BREAKING CHANGES:
- Single-spectrum fitting only (enforces exactly one row selected)
- Gauss fitting now uses FWHM parameter instead of Gaussian width sigma
- Removed multi-row batch processing capability
NEW FEATURES:
- Generic model architecture: arbitrary number of peaks (determined by length of FitParameter.peakArea)
- Full Shirley background support for both Gaussian and Pseudo-Voigt peak shapes
- Comprehensive parameter validation system with detailed error messages
- Support for shared vs per-peak Shirley K parameters
- New fitting modes: 'positionShirley', 'widthShirley', 'widthPositionShirley'
- New custom mode: 'TwoSpinOrbitDoubletPseudoVoigtShirley'
- Automatic field name typo correction ('Bond' → 'Bound')
- Enhanced results export: now includes peakEta and peakShirleyK columns
REFACTORING:
- Centralized peak and background equations in helper functions
- gaussPeak(), lorentzPeak(), pseudoVoigtPeak()
- linearBackground(), activeShirleyBackgroundFwhm()
- fwhm2w() conversion utility
- Extracted model generation to genericModelGenerator()
- Modular validation helpers: checkFieldDimension(), checkBoundsPair()
- Standardized parameter vector layouts documented for all mode/background/peak-type combinations
- Improved column resizing logic with resizeColumnHelper()
- Enhanced plotting integration with nappPlot.m and nappAddFitToPlot.m
ARCHITECTURE:
- Unified parameter extraction for all fitting modes in centralized switch-case structure
- Consistent FWHM-based width parameterization across all peak types
- Mode-specific Shirley K sizing (scalar for shared modes, array for per-peak modes)
- Comprehensive inline documentation of parameter vector layouts (50+ combinations)
IMPROVEMENTS:
- Backward compatibility for 'gauss' width mode (auto-converts to FWHM)
- Robust bounds checking with detailed diagnostic messages
- Enhanced figure generation: residuals plot + fit visualization in tiledlayout
- Better error handling for empty/malformed data structures
- NaN-padded result arrays for variable peak counts
FILE SIZE: ~73KB → ~152KB (107% increase due to comprehensive documentation and generic architecture)
152 lines
4.8 KiB
Matlab
152 lines
4.8 KiB
Matlab
function plotExportedData(dataDirectory)
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%plotExportedData Plot all exported ASCII data files in one figure
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%
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% This function reads all .txt files from the exported data (created by
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% exportFigureData) and plots them in a single figure for visual comparison.
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% File names are parsed to extract axis labels and legend entries.
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%
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% SYNTAX:
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% plotExportedData() % Uses current working directory
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% plotExportedData(dataDirectory) % Uses specified directory path
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%
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% INPUTS:
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% dataDirectory : char or string (optional)
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% Path to directory containing exported .txt files.
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% If omitted, uses current working directory (pwd).
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%
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% OUTPUT:
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% A new figure with all data plotted as lines. Axis labels and legend
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% entries are reconstructed from the file names.
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%
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% NOTES:
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% - Reads all .txt files in the specified directory
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% - File name format expected: <FigureTitle>_[<TileTitle>_]<YLabel>_vs_<XLabel>_<LineLabel>.txt
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% - Plots are created with underscores converted back to spaces for display
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% - X and Y axis labels are set based on parsed filename
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% - Legend shows line labels from filenames
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% - All data is plotted in a single axes for direct visual comparison
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%
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% EXAMPLE:
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% % After running exportFigureData():
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% plotExportedData()
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% % or
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% plotExportedData('../exported_data/')
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% Handle input: use current directory if none provided
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if nargin == 0 || isempty(dataDirectory)
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dataDirectory = pwd;
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end
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% Get all .txt files in the directory
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fileStruct = dir(fullfile(dataDirectory, '*.txt'));
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if isempty(fileStruct)
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warning('plotExportedData:NoFiles', 'No .txt files found in %s', dataDirectory);
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return;
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end
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% Create a new figure
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fig = figure('Name', 'Exported Data Comparison', 'NumberTitle', 'off');
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ax = axes(fig);
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hold(ax, 'on');
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grid(ax, 'on');
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% Storage for axis labels (to ensure consistency)
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xLabelStr = '';
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yLabelStr = '';
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legendEntries = {};
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% Loop over all .txt files
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for ii = 1:length(fileStruct)
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fileName = fileStruct(ii).name;
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filePath = fullfile(dataDirectory, fileName);
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% Read the data
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try
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data = readmatrix(filePath);
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catch ME
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warning('plotExportedData:ReadFailed', 'Could not read file: %s\n%s', fileName, ME.message);
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continue;
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end
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% Check if data has at least 2 columns
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if size(data, 2) < 2 || size(data, 1) < 1
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warning('plotExportedData:InvalidData', 'File %s does not have valid X,Y columns', fileName);
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continue;
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end
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xData = data(:, 1);
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yData = data(:, 2);
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% Parse filename to extract labels
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% Expected format: <FigureTitle>_[<TileTitle>_]<YLabel>_vs_<XLabel>_<LineLabel>.txt
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% Remove .txt extension
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nameNoExt = fileName(1:end-4);
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% Split by '_vs_' to separate y-axis label from the rest
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parts = strsplit(nameNoExt, '_vs_');
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if length(parts) >= 2
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% Extract line label (after _vs_<XLabel>_)
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rightPart = parts{2}; % <XLabel>_<LineLabel>
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% Find the last underscore to separate XLabel from LineLabel
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underscores = find(rightPart == '_');
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if ~isempty(underscores)
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lastUnderscore = underscores(end);
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xLabelExtracted = rightPart(1:lastUnderscore-1);
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lineLabel = rightPart(lastUnderscore+1:end);
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else
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xLabelExtracted = rightPart;
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lineLabel = 'data';
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end
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% Extract y-axis label (before _vs_)
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yLabelExtracted = parts{1};
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% Remove figure title (first part before first underscore)
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% This is tricky, so we'll keep what we have and note it's approximate
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% Convert underscores back to spaces for display
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xLabelDisplay = strrep(xLabelExtracted, '_', ' ');
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yLabelDisplay = strrep(yLabelExtracted, '_', ' ');
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lineLabel = strrep(lineLabel, '_', ' ');
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% Store axis labels (use the first valid ones found)
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if isempty(xLabelStr)
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xLabelStr = xLabelDisplay;
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end
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if isempty(yLabelStr)
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yLabelStr = yLabelDisplay;
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end
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else
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% Fallback if filename parsing fails
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lineLabel = nameNoExt;
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end
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% Plot the data
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plot(ax, xData, yData, 'DisplayName', lineLabel, 'LineWidth', 1.5, 'Marker', 'o', 'MarkerSize', 4);
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% Store legend entry
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legendEntries{end+1} = lineLabel;
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end
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% Set axis labels
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xlabel(ax, xLabelStr, 'Interpreter', 'none');
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ylabel(ax, yLabelStr, 'Interpreter', 'none');
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title(ax, 'Exported Data Comparison', 'Interpreter', 'none');
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% Add legend
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if ~isempty(legendEntries)
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legend(ax, legendEntries, 'Interpreter', 'none', 'Location', 'best');
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end
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% Optimize figure appearance
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grid(ax, 'on');
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hold(ax, 'off');
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fprintf('Plotted %d data files from: %s\n', length(fileStruct), dataDirectory);
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end
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