name','sample','xRayEkin_eV','scientaPassEnergy_eV','lastModifiedDatestr','sampleTemp_dC',...
+    'cellPressure_mbar' }))
+disp(FileList(tmpDataSelection2,{'name','scientaLensMode','xRayEkinRange_eV','scientaPassEnergy_eV'}))
+
              name                    sample          xRayEkin_eV    scientaPassEnergy_eV      lastModifiedDatestr       sampleTemp_dC    cellPressure_mbar
+    _________________________    _________________    ___________    ____________________    ________________________    _____________    _________________
+
+    {'0077077_C1s_900eV.ibw'}    {'CO2 gas-phase'}      {[900]}               50             {'28-Feb-2022 20:52:12'}       19.966              1.3599     
+    {'0080080_C1s_650eV.ibw'}    {'CO2 gas-phase'}      {[650]}               50             {'28-Feb-2022 20:59:57'}       19.993               1.432     
+    {'0081081_C1s_650eV.ibw'}    {'CO2 gas-phase'}      {[650]}               50             {'28-Feb-2022 21:03:12'}       20.015              1.0105     
+    {'0082082_C1s_900eV.ibw'}    {'CO2 gas-phase'}      {[900]}               50             {'28-Feb-2022 21:07:49'}       19.994             0.99001     
+
+              name               scientaLensMode     xRayEkinRange_eV    scientaPassEnergy_eV
+    _________________________    ________________    ________________    ____________________
+
+    {'0077077_C1s_900eV.ibw'}    {'T_HiPPHAXPES'}       900    900                50         
+    {'0077077_O1s_900eV.ibw'}    {'T_HiPPHAXPES'}       900    900                50         
+
+

Work with data: Modify data in table

There might be bad sweeps (sequence iterations) either with too low signal to noise or because some setting was changed during the run. These can be removed by directly addressing the data in the images. Same procedure, first the data (table row) is filtered, then the image modified for the selected data.

remove one sweep

tmpDataSelection = contains(FileList.name,'077_C1s')& ...
+      (month(FileList.lastModifiedDatenum) == 2) &...
+      (year(FileList.lastModifiedDatenum) == 2022);
+FileList(tmpDataSelection,:).image{:}(:,3)=[];
+
tmpDataSelection = contains(FileList.name,'077_O1s')& ...
+      (month(FileList.lastModifiedDatenum) == 2) &...
+      (year(FileList.lastModifiedDatenum) == 2022);
+FileList(tmpDataSelection,:).image{:}(:,3)=[];
+

remove several sweeps

tmpDataSelection = contains(FileList.name,'059_C1s')& ...
+     (month(FileList.lastModifiedDatenum) == 10) &...
+     (year(FileList.lastModifiedDatenum) == 2021);
+FileList(tmpDataSelection,:).image{:}(:,5:15)=[];
+

remove all data (complete table rows) outside a specific time window

tmpTime.start              = datenum('30-Apr-2019 02:00:00');
+tmpTime.end                = datenum('30-Apr-2019 05:00:00');
+toDelete = Table_FileList.datenum <= tmpTime.start;
+Table_FileList(toDelete,:) = [];
+toDelete = Table_FileList.datenum >= tmpTime.end;
+Table_FileList(toDelete,:) = [];
+

Correct beam line-offset in data

This will correct 1.6 from the X-ray energies, of particular importance for NEXAFS data. One can also do this on selected data.

beamlineOffset = 1.6;
+FileList.xRayEkin_eV      = cellfun(@(x) x+beamlineOffset,FileList.xRayEkin_eV,'UniformOutput',false);
+

Add data (columns) to table

Calculation results for each row can be added to data tables using standard Matlab functions. This example illustrates the use of anonymous functions, their call for each row using cellfun, and the generation of additional columns to which (selection of) the data are written.

fun1        =@(c) interp1(IzeroAugInCell(:,1),IzeroAugInCell(:,2), c);
+fun2        =@(c) interp1(IzeroAugInCell(:,1),IzeroAugInCell(:,3), c);
+tmpMatch    = (month(ListNexafs.lastModifiedDatenum) == 8) &...
+    (year(ListNexafs.lastModifiedDatenum) == 2020) |...
+    (startsWith(ListNexafs.name, 'sum_Aug'));
+ListNexafs.uhvI0(tmpMatch)      = cellfun(fun1, ListNexafs.xRayEkin_eV(tmpMatch)  ,'uni' , 0);
+ListNexafs.uhvI0std(tmpMatch)   = cellfun(fun2, ListNexafs.xRayEkin_eV(tmpMatch)  ,'uni' , 0);
+clearvars tmp* fun*
+

Plot data: XPS images

We use the nappPlot function to plot the images. For this, we specify the column of the data table that should be plotted: 'tableVarialbe','image' plots the image for all data in FileList that are selected by the logical array tmpDataSelection (See Filtering table above).

nappPlot(FileList,tmpDataSelection,'tableVariable','image');
+

Plot data: XPS and NEXAFS images

This example filters for a XPS file name and a NEXAFS file name and shows two things. First, that the XPS file name is not unique and filtering thus needs to be combined with extra parameters such as date and second how NEXAS and XPS data can be simultaneously passed to the nappPlot function

tmpDataSelection = matches(FileList.name,'0067067_O1s_1000eV.ibw') | matches(FileList.name, '0063_20200824_042852_O_K_edge.h5');
+nappPlot(FileList,tmpDataSelection);
+

Plot data: XPS spectra

We use the nappPlot function to plot the spectra by selecting 'spectrum_countsPerSecond' as 'tableVariable'. Further options include the binding or kinetic energy scale, and each spectrum in a separate window, or all in one window by setting the 'mode'. This works, of course, only after the spectrum has been generated using the function nappGenerateSpectra.

nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',...
+ 'mode','AllInOne','energyScale','kinetic');
+

Plot data: NEXAFS spectra

We use the same, one-and-only nappPlot function to plot the NEXAFS spectra by selecting 'spectrum_counts' as 'tableVariable' and 'energyScale' as 'xRay'. Further options include plotting each spectrum in a separate window, or all in one window by setting the 'mode'. This works, of course, only after the spectrum has been generated using the function nappGenerateSpectra.

nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach')
+

Plot data: Figure layout

The nappPlot function has 3 pre-defined figure layouts optimised for the computer screen, for powerpoint presentation or for word (and other text) files:

nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach','figureMode','screen');
+
nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach','figureMode','word');
+

nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach','figureMode','powerpoint');

Plot data: Export the Figure (for use in powerpoint)

Either, copy paste the figure, or use this command on the front most figure in Matlab:

set(gcf,'InvertHardcopy','on');
+print('NameForFigureFile, '-dpng', '-r220');
+

Plot data: Add region labels to survey

Here is an example of how to mark regions of interest in survey plots. For this, a survey must be the topmost figure.

   dataObjs    = findobj(gcf,'-property','YData');
+   tmpxShift          = 5;         % binding energy shift and mono offset
+   tmpxRayEnergy      = 900;       % of this survey
+   tmpyPosition       = 0.5E5;     % y position of labels, delta to signal height,  in axis scale
+   tmpyPositionTwo    = 0.1E5;     % optional, to shift neighouring labels up and dow
+   % n
+   % Au peaks
+   nappAnnotateSurvey(tmpxRayEnergy-57-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'Au5p3/2');
+   nappAnnotateSurvey(tmpxRayEnergy-74-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au5p5/2');
+   nappAnnotateSurvey(tmpxRayEnergy-84-tmpxShift,tmpyPosition,dataObjs(1),'Au4f7/2');
+   nappAnnotateSurvey(tmpxRayEnergy-88-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'Au4f5/2');
+   nappAnnotateSurvey(tmpxRayEnergy-107-tmpxShift,tmpyPosition,dataObjs(1),'Au5s');
+   nappAnnotateSurvey(tmpxRayEnergy-335-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au4d1/2');
+   nappAnnotateSurvey(tmpxRayEnergy-353-tmpxShift,tmpyPosition,dataObjs(1),'Au4d3/2');
+   nappAnnotateSurvey(tmpxRayEnergy-546-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au4p3/2');
+   nappAnnotateSurvey(tmpxRayEnergy-643-tmpxShift,tmpyPosition,dataObjs(1),'Au4p1/2');
+   nappAnnotateSurvey(tmpxRayEnergy-762-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au4s');
+   nappAnnotateSurvey(tmpxRayEnergy-8-tmpxShift,tmpyPosition,dataObjs(1),'AuVB');
+   % usual suspects
+   nappAnnotateSurvey(tmpxRayEnergy-285-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'C1s');
+   nappAnnotateSurvey(tmpxRayEnergy-534-tmpxShift,tmpyPosition,dataObjs(1),'O1s');
+   nappAnnotateSurvey(tmpxRayEnergy-30-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'O2s');
+   nappAnnotateSurvey(tmpxRayEnergy-405-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'N1s');
+   nappAnnotateSurvey(tmpxRayEnergy-495-tmpxShift,tmpyPosition,dataObjs(1),'Sn3d');
+   nappAnnotateSurvey(tmpxRayEnergy-691-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'F1s');
+   nappAnnotateSurvey(tmpxRayEnergy-295-tmpxShift,tmpyPosition,dataObjs(1),'K2p');
+   nappAnnotateSurvey(tmpxRayEnergy-380-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'K2s');
+   nappAnnotateSurvey(tmpxRayEnergy-153-tmpxShift,tmpyPosition,dataObjs(1),'Si2s');
+   nappAnnotateSurvey(tmpxRayEnergy-100-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Si2p');
+   nappAnnotateSurvey(tmpxRayEnergy-197-tmpxShift,tmpyPosition,dataObjs(1),'Cl2p');
+   nappAnnotateSurvey(tmpxRayEnergy-286-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'Sn3p');
+   % Some Auger
+   nappAnnotateSurvey(360-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'N KLL');
+   nappAnnotateSurvey(500-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'O KLL');
+   % tid up
+   clearvars tmp*

Process data: Align sequence iterations in images

To shift and align the kinetic energy of each sequence iteration relative to each other, one can use

  1. nappDetermineShiftXps: calculate the kinetic energy shift of each sequence iteration of an image relative to one sequence iteration (first is default)
  2. nappCopyShift: optionally copy the kinetic energy shift to other data
  3. nnappAlignImages: shift each sequence iterations of an image so that the peak maxima align.
% compile data
+tmpDataSelection = contains(FileList.name,'67_O1s') ...
+    & (month(FileList.lastModifiedDatenum) == 8) ...
+    & (year(FileList.lastModifiedDatenum) == 2021);
+% plot images
+nappPlot(FileList,tmpDataSelection,'tableVariable','image');
+% align images
+FileList = nappDetermineShiftXps(FileList,'tableSelection',tmpDataSelection,...
+    'showFigures','off','tableVariable','image');
+FileList = nappAlignImages(FileList,'tableSelection',tmpDataSelection,...
+    'tableVariable','image');
+% plot images
+nappPlot(FileList,tmpDataSelection,'tableVariable','image');
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 26 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 17 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 14 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 29 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 27 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 36 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 25 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 26 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 43 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 22 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 37 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 36 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 42 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 38 local solver runs converged with a positive local solver exit flag.
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 41 local solver runs converged with a positive local solver exit flag.
+

Process data: Generate XPS spectra

All sequence iterations of an image are summed or the mean of all sequence iterations is calculated. The following command calculates the average of all sequence iterations from the filtered files in the FileList table. The spectrum based on the mean is saved in the column 'spectrum_countsPerSecond'.

FileList = nappGenerateSpectra(FileList,tmpDataSelection);
+

Process data: Generate NEXAFS spectra

% All Auger spectra of an image are summed. Options include to sum the data with the energy interval of the aquisition, or to use the trapz function to normalise to 1 eV data spacing. The NEXAFS spectrua are always saved in the column 'spectrum_counts'.

FileList = nappGenerateSpectra(FileList,'tableSelection',tmpDataSelection,'mode','sum');
+
FileList = nappGenerateSpectra(FileList,tmpDataSelection);
+

Process data: Align XPS spectra to background

To align the spectra to a background the function nappBacktround can be used. Options include to compute the mean or a linear regression. Here, we calculate the mean between 367 and 370 eV.

FileList = nappBackground(FileList,367,370,'tableSelection',tmpDataSelection,'...
+energyScale','kinetic','mode','mean');
+

Process data: Align NEXAFS spectra to background

To align the spectra to a background the function nappBacktround can be used. Options include to compute the mean or a linear regression. Here, we calculate the mean between 522 and 525 eV xRay energy.

FileList = nappBackground(FileList,522,525,'tableSelection',tmpDataSelection,...
+'tableVariable','spectrum_counts','energyScale','xRay','mode','mean');
+

Process data: Gauss peak fit

Gauss fitting can be used to determine area, width, and position of PE peaks. nappFitGaussXps de-convolutes the PE signal using 4 features. The fits can be constrained by

  • 'widthPosition' (Default): With of all peaks is identical. Position of peaks 2-3 is set relative to peak 1.
  • 'position': Position of peaks 2-3 is set relative to peak 1.
  • 'width': all peaks have same width
  • 'unconstrained': Each gauss peak is fitted independent.
  • 'unconstrainedAndWidthPosition': One unconstrained peak #3 (for gas phase feature) and 4 peaks constrained in width and/or position

The function needs fit parameters as input, such as min and max peak area, width, and position; initial values for fitting; and the spectrum range.

  • spectrum range: define the region of the PE spectrum used for fitting (plus and minus from peak 1 position). % position of peak 2-4 are relative to peak 1, that of peak 1 absolute (either in binding or kinetic energy scale)
  • If you are only interested in less than 4 peaks, choose small dummy constrains for those peaks you don't want to fit.
% initial fit parameters
+tmpFitParameters.peakArea = [1E4 5E3 0.1 0.1];
+tmpFitParameters.peakWidth = [2.0 2.0 0.1 0.1];
+tmpFitParameters.peakPos = [363 -1 -2 -3];
+% lower bonds
+tmpFitParameters.peakAreaLowerBond = [1E3 5E3 0.1 0.1];
+tmpFitParameters.peakWidthLowerBond = [2.0 2.0 0.1 0.1];
+tmpFitParameters.peakPosLowerBond = 361;
+% upper bonds
+tmpFitParameters.peakAreaUpperBond = [1E6 10E4 0.1 0.1];
+tmpFitParameters.peakWidthUpperBond = [3.0 2.0 0.1 0.1];
+tmpFitParameters.peakPosUpperBond = 365;
+% spectrum range
+tmpFitParameters.backgroundRange = [5 5];
+

% „position“ mode tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; tmpFitParameters.peakWidth = [abs#1 abs#2 abs#3 abs#4]; tmpFitParameters.peakPos = [abs#1 rel#2 rel#3 rel#4];

tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; tmpFitParameters.peakWidthUpperBond = [#1 #2 #3 #4]; tmpFitParameters.peakPosUpperBond = #1; tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; tmpFitParameters.peakWidthLowerBond = [#1 #2 #3 #4]; tmpFitParameters.peakPosLowerBond = #1;

% „unconstrained“ mode tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; tmpFitParameters.peakWidth = [abs#1 abs#2 abs#3 abs#4]; tmpFitParameters.peakPos = [abs#1 abs#2 abs#3 abs#4];

tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; tmpFitParameters.peakWidthUpperBond = [#1 #2 #3 #4]; tmpFitParameters.peakPosUpperBond = [#1 #2 #3 #4]; tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; tmpFitParameters.peakWidthLowerBond = [#1 #2 #3 #4]; tmpFitParameters.peakPosLowerBond = [#1 #2 #3 #4];

% „ widthPosition“ mode tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; tmpFitParameters.peakWidth = [abs#1-#4]; tmpFitParameters.peakPos = [abs#1 rel#2 rel#3 rel#4];

tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; tmpFitParameters.peakWidthUpperBond = #1-#4; tmpFitParameters.peakPosUpperBond = #1; tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; tmpFitParameters.peakWidthLowerBond = #1-#4; tmpFitParameters.peakPosLowerBond = #1;

% „ width“ mode tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; tmpFitParameters.peakWidth = [abs#1-#4]; tmpFitParameters.peakPos = [abs#1 abs#2 abs#3 abs#4];

tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; tmpFitParameters.peakWidthUpperBond = #1-#4; tmpFitParameters.peakPosUpperBond = [#1 #2 #3 #4]; tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; tmpFitParameters.peakWidthLowerBond = #1-#4; tmpFitParameters.peakPosLowerBond = [#1 #2 #3 #4];

% „ unconstrainedAndWidthPosition" mode (novel: rel distance fit parameter) tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4 abs#5]; tmpFitParameters.peakWidth = [abs#1,2,4,5 abs#3]; tmpFitParameters.peakPos = [rel#1 abs#2 abs#3 abs#4 abs#5];

tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4 #5]; tmpFitParameters.peakWidthUpperBond = [#1,2,4,5 #3]; tmpFitParameters.peakPosUpperBond = [#1 #2 #3 #4 #5]; tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; tmpFitParameters.peakWidthLowerBond = [#1,2,4,5 #3]; tmpFitParameters.peakPosLowerBond = [#1 #2 #3 #4];

FileList = nappFitGaussXps(FileList,tmpDataSelection,tmpFitParameters,'tableSelection',tmpDataSelection,...
+    'energyScale','kinetic','mode','position','showFigures','on');
+

% The fit results are written to the data table. Peak position is only written to the table if in binding energy mode. Further, results are plotted to the command line and fits are shown in graphs:

+GlobalSearch stopped because it analyzed all the trial points.
+
+All 32 local solver runs converged with a positive local solver exit flag.
+ 
+ 
+Fit results
+0035035_O1s_900eV.ibw
+ 
+             position      FWHW       width        area    
+             _________    _______    _______    ___________
+
+    peak1    {'363.6'}    {'2.4'}    {'2.0'}    {' 644646'}
+    peak2    {'362.6'}    {'2.4'}    {'2.0'}    {'   5000'}
+    peak3    {'361.6'}    {'0.1'}    {'0.1'}    {'      0'}
+    peak4    {'360.6'}    {'0.1'}    {'0.1'}    {'      0'}
+    peak5    {'NaN'  }    {'NaN'}    {'NaN'}    {'    NaN'}
+
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 43 local solver runs converged with a positive local solver exit flag.
+ 
+ 
+Fit results
+0056056_O1s_900eV.ibw
+ 
+             position      FWHW       width        area    
+             _________    _______    _______    ___________
+
+    peak1    {'363.2'}    {'2.4'}    {'2.0'}    {' 291250'}
+    peak2    {'362.2'}    {'2.4'}    {'2.0'}    {'   5000'}
+    peak3    {'361.2'}    {'0.1'}    {'0.1'}    {'      0'}
+    peak4    {'360.2'}    {'0.1'}    {'0.1'}    {'      0'}
+    peak5    {'NaN'  }    {'NaN'}    {'NaN'}    {'    NaN'}
+
+
+GlobalSearch stopped because it analyzed all the trial points.
+
+All 36 local solver runs converged with a positive local solver exit flag.
+ 
+ 
+Fit results
+0060060_O1s_900eV.ibw
+ 
+             position      FWHW       width        area    
+             _________    _______    _______    ___________
+
+    peak1    {'363.4'}    {'2.4'}    {'2.0'}    {' 291466'}
+    peak2    {'362.4'}    {'2.4'}    {'2.0'}    {'   5000'}
+    peak3    {'361.4'}    {'0.1'}    {'0.1'}    {'      0'}
+    peak4    {'360.4'}    {'0.1'}    {'0.1'}    {'      0'}
+    peak5    {'NaN'  }    {'NaN'}    {'NaN'}    {'    NaN'}
+
+Could not write results to table. Writing only 4 entries
+

Process data: Norm spectra

To normalise spectra, nappScaleToArea can be used. A typical example is to normalise C1s to the O1s peak area to compensate for changes in the working distance. The function uses the peakArea table column, thus nappFitGaussXps needs to run first. Results are written to the table variable spectrum_countsNorm (as the unit is no longer countsPerSecond). To normalise C1s to the O1s peak area, select C1s spectra using a logical (tmpDataSelection), and choose C1s for regionOld and O1s for regionNew:

  • regionOld: C1s (default) or O1s - region that will be normalised
  • regionNew: O1s (default) or C1s - peak area that will be used to normalise
FileList = nappScale(FileList,tmpDataSelection,'regionOld','C1s','regionNew','O1s');
+nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsNorm');
+

Process data: Binding energy scale

To calculate the binding energy, you need to

  1. nappDetermineShiftXps: calculate the kinetic energy shift relative to a reference value
  2. nappCopyShift: optionally copy the kinetic energy shift to other data
  3. nappBindingEnergyXps: calculate the binding energy based on the kinetic energy shift either determined relative to a reference or copied to the individual data.

The following example shows how the kinetic energy shift is calculated based on selected O1s spectra relative to 535 eV, copied to the C1s data with the same file number, and finally the binding energy of the C1s data is calculated (based on the observed shift of the O1s of the same sequence run) and plotted

close all
+% generate spectra for C1s and O1s
+tmpDataSelection =  matches(FileList.sample,'Ice with N2')...
+    & ~contains(FileList.sample,'(bad data)')...
+    & (contains(FileList.name,'O1s') | contains(FileList.name,'C1s'))...
+    & FileList.xRayEkinRange_eV(:,1) == 900 ...
+    & FileList.scientaPassEnergy_eV == 50 ...
+    & (month(FileList.lastModifiedDatenum) == 2) ...
+    & (year(FileList.lastModifiedDatenum) == 2022) ...
+    & (day(FileList.lastModifiedDatenum) >= 27);
+FileList = nappGenerateSpectra(FileList,tmpDataSelection);
+FileList = nappBackground(FileList,367,370,'tableSelection',tmpDataSelection,'energyScale','kinetic',...
+    'mode','mean');
+% determine shift of O1s
+tmpDataSelection =  matches(FileList.sample,'Ice with N2')...
+    & ~contains(FileList.sample,'(bad data)')...
+    & contains(FileList.name,'O1s')...
+    & FileList.xRayEkinRange_eV(:,1) == 900 ...
+    & FileList.scientaPassEnergy_eV == 50 ...
+    & (month(FileList.lastModifiedDatenum) == 2) ...
+    & (year(FileList.lastModifiedDatenum) == 2022) ...
+    & (day(FileList.lastModifiedDatenum) >= 27);
+FileList = nappDetermineShiftXps(FileList,'tableSelection',tmpDataSelection,...
+          'showFigures','off','tableVariable','spectrum_countsPerSecond','binEnReference',533);
+% copy shift from O1s to C1s
+FileList = nappCopyShift(FileList,tmpDataSelection,'energyScale','binding');
+% calculate binding energy of these C1s
+tmpDataSelection =  matches(FileList.sample,'Ice with N2')...
+    & ~contains(FileList.sample,'(bad data)')...
+    & contains(FileList.name,'C1s') & FileList.xRayEkinRange_eV(:,1) == 900 ...
+    & FileList.scientaPassEnergy_eV == 50 ...
+    & (month(FileList.lastModifiedDatenum) == 2) ...
+    & (year(FileList.lastModifiedDatenum) == 2022) ...
+    & (day(FileList.lastModifiedDatenum) >= 27);
+FileList = nappBindingEnergyXps(FileList,'tableSelection',tmpDataSelection);
+% plot C1s spectra
+nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',...
+    'mode','AllInOne','energyScale','kinetic');
+nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',...
+    'mode','AllInOne','energyScale','binding');
+

Process data: Combine spectra

To get better statistics (signal-to-noise), repeated measurements can be added or averaged into one spectrum. The results are written into a matrix with energy in column 1, counts in column2, and standard deviation in column 3 (only for mean). So, the nappFunctions can no longer be used for this data format.

tmpDataSelection =  contains(FileList.name,'C1s')...
+    & contains(FileList.sample,'MgO ice AA')...
+    &  ~endsWith(FileList.sample,'(bad data)')...
+    & FileList.sampleTemp_dC >= -26 & FileList.sampleTemp_dC <= -24;
+MgO_C1s_Warm = nappCombineSpectra(FileList,'tableRow',1,...
+    'tableSelection',tmpDataSelection,'tableVariable',...
+    'spectrum_countsPerSecond','EnergyScale','binding','mode','average');
+


