448 lines
18 KiB
Matlab
448 lines
18 KiB
Matlab
%% ===== BEC-Stripes Settings =====
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% Specify data location to run analysis on
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%%
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dataSources = {
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struct('sequence', 'StructuralPhaseTransition', ...
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'date', '2025/10/11', ...
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'runs', [1]) % specify run numbers as a string in "" or just as a numeric value
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};
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%%
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%{
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dataSources = {
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struct('sequence', 'StructuralPhaseTransition', ...
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'date', '2025/10/10', ...
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'runs', [2]) % specify run numbers as a string in "" or just as a numeric value
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};
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%}
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%%
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options = struct();
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% File paths
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options.baseDataFolder = '//DyLabNAS/Data';
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options.FullODImagesFolder = 'E:/Data - Experiment/FullODImages/202510';
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options.measurementName = 'BECToStripes';
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scriptFullPath = mfilename('fullpath');
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options.saveDirectory = fileparts(scriptFullPath);
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% Camera / imaging settings
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options.cam = 4; % 1 - ODT_1_Axis_Camera; 2 - ODT_2_Axis_Camera; 3 - Horizontal_Axis_Camera;, 4 - Vertical_Axis_Camera;
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options.angle = 0; % angle by which image will be rotated
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options.center = [1420, 2040];
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options.span = [200, 200];
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options.fraction = [0.1, 0.1];
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options.pixel_size = 5.86e-6; % in meters
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options.magnification = 23.2;
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options.ImagingMode = 'HighIntensity';
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options.PulseDuration = 5e-6; % in s
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% Fourier analysis settings
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options.theta_min = deg2rad(0);
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options.theta_max = deg2rad(180);
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options.N_radial_bins = 500;
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options.Radial_Sigma = 2;
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options.Radial_WindowSize = 5; % odd number
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options.k_min = 1.2771; % μm⁻¹
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options.k_max = 2.5541; % μm⁻¹
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options.N_angular_bins = 180;
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options.Angular_Threshold = 75;
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options.Angular_Sigma = 2;
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options.Angular_WindowSize = 5;
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options.zoom_size = 50;
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% Flags
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options.skipUnshuffling = false;
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options.skipNormalization = false;
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options.skipFringeRemoval = true;
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options.skipPreprocessing = true;
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options.skipMasking = true;
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options.skipIntensityThresholding = true;
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options.skipBinarization = true;
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options.skipFullODImagesFolderUse = false;
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options.skipSaveData = false;
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options.skipSaveFigures = true;
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options.skipSaveProcessedOD = true;
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options.skipLivePlot = true;
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options.showProgressBar = true;
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% Extras
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options.font = 'Bahnschrift';
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switch options.measurementName
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case 'BECToDroplets'
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options.scan_parameter = 'rot_mag_field';
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options.flipSortOrder = false;
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options.scanParameterUnits = 'gauss';
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options.titleString = 'BEC to Droplets';
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case 'BECToStripes'
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options.scan_parameter = 'rot_mag_field';
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options.flipSortOrder = false;
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options.scanParameterUnits = 'gauss';
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options.titleString = 'BEC to Stripes';
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case 'DropletsToStripes'
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options.scan_parameter = 'ps_rot_mag_fin_pol_angle';
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options.flipSortOrder = false;
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options.scanParameterUnits = 'degrees';
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options.titleString = 'Droplets to Stripes';
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case 'StripesToDroplets'
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options.scan_parameter = 'ps_rot_mag_fin_pol_angle';
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options.flipSortOrder = false;
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options.scanParameterUnits = 'degrees';
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options.titleString = 'Stripes to Droplets';
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end
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%% ===== Collect Images and Launch Viewer =====
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[options.selectedPath, options.folderPath] = Helper.selectDataSourcePath(dataSources, options);
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[od_imgs, scan_parameter_values, scan_reference_values, file_list] = Helper.collectODImages(options);
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%% Conduct spectral analysis
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spectral_analysis_results = Analyzer.extractFullRadialSpectralDistribution(od_imgs, options);
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%% ------------------ 1. Plot of all Radial Spectral Distribution Curves ------------------
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Plotter.plotSpectralCurves( ...
