%% How do I ....
clc;clear all;close all
load FileList.mat

%% ... quick-and-dirty normalize
%
% Normalize counts per second to a reference intensity? You need to plot the
% two spectra and use the cursor to read the intensities from the figures.
% Then change the spectra intensities directly in the table as shown here:
%
% Do not save the FileList. This way you can reload it from the MAT file to
% start fresh.
close all;clc
tmpDataSelection =  matches(FileList.name,"0146146_Cl2p_850eV.ibw");
FileList = nappGenerateSpectra(FileList,tmpDataSelection);
nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond','mode','OneEach');
xlim([647 652])
FileList(tmpDataSelection,:).spectrum_countsPerSecond{:} = FileList(tmpDataSelection,:).spectrum_countsPerSecond{:} .* 22335./39687;
nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond','mode','OneEach');
xlim([647 652])
ylabel("counts [norm to Al]")
legend
distFig

%% ... quick-and-dirty shift spectra
%
% If you do not want to generate the binding-energy scale using the
% nappMATLAB function.
close all;clc
% Select your data based on the filename
tmpDataSelection = startsWith(FileList.name, "0191191_O1s_VB_525eV");
% List the selected files in the command window
disp(FileList(tmpDataSelection,{'name','lastModifiedDatestr','scientaPassEnergy_eV'}))
% Generate spectra
FileList = nappGenerateSpectra(FileList,tmpDataSelection);
% Plot in kinetic-energy mode
nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond','mode','AllInOne','energyScale','kinetic');
% Apply the shift to kinetic energy manually and plot
FileList(tmpDataSelection,:).scientaEkin_eV{:} = FileList(tmpDataSelection,:).scientaEkin_eV{:}-20;
nappPlot(FileList,tmpDataSelection,'tableVariable','spectrum_countsPerSecond','mode','AllInOne','energyScale','kinetic');
distFig

%% ... remove a sweep (sequence iteration) from data
close all; clc
% Remove sweep 3:
tmpDataSelection = contains(FileList.name,'0146146_Al2p_850eV.ibw');
nappPlot(FileList,tmpDataSelection,'tableVariable','image')
FileList(tmpDataSelection,:).image{:}(:,3)=[];
nappPlot(FileList,tmpDataSelection,'tableVariable','image')
distFig

%% ... remove several sweeps
close all; clc
tmpDataSelection = contains(FileList.name,'0146146_Al2p_850eV.ibw');
% Remove sweeps 5–9
nappPlot(FileList,tmpDataSelection,'tableVariable','image')
FileList(tmpDataSelection,:).image{:}(:,5:9)=[];
nappPlot(FileList,tmpDataSelection,'tableVariable','image')
distFig

%% ... correct beamline offset
% This will correct 1.6 eV on the X-ray energies, which is particularly
% important for NEXAFS data. One can also do this on selected data only.
FileList.xRayEkin_eV = cellfun(@(x) x+1.6,FileList.xRayEkin_eV,'UniformOutput',false);

%% ... on-the-fly shift data in a figure
tmpDataSelection =  month(FileList.lastModifiedDatenum) == 11 ...
    & year(FileList.lastModifiedDatenum) == 2025 ...
    & ~contains(FileList.sample,"(bad data)") ...
    & contains(FileList.name,"O_Kedge_Resonant") ...
    & contains(FileList.name,"0025");
nappPlot(FileList,tmpDataSelection,'tableVariable','image','mode','AugerMeitner','AugerMeitnerEnergies',[525,545,550]);
hax = gca;
hax.XDir = 'reverse';
xlabel('Auger-Meitner binding energy [eV]');
% Shift data (same works in Y direction)
dataObjs = findobj(gcf,'-property','YData');
dataObjs(1).XData = dataObjs(1).XData -10;
dataObjs(2).XData = dataObjs(2).XData +10;
dataObjs(3).XData = dataObjs(3).XData +20;

%% ... on-the-fly smooth data in a figure
clc;close all
tmpDataSelection =  month(FileList.lastModifiedDatenum) == 11 ...
    & year(FileList.lastModifiedDatenum) == 2025 ...
    & ~contains(FileList.sample,"(bad data)") ...
    & contains(FileList.name,"O_Kedge_Resonant") ...
    & contains(FileList.name,"0025");
nappPlot(FileList,tmpDataSelection,'tableVariable','image','mode','AugerMeitner','AugerMeitnerEnergies',[525,545,550]);
hax = gca;
hax.XDir = 'reverse';
xlabel('Auger-Meitner binding energy [eV]');
dataObjs = findobj(gcf,'-property','YData');
y = dataObjs(1).YData;
dataObjs(1).YData = smoothdata(y ,'sgolay',10);
y = dataObjs(2).YData;
dataObjs(2).YData = smoothdata(y ,'sgolay',10);
y = dataObjs(3).YData;
dataObjs(3).YData = smoothdata(y ,'sgolay',10);

%% ... on-the-fly remove data from a figure
clc;close all
tmpDataSelection =  month(FileList.lastModifiedDatenum) == 11 ...
    & year(FileList.lastModifiedDatenum) == 2025 ...
    & ~contains(FileList.sample,"(bad data)") ...
    & contains(FileList.name,"O_Kedge_Resonant") ...
    & contains(FileList.name,"0025");
nappPlot(FileList,tmpDataSelection,'tableVariable','image','mode','AugerMeitner','AugerMeitnerEnergies',[525,545,550]);
hax = gca;
hax.XDir = 'reverse';
xlabel('Auger-Meitner binding energy [eV]');

dataObjs = findobj(gcf,'-property','YData');
delete(dataObjs(1))
legend('545','550');

%% ... on-the-fly change colors in a figure
clc;close all
tmpDataSelection =  month(FileList.lastModifiedDatenum) == 11 ...
    & year(FileList.lastModifiedDatenum) == 2025 ...
    & ~contains(FileList.sample,"(bad data)") ...
    & contains(FileList.name,"O_Kedge_Resonant") ...
    & contains(FileList.name,"0025");
nappPlot(FileList,tmpDataSelection,'tableVariable','image','mode','AugerMeitner','AugerMeitnerEnergies',[525,545,550]);
hax = gca;
hax.XDir = 'reverse';
xlabel('Auger-Meitner binding energy [eV]');

dataObjs = findobj(gcf,'-property','YData');
dataObjs(2).Color = [184 184 185]/255;
dataObjs(3).Color = [58 162 190]/255;