Published with MATLAB® R2021b

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a/nappIce/HowTo/nappIceHowTo.m b/nappIce/HowTo/nappIceHowTo.m new file mode 100644 index 0000000..a1e5ed8 --- /dev/null +++ b/nappIce/HowTo/nappIceHowTo.m @@ -0,0 +1,1382 @@ +%% How to analyse ISS XPS and NEXAFS data using Matlab +% +%% Introduction: Concept +% +% NEXAFS and XPS data from beam times is imported into a MATLAB table. The +% table allows to add meta data such as sample temperature, cell pressure, +% or Scienta settings (pass energy, etc). Further, data from several +% beam times can be imported and then filtered - for example to process all +% gas-phase CO2 PE from the last 5 years; or all ice NEXAFS at -10° to +% -12°C. Functions and the table are organised such that one can always go +% back to raw data to re-do the analysis or continue with processed data. +% +% The basic idea is that a set of MATLAB functions that import the data of +% different format and from various sources and that can be used to perform +% basic XPS and NEXAFS data processing are used, shared, and developed by +% all group members. This requires common data formats and naming. The +% scripts/live scripts/functions that are used to call the common MATLAB +% functions are written, stored, named individually by each user. +% +% +% +% +% +%% Introduction: Function calls +% +% Most functions need the MATLAB data table as input. The output can be +% stored in the same data table adding data to the original data table, or +% in a new one - thus creating a copy. Some functions such as those used +% for plotting do not write data. +%% +% +% InputTable = nappFunctionAbc(InputTable); +% +%% +% This command runs the function nappFunctionAbc on the data table +% _InputTable_ and writes the results into the same table (with the name +% _InputTable_. +% +% The _InputTable_ may hold different data types such as XPS data, NEXAFS, +% and pictures. Mostly, the functions require one and the same data type as +% input. *The _InputTable_ needs to be filtered when passed to a function* +% (see below). Exceptions from this are the |nappGenerateSpectra| and +% |nappPlot| functions that can be called with some limitations with +% mixed data as input (including pictures, that are ignored). +% +%% +% +% OutputTable = nappFunctionAbc(InputTable); +% +%% +% +% This command runs the same function on the data in the table _InputTable and +% writes the results into the data table _OutputTable_ which is a full copy +% of _InputTable_ plus the results of the function nappFunctionAbc. +% +% +% Most functions allow to set a number of optional input parameters, some +% require additional mandatory input. Please check the documentation of +% each function for further help: +% +%% +% +% help nappFunctionAbc +% +%% +% +% The mandatory input comes first in each function call. In the following +% example the data of the _InputTable_ is passed to the function as well as +% the variables _x_ and _y_. The optional function input is given just like +% in any MATLAB function using parameter descriptions: 'option',setting. +% Setting can be a text string in quotes, or a variable (array, logical, +% table, date number, etc). Most common are: +% +%% +% +% OutputTable = nappFunctionAbc(InputTable,x,y,'tableSelection',tmpDataSelection,'... +% 'tableVariable','TableVariable', energyScale','kinetic','mode','mean'); +% +%% +% * 'tableSelection': allows to filter the table and run the function only +% on selected table lines. tmpDataSelection is a logical array, see section +% Work with data: Filter table in this document. +% * 'tableVariable': allows to choose the data of the data table that the +% function should work with. See Introduction: Data structure section in +% this document. +% * 'energyScale': allows to use kinetic or binding energy scale to plot or +% perform calculation. +% * 'mode': allows to select options for functions such as using mean or +% sum for calculations, etc. +% * 'showFigures': allows to view or view not figures and function output. +% +% Please consult the help files of each function for a complete list of +% options. + +% +%% Introduction: Data structure +% +% It starts with importing the multi-dimensional IgorPro files that the SES +% software saves or with the h5 file structure that is saved for the NEXAFS +% data. +% +% * Upon import of the SES data, region iterations are averaged and +% counts are normalised to 1 s. +% * NEXAFS data... +% +% The data are then saved in a data table, each file in one row and the +% data in columns. Columns are called table variables in MATLAB and in the +% nappFunctions. The data columns are: +% +% * *image*: PE data: Intensity in counts-per-second vs. kinetic energy and sequence +% iteration. Functions that work with image data, overwrite this column. +% * *imageRoh*: a copy of image at the time of data import. +% * *spectrum_countsPerSecond* and *spectrum_counts*: Hold the spectra that +% are computed from the image. These data columns are modified by +% nappFunctions that work with spectrum data. +% * *spectrumRoh_countsPerSecond* and *spectrumRoh_counts*: a copy of the +% spectrum data at time of generation. +% +% In other words, the data in the columns spectrum_countsPerSecond, +% spectrum_counts, image always hold the processed data and are modified by +% each function call. The Roh data allows to go back and re-do the +% processing. Next to this the data table stores analyser settings such as +% scientaEkin and sample parameters such as temperature and pressure. View +% the data table in the data viewer or command window of MATLAB to see all +% columns. This data structure allows to process all data and then still plot +% images, unprocessed data, or processed data of selected experiments. +%% ToDo +% +% * add code for intensity vs. time plotting +% * add code for average and plot iterations. +% * get rid of peakfind and replace by gauss fitting +% * use gauss fitting function within functions? +% * Tidy html output, and get Yanisha's feedback +% * Add section on how to modify figures after plotting +% * add section on how to access data in table +% * add section on how to merge data tables +% * Work on code and add section how to remove XPS from NEXAFS +% * Work on code and add section on I0 including 2nd order light +% * Add code to add combined spectra to data table as row. +% * Update help files for NEXAFS functions and NEXAFS options in general +% functions. +% * Set-up folders for Yanisha + +%% Prepare: Initialise MATLAB +% +% You need to have access to the folder holding the functions and helper +% files. These are shared via switch drive. +% +% *Add the paths to the initializeMatlab function at the end of this +% script* This function needs to be added to the end of each of your +% scripts or live scripts. Below is an example. +% +%% +% +% function [myColorMap, PsiFarbe] = initializeMatlab +% %initializeMatlab Sets NappIce specific settings +% % Adds Napp files to path and defines file locations for mac, windows, +% % and Matlab online (which runs on unix) +% +% % change working directory +% path = matlab.desktop.editor.getActiveFilename; +% [filepath,~,~] = fileparts(path); +% cd(filepath); +% +% % The fitting routines writes quite a lot of feedback and warnings. I shut them off. +% warning('off','all') +% warning off backtrace +% warning off verbose +% +% % Functions and helper files path: +% if ismac +% % add Napp files to path +% addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/Add-Ons'); +% addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/nappIce'); +% elseif ispc +% % add Napp files to path +% addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/Add-Ons'); +% addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/nappIce'); +% elseif isunix +% % add Napp files to path +% addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/Add-Ons'); +% addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/nappIce'); +% end +% +% % Color maps +% myColorMap.red = colormap(autumn(7)); +% myColorMap.blue = colormap(winter(7)); +% +% % define PSI cooperate identity colours +% PsiFarbe.hellgrau = [226 226 226]/255; +% PsiFarbe.mittelgrau = [184 184 184]/255; +% PsiFarbe.dunkelgrau = [78 78 77]/255; +% PsiFarbe.blaugrau = [236 236 243]/255; % This is actually not a PSI colour +% PsiFarbe.gelb = [239 200 37]/255; +% PsiFarbe.hellorange = [227 164 31]/255; +% PsiFarbe.dunkelorange = [207 92 22]/255; +% PsiFarbe.hellrot = [164 36 23]/255; +% PsiFarbe.dunkelbraun = [114 85 65]/255; +% PsiFarbe.hellbraun = [127 119 47]/255; +% PsiFarbe.mittelgruen = [135 150 59]/255; +% PsiFarbe.hellgruen = [195 214 47]/255; +% PsiFarbe.dunkelgruen = [72 130 33]/255; +% PsiFarbe.dunkelrot = [104 47 86]/255; +% PsiFarbe.dunkelblau = [37 65 108]/255; +% PsiFarbe.mittelgruenblau = [61 164 168]/255; +% PsiFarbe.hellblau = [58 162 190]/255; +% PsiFarbe.mittelblau = [50 118 158]/255; +% +% end +%% +% The path might be different +% on your computer depending how you have set up SwitchDrive: +% +%% +% +% addpath('C:\Users\bletry_c\switchdrive\PSI_Matlab\nappIce'); +% addpath('C:\Users\bletry_c\switchdrive\PSI_Matlab\Add-Ons'); +% +%% +% then run the initialiseMatlab function: +%% +% clearvars +% [myColorMap, PsiFarbe] = initializeMatlab; +% close all +% clc + +%% Prepare: ISS data structure and path to local copy of ISS data +% +% Data needs to be organised in beam time folders that can be located on the +% Napp drive or locally on your computer. The data folder naming and +% structure within the beam time folder (orange on figure) is strict and +% there must not be any subfolders in the data folders: +% +% +% +% +%% +% * NEXAFS holds *.h5 XAS data +% * Photos holds *.bmp pictures +% * Pressure holds the *.dat LabView files +% * SES holds the *.ibw PE data. +% * To run the scripts, there *needs to be at +% least ONE *.ibw file in the SES folder* +% +% +% +% *beam time folder location* +% +% * The beam time folder can be a subfolder of any number of folders. +% * The beam time folder needs to have the same name, same subfolders, and +% folders above (path) locally and on the NAPP drive. This can be set by +% the user when calling the import function. As standard, we use +% "year:YYYY_MM__monthIssIceNapp" +% * on Napp drive: the beam time folder (and folders above) needs to be +% within the "SC Data" folder +% * locally: the beam time folder (and folders above) needs to be within +% your "MATLAB home folder:NAPP:SC Data" folder +% +% +% The see all import options (few examples given below) check out the +% nappFileList.m help (this works for all nappIce functions): +%% +% +% help nappFileList.m +% +%% Helper functions +% +% * Napp_p_ice(T_current) states and plots the vapour pressure of ice between 200-270 K +% * Napp_p_RH(T_current,RH) calculates the partial pressure of water for a given +% temperature and relative humidity. +% * Napp_RH_p(T_current,partial_pressure_water) calculates the relative humidity for a given +% temperature and water pressure. +%% Import ISS data: Complete beam time folder +% +%% +% +% FileList = nappFileList('2022/2022_02__FebIssIceNapp'); +% +%% +% This will create a new data table "FileList" overwriting any previous +% versions of this list with data imported from the local copy of the beam +% time folder with the name "2022_02__FebIssIceNapp" being a subfolder of +% the folder "2022". +%% +clearvars +%% +[myColorMap, PsiFarbe] = initializeMatlab; +close all +clc +%% +if isfile('nappIceHowToData.mat') + load('nappIceHowToData.mat') + disp('data read from mat file') +else + FileList = nappFileList('2022/2022_02__FebIssIceNapp'); + % add photon energy to table + FileList = addPhotonEnergy(FileList,[1,8:12,26],1000,2,2022); + FileList = addPhotonEnergy(FileList,[2:3,5,7,13:14,16:18,20:25,27:31,33:35,37:38,40,42,44,46,47,49:51,54:56,60:62,65:66,68,70,73,74,76,77,82],900,2,2022); + FileList = addPhotonEnergy(FileList,[4,6,15,19,58,59,64,67,72,80,81],650,2,2022); + FileList = addPhotonEnergy(FileList,[32,36,39,41,43,45,48,57,63,69,71,75,78,83],1150,2,2022); + FileList = addPhotonEnergy(FileList,79,NaN,2,2022); + % add sample description + FileList = addSampleNotes(FileList,[1,8:11],'Sample holder',2,2022); + FileList = addSampleNotes(FileList,[2:7,35:36,56:60],'Ice with N2',2,2022); + FileList = addSampleNotes(FileList,[12:34,54:55],'Ice',2,2022); + FileList = addSampleNotes(FileList,[16,20],'Ice (bad data)',2,2022); + FileList = addSampleNotes(FileList,[37:51,61:72],'Ice with N2 and phenol in Ar',2,2022); + FileList = addSampleNotes(FileList,44,'Ice with N2 and phenol in Ar (bad data)',2,2022); + FileList = addSampleNotes(FileList,73:76,'H2O gas-phase',2,2022); + FileList = addSampleNotes(FileList,73,'H2O gas-phase (bad data)',2,2022); + FileList = addSampleNotes(FileList,77:83,'CO2 gas-phase',2,2022); + FileList = addSampleNotes(FileList,79,'CO2 gas-phase (bad data)',2,2022); + % import data and add to data table + FileList = nappFileList('2021/2021_10__OctIssIceNapp',FileList); + FileList = nappFileList('2021/2021_08__AugIssIceNapp',FileList); + % add photon energy to table + FileList = addPhotonEnergy(FileList,1:10,1000,8,2021); + FileList = addPhotonEnergy(FileList,36:42,1000,8,2021); + FileList = addPhotonEnergy(FileList,51:72,1000,8,2021); + FileList = addPhotonEnergy(FileList,78:120,1000,8,2021); + FileList = addPhotonEnergy(FileList,1:6,1000,10,2021); + FileList = addPhotonEnergy(FileList,8,500,10,2021); + FileList = addPhotonEnergy(FileList,10,750,10,2021); + FileList = addPhotonEnergy(FileList,13,500,10,2021); + FileList = addPhotonEnergy(FileList,16,500,10,2021); + FileList = addPhotonEnergy(FileList,17,750,10,2021); + FileList = addPhotonEnergy(FileList,18:20,500,10,2021); + FileList = addPhotonEnergy(FileList,21,750,10,2021); + FileList = addPhotonEnergy(FileList,23,500,10,2021); + FileList = addPhotonEnergy(FileList,26,600,10,2021); + FileList = addPhotonEnergy(FileList,27,850,10,2021); + FileList = addPhotonEnergy(FileList,28:31,600,10,2021); + FileList = addPhotonEnergy(FileList,32:51,1000,10,2021); + FileList = addPhotonEnergy(FileList,53:68,1000,10,2021); + FileList = addPhotonEnergy(FileList,[74,76:85,87:91,93:94],1000,10,2021); + % add sample description + FileList = addSampleNotes(FileList,1:10,'MgO in N2',8,2021); + FileList = addSampleNotes(FileList,36:39,'MgO in H2O',8,2021); + FileList = addSampleNotes(FileList,40:44,'MgO in N2',8,2021); + FileList = addSampleNotes(FileList,45:49,'MgO in Ar',8,2021); + FileList = addSampleNotes(FileList,[51,53:55],'MgO in UHV',8,2021); + FileList = addSampleNotes(FileList,56:60,'MgO ice (bad data)',8,2021); + FileList = addSampleNotes(FileList,[61,66:72],'MgO ice in Ar HONO',8,2021); + FileList = addSampleNotes(FileList,61,'MgO ice in Ar HONO (bad data)',8,2021); + FileList = addSampleNotes(FileList,[68,69,70, 72],'MgO ice in Ar HONO on(bad data)',8,2021); + FileList = addSampleNotes(FileList,78:80,'MgO in UHV',8,2021); + FileList = addSampleNotes(FileList,81:82,'MgO in H2O',8,2021); + FileList = addSampleNotes(FileList,83:85,'MgO ice',8,2021); + FileList = addSampleNotes(FileList,86:94,'MgO ice AA in Ar',8,2021); + FileList = addSampleNotes(FileList,[86 88],'MgO ice AA in Ar (bad data)',8,2021); % temporarily, Ar very dominating + FileList = addSampleNotes(FileList,89,'MgO ice AA in Ar (bad data)',8,2021); + FileList = addSampleNotes(FileList,98,'Ar',8,2021); + FileList = addSampleNotes(FileList,99,'SiO2 in H2O',8,2021); + FileList = addSampleNotes(FileList,100:103,'SiO2 ice',8,2021); + FileList = addSampleNotes(FileList,104:110,'SiO2 ice AA in Ar',8,2021); + FileList = addSampleNotes(FileList,111:112,'SiO2 ice',8,2021); + FileList = addSampleNotes(FileList,113:118,'SiO2 ice AA in Ar',8,2021); + FileList = addSampleNotes(FileList,119:120,'CO2',8,2021); + + FileList = addSampleNotes(FileList,1,'MgO in N2',10,2021); + FileList = addSampleNotes(FileList,2,'MgO in N2, PE 50, Slits 1/1/1',10,2021); + FileList = addSampleNotes(FileList,3,'MgO in N2, PE 50, Slits 1/1/1',10,2021); + FileList = addSampleNotes(FileList,5,'MgO in N2, PE 50, Slits 1/0.5/0.5',10,2021); + FileList = addSampleNotes(FileList,6,'MgO in N2, PE 50, Slits 1/1/1',10,2021); + FileList = addSampleNotes(FileList,8,'MgO in N2, PE 20, Slits 1/1/1',10,2021); + FileList = addSampleNotes(FileList,10,'MgO in N2, PE 20, Slits 1/1/1',10,2021); + FileList = addSampleNotes(FileList,13,'MgO in N2, PE 20, Slits 1/1/1',10,2021); + FileList = addSampleNotes(FileList,16,'MgO in N2, PE 20, Slits 1/0.8/0.8',10,2021); + FileList = addSampleNotes(FileList,18,'MgO in N2, PE 20, Slits 1/0.8/0.8',10,2021); + FileList = addSampleNotes(FileList,19,'MgO in N2, PE 20, Slits 0.5/1/1',10,2021); + FileList = addSampleNotes(FileList,20,'MgO in N2, PE 20, Slits 0.5/1/1',10,2021); + FileList = addSampleNotes(FileList,21,'MgO in N2, PE 20, Slits 0.5/1/1',10,2021); + FileList = addSampleNotes(FileList,23,'MgO in N2, PE 20, Slits 0.5/1/1',10,2021); + FileList = addSampleNotes(FileList,26,'MgO in N2, PE 50, Slits 0.5/1/1',10,2021); + FileList = addSampleNotes(FileList,27,'MgO in N2, PE 20, Slits 0.5/1/1',10,2021); + FileList = addSampleNotes(FileList,28,'MgO in N2, PE 50, Slits 0.5/0.5/0.5',10,2021); + FileList = addSampleNotes(FileList,29,'MgO in N2, PE 50, Slits 1/1/1',10,2021); + FileList = addSampleNotes(FileList,31,'MgO in N2, PE 20, Slits 1/1/1',10,2021); + FileList = addSampleNotes(FileList,32:33,'MgO in N2',10,2021); + FileList = addSampleNotes(FileList,34:36,'MgO ice',10,2021); + FileList = addSampleNotes(FileList,37:41,'MgO in H2O',10,2021); + FileList = addSampleNotes(FileList,42:51,'MgO ice',10,2021); + FileList = addSampleNotes(FileList,45,'MgO ice (bad data)',10,2021); + FileList = addSampleNotes(FileList,[53:68,70:71],'MgO ice AA in N2' ,10,2021); + FileList = addSampleNotes(FileList,54,'MgO ice AA in N2 (bad data)' ,10,2021); + FileList = addSampleNotes(FileList,68,'MgO ice AA in N2 (bad data)' ,10,2021); + FileList = addSampleNotes(FileList,63,'MgO ice AA in N2 (bad data)' ,10,2021); + FileList = addSampleNotes(FileList, [72,74],'MgO in H2O' ,10,2021); + FileList = addSampleNotes(FileList, [76,78:80],'MgO in N2 AA plus H2O' ,10,2021); + FileList = addSampleNotes(FileList,81:82,'SiO2 in N2',10,2021); + FileList = addSampleNotes(FileList,83:85,'SiO2 ice',10,2021); + FileList = addSampleNotes(FileList,87:90,'SiO2 in H2O',10,2021); + FileList = addSampleNotes(FileList,91,'SiO2 AA in N2',10,2021); + FileList = addSampleNotes(FileList,93:94,'SiO2 in H2O AA',10,2021); + % import + FileList = nappFileList('2020/202008AugustISS',FileList); + FileList = addSampleNotes(FileList,3,'diode upstream',8,2020); + FileList = addSampleNotes(FileList,4,'diode in-cell',8,2020); + FileList = addSampleNotes(FileList,8,'diode upstream',8,2020); + FileList = addSampleNotes(FileList,9,'diode in-cell',8,2020); + FileList = addSampleNotes(FileList,10,'diode in-cell',8,2020); + FileList = addSampleNotes(FileList,11,'diode upstream',8,2020); + FileList = addSampleNotes(FileList,13:23,'O_K-edge ice',8,2020); + FileList = addSampleNotes(FileList,13:18,'O_K-edge ice (bad S/N)',8,2020); + FileList = addSampleNotes(FileList,[15,19,20],'O_K-edge ice (no notes)',8,2020); + %ListNexafs = addSampleNotes(ListNexafs,21:23,'O_K-edge ice (ice unstable)',8,2020); + FileList = addSampleNotes(FileList,24,'diode (no notes)',8,2020); + FileList = addSampleNotes(FileList,25,'diode upstream',8,2020); + FileList = addSampleNotes(FileList,[26,28,30],'O_K-edge gold',8,2020); + FileList = addSampleNotes(FileList,[27,29,31],'O_K-edge gold (no notes)',8,2020); + FileList = addSampleNotes(FileList,[32,33],'(no notes)',8,2020); + FileList = addSampleNotes(FileList,[34,35,37,38],'diode in-cell',8,2020); + FileList = addSampleNotes(FileList,[36,39:42],'diode upstream',8,2020); + FileList = addSampleNotes(FileList,43:45,'O_K-edge gold',8,2020); + FileList = addSampleNotes(FileList,[48,50],'diode upstream',8,2020); + FileList = addSampleNotes(FileList,[49,51,54],'(no notes)',8,2020); + FileList = addSampleNotes(FileList,[43:45,52,53,55:59],'O_K-edge gold',8,2020); + FileList = addSampleNotes(FileList,53,'O_K-edge gas-phase (interference)',8,2020); + FileList = addSampleNotes(FileList,54,'O_K-edge (no data)',8,2020); + FileList = addSampleNotes(FileList,55,'O_K-edge gas-phase',8,2020); + FileList = addSampleNotes(FileList,60,'diode upstream',8,2020); + FileList = addSampleNotes(FileList,[61,63],'O_K-edge ice',8,2020); + % ListNexafs = addSampleNotes(ListNexafs,61,'O_K-edge ice (ice unstable)',8,2020); + FileList = addSampleNotes(FileList,62,'O_K-edge ice (no notes)',8,2020); + FileList = addSampleNotes(FileList,64,'diode upstream',8,2020); + FileList = addSampleNotes(FileList,65,'diode in-cell',8,2020); + FileList = addSampleNotes(FileList,66,'diode in-cell',8,2020); + save('nappIceHowToData.mat','FileList'); +end + +%% Import ISS data: Error messages +% +% If you get a message like this in the command window +% +% There appears to be no file in the SES folder. Add at least one file first. +% I quit now +% +%% +% and MATLAB quits running the script, please check that there is at least +% a *.ibw file in the SES folder +%% +% If you instead get a message like this +% +% There is something wrong with the path. Check for typo and that the drives are mounted +% I quit now +% +%% +% and MATLAB quits running the script, please check +% +% * that there are no typos in the path names +% * that the drives are mounted. +%% Import ISS data: Add data to existing data table +% +% This will import data from the beam time folder +% "2021/2021_08__AugIssIceNapp" on the NAPP drive adding the data to the data table +% "FileList" in the MATLAB workspace +%% +% FileList = nappFileList('2021/2021_08__AugIssIceNapp',FileList,'mode','nappDrive'); +%% Import ISS data: Add new SES or NEXAFS files from local beam time folder +% +% Using the mode 'localNew' the content of the beam time folder will be +% compared to that of the FileList in the workspace and only those files +% not yet imported will be processed. This is a little faster and preserves +% any changes to the FileList. *To prevent data failure of running SES +% measurements, this only works on the local copy of the beam time folder* +%% +% +% FileList = nappFileList('2022/2022_02__FebIssIceNapp',FileList,'mode','localNew'); +% +%% Import ISS data: Choose files manually +% +% This will open a windows file explorer window where you can choose as +% many data files to be imported as you want. In this example, a new +% FileList is written, overwriting any previous versions in the workspace. +%% +% +% FileList = nappFileList('2022/2022_02__FebIssIceNapp','mode','nappDrivePick'); +% +% +% +% +% +%% Work with data: Excel +% +% The nappFileList.m function also writes a csv file to the beam time +% folder. Open it as xlsx and use Excels formatting and filtering tools to +% work with your data set. So, the xlsx file is edited manually and might +% contain additional information that you have added such as slit settings, +% comments, type of sample, scope of the measurement, etc. The csv file it +% automatically generated and might thus be frequently be over-written. Use +% copy/paste to update the xlsx file with new data, formatting will be +% automatically applied to new data then. +%% +% +% +% +% +% +%% Work with data: Add photon energy to table (XPS) +% +% ISS beamline does not log settings of SES data. Photon energy, which is +% needed to calculate the binding energy later, needs to be added manually. +% This will read the FileList table and add the photon energy "1000" to the +% SES data with file numbers 1,8 to 12, and 26 acquired in February (month +% "2") of the year "2022"). Note, this is only adding to XPS data, NEXAFS +% data are not touched: +%% +% +% FileList = addPhotonEnergy(FileList,[1,8:12,26],1000,2,2022); +% + +%% Work with data: Add sample description +% +% Sample description to label figures and for filtering data can be added. +% It does not make sense to use temperature or pressure, as these data are +% written to the table anyway. It does make sense to use standard phrases +% to enable filtering all beam time data. This code example follow the same +% input structure as the addPhotonEnergy function. This function works on +% both NEXAFS and XPS data. One may limit and select either one +% specifically by adding either 'NEXAFS' or 'XPS' strings as last input +% parameter. This is optional, if not specified function runs on both data +% types: +%% +% +% FileList = addSampleNotes(FileList,[1,8:11],'Sample holder',2,2022,'XPS'); +% FileList = addSampleNotes(FileList,[1,8:11],'Sample holder',2,2022,'NEXAFS'); +% FileList = addSampleNotes(FileList,[2:7,35:36,56:60],'Ice with N2',2,2022); +% FileList = addSampleNotes(FileList,73:76,'H2O gas-phase',2,2022); +% FileList = addSampleNotes(FileList,73,'H2O gas-phase (bad data)',2,2022); +%% Work with data: Filter table +% +% An advantage of the data table is filtering. This works with standard +% MATLAB functions using logical operations. Main motivation of filtering +% is to work with selected subset of data which for example can be +% processed with the same settings, fitted with the same constrains, or +% shall be plotted in one graph for comparison. +% +% Further, the _InputTable_ may hold different data types such as XPS data, +% NEXAFS, and pictures. Mostly, the functions require one and the same data +% type as input. Therefore, *the _InputTable_ needs to be filtered when +% passed to most functions*. Exceptions from this are the +% |nappGenerateSpectra| and |nappPlot| functions that can be called with +% some limitations in the settings with mixed data as input (including +% pictures, that are ignored). +% +% The first example filter CO2 gas-phase C1s PE data that is not "(bad +% data)" and has a pass energy of 50 eV. In the second example, we pick a +% C1s or O1s PE data from the SES file #77 from February 2022. Any table +% column can be used for filtering. "&" means AND "|" is OR. +% +%% +% tmpDataSelection1 = matches(FileList.sample,'CO2 gas-phase') ... +% & ~contains(FileList.sample,'(bad data)')... +% & contains(FileList.name,'C1s')... +% & FileList.scientaPassEnergy_eV == 50 ; +% +% tmpDataSelection2 = (contains(FileList.name,'077_C1s') | contains(FileList.name,'077_O1s')) ... +% (month(FileList.lastModifiedDatenum) == 2) &... +% (year(FileList.lastModifiedDatenum) == 2022); +%% +tmpDataSelection1 = matches(FileList.sample,'CO2 gas-phase') ... + & ~contains(FileList.sample,'(bad data)')... + & contains(FileList.name,'C1s')... + & FileList.scientaPassEnergy_eV == 50 ; + + +tmpDataSelection2 = (contains(FileList.name,'077_C1s') | contains(FileList.name,'077_O1s'))& ... + (month(FileList.lastModifiedDatenum) == 2) &... + (year(FileList.lastModifiedDatenum) == 2022); + +%% Work with data: Display filtered table and selected columns +% +% MATLAB tables allow to address the columns by name. To display only the +% rows that match the filter criteria and only specific columns, code like +% the examples below can be used: +%% +% disp(FileList(tmpDataSelection1,{'name','sample','xRayEkin_eV','scientaPassEnergy_eV','lastModifiedDatestr','sampleTemp_dC',... +% 'cellPressure_mbar' })) +% disp(FileList(tmpDataSelection2,{'name','scientaLensMode','xRayEkinRange_eV','scientaPassEnergy_eV'})) +%% +disp(FileList(tmpDataSelection1,{'name','sample','xRayEkin_eV','scientaPassEnergy_eV','lastModifiedDatestr','sampleTemp_dC',... + 'cellPressure_mbar' })) +disp(FileList(tmpDataSelection2,{'name','scientaLensMode','xRayEkinRange_eV','scientaPassEnergy_eV'})) +clearvars tmp* +%% +% +%% Work with data: Modify data in table +% +% There might be bad sweeps (sequence iterations) either with too low +% signal to noise or because some setting was changed during the run. These +% can be removed by directly addressing the data in the images. Same +% procedure, first the data (table row) is filtered, then the image +% modified for the selected data. +% +% *remove one sweep* +%% +% +% tmpDataSelection = contains(FileList.name,'077_C1s')& ... +% (month(FileList.lastModifiedDatenum) == 2) &... +% (year(FileList.lastModifiedDatenum) == 2022); +% FileList(tmpDataSelection,:).image{:}(:,3)=[]; +% +% tmpDataSelection = contains(FileList.name,'077_O1s')& ... +% (month(FileList.lastModifiedDatenum) == 2) &... +% (year(FileList.lastModifiedDatenum) == 2022); +% FileList(tmpDataSelection,:).image{:}(:,3)=[]; +% +%% +% *remove several sweeps* +% +%% +% +% tmpDataSelection = contains(FileList.name,'059_C1s')& ... +% (month(FileList.lastModifiedDatenum) == 10) &... +% (year(FileList.lastModifiedDatenum) == 2021); +% FileList(tmpDataSelection,:).image{:}(:,5:15)=[]; +%% +% *remove all data (complete table rows) outside a specific time window* +% +%% +% tmpTime.start = datenum('30-Apr-2019 02:00:00'); +% tmpTime.end = datenum('30-Apr-2019 05:00:00'); +% toDelete = Table_FileList.datenum <= tmpTime.start; +% Table_FileList(toDelete,:) = []; +% toDelete = Table_FileList.datenum >= tmpTime.end; +% Table_FileList(toDelete,:) = []; +%% +% *Correct beam line-offset in data* +% +% This will correct 1.6 from the X-ray energies, of particular importance +% for NEXAFS data. One can also do this on selected data. +%% +% beamlineOffset = 1.6; +% FileList.xRayEkin_eV = cellfun(@(x) x+beamlineOffset,FileList.xRayEkin_eV,'UniformOutput',false); +%% Add data (columns) to table +% +% Calculation results for each row can be added to data tables using +% standard Matlab functions. This example illustrates the use of +% anonymous functions, their call for each row using |cellfun|, and +% the generation of additional columns to which (selection of) the data are +% written. +%% +% +% fun1 =@(c) interp1(IzeroAugInCell(:,1),IzeroAugInCell(:,2), c); +% fun2 =@(c) interp1(IzeroAugInCell(:,1),IzeroAugInCell(:,3), c); +% tmpMatch = (month(ListNexafs.lastModifiedDatenum) == 8) &... +% (year(ListNexafs.lastModifiedDatenum) == 2020) |... +% (startsWith(ListNexafs.name, 'sum_Aug')); +% ListNexafs.uhvI0(tmpMatch) = cellfun(fun1, ListNexafs.xRayEkin_eV(tmpMatch) ,'uni' , 0); +% ListNexafs.uhvI0std(tmpMatch) = cellfun(fun2, ListNexafs.xRayEkin_eV(tmpMatch) ,'uni' , 0); +% clearvars tmp* fun* + +%% Plot data: XPS images +% +% We use the nappPlot function to plot the images. For this, we specify +% the column of the data table that should be plotted: +% 'tableVarialbe','image' plots the image for all data in FileList that are +% selected by the logical array tmpDataSelection (See _Filtering table_ +% above). +%% +% +% nappPlot(FileList,tmpDataSelection,'tableVariable','image'); +% +%% +close all +tmpDataSelection = contains(FileList.name,'035_O1s') & FileList.xRayEkinRange_eV(:,1) == 900 ... + & FileList.scientaPassEnergy_eV == 50 ... + & (month(FileList.lastModifiedDatenum) == 2) ... + & (year(FileList.lastModifiedDatenum) == 2022) ... + & (day(FileList.lastModifiedDatenum) >= 27); +nappPlot(FileList,tmpDataSelection,'tableVariable','image'); +%% Plot data: XPS and NEXAFS images +% +% This example filters for a XPS file name and a NEXAFS file name and shows +% two things. First, that the XPS file name is not unique and filtering +% thus needs to be combined with extra parameters such as date and second +% how NEXAS and XPS data can be simultaneously passed to the |nappPlot| +% function +%% +% tmpDataSelection = matches(FileList.name,'0067067_O1s_1000eV.ibw') | matches(FileList.name, '0063_20200824_042852_O_K_edge.h5'); +% nappPlot(FileList,tmpDataSelection); + +%% +tmpDataSelection = matches(FileList.name,'0067067_O1s_1000eV.ibw') | matches(FileList.name, '0063_20200824_042852_O_K_edge.h5'); +nappPlot(FileList,tmpDataSelection); +%% Plot data: XPS spectra +% +% We use the nappPlot function to plot the spectra by selecting +% 'spectrum_countsPerSecond' as 'tableVariable'. Further options include +% the binding or kinetic energy scale, and each spectrum in a separate +% window, or all in one window by setting the 'mode'. This works, of +% course, only after the spectrum has been generated using the function +% nappGenerateSpectra. +%% +% +% nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',... +% 'mode','AllInOne','energyScale','kinetic'); +% +%% +close all +tmpDataSelection = matches(FileList.sample,'Ice with N2')... + & ~contains(FileList.sample,'(bad data)')... + & contains(FileList.name,'O1s') & FileList.xRayEkinRange_eV(:,1) == 