bartels-rausch
091cf00e77
* Transitioned nappNorm, nappDetermineShift, and nappCopyShift to use modern MATLAB arguments blocks, removing their legacy functionSignatures.json entries.
* Refactored nappNorm to rely on prior peak fitting results (e.g., from nappFitGaussXps) for normalization rather than performing the fitting internally.
* Decoupled energy calibration: nappDetermineShift now solely calculates internal binding energy shifts, and nappCopyShift distributes them using a unified matching engine ('earlier', 'after', 'spectrumNumber').
* Implemented a Universal Logging Block to track data provenance, automatically appending execution timestamps and caller script names to processed rows.
* Updated nappCombineSpectra to output a logDataSource cell array and cleanly name combined spectra.
* Created nappSaveDataTable for automatic, script-named .mat file saving, complete with a Live Editor interceptor.
* Added a publish-mode silencer to nappFitGaussXps to prevent optimizer spam in generated PDFs.
* Updated readme.md to document the new arguments structure, the 3-step calibration workflow, the matching engine, and the new table variables.
249 lines
8.4 KiB
Matlab
249 lines
8.4 KiB
Matlab
function nappAddFitToPlot(DataTable, varargin)
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% nappAddFitToPlot - Plot fitted peaks with proper decomposition
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% FIXED: Correct pseudo-Voigt normalization and FWHM extraction
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% Parse input arguments
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p = inputParser;
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addOptional(p, 'tableSelection', []);
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addOptional(p, 'plotHandle', gca);
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addOptional(p, 'peakWidthMode', 'FWHM');
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addOptional(p, 'energyScale', 'kinetic');
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parse(p, varargin{:});
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% Get data from table
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if isempty(p.Results.tableSelection)
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fitData = DataTable(1, :);
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else
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fitData = DataTable(p.Results.tableSelection, :);
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end
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% Get energy range from current figure xlim
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ax = p.Results.plotHandle;
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axes(ax);
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xlims = xlim(ax);
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energyMin = xlims(1);
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energyMax = xlims(2);
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% Create energy range with 0.2 eV step
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energyStep = 0.2;
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energyRange = (energyMin:energyStep:energyMax)';
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% =====================================================================
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% COUNT ONLY NON-NaN PEAKS
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% =====================================================================
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peakArea_vals = fitData.peakArea; % Extract from cell
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validPeaks = ~isnan(peakArea_vals); % Find non-NaN values
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nPeaks = sum(validPeaks); % Count valid peaks
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fprintf('Found %d valid peaks (non-NaN)\n', nPeaks);
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if isempty(energyRange) || nPeaks == 0
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warning('No valid fit data to plot');
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return;
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end
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% Initialize output
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peakCurves = zeros(length(energyRange), nPeaks);
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totalFit = zeros(size(energyRange));
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peakTypes = cell(nPeaks, 1);
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% Extract peak parameters (cell arrays)
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peakPos_vals = fitData.peakPosition;
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peakFWHM_vals = fitData.peakFWHM;
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% Check for peak eta parameter (pseudo-Voigt indicator)
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hasPeakEta = ismember('peakEta', fitData.Properties.VariableNames) && ...
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~all(isnan(fitData.peakEta));
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if hasPeakEta
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peakEta_vals = fitData.peakEta;
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end
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% =====================================================================
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% MAIN LOOP: Process each VALID peak
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% =====================================================================
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validIdx = find(validPeaks); % Get indices of valid peaks
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for i = 1:nPeaks
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iPeak = validIdx(i); % Actual peak index in array
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% Extract peak parameters
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pos = peakPos_vals(iPeak);
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A_total = peakArea_vals(iPeak);
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FWHM = peakFWHM_vals(iPeak);
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% Skip if FWHM is NaN or invalid
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if isnan(FWHM) || FWHM <= 0
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fprintf(' WARNING: Peak %d has invalid FWHM = %g, skipping\n', iPeak, FWHM);
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continue;
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end
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% Check if this is a pseudo-Voigt peak
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if hasPeakEta && ~isnan(peakEta_vals(iPeak))
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% ============================================================
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% PSEUDO-VOIGT: Gaussian + Lorentzian blend
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% eta = Gaussian fraction (0 = pure Lorentzian, 1 = pure Gaussian)
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% ============================================================
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eta = peakEta_vals(iPeak);
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% === GAUSSIAN COMPONENT (FWHM-based) ===
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% G(E) = A_gauss * sqrt(4*ln(2)/pi) / FWHM * exp(-4*ln(2)*(E-E0)^2/FWHM^2)
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% This is normalized so integral = A_gauss
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A_gauss = eta * A_total; % Gaussian gets eta fraction of total area
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gauss_norm = sqrt(4*log(2)/pi) / FWHM;
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peakG = A_gauss .* gauss_norm .* ...
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exp(-4*log(2) * ((energyRange - pos)./FWHM).^2);
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% === LORENTZIAN COMPONENT (FWHM-based) ===
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% L(E) = A_lorentz * (FWHM/2) / pi / ((E-E0)^2 + (FWHM/2)^2)
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% This is normalized so integral = A_lorentz
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A_lorentz = (1 - eta) * A_total; % Lorentzian gets (1-eta) fraction
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gamma = FWHM / 2; % Half-width at half-maximum
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peakL = A_lorentz .* (gamma / pi) ./ ...
