132 lines
5.4 KiB
Matlab
132 lines
5.4 KiB
Matlab
%% How do I ....
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clc;clear all;close all
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load FileList.mat
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%% ... quick-and-dirty normalize
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%
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% Normalize counts per second to a reference intensity? You need to plot the
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% two spectra and use the cursor to read the intensities from the figures.
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% Then change the spectra intensities directly in the table as shown here:
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%
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% Do not save the FileList. This way you can reload it from the MAT file to
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% start fresh.
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close all;clc
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tmpDataSelection = matches(FileList.name,"0146146_Cl2p_850eV.ibw");
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FileList = nappGenerateSpectra(FileList,tmpDataSelection);
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nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond','mode','OneEach');
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xlim([647 652])
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FileList(tmpDataSelection,:).spectrum_countsPerSecond{:} = FileList(tmpDataSelection,:).spectrum_countsPerSecond{:} .* 22335./39687;
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nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond','mode','OneEach');
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xlim([647 652])
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ylabel("counts [norm to Al]")
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legend
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distFig
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%% ... quick-and-dirty shift spectra
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%
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% If you do not want to generate the binding-energy scale using the
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% nappMATLAB function.
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close all;clc
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% Select your data based on the filename
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tmpDataSelection = startsWith(FileList.name, "0191191_O1s_VB_525eV");
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% List the selected files in the command window
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disp(FileList(tmpDataSelection,{'name','lastModifiedDatestr','scientaPassEnergy_eV'}))
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% Generate spectra
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FileList = nappGenerateSpectra(FileList,tmpDataSelection);
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% Plot in kinetic-energy mode
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nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond','mode','AllInOne','energyScale','kinetic');
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% Apply the shift to kinetic energy manually and plot
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FileList(tmpDataSelection,:).scientaEkin_eV{:} = FileList(tmpDataSelection,:).scientaEkin_eV{:}-20;
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nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond','mode','AllInOne','energyScale','kinetic');
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distFig
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%% ... remove a sweep (sequence iteration) from data
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close all; clc
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% Remove sweep 3:
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tmpDataSelection = contains(FileList.name,'0146146_Al2p_850eV.ibw');
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nappPlot(FileList,tmpDataSelection,'tableVariable','image')
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FileList(tmpDataSelection,:).image{:}(:,3)=[];
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nappPlot(FileList,tmpDataSelection,'tableVariable','image')
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distFig
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%% ... remove several sweeps
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close all; clc
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tmpDataSelection = contains(FileList.name,'0146146_Al2p_850eV.ibw');
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% Remove sweeps 5–9
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nappPlot(FileList,tmpDataSelection,'tableVariable','image')
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FileList(tmpDataSelection,:).image{:}(:,5:9)=[];
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nappPlot(FileList,tmpDataSelection,'tableVariable','image')
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distFig
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%% ... correct beamline offset
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% This will correct 1.6 eV on the X-ray energies, which is particularly
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% important for NEXAFS data. One can also do this on selected data only.
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FileList.xRayEkin_eV = cellfun(@(x) x+1.6,FileList.xRayEkin_eV,'UniformOutput',false);
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%% ... on-the-fly shift data in a figure
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tmpDataSelection = month(FileList.lastModifiedDatenum) == 11 ...
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& year(FileList.lastModifiedDatenum) == 2025 ...
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& ~contains(FileList.sample,"(bad data)") ...
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& contains(FileList.name,"O_Kedge_Resonant") ...
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& contains(FileList.name,"0025");
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nappPlot(FileList,tmpDataSelection,'tableVariable','image','mode','AugerMeitner','AugerMeitnerEnergies',[525,545,550]);
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hax = gca;
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hax.XDir = 'reverse';
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xlabel('Auger-Meitner binding energy [eV]');
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% Shift data (same works in Y direction)
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dataObjs = findobj(gcf,'-property','YData');
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dataObjs(1).XData = dataObjs(1).XData -10;
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dataObjs(2).XData = dataObjs(2).XData +10;
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dataObjs(3).XData = dataObjs(3).XData +20;
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%% ... on-the-fly smooth data in a figure
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clc;close all
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tmpDataSelection = month(FileList.lastModifiedDatenum) == 11 ...
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& year(FileList.lastModifiedDatenum) == 2025 ...
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& ~contains(FileList.sample,"(bad data)") ...
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& contains(FileList.name,"O_Kedge_Resonant") ...
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& contains(FileList.name,"0025");
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nappPlot(FileList,tmpDataSelection,'tableVariable','image','mode','AugerMeitner','AugerMeitnerEnergies',[525,545,550]);
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hax = gca;
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hax.XDir = 'reverse';
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xlabel('Auger-Meitner binding energy [eV]');
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dataObjs = findobj(gcf,'-property','YData');
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y = dataObjs(1).YData;
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dataObjs(1).YData = smoothdata(y ,'sgolay',10);
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y = dataObjs(2).YData;
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dataObjs(2).YData = smoothdata(y ,'sgolay',10);
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y = dataObjs(3).YData;
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dataObjs(3).YData = smoothdata(y ,'sgolay',10);
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%% ... on-the-fly remove data from a figure
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clc;close all
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tmpDataSelection = month(FileList.lastModifiedDatenum) == 11 ...
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& year(FileList.lastModifiedDatenum) == 2025 ...
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& ~contains(FileList.sample,"(bad data)") ...
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& contains(FileList.name,"O_Kedge_Resonant") ...
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& contains(FileList.name,"0025");
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nappPlot(FileList,tmpDataSelection,'tableVariable','image','mode','AugerMeitner','AugerMeitnerEnergies',[525,545,550]);
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hax = gca;
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hax.XDir = 'reverse';
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xlabel('Auger-Meitner binding energy [eV]');
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dataObjs = findobj(gcf,'-property','YData');
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delete(dataObjs(1))
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legend('545','550');
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%% ... on-the-fly change colors in a figure
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clc;close all
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tmpDataSelection = month(FileList.lastModifiedDatenum) == 11 ...
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& year(FileList.lastModifiedDatenum) == 2025 ...
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& ~contains(FileList.sample,"(bad data)") ...
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& contains(FileList.name,"O_Kedge_Resonant") ...
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& contains(FileList.name,"0025");
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nappPlot(FileList,tmpDataSelection,'tableVariable','image','mode','AugerMeitner','AugerMeitnerEnergies',[525,545,550]);
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hax = gca;
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hax.XDir = 'reverse';
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xlabel('Auger-Meitner binding energy [eV]');
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dataObjs = findobj(gcf,'-property','YData');
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dataObjs(2).Color = [184 184 185]/255;
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dataObjs(3).Color = [58 162 190]/255;
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