900 ... + & FileList.scientaPassEnergy_eV == 50 ... + & (month(FileList.lastModifiedDatenum) == 2) ... + & (year(FileList.lastModifiedDatenum) == 2022) ... + & (day(FileList.lastModifiedDatenum) >= 27); +FileList = nappGenerateSpectra(FileList,tmpDataSelection); +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',... + 'mode','AllInOne','energyScale','kinetic'); +%% Plot data: NEXAFS spectra +% +% We use the same, one-and-only nappPlot function to plot the NEXAFS +% spectra by selecting 'spectrum_counts' as 'tableVariable' and +% 'energyScale' as 'xRay'. Further options include plotting each spectrum +% in a separate window, or all in one window by setting the 'mode'. This +% works, of course, only after the spectrum has been generated using the +% function nappGenerateSpectra. +%% +% +% nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach') +% +%% +% +close all +clc +tmpDataSelection = contains(FileList.name, '0063_20200824_042852_O_K_edge'); +% Sum Auger-Meitner Spectrum +FileList = nappGenerateSpectra(FileList,'tableSelection',tmpDataSelection,'mode','sum'); +% Plot +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach'); +%% Plot data: Figure layout +% +% The |nappPlot| function has 3 pre-defined figure layouts optimised for +% the computer screen, for powerpoint presentation or for word (and other +% text) files: +%% +% +% nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach','figureMode','screen'); +% +%% +close all +clc +tmpDataSelection = contains(FileList.name, '0063_20200824_042852_O_K_edge'); +% Sum Auger-Meitner Spectrum +FileList = nappGenerateSpectra(FileList,'tableSelection',tmpDataSelection,'mode','sum'); +% Plot +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach','figureMode','screen'); +%% +% +% nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach','figureMode','word'); +% +%% +close all +clc +tmpDataSelection = contains(FileList.name, '0063_20200824_042852_O_K_edge'); +% Sum Auger-Meitner Spectrum +FileList = nappGenerateSpectra(FileList,'tableSelection',tmpDataSelection,'mode','sum'); +% Plot +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach','figureMode','word'); +%% +% +% nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach','figureMode','powerpoint'); +% +%% +close all +clc +tmpDataSelection = contains(FileList.name, '0063_20200824_042852_O_K_edge'); +% Sum Auger-Meitner Spectrum +FileList = nappGenerateSpectra(FileList,'tableSelection',tmpDataSelection,'mode','sum'); +% Plot +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach','figureMode','powerpoint'); +%% Plot data: Export the Figure (for use in powerpoint) +% +% Either, copy paste the figure, or use this command on the front most +% figure in Matlab: +%% +% +% set(gcf,'InvertHardcopy','on'); +% print('NameForFigureFile, '-dpng', '-r220'); +% +%% Plot data: Add region labels to survey +% +% Here is an example of how to mark regions of interest in survey plots. +% For this, a survey must be the topmost figure. + +%% +% dataObjs = findobj(gcf,'-property','YData'); +% tmpxShift = 5; % binding energy shift and mono offset +% tmpxRayEnergy = 900; % of this survey +% tmpyPosition = 0.5E5; % y position of labels, delta to signal height, in axis scale +% tmpyPositionTwo = 0.1E5; % optional, to shift neighouring labels up and dow +% % n +% % Au peaks +% nappAnnotateSurvey(tmpxRayEnergy-57-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'Au5p3/2'); +% nappAnnotateSurvey(tmpxRayEnergy-74-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au5p5/2'); +% nappAnnotateSurvey(tmpxRayEnergy-84-tmpxShift,tmpyPosition,dataObjs(1),'Au4f7/2'); +% nappAnnotateSurvey(tmpxRayEnergy-88-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'Au4f5/2'); +% nappAnnotateSurvey(tmpxRayEnergy-107-tmpxShift,tmpyPosition,dataObjs(1),'Au5s'); +% nappAnnotateSurvey(tmpxRayEnergy-335-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au4d1/2'); +% nappAnnotateSurvey(tmpxRayEnergy-353-tmpxShift,tmpyPosition,dataObjs(1),'Au4d3/2'); +% nappAnnotateSurvey(tmpxRayEnergy-546-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au4p3/2'); +% nappAnnotateSurvey(tmpxRayEnergy-643-tmpxShift,tmpyPosition,dataObjs(1),'Au4p1/2'); +% nappAnnotateSurvey(tmpxRayEnergy-762-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au4s'); +% nappAnnotateSurvey(tmpxRayEnergy-8-tmpxShift,tmpyPosition,dataObjs(1),'AuVB'); +% % usual suspects +% nappAnnotateSurvey(tmpxRayEnergy-285-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'C1s'); +% nappAnnotateSurvey(tmpxRayEnergy-534-tmpxShift,tmpyPosition,dataObjs(1),'O1s'); +% nappAnnotateSurvey(tmpxRayEnergy-30-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'O2s'); +% nappAnnotateSurvey(tmpxRayEnergy-405-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'N1s'); +% nappAnnotateSurvey(tmpxRayEnergy-495-tmpxShift,tmpyPosition,dataObjs(1),'Sn3d'); +% nappAnnotateSurvey(tmpxRayEnergy-691-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'F1s'); +% nappAnnotateSurvey(tmpxRayEnergy-295-tmpxShift,tmpyPosition,dataObjs(1),'K2p'); +% nappAnnotateSurvey(tmpxRayEnergy-380-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'K2s'); +% nappAnnotateSurvey(tmpxRayEnergy-153-tmpxShift,tmpyPosition,dataObjs(1),'Si2s'); +% nappAnnotateSurvey(tmpxRayEnergy-100-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Si2p'); +% nappAnnotateSurvey(tmpxRayEnergy-197-tmpxShift,tmpyPosition,dataObjs(1),'Cl2p'); +% nappAnnotateSurvey(tmpxRayEnergy-286-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'Sn3p'); +% % Some Auger +% nappAnnotateSurvey(360-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'N KLL'); +% nappAnnotateSurvey(500-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'O KLL'); +% % tid up +% clearvars tmp* + +%% +close all +tmpDataSelection = contains(FileList.name,'007_Survey'); +FileList = nappGenerateSpectra(FileList,tmpDataSelection); +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',... + 'mode','AllInOne','energyScale','kinetic'); +% add text to Figure +dataObjs = findobj(gcf,'-property','YData'); +tmpxShift = 6; +tmpxRayEnergy = 900; +tmpyPosition = 0.5E5; +tmpyPositionTwo = 0.1E5; +% Au peaks +nappAnnotateSurvey(tmpxRayEnergy-57-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'Au5p3/2'); +nappAnnotateSurvey(tmpxRayEnergy-74-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au5p5/2'); +nappAnnotateSurvey(tmpxRayEnergy-84-tmpxShift,tmpyPosition,dataObjs(1),'Au4f7/2'); +nappAnnotateSurvey(tmpxRayEnergy-88-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'Au4f5/2'); +nappAnnotateSurvey(tmpxRayEnergy-107-tmpxShift,tmpyPosition,dataObjs(1),'Au5s'); +nappAnnotateSurvey(tmpxRayEnergy-335-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au4d1/2'); +nappAnnotateSurvey(tmpxRayEnergy-353-tmpxShift,tmpyPosition,dataObjs(1),'Au4d3/2'); +nappAnnotateSurvey(tmpxRayEnergy-546-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au4p3/2'); +nappAnnotateSurvey(tmpxRayEnergy-643-tmpxShift,tmpyPosition,dataObjs(1),'Au4p1/2'); +nappAnnotateSurvey(tmpxRayEnergy-762-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Au4s'); +nappAnnotateSurvey(tmpxRayEnergy-8-tmpxShift,tmpyPosition,dataObjs(1),'AuVB'); +% usual suspects +nappAnnotateSurvey(tmpxRayEnergy-285-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'C1s'); +nappAnnotateSurvey(tmpxRayEnergy-534-tmpxShift,tmpyPosition,dataObjs(1),'O1s'); +nappAnnotateSurvey(tmpxRayEnergy-30-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'O2s'); +nappAnnotateSurvey(tmpxRayEnergy-405-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'N1s'); +nappAnnotateSurvey(tmpxRayEnergy-495-tmpxShift,tmpyPosition,dataObjs(1),'Sn3d'); +nappAnnotateSurvey(tmpxRayEnergy-691-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'F1s'); +nappAnnotateSurvey(tmpxRayEnergy-295-tmpxShift,tmpyPosition,dataObjs(1),'K2p'); +nappAnnotateSurvey(tmpxRayEnergy-380-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'K2s'); +nappAnnotateSurvey(tmpxRayEnergy-153-tmpxShift,tmpyPosition,dataObjs(1),'Si2s'); +nappAnnotateSurvey(tmpxRayEnergy-100-tmpxShift,tmpyPosition+tmpyPositionTwo,dataObjs(1),'Si2p'); +nappAnnotateSurvey(tmpxRayEnergy-197-tmpxShift,tmpyPosition,dataObjs(1),'Cl2p'); +nappAnnotateSurvey(tmpxRayEnergy-286-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'Sn3p'); +% Some Auger +nappAnnotateSurvey(360-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'N KLL'); +nappAnnotateSurvey(500-tmpxShift,tmpyPosition-tmpyPositionTwo,dataObjs(1),'O KLL'); +% tid up +clearvars tmp* + +%% Process data: Align sequence iterations in images +% +% To shift and align the kinetic energy of each sequence iteration relative +% to each other, one can use +% +% # nappDetermineShiftXps: calculate the kinetic energy shift of each +% sequence iteration of an image relative to one sequence iteration (first +% is default) +% # nappCopyShift: optionally copy the kinetic energy shift to other data +% # nnappAlignImages: shift each sequence iterations of an image so that +% the peak maxima align. +%% +% +% % compile data +% tmpDataSelection = contains(FileList.name,'67_O1s') ... +% & (month(FileList.lastModifiedDatenum) == 8) ... +% & (year(FileList.lastModifiedDatenum) == 2021); +% % plot images +% nappPlot(FileList,tmpDataSelection,'tableVariable','image'); +% % align images +% FileList = nappDetermineShiftXps(FileList,'tableSelection',tmpDataSelection,... +% 'showFigures','off','tableVariable','image'); +% FileList = nappAlignImages(FileList,'tableSelection',tmpDataSelection,... +% 'tableVariable','image'); +% % plot images +% nappPlot(FileList,tmpDataSelection,'tableVariable','image'); + +%% +close all +clc +% compile data +tmpDataSelection = contains(FileList.name,'67_O1s') ... + & (month(FileList.lastModifiedDatenum) == 8) ... + & (year(FileList.lastModifiedDatenum) == 2021); +% plot images +nappPlot(FileList,tmpDataSelection,'tableVariable','image'); +% align images +FileList = nappDetermineShiftXps(FileList,'tableSelection',tmpDataSelection,... + 'showFigures','off','tableVariable','image'); +FileList = nappAlignImages(FileList,'tableSelection',tmpDataSelection,... + 'tableVariable','image'); +% plot images +nappPlot(FileList,tmpDataSelection,'tableVariable','image'); +%% Process data: Generate XPS spectra +% +% All sequence iterations of an image are summed or the mean of all +% sequence iterations is calculated. The following command calculates the +% average of all sequence iterations from the filtered files in the +% FileList table. The spectrum based on the mean is saved in the column +% 'spectrum_countsPerSecond'. +%% +% +% FileList = nappGenerateSpectra(FileList,tmpDataSelection); +% +%% Process data: Generate NEXAFS spectra +% +% % All Auger spectra of an image are summed. Options include to sum the +% data with the energy interval of the aquisition, or to use the trapz +% function to normalise to 1 eV data spacing. The NEXAFS spectrua are +% always saved in the column 'spectrum_counts'. +%% +% +% FileList = nappGenerateSpectra(FileList,'tableSelection',tmpDataSelection,'mode','sum'); +% +%% +close all +clc +tmpDataSelection = contains(FileList.name, '0063_20200824_042852_O_K_edge'); +% Sum Auger-Meitner Spectrum +FileList = nappGenerateSpectra(FileList,'tableSelection',tmpDataSelection,'mode','sum'); +% Plot +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach'); + +%% +% +% FileList = nappGenerateSpectra(FileList,tmpDataSelection); +% +%% Process data: Align XPS spectra to background +% +% To align the spectra to a background the function nappBacktround can +% be used. Options include to compute the mean or a linear regression. +% Here, we calculate the mean between 367 and 370 eV. +%% +% +% FileList = nappBackground(FileList,367,370,'tableSelection',tmpDataSelection,'... +% energyScale','kinetic','mode','mean'); +% +%% +close all +clc +tmpDataSelection = matches(FileList.sample,'Ice with N2')... + & ~contains(FileList.sample,'(bad data)')... + & contains(FileList.name,'O1s') & FileList.xRayEkinRange_eV(:,1) == 900 ... + & FileList.scientaPassEnergy_eV == 50 ... + & (month(FileList.lastModifiedDatenum) == 2) ... + & (year(FileList.lastModifiedDatenum) == 2022) ... + & (day(FileList.lastModifiedDatenum) >= 27); +FileList = nappGenerateSpectra(FileList,tmpDataSelection); +FileList = nappBackground(FileList,367,370,'tableSelection',tmpDataSelection,'energyScale','kinetic',... + 'mode','mean'); +% plot spectra +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',... + 'mode','AllInOne','energyScale','kinetic'); + +%% Process data: Align NEXAFS spectra to background +% +% To align the spectra to a background the function nappBacktround can +% be used. Options include to compute the mean or a linear regression. +% Here, we calculate the mean between 522 and 525 eV xRay energy. +%% +% +% FileList = nappBackground(FileList,522,525,'tableSelection',tmpDataSelection,... +% 'tableVariable','spectrum_counts','energyScale','xRay','mode','mean'); +% +%% +close all +clc +tmpDataSelection = contains(FileList.name, '0063_20200824_042852_O_K_edge'); +% Sum Auger-Meitner Spectrum +FileList = nappGenerateSpectra(FileList,'tableSelection',tmpDataSelection,'mode','sum'); +% Background +FileList = nappBackground(FileList,522,525,'tableSelection',tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay',... + 'mode','mean'); +% Plot +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_counts','energyScale','xRay','mode','OneEach'); + +%% Process data: Gauss peak fit +% +% Gauss fitting can be used to determine area, width, and position of PE +% peaks. nappFitGaussXps de-convolutes the PE signal using 4 features. The +% fits can be constrained by +% +% * 'widthPosition' (Default): With of all peaks is identical. Position of +% peaks 2-3 is set relative to peak 1. +% * 'position': Position of peaks 2-3 is set relative to peak 1. +% * 'width': all peaks have same width +% * 'unconstrained': Each gauss peak is fitted independent. +% * 'unconstrainedAndWidthPosition': One unconstrained peak #3 (for gas phase +% feature) and 4 peaks constrained in width and/or position +% +% +% The function needs fit parameters as input, such as min and max peak +% area, width, and position; initial values for fitting; and the spectrum +% range. +% +% * spectrum range: define the region of the PE spectrum used for fitting +% (plus and minus from peak 1 position). +% % position of peak 2-4 are relative to peak 1, that of peak 1 absolute +% (either in binding or kinetic energy scale) +% * If you are only interested in less than 4 peaks, choose small dummy +% constrains for those peaks you don't want to fit. +% +%% +% % initial fit parameters +% tmpFitParameters.peakArea = [1E4 5E3 0.1 0.1]; +% tmpFitParameters.peakWidth = [2.0 2.0 0.1 0.1]; +% tmpFitParameters.peakPos = [363 -1 -2 -3]; +% % lower bonds +% tmpFitParameters.peakAreaLowerBond = [1E3 5E3 0.1 0.1]; +% tmpFitParameters.peakWidthLowerBond = [2.0 2.0 0.1 0.1]; +% tmpFitParameters.peakPosLowerBond = 361; +% % upper bonds +% tmpFitParameters.peakAreaUpperBond = [1E6 10E4 0.1 0.1]; +% tmpFitParameters.peakWidthUpperBond = [3.0 2.0 0.1 0.1]; +% tmpFitParameters.peakPosUpperBond = 365; +% % spectrum range +% tmpFitParameters.backgroundRange = [5 5]; +% +% % „position“ mode +% tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakWidth = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakPos = [abs#1 rel#2 rel#3 rel#4]; +% +% tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakPosUpperBond = #1; +% tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakPosLowerBond = #1; +% +% +% % „unconstrained“ mode +% tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakWidth = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakPos = [abs#1 abs#2 abs#3 abs#4]; +% +% tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakPosUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakPosLowerBond = [#1 #2 #3 #4]; +% +% +% % „ widthPosition“ mode +% tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakWidth = [abs#1-#4]; +% tmpFitParameters.peakPos = [abs#1 rel#2 rel#3 rel#4]; +% +% tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthUpperBond = #1-#4; +% tmpFitParameters.peakPosUpperBond = #1; +% tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthLowerBond = #1-#4; +% tmpFitParameters.peakPosLowerBond = #1; +% +% % „ width“ mode +% tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakWidth = [abs#1-#4]; +% tmpFitParameters.peakPos = [abs#1 abs#2 abs#3 abs#4]; +% +% tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthUpperBond = #1-#4; +% tmpFitParameters.peakPosUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthLowerBond = #1-#4; +% tmpFitParameters.peakPosLowerBond = [#1 #2 #3 #4]; +% +% +% % „ unconstrainedAndWidthPosition" mode (novel: rel distance fit parameter) +% tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4 abs#5]; +% tmpFitParameters.peakWidth = [abs#1,2,4,5 abs#3]; +% tmpFitParameters.peakPos = [rel#1 abs#2 abs#3 abs#4 abs#5]; +% +% tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4 #5]; +% tmpFitParameters.peakWidthUpperBond = [#1,2,4,5 #3]; +% tmpFitParameters.peakPosUpperBond = [#1 #2 #3 #4 #5]; +% tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthLowerBond = [#1,2,4,5 #3]; +% tmpFitParameters.peakPosLowerBond = [#1 #2 #3 #4]; +% +% +% FileList = nappFitGaussXps(FileList,tmpDataSelection,tmpFitParameters,'tableSelection',tmpDataSelection,... +% 'energyScale','kinetic','mode','position','showFigures','on'); +%% +% % The fit results are written to the data table. Peak position is only +% written to the table if in binding energy mode. Further, results are +% plotted to the command line and fits are shown in graphs: +%% +close all +tmpDataSelection = matches(FileList.sample,'Ice with N2')... + & ~contains(FileList.sample,'(bad data)')... + & contains(FileList.name,'O1s') & FileList.xRayEkinRange_eV(:,1) == 900 ... + & FileList.scientaPassEnergy_eV == 50 ... + & (month(FileList.lastModifiedDatenum) == 2) ... + & (year(FileList.lastModifiedDatenum) == 2022) ... + & (day(FileList.lastModifiedDatenum) >= 27); +FileList = nappBackground(FileList,367,370,'tableSelection',tmpDataSelection,'energyScale','kinetic',... + 'mode','mean'); +tmpFitParameters.peakArea = [1E4 5E3 0.1 0.1]; +tmpFitParameters.peakWidth = [2.0 2.0 0.1 0.1]; +tmpFitParameters.peakPos = [363 -1 -2 -3]; % position of peak 2-4 are relative to peak 1 + +tmpFitParameters.peakAreaLowerBond = [1E3 5E3 0.1 0.1]; +tmpFitParameters.peakWidthLowerBond = [2.0 2.0 0.1 0.1]; +tmpFitParameters.peakPosLowerBond = 361; + +tmpFitParameters.peakAreaUpperBond = [1E6 10E4 0.1 0.1]; +tmpFitParameters.peakWidthUpperBond = [3.0 2.0 0.1 0.1]; +tmpFitParameters.peakPosUpperBond = 365; + +tmpFitParameters.backgroundRange = [5 5]; +FileList = nappFitGaussXps(FileList,tmpDataSelection,tmpFitParameters,'tableSelection',tmpDataSelection,... + 'energyScale','kinetic','mode','position','showFigures','on'); + +%% Process data: Norm spectra +% +% To normalise spectra, nappScaleToArea can be used. A typical example is +% to normalise C1s to the O1s peak area to compensate for changes in the +% working distance. The function uses the peakArea table column, thus +% nappFitGaussXps needs to run first. Results are written to the table +% variable spectrum_countsNorm (as the unit is no longer countsPerSecond). +% To normalise C1s to the O1s peak area, select C1s spectra using a logical +% (tmpDataSelection), and choose C1s for regionOld and O1s for regionNew: +% +% * regionOld: C1s (default) or O1s - region that will be normalised +% * regionNew: O1s (default) or C1s - peak area that will be used to normalise +% +%% +% +% FileList = nappScale(FileList,tmpDataSelection,'regionOld','C1s','regionNew','O1s'); +% nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsNorm'); +% +%% +close all +clc +tmpDataSelection = matches(FileList.sample,'Ice with N2')... + & ~contains(FileList.sample,'(bad data)')... + & contains(FileList.name,'O1s') & FileList.xRayEkinRange_eV(:,1) == 900 ... + & FileList.scientaPassEnergy_eV == 50 ... + & (month(FileList.lastModifiedDatenum) == 2) ... + & (year(FileList.lastModifiedDatenum) == 2022) ... + & (day(FileList.lastModifiedDatenum) >= 27); +% plot spectra +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',... + 'mode','AllInOne','energyScale','kinetic'); +% scale to area +FileList = nappScale(FileList,tmpDataSelection,'regionOld','O1s','regionNew','O1s'); +FileList = nappBackground(FileList,367,370,'tableSelection',tmpDataSelection,'energyScale','kinetic',... + 'mode','mean','tableVariable','spectrum_countsNorm'); +% plot spectra +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsNorm',... + 'mode','AllInOne','energyScale','kinetic'); +tmpDataSelection = matches(FileList.sample,'Ice with N2')... + & ~contains(FileList.sample,'(bad data)')... + & contains(FileList.name,'C1s') & FileList.xRayEkinRange_eV(:,1) == 900 ... + & FileList.scientaPassEnergy_eV == 50 ... + & (month(FileList.lastModifiedDatenum) == 2) ... + & (year(FileList.lastModifiedDatenum) == 2022) ... + & (day(FileList.lastModifiedDatenum) >= 27); +% Generate spectra +FileList = nappGenerateSpectra(FileList,tmpDataSelection); +% plot spectra +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',... + 'mode','AllInOne','energyScale','kinetic'); +% scale to area +FileList = nappScale(FileList,tmpDataSelection,'regionOld','C1s','regionNew','O1s'); +FileList = nappBackground(FileList,615,617,'tableSelection',tmpDataSelection,'energyScale','kinetic',... + 'mode','mean','tableVariable','spectrum_countsNorm'); +% plot spectra +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsNorm'); +%% Process data: Binding energy scale +% +% To calculate the binding energy, you need to +% +% # nappDetermineShiftXps: calculate the kinetic energy shift relative to a reference value +% # nappCopyShift: optionally copy the kinetic energy shift to other data +% # nappBindingEnergyXps: calculate the binding energy based on the kinetic +% energy shift either determined relative to a reference or copied to the +% individual data. +% +% The following example shows how the kinetic energy shift is calculated +% based on selected O1s spectra relative to 535 eV, copied to the C1s data +% with the same file number, and finally the binding energy of the C1s data is +% calculated (based on the observed shift of the O1s of the same sequence +% run) and plotted +%% +% +% close all +% % generate spectra for C1s and O1s +% tmpDataSelection = matches(FileList.sample,'Ice with N2')... +% & ~contains(FileList.sample,'(bad data)')... +% & (contains(FileList.name,'O1s') | contains(FileList.name,'C1s'))... +% & FileList.xRayEkinRange_eV(:,1) == 900 ... +% & FileList.scientaPassEnergy_eV == 50 ... +% & (month(FileList.lastModifiedDatenum) == 2) ... +% & (year(FileList.lastModifiedDatenum) == 2022) ... +% & (day(FileList.lastModifiedDatenum) >= 27); +% FileList = nappGenerateSpectra(FileList,tmpDataSelection); +% FileList = nappBackground(FileList,367,370,'tableSelection',tmpDataSelection,'energyScale','kinetic',... +% 'mode','mean'); +% % determine shift of O1s +% tmpDataSelection = matches(FileList.sample,'Ice with N2')... +% & ~contains(FileList.sample,'(bad data)')... +% & contains(FileList.name,'O1s')... +% & FileList.xRayEkinRange_eV(:,1) == 900 ... +% & FileList.scientaPassEnergy_eV == 50 ... +% & (month(FileList.lastModifiedDatenum) == 2) ... +% & (year(FileList.lastModifiedDatenum) == 2022) ... +% & (day(FileList.lastModifiedDatenum) >= 27); +% FileList = nappDetermineShiftXps(FileList,'tableSelection',tmpDataSelection,... +% 'showFigures','off','tableVariable','spectrum_countsPerSecond','binEnReference',533); +% % copy shift from O1s to C1s +% FileList = nappCopyShift(FileList,tmpDataSelection,'energyScale','binding'); +% % calculate binding energy of these C1s +% tmpDataSelection = matches(FileList.sample,'Ice with N2')... +% & ~contains(FileList.sample,'(bad data)')... +% & contains(FileList.name,'C1s') & FileList.xRayEkinRange_eV(:,1) == 900 ... +% & FileList.scientaPassEnergy_eV == 50 ... +% & (month(FileList.lastModifiedDatenum) == 2) ... +% & (year(FileList.lastModifiedDatenum) == 2022) ... +% & (day(FileList.lastModifiedDatenum) >= 27); +% FileList = nappBindingEnergyXps(FileList,'tableSelection',tmpDataSelection); +% % plot C1s spectra +% nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',... +% 'mode','AllInOne','energyScale','kinetic'); +% nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',... +% 'mode','AllInOne','energyScale','binding'); +%% +% +close all +tmpDataSelection = matches(FileList.sample,'Ice with N2')... + & ~contains(FileList.sample,'(bad data)')... + & (contains(FileList.name,'O1s') | contains(FileList.name,'C1s'))... + & FileList.xRayEkinRange_eV(:,1) == 900 ... + & FileList.scientaPassEnergy_eV == 50 ... + & (month(FileList.lastModifiedDatenum) == 2) ... + & (year(FileList.lastModifiedDatenum) == 2022) ... + & (day(FileList.lastModifiedDatenum) >= 27); +FileList = nappGenerateSpectra(FileList,tmpDataSelection); +FileList = nappBackground(FileList,367,370,'tableSelection',tmpDataSelection,'energyScale','kinetic',... + 'mode','mean'); +% determine shift of O1s +tmpDataSelection = matches(FileList.sample,'Ice with N2')... + & ~contains(FileList.sample,'(bad data)')... + & contains(FileList.name,'O1s')... + & FileList.xRayEkinRange_eV(:,1) == 900 ... + & FileList.scientaPassEnergy_eV == 50 ... + & (month(FileList.lastModifiedDatenum) == 2) ... + & (year(FileList.lastModifiedDatenum) == 2022) ... + & (day(FileList.lastModifiedDatenum) >= 27); +FileList = nappDetermineShiftXps(FileList,'tableSelection',tmpDataSelection,... + 'showFigures','off','tableVariable','spectrum_countsPerSecond','binEnReference',533); +% copy shift from O1s to C1s +FileList = nappCopyShift(FileList,tmpDataSelection,'energyScale','binding'); +% calculate binding energy of these C1s +tmpDataSelection = matches(FileList.sample,'Ice with N2')... + & ~contains(FileList.sample,'(bad data)')... + & contains(FileList.name,'C1s') & FileList.xRayEkinRange_eV(:,1) == 900 ... + & FileList.scientaPassEnergy_eV == 50 ... + & (month(FileList.lastModifiedDatenum) == 2) ... + & (year(FileList.lastModifiedDatenum) == 2022) ... + & (day(FileList.lastModifiedDatenum) >= 27); +FileList = nappBindingEnergyXps(FileList,'tableSelection',tmpDataSelection); +% plot C1s spectra +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',... + 'mode','AllInOne','energyScale','kinetic'); +nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond',... + 'mode','AllInOne','energyScale','binding'); +%% Process data: Combine spectra +% +% To get better statistics (signal-to-noise), repeated measurements can be +% added or averaged into one spectrum. The results are written into a +% matrix with energy in column 1, counts in column2, and standard deviation +% in column 3 (only for mean). So, the nappFunctions can no longer be used +% for this data format. +%% +% +% tmpDataSelection = contains(FileList.name,'C1s')... +% & contains(FileList.sample,'MgO ice AA')... +% & ~endsWith(FileList.sample,'(bad data)')... +% & FileList.sampleTemp_dC >= -26 & FileList.sampleTemp_dC <= -24; +% MgO_C1s_Warm = nappCombineSpectra(FileList,'tableRow',1,... +% 'tableSelection',tmpDataSelection,'tableVariable',... +% 'spectrum_countsPerSecond','EnergyScale','binding','mode','average'); + +%% +close all +tmpDataSelection = contains(FileList.name,'C1s')... + & contains(FileList.sample,'MgO ice AA')... + & ~endsWith(FileList.sample,'(bad data)')... + & FileList.sampleTemp_dC >= -26 & FileList.sampleTemp_dC <= -24; +FileList = nappGenerateSpectra(FileList,tmpDataSelection); +MgO_C1s_Warm = nappCombineSpectra(FileList,'tableRow',1,... + 'tableSelection',tmpDataSelection,'tableVariable',... + 'spectrum_countsPerSecond','EnergyScale','kinetic','mode','average'); +figure +% axes('Parent',gcf,'XDir','reverse') +hold(gca,'on'); +plot(MgO_C1s_Warm(:,1),MgO_C1s_Warm(:,2),'--','linewidth',2) +title('acetic acid adsorption') +legend({'ice on MgO, -25°C'},... + 'location','SouthOutside','Orientation','horizontal') +xlim([704,714]); +xlabel('kinetic energy [eV]') +ylabel('PE [counts per second]') + +%% +function [myColorMap, PsiFarbe] = initializeMatlab +%initializeMatlab Sets NappIce specific settings +% Adds Napp files to path and defines file locations for mac, windows, +% and Matlab online (which runs on unix) + +% change working directory +path = matlab.desktop.editor.getActiveFilename; +[filepath,~,~] = fileparts(path); +cd(filepath); + +% The fitting routines writes quite a lot of feedback and warnings. I shut them off. +warning('off','all') +warning off backtrace +warning off verbose + +% Functions and helper files path: +if ismac + % add Napp files to path + addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/Add-Ons'); + addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/nappIce'); +elseif ispc + % add Napp files to path + addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/Add-Ons'); + addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/nappIce'); +elseif isunix + % add Napp files to path + addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/Add-Ons'); + addpath('/Users/bartels-rausch/SwitchDrive/PSI_Matlab/nappIce'); +end + +% Color maps +myColorMap.red = colormap(autumn(7)); +myColorMap.blue = colormap(winter(7)); + +% define PSI cooperate identity colours +PsiFarbe.hellgrau = [226 226 226]/255; +PsiFarbe.mittelgrau = [184 184 184]/255; +PsiFarbe.dunkelgrau = [78 78 77]/255; +PsiFarbe.blaugrau = [236 236 243]/255; % This is actually not a PSI colour +PsiFarbe.gelb = [239 200 37]/255; +PsiFarbe.hellorange = [227 164 31]/255; +PsiFarbe.dunkelorange = [207 92 22]/255; +PsiFarbe.hellrot = [164 36 23]/255; +PsiFarbe.dunkelbraun = [114 85 65]/255; +PsiFarbe.hellbraun = [127 119 47]/255; +PsiFarbe.mittelgruen = [135 150 59]/255; +PsiFarbe.hellgruen = [195 214 47]/255; +PsiFarbe.dunkelgruen = [72 130 33]/255; +PsiFarbe.dunkelrot = [104 47 86]/255; +PsiFarbe.dunkelblau = [37 65 108]/255; +PsiFarbe.mittelgruenblau = [61 164 168]/255; +PsiFarbe.hellblau = [58 162 190]/255; +PsiFarbe.mittelblau = [50 118 158]/255; + +end + + diff --git a/nappIce/HowTo/nappIceHowToData.mat b/nappIce/HowTo/nappIceHowToData.mat new file mode 100644 index 0000000..d712101 Binary files /dev/null and b/nappIce/HowTo/nappIceHowToData.mat differ diff --git a/nappIce/LabView_importData.m b/nappIce/LabView_importData.m new file mode 100644 index 0000000..ce8dab9 --- /dev/null +++ b/nappIce/LabView_importData.m @@ -0,0 +1,157 @@ +function LabView = LabView_importData(fullFileName,varargin) +% +% LabView_importData reads data log ASCII files stored by LabView into +% a Matlab time series. +% +% LabView = LabView_importData(A) imports file A +% and stores its content as time series in a structure called "LabView". +% +% LabView = LabView_importData(A,LabView) imports file A +% and appends its content as time series to the LabView structure. +% +% +% Example +% LabView = LabView_importData('exmpl.dat',LabView) +% +% Input +% * Napp_chamber_file: Complete and absolute path to the Napp chamber log file. +% * LabView: name of output structure. Always call this'LabView' +% +% Output +% * LabView: time series, the name starting with "ts" +% followed by date and time the recording started. +% +% See also LABVIEW_COMBINE, LABVIEW_PLOT, LABVIEW_CUTDATA +% +%% Data Structure +% +% Data structure before 4.3.2019 +% col 1: Date +% col 2: Time +% col 3: Reservoir "Pressure 1" - Unit "1 water" - mbar -> ts.Data:2 +% col 4: Reservoir "Pressure 2" - Unit "2 other" - mbar -> ts.Data:3 +% col 5: Baratron 1 - cell - 1mbar max - mbar -> ts.Data:4 +% col 6: Baratron 2 - cell - 10mbar max - mbar -> ts.Data:8 +% col 7: Baratron 3 - cell - 0.05mbar max - mbar -> ts.Data:9 +% col 8: Baratron 4 - - mbar +% col 9: Temp.Ice Sample - °C -> ts.Data:1 +% col 10: Temp.Heated Sample +% col 11: none +% col 12: Temp. Reservoir "Cooler 1" - °C -> ts.Data:5 +% col 13: Temp. Reservoir "Cooler 2" - °C -> ts.Data:6 +% col 14: Flow He(cryoholder) - l/min -> ts.Data:7 +% col 15: none +% col 16: none +% +% Data structure after 4.3.2019 +% col 1: Date +% col 2: Time +% col 3: Reservoir "Pressure 1" - Unit "1 water" - mbar -> ts.Data:2 +% col 4: Reservoir "Pressure 2" - Unit "2 other" - mbar -> ts.Data:3 +% col 5: Baratron 1 - cell - 1mbar max - mbar -> ts.Data:4 +% col 6: Baratron 2 - cell - 10mbar max - mbar -> ts.Data:8 +% col 7: Baratron 3 - cell - 0.05mbar max - mbar -> ts.Data:9 +% col 8: Baratron 4 - - mbar +% col 9: Temp.Ice Sample - °C -> ts.Data:1 +% col 10: Temp.Heated Sample +% col 11: Temp. Reservoir "Cooler 1" - °C -> ts.Data:5 +% col 12: Temp. Reservoir "Cooler 2" - °C -> ts.Data:6 +% col 13: Flow He(cryoholder) - l/min -> ts.Data:7 +% col 14: Flow gas 1 +% col 15: Pressure chamber - mbar +% col 16: x-position of cryoholder - mm -> ts.Data:10 +% col 17: y-position of cryoholder - mm -> ts.Data:11 +% col 18: z-position of cryoholder - mm -> ts.Data:12 +% col 19: nothing +% col 20: Temp.Sealing - °C -> ts.Data:13 + + +%% + +% Create an InputParser object +p = inputParser; +% Add inputs to the scheme. +defaultAppendToStructure = 0; +addRequired(p,'fullFileName',@isfile); +addOptional(p,'appendToStructure',defaultAppendToStructure,@isstruct); +% Parse the inputs. +parse(p,fullFileName,varargin{:}) + +%% +% get filedate +[~,name,~] = fileparts(p.Results.fullFileName); +tmp = strsplit(name,'_PC'); +filedate = datenum(tmp{1},'yyyy-mm-dd_HH.MM.SS'); + +clearvars name tmp + +%% +% parse structure to append to + +if isstruct(p.Results.appendToStructure) + LabView = p.Results.appendToStructure; +end +%% +if datenum(filedate) <= datenum('04-Mar-2019 13:30:00') + + fid = fopen(p.Results.fullFileName); + data = textscan(fid, ... + '%s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f',... + 'HeaderLines',1); % data file has 2 text columns, followed by 14 numeric columns + fclose(fid); + % define time series + LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]) ... + = timeseries([data{9} data{3} data{4} data{5} data{12} ... + data{13} data{14} data{6} data{7}] , ... + datestr(datenum([char(data{1}), char(data{2})],... + 'dd.mm.yyyyHH:MM:SS'),0)); + LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]).Name ... + = 'Readout Napp Chamber raw signal'; + clear fid ans formatOut nans t x + +elseif datenum(filedate) >= datenum('15-Sep-2021 01:00:00') + + fid = fopen(p.Results.fullFileName); + data = textscan(fid, ... + '%s %s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f',... + 'HeaderLines',1); % + + fclose(fid); + % the date formating in the dat file is really messed up. Try to make + % it consitent with MATLAB. The problem is that MATLAB does not + % understand 1 digit month and hours. + % + % + % Split the date in column 1 into year,month,day + newDateSplit = cellfun(@(x) split(char(x),'/'),data{1},'UniformOutput', false); + % Split the time in column 2 into hours, minutes, seconds + newTimeSplit = cellfun(@(x) split(char(x),':'),data{2},'UniformOutput', false); + % combine both with the am/pm string in column 3 to a new datestring + customDateStr = cellfun(@(x,y,z) [datestr(datenum([str2double(x{3}),str2double(x{1}),str2double(x{2}),str2double(y{1}),str2double(y{2}),str2double(y{3})])), ' ', char(z)], newDateSplit,newTimeSplit,data{3}, 'uniformOutput',false) ; + % define time series + LabView.