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((energyRange - pos).^2 + gamma.^2);
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% === COMBINED PSEUDO-VOIGT ===
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peak = peakG + peakL;
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peakTypes{i} = sprintf('Pseudo-Voigt (η=%.3f)', eta);
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else
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% ============================================================
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% PURE GAUSSIAN using FWHM
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% G(E) = A * sqrt(4*ln(2)/pi) / FWHM * exp(-4*ln(2)*(E-E0)^2/FWHM^2)
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% ============================================================
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gauss_norm = sqrt(4*log(2)/pi) / FWHM;
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peak = A_total .* gauss_norm .* ...
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exp(-4*log(2) * ((energyRange - pos)./FWHM).^2);
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peakTypes{i} = 'Gaussian';
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end
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peakCurves(:, i) = peak;
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totalFit = totalFit + peak;
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end
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% =====================================================================
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% ADD BACKGROUND
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% =====================================================================
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% Check for Shirley background parameters
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hasShirleyK = ismember('peakShirleyK', fitData.Properties.VariableNames) && ...
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~all(isnan(fitData.peakShirleyK));
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if hasShirleyK
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% SHIRLEY BACKGROUND RECONSTRUCTION
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peakShirleyK_vals = fitData.peakShirleyK;
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bkgrd = zeros(size(energyRange));
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for i = 1:nPeaks
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iPeak = validIdx(i);
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% Extract parameters
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area = peakArea_vals(iPeak);
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FWHM = peakFWHM_vals(iPeak);
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pos = peakPos_vals(iPeak);
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if ismember('peakEta', fitData.Properties.VariableNames) && ~all(isnan(fitData.peakEta))
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eta = peakEta_vals(iPeak);
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else
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eta = 1;
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end
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K = peakShirleyK_vals(iPeak);
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% Calculate width parameters
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w = FWHM / sqrt(log(4));
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sigma = w / 2;
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gamma = FWHM / 2;
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% Cumulative Distribution Functions (CDFs) going from 0 to 1
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% This represents the integral of the peak from -infinity to E
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G_cdf = 0.5 * (1 + erf((energyRange - pos) / (sqrt(2) * sigma)));
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L_cdf = 0.5 + (1/pi) * atan((energyRange - pos) / gamma);
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% Combined Pseudo-Voigt CDF
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integral_fraction = eta * G_cdf + (1 - eta) * L_cdf;
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% Shirley Contribution
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if matches(p.Results.energyScale, 'kinetic')
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% For Kinetic Energy: background is higher at LOWER energies.
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% Step goes from 1 (at E << pos) to 0 (at E >> pos)
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shirleycontrib = K * area * (1 - integral_fraction);
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else
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% For Binding Energy: background is higher at HIGHER energies.
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% Step goes from 0 (at E << pos) to 1 (at E >> pos)
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shirleycontrib = K * area * integral_fraction;
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end
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bkgrd = bkgrd + shirleycontrib;
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end
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% Add constant offset C0
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if ismember('peakBackground', fitData.Properties.VariableNames)
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C0 = fitData.peakBackground(2); % Second element is C0
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bkgrd = bkgrd + C0;
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end
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backgroundType = 'Shirley';
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else
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% LINEAR BACKGROUND (existing code)
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if ismember('peakBackground', fitData.Properties.VariableNames)
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bkgrd_vals = fitData.peakBackground;
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if length(bkgrd_vals) >= 2
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slope = bkgrd_vals(1);
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intercept = bkgrd_vals(2);
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else
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slope = 0;
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intercept = bkgrd_vals(1);
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end
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else
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slope = 0;
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intercept = 0;
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end
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bkgrd = slope .* energyRange + intercept;
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backgroundType = sprintf('Linear (slope=%.4f, intercept=%.4f)', slope, intercept);
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end
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totalFit = totalFit + bkgrd;
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% =====================================================================
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% PLOT RESULTS
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% =====================================================================
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axes(ax);
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hold on;
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% Plot total fit (thick red line)
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plot(energyRange, totalFit, '-', 'LineWidth', 2.5, 'Color', [0.8 0.2 0.2], 'DisplayName', 'Total Fit');
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% Plot background (dotted gray line)
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plot(energyRange, bkgrd, ':', 'LineWidth', 1.5, 'Color', [0.5 0.5 0.5], 'DisplayName', 'Background');
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% Plot individual peaks (dashed colored lines)
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colors = lines(nPeaks);
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for i = 1:nPeaks
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if any(peakCurves(:, i)) % Only plot if non-zero
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plot(energyRange, peakCurves(:, i)+bkgrd, '--', 'LineWidth', 1.2, ...
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'Color', colors(i,:), 'DisplayName', sprintf('Peak %d', i));
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end
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end
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legend('show', 'Location', 'best');
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hold off;
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% % =====================================================================
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% % DISPLAY INFORMATION
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% % =====================================================================
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% fprintf('\n=== FIT PLOTTED SUCCESSFULLY ===\n');
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% fprintf('Valid peaks: %d\n', nPeaks);
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% fprintf('Peak type(s): ');
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% for i = 1:nPeaks
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% fprintf('%s', peakTypes{i});
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% if i < nPeaks, fprintf('; '); end
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% end
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% fprintf('\n');
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% fprintf('Energy range: %.1f - %.1f eV\n', min(energyRange), max(energyRange));
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% fprintf('=====================================\n\n');
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% fprintf('Background: %s\n', backgroundType);
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end
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