191 lines
7.7 KiB
Matlab
191 lines
7.7 KiB
Matlab
%% ===== Stripes-Droplets: Compare Mean and Variance Across Data Sources =====
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% Author: Karthik
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% Date: 2025-10-29
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% Version: 1.2
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%
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% Description:
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% Loops through multiple data sources, performs angular spectral analysis,
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% extracts the first two cumulants (Mean, Variance), and plots them
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% together in a 1×2 tiled layout
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% Each curve can be labeled manually.
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%
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% Saves both figure (.fig) and data (.mat) for replotting later.
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clear; clc; close all;
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%% ===== Define Data Sources and Labels =====
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dataSourcesList = {
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struct('sequence', 'StructuralPhaseTransition', 'date', '2025/10/13', 'runs', [11]), ...
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struct('sequence', 'StructuralPhaseTransition', 'date', '2025/10/13', 'runs', [12]), ...
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struct('sequence', 'StructuralPhaseTransition', 'date', '2025/10/14', 'runs', [0]), ...
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struct('sequence', 'StructuralPhaseTransition', 'date', '2025/10/14', 'runs', [1]), ...
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struct('sequence', 'StructuralPhaseTransition', 'date', '2025/10/14', 'runs', [2]), ...
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struct('sequence', 'StructuralPhaseTransition', 'date', '2025/10/14', 'runs', [3]), ...
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struct('sequence', 'StructuralPhaseTransition', 'date', '2025/10/14', 'runs', [4])
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};
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curveLabels = {'B = 2.55 G', 'B = 2.50 G', 'B = 2.