(['ts_' datestr(customDateStr{1},'YYYYmmdd_HHMM')]) ... + = timeseries([data{10} data{4} data{5} data{6} data{12} ... + data{13} data{14} data{7} data{8} data{17} data{18} data{19} data{21}], ... + customDateStr); + LabView.(['ts_' datestr(customDateStr{1},'YYYYmmdd_HHMM')]).Name ... + = 'Readout Napp Chamber raw signal'; + clearvars fid ans formatOut nans t x new* custom* +else + fid = fopen(p.Results.fullFileName); + data = textscan(fid, ... + '%s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f',... + 'HeaderLines',1); % data file has 2 text columns, followed by 16 numeric columns + fclose(fid); + % define time series + + LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]) ... + = timeseries([data{9} data{3} data{4} data{5} data{11} ... + data{12} data{13} data{6} data{7} data{16} data{17} data{18} data{20}] , ... + datestr(datenum([char(data{1}), char(data{2})],... + 'dd.mm.yyyyHH:MM:SS'),0)); + + LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]).Name ... + = 'Readout Napp Chamber raw signal'; + clear fid ans formatOut nans t x +end +end \ No newline at end of file diff --git a/nappIce/Napp_RH_p.m b/nappIce/Napp_RH_p.m new file mode 100644 index 0000000..540b65a --- /dev/null +++ b/nappIce/Napp_RH_p.m @@ -0,0 +1,38 @@ +function relHum = Napp_RH_p(T_current,partial_pressure_water) +%Napp_RH_p calculates the relative humidity for a given +% temperature and water pressure. +% +% With the relative humidity referenced +% to liquid water (RH_w) as opposed to ice (RH_i), the activity of water +% is: activity_w = RH_{water}/100 +% +% +% * Napp_p_RH(T_current,RH) +% * Napp_p_RH([253.15, 263.15, 273.15],[60, 80, 90]) +% * Napp_p_RH(273.15-20,80) +% +% +% *input* +% T_current in K: temperature +% RH in %: relative humidity (RH_{water}) +% +% *output* +% partial pressure of water in mbar + +%% +% +% *water*: +% NIST webbook: Bridgeman and Aldrich, 1964 give parametrisation from 273 +% to 303 K in bar. log10(p) = A - B/ (T+C). +A = 5.40221; +B = 1838.675; +C = -31.737; + +p_w = 10.^(A - B./(T_current+C)) .* 1E3; % mbar +RH = (partial_pressure_water*100)/p_w; +relHum = RH; + +for i = 1:length(T_current) + fprintf('RH of %.0f percent at %.1f K (%.1f dC) and %.2f mbar .\n',RH,T_current,T_current-273.15,partial_pressure_water) +end +end \ No newline at end of file diff --git a/nappIce/Napp_p_RH.m b/nappIce/Napp_p_RH.m new file mode 100644 index 0000000..d9e3378 --- /dev/null +++ b/nappIce/Napp_p_RH.m @@ -0,0 +1,34 @@ +function Napp_p_RH(T_current,RH) +%Napp_p_RH calculates the partial pressure of water for a given +% temperature and relative humidity. With the relative humidity referenced +% to liquid water (RH_w) as opposed to ice (RH_i), the activity of water +% is: activity_w = RH_{water}/100 +% +% * Napp_p_RH(T_current,RH) +% * Napp_p_RH([253.15, 263.15, 273.15],[60, 80, 90]) +% * Napp_p_RH(273.15-20,80) +% +% +% *input* +% T_current in K: temperature +% RH in %: relative humidity (RH_{water}) +% +% *output* +% partial pressure of water in mbar + +%% +% +% *water*: +% NIST webbook: Bridgeman and Aldrich, 1964 give parametrisation from 273 +% to 303 K in bar. log10(p) = A - B/ (T+C). +A = 5.40221; +B = 1838.675; +C = -31.737; + +p_w = 10.^(A - B./(T_current+C)) .* 1E3; % mbar + + +for i = 1:length(T_current) + fprintf('The partial pressure of water with a RH of %.0f percent at %.1f K (%.1f dC) is %.2f mbar .\n',RH(i),T_current(i),T_current(i)-273.15,p_w(i).*RH(i)./100) +end +end \ No newline at end of file diff --git a/nappIce/Napp_p_ice.m b/nappIce/Napp_p_ice.m new file mode 100644 index 0000000..b1cb7b5 --- /dev/null +++ b/nappIce/Napp_p_ice.m @@ -0,0 +1,49 @@ +function p = Napp_p_ice(T_current) +%Napp_p_ice(T_current) plots the vapour pressure of ice between 200-270 K +% and marks the vapour pressure of ice at a given temperature. It also +% displays the vapour pressure at a temperature of choice in the command +% window. +% +% * Napp_p_ice(T_current) +% * p = Napp_p_ice([253.15, 263.15, 273.15]) +% +% *input* +% T_current in K: temperature of ice; (format: either single numbers or array) +% +% *output* +% vapour pressure of ice in mbar + +%% Water vapour pressure above the ice and in pure liquid water. + +T = 200:0.2:273; % K, temperature range +% Marti, J., and K. Mauersberger, Geophys. Res.Lett., 20, 363?366, 1993. +% gives parameterization from 169 - 273K in Pa. (log10(p)= A1/T+B) +A_1 = -2663.5; +B_1 = 12.537; +p_i = 10.^(A_1./T + B_1).*1E-5.*1E3; % mbar +p = 10.^(A_1./T_current + B_1).*1E-5.*1E3; % mbar + +% plot +figure( 'Name', 'vapour pressure over ice') +axes1 = axes('Parent',gcf,'XDir','reverse','FontSize',16); +box on +hold on +% relative humidity above ice +plot(p_i,T,'LineWidth',2) +xlim([0 6.5]); +ylim([220 275]); +xticks(0:0.5:6.5) +grid on +grid minor +title('vapour pressure over ice'); + +xlabel('p [mbar]'); +ylabel('temperature [K]'); + +%% write to command line +for i = 1:length(T_current) + plot(10.^(A_1./T_current(i) + B_1).*1E-5.*1E3,T_current(i),'x','MarkerSize',25,'LineWidth',3); + text(10.^(A_1./T_current(i) + B_1).*1E-5.*1E3, T_current(i),[' <- ' num2str(T_current(i))],'FontSize',12); + fprintf('The vapour pressure of ice at %.1f K (%.1f dC) is %.2f mbar \n',T_current(i),T_current(i)-273.15,10.^(A_1./T_current(i) + B_1).*1E-5.*1E3) +end +end \ No newline at end of file diff --git a/nappIce/ToBeAdded/EnsureLength.m b/nappIce/ToBeAdded/EnsureLength.m new file mode 100644 index 0000000..f561e5e --- /dev/null +++ b/nappIce/ToBeAdded/EnsureLength.m @@ -0,0 +1,43 @@ +[x1, y1] = prepareCurveData(data1(:,1),data1(:,2)); +[x2, y2] = prepareCurveData(data2(:,1),data2(:,2)); +[x3, y3] = prepareCurveData(data3(:,1),data3(:,2)); + + +% Define equation to fit data +% I use the area Gauss equations here, which I took from the OriginPro +% documentation. https://www.originlab.com/doc/Origin-Help/Gauss-FitFunc +% +% Gauss = area/(width*sqrt(pi/2)) * exp(-2*(x-position)^2/width^2) +% +% where FWHM = width * sqrt(ln(4)) + +% Next, the data will be arranged in a matrix - where all elements need +% to have the same length. Workaround: give both data sets same length. +xLow = [min(x1) min(x2) min(x3)]; +xHigh = [max(x1) max(x2) max(x3)]; +x1start = find(x1 <= min(xHigh),1); +x2start = find(x2 <= min(xHigh),1); +x3start = find(x3 <= min(xHigh),1); +x1end = find(x1 <= max(xLow),1); +x2end = find(x2 <= max(xLow),1); +x3end = find(x3 <= max(xLow),1); +x1 = x1(x1start:x1end); +x2 = x2(x2start:x2end); +x3 = x3(x3start:x3end); +y1 = y1(x1start:x1end); +y2 = y2(x2start:x2end); +y3 = y3(x3start:x3end); + +% if - for any reason - the 3 vectors have different scaling, they might +% end up with different sizes. Here is a workaround +sizeOfX = [size(x1,1) size(x2,1) size(x3,1)]; % find size of each X +if range(sizeOfX) ~= 0 % cut all to shortest range + x1 = x1(1:min(sizeOfX)); + x2 = x2(1:min(sizeOfX)); + x3 = x3(1:min(sizeOfX)); + y1 = y1(1:min(sizeOfX)); + y2 = y2(1:min(sizeOfX)); + y3 = y3(1:min(sizeOfX)); +end +clearvars sizeOfX + diff --git a/nappIce/ToBeAdded/XPS_MeanSeqIterations.m b/nappIce/ToBeAdded/XPS_MeanSeqIterations.m new file mode 100644 index 0000000..606361a --- /dev/null +++ b/nappIce/ToBeAdded/XPS_MeanSeqIterations.m @@ -0,0 +1,76 @@ +function datafile = XPS_MeanSeqIterations(selection_spectra,selection_region, datafile, numberToAverage) +% +% XPS_MeanSeqIterations generates a new data structure by combining and +% averaging a fixed number or sequence interations. This is usefull if for +% example the dwell time was too short to get spectra with a good S/N. +% +% THIS MODIFIES THE RAW DATA in Matlab. +% +% +% XPS = XPS_MeanSeqIterations([346 347],'', XPS); processes +% the first region of spectra 346 and 347. The number of sequence +% iterations to average is determined automatically. +% +% XPS = XPS_MeanSeqIterations([346 347],'', XPS,5); processes +% the first region of spectra 346 and 347. It averages 5 sequence +% iterations. +% +% +% Input +% XPS_background(selection_spectra,selection_region, datafile, hPeaks,excludeBackgroundFit, findPeak,plotFigures) +% * selection_spectra: List of PE spectra to be imported. Numeric list of +% Spectra Number: [25 26] +% * datafile: XPS data structure in workspace. Output from XPS_importData +% function. +% * numberToAverage (optional): Choose how many sequence iterations you +% would like to average. +% +% Output: +% * modified data structure y +% * modified dwellTime meta-data +% * modified sequenceIterations meta-data + +if ~exist('numberToAverage','var') + numberToAverage = 0; +end + + + +for s = 1:length(selection_spectra) + %% Select spectra in data structure + % + + % get list of spectra in data structure + spectraNames = fieldnames(datafile); + % find those that match the spectrum number to be plotted + % (contains gives a list of 0 or 1 for no match and match, resp. and + % find list the rows of matches.) + + + for r = 1:length(selection_region) + + tmp = find(endsWith(spectraNames,[num2str(selection_spectra(s)) char(selection_region(r))])); + if numberToAverage == 0 + % Get the prime factors of the data structure size in the 2nd dimension + % (i.e. number of sequence iterations) + tmp_avnumb = factor(size(datafile.(spectraNames{tmp}).y,2)); + % Use the first prime factor to select number of iterations to + % be averaged. + numberToAverage = tmp_avnumb(1); + end + + % Calculate mean, reshape, and re-size data structure + RM = reshape(datafile.(spectraNames{tmp}).y,... + size(datafile.(spectraNames{tmp}).y,1), numberToAverage, []) ; % Reshape + datafile.(spectraNames{tmp}).y = squeeze(mean(RM,2)) ; + datafile.(spectraNames{tmp}).y_processed = squeeze(mean(RM,2)); + + % update the meta-data + datafile.(spectraNames{tmp}).dwellTime = datafile.(spectraNames{tmp}).dwellTime * numberToAverage; + datafile.(spectraNames{tmp}).sequenceIterations = datafile.(spectraNames{tmp}).sequenceIterations / numberToAverage; + end + +end +disp('*************************************************') +disp('* Voila: XPS_MeanSeqIterations done ! *') +disp('*************************************************') \ No newline at end of file diff --git a/nappIce/addPhotonEnergy.m b/nappIce/addPhotonEnergy.m new file mode 100644 index 0000000..c4fd443 --- /dev/null +++ b/nappIce/addPhotonEnergy.m @@ -0,0 +1,22 @@ +function FileList = addPhotonEnergy(FileList,fileNumber,notesToAdd,dataMonth,dataYear) +%addPhotonEnergy adds the beam lines photon energy to the data table +% +% FileList = addPhotonEnergy(FileList,[1,8:12,26],1000,2,2022); +% +% Input to this function are +% +% * the name of the data table, +% * the file numbers of the SES scans to which the data should be added +% * the photon energy in eV, +% * the month and the year that the data was acquired + +for ii = 1:length(fileNumber) + tmpMatch = (startsWith(FileList.name, sprintf('%04.0f',fileNumber(ii)))) & ... + (month(FileList.lastModifiedDatenum) == dataMonth) &... + (year(FileList.lastModifiedDatenum) == dataYear) &... + (endsWith(FileList.name, '.ibw')); + + FileList(tmpMatch,:).xRayEkin_eV = num2cell(repmat(notesToAdd,size(FileList.xRayEkin_eV(tmpMatch),1),1)); + FileList(tmpMatch,:).xRayEkinRange_eV = repmat([min(notesToAdd) max(notesToAdd)],size(FileList.xRayEkin_eV(tmpMatch),1),1); +end +end \ No newline at end of file diff --git a/nappIce/addSampleNotes.m b/nappIce/addSampleNotes.m new file mode 100644 index 0000000..9c069d2 --- /dev/null +++ b/nappIce/addSampleNotes.m @@ -0,0 +1,52 @@ +function DataTable = addSampleNotes(DataTable,fileNumber,notesToAdd,dataMonth,dataYear,tableSelection) +%addSampleNotes adds a sample description to the data +% +% FileList = addSampleNotes(FileList,44,'Ice with N2 and phenol in Ar (bad data)',2,2022); +% +% Input to this function are +% +% * the name of the data table, +% * the file numbers of the SES scans to which the info should be added +% * a text string describing the sample, +% * the month and the year that the data was aquired +% * optional: 'XPS' or 'NEXAFS' as last input argument to limit to either XPS data or NEXAFS +% data + +% check if "sample" table variable (column) exist, if not add it +existColumn = strcmp('sample',DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.sample = cellstr(repmat(' ',size(DataTable,1),1)); +end + +for ii = 1:length(fileNumber) + if ~exist('tableSelection','var') + % select the data + tmpMatch = (startsWith(DataTable.name, sprintf('%04.0f',fileNumber(ii)))) & ... + (month(DataTable.lastModifiedDatenum) == dataMonth) &... + (year(DataTable.lastModifiedDatenum) == dataYear); + else + if matches(tableSelection,'XPS') + % select the data + tmpMatch = (startsWith(DataTable.name, sprintf('%04.0f',fileNumber(ii)))) & ... + (month(DataTable.lastModifiedDatenum) == dataMonth) &... + (year(DataTable.lastModifiedDatenum) == dataYear) &... + (endsWith(DataTable.name, '.ibw')); + elseif matches(tableSelection,'NEXAFS') + % select the data + tmpMatch = (startsWith(DataTable.name, sprintf('%04.0f',fileNumber(ii)))) & ... + (month(DataTable.lastModifiedDatenum) == dataMonth) &... + (year(DataTable.lastModifiedDatenum) == dataYear)&... + (endsWith(DataTable.name, '.h5')); + end + end + % clear existing data (to prevent 2 entries per field) + existColumn = strcmp('sample',DataTable.Properties.VariableNames); + if any(existColumn) + if ~isempty(DataTable(tmpMatch,:).sample) + DataTable(tmpMatch,:).sample = cellstr(repmat(' ',size(DataTable(tmpMatch,:),1),1)); + end + end + DataTable(tmpMatch,:).sample = cellstr(repmat(notesToAdd,size(DataTable(tmpMatch,:),1),1)); +end +end + diff --git a/nappIce/nappAlignImages.m b/nappIce/nappAlignImages.m new file mode 100644 index 0000000..4af7cc6 --- /dev/null +++ b/nappIce/nappAlignImages.m @@ -0,0 +1,78 @@ +function DataTable = nappAlignImages(DataTable,varargin) +%nappAlignImages shifts each sequence iteration to align images with a +%drifting kinetic energy of the PE features. +% +% FileList = nappAlignImages(FileList,'tableSelection',tmpDataSelection,... +% 'tableVariable','image'); +% +% +% *input* +% FileList: data table +% tableSelection (optional): logical array to filter data table +% tableVariable: choose to process either imageRoh (default) or image data. +% +% *requirements* +% nappAlignImages shifts each sequence iteration using the data given in +% the table variable kineticEnergyShift. These shifts for each sequence +% iteration need to be determined before running this function. Run +% nappDetermineShiftXps first. +% +% *output* +% The table variable image will be overwritten with the shifted +% image. +% +% See also nappDetermineShiftXps.m + +defaultTableVariable = 'imageRoh'; +expectedTableVariable = {'imageRoh','image'}; +defaultTableSelection = true(size(DataTable,1)); + +% Parse input +p = inputParser; +addRequired(p,'DataTable',@istable); +addParameter(p,'tableSelection',defaultTableSelection,@islogical); +addParameter(p,'tableVariable',defaultTableVariable,... + @(x) any(validatestring(x,expectedTableVariable))); +parse(p,DataTable,varargin{:}); + + +% check input (all elements of input variable need to have non-zero size) +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + +if matches(p.Results.tableVariable,'imageRoh') + % interpolate image data + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + for ij = 1:size(DataTable(p.Results.tableSelection,:).imageRoh{ii},2) + tmp_1(:,ij)= ... + interp1(DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}(:)+... + p.Results.DataTable(p.Results.tableSelection,:).kineticEnergyShift{ii}(ij),... + DataTable(p.Results.tableSelection,:).imageRoh{ii}(:,ij),... + DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}(:)); + + end + DataTable(p.Results.tableSelection,:).image{ii}=tmp_1; + clearvars tmp_1 + + end +else + % interpolate image data + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + for ij = 1:size(p.Results.DataTable(p.Results.tableSelection,:).image{ii},2) + + tmp_1(:,ij)= ... + interp1(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(:)+... + p.Results.DataTable(p.Results.tableSelection,:).kineticEnergyShift{ii}(ij),... + p.Results.DataTable(p.Results.tableSelection,:).image{ii}(:,ij),... + p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(:)); + + end + DataTable(p.Results.tableSelection,:).image{ii}=tmp_1; + clearvars tmp_1 + end +end +end + + diff --git a/nappIce/nappAnnotateSurvey.m b/nappIce/nappAnnotateSurvey.m new file mode 100644 index 0000000..18dca06 --- /dev/null +++ b/nappIce/nappAnnotateSurvey.m @@ -0,0 +1,10 @@ +function nappAnnotateSurvey(X,Y,dataObjs,labeltext) +% nappAnnotateSurvey adds region labels to a survey in the topmost figure. +ha = annotation('arrow'); % store the arrow information in ha +ha.Parent = gca; % associate the arrow the the current axes +ha.X = [X X]; % the location in data units +tmp.X=find(dataObjs.XData >= X,1); +tmp.Y=dataObjs.YData(tmp.X); +ha.Y = [tmp.Y+Y tmp.Y+(Y/10)]; +text(X,tmp.Y+Y,labeltext,'HorizontalAlignment','center') +end diff --git a/nappIce/nappBackground.m b/nappIce/nappBackground.m new file mode 100644 index 0000000..77434f6 --- /dev/null +++ b/nappIce/nappBackground.m @@ -0,0 +1,187 @@ + function DataTable = nappBackground(DataTable,varargin) +%nappBackground determines and subtracts the background from PE or XAS spectra +% +% FileList = nappBackground(FileList,energyStart,energyEnd); +% +% FileList = nappBackground(FileList,368,370,'tableSelection',tmpDataSelection,'energyScale','kinetic',... +% 'mode','mean','showFigures','off'); +% +% +% *input* +% FileList: data table +% energyStart: smallest value of energy range to use for background calculation +% (can also be binding energy) +% energyEnd: largest value of energy energy range to use for background calculation +% (can also be binding energy) +% tableSelection (optional): logical array to filter data table +% tableVariable: choose to process either +% 'spectrum_counts','spectrum_countsPerSecond' (default), or +% 'spectrum_countsNorm'. +% mode: mean(default) subtract the mean of the energy range from +% spectrum; linfit subtract a linear regression through the energy range +% from spectrum +% showFigures, on(default): show fit in figure, off do not show fit in +% figure +% energyScale: kinetic(default): work with kinetic energy scale; binding +% works with binding energy scale. +% +% +% *output* +% The table variable passed to the function as tableVariable +% parameter will be overwritten with the background subtracted spectrum. +% +% The function parameters (mode, energyStart, energyEnd) are written +% to the table as log. + + + +% Define conditions and defaults of input +defaultTableVariable = 'spectrum_countsPerSecond'; +expectedTableVariable = {'spectrum_counts','spectrum_countsPerSecond','spectrum_countsNorm'}; +defaultMode = 'mean'; +expectedMode = {'mean','linfit'}; +defaultTableSelection = true(size(DataTable,1),1); +defaultShowFigures = 'on'; +expectedShowFigures = {'on','off'}; +defaultEnergyScale = 'kinetic'; +expectedEnergyScale = {'kinetic','binding','xRay'}; + +% Parse input +p = inputParser; +addRequired(p,'DataTable',@istable); +addRequired(p,'energyStart',@isnumeric) +addRequired(p,'energyEnd',@isnumeric) +addOptional(p,'tableSelection',defaultTableSelection,@islogical); +addParameter(p,'tableVariable',defaultTableVariable,... + @(x) any(validatestring(x,expectedTableVariable))); +addParameter(p,'mode',defaultMode,... + @(x) any(validatestring(x,expectedMode))); +addParameter(p,'showFigures',defaultShowFigures,... + @(x) any(validatestring(x,expectedShowFigures))); +addParameter(p,'energyScale',defaultEnergyScale,... + @(x) any(validatestring(x,expectedEnergyScale))); +parse(p,DataTable,varargin{:}); + +% check input (all elements of input variable need to have non-zero size) +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + +% add empty table variables (if they don't exist) +existColumn = strcmp('logBackgroundRange',DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.logBackgroundRange = NaN(size(DataTable,1),2); +end +existColumn = strcmp('logBackgroundMode',DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.logBackgroundMode = cellstr(repmat(' ',size(p.Results.DataTable,1),1)); +end +existColumn = strcmp('logBackgroundDate',DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.logBackgroundDate = cellstr(repmat(' ',size(p.Results.DataTable,1),1)); +end + + +% repeat this for all columns in input. +for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if contains(p.Results.energyScale,'kinetic') + % LINEAR FIT + if contains(p.Results.mode,'linfit') + disp('linfit not yet supported') + % MEAN + else + b_1 = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii} >= p.Results.energyStart,1); + b_2 = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii} >= p.Results.energyEnd,1); + + if b_2 == 1 + b_2=10; + end + + b_mean = mean(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(b_1:b_2),'omitnan'); + tmp(ii,1) = cellfun(@(x) x-b_mean,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable)(ii),'UniformOutput',false); + + + end + + elseif contains(p.Results.energyScale,'binding') + if contains(p.Results.mode,'linfit') + disp('linfit not yet supported') + % MEAN + else + b_1 = find(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii} <= p.Results.energyStart,1); + b_2 = find(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii} <= p.Results.energyEnd,1); + + if b_2 == 1 + b_2=10; + end + + b_mean = mean(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(b_2:b_1),'omitnan'); + tmp(ii,1) = cellfun(@(x) x-b_mean,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable)(ii),'UniformOutput',false); + + + end + elseif contains(p.Results.energyScale,'xRay') + if contains(p.Results.mode,'linfit') % LINEAR FIT + + % Fit: 'untitled fit 1'. + [xData, yData] = prepareCurveData( p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}, ... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}); + % Set up fittype and options. + ft = fittype( 'poly1' ); + excludedPoints = excludedata( xData, yData, 'domain',[p.Results.energyStart p.Results.energyEnd] ); + fo = fitoptions('Exclude', excludedPoints); + % Fit model to data. + [fitresult, ~] = fit( xData, yData, ft, fo ); + if contains(p.Results.showFigures,'on') + % Plot fit with data. + figure( 'Name', 'fit pre-edge' ); + h = plot( fitresult, xData, yData, excludedPoints ); + xlabel('Photon Energy eV') + ylabel('partial A-M.E.Y.') + grid on + title(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'Interpreter','none') + end + tmp{ii,1} = p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}-fitresult(p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}); + + elseif contains(p.Results.mode,'mean') % mean + + if p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(1) < p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(end) + % prepare Data + + [xData, yData] = prepareCurveData( p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}, ... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}); + % MEAN + b_1 = find(xData >= p.Results.energyStart,1); + b_2 = find(xData >= p.Results.energyEnd,1); + + b_mean = mean(yData(b_1:b_2)); + elseif p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(1) > p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(end) + % prepare Data + [xData, yData] = prepareCurveData( p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}, ... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}); + % MEAN + b_1 = find(xData <= p.Results.energyStart,1); + b_2 = find(xData <= p.Results.energyEnd,1); + + b_mean = mean(yData(b_2:b_1)); + else + disp('Warning: Issue with NEXAFS data or energies') + end + + + tmp(ii,1) = cellfun(@(x) x-b_mean,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable)(ii),'UniformOutput',false); + end + + + end +end + +% fill selected rows +DataTable(p.Results.tableSelection,:).(p.Results.tableVariable) = tmp; +% write log to table +DataTable.logBackgroundMode(p.Results.tableSelection,:) = cellstr(repmat(p.Results.mode,size(p.Results.DataTable(p.Results.tableSelection,:),1),1)); +DataTable.logBackgroundRange(p.Results.tableSelection,:) = repmat([p.Results.energyStart p.Results.energyEnd],size(p.Results.DataTable(p.Results.tableSelection,:),1),1); +DataTable.logBackgroundDate(p.Results.tableSelection,:) = cellstr(repmat(datestr(now),size(p.Results.DataTable(p.Results.tableSelection,:),1),1)); + +end \ No newline at end of file diff --git a/nappIce/nappBackgroundXps.m b/nappIce/nappBackgroundXps.m new file mode 100644 index 0000000..72d5d46 --- /dev/null +++ b/nappIce/nappBackgroundXps.m @@ -0,0 +1,114 @@ +function DataTable = nappBackground(DataTable,varargin) +%nappBackground determines and subtracts the background from PE or XAS spectra +% +% FileList = nappBackground(FileList,energyStart,energyEnd); +% +% FileList = nappBackground(FileList,368,370,'tableSelection',tmpDataSelection,'energyScale','kinetic',... +% 'mode','mean','showFigures','off'); +% +% +% *input* +% FileList: data table +% energyStart: smallest value of energy range to use for background calculation +% (can also be binding energy) +% energyEnd: largest value of energy energy range to use for background calculation +% (can also be binding energy) +% tableSelection (optional): logical array to filter data table +% tableVariable: choose to process either +% 'spectrum_counts','spectrum_countsPerSecond' (default), or +% 'spectrum_countsNorm'. +% mode: mean(default) subtract the mean of the energy range from +% spectrum; linfit subtract a linear regression through the energy range +% from spectrum +% showFigures, on(default): show fit in figure, off do not show fit in +% figure +% energyScale: kinetic(default): work with kinetic energy scale; binding +% works with binding energy scale. +% +% +% *output* +% The table variable passed to the function as tableVariable +% parameter will be overwritten with the background subtracted spectrum. +% +% The function parameters (mode, energyStart, energyEnd) are written +% to the table as log. + + + +% Define conditions and defaults of input +defaultTableVariable = 'spectrum_countsPerSecond'; +expectedTableVariable = {'spectrum_counts','spectrum_countsPerSecond','spectrum_countsNorm'}; +defaultMode = 'mean'; +expectedMode = {'mean','linfit'}; +defaultTableSelection = true(size(DataTable,1),1); +defaultShowFigures = 'on'; +expectedShowFigures = {'on','off'}; +defaultEnergyScale = 'kinetic'; +expectedEnergyScale = {'kinetic','binding'}; + +% Parse input +p = inputParser; + addRequired(p,'DataTable',@istable); + addRequired(p,'energyStart',@isnumeric) + addRequired(p,'energyEnd',@isnumeric) + addOptional(p,'tableSelection',defaultTableSelection,@islogical); + addParameter(p,'tableVariable',defaultTableVariable,... + @(x) any(validatestring(x,expectedTableVariable))); + addParameter(p,'mode',defaultMode,... + @(x) any(validatestring(x,expectedMode))); + addParameter(p,'showFigures',defaultShowFigures,... + @(x) any(validatestring(x,expectedShowFigures))); +addParameter(p,'energyScale',defaultEnergyScale,... + @(x) any(validatestring(x,expectedEnergyScale))); +parse(p,DataTable,varargin{:}); + + % check input (all elements of input variable need to have non-zero size) +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + + % repeat this for all columns in input. +for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if contains(p.Results.energyScale,'kinetic') + % LINEAR FIT + if contains(p.Results.mode,'linfit') + disp('linfit not yet supported') + % MEAN + else + b_1 = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii} >= p.Results.energyStart,1); + b_2 = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii} >= p.Results.energyEnd,1); + + if b_2 == 1 + b_2=10; + end + + b_mean = mean(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(b_1:b_2),'omitnan'); + tmp(ii,1) = cellfun(@(x) x-b_mean,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable)(ii),'UniformOutput',false); + + + end + + elseif contains(p.Results.energyScale,'binding') + if contains(p.Results.mode,'linfit') + disp('linfit not yet supported') + % MEAN + else + b_1 = find(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii} <= p.Results.energyStart,1); + b_2 = find(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii} <= p.Results.energyEnd,1); + + if b_2 == 1 + b_2=10; + end + + b_mean = mean(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(b_2:b_1),'omitnan'); + tmp(ii,1) = cellfun(@(x) x-b_mean,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable)(ii),'UniformOutput',false); + + + end + end +end +% fill selected rows +DataTable(p.Results.tableSelection,:).