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spectral_analysis_results.S_k_all, ...
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spectral_analysis_results.k_rho_vals, ...
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scan_reference_values, ... % correct scan params
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'Title', options.titleString, ...
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'XLabel', 'k_\rho', ...
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'YLabel', 'S(k_\rho)', ...
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'YScale', 'log', ...
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'XLim', [min(spectral_analysis_results.k_rho_vals), max(spectral_analysis_results.k_rho_vals)], ...
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'HighlightEvery', 10, ... % highlight every 10th repetition
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'FontName', options.font, ...
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'FigNum', 1, ...
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'TileTitlePrefix', 'B', ... % user-defined tile prefix
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'TileTitleSuffix', 'G', ... % user-defined suffix (e.g., degrees symbol)
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SpectralCurves.fig', ...
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'SaveDirectory', options.saveDirectory);
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%% ------------------ 2. Fit truncated Radial Spectral Distribution Curves ------------------
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[fitResults, rawCurves] = Analyzer.fitTwoGaussianCurvesToRadialSpectralDistribution(...
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spectral_analysis_results.S_k_all, ... % radial spectral curves
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spectral_analysis_results.k_rho_vals, ... % corresponding k_rho values
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'KRhoRange', [0, 3], ... % truncate curves to 0 <= k_rho <= 3
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'AmplitudeRange', [0, 0.3], ... % truncate curves to y >= 0 (all amplitudes)
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'ResidualThreshold', 0.175, ... % maximum allowed residual
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'PositionThreshold', 0.5, ... % minimum separation between peaks
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'AmplitudeThreshold', 0.015); ... % minimum secondary peak fraction
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%% Post-fit diagnostics
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% --- Determine max number of parameters across all fits ---
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maxParams = max(cellfun(@numel, {fitResults.pFit}));
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% --- Preallocate padded array ---
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Ncurves = numel(fitResults);
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pFit_all = nan(Ncurves, maxParams);
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% --- Fill padded array ---
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for k = 1:Ncurves
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pk = fitResults(k).pFit;
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pFit_all(k,1:numel(pk)) = pk;
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end
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isValid_all = [fitResults.isValid]; % logical vector
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% --- Extract parameters of the SECOND Gaussian only ---
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% For both 2G and 3G, second Gaussian = indices 4:6
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pSecond = pFit_all(:, 4:6);
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% --- Diagnostics ---
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numWithNaN = sum(any(isnan(pSecond), 2));
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numWithZero = sum(any(pSecond == 0, 2));
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numValid = sum(isValid_all);
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% Display summary
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fprintf('\n--- Fit diagnostics (second Gaussian only) ---\n');
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fprintf('Curves with ≥1 NaN in second Gaussian params: %d\n', numWithNaN);
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fprintf('Curves with ≥1 zero in second Gaussian params: %d\n', numWithZero);
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fprintf('Curves marked as isValid = true: %d\n', numValid);
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fprintf('----------------------------------------\n\n');
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%% ------------------ Plot Fits on Raw ------------------
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options.skipLivePlot = true;
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Plotter.plotTwoModeGaussianFitsOnRawRSD(fitResults, rawCurves, 4, 6, ...
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'SkipLivePlot', options.skipLivePlot, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveDirectory', options.saveDirectory);
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%% ------------------ Interactive Fit Viewer ------------------
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Analyzer.runInteractiveRSDTwoGaussianFitGUI(spectral_analysis_results);
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%% ------------------ 3. Plot fit parameters - amplitude ------------------
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Plotter.plotFitParameterPDF(fitResults, scan_reference_values, 'A2', ...
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'Title', options.titleString, ...
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'XLabel', 'B (G)', ...
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'YLabel', 'Secondary peak amplitude', ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'FigNum', 2, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SecondaryPeakAmplitudePDF.fig', ...
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'SaveDirectory', options.saveDirectory, ...
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'PlotType', 'histogram', ...
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'NumberOfBins', 20, ...
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'NormalizeHistogram', true, ...
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'Colormap', @Colormaps.coolwarm, ...
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'XLim', [min(scan_reference_values), max(scan_reference_values)], ...
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'YLim', [0, 0.01]);
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%% ------------------ 4. Plot fit parameters - position ------------------
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Plotter.plotFitParameterPDF(fitResults, scan_reference_values, 'mu2', ...
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'Title', options.titleString, ...
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'XLabel', 'B (G)', ...
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'YLabel', 'Secondary peak position (k_\rho, \mum^{-1})', ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'FigNum', 3, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SecondaryPeakPositionPDF.fig', ...
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'SaveDirectory', options.saveDirectory, ...
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'PlotType', 'histogram', ...
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'NumberOfBins', 20, ...
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'NormalizeHistogram', true, ...
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'Colormap', @Colormaps.coolwarm, ...
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'XLim', [min(scan_reference_values), max(scan_reference_values)], ...
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'YLim', [0, 3]);
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%% ------------------ 5. Plot fit parameters - width ------------------
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Plotter.plotFitParameterPDF(fitResults, scan_reference_values, 'sigma2', ...
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'Title', options.titleString, ...
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'XLabel', 'B (G)', ...
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'YLabel', 'Secondary peak width (\sigma, rad)', ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'FigNum', 4, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SecondaryPeakWidthPDF.fig', ...
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'SaveDirectory', options.saveDirectory, ...
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'PlotType', 'histogram', ...
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'NumberOfBins', 20, ...
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'NormalizeHistogram', true, ...
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'Colormap', @Colormaps.coolwarm, ...
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'XLim', [min(scan_reference_values), max(scan_reference_values)], ...
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'YLim', [0, 1.5]);
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%% ------------------ 6. Plot secondary Gaussian range ------------------
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Plotter.plotSecondaryGaussianRange(fitResults, scan_reference_values, ...
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'Title', options.titleString, ...
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'XLabel', 'B (G)', ...
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'YLabel', '\mu_2 \pm \sigma_2 (rad)', ...
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'YLim', [0, 5], ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'FigNum', 5, ...
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'NumberOfBins', 20, ...
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'NormalizeHistogram', true, ...
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'Colormap', @Colormaps.coolwarm, ...
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'OverlayMeanSEM', true, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SecondaryGaussianRange.fig', ...
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'SaveDirectory', options.saveDirectory);
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%% ------------------ 7. Plot fit parameters of mean shifted Angular Spectral Distribution Curves ------------------
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avgData = Analyzer.computeSpectralAverages(spectral_analysis_results.S_k_all, scan_reference_values);
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% Extract averaged curves (mean across repetitions)
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curves_mean = avgData.curves_mean; % [N_scanValues × N_k_rho]
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krho_values = spectral_analysis_results.k_rho_vals;
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% ---------- Fit two-Gaussian model to mean curves ----------
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[fitResultsMean, ~] = Analyzer.fitTwoGaussianCurvesToRadialSpectralDistribution(...
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curves_mean, ...
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krho_values, ...
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'KRhoRange', [0, 3], ... % truncate curves to 0 <= k_rho <= 3
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'AmplitudeRange', [0, 0.3], ... % truncate curves to y >= 0 (all amplitudes)
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'ResidualThreshold', 0.175, ... % maximum allowed residual
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'PositionThreshold', 0.5, ... % minimum separation between peaks
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'AmplitudeThreshold', 0.015); % minimum secondary peak fraction
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% ---------- Extract fit parameters ----------
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N_params = numel(fitResultsMean);
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amp2_vals = nan(1, N_params);
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mu2_vals = nan(1, N_params);
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sigma2_vals = nan(1, N_params);
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for i = 1:N_params
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pFit = fitResultsMean(i).pFit;
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if all(~isnan(pFit))
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amp2_vals(i) = pFit(4);
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mu2_vals(i) = pFit(5);
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sigma2_vals(i) = pFit(6);
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end
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end
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% ---------- Plot with SEM ----------
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Plotter.plotMeanWithSE(scan_reference_values, amp2_vals, ...