(p.Results.tableVariable) = tmp; + +end \ No newline at end of file diff --git a/nappIce/nappBindingEnergyXps.m b/nappIce/nappBindingEnergyXps.m new file mode 100644 index 0000000..de26fe1 --- /dev/null +++ b/nappIce/nappBindingEnergyXps.m @@ -0,0 +1,69 @@ +function DataTable = nappBindingEnergyXps(DataTable,varargin) +%nappBindingEnergyXps calculates the binding energy scale for spectra based +%on the binding energy shift. +% +% *Requirement* +% Needs table variable bindingEnergyShift as input. Run +% nappDetermineShiftXps.m or nappCopyShift.m first +% +% FileList = nappBindingEnergyXps(FileList,'tableSelection',... +% tmpDataSelection); +% +% +% *input* +% FileList: data table +% tableSelection (optional): logical array to filter data table +% tableVariable: choose to process either +% 'spectrum_counts','spectrum_countsPerSecond' (default) +% +% +% *output* +% new table variable bindingEnergy_eV holding the binding energy for +% the data. +% +% +% See also nappnappAlignImages.m nappBindingEnergyXps nappFitGaussXps.m +% nappCopyShift.m nappDetermineShiftXps.m + +defaultTableVariable = 'spectrum_countsPerSecond'; +expectedTableVariable = {'spectrum_counts','spectrum_countsPerSecond'}; +defaultTableSelection = true(size(DataTable,1),1); + +% Parse input +p = inputParser; +addRequired(p,'DataTable',@istable); +addParameter(p,'tableSelection',defaultTableSelection,@islogical); +addParameter(p,'tableVariable',defaultTableVariable,... + @(x) any(validatestring(x,expectedTableVariable))); +parse(p,DataTable,varargin{:}); + +% check input (all elements of input variable need to have non-zero size) +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + +% add empty variable to table +existColumn = strcmp('bindingEnergy_eV',DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.bindingEnergy_eV = cell(size(DataTable,1),1); +end + +if any(isnan(cell2mat(p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV))) + disp('Opps, X-ray energy is empty. Please add manually. Will stop now'); + return +end + + % repeat this for all columns in input. + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + %% + if isnan(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergyShift(ii)) + tmp_2(:,1) = p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii} - p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}; + else + tmp_2(:,1) = p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii} - p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii} - p.Results.DataTable(p.Results.tableSelection,:).bindingEnergyShift(ii); + end + tmp_3{ii,1} =tmp_2; + clearvars tmp_2 + end + DataTable.bindingEnergy_eV(p.Results.tableSelection,:) = tmp_3; +end diff --git a/nappIce/nappCombineSpectra.m b/nappIce/nappCombineSpectra.m new file mode 100644 index 0000000..d5b4ed5 --- /dev/null +++ b/nappIce/nappCombineSpectra.m @@ -0,0 +1,100 @@ +function combinedSpectrum = nappCombineSpectra(DataTable,varargin) +%nappCombineSpectra combines selected PE or NEXAFS spectra into one. Data +%are intrapolated along x-axis. +% +% MgO_C1s_Warm = nappCombineSpectra(FileList,'tableRow',1,... +% 'tableSelection',tmpDataSelection,'tableVariable',... +% 'spectrum_countsNorm','EnergyScale','binding','mode','average'); +% +% *input* +% FileList: data table +% tableSelection (optional): logical array to filter data table +% tableVariable (optional): select source: 'nexafsSpectrum','spectrum_counts','spectrum_countsPerSecond',... +% 'spectrum_countsNorm','nexafsSpectrumPreBackground','nexafsSpectrumPreNorm',... +% 'nexafsSpectrumPreGasPhase','nexafsSpectrumPreI0','nexafsSpectrumPreAdvCarb' +% tableRow (optional): default 1. Defines the row in filtered table (to be +% processed). The x-axis of that data set will be used for interpolation. +% mode: mean (default) averages the spectra; sum adds them, subtract not +% coded yet. +% energyScale (optional): kinetic (default) or binding energy scale; only relevant +% for PE spectra, not for NEXAFS +% +% +% *output* +% a matrix with energy in column 1, counts in column2, and standard +% deviation in column 3 (only for mean). +% + + +expectedTableVariable = {'nexafsSpectrum','spectrum_counts','spectrum_countsPerSecond',... + 'spectrum_countsNorm','nexafsSpectrumPreBackground','nexafsSpectrumPreNorm',... + 'nexafsSpectrumPreGasPhase','nexafsSpectrumPreI0','nexafsSpectrumPreAdvCarb'}; +defaultTableSelection = true(size(DataTable,1)); +defaultTableRow = 1; +defaultMode = 'sum'; +expectedMode = {'sum','average','subtract'}; +defaultEnergyScale = 'kinetic'; +expectedEnergyScale = {'kinetic','binding','xRay'}; + + +% Parse input +p = inputParser; +addRequired(p,'DataTable',@istable); +addParameter(p,'tableSelection',defaultTableSelection,@islogical); +addParameter(p,'tableRow',defaultTableRow,@isnumeric); +addParameter(p,'tableVariable',... + @(x) any(validatestring(x,expectedTableVariable))); +addParameter(p,'mode',defaultMode,... + @(x) any(validatestring(x,expectedMode))); +addParameter(p,'energyScale',defaultEnergyScale,... + @(x) any(validatestring(x,expectedEnergyScale))); + +parse(p,DataTable,varargin{:}); + +% check input (all elements of input variable need to have non-zero size) +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + +if (contains(p.Results.tableVariable,'counts')) && (contains(p.Results.energyScale,'kinetic')) + tmpX = p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV; +elseif (contains(p.Results.tableVariable,'counts')) && (contains(p.Results.energyScale,'binding')) + tmpX = p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV; +elseif contains(p.Results.tableVariable,'counts') && (contains(p.Results.energyScale,'xRay')) + tmpX = p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV; +end + + + if contains(p.Results.energyScale,'binding') + tmpStart = min(cellfun(@(x) x(1), tmpX)); + tmpEnd = max(cellfun(@(x) x(end), tmpX)); + tmpStartIndex = find(tmpX{p.Results.tableRow} <= tmpStart,1); + tmpEndIndex = find(tmpX{p.Results.tableRow} <= tmpEnd,1); + else + tmpStart = max(cellfun(@(x) x(1), tmpX)); + tmpEnd = min(cellfun(@(x) x(end), tmpX)); + tmpStartIndex = find(tmpX{p.Results.tableRow} >= tmpStart,1); + tmpEndIndex = find(tmpX{p.Results.tableRow} >= tmpEnd,1); + end + + xq = tmpX{p.Results.tableRow}(tmpStartIndex:tmpEndIndex); + % repeat this for all columns in input. + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + x = tmpX{ii}; + v = p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}; + vq(:,ii) = interp1(x,v,xq); + end + + + +combinedSpectrum(:,1) = xq; +if contains(p.Results.mode,'sum') + combinedSpectrum(:,2) = sum(vq,2); +elseif contains(p.Results.mode,'average') + combinedSpectrum(:,2) = mean(vq,2); + combinedSpectrum(:,3) = std(vq,0,2); +elseif contains(p.Results.mode,'subtract') + disp('Not supported yet') % FIXME: subtraction is not implemented yet. +end +end diff --git a/nappIce/nappCopyShift.m b/nappIce/nappCopyShift.m new file mode 100644 index 0000000..6e586e0 --- /dev/null +++ b/nappIce/nappCopyShift.m @@ -0,0 +1,99 @@ +function DataTable = nappCopyShift(DataTable,varargin) +%nappBindingEnergyXps calculates the binding energy scale for spectra based +%on the binding energy shift. +% +% For each spectrum with a given file number, the function copies the shift from data of a specified +% region to another region of choice. +% +% *Requirement* +% Needs table variable bindingEnergyShift as input. Run +% nappDetermineShiftXps.m first on selected region. +% +% FileList = nappCopyShift(FileList,tmpDataSelection,'energyScale','binding'); +% +% *input* +% FileList: data table +% tableSelection (optional): logical array to filter data table +% regionOld: O1s (default) or C1s - source of shift data +% regionNew: C1s (default), N1s or O1s - shift data will be copied to this +% region +% energyScale: kinetic (default) or binding: process either the kinetic +% (for images) or the binding energy shift data (for spectra) +% +% *output* +% Table variable bindingEnergy_eV holding the binding energy for +% the data. +% +% See also nappnappAlignImages.m nappBindingEnergyXps nappFitGaussXps.m +% nappCopyShift.m nappDetermineShiftXps.m + +% Define conditions and defaults of input +% Old region must be also selected in tableSelection! it is kind like +% double. +defaultRegionOld = 'O1s'; +expectedRegionOld = {'O1s','C1s','N1s'}; +defaultRegionNew = 'C1s'; +expectedRegionNew = {'O1s','C1s','N1s','Cl2p'}; +defaultTableSelection = true(size(DataTable,1)); +defaultEnergyScale = 'kinetic'; +expectedEnergyScale = {'kinetic','binding'}; + + +% Parse input +p = inputParser; +addRequired(p,'DataTable',@istable); +addOptional(p,'tableSelection',defaultTableSelection,@islogical); +addParameter(p,'regionOld',defaultRegionOld,... + @(x) any(validatestring(x,expectedRegionOld))); +addParameter(p,'regionNew',defaultRegionNew,... + @(x) any(validatestring(x,expectedRegionNew))); +addParameter(p,'energyScale',defaultEnergyScale,... + @(x) any(validatestring(x,expectedEnergyScale))); +parse(p,DataTable,varargin{:}); + +if contains(p.Results.energyScale,'kinetic') + % repeat this for all columns in input. + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + % get name and date + tmpName = replace(p.Results.DataTable(p.Results.tableSelection,:).name{ii}, ... + p.Results.regionOld,p.Results.regionNew); + tmpDate = p.Results.DataTable(p.Results.tableSelection,:).lastModifiedDatenum(ii); + % select spectra + tmpDataSelection = contains(p.Results.DataTable.name,tmpName)... + & ismember(year(p.Results.DataTable.lastModifiedDatenum),year(tmpDate))... + & ismember(month(p.Results.DataTable.lastModifiedDatenum),month(tmpDate))... + & ismember(day(p.Results.DataTable.lastModifiedDatenum),day(tmpDate))... + & ismember(hour(p.Results.DataTable.lastModifiedDatenum),hour(tmpDate))... + & ismember(minute(p.Results.DataTable.lastModifiedDatenum),minute(tmpDate)); + + if ~any(tmpDataSelection) == 1 + disp('There is something wrong with the data time info') + disp(tmpName) + end + % replace the region in the name and copy the data + DataTable.kineticEnergyShift(tmpDataSelection,:) = p.Results.DataTable(p.Results.tableSelection,:).kineticEnergyShift(ii); + end +elseif contains(p.Results.energyScale,'binding') + % repeat this for all columns in input. + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + % get name and date + tmpName = replace(p.Results.DataTable(p.Results.tableSelection,:).name{ii}, ... + p.Results.regionOld,p.Results.regionNew); + tmpDate = p.Results.DataTable(p.Results.tableSelection,:).lastModifiedDatenum(ii); + % select spectra + tmpDataSelection = contains(p.Results.DataTable.name,tmpName)... + & ismember(year(p.Results.DataTable.lastModifiedDatenum),year(tmpDate))... + & ismember(month(p.Results.DataTable.lastModifiedDatenum),month(tmpDate))... + & ismember(day(p.Results.DataTable.lastModifiedDatenum),day(tmpDate))... + & ismember(hour(p.Results.DataTable.lastModifiedDatenum),hour(tmpDate))... + & ismember(minute(p.Results.DataTable.lastModifiedDatenum),minute(tmpDate)); + if ~any(tmpDataSelection) == 1 + disp('There is something wrong with the data time info') + disp(tmpName) + end + % replace the region in the name and copy the data + DataTable.bindingEnergyShift(tmpDataSelection,:) = p.Results.DataTable(p.Results.tableSelection,:).bindingEnergyShift(ii); + end +end + +end \ No newline at end of file diff --git a/nappIce/nappDetermineShiftXps.m b/nappIce/nappDetermineShiftXps.m new file mode 100644 index 0000000..1d3d1c5 --- /dev/null +++ b/nappIce/nappDetermineShiftXps.m @@ -0,0 +1,386 @@ +function DataTable = nappDetermineShiftXps(DataTable,varargin) +%nappDetermineShiftXps determines the relative shift of each sequence +%iteration in images or the absolute shift of spectra to a binding energy reference +% +% FileList = nappDetermineShiftXps(FileList,eKinStart,eKinEnd,'tableSelection',tmpDataSelection,... +% 'showFigures','off','tableVariable','spectrum_countsPerSecond','binEnReference',535); +% +% FileList = nappDetermineShiftXps(FileList,'tableSelection',tmpDataSelection,... +% 'showFigures','on','tableVariable','image'); +% +% *input* +% FileList: data table +% eKinStart (optional): smallest value of energy range to use for +% peak fitting. Peak fitting is used to get position of peak +% eKinEnd (optional): largest value of energy energy range to use for +% peak fitting. Peak fitting is used to get position of peak +% tableSelection (optional): logical array to filter data table +% tableVariable: choose to process either +% 'spectrum_counts','spectrum_countsPerSecond' (default), => absolute binding energy shift will be determined or +% ,'image','imageRoh'=> relative kinetic energy shift will be determined. +% binEnReference: Reference BE in eV for spectra energy scale +% kinEnReference: Sequence iteration to which the image should be +% aligned, default is 1. +% minPeakWidth: findpeak parameter, default 0.1 +% minPeakHeight: findpeak parameter, default 0.1 +% movMeanWindow: findpeak parameter, default 1 +% showFigures, on(default): show fit in figure, off do not show fit in figure +% +% +% *output* +% new table variable kineticEnergyShift for images +% new table variable bindingEnergyShift for spectra +% +% +% *ToDo* +% +% FIXME: make use of O1s fit more general => use nappFitGaussXps.m function +% FIXME: Do not use peakfind for image fit => use nappFitGaussXps.m function +% +% +% See also nappnappAlignImages.m nappBindingEnergyXps nappFitGaussXps.m nappCopyShift.m + +defaultKinEnReference = 1; +defaultTableVariable = 'spectrum_countsPerSecond'; +expectedTableVariable = {'spectrum_counts','spectrum_countsPerSecond','image','imageRoh'}; +defaultTableSelection = true(size(DataTable,1)); +defaultMinPeakWidth = 0.1; +defaultMinPeakHeight = 0.1; +defaultMovMeanWindow = 1; +defaultShowFigures = 'off'; +expectedShowFigures = {'on','off'}; + + +%% + +% Parse input +p = inputParser; +addRequired(p,'DataTable',@istable); +addOptional(p,'eKinStart',@isnumeric) +addOptional(p,'eKinEnd',@isnumeric) +addParameter(p,'binEnReference',@isnumeric) +addParameter(p,'kinEnReference',defaultKinEnReference,@isnumeric) +addParameter(p,'tableSelection',defaultTableSelection,@islogical); +addParameter(p,'minPeakWidth',defaultMinPeakWidth,@isnumeric); +addParameter(p,'minPeakHeight',defaultMinPeakHeight,@isnumeric); +addParameter(p,'movMeanWindow',defaultMovMeanWindow ,@isnumeric); +addParameter(p,'tableVariable',defaultTableVariable,... + @(x) any(validatestring(x,expectedTableVariable))); +addParameter(p,'showFigures',defaultShowFigures,... + @(x) any(validatestring(x,expectedShowFigures))); +parse(p,DataTable,varargin{:}); + +% check input (all elements of input variable need to have non-zero size) +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + +% add empty variable to table +if contains(p.Results.tableVariable,'image') + existColumn = strcmp('kineticEnergyShift',DataTable.Properties.VariableNames); + if ~any(existColumn) + DataTable.kineticEnergyShift = cell(size(DataTable,1),1); + end +else + existColumn = strcmp('bindingEnergyShift',DataTable.Properties.VariableNames); + if ~any(existColumn) + DataTable.bindingEnergyShift = NaN(size(DataTable,1),1); + end +end +%Colors; define PSI cooperate identity colours +PsiFarbe.hellgrau = [226 226 226]/255; +PsiFarbe.mittelgrau = [184 184 184]/255; +PsiFarbe.dunkelgrau = [78 78 77]/255; +PsiFarbe.blaugrau = [236 236 243]/255; % This is actually not a PSI colour +PsiFarbe.gelb = [239 200 37]/255; +PsiFarbe.hellorange = [227 164 31]/255; +PsiFarbe.dunkelorange = [207 92 22]/255; +PsiFarbe.hellrot = [164 36 23]/255; +PsiFarbe.dunkelbraun = [114 85 65]/255; +PsiFarbe.hellbraun = [127 119 47]/255; +PsiFarbe.mittelgruen = [135 150 59]/255; +PsiFarbe.hellgruen = [195 214 47]/255; +PsiFarbe.dunkelgruen = [72 130 33]/255; +PsiFarbe.dunkelrot = [104 47 86]/255; +PsiFarbe.dunkelblau = [37 65 108]/255; +PsiFarbe.mittelgruenblau = [61 164 168]/255; +PsiFarbe.hellblau = [58 162 190]/255; +PsiFarbe.mittelblau = [50 118 158]/255; + +% confirm that X-ray energy is set +if any(isnan(cell2mat(p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV))) + disp('Opps, X-ray energy is empty. Please add manually. Will stop now'); + return +end +if matches(p.Results.tableVariable,'image') + % repeat this for all columns in input. + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + %% + try + if isnumeric(p.Results.eKinStart) + start = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}... + >= p.Results.eKinStart,1); + stop = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}... + >= p.Results.eKinEnd,1); + else + start = 1; + stop = length(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}); + end + catch + warning('There is something wrong with the eKinStart and/or eKinEnd parameters'); + disp('There is something wrong with the eKinStart and/or eKinEnd parameters'); + end + + for ij = 1:size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2) + [B,x1,y1] = GaussFitOnePeak([p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(start:stop)',... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(start:stop,ij)]); + tmp_1(ij) = p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}-B(3); + % plot result + if matches(p.Results.showFigures,'on') + % define equations to be plotted + Gauss = @(x,Hgt, Pos, Wdt) Hgt./(Wdt.*sqrt(pi/2))*exp(-2.*((x - Pos).^2/Wdt.^2)); + linear = @(x,slp,intrcpt) slp*x+intrcpt; + figure( 'Name', 'Gauss Multi Fit ') + tiledlayout(1,1) + nexttile; + %Define gauss peaks with hight, position, width from fitting results + yData_pk1= Gauss(x1 ,B(1), B(3), B(2)); + yData_pk2= Gauss(x1 ,B(4), B(6), B(5)); + bkgrd = linear(x1,B(7),B(8)); + % plot data + plot(x1,y1,'.') + hold on + % plot fit + h = plot(x1,yData_pk1+yData_pk2+bkgrd); + h.LineWidth=2; + h.Color = PsiFarbe.dunkelblau; + % plot each gauss peak + h = plot(x1,yData_pk1+bkgrd); + h.LineWidth=1.5; + h.Color = PsiFarbe.gelb; + h = plot(x1,yData_pk2+bkgrd); + h.LineWidth=1.5; + h.Color = PsiFarbe.gelb; + + legend OFF + xlabel('Kinetic Energy [eV]'); + ylabel('PE intensity [-]'); + grid on + + % List results in table + + disp('Results'); + disp(' ' ); + disp(cell2table({sprintf('%.1f',B(3)),... + sprintf('%.1f',B(2)*sqrt(log(4))),... + sprintf('%.1f',B(2)),... + sprintf('%7.0f',B(1))},... + 'VariableNames',{'position';'FWHW';'width';'area'},... + 'RowNames',{'pk 1'})); + end + end + %% + + + DataTable(p.Results.tableSelection,:).kineticEnergyShift{ii} = tmp_1-tmp_1(p.Results.kinEnReference); + clearvars tmp_1 + fh = findobj( 'Type', 'Figure', 'Name', 'Gauss Multi Fit '); + close(fh) + fh = findobj( 'Type', 'Figure', 'Name', 'GlobalSearch'); + close(fh) + end +elseif matches(p.Results.tableVariable,'imageRoh') + % repeat this for all columns in input. + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + + %% + try + if isnumeric(p.Results.eKinStart) && isempty(DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}) + start = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}... + >= p.Results.eKinStart,1); + stop = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}... + >= p.Results.eKinEnd,1); + elseif isnumeric(p.Results.eKinStart) && ~isempty(DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}) + start = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}... + >= p.Results.eKinStart,1); + stop = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}... + >= p.Results.eKinEnd,1); + elseif isempty(DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}) + start = 1; + stop = length(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}); + else + start = 1; + stop = length(DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}); + end + catch + warning('There is something wrong with the eKinStart and/or eKinEnd parameters'); + disp('There is something wrong with the eKinStart and/or eKinEnd parameters'); + end + for ij = 1:size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2) + if isempty(DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}) + [B,x1,y1] = GaussFitOnePeak([p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(start:stop)',... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(start:stop,ij)]); + else + [B,x1,y1] = GaussFitOnePeak([DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}(start:stop)',... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(start:stop,ij)]); + end + + tmp_1(ij) = p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}-B(3); + % plot result + if matches(p.Results.showFigures,'on') + % define equations to be plotted + Gauss = @(x,Hgt, Pos, Wdt) Hgt./(Wdt.*sqrt(pi/2))*exp(-2.*((x - Pos).^2/Wdt.^2)); + linear = @(x,slp,intrcpt) slp*x+intrcpt; + figure( 'Name', 'Gauss Multi Fit ') + tiledlayout(1,1) + nexttile; + %Define gauss peaks with hight, position, width from fitting results + yData_pk1= Gauss(x1 ,B(1), B(3), B(2)); + yData_pk2= Gauss(x1 ,B(4), B(6), B(5)); + bkgrd = linear(x1,B(7),B(8)); + % plot data + plot(x1,y1,'.') + hold on + % plot fit + h = plot(x1,yData_pk1+yData_pk2+bkgrd); + h.LineWidth=2; + h.Color = PsiFarbe.dunkelblau; + % plot each gauss peak + h = plot(x1,yData_pk1+bkgrd); + h.LineWidth=1.5; + h.Color = PsiFarbe.gelb; + h = plot(x1,yData_pk2+bkgrd); + h.LineWidth=1.5; + h.Color = PsiFarbe.gelb; + + legend OFF + xlabel('Kinetic Energy [eV]'); + ylabel('PE intensity [-]'); + grid on + + % List results in table + + disp('Results'); + disp(' ' ); + disp(cell2table({sprintf('%.1f',B(3)),... + sprintf('%.1f',B(2)*sqrt(log(4))),... + sprintf('%.1f',B(2)),... + sprintf('%7.0f',B(1))},... + 'VariableNames',{'position';'FWHW';'width';'area'},... + 'RowNames',{'pk 1'})); + end + end + %% + + DataTable(p.Results.tableSelection,:).kineticEnergyShift{ii} = tmp_1-tmp_1(p.Results.kinEnReference); + clearvars tmp_1 + fh = findobj( 'Type', 'Figure', 'Name', 'Gauss Multi Fit '); + close(fh) + fh = findobj( 'Type', 'Figure', 'Name', 'GlobalSearch'); + close(fh) + end +else + % repeat this for all columns in input. + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + %% + try + if isnumeric(p.Results.eKinStart) + start = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}... + >= p.Results.eKinStart,1); + stop = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}... + >= p.Results.eKinEnd,1); + else + start = 1; + stop = length(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}); + end + catch + warning('There is something wrong with the eKinStart and/or eKinEnd parameters'); + disp('There is something wrong with the eKinStart and/or eKinEnd parameters'); + end + if contains(p.Results.showFigures,'on') + figure + + findpeaks(movmean(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(start:stop),... + p.Results.movMeanWindow),... + p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(start:stop),... + 'MinPeakWidth',p.Results.minPeakWidth,'MinPeakHeight',p.Results.minPeakHeight) + end + [pks,locs]=findpeaks(movmean(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(start:stop),... + p.Results.movMeanWindow),... + p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(start:stop),... + 'MinPeakWidth',p.Results.minPeakWidth,'MinPeakHeight',p.Results.minPeakHeight); + + %% + + [~,I] = max(pks); + tmp_1(ii,1) = p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}-locs(I)-p.Results.binEnReference; + clearvars tmp_2 + end + + DataTable.bindingEnergyShift(p.Results.tableSelection) = tmp_1; +end + +end +function [B,x1,y1] = GaussFitOnePeak(data1) + + +[x1, y1] = prepareCurveData(data1(:,1),data1(:,2)); + +% make data slimmer so that background makes sense +[~,I] = max(y1); +tmp1 = find(x1>=x1(I)-5,1); +tmp2 = find(x1>=x1(I)+5,1); +if isempty(tmp2) + y1 = y1(tmp1:end); + x1 = x1(tmp1:end); +else + y1 = y1(tmp1:tmp2); + x1 = x1(tmp1:tmp2); +end +[~,I] = max(y1); + +% Define equation to fit data +% I use the area Gauss equations here, which I took from the OriginPro +% documentation. https://www.originlab.com/doc/Origin-Help/Gauss-FitFunc +% +% Gauss = area/(width*sqrt(pi/2)) * exp(-2*(x-position)^2/width^2) +% +% where FWHM = width * sqrt(ln(4)) + +% Data set 1: +yfcn1 = @(b,x)... + b(1)/(b(2)*sqrt(pi/2))*exp(-2.*((x(:,1) - b(3)).^2/b(2).^2)) ... % Gauss peak 1: C-H, Ac- + + b(4)/(b(5)*sqrt(pi/2))*exp(-2.*((x(:,1)- b(6)).^2/b(5).^2))... % Gauss peak 2: C-OOH, Ac- + +b(7).*x(:,1)+b(8); % linear background + +B0 = [80000 1.5 x1(I) ... + 10 1.0 x1(I)-4 ... + 0 0]; + + +% lower bonds +lb = [1000 0.5 x1(I)-1. ... + 10 1.0 x1(I)-5 ... + -Inf -Inf]; + + +% upper bond +ub = [Inf 3 x1(I)+1 ... + 10 1.0 x1(I)-3 ... + Inf Inf]; + + +% Fit equations: Gauss eq. 1 with data +yfcn = @(b,x) yfcn1(b,x); +% We find an optimal fit by minimising the residuals: +fitfcnw = @(b) sum((y1 - yfcn(b,x1)).^2); + +problem = createOptimProblem('fmincon', 'x0',B0, 'lb',lb,'ub',ub, 'objective',fitfcnw); +gs = GlobalSearch('PlotFcns',@gsplotbestf); +B = run(gs,problem); + + + + +end \ No newline at end of file diff --git a/nappIce/nappFileList.m b/nappIce/nappFileList.m new file mode 100644 index 0000000..7e48225 --- /dev/null +++ b/nappIce/nappFileList.m @@ -0,0 +1,1098 @@ +function ListFiles = nappFileList(dataPath,varargin) +% nappFileList lists all XAS, PE, and picture data of a specific beam +% time. Analyser and sample settings such as pass energy, lens mode, +% temperature, position, and pressure are added. +% +% +% * listFiles = nappFileList('2019\April_NanoXAS') imports data from beam +% time folder on local computer, generates a new matlab table 'listFiles' +% in the current workspace, and a csv file from data in the +% 'SC_Data/2019/April_NanoXAS' . +% +% * listFiles = nappFileList('2019\April_NanoXAS',listFiles) imports data from beam +% time folder on local computer, adds data to the existing matlab table +% 'listFiles' in the current workspace, and a csv file from data in the +% 'SC_Data/2019/April_NanoXAS' . +% +% Input Arguments +% +% * dataPath, mandatory: year and name of folder that holds the beam time data. +% Text string with format year/name of folder: '2019/April_NanoXAS' +% * DataTable, optional: DataTable to which imported data is added. +% * 'mode','local'; default: imports from local server address +% * 'mode','nappDrive'; imports from napp drive. Needs to be mounted. +% * 'mode','localNew'; imports only new files that have not yet been +% imported. Needs existing data table as input. +% * 'mode','nappDrivePick'; lets user select files in file browser window. Default address is Napp beam time folder. +% * 'mode','localPick'; lets user select files in file browser window. Default address is local beam time folder. +% +% Dependencies +% +% * beam time folder must be located at server/NAPP/SC Data/dataPath. +% dataPath is user input. server needs to be defined at line ~100 of this +% function. +% * XPS data in igor *.ibw format need to be in SES subfolder +% * Photos in *.bmp format need to be in Photos folder +% * NEXAFS data in *.h5 format need to be in NEXAFS subfolder +% * Labview pressure and temperature log need to be in Pressure subfolder. +% * Uses the IgorPro importer for Matlab: +% https://ch.mathworks.com/matlabcentral/fileexchange/42679-igor-pro-file-format-ibw-to-matlab-variable +% * needs at least 1 .*ibw file in the SES subfolder +% +% +% Output +% +% * ListFiles: Matlab table listing XPS, NEXAFS, and photo files with settings +% * YYYYmmm_DataList.csv (2019Apr_DataList.csv): Semicolon separated ASCII +% file for import to Excel in beamtime folder +% +% +% Further info +% +% * Do not run while SES or NEXAFS data are being recorded. Data will be +% lost by SES software. +% * Region iterations are averaged during import +% * counts are normalised to 1s dwell time during import. That is, the +% counts are in cps after import. +% +% +% Matlab Version +% +% * Matlab 2018a or higher +% +% +% See also TABLE IBWread h5read DIR LabView_importData +% +%% +% +% TODO +% +% * FIXME: Add videos and jpg +% +%% Updated +% +% * January 2020, added new h5 file structure and naming convention. +% * March 2021, added possibility to work on local file structure +% * March 2021, added Lens Mode as column (have not tested this for older +% NEXAFS files). +% * April 2021, X-ray kinetic energy and images are now made unique +% * March 2022, input now using varargin +% * March 2022, strict data structure required for local and remote sources + +%% Input +% Define conditions and defaults of input +defaultMode = 'local'; +expectedMode = {'local','nappDrive','localNew','nappDrivePick','localPick'}; +defaultImportLabView = 'on'; +expectedImportLabView = {'on','off'}; +% Parse input +p = inputParser; +addRequired(p,'dataPath'); +addOptional(p,'DataTable',@istable); +addParameter(p,'mode',defaultMode,... + @(x) any(validatestring(x,expectedMode))); +addParameter(p,'importLabView',defaultImportLabView,... + @(x) any(validatestring(x,expectedImportLabView))); +parse(p,dataPath,varargin{:}); +%% Data Paths +% +% Mac and Windows use different notations to address network drives. For +% windows, we use the UNC naming convention. This is a more recent way to +% address mounted drives that does not rely on the use of drive letters. +% The letters might be different for the same drive on different computer. + + +if contains(p.Results.mode,'local') + % Data server address + if ismac + server = '/Users/bartels-rausch/Forschung_Einsam/PSI_SLS/'; + elseif ispc + server = userpath; + end +elseif contains(p.Results.mode,'nappDrive') + % Data server address + if ismac + server = '/Volumes/'; + elseif ispc + server = '\\fs03\'; + end +end +dataPath = fullfile(server,'NAPP','SC Data',dataPath); +% Data Paths to subdirectories for specific files: +dataPath_XPS = fullfile(dataPath, 'SES'); +dataPath_Photo = fullfile(dataPath, 'Photos'); +dataPath_NEXAFS = fullfile(dataPath, 'NEXAFS'); +dataPath_LabView = fullfile(dataPath, 'Pressure'); + +% +if ~isfolder(dataPath_XPS) + warning('There is something wrong with the path. Check for typo and that the drives are mounted') + disp('There is something wrong with the path. Check for typo and that the drives are mounted') + disp('I quit now') + return +end + + +%% Naming Convention +% +% See: MATLAB Programming Style Guidelines, by Richard Johnson +% +% * Variable: mixed case words starting with lower case: credibleThreat, qualityOfLife +% * Variables with a large scope should have meaningful names. Variables +% with a small scope can have short names. +% * A convention on pluralisation should be followed consistently. +% * Named constants (including globals) should be all uppercase using +% underscore to separate words. MAX_ITERATIONS, COLOR_RED +% * Structure names should begin with a capital letter: SegmentData.length +% * The prefix n should be used for variables representing the number of +% objects. A MATLAB-specific addition is the use of m for number of rows +% (based on matrix notation). nFiles, mRows +% * Iterator variables should be named or prefixed with i. for iPosition = +% 1:nPositions, ii, ij, ik.... +% * Functions should have meaningful names written in lower case. +% computetotalwidth(), Avoid compwid(); +% + + + +%% Query beam time folder content +% +% We use MATLAB's 'dir' command which writes the content of a folder into a +% structure with the following fields: +% +% * name +% * folder +% * date +% * bytes +% * isdir +% * datenum +% +% XPS data: Create a structure 'TmpFileList{1}' with all Igor files in the +% directory and its subfolders (1st level). The '\N*' at the beginning is +% important. Otherwise hidden files starting with a . will also be listed. +% Obviously, Igor file names from SES software and h5 file names from Epics +% (NEXAFS) need to start with an N, otherwise change the search term below: +% +% THE ** notation needs a recent version of Matlab, 2014 does not work. + +if endsWith(p.Results.mode,'Pick') + % select files (Xps or Nexafs, ignoring photos) to be imported from data directory + % (data can be taken from any directory; files need to be in same directory) + [filePick,pathPick] = uigetfile({'*.ibw;*.h5'},... + 'Select One or More Files', dataPath,... + 'MultiSelect', 'on'); + % make lists for Nexafs and for XPS + if ischar(filePick) + filePick = {filePick}; + end + filePickXps = filePick(endsWith(filePick,'.ibw')); + filePickNexafs = filePick(endsWith(filePick,'.h5')); + + if isempty(filePickXps) + TmpFileList{1} = dir([dataPath_XPS filesep '**' filesep '*.trallalla']); + else + for ii = 1:size(filePickXps,2) + TmpFileList{1}(ii,1) = dir([pathPick filePickXps{ii}]); + end + end + if isempty(filePickNexafs) + TmpFileList{2} = dir([dataPath_NEXAFS filesep '**' filesep '*.trallalla']); + else + for ii = 1:size(filePickNexafs,2) + TmpFileList{2}(ii,1) = dir([pathPick filePickNexafs{ii}]); + end + end + % make a empty file list for photos, to be consitent with code + TmpFileList{3} = dir([dataPath_Photo filesep '**' filesep '*.trallalla']); +else + + % SES files in IGOR format list all files, then get rid of system files + TmpFileList{1} = dir([dataPath_XPS filesep '**' filesep '*.ibw']); + TmpFileList{1} = TmpFileList{1}(find(~cellfun(@isempty,regexp({TmpFileList{1}.name},'^[a-zA-Z0-9]\w*')))); %#ok + % EPICS files in h5 format list all files, then get rid of system files + TmpFileList{2} = dir([dataPath_NEXAFS filesep '**' filesep '*.h5']); + TmpFileList{2} = TmpFileList{2}(find(~cellfun(@isempty,regexp({TmpFileList{2}.name},'^[a-zA-Z0-9]\w*')))); %#ok + % Photos list all files, then get rid of system files + TmpFileList{3} = dir([dataPath_Photo filesep '**' filesep '*.bmp']); + TmpFileList{3} = TmpFileList{3}(find(~cellfun(@isempty,regexp({TmpFileList{3}.name},'^[a-zA-Z0-9]\w*')))); %#ok + + % The second line of code filters all files that start with Numbers or + % letters. All system files starting with a . or ~ are discarded. + + % only process new files + if (istable(p.Results.DataTable) & matches(p.Results.mode,'localNew')) % do this only if previous list was input to function call + tmpXpsFiles = endsWith(p.Results.DataTable.name,'.ibw'); % get XPS files in current data table + tmpMissingFiles = ~ismember({TmpFileList{1}(:).name},p.Results.DataTable.name(tmpXpsFiles,:)); % find those files that are yet imported + TmpFileList{1} = TmpFileList{1}(tmpMissingFiles); + + tmpNexafsFiles = endsWith(p.Results.DataTable.name,'.h5'); % get XPS files in current data table + tmpMissingFiles = ~ismember({TmpFileList{2}(:).name},p.Results.DataTable.name(tmpNexafsFiles,:)); % find those files that are yet imported + TmpFileList{2} = TmpFileList{2}(tmpMissingFiles); + + tmpPhotoFiles = endsWith(p.Results.DataTable.name,'.bmp'); % get XPS files in current data table + tmpMissingFiles = ~ismember({TmpFileList{3}(:).name},p.Results.DataTable.name(tmpPhotoFiles,:)); % find those files that are yet imported + TmpFileList{3} = TmpFileList{3}(tmpMissingFiles); + + end +end + + + +% get date of last and first .ibw file in folder . +tmp.fileinfo = dir([dataPath_XPS '/*.ibw']); +if isempty(tmp.fileinfo) + warning('There appears to be no file in the SES folder. Add at least one file first.') + disp('There appears to be no file in the SES folder. Add at least one file first.') + disp('I quit now') + return +end + +try + tmp.fileinfo = dir([dataPath_XPS '/*.ibw']); + filedate_first = tmp.fileinfo(1).datenum; + clearvars name tmp +catch + disp('Error getting ibw file date.') +end + +%% Import XPS data to get SES settings +% +% Uses the IgorPro importer for Matlab: +% https://ch.mathworks.com/matlabcentral/fileexchange/42679-igor-pro-file-format-ibw-to-matlab-variable +% +% Normally, Matlab stops when an error occurs. I use 'try' to force Matlab +% to continue even if an error occurs. Matlab will instead print a warning, +% as defined after the 'catch'. Error might occur when single data files +% can't be read. If a warning comes up, check the corresponding data file +% and try to resolve it. I suggest to rename these original data files that +% are damaged, or not complete (because measurement was aborted) to +% "ignore_filename". + +for ii = 1:size(TmpFileList{1},1) % cycle through each XPS file + + + try + PE = IBWread([TmpFileList{1}(ii).folder filesep TmpFileList{1}(ii).name]); % read XPS file + catch + warning('Problem reading the Igor file') + disp('Problem reading the Igor file') + fprintf('Number %.0f: %s \n',ii,[TmpFileList{1}(ii).folder filesep TmpFileList{1}(ii).name]) + end + fclose('all'); + + try + %% Convert SES meta data into variables + % + % Upon import, all meta data are written into _WaveNotes_ variable. + % Here, I select the meta data for each setting and write those + % into individual variables that are then added to the list. + + % Split the WaveNotes text string into individual strings at each line break. + % (This is a work-around. Did not manage to select values with regexp + % function only.) + tmp = regexp(PE.WaveNotes, '\r', 'split'); + % Then, read out the values into variables using a combination of string operations: + + % Start date/time of measurement + PE.creationDate = datevec([char(regexp(tmp{29},'((?