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'Title', options.titleString, ...
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'XLabel', 'B (G)', ...
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'YLabel', 'Secondary peak amplitude', ...
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'FigNum', 6, ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SecondaryPeakAmplitudeMeanWithSEM.fig', ...
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'SaveDirectory', options.saveDirectory);
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Plotter.plotMeanWithSE(scan_reference_values, mu2_vals, ...
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'Title', options.titleString, ...
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'XLabel', 'B (G)', ...
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'YLabel', 'Secondary peak position (k_\rho, \mum^{-1})', ...
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'FigNum', 7, ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SecondaryPeakPositionMeanWithSEM.fig', ...
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'SaveDirectory', options.saveDirectory);
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Plotter.plotMeanWithSE(scan_reference_values, sigma2_vals, ...
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'Title', options.titleString, ...
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'XLabel', 'B (G)', ...
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'YLabel', 'Secondary peak width (\sigma, rad)', ...
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'FigNum', 8, ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SecondaryPeakWidthMeanWithSEM.fig', ...
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'SaveDirectory', options.saveDirectory);
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%% ------------------ 8. Compare mean of individual fits vs fit of mean ------------------
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paramMap = struct('A1',1,'mu1',2,'sigma1',3,'A2',4,'mu2',5,'sigma2',6);
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paramNames = {'A2', 'mu2', 'sigma2'};
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paramLabels = {'Secondary peak amplitude', 'Secondary peak position (k_\rho, \mum^{-1})', 'Secondary peak width (\sigma, rad)'};
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meanOfIndividualFits = struct();
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fitOfMeanCurve = struct();
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for p = 1:numel(paramNames)
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paramName = paramNames{p};
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paramLabel = paramLabels{p};
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paramIdx = paramMap.(paramName);
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% --- Mean of individual fits per scan_reference_values ---
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meanVals = nan(size(scan_reference_values)); % already unique
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for k = 1:numel(scan_reference_values)
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thisAlpha = scan_reference_values(k);
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mask = scan_parameter_values == thisAlpha; % pick all repetitions
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pvals = arrayfun(@(f) f.pFit(paramIdx), fitResults(mask), 'UniformOutput', true);
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meanVals(k) = mean(pvals(~isnan(pvals) & isfinite(pvals)), 'omitnan');
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end
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meanOfIndividualFits.(paramName) = meanVals;
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% --- Fit of mean curve ---
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switch paramName
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case 'A2'
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fitOfMeanCurve.(paramName) = amp2_vals;
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case 'mu2'
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fitOfMeanCurve.(paramName) = mu2_vals;
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case 'sigma2'
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fitOfMeanCurve.(paramName) = sigma2_vals;
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end
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% --- Plot comparison ---
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fig = figure('Name', 'Comparison', 'NumberTitle', 'off');
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set(fig, 'Color', 'w', 'Position', [100 100 950 750]);
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hold on;
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plot(scan_reference_values, meanOfIndividualFits.(paramName), 'o-', 'LineWidth', 1.8, ...
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'DisplayName', 'Mean of Individual Fits');
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plot(scan_reference_values, fitOfMeanCurve.(paramName), 's--', 'LineWidth', 1.8, ...