<=Date=).*)','match')) ... + ' ' char(regexp(tmp{30},'((?<=Time=).*)','match'))]); + % Pass energy + PE.passEnergy = str2double(char(regexp(tmp{5},'((?<=Pass Energy=).*)','match'))); + % Dwell time (or step time) + PE.dwellTime = str2double(char(regexp(tmp{15},'((?<=Step Time=).*)','match'))); + % Energy step + PE.scientaEkinStep = str2double(char(regexp(tmp{14},'((?<=Energy Step=).*)','match'))); + % Region name + PE.regionName = char(regexp(tmp{3},'((?<=Region Name=).*)','match')); + % Acquisition Mode + PE.acquisitionMode = char(regexp(tmp{9},'((?<=Acquisition Mode=).*)','match')); + + % kinetic energy + for n = 1:size(PE.y,1) + PE.x(n)= PE.x0(1) + (n-1)*PE.dx(1); + end + % lens mode + PE.lensMode = char(regexp(tmp{4},'((?<=Lens Mode=).*)','match')); + % define iterations + if PE.Ndim == 3 + PE.regionIterations = size(PE.y,2); + PE.sequenceIterations = size(PE.y,3); + else + PE.regionIterations = 1; + PE.sequenceIterations = size(PE.y,2); + end + + % average region iterations + if PE.Ndim == 3 + PE.y = squeeze(mean(PE.y,2)); + end + % normalise data to 1ms + PE.y = PE.y .* 1000 ./ PE.dwellTime; + % Pass energy + PE.passEnergy = str2double(char(regexp(tmp{5},'((?<=Pass Energy=).*)','match'))); + catch + warning('Problem reading the PE variable') + disp('Problem reading the PE variable') + fprintf('Number %.0f: %s \n',ii,[TmpFileList{1}(ii).folder filesep TmpFileList{1}(ii).name]) + end + + %% Write SES meta data variables into XPS FileList structure + + try + TmpFileList{1}(ii).creationDate = PE.creationDate; + TmpFileList{1}(ii).image = PE.y; + TmpFileList{1}(ii).spectrum_counts = NaN; + TmpFileList{1}(ii).spectrum_countsPerSecond = NaN; + TmpFileList{1}(ii).xRayEkin_eV = NaN; + TmpFileList{1}(ii).xRayEkinRange_eV = [NaN NaN]; + % SES pass energy + TmpFileList{1}(ii).scientaPassEnergy_eV = PE.passEnergy; % in eV + % SES dwell time + TmpFileList{1}(ii).scientaDwellTime_ms = PE.dwellTime; % in ms + % SES region Name + TmpFileList{1}(ii).regionName = PE.regionName; + TmpFileList{1}(ii).scientaAcquisitionMode = PE.acquisitionMode; + % SES kinetic energy window + TmpFileList{1}(ii).scientaEkinRange_eV = [PE.x(1) PE.x(end)]; + TmpFileList{1}(ii).scientaEkinStep_eV = PE.scientaEkinStep; + TmpFileList{1}(ii).scientaEkin_eV = PE.x; + % Beamline Intensity (I0 during NEXAFS) + TmpFileList{1}(ii).beamlineInt = cell(1); + % SES lens mode + TmpFileList{1}(ii).scientaLensMode = PE.lensMode; + TmpFileList{1}(ii).scientaRegionIterations = PE.regionIterations; + TmpFileList{1}(ii).scientaSequenceIterations = PE.sequenceIterations; + TmpFileList{1}(ii).imageRoh = PE.y; + TmpFileList{1}(ii).spectrum_countsPerSecondRoh = NaN; + TmpFileList{1}(ii).importDate = datestr(now); + try + TmpFileList{1}(ii).analysisDir = file.mFile; + catch + TmpFileList{1}(ii).analysisDir = pwd; + end + catch + warning('Problem with a XPS data file for XPS list') + disp('Problem with a XPS data file for XPS list') + fprintf('Number %.0f: %s \n',ii,[TmpFileList{1}(ii).folder filesep TmpFileList{1}(ii).name]) + fprintf('Number %.0f: %s \n',ii,datestr(TmpFileList{1}(ii).datenum)) + end + +end +disp('*************************************************') +disp('* Voila: Done reading & writing XPS data! *') +disp('*************************************************') + + +%% Read and write NEXAFS meta data +% +% The h5 file is much nicer organised, so we do not need string operations +% to select individual meta data. The data can be directly addressed and +% written into the list structure: + +if datenum(filedate_first) >= datenum('31-Dec-2019 23:59:00') + for ii = 1:size(TmpFileList{2},1) % do this for each list element + + %if ~isempty(h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/energy')) + % creation date of file + TmpFileList{2}(ii).creationDate = datevec(NaN); + try + % read data + %if datenum(filedate_first) <= datenum('21-Nov-2020 00:01:00') % Date not exaclty certain. + try + TmpImage= h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/spectrum'); + %else + catch + TmpImage = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/scienta spectrum'); + end + % 21.8.20 changed from spectrum to scienta spectrum, later + % switched back to scienta. + + % Spectrum + TmpFileList{2}(ii).spectrum_counts = NaN; + TmpFileList{2}(ii).spectrum_countsPerSecond = NaN; + + % import Photon Energy (cols) + TmpXrayEkin = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/energy'); % X-ray excitation energy; Photon energy in eV + TmpXrayEkin(TmpXrayEkin==0)=[]; + + if isempty(TmpXrayEkin) + TmpFileList{2}(ii).xRayEkinRange_eV = [NaN NaN]; + else + TmpFileList{2}(ii).xRayEkinRange_eV = [TmpXrayEkin(1) TmpXrayEkin(end)]; + end + + % Make unique + [TmpFileList{2}(ii).xRayEkin_eV, ind] = unique(TmpXrayEkin); + TmpFileList{2}(ii).image = TmpImage(:,ind); + + % NEXAFS pass energy + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/attrs/PassEnergy'); % in eV + TmpFileList{2}(ii).scientaPassEnergy_eV = str2double(tmp(1)); + + + % NEXAFS dwell time + if datenum(filedate_first) >= datenum('1-Feb-2020 23:59:00') + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/attrs/ScientaStepTime')*1000; % in ms + + else + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/attrs/StepTime')*1000; % in ms + end + TmpFileList{2}(ii).scientaDwellTime_ms = tmp(1); + % NEXAFS region Name + if TmpFileList{2}(ii).xRayEkinRange_eV(:,1) <= 530 && TmpFileList{2}(ii).xRayEkinRange_eV(:,2) >= 530 + TmpFileList{2}(ii).regionName = 'O K-edge NEXAFS'; + else + TmpFileList{2}(ii).regionName = 'NEXAFS'; + end + + % Acquisition mode + TmpFileList{2}(ii).scientaAcquisitionMode = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/attrs/AcquisitionMode'); + if strcmp(TmpFileList{2}(ii).scientaAcquisitionMode,'Fixed') + % NEXAFS kinetic energy window - fixed mode + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/attrs/ScientaCenterEnergy'); % in eV + TmpFileList{2}(ii).scientaEkinRange_eV = [tmp(1)-TmpFileList{2}(ii).scientaPassEnergy_eV/20 tmp(1)+TmpFileList{2}(ii).scientaPassEnergy_eV/20]; + TmpFileList{2}(ii).scientaEkinStep_eV = NaN; + TmpFileList{2}(ii).scientaEkin_eV = linspace(TmpFileList{2}(ii).scientaEkinRange_eV(:,1)... + ,TmpFileList{2}(ii).scientaEkinRange_eV(:,2),size(TmpFileList{2}(ii).image,1))'; + else + % NEXAFS kinetic energy window - scan mode + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/attrs/ScientaLowEnergy'); % in eV + tmp2 = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/attrs/ScientaHighEnergy'); + TmpFileList{2}(ii).scientaEkinRange_eV = [tmp(1) tmp2(1)]; + TmpFileList{2}(ii).scientaEkinStep_eV = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/attrs/StepSize'); + TmpFileList{2}(ii).scientaEkin_eV = [TmpFileList{2}(ii).scientaEkinRange_eV(:,1):TmpFileList{2}(ii).scientaEkinStep_eV(1):TmpFileList{2}(ii).scientaEkinRange_eV(:,2)]'; + end + + % read I_0 + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/i0'); + TmpFileList{2}(ii).beamlineInt = abs(tmp(ind)); + + % Lens Mode + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/attrs/LensMode'); + TmpFileList{2}(ii).scientaLensMode = tmp{1}; + clearvars tmp + + TmpFileList{2}(ii).scientaRegionIterations = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/scan 1/attrs/NumIterations'); + TmpFileList{2}(ii).scientaSequenceIterations = 1; + + catch + warning('Problem with a NEXAFS data file in NEXAFS list') + disp('Problem with a NEXAFS data file in NEXAFS list') + fprintf('Number %.0f: %s \n',ii,[TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name]) + fprintf('Number %.0f: %s \n',ii,datestr(TmpFileList{2}(ii).datenum)) + end + + TmpFileList{2}(ii).imageRoh = TmpFileList{2}(ii).image; + TmpFileList{2}(ii).spectrum_countsPerSecondRoh = TmpFileList{2}(ii).spectrum_countsPerSecond; + % log + TmpFileList{2}(ii).importDate = datestr(now); + try + TmpFileList{2}(ii).analysisDir = file.mFile; + catch + TmpFileList{2}(ii).analysisDir = pwd; + end + end + %end +else + for ii = 1:size(TmpFileList{2},1) % do this for each list element + try + % NEXAFS pass energy + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/entry/instrument/NDAttributes/PassEnergy'); % in eV + % TODO: Confirm that this assignment is correct. (The number refer to the list number in epics software) + if tmp(1) == 1 + TmpFileList{2}(ii).passEnergy_eV = {[20]}; + elseif tmp(1) == 2 + TmpFileList{2}(ii).passEnergy_eV = {[50]}; + elseif tmp(1) == 3 + TmpFileList{2}(ii).passEnergy_eV = {[100]}; + elseif tmp(1) == 4 + TmpFileList{2}(ii).passEnergy_eV = {[200]}; + end + + % NEXAFS dwell time + if datenum(filedate_first) >= datenum('1-Feb-2020 23:59:00') + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/entry/instrument/NDAttributes/ScientaStepTime')*1000; % in ms + + else + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/entry/instrument/NDAttributes/StepTime')*1000; % in ms + end + TmpFileList{2}(ii).dwellTime_ms = tmp(1); + % NEXAFS region Name + TmpFileList{2}(ii).regionName = 'NEXAFS'; + % FIXME: Can we differentiate O K-edge, N K-edge, C K-edge based on the h5-file meta data? + + % NEXAFS kinetic energy window + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/entry/instrument/NDAttributes/LowEnergy'); % in eV + tmp2 = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/entry/instrument/NDAttributes/HighEnergy'); + TmpFileList{2}(ii).kinRange_eV = [tmp(1) tmp2(1)]; + + % Lens mode + tmp = h5read([TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name],'/entry/instrument/NDAttributes/LensMode'); + TmpFileList{2}(ii).scientaLensMode = tmp{1}; + clearvars tmp + catch + warning('Problem with a NEXAFS data file in NEXAFS list') + disp('Problem with a NEXAFS data file in NEXAFS list') + fprintf('Number %.0f: %s \n',ii,[TmpFileList{2}(ii).folder filesep TmpFileList{2}(ii).name]) + fprintf('Number %.0f: %s \n',ii,datestr(TmpFileList{2}(ii).datenum)) + end + + end +end + +% check for empty entries + +disp('*************************************************') +disp('* Voila: Done reading and writing NEXAFS data! *') +disp('*************************************************') +%% Create Picture List +% +% The file structure needs same number of fields as SES and NEXAFS data. +% Set them to NaN (Not-a-Number). + + +for ii = 1:size(TmpFileList{3},1) % do this for each picture in the list + + + TmpFileList{3}(ii).creationDate = datevec(NaN); + TmpFileList{3}(ii).image = NaN; + TmpFileList{3}(ii).spectrum_counts = NaN; + TmpFileList{3}(ii).spectrum_countsPerSecond = NaN; + TmpFileList{3}(ii).xRayEkin_eV = NaN; + TmpFileList{3}(ii).xRayEkinRange_eV = [NaN NaN]; + TmpFileList{3}(ii).scientaPassEnergy_eV = NaN; + TmpFileList{3}(ii).scientaDwellTime_ms = NaN; + TmpFileList{3}(ii).regionName = ' '; + TmpFileList{3}(ii).scientaAcquisitionMode = ' '; + TmpFileList{3}(ii).scientaEkinRange_eV = [NaN NaN]; + TmpFileList{3}(ii).scientaEkinStep_eV = NaN; + TmpFileList{3}(ii).scientaEkin_eV = NaN; + TmpFileList{3}(ii).beamlineInt = cell(1); + TmpFileList{3}(ii).scientaLensMode = ' '; + TmpFileList{3}(ii).scientaRegionIterations = NaN; + TmpFileList{3}(ii).scientaSequenceIterations = NaN; + TmpFileList{3}(ii).imageRoh = {NaN}; + TmpFileList{3}(ii).spectrum_countsPerSecondRoh = NaN; + TmpFileList{3}(ii).importDate = ' '; + TmpFileList{3}(ii).analysisDir = ' '; + + +end + + +%% Merge lists into one +% + +% get index of non-empty structures +tf =~cellfun(@isempty,TmpFileList); + +% merge the non-empty list structures into one structure +ListFiles = cat(1,TmpFileList{tf}); + +% remove lines with empty images +for ii = 1:size(ListFiles,1) + tmpLogic(ii) = isempty(ListFiles(ii).image); + noncells = tmpLogic; +end +ListFiles(noncells) = []; + +clearvars -except ListFiles server dataPath* p + + +%% + + + +%% Sort by date + +% First, we need to convert into a table, because structures can not be sorted: +ListFiles = struct2table(ListFiles,'AsArray',true); +% Then, we sort the table based on the time (6th column, datenum) +ListFiles = sortrows(ListFiles,6); +% Then, remove un-needed columns +ListFiles = removevars(ListFiles,{'bytes','isdir'}); + +disp('*************************************************') +disp('* Voila: Done creating data list! *') +disp('*************************************************') +%% Import LabView data +% +if matches(p.Results.importLabView,'on') + if isfolder(dataPath_LabView) % verify that this folder exists. + try + % Get list of all files in that folder + TmpFileList = dir([dataPath_LabView filesep '**' filesep '20*.dat']); + + % import LabView data + LabView = LabView_importData(fullfile(TmpFileList(1).folder,TmpFileList(1).name)); % Overwrite LabView data in workspace, if this is the first import + if size(TmpFileList,1) > 1 % for additional data files, add these to the LabView data structure. + for ii = 2:size(TmpFileList,1) + LabView = LabView_importData(fullfile(TmpFileList(ii).folder,TmpFileList(ii).name),LabView); + end + end + catch + warning('Problem with LabView file') + disp('Problem reading LabView file') + end + end + disp('*************************************************') + disp('* Voila: Done reading LabView data! *') + disp('*************************************************') + + clearvars TmpFileList + + try + % combine data and/or rename + LabView = LabView_combine(LabView); + catch + warning('Problem with LabView file') + disp('Problem merging LabView files') + disp('Check number of columns for each file') + end + + %% Extent list with LabView data + + %Query time of each data file and get LabView log for that time. + + for ii = 1:size(ListFiles,1) + + try + + % The time of the data and the logging of LabView are not + % necessarily occurring at precisely the same time. So, here define + % a time range (50 seconds) and get all + % data between these times. + tse1 = tsdata.event('Start',datenum(ListFiles.datenum(ii)),'Datenum'); + tse2 = tsdata.event('End',datenum(ListFiles.datenum(ii)+seconds(50)),'Datenum'); + tmp = gettsbetweenevents(LabView.merge,tse1,tse2); + + if ~isempty(tmp.Data) % only do this if LabView data are not missing (because data logging was off). + + % Cryo-holder set T (Sample holder temperature is in field ts.Data:1) + ListFiles.sampleTemp_dC(ii) = tmp.Data(1,1); % in °C (only get data in first row of tmp) + % Cell pressure + % (TODO: Pick correct Baratron read out: either field: ts.Data 4,8,and 9) + ListFiles.cellPressure_mbar(ii) = tmp.Data(1,4); % in mbar + % vapour pressure over ice: + if ListFiles.cellPressure_mbar(ii) >= 0 + % Marti, J., and K. Mauersberger, Geophys. Res.Lett., 20, 363?366, 1993. + % gives parameterisation from 169 - 273K in Pa. (log10(p)= A1/T+B) + A_1 = -2663.5; + B_1 = 12.537; + ListFiles.iceTemp_dC(ii) = A_1/(log10(ListFiles.cellPressure_mbar(ii)*100)-B_1)-273.15; + else + ListFiles.iceTemp_dC(ii) = NaN; + end + + if datenum(ListFiles.datenum(ii)) >= datenum('04-Mar-2019 13:30:00') % import additional data, logged after 03/2019 + ListFiles.smplX_mm(ii) = tmp.Data(1,10); + ListFiles.smplY_mm(ii) = tmp.Data(1,11); + ListFiles.smplZ_mm(ii) = tmp.Data(1,12); + ListFiles.sealingTemp(ii) = tmp.Data(1,13); + else % if these sub-set of data is not logged, set to NaN + ListFiles.smplX_mm(ii) = NaN; + ListFiles.smplY_mm(ii) = NaN; + ListFiles.smplZ_mm(ii) = NaN; + ListFiles.sealingTemp(ii) = NaN; + end + else % if there are no LabView data stored, set all entries to NaN + ListFiles.sampleTemp_dC(ii) = NaN; + ListFiles.iceTemp_dC(ii) = NaN; + ListFiles.cellPressure_mbar(ii) = NaN; + ListFiles.smplX_mm(ii) = NaN; + ListFiles.smplY_mm(ii) = NaN; + ListFiles.smplZ_mm(ii) = NaN; + ListFiles.sealingTemp(ii) = NaN; + end + clearvars tmp + catch + warning('Problem merging LabView data into data table') + disp('Problem merging LabView data into data table') + %fprintf('Number %.0f: %s \n',ii,[ListFiles.folder(ii) filesep ListFiles.name(ii)]) + %fprintf('Number %.0f: %s \n',ii,datestr(ListFiles.datenum(ii))) + end + end + + disp('*************************************************') + disp('* Voila: Done writing LabView data! *') + disp('*************************************************') +end +%% Make table nicer +% + +if ~iscell(ListFiles.spectrum_countsPerSecond) + ListFiles.spectrum_countsPerSecond = cell(size(ListFiles,1),1); +end +if ~iscell(ListFiles.spectrum_counts) + ListFiles.spectrum_counts = cell(size(ListFiles,1),1); +end +if ~iscell(ListFiles.xRayEkin_eV) + ListFiles.xRayEkin_eV = cell(size(ListFiles,1),1); +end +if ~iscell(ListFiles.scientaEkin_eV) + for ii = 1:size(ListFiles,1) + tmp{ii,:} = ListFiles.scientaEkin_eV(ii,:); + end + ListFiles.scientaEkin_eV = tmp; +end + + + +% rename date fields and delete those fields not needed +[ListFiles.lastModifiedDatestr] = ListFiles.date; +[ListFiles.lastModifiedDatenum] = ListFiles.datenum; +ListFiles = removevars(ListFiles, {'date','datenum'}); + +% Copy Ekin Data +existColumn = strcmp('scientaEkinRoh_eV',ListFiles.Properties.VariableNames); +if any(existColumn) + ListFiles = removevars(ListFiles,'scientaEkinRoh_eV'); +end +existColumn = strcmp('scientaEkinRoh_eV',ListFiles.Properties.VariableNames); +if ~any(existColumn) + % save current ekin data before they are modified + ListFiles.scientaEkinRoh_eV= ListFiles.scientaEkin_eV; +end +if ~iscell(ListFiles.scientaEkinRoh_eV) + for ii = 1:size(ListFiles,1) + tmp{ii,:} = ListFiles.scientaEkinRoh_eV(ii,:); + end + ListFiles.scientaEkinRoh_eV = tmp; +end +% work around for table variables with fitting results having the wrong +% size: +% first delete the old entries + +existColumn = strcmp('peakPosition',ListFiles.Properties.VariableNames); +if any(existColumn) + ListFiles = removevars(ListFiles,'peakPosition'); +end +existColumn = strcmp('peakArea',ListFiles.Properties.VariableNames); +if any(existColumn) + ListFiles = removevars(ListFiles,'peakArea'); +end +existColumn = strcmp('peakFWHM',ListFiles.Properties.VariableNames); +if any(existColumn) + ListFiles = removevars(ListFiles,'peakFWHM'); +end +% then re-create them with right size +% 11/22 change to 5 entries from 4. +existColumn = strcmp('peakPosition',ListFiles.Properties.VariableNames); +if ~any(existColumn) + % save current ekin data before they are modified + ListFiles.peakPosition= NaN(size(ListFiles,1),5); +end +existColumn = strcmp('peakArea',ListFiles.Properties.VariableNames); +if ~any(existColumn) + % save current ekin data before they are modified + ListFiles.peakArea= NaN(size(ListFiles,1),5); +end +existColumn = strcmp('peakFWHM',ListFiles.Properties.VariableNames); +if ~any(existColumn) + % save current ekin data before they are modified + ListFiles.peakFWHM= NaN(size(ListFiles,1),5); +end +existColumn = strcmp('sample',ListFiles.Properties.VariableNames); +if ~any(existColumn) + ListFiles.sample = cellstr(repmat(' ',size(ListFiles,1),1)); +end +% add the imported data to previous list (if passed to function upon call) +if istable(p.Results.DataTable) % do this only if previous list was input to function call + % find table variables that are missing in ListFiles + existColumn = strcmp('sample',p.Results.DataTable.Properties.VariableNames); + if ~any(existColumn) + p.Results.DataTable.sample = cellstr(repmat(' ',size(p.Results.DataTable,1),1)); + end + tmpMissing = ~ismember(p.Results.DataTable.Properties.VariableNames,ListFiles.Properties.VariableNames); + % find all table variables that are cells + tmpCell = cellfun(@(x) iscell(p.Results.DataTable.(x)), p.Results.DataTable.Properties.VariableNames); + % find all table variables that are numbers + tmpNumber = cellfun(@(x) isnumeric(p.Results.DataTable.(x)), p.Results.DataTable.Properties.VariableNames); + % table variabes that hold cells and are missing + tmpCellVariables = p.Results.DataTable.Properties.VariableNames(tmpMissing & tmpCell); + % table variables that hold numbers and are missing + tmpNumberVariables = p.Results.DataTable.Properties.VariableNames(tmpMissing & tmpNumber); + % add empty table variables for missing cell and for number variables + if ~isempty(tmpCellVariables) + for i = 1: size(p.Results.DataTable(:,tmpMissing & tmpCell),2) + ListFiles = addvars(ListFiles,cell(size(ListFiles,1),1),'NewVariableNames',tmpCellVariables{i}); + end + end + if ~isempty(tmpNumberVariables) + for i = 1: size(p.Results.DataTable(:,tmpMissing & tmpNumber),2) + ListFiles = addvars(ListFiles,nan(size(ListFiles,1),1),'NewVariableNames',tmpNumberVariables{i}); + end + end + +% % % sort the tables, if they have not the same order +% tmpCompareTables = cellfun(@isequal, ListFiles.Properties.VariableNames', p.Results.DataTable.Properties.VariableNames'); +% +% if ~all(tmpCompareTables) +% indexDifferenzes = find(ismember(p.Results.DataTable.Properties.VariableNames',ListFiles.Properties.VariableNames(~tmpCompareTables)','rows')); +% nameListFiles =ListFiles.Properties.VariableNames(~tmpCompareTables); +% +% for ii = 1:size(indexDifferenzes,1) +% tmpIndx = find(ismember(p.Results.DataTable.Properties.VariableNames',nameListFiles{ii},'rows')); +% tmpPreviousVarName = p.Results.DataTable.Properties.VariableNames{tmpIndx-1}; +% ListFiles = movevars(ListFiles,nameListFiles{ii},'After',tmpPreviousVarName); +% fprintf("%s comes after %s \n", nameListFiles{ii},tmpPreviousVarName) +% end +% +% end + + + + % merge tables (append imported data to previous table) + ListFiles = [p.Results.DataTable; ListFiles]; + % Then, we sort the table based on the time (datenum) + ListFiles = sortrows(ListFiles,'lastModifiedDatenum'); +end + +%% Export + +ExportList = removevars(ListFiles, {'image', 'spectrum_counts', 'spectrum_countsPerSecond', 'scientaEkin_eV', 'beamlineInt', 'imageRoh', 'scientaEkinRoh_eV', 'xRayEkin_eV'}); +% TODO check windows formatting +try + % write a ;-separated list for export to excel. + writetable(ExportList,fullfile(dataPath,[datestr(ExportList.lastModifiedDatenum(1),'mmmYYYY') '_DataList.csv']),'Delimiter',','); + + if ispc + % and open in Excel; works only on Windows Machines + winopen(fullfile(dataPath,[datestr(ExportList.lastModifiedDatenum(1),'mmmYYYY') '_DataList.csv'])); + end +catch + warning('Problem writing Excel File (*.csv). Make sure it is not open in Excel') +end + + + + +disp('*************************************************') +disp('* Voila: nappFileList.m finished ! *') +disp('*************************************************') + + +end + +function LabView = LabView_importData(fullFileName,varargin) +% +% LabView_importData reads data log ASCII files stored by LabView into +% a Matlab time series. +% +% LabView = LabView_importData(A) imports file A +% and stores its content as time series in a structure called "LabView". +% +% LabView = LabView_importData(A,LabView) imports file A +% and appends its content as time series to the LabView structure. +% +% +% Example +% LabView = LabView_importData('exmpl.dat',LabView) +% +% Input +% * Napp_chamber_file: Complete and absolute path to the Napp chamber log file. +% * LabView: name of output structure. Always call this'LabView' +% +% Output +% * LabView: time series, the name starting with "ts" +% followed by date and time the recording started. +% +% See also LABVIEW_COMBINE, LABVIEW_PLOT, LABVIEW_CUTDATA +% +%% Data Structure +% +% Data structure before 4.3.2019 +% col 1: Date +% col 2: Time +% col 3: Reservoir "Pressure 1" - Unit "1 water" - mbar -> ts.Data:2 +% col 4: Reservoir "Pressure 2" - Unit "2 other" - mbar -> ts.Data:3 +% col 5: Baratron 1 - cell - 1mbar max - mbar -> ts.Data:4 +% col 6: Baratron 2 - cell - 10mbar max - mbar -> ts.Data:8 +% col 7: Baratron 3 - cell - 0.05mbar max - mbar -> ts.Data:9 +% col 8: Baratron 4 - - mbar +% col 9: Temp.Ice Sample - °C -> ts.Data:1 +% col 10: Temp.Heated Sample +% col 11: none +% col 12: Temp. Reservoir "Cooler 1" - °C -> ts.Data:5 +% col 13: Temp. Reservoir "Cooler 2" - °C -> ts.Data:6 +% col 14: Flow He(cryoholder) - l/min -> ts.Data:7 +% col 15: none +% col 16: none +% +% Data structure after 4.3.2019 +% col 1: Date +% col 2: Time +% col 3: Reservoir "Pressure 1" - Unit "1 water" - mbar -> ts.Data:2 +% col 4: Reservoir "Pressure 2" - Unit "2 other" - mbar -> ts.Data:3 +% col 5: Baratron 1 - cell - 1mbar max - mbar -> ts.Data:4 +% col 6: Baratron 2 - cell - 10mbar max - mbar -> ts.Data:8 +% col 7: Baratron 3 - cell - 0.05mbar max - mbar -> ts.Data:9 +% col 8: Baratron 4 - - mbar +% col 9: Temp.Ice Sample - °C -> ts.Data:1 +% col 10: Temp.Heated Sample +% col 11: Temp. Reservoir "Cooler 1" - °C -> ts.Data:5 +% col 12: Temp. Reservoir "Cooler 2" - °C -> ts.Data:6 +% col 13: Flow He(cryoholder) - l/min -> ts.Data:7 +% col 14: Flow gas 1 +% col 15: Pressure chamber - mbar +% col 16: x-position of cryoholder - mm -> ts.Data:10 +% col 17: y-position of cryoholder - mm -> ts.Data:11 +% col 18: z-position of cryoholder - mm -> ts.Data:12 +% col 19: nothing +% col 20: Temp.Sealing - °C -> ts.Data:13 + + +%% + +% Create an InputParser object +p = inputParser; +% Add inputs to the scheme. +defaultAppendToStructure = 0; +addRequired(p,'fullFileName',@isfile); +addOptional(p,'appendToStructure',defaultAppendToStructure,@isstruct); +% Parse the inputs. +parse(p,fullFileName,varargin{:}) + +%% +% get filedate +[~,name,~] = fileparts(p.Results.fullFileName); +tmp = strsplit(name,'_PC'); +filedate = datenum(tmp{1},'yyyy-mm-dd_HH.MM.SS'); + +clearvars name tmp + +%% +% parse structure to append to + +if isstruct(p.Results.appendToStructure) + LabView = p.Results.appendToStructure; +end +%% +if datenum(filedate) <= datenum('04-Mar-2019 13:30:00') + + fid = fopen(p.Results.fullFileName); + data = textscan(fid, ... + '%s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f',... + 'HeaderLines',1); % data file has 2 text columns, followed by 14 numeric columns + fclose(fid); + % define time series + LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]) ... + = timeseries([data{9} data{3} data{4} data{5} data{12} ... + data{13} data{14} data{6} data{7}] , ... + datestr(datenum([char(data{1}), char(data{2})],... + 'dd.mm.yyyyHH:MM:SS'),0)); + LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]).Name ... + = 'Readout Napp Chamber raw signal'; + clear fid ans formatOut nans t x + +elseif datenum(filedate) >= datenum('15-Sep-2021 01:00:00') && datenum(filedate) <= datenum('01-Apr-2023 01:00:00') + % during this time, date and time were in american format. + fid = fopen(p.Results.fullFileName); + data = textscan(fid, ... + '%s %s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f',... + 'HeaderLines',1); % + + fclose(fid); + % the date formating in the dat file is really messed up. Try to make + % it consitent with MATLAB. The problem is that MATLAB does not + % understand 1 digit month and hours. + % + % + % Split the date in column 1 into year,month,day + newDateSplit = cellfun(@(x) split(char(x),'/'),data{1},'UniformOutput', false); + % Split the time in column 2 into hours, minutes, seconds + newTimeSplit = cellfun(@(x) split(char(x),':'),data{2},'UniformOutput', false); + % combine both with the am/pm string in column 3 to a new datestring + customDateStr = cellfun(@(x,y,z) [datestr(datenum([str2double(x{3}),str2double(x{1}),str2double(x{2}),str2double(y{1}),str2double(y{2}),str2double(y{3})])), ' ', char(z)], newDateSplit,newTimeSplit,data{3}, 'uniformOutput',false) ; + + % define time series + LabView.(['ts_' datestr(customDateStr{1},'YYYYmmdd_HHMM')]) ... + = timeseries([data{10} data{4} data{5} data{6} data{12} ... + data{13} data{14} data{7} data{8} data{17} data{18} data{19} data{21}], ... + customDateStr); + LabView.(['ts_' datestr(customDateStr{1},'YYYYmmdd_HHMM')]).Name ... + = 'Readout Napp Chamber raw signal'; + clearvars fid ans formatOut nans t x new* custom* + + +elseif datenum(filedate) >= datenum('01-Apr-2023 02:00:00') + + fid = fopen(p.Results.fullFileName); + data = textscan(fid, ... + '%s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f',... + 'HeaderLines',1); + % data file has 2 text columns, followed by 18 numeric columns (THE AM + % PM IS MISSING and some changes to the LabView file. Confirm with Luca....) + fclose(fid); + % define time series + + LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]) ... + = timeseries([data{9} data{3} data{4} data{5} data{11} ... + data{12} data{20} data{6} data{7} data{15} data{16} data{17} data{19}] , ... + datestr(datenum([char(data{1}), char(data{2})],... + 'dd.mm.yyyyHH:MM:SS'),0)); + + LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]).Name ... + = 'Readout Napp Chamber raw signal'; + clear fid ans formatOut nans t x + +else + fid = fopen(p.Results.fullFileName); + data = textscan(fid, ... + '%s %s %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f',... + 'HeaderLines',1); % data file has 2 text columns, followed by 14 numeric columns + fclose(fid); + % define time series + + LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]) ... + = timeseries([data{9} data{3} data{4} data{5} data{11} ... + data{12} data{13} data{6} data{7} data{16} data{17} data{18} data{20}] , ... + datestr(datenum([char(data{1}), char(data{2})],... + 'dd.mm.yyyyHH:MM:SS'),0)); + + LabView.