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'DisplayName', 'Fit of Mean Curve');
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hold off;
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xlabel('B (G)', 'FontName', options.font, 'FontSize', 16);
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ylabel(paramLabel, 'FontName', options.font, 'FontSize', 16);
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title(options.titleString, 'FontName', options.font, 'FontSize', 16);
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legend('Location', 'northeast');
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grid on;
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set(gca, 'FontSize', 14);
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if ~options.skipSaveFigures
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saveas(fig, fullfile(options.saveDirectory, ['Compare_' paramName '.fig']));
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exportgraphics(fig, fullfile(options.saveDirectory, ['Compare_' paramName '.png']), 'Resolution', 300);
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end
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end
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%% ------------------ 9. Save Fit Results ------------------
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outputDir = fullfile(options.saveDirectory, 'BECToS_RSDFitData');
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if ~exist(outputDir, 'dir')
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mkdir(outputDir);
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end
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% --- Define filenames for each variable ---
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file_scanParamVals = fullfile(outputDir, 'scan_parameter_values');
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file_scanRefVals = fullfile(outputDir, 'scan_reference_values');
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file_fitResults = fullfile(outputDir, 'fitResults.mat');
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file_rawCurves = fullfile(outputDir, 'rawCurves.mat');
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file_spectralResults = fullfile(outputDir, 'spectral_analysis_results.mat');
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file_meanFits = fullfile(outputDir, 'fitOfMeanCurve.mat');
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file_indivFits = fullfile(outputDir, 'meanOfIndividualFits.mat');
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% --- Save each variable separately ---
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save(file_scanParamVals, 'scan_parameter_values', '-v7.3');
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save(file_scanRefVals, 'scan_reference_values', '-v7.3');
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save(file_fitResults, 'fitResults', '-v7.3');
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save(file_rawCurves, 'rawCurves', '-v7.3');
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save(file_spectralResults, 'spectral_analysis_results', '-v7.3');
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save(file_meanFits, 'fitOfMeanCurve', '-v7.3');
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save(file_indivFits, 'meanOfIndividualFits', '-v7.3');
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fprintf('\n--- Fit data saved successfully ---\n');
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fprintf('scanParamVals: %s\n', file_scanParamVals);
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fprintf('scanRefVals: %s\n', file_scanRefVals);
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fprintf('fitResults: %s\n', file_fitResults);
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fprintf('rawCurves: %s\n', file_rawCurves);
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fprintf('spectral_analysis_results:%s\n', file_spectralResults);
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fprintf('fitOfMeanCurve: %s\n', file_meanFits);
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fprintf('meanOfIndividualFits: %s\n', file_indivFits);
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fprintf('----------------------------------\n\n');
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%{
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%% ------------------ Single Gaussian Fit to truncated Radial Spectral Distribution Curves ------------------
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[fitResults, rawCurves] = Analyzer.fitSingleGaussianCurvesToRadialSpectralDistribution(...
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spectral_analysis_results.S_k_all, ... % radial spectral curves
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spectral_analysis_results.k_rho_vals, ... % corresponding k_rho values
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'KRhoRange', [0.5, 3], ... % truncate curves to 0 <= k_rho <= 3
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'ResidualThreshold', 0.15); % maximum allowed residual
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Plotter.plotSingleGaussianFitParameterPDF(fitResults, scan_reference_values, 'A', ...
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'Title', options.titleString, ...
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'XLabel', 'B (G)', ...
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'YLabel', 'Peak amplitude', ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'FigNum', 2, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'PeakAmplitudePDF.fig', ...
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'SaveDirectory', options.saveDirectory, ...
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'PlotType', 'histogram', ...
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'NumberOfBins', 20, ...
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'NormalizeHistogram', true, ...
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'Colormap', @Colormaps.coolwarm, ...
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'XLim', [min(scan_reference_values), max(scan_reference_values)], ...
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'YLim', [0, 0.01]);
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Plotter.plotSingleGaussianFitParameterPDF(fitResults, scan_reference_values, 'mu', ...
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'Title', options.titleString, ...
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'XLabel', 'B (G)', ...
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'YLabel', 'Peak position', ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'FigNum', 3, ... % changed figure number to avoid overlap
|
||
'SkipSaveFigures', options.skipSaveFigures, ...
|
||
'SaveFileName', 'PeakPositionPDF.fig', ...
|
||
'SaveDirectory', options.saveDirectory, ...
|
||
'PlotType', 'histogram', ...
|
||
'NumberOfBins', 20, ...
|
||
'NormalizeHistogram', true, ...
|
||
'Colormap', @Colormaps.coolwarm, ...
|
||
'XLim', [min(scan_reference_values), max(scan_reference_values)], ...
|
||
'YLim', [0, 3]);
|
||
|
||
%} |