(['ts_' datestr(datenum([char(data{1}{1}), char(data{2}{1})],'dd.mm.yyyyHH:MM:SS'),'YYYYmmdd_HHMM')]).Name ... + = 'Readout Napp Chamber raw signal'; + clear fid ans formatOut nans t x +end +end + +function data_structure = LabView_combine(data_structure) +% LabView_combine can be used to merge time series into one. +% +% LabView = LabView_combine(LabView) merges all timeseries in the structure +% LabView into the new timeseries "merge" +% and adds this timeseries to the LabView structure +% +% +% Input +% * data_structure: name of the structure holding the time series +% +% Output +% * data_structure.merge: New time series combining all ts in this structure +% +% See also LABVIEW_IMPORTDATA, LABVIEW_PLOT + +% delete previous merged data +if isfield(data_structure,'merge') + data_structure = rmfield(data_structure, 'merge'); +end + +% sort them chronologically +data_structure = orderfields(data_structure); + +% query list of time series +list_ts = fieldnames(data_structure); + +% and merge all of them into one time series +for ii = 1:length(list_ts) + if ii == 1 + data_structure.merge = data_structure.(list_ts{1}); + else + data_structure.merge = append(data_structure.merge,data_structure.(list_ts{ii})); + end +end + + + + +end diff --git a/nappIce/nappFitGaussXps.m b/nappIce/nappFitGaussXps.m new file mode 100644 index 0000000..12e9f93 --- /dev/null +++ b/nappIce/nappFitGaussXps.m @@ -0,0 +1,522 @@ +function DataTable = nappFitGaussXps(DataTable,~,varargin) +%nappFitGaussXps fits PE spectra with up to 4 or 5 Gauss peaks. Different sets +%of constrains can be used. +% +% FileList = +% nappFitGaussXps(FileList,tmpFitParameters,'tableSelection',tmpDataSelection); +% +% *input* +% FileList: data table tmpFitParameters: You can give settings for the 4 +% peaks (5 in some cases), use small (negligible) values if you are +% interested in less than 4 peaks. +% +% % „position“ mode +% tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakWidth = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakPos = [abs#1 rel#2 rel#3 rel#4]; +% +% tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakPosUpperBond = #1; +% tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakPosLowerBond = #1; +% +% +% % „unconstrained“ mode +% tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakWidth = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakPos = [abs#1 abs#2 abs#3 abs#4]; +% +% tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakPosUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakPosLowerBond = [#1 #2 #3 #4]; +% +% +% % „ widthPosition“ mode +% 1.5 +% +% % „ width“ mode +% tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4]; +% tmpFitParameters.peakWidth = [abs#1-#4]; +% tmpFitParameters.peakPos = [abs#1 abs#2 abs#3 abs#4]; +% +% tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthUpperBond = #1-#4; +% tmpFitParameters.peakPosUpperBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthLowerBond = #1-#4; +% tmpFitParameters.peakPosLowerBond = [#1 #2 #3 #4]; +% +% +% % „ unconstrainedAndWidthPosition" mode (novel: rel distance fit parameter) +% tmpFitParameters.peakArea = [abs#1 abs#2 abs#3 abs#4 abs#5]; +% tmpFitParameters.peakWidth = [abs#1,2,4,5 abs#3]; +% tmpFitParameters.peakPos = [rel#1 abs#2 abs#3 abs#4 abs#5]; +% +% tmpFitParameters.peakAreaUpperBond = [#1 #2 #3 #4 #5]; +% tmpFitParameters.peakWidthUpperBond = [#1,2,4,5 #3]; +% tmpFitParameters.peakPosUpperBond = [#1 #2 #3 #4 #5]; +% tmpFitParameters.peakAreaLowerBond = [#1 #2 #3 #4]; +% tmpFitParameters.peakWidthLowerBond = [#1,2,4,5 #3]; +% tmpFitParameters.peakPosLowerBond = [#1 #2 #3 #4]; +% +% +% +% tableSelection (optional): logical array to filter data table +% tableVariable (optional): select source: image(default),'imageRoh' +% mode: +% 'unconstrained': Each gauss peak is fitted independent. +% 'widthPosition' (Default): With of all peaks is identical. Position of peaks +% 2-3 is set relative to peak 1. +% 'position': Position of peaks 2-3 is set relative to peak 1. +% 'width': all peaks have same width +% 'unconstrainedAndWidthPosition': One unconstrained peak #3 (for gas phase +% feature) and 4 peaks constrained in width and/or position +% energyScale: kinetic (default) or binding +% showFigures: on(default) or off: display Gauss fits in figure. +% +% +% *output* +% table variables peakPosition, peakFWHM, and peakArea with fit +% results for peaks 1-4(5) +% fit results are printed in command window and graph with fits is +% shown. +% + + + +% Define conditions and defaults of input +defaultTableVariable = 'spectrum_countsPerSecond'; +expectedTableVariable = {'spectrum_counts','spectrum_countsPerSecond','spectrum_countsNorm'}; +defaultMode = 'widthPosition'; +expectedMode = {'unconstrained','widthPosition','position','width','unconstrainedAndWidthPosition'}; +defaultTableSelection = true(size(DataTable,1),1); +defaultShowFigures = 'on'; +expectedShowFigures = {'on','off'}; +defaultEnergyScale = 'kinetic'; +expectedEnergyScale = {'kinetic','binding'}; + + +% Parse input +p = inputParser; +addRequired(p,'DataTable',@istable); % TODO: allow combinedSpectrum input. +addRequired(p,'FitParameter',@isstruct); +addOptional(p,'tableSelection',defaultTableSelection,@islogical); +addParameter(p,'tableVariable',defaultTableVariable,... + @(x) any(validatestring(x,expectedTableVariable))); +addParameter(p,'mode',defaultMode,... + @(x) any(validatestring(x,expectedMode))); +addParameter(p,'showFigures',defaultShowFigures,... + @(x) any(validatestring(x,expectedShowFigures))); +addParameter(p,'energyScale',defaultEnergyScale,... + @(x) any(validatestring(x,expectedEnergyScale))); +parse(p,DataTable,varargin{:}); + +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + +% define PSI cooperate identity colours +PsiFarbe.hellgrau = [226 226 226]/255; +PsiFarbe.mittelgrau = [184 184 184]/255; +PsiFarbe.dunkelgrau = [78 78 77]/255; +PsiFarbe.blaugrau = [236 236 243]/255; % This is actually not a PSI colour +PsiFarbe.gelb = [239 200 37]/255; +PsiFarbe.hellorange = [227 164 31]/255; +PsiFarbe.dunkelorange = [207 92 22]/255; +PsiFarbe.hellrot = [164 36 23]/255; +PsiFarbe.dunkelbraun = [114 85 65]/255; +PsiFarbe.hellbraun = [127 119 47]/255; +PsiFarbe.mittelgruen = [135 150 59]/255; +PsiFarbe.hellgruen = [195 214 47]/255; +PsiFarbe.dunkelgruen = [72 130 33]/255; +PsiFarbe.dunkelrot = [104 47 86]/255; +PsiFarbe.dunkelblau = [37 65 108]/255; +PsiFarbe.mittelgruenblau = [61 164 168]/255; +PsiFarbe.hellblau = [58 162 190]/255; +PsiFarbe.mittelblau = [50 118 158]/255; + +% Define equation to fit data +% I use the area Gauss equations here, which I took from the OriginPro +% documentation. https://www.originlab.com/doc/Origin-Help/Gauss-FitFunc +% +% Gauss = area/(width*sqrt(pi/2)) * exp(-2*(x-position)^2/width^2) +% +% where FWHM = width * sqrt(ln(4)) + + +% fitting equation +if matches(p.Results.mode,'position') + yfcn1 = @(tmpB,x)... + tmpB(1)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1) - tmpB(3)).^2/tmpB(2).^2)) ... % Gauss peak 1 + + tmpB(4)/(tmpB(5)*sqrt(pi/2))*exp(-2.*((x(:,1)- (tmpB(3)+p.Results.FitParameter.peakPos(1,2))).^2/tmpB(5).^2))... % Gauss peak 2 + + tmpB(6)/(tmpB(7)*sqrt(pi/2))*exp(-2.*((x(:,1)- (tmpB(3)+p.Results.FitParameter.peakPos(1,3))).^2/tmpB(7).^2))... % Gauss peak 3 + + tmpB(8)/(tmpB(9)*sqrt(pi/2))*exp(-2.*((x(:,1)- (tmpB(3)+p.Results.FitParameter.peakPos(1,4))).^2/tmpB(9).^2))... % Gauss peak 4 + +tmpB(10).*x(:,1)+tmpB(11); % linear background + + % initial value + B0= [p.Results.FitParameter.peakArea(1,1) p.Results.FitParameter.peakWidth(1,1) p.Results.FitParameter.peakPos(1,1)... % Gauss peak 1 + p.Results.FitParameter.peakArea(1,2) p.Results.FitParameter.peakWidth(1,2)... % Gauss peak 2 + p.Results.FitParameter.peakArea(1,3) p.Results.FitParameter.peakWidth(1,3)... % Gauss peak 3 + p.Results.FitParameter.peakArea(1,4) p.Results.FitParameter.peakWidth(1,4)... % Gauss peak 4 + 0 0]; % linear background + % lower bonds + lb = [p.Results.FitParameter.peakAreaLowerBond(1,1) p.Results.FitParameter.peakWidthLowerBond(1,1) p.Results.FitParameter.peakPosLowerBond(1,1) ... % Gauss peak 1 + p.Results.FitParameter.peakAreaLowerBond(1,2) p.Results.FitParameter.peakWidthLowerBond(1,2) ... % Gauss peak 2 + p.Results.FitParameter.peakAreaLowerBond(1,3) p.Results.FitParameter.peakWidthLowerBond(1,3) ... % Gauss peak 3 + p.Results.FitParameter.peakAreaLowerBond(1,4) p.Results.FitParameter.peakWidthLowerBond(1,4) ... % Gauss peak 4 + 0 0]; % linear background + % upper bond + ub = [p.Results.FitParameter.peakAreaUpperBond(1,1) p.Results.FitParameter.peakWidthUpperBond(1,1) p.Results.FitParameter.peakPosUpperBond(1,1) ... % Gauss peak 1 + p.Results.FitParameter.peakAreaUpperBond(1,2) p.Results.FitParameter.peakWidthUpperBond(1,2) ... % Gauss peak 2 + p.Results.FitParameter.peakAreaUpperBond(1,3) p.Results.FitParameter.peakWidthUpperBond(1,3) ... % Gauss peak 3 + p.Results.FitParameter.peakAreaUpperBond(1,4) p.Results.FitParameter.peakWidthUpperBond(1,4) ... % Gauss peak 4 + Inf Inf]; % linear background +elseif matches(p.Results.mode,'unconstrained') + yfcn1 = @(tmpB,x)... + tmpB(1)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1) - tmpB(3)).^2/tmpB(2).^2)) ... % Gauss peak 1 + + tmpB(4)/(tmpB(5)*sqrt(pi/2))*exp(-2.*((x(:,1)- tmpB(6)).^2/tmpB(5).^2))... % Gauss peak 2 + + tmpB(7)/(tmpB(8)*sqrt(pi/2))*exp(-2.*((x(:,1)- tmpB(9)).^2/tmpB(8).^2))... % Gauss peak 3 + + tmpB(10)/(tmpB(11)*sqrt(pi/2))*exp(-2.*((x(:,1)- tmpB(12)).^2/tmpB(11).^2))... % Gauss peak 4 + +tmpB(13).*x(:,1)+tmpB(14); % linear background + + % initial value + B0= [p.Results.FitParameter.peakArea(1,1) p.Results.FitParameter.peakWidth(1,1) p.Results.FitParameter.peakPos(1,1)... % Gauss peak 1 + p.Results.FitParameter.peakArea(1,2) p.Results.FitParameter.peakWidth(1,2) p.Results.FitParameter.peakPos(1,2)... % Gauss peak 2 + p.Results.FitParameter.peakArea(1,3) p.Results.FitParameter.peakWidth(1,3) p.Results.FitParameter.peakPos(1,3)... % Gauss peak 3 + p.Results.FitParameter.peakArea(1,4) p.Results.FitParameter.peakWidth(1,4) p.Results.FitParameter.peakPos(1,4)... % Gauss peak 4 + 0 0]; % linear background + % lower bonds + lb = [p.Results.FitParameter.peakAreaLowerBond(1,1) p.Results.FitParameter.peakWidthLowerBond(1,1) p.Results.FitParameter.peakPosLowerBond(1,1) ... % Gauss peak 1 + p.Results.FitParameter.peakAreaLowerBond(1,2) p.Results.FitParameter.peakWidthLowerBond(1,2) p.Results.FitParameter.peakPosLowerBond(1,2)... % Gauss peak 2 + p.Results.FitParameter.peakAreaLowerBond(1,3) p.Results.FitParameter.peakWidthLowerBond(1,3) p.Results.FitParameter.peakPosLowerBond(1,3)... % Gauss peak 3 + p.Results.FitParameter.peakAreaLowerBond(1,4) p.Results.FitParameter.peakWidthLowerBond(1,4) p.Results.FitParameter.peakPosLowerBond(1,4)... % Gauss peak 4 + 0 0]; % linear background + % upper bond + ub = [p.Results.FitParameter.peakAreaUpperBond(1,1) p.Results.FitParameter.peakWidthUpperBond(1,1) p.Results.FitParameter.peakPosUpperBond(1,1) ... % Gauss peak 1 + p.Results.FitParameter.peakAreaUpperBond(1,2) p.Results.FitParameter.peakWidthUpperBond(1,2) p.Results.FitParameter.peakPosUpperBond(1,2)... % Gauss peak 2 + p.Results.FitParameter.peakAreaUpperBond(1,3) p.Results.FitParameter.peakWidthUpperBond(1,3) p.Results.FitParameter.peakPosUpperBond(1,3)... % Gauss peak 3 + p.Results.FitParameter.peakAreaUpperBond(1,4) p.Results.FitParameter.peakWidthUpperBond(1,4) p.Results.FitParameter.peakPosUpperBond(1,4)... % Gauss peak 4 + Inf Inf]; % linear background +elseif matches(p.Results.mode,'widthPosition') + yfcn1 = @(tmpB,x)... + tmpB(1)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1) - tmpB(3)).^2/tmpB(2).^2)) ... % Gauss peak 1 + + tmpB(4)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1)- (tmpB(3)+p.Results.FitParameter.peakPos(1,2))).^2/tmpB(2).^2))... % Gauss peak 2 + + tmpB(5)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1)- (tmpB(3)+p.Results.FitParameter.peakPos(1,3))).^2/tmpB(2).^2))... % Gauss peak 3 + + tmpB(6)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1)- (tmpB(3)+p.Results.FitParameter.peakPos(1,4))).^2/tmpB(2).^2))... % Gauss peak 4 + +tmpB(7).*x(:,1)+tmpB(8); % linear background + + % initial value + B0= [p.Results.FitParameter.peakArea(1,1) p.Results.FitParameter.peakWidth(1,1) p.Results.FitParameter.peakPos(1,1)... % Gauss peak 1 + p.Results.FitParameter.peakArea(1,2) ... % Gauss peak 2 + p.Results.FitParameter.peakArea(1,3) ... % Gauss peak 3 + p.Results.FitParameter.peakArea(1,4)... % Gauss peak 4 + 0 0]; % linear background + % lower bonds + lb = [p.Results.FitParameter.peakAreaLowerBond(1,1) p.Results.FitParameter.peakWidthLowerBond(1,1) p.Results.FitParameter.peakPosLowerBond(1,1) ... % Gauss peak 1 + p.Results.FitParameter.peakAreaLowerBond(1,2) ... % Gauss peak 2 + p.Results.FitParameter.peakAreaLowerBond(1,3) ... % Gauss peak 3 + p.Results.FitParameter.peakAreaLowerBond(1,4) ... % Gauss peak 4 + 0 0]; % linear background + % upper bond + ub = [p.Results.FitParameter.peakAreaUpperBond(1,1) p.Results.FitParameter.peakWidthUpperBond(1,1) p.Results.FitParameter.peakPosUpperBond(1,1) ... % Gauss peak 1 + p.Results.FitParameter.peakAreaUpperBond(1,2) ... % Gauss peak 2 + p.Results.FitParameter.peakAreaUpperBond(1,3) ... % Gauss peak 3 + p.Results.FitParameter.peakAreaUpperBond(1,4) ... % Gauss peak 4 + Inf Inf]; % linear background +elseif matches(p.Results.mode,'width') + yfcn1 = @(tmpB,x)... + tmpB(1)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1) - tmpB(3)).^2/tmpB(2).^2)) ... % Gauss peak 1 + + tmpB(4)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1)- tmpB(5)).^2/tmpB(2).^2))... % Gauss peak 2 + + tmpB(6)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1)- tmpB(7)).^2/tmpB(2).^2))... % Gauss peak 3 + + tmpB(8)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1)- tmpB(9)).^2/tmpB(2).^2))... % Gauss peak 4 + +tmpB(10).*x(:,1)+tmpB(11); % linear background + + % initial value + B0= [p.Results.FitParameter.peakArea(1,1) p.Results.FitParameter.peakWidth(1,1) p.Results.FitParameter.peakPos(1,1)... % Gauss peak 1 + p.Results.FitParameter.peakArea(1,2) p.Results.FitParameter.peakPos(1,2)... % Gauss peak 2 + p.Results.FitParameter.peakArea(1,3) p.Results.FitParameter.peakPos(1,3)... % Gauss peak 3 + p.Results.FitParameter.peakArea(1,4) p.Results.FitParameter.peakPos(1,4)... % Gauss peak 4 + 0 0]; % linear background + % lower bonds + lb = [p.Results.FitParameter.peakAreaLowerBond(1,1) p.Results.FitParameter.peakWidthLowerBond(1,1) p.Results.FitParameter.peakPosLowerBond(1,1) ... % Gauss peak 1 + p.Results.FitParameter.peakAreaLowerBond(1,2) p.Results.FitParameter.peakWidthLowerBond(1,2) ... % Gauss peak 2 + p.Results.FitParameter.peakAreaLowerBond(1,3) p.Results.FitParameter.peakWidthLowerBond(1,3) ... % Gauss peak 3 + p.Results.FitParameter.peakAreaLowerBond(1,4) p.Results.FitParameter.peakWidthLowerBond(1,4) ... % Gauss peak 4 + 0 0]; % linear background + % upper bond + ub = [p.Results.FitParameter.peakAreaUpperBond(1,1) p.Results.FitParameter.peakWidthUpperBond(1,1) p.Results.FitParameter.peakPosUpperBond(1,1) ... % Gauss peak 1 + p.Results.FitParameter.peakAreaUpperBond(1,2) p.Results.FitParameter.peakWidthUpperBond(1,2) ... % Gauss peak 2 + p.Results.FitParameter.peakAreaUpperBond(1,3) p.Results.FitParameter.peakWidthUpperBond(1,3) ... % Gauss peak 3 + p.Results.FitParameter.peakAreaUpperBond(1,4) p.Results.FitParameter.peakWidthUpperBond(1,4) ... % Gauss peak 4 + Inf Inf]; % linear background + +elseif matches(p.Results.mode,'unconstrainedAndWidthPosition') % Novum, also the distance between peaks is a fit parameter. [Gauss = area/(width*sqrt(pi/2)) * exp(-2*(x-position)^2/width^2)] + yfcn1 = @(tmpB,x)... + tmpB(1)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1) - (tmpB(3)+tmpB(14))).^2/tmpB(2).^2)) ... % Gauss peak 1: width and position + + tmpB(4)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1) - tmpB(3)).^2/tmpB(2).^2))... % Gauss peak 2: width and position + + tmpB(5)/(tmpB(6)*sqrt(pi/2))*exp(-2.*((x(:,1) - tmpB(7)).^2/tmpB(6).^2))... % Gauss peak 3: unconstrained + + tmpB(8)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1) - tmpB(9)).^2/tmpB(2).^2))... % Gauss peak 4: width + + tmpB(10)/(tmpB(2)*sqrt(pi/2))*exp(-2.*((x(:,1)- tmpB(11)).^2/tmpB(2).^2))... % Gauss peak 5: width + + tmpB(12).*x(:,1)+tmpB(13); % linear background + + % initial value + B0= [p.Results.FitParameter.peakArea(1,1) p.Results.FitParameter.peakWidth(1,1) p.Results.FitParameter.peakPos(1,2)... % Gauss peak 1 + p.Results.FitParameter.peakArea(1,2) ... % Gauss peak 2 + p.Results.FitParameter.peakArea(1,3) p.Results.FitParameter.peakWidth(1,2) p.Results.FitParameter.peakPos(1,3)... % Gauss peak 3 + p.Results.FitParameter.peakArea(1,4) p.Results.FitParameter.peakPos(1,4)... % Gauss peak 4 + p.Results.FitParameter.peakArea(1,5) p.Results.FitParameter.peakPos(1,5)... % Gauss peak 5 + 0 0 ... % linear background + p.Results.FitParameter.peakPos(1,1)]; + % lower bonds + lb = [p.Results.FitParameter.peakAreaLowerBond(1,1) p.Results.FitParameter.peakWidthLowerBond(1,1) p.Results.FitParameter.peakPosLowerBond(1,2) ... % Gauss peak 1 + p.Results.FitParameter.peakAreaLowerBond(1,2) ... % Gauss peak 2 + p.Results.FitParameter.peakAreaLowerBond(1,3) p.Results.FitParameter.peakWidthLowerBond(1,2) p.Results.FitParameter.peakPosLowerBond(1,3) ... % Gauss peak 3 + p.Results.FitParameter.peakAreaLowerBond(1,4) p.Results.FitParameter.peakPosLowerBond(1,4) ... + p.Results.FitParameter.peakAreaLowerBond(1,5) p.Results.FitParameter.peakPosLowerBond(1,5) ...% Gauss peak 4 + 0 0 ... % linear background + p.Results.FitParameter.peakPosLowerBond(1,1)]; + + % upper bond + ub = [p.Results.FitParameter.peakAreaUpperBond(1,1) p.Results.FitParameter.peakWidthUpperBond(1,1) p.Results.FitParameter.peakPosUpperBond(1,2) ... % Gauss peak 1 + p.Results.FitParameter.peakAreaUpperBond(1,2) ... % Gauss peak 2 + p.Results.FitParameter.peakAreaUpperBond(1,3) p.Results.FitParameter.peakWidthUpperBond(1,2) p.Results.FitParameter.peakPosUpperBond(1,3) ... % Gauss peak 3 + p.Results.FitParameter.peakAreaUpperBond(1,4) p.Results.FitParameter.peakPosUpperBond(1,4) ... + p.Results.FitParameter.peakAreaUpperBond(1,5) p.Results.FitParameter.peakPosUpperBond(1,5) ... % Gauss peak 4 + Inf Inf ... % linear background + p.Results.FitParameter.peakPosUpperBond(1,1)]; % shift upper bond +end + +for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if contains(p.Results.energyScale,'kinetic') + [x1, y1] = prepareCurveData(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii},... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}); + % make data slimmer so that background fit improved + if p.Results.FitParameter.peakPos(1,1) >= 10 + tmp1 = find(x1>=p.Results.FitParameter.peakPos(1,1)-p.Results.FitParameter.backgroundRange(1,1),1); + tmp2 = find(x1>=p.Results.FitParameter.peakPos(1,1)+p.Results.FitParameter.backgroundRange(1,2),1); + else + tmp1 = find(x1>=p.Results.FitParameter.peakPos(1,2)-p.Results.FitParameter.backgroundRange(1,1),1); + tmp2 = find(x1>=p.Results.FitParameter.peakPos(1,2)+p.Results.FitParameter.backgroundRange(1,2),1); + end + if isempty(tmp2) + y1 = y1(tmp1:end); + x1 = x1(tmp1:end); + else + y1 = y1(tmp1:tmp2); + x1 = x1(tmp1:tmp2); + end + % Fit equations: Gauss eq. 1 with data + yfcn = @(tmpB,x) yfcn1(tmpB,x); + % We find an optimal fit by minimising the residuals: + fitfcnw = @(tmpB) sum((y1 - yfcn(tmpB,x1)).^2); + problem = createOptimProblem('fmincon', 'x0',B0, 'lb',lb,'ub',ub, 'objective',fitfcnw); + gs = GlobalSearch('PlotFcns',@gsplotbestf); + tmpB = run(gs,problem); + elseif contains(p.Results.energyScale,'binding') + [x1, y1] = prepareCurveData(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii},... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}); + % make data slimmer so that background fit improves + if p.Results.FitParameter.peakPos(1,1) >= 10 + tmp2 = find(x1<=p.Results.FitParameter.peakPos(1,1)-p.Results.FitParameter.backgroundRange(1,1),1); + tmp1 = find(x1<=p.Results.FitParameter.peakPos(1,1)+p.Results.FitParameter.backgroundRange(1,2),1); + else + tmp2 = find(x1<=p.Results.FitParameter.peakPos(1,2)-p.Results.FitParameter.backgroundRange(1,1),1); + tmp1 = find(x1<=p.Results.FitParameter.peakPos(1,2)+p.Results.FitParameter.backgroundRange(1,2),1); + end + if isempty(tmp2) + y1 = y1(tmp1:end); + x1 = x1(tmp1:end); + else + y1 = y1(tmp1:tmp2); + x1 = x1(tmp1:tmp2); + end + % Fit equations: Gauss eq. 1 with data + yfcn = @(tmpB,x) yfcn1(tmpB,x); + % We find an optimal fit by minimising the residuals: + fitfcnw = @(tmpB) sum((y1 - yfcn(tmpB,x1)).^2); + problem = createOptimProblem('fmincon', 'x0',B0, 'lb',lb,'ub',ub, 'objective',fitfcnw); + gs = GlobalSearch('PlotFcns',@gsplotbestf); + tmpB = run(gs,problem); + end + % compile results into variable B with same dimension for all + % fit-types (Area Width Position): + if matches(p.Results.mode,'position') + B = [tmpB(1) tmpB(2) tmpB(3)... + tmpB(4) tmpB(5) tmpB(3)+p.Results.FitParameter.peakPos(1,2) ... + tmpB(6) tmpB(7) tmpB(3)+p.Results.FitParameter.peakPos(1,3)... + tmpB(8) tmpB(9) tmpB(3)+p.Results.FitParameter.peakPos(1,4)... + tmpB(10) tmpB(11)... + NaN NaN NaN]; + elseif matches(p.Results.mode,'unconstrained') + B = [tmpB(1) tmpB(2) tmpB(3)... + tmpB(4) tmpB(5) tmpB(6) ... + tmpB(7) tmpB(8) tmpB(9) ... + tmpB(10) tmpB(11) tmpB(12) ... + tmpB(13) tmpB(14)... + NaN NaN NaN]; + elseif matches(p.Results.mode,'widthPosition') + B = [tmpB(1) tmpB(2) tmpB(3)... + tmpB(4) tmpB(2) tmpB(3)+p.Results.FitParameter.peakPos(1,2)... + tmpB(5) tmpB(2) tmpB(3)+p.Results.FitParameter.peakPos(1,3)... + tmpB(6) tmpB(2) tmpB(3)+p.Results.FitParameter.peakPos(1,4)... + tmpB(7) tmpB(8)... + NaN NaN NaN]; + elseif matches(p.Results.mode,'width') + B = [tmpB(1) tmpB(2) tmpB(3)... + tmpB(4) tmpB(2) tmpB(5)... + tmpB(6) tmpB(2) tmpB(8)... + tmpB(9) tmpB(2) tmpB(10)... + tmpB(11) tmpB(12)... + NaN NaN NaN]; + elseif matches(p.Results.mode,'unconstrainedAndWidthPosition') + B = [tmpB(1) tmpB(2) tmpB(3)+tmpB(14)... + tmpB(4) tmpB(2) tmpB(3)... + tmpB(5) tmpB(6) tmpB(7)... + tmpB(8) tmpB(2) tmpB(9)... + tmpB(12) tmpB(13) ... + tmpB(10) tmpB(2) tmpB(11)]; + end + + % print out result table and result plots based on B. Because B has the + % same structure for all fit types, the same code for printing and + % plotting can be used for all fit types. + + if matches(p.Results.showFigures,'on') + % Display results in table + disp(' ' ); + disp(' ' ); + disp('Fit results') + disp(p.Results.DataTable(p.Results.tableSelection,:).name{ii}); + disp(' ' ); + disp(cell2table({sprintf('%.1f',B(3)),... + sprintf('%.1f',B(2)*sqrt(log(4))),... + sprintf('%.1f',B(2)),... + sprintf('%7.0f',B(1));... + sprintf('%.1f',B(6)),... + sprintf('%.1f',B(5)*sqrt(log(4))),... + sprintf('%.1f',B(5)),... + sprintf('%7.0f',B(4));... + sprintf('%.1f',B(9)),... + sprintf('%.1f',B(8)*sqrt(log(4))),... + sprintf('%.1f',B(8)),... + sprintf('%7.0f',B(7));... + sprintf('%.1f',B(12)),... + sprintf('%.1f',B(11)*sqrt(log(4))),... + sprintf('%.1f',B(11)),... + sprintf('%7.0f',B(10)); ... + sprintf('%.1f',B(17)),... + sprintf('%.1f',B(16)*sqrt(log(4))),... + sprintf('%.1f',B(16)),... + sprintf('%7.0f',B(15))},... + 'VariableNames',{'position';'FWHW';'width';'area'},... + 'RowNames',{'peak1','peak2','peak3','peak4','peak5'})); % 'RowNames',{'peak1','peak2','peak3','peak4','peak5'})); + + % plot result + % eliminate NaN in B + B(isnan(B))=0.01; + % define equations to be plotted + Gauss = @(x, A, Pos, Wdt) A./(Wdt.*sqrt(pi/2))*exp(-2.*((x - Pos).^2/Wdt.^2)); + linear = @(x,slp,intrcpt) slp*x+intrcpt; + figure( 'Name', 'Gauss Multi Fit ') + tiledlayout(1,1) + ax(1) = nexttile; + % define high-resolution x for plotting + if x1(1)<= x1(end) + xGaussPlot = x1(1):0.01:x1(end); + else + xGaussPlot = x1(1):-0.01:x1(end); + end + + %Define gauss peaks + yData_pk1= Gauss(xGaussPlot ,B(1), B(3), B(2)); + yData_pk2= Gauss(xGaussPlot ,B(4), B(6), B(5)); + yData_pk3= Gauss(xGaussPlot ,B(7), B(9), B(8)); + yData_pk4= Gauss(xGaussPlot ,B(10), B(12), B(11)); + yData_pk5= Gauss(xGaussPlot ,B(15), B(17), B(16)); + bkgrd = linear(xGaussPlot,B(13),B(14)); + % plot data + plot(x1,y1,'.') + hold on + % plot fit + h = plot(xGaussPlot,yData_pk1+yData_pk2+yData_pk3+yData_pk4+yData_pk5+bkgrd); + h.LineWidth=2; + h.Color = PsiFarbe.dunkelblau; + % plot each gauss peak + h = plot(xGaussPlot,yData_pk1+bkgrd); + h.LineWidth=1.5; + h.Color = PsiFarbe.gelb; + h = plot(xGaussPlot,yData_pk2+bkgrd); + h.LineWidth=1.5; + h.Color = PsiFarbe.gelb; + h = plot(xGaussPlot,yData_pk3+bkgrd); + h.LineWidth=1.5; + h.Color = PsiFarbe.gelb; + h = plot(xGaussPlot,yData_pk4+bkgrd); + h.LineWidth=1.5; + h.Color = PsiFarbe.gelb; + h = plot(xGaussPlot,yData_pk5+bkgrd); + h.LineWidth=1.5; + h.Color = PsiFarbe.gelb; + plot(xGaussPlot, bkgrd); + set(ax(1),'Xdir','reverse'); + legend OFF + xlabel('Binding Energy [eV]'); + ylabel('PE intensity [-]'); + grid on + end + % Write results to List, we need all fitting results + resultsPeakPos(ii,:) = [B(3), B(6), B(9), B(12), B(16)] ; %#ok<*AGROW> + resultsPeakFWHW(ii,:) = [B(2).*sqrt(log(4)), B(5).*sqrt(log(4)), B(8).*sqrt(log(4)), B(11).*sqrt(log(4)), B(17).*sqrt(log(4))] ; + resultsPeakArea(ii,:) = [B(1), B(4), B(7), B(10) B(15)] ; + % resultsBkgrd(ii,:) = [B(13), B(14)] ; +end + + +% write results to data table +try + existColumn = strcmp('peakPosition',p.Results.DataTable.Properties.VariableNames); + if ~any(existColumn) + DataTable.peakPosition = NaN(size(p.Results.DataTable,1),size(resultsPeakPos,2)); + end + existColumn = strcmp('peakArea',p.Results.DataTable.Properties.VariableNames); + if ~any(existColumn) + DataTable.peakArea = NaN(size(p.Results.DataTable,1),size(resultsPeakArea,2)); + end + existColumn = strcmp('peakFWHM',p.Results.DataTable.Properties.VariableNames); + if ~any(existColumn) + DataTable.peakFWHM = NaN(size(p.Results.DataTable,1),size(resultsPeakFWHW,2)); + end + %if contains(p.Results.energyScale,'binding') + DataTable(p.Results.tableSelection,:).peakPosition = resultsPeakPos(:,:); + %end + DataTable(p.Results.tableSelection,:).peakFWHM = resultsPeakFWHW(:,:); + DataTable(p.Results.tableSelection,:).peakArea = resultsPeakArea(:,:); +catch + disp('Could not write results to table. Writing only 4 entries') + existColumn = strcmp('peakPosition',p.Results.DataTable.Properties.VariableNames); + if ~any(existColumn) + DataTable.peakPosition = NaN(size(p.Results.DataTable,1),size(resultsPeakPos,2)); + end + existColumn = strcmp('peakArea',p.Results.DataTable.Properties.VariableNames); + if ~any(existColumn) + DataTable.peakArea = NaN(size(p.Results.DataTable,1),size(resultsPeakArea,2)); + end + existColumn = strcmp('peakFWHM',p.Results.DataTable.Properties.VariableNames); + if ~any(existColumn) + DataTable.peakFWHM = NaN(size(p.Results.DataTable,1),size(resultsPeakFWHW,2)); + end + %if contains(p.Results.energyScale,'binding') + DataTable(p.Results.tableSelection,:).peakPosition = resultsPeakPos(:,1:4); + %end + DataTable(p.Results.tableSelection,:).peakFWHM = resultsPeakFWHW(:,1:4); + DataTable(p.Results.tableSelection,:).peakArea = resultsPeakArea(:,1:4); +end + + +end \ No newline at end of file diff --git a/nappIce/nappGenerateSpectra.m b/nappIce/nappGenerateSpectra.m new file mode 100644 index 0000000..0bf923f --- /dev/null +++ b/nappIce/nappGenerateSpectra.m @@ -0,0 +1,126 @@ +function DataTable = nappGenerateSpectra(DataTable,varargin) +%nappGenerateSpectra reduces the dimension of images to generate spectra +% +% nappGenerateSpectra(FileList,tmpDataSelection) +% +% *input* +% FileList: data table +% tableSelection (optional): logical array to filter data table +% tableVariable (optional): select source: image(default),'imageRoh' +% mode: mean (default) averages the sequence iterations; sum adds them +% +% *output* +% with mode mean the spectrum will be saved in the table variable spectrum_countsPerSecond +% with mode sum the spectrum will be saved in the table variable spectrum_counts +% +% FIXME: spectrum_counts is not implemented yet. + +% Define conditions and defaults of input +defaultTableVariable = 'image'; +expectedTableVariable = {'image','imageRoh'}; +defaultMode = 'mean'; +expectedMode = {'mean','sum','trapz'}; +defaultEkinStart = 0; +defaultEkinEnd = 0; +defaultTableSelection = true(size(DataTable,1)); + +% Parse input +p = inputParser; +addRequired(p,'DataTable',@istable); +addOptional(p,'tableSelection',defaultTableSelection,@islogical); +addParameter(p,'tableVariable',defaultTableVariable,... + @(x) any(validatestring(x,expectedTableVariable))); +addParameter(p,'mode',defaultMode,... + @(x) any(validatestring(x,expectedMode))); +addParameter(p,'iterationRange',[0:0]); +addParameter(p,'eKinStart',defaultEkinStart,@isnumeric) +addParameter(p,'eKinEnd',defaultEkinEnd,@isnumeric) +parse(p,DataTable,varargin{:}); + +% add empty variable to table +existColumn = strcmp('spectrum_countsPerSecond',p.Results.DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.spectrum_countsPerSecond = cell(size(p.Results.DataTable,1),1); +end +existColumn = strcmp('spectrum_counts',p.Results.DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.spectrum_counts = cell(size(p.Results.DataTable,1),1); +end +existColumn = strcmp('logGenerateRange',p.Results.DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.logGenerateRange = NaN(size(p.Results.DataTable,1),2); +end +existColumn = strcmp('logGenerateDate',p.Results.DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.logGenerateDate = cellstr(repmat(' ',size(p.Results.DataTable,1),1)); +end +existColumn = strcmp('logGenerateMode',p.Results.DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.logGenerateDate = cellstr(repmat(' ',size(p.Results.DataTable,1),1)); +end + +% check input (all elements of input variable need to have non-zero size) +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + +% create empty variables +tmp_3 = cell(size(p.Results.DataTable(p.Results.tableSelection,:),1),1); +tmp_6 = cell(size(p.Results.DataTable(p.Results.tableSelection,:),1),1); +tmp_4 = NaN(size(p.Results.DataTable(p.Results.tableSelection,:),1),1); +tmp_5 = NaN(size(p.Results.DataTable(p.Results.tableSelection,:),1),1); +% repeat this for all columns in input. +for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'h5') % let's do NEXAFS first. + % Get index of EkinStart and EkinEnd + if (p.Results.eKinStart) == 0 + tmp_1 = 1; + else + tmp_1 = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii} >= p.Results.eKinStart,1); + end + if (p.Results.eKinEnd) == 0 + tmp_2 = length(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}); + else + tmp_2 = find(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii} >= p.Results.eKinEnd,1); + end + + if contains(p.Results.mode,'trapz') + tmp_3(ii,1)= {trapz(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(tmp_1:tmp_2),... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(tmp_1:tmp_2,:))'}; + elseif (contains(p.Results.mode,'sum') | contains(p.Results.mode,'mean')) + + tmp_3(ii,1) = {sum(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(tmp_1:tmp_2,:),1)'}; %#ok<*AGROW> + end + % log + tmp_4(ii,1) = p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(tmp_1); + tmp_5(ii,1) = p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(tmp_2); + elseif endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'ibw') % then do Igorfiles + if p.Results.iterationRange(1) == 0 + startRange = 1; + endRange = size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2); + else + startRange = p.Results.iterationRange(1); + endRange = p.Results.iterationRange(2); + end + + if (contains(p.Results.mode,'mean') | contains(p.Results.mode,'trapz')) + tmp_6(ii,1)= {mean(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(:,startRange:endRange),2)}; + elseif contains(p.Results.mode,'sum') + tmp_3(ii,1) = {sum(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(:,startRange:endRange),2)}; %#ok<*AGROW> + end + % log + tmp_4(ii,1) = startRange; + tmp_5(ii,1) = endRange; + end +end + +% write results to table + DataTable.spectrum_counts(p.Results.tableSelection) = tmp_3; + DataTable.spectrum_countsPerSecond(p.Results.tableSelection) = tmp_6; +% write log to table + DataTable.logGenerateMode(p.Results.tableSelection,:) = cellstr(repmat(p.Results.mode,size(p.Results.DataTable(p.Results.tableSelection,:),1),1)); + DataTable.logGenerateRange(p.Results.tableSelection,:) = [tmp_4 tmp_5]; + DataTable.logGenerateDate(p.Results.tableSelection,:) = cellstr(repmat(datestr(now),size(p.Results.DataTable(p.Results.tableSelection,:),1),1)); + +end \ No newline at end of file diff --git a/nappIce/nappImage.m b/nappIce/nappImage.m new file mode 100644 index 0000000..6f35383 --- /dev/null +++ b/nappIce/nappImage.m @@ -0,0 +1,58 @@ + function nappImage(DataTable,varargin) + % + % h_img = Napp_plotImage(StructArrayData) plots an image of the + % NEXAFS data set in the NEXAFS data structure. + % + % Output: an image figure, with a handle. The handle is important to + % select these images for XPS removal + +% Define conditions and defaults of input +defaultTableVariable = {'image'}; +expectedTableVariable = {'image','imageRoh'}; +defaultTableSelection = true(size(DataTable,1)); + + +% Parse input +p = inputParser; + addRequired(p,'DataTable',@istable); + addOptional(p,'tableSelection',defaultTableSelection,@islogical); + addParameter(p,'tableVariable',defaultTableVariable,... + @(x) any(validatestring(x,expectedTableVariable))); +parse(p,DataTable,varargin{:}); + +% check input (all elements of input variable need to have non-zero size) +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + figure('Name',p.Results.DataTable(p.Results.tableSelection,:).name{ii}); + + % Create axes + hold(gca,'on'); + % Try to plot image with x and y + try + image(p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii},p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii},... + p.Results.DataTable.(p.Results.DataFieldname){ii},'Parent',gca,'CDataMapping','scaled'); + axis(gca,'ij'); + set(gca,'Layer','top'); + xlim([p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(1) p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(end)]); + ylim([p.Results.DataTable(p.Results.tableSelection,:).scientaEkinMin_eV(ii) p.Results.DataTable(p.Results.tableSelection,:).scientaEkinMax_eV(ii)]); + xlabel('Photon energy [eV]') + ylabel('Auger energy [eV]') + % if this does not work, plot without scaling (just with row and column numbers) + catch + image(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},'Parent',gca,'CDataMapping','scaled'); + axis(gca,'ij'); + set(gca,'Layer','top'); + ylim([1 size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},1)]); + xlim([1 size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)]); + xlabel('# Photon energy, column number') + ylabel('# Auger energy, column number') + end + + box(gca,'on'); + title(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'Interpreter','none') + end + end \ No newline at end of file diff --git a/nappIce/nappPlot.m b/nappIce/nappPlot.m new file mode 100644 index 0000000..8535955 --- /dev/null +++ b/nappIce/nappPlot.m @@ -0,0 +1,551 @@ +function hdl = nappPlot(DataTable,varargin) +%nappPlot is the one-and-only function to plot PE spectra and images. +% +% nappPlotXps(FileList,tmpDataSelection) +% +% *input* +% FileList: data table +% tableSelection (optional): logical array to filter data table +% tableVariable (optional): select what to plot: image(default),'imageRoh','spectrum_countsPerSecond','spectrum_counts','spectrum_countsNorm' +% energyScale: kinetic (default) or binding, energy scale to be used for +% plots. +% mode: AllInOne (default) all spectra are plotted in one figure, images +% are plotted in one figure each; OneEach: all spectra are plotted in one +% figure each; iterations: each spectrum is plotted in one figure each +% showing the individual sequence iterations. +% plotStep, default 1: Specify the i-th iterations that should be +% plotted. +% +% +% *output* +% just a figure, with handle. +%% TODO +% +% TODO: Add averaging in image and in iteration plot +% TODO: Make code nicer (NEXAFS plotting) + +% Define conditions and defaults of input +defaultTableVariable = 'image'; +expectedTableVariable = {'image','imageRoh','spectrum_countsPerSecond','spectrum_counts','spectrum_countsNorm'}; +defaultMode = 'AllInOne'; +expectedMode = {'AllInOne','OneEach','iterations'}; +defaultFigureMode = 'screen'; +expectedFigureMode = {'screen','powerpoint','word'}; +defaultEnergyScale = 'kinetic'; +expectedEnergyScale = {'kinetic','binding','xRay'}; +defaultTableSelection = true(size(DataTable,1),1); +defaultPlotStep = 1; + +% Parse input +p = inputParser; +addRequired(p,'DataTable',@istable); +addOptional(p,'tableSelection',defaultTableSelection,@islogical); +addParameter(p,'tableVariable',defaultTableVariable,... + @(x) any(validatestring(x,expectedTableVariable))); +addParameter(p,'mode',defaultMode,... + @(x) any(validatestring(x,expectedMode))); +addParameter(p,'figureMode',defaultFigureMode,... + @(x) any(validatestring(x,expectedFigureMode))); +addParameter(p,'energyScale',defaultEnergyScale,... + @(x) any(validatestring(x,expectedEnergyScale))); +addParameter(p,'plotStep',defaultPlotStep); +parse(p,DataTable,varargin{:}); + +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + + +% make figure, with options for output. +if contains(p.Results.figureMode ,'screen') % standard + alw = get(groot,'DefaultAxesLineWidth'); + fsz = get(groot,'DefaultAxesFontSize'); + lw = 2; %get(groot,'DefaultLineLineWidth'); + fnt = get(groot,'DefaultAxesFontName'); + loc = 'northeastoutside'; + unt = 'pixels'; + pos = [20 100 800 500]; + +elseif contains(p.Results.figureMode,'powerpoint') + alw = 2; + fsz = 26; + lw = 4; + fnt = 'Helvetica Neue'; + loc = 'northeastoutside'; + unt = 'pixels'; + pos = [300 200 1280 720]; + +elseif contains(p.Results.figureMode,'word') + alw = 0.75; + fsz = 10; + lw = 0.5; + fnt = 'Helvetica Neue'; + loc = 'southoutside'; + unt = 'centimeters'; + pos = [8 10 8 10]; + +end + + + + + +if matches(p.Results.tableVariable,'image') + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'h5') % let's do NEXAFS first. + hdl = figure('Name',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'units', unt,'Position',pos); + + % Create axes + hold(gca,'on'); + % Try to plot image with x and y + try + % interpolate, to have equal x spacing for image plot + Xq = p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(1):0.1:p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(end); + Vq = interp2(p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii},p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii},... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},Xq,p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}); + image(Xq,p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii},... + Vq,'Parent',gca,'CDataMapping','scaled'); + axis(gca,'ij'); + set(gca,'Layer','top'); + xlim([p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(1) p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(end)]); + ylim([p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRange_eV(ii,1) p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRange_eV(ii,2)]); + hXLabel = xlabel('Photon energy [eV]'); + hYLabel = ylabel('Auger energy [eV]'); + % if this does not work, plot without scaling (just with row and column numbers) + catch + image(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},'Parent',gca,'CDataMapping','scaled'); + axis(gca,'ij'); + set(gca,'Layer','top'); + ylim([1 size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},1)]); + xlim([1 size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)]); + hXLabel = xlabel('# Photon energy, column number'); + hYLabel = ylabel('# Auger energy, column number'); + end + + box(gca,'on'); + if ~matches(p.Results.figureMode,'word') + title(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'Interpreter','none') + end + set( gca, ... + 'FontName' , fnt,'FontSize' , fsz ); + set([hXLabel, hYLabel], ... + 'FontName' , fnt); + set([hXLabel, hYLabel] , ... + 'FontSize' , 1.2*fsz ); + + set(gca, ... + 'Box' , 'off' , ... + 'TickDir' , 'out' , ... + 'TickLength' , [.02 .02] , ... + 'XMinorTick' , 'on' , ... + 'YMinorTick' , 'off' , ... + 'XGrid' , 'on' , ... + 'XColor' , [0 0 0], ... + 'YColor' , [0 0 0], ... + 'LineWidth' , alw ); + elseif endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'ibw') + + if contains(p.Results.energyScale,'kinetic') + hdl = figure('Name',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'units', unt,'Position',pos); + + % Create axes + hold(gca,'on'); + image(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii},... + 1:length(1:size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)),... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}',... + 'Parent',gca,'CDataMapping','scaled'); + axis(gca,'ij'); + set(gca,'Layer','top'); + ylim([1 size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)]); + xlim([p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(1) p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(end)]); + hXLabel = xlabel('Electron energy [eV]'); + hYLabel = ylabel('Sequence iteration'); + elseif contains(p.Results.energyScale,'binding') + hdl = figure('Name',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'units', unt,'Position',pos); + + % Create axes + hold(gca,'on'); + image(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii},... + 1:length(1:size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)),... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}',... + 'Parent',gca,'CDataMapping','scaled'); + axis(gca,'ij'); + set(gca,'Layer','top'); + ylim([1 size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)]); + % xlim([p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV(ii,1) p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV(ii,2)]); + hXLabel = xlabel('Binding energy [eV]'); + hYLabel = ylabel('Sequence iteration'); + end + box(gca,'on'); + existColumn = strcmp('sample',p.Results.DataTable.Properties.VariableNames); + if ~matches(p.Results.figureMode,'word') + if ~any(existColumn) + title([{p.Results.DataTable(p.Results.tableSelection,:).name{ii} p.Results.DataTable(p.Results.tableSelection,:).lastModifiedDatestr{ii}}],'Interpreter','none') + else + title([{p.Results.DataTable(p.Results.tableSelection,:).name{ii} p.Results.DataTable(p.Results.tableSelection,:).sample{ii} p.Results.DataTable(p.Results.tableSelection,:).lastModifiedDatestr{ii}}] ,'Interpreter','none') + end + end + set( gca, ... + 'FontName' , fnt,'FontSize' , fsz ); + set([hXLabel, hYLabel], ... + 'FontName' , fnt); + set([hXLabel, hYLabel] , ... + 'FontSize' , 1.2*fsz ); + + set(gca, ... + 'Box' , 'off' , ... + 'TickDir' , 'out' , ... + 'TickLength' , [.02 .02] , ... + 'XMinorTick' , 'on' , ... + 'YMinorTick' , 'off' , ... + 'XGrid' , 'on' , ... + 'XColor' , [0 0 0], ... + 'YColor' , [0 0 0], ... + 'LineWidth' , alw ); + end + end +end +if matches(p.Results.tableVariable,'imageRoh') + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'h5') % let's do NEXAFS first. + hdl = figure('Name',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'units', unt,'Position',pos); + + % Create axes + hold(gca,'on'); + % Try to plot image with x and y + try + image(p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii},p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii},... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},'Parent',gca,'CDataMapping','scaled'); + axis(gca,'ij'); + set(gca,'Layer','top'); + xlim([p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(1) p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(end)]); + ylim([p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRange_eV(ii,1) p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRange_eV(ii,2)]); + hXLabel = xlabel('Photon energy [eV]'); + hYLabel = ylabel('Auger energy [eV]'); + % if this does not work, plot without scaling (just with row and column numbers) + catch + image(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},'Parent',gca,'CDataMapping','scaled'); + axis(gca,'ij'); + set(gca,'Layer','top'); + ylim([1 size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},1)]); + xlim([1 size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)]); + hXLabel = xlabel('# Photon energy, column number'); + hYLabel = ylabel('# Auger energy, column number'); + end + + box(gca,'on'); + set( gca, ... + 'FontName' , fnt,'FontSize' , fsz ); + set([hXLabel, hYLabel], ... + 'FontName' , fnt); + set([hXLabel, hYLabel] , ... + 'FontSize' , 1.2*fsz ); + + set(gca, ... + 'Box' , 'off' , ... + 'TickDir' , 'out' , ... + 'TickLength' , [.02 .02] , ... + 'XMinorTick' , 'on' , ... + 'YMinorTick' , 'off' , ... + 'XGrid' , 'on' , ... + 'XColor' , [0 0 0], ... + 'YColor' , [0 0 0], ... + 'LineWidth' , alw ); + elseif endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'ibw') + + if contains(p.Results.energyScale,'kinetic') + hdl = figure('Name',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'units', unt,'Position',pos); + + % Create axes + hold(gca,'on'); + existColumn = strcmp('scientaEkinRoh_eV',DataTable.Properties.VariableNames); + if any(existColumn) + image(p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii},... + 1:length(1:size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)),... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}',... + 'Parent',gca,'CDataMapping','scaled'); + xlim([p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}(1) p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRoh_eV{ii}(end)]); + + else + image(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii},... + 1:length(1:size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)),... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}',... + 'Parent',gca,'CDataMapping','scaled'); + xlim([p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(1) p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}(end)]); + + end + axis(gca,'ij'); + set(gca,'Layer','top'); + ylim([1 size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)]); + hXLabel = xlabel('Electron energy [eV]'); + hYLabel = ylabel('Sequence iteration'); + elseif contains(p.Results.energyScale,'binding') + hdl = figure('Name',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'units', unt,'Position',pos); + + % Create axes + hold(gca,'on'); + image(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii},... + 1:length(1:size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)),... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}',... + 'Parent',gca,'CDataMapping','scaled'); + axis(gca,'ij'); + set(gca,'Layer','top'); + ylim([1 size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2)]); + % xlim([p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV(ii,1) p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV(ii,2)]); + hXLabel = xlabel('Binding energy [eV]'); + hYLabel = ylabel('Sequence iteration'); + + end + box(gca,'on'); + + existColumn = strcmp('sample',p.Results.DataTable.Properties.VariableNames); + if ~matches(p.Results.figureMode,'word') + if ~any(existColumn) + title([{p.Results.DataTable(p.Results.tableSelection,:).name{ii} p.Results.DataTable(p.Results.tableSelection,:).lastModifiedDatestr{ii}}],'Interpreter','none') + else + title([{p.Results.DataTable(p.Results.tableSelection,:).name{ii} p.Results.DataTable(p.Results.tableSelection,:).sample{ii} p.Results.DataTable(p.Results.tableSelection,:).lastModifiedDatestr{ii}}] ,'Interpreter','none') + end + end + set( gca, ... + 'FontName' , fnt,'FontSize' , fsz ); + set([hXLabel, hYLabel], ... + 'FontName' , fnt); + set([hXLabel, hYLabel] , ... + 'FontSize' , 1.2*fsz ); + + set(gca, ... + 'Box' , 'off' , ... + 'TickDir' , 'out' , ... + 'TickLength' , [.02 .02] , ... + 'XMinorTick' , 'on' , ... + 'YMinorTick' , 'off' , ... + 'XGrid' , 'on' , ... + 'XColor' , [0 0 0], ... + 'YColor' , [0 0 0], ... + 'LineWidth' , alw ); + end + end +end + + +if contains(p.Results.tableVariable,'spectrum') + if contains(p.Results.mode,'OneEach') + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + hdl = figure('Name',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'units', unt,'Position',pos); + + % Create axes + hold(gca,'on'); + if (contains(p.Results.energyScale,'kinetic') & endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'ibw')) + hplot = plot(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii},... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}'); + hplot.LineWidth = lw; + hXLabel = xlabel('Electron kinetic energy [eV]'); + xlim([p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRange_eV(ii,1) p.Results.DataTable(p.Results.tableSelection,:).scientaEkinRange_eV(ii,2)]); + + elseif (contains(p.Results.energyScale,'binding') & endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'ibw')) + hplot = plot(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii},... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}'); + hplot.LineWidth = lw; + hXLabel= xlabel('Binding energy [eV]'); + xlim([min(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy{ii}) max(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii})]); + + elseif (contains(p.Results.energyScale,'xRay') | endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'h5')) + hplot = plot(p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii},... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}); + hplot.LineWidth = lw; + hXLabel = xlabel('Photon Energy eV'); + xlim([p.Results.DataTable(p.Results.tableSelection,:).xRayEkinRange_eV(ii,1) p.Results.DataTable(p.Results.tableSelection,:).xRayEkinRange_eV(ii,2)]); + + end + if contains(p.Results.tableVariable,'Norm') + hYLabel = ylabel('Counts [arb. unit]'); + elseif contains(p.Results.energyScale,'xRay') + hYLabel = ylabel('partial A-M.E.Y.'); + else + hYLabel = ylabel('Counts per second'); + end + + + box(gca,'on'); + existColumn = strcmp('sample',p.Results.DataTable.Properties.VariableNames); + if ~matches(p.Results.figureMode,'word') + if ~any(existColumn) + title([{p.Results.DataTable(p.Results.tableSelection,:).name{ii} p.Results.DataTable(p.Results.tableSelection,:).lastModifiedDatestr{ii}}],'Interpreter','none') + else + title([{p.Results.DataTable(p.Results.tableSelection,:).name{ii} p.Results.DataTable(p.Results.tableSelection,:).sample{ii} p.Results.DataTable(p.Results.tableSelection,:).lastModifiedDatestr{ii}}] ,'Interpreter','none') + end + end + + set( gca, ... + 'FontName' , fnt,'FontSize' , fsz ); + set([hXLabel, hYLabel], ... + 'FontName' , fnt); + set([hXLabel, hYLabel] , ... + 'FontSize' , 1.2*fsz ); + + set(gca, ... + 'Box' , 'off' , ... + 'TickDir' , 'out' , ... + 'TickLength' , [.02 .02] , ... + 'XMinorTick' , 'on' , ... + 'YMinorTick' , 'off' , ... + 'XGrid' , 'on' , ... + 'XColor' , [0 0 0], ... + 'YColor' , [0 0 0], ... + 'LineWidth' , alw ); + + end + end + + if contains(p.Results.mode,'AllInOne') + % generate colormap + + hdl = figure('Name','AllInOneSpectrum','units', unt,'Position',pos); + if size(p.Results.DataTable(p.Results.tableSelection,:),1) >= 7 + tmp_color = colormap(parula(size(p.Results.DataTable(p.Results.tableSelection,:),1))); + else + tmp_color = colormap(lines(size(p.Results.DataTable(p.Results.tableSelection,:),1))); + end + if contains(p.Results.energyScale,'kinetic') + % axes('Parent',gcf,'XDir','reverse') + hold(gca,'on'); + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'ibw') + hplot = plot(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii},... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}','DisplayName',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'Color',tmp_color(ii,:)); + hplot.LineWidth = lw; + end + end + hXLabel = xlabel('Electron kinetic energy [eV]'); + elseif contains(p.Results.energyScale,'binding') + axes('Parent',gcf,'XDir','reverse') + hold(gca,'on'); + + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'ibw') + hplot = plot(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii},... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}','DisplayName',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'Color',tmp_color(ii,:)); + hplot.LineWidth = lw; + end + end + hXLabel= xlabel('Binding energy [eV]'); + elseif contains(p.Results.energyScale,'xRay') + hold(gca,'on'); + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'h5') + hplot = plot(p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii},... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},... + 'DisplayName',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'Color',tmp_color(ii,:)); + hplot.LineWidth = lw; + end + end + hXLabel = xlabel('Photon Energy eV'); + end + if contains(p.Results.tableVariable,'Norm') + hYLabel = ylabel('Counts [arb. unit]'); + elseif contains(p.Results.energyScale,'xRay') + hYLabel = ylabel('partial A-M.E.Y.'); + else + hYLabel = ylabel('Counts per second'); + end + + + box(gca,'on'); + if ~matches(p.Results.figureMode,'word') + title('PE Spectra','Interpreter','none') + hlegend = legend(p.Results.DataTable(p.Results.tableSelection,:).name{:}); + hlegend.FontSize = fsz; + hlegend.Interpreter = 'none'; + hlegend.Location = loc; + set(legend, 'Interpreter','none') + end + set( gca, ... + 'FontName' , fnt,'FontSize' , fsz ); + set([hXLabel, hYLabel], ... + 'FontName' , fnt); + set([hXLabel, hYLabel] , ... + 'FontSize' , 1.2*fsz ); + + set(gca, ... + 'Box' , 'off' , ... + 'TickDir' , 'out' , ... + 'TickLength' , [.02 .02] , ... + 'XMinorTick' , 'on' , ... + 'YMinorTick' , 'off' , ... + 'XGrid' , 'on' , ... + 'XColor' , [0 0 0], ... + 'YColor' , [0 0 0], ... + 'LineWidth' , alw ); + + + + end + + +end +if contains(p.Results.mode,'iterations') + % generate colormap + + for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'ibw') + + hdl = figure('Name',p.Results.DataTable(p.Results.tableSelection,:).name{ii},'units', unt,'Position',pos); + if size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2) >= 7 + tmp_color = colormap(parula(size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2))); + else + tmp_color = colormap(lines(size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2))); + end + + % Create axes + hold(gca,'on'); + + if contains(p.Results.energyScale,'kinetic') + for ij = 1:p.Results.plotStep:size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2) + hplot= plot(p.Results.DataTable(p.Results.tableSelection,:).scientaEkin_eV{ii}',... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(:,ij),'Color',tmp_color(ij,:)); + hplot.LineWidth = lw; + hold on + end + xlabel('Electron kinetic energy [eV]') + elseif contains(p.Results.energyScale,'binding') + for ij = 1:p.Results.plotStep:size(p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii},2) + hplot = plot(p.Results.DataTable(p.Results.tableSelection,:).bindingEnergy_eV{ii}',... + p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}(:,ij),'Color',tmp_color(ii,:)); + hplot.LineWidth = lw; + end + hXLabel = xlabel('Binding energy [eV]'); + end + if contains(p.Results.tableVariable,'Norm') + hYLabel = ylabel('Counts [arb. unit]'); + else + hYLabel = ylabel('Counts per second'); + end + + + box(gca,'on'); + if ~matches(p.Results.figureMode,'word') + title([{p.Results.DataTable(p.Results.tableSelection,:).name{ii} p.Results.DataTable(p.Results.tableSelection,:).sample{ii} p.Results.DataTable(p.Results.tableSelection,:).lastModifiedDatestr{ii}}] ,'Interpreter','none') + end + set( gca, ... + 'FontName' , fnt,'FontSize' , fsz ); + set([hXLabel, hYLabel], ... + 'FontName' , fnt); + set([hXLabel, hYLabel] , ... + 'FontSize' , 1.2*fsz ); + + set(gca, ... + 'Box' , 'off' , ... + 'TickDir' , 'out' , ... + 'TickLength' , [.02 .02] , ... + 'XMinorTick' , 'on' , ... + 'YMinorTick' , 'off' , ... + 'XGrid' , 'on' , ... + 'XColor' , [0 0 0], ... + 'YColor' , [0 0 0], ... + 'LineWidth' , alw ); + end + end +end +end + diff --git a/nappIce/nappScale.m b/nappIce/nappScale.m new file mode 100644 index 0000000..fc81083 --- /dev/null +++ b/nappIce/nappScale.m @@ -0,0 +1,193 @@ +function DataTable = nappScale(DataTable,varargin) +%nappScale can be used to normalise XPS spectra to the peak area. The peak +%of the same region or of a different region with identical SES file +%number can be used for XPS data. NEXAFS spectra can be normed to their +%area or to the intensity at an energy range of choice. +% +% FileList = nappScale(FileList,tmpDataSelection,'regionOld','C1s','regionNew','O1s'); +% +% *input* +% FileList: data table +% tableSelection (optional): logical array to filter data table. These +% spectra will be normalised. +% regionOld: C1s (default) or O1s, N1s - region spectra that will be +% normalised. Needs to be identical to the table selection (filter). +% regionNew: O1s (default) or C1s, N1s - peak area that will be used to normalise +% peakNumber: Number of the feature that should be used for fitting +% (nappFitGaussXps gives results for 4 features, default is 1) +% +% The region in tableSelection and regionOld MUST be identical. +% +% +% *output* +% table variable spectrum_countsNorm + +% Define conditions and defaults of input +defaultTableVariable = 'spectrum_countsPerSecond'; +expectedTableVariable = {'spectrum_counts','spectrum_countsPerSecond','spectrum_countsNorm'}; +defaultMode = 'area'; +expectedMode = {'intensity','area'}; +defaultRegionOld = 'C1s'; +expectedRegionOld = {'O1s','C1s','N1s','Cl2p'}; +defaultRegionNew = 'O1s'; +expectedRegionNew = {'O1s','C1s','N1s'}; +defaultPeakNumber = 1; +defaultTableSelection = true(size(DataTable,1)); + + +% Parse input +p = inputParser; +addRequired(p,'DataTable',@istable); +addOptional(p,'tableSelection',defaultTableSelection,@islogical); +addOptional(p,'energyStart',@isnumeric) +addOptional(p,'energyEnd',@isnumeric) +addParameter(p,'tableVariable',defaultTableVariable,... + @(x) any(validatestring(x,expectedTableVariable))); +addParameter(p,'regionOld',defaultRegionOld,... + @(x) any(validatestring(x,expectedRegionOld))); +addParameter(p,'regionNew',defaultRegionNew,... + @(x) any(validatestring(x,expectedRegionNew))); +addParameter(p,'peakNumber',defaultPeakNumber); +addParameter(p,'mode',defaultMode,... + @(x) any(validatestring(x,expectedMode))); +parse(p,DataTable,varargin{:}); + +% add empty variable to table +existColumn = strcmp('spectrum_countsNorm',DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.spectrum_countsNorm = cell(size(DataTable,1),1); +end + +existColumn = strcmp('logScaleRange',DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.logBackgroundRange = NaN(size(DataTable,1),2); +end +existColumn = strcmp('logScaleMode',DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.logBackgroundMode = cellstr(repmat(' ',size(p.Results.DataTable,1),1)); +end +existColumn = strcmp('logScaleDate',DataTable.Properties.VariableNames); +if ~any(existColumn) + DataTable.logBackgroundDate = cellstr(repmat(' ',size(p.Results.DataTable,1),1)); +end + +% check input (all elements of input variable need to have non-zero size) +if ~all(cell2mat(cellfun(@size,p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable),'UniformOutput',false)),'all') + disp('The table variable appears to be empty. I quit now') + error('The table variable appears to be empty.') +end + + +% repeat this for all columns in input. +for ii = 1:size(p.Results.DataTable(p.Results.tableSelection,:),1) + if endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'ibw') + % get name and date of input file and replace old region with new + % region. This will be the files where the peak area is taken from. + tmpName = replace(p.Results.DataTable(p.Results.tableSelection,:).name{ii}, ... + p.Results.regionOld,p.Results.regionNew); + tmpDate = p.Results.DataTable(p.Results.tableSelection,:).lastModifiedDatenum(ii); + % select spectra based on the new names and dates of original file + tmpDataSelection = contains(p.Results.DataTable.name,tmpName)... + & ismember(year(p.Results.DataTable.lastModifiedDatenum),year(tmpDate))... + & ismember(month(p.Results.DataTable.lastModifiedDatenum),month(tmpDate))... + & ismember(day(p.Results.DataTable.lastModifiedDatenum),day(tmpDate))... + & ismember(hour(p.Results.DataTable.lastModifiedDatenum),hour(tmpDate))... + & ismember(minute(p.Results.DataTable.lastModifiedDatenum),minute(tmpDate)); + % check peak area + existColumn = strcmp('peakArea',DataTable.Properties.VariableNames); + if any(existColumn) + if isnan(DataTable( tmpDataSelection,:).peakArea(p.Results.peakNumber)) + disp('The peak area appears to be empty. I quit now') + disp(DataTable( tmpDataSelection,:).name{ii}) + error('The peak area appears to be empty.') + end + else + disp('The data table appear to have not peak area column. I quit now') + error('No peak area column') + end + % do the norming + if contains(p.Results.mode,'area') + DataTable(p.Results.tableSelection,:).spectrum_countsNorm{ii} = ... + DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}... + ./ DataTable( tmpDataSelection,:).peakArea(p.Results.peakNumber); + elseif contains(p.Results.mode,'intensity') + disp('Intensity mode not yet programmed for XPS data') + end + + elseif endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'h5') + % if ~exist(p.Results.energyStart) | ~exist(p.Results.energyEnd) + % disp('The energy region used for normalisation appears to be empty. I quit now') + % error('The energy region used to normalise appears to be empty.') + % end + if contains(p.Results.mode,'intensity') + if p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(1)... + < p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(end) + % prepare Data + [xData, yData] = prepareCurveData(p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}... + , p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}); + % MEAN + b_1 = find(xData >= p.Results.energyStart,1); + b_2 = find(xData >= p.Results.energyEnd,1); + + b_mean = mean(yData(b_1:b_2)); + elseif p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(1)... + > p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(end) + % prepare Data + [xData, yData] = prepareCurveData( p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}... + , p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}); + % MEAN + b_1 = find(xData <= p.Results.energyStart,1); + b_2 = find(xData <= p.Results.energyEnd,1); + + b_mean = mean(yData(b_2:b_1)); + else + disp('Warning: Issue with NEXAFS_col_scaling') + end + + tmp_3(:,1) = p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}... + ./b_mean; + + DataTable(p.Results.tableSelection,:).spectrum_countsNorm{ii} = tmp_3; + clearvars tmp_3 + elseif contains(p.Results.mode,'area') + if p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(1)... + < p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(end) + % prepare Data + [xData, yData] = prepareCurveData( p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}... + , p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}); + % Area + b_1 = find(xData >= p.Results.energyStart,1); + b_2 = find(xData >= p.Results.energyEnd,1); + + b_area = trapz(xData(b_1:b_2),yData(b_1:b_2)); + elseif p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(1)... + > p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}(end) + % prepare Data + [xData, yData] = prepareCurveData( p.Results.DataTable(p.Results.tableSelection,:).xRayEkin_eV{ii}... + , p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}); + % MEAN + b_1 = find(xData <= p.Results.energyStart,1); + b_2 = find(xData <= p.Results.energyEnd,1); + + b_area = trapz(xData(b_2:b_1),yData(b_2:b_1)); + else + disp('Warning: Issue with NEXAFS_col_scaling') + end + + tmp_3(:,1) = p.Results.DataTable(p.Results.tableSelection,:).(p.Results.tableVariable){ii}... + ./b_area; + + DataTable(p.Results.tableSelection,:).spectrum_countsNorm{ii} = tmp_3; + clearvars tmp_3 + + end + end +end +% write log to table +DataTable.logScaleMode(p.Results.tableSelection,:) = cellstr(repmat(p.Results.mode,size(p.Results.DataTable(p.Results.tableSelection,:),1),1)); +if endsWith(p.Results.DataTable(p.Results.tableSelection,:).name{ii},'h5') + DataTable.logScaleRange(p.Results.tableSelection,:) = repmat([p.Results.energyStart p.Results.energyEnd],size(p.Results.DataTable(p.Results.tableSelection,:),1),1); +end +DataTable.logScaleDate(p.Results.tableSelection,:) = cellstr(repmat(datestr(now),size(p.Results.DataTable(p.Results.tableSelection,:),1),1)); + +end \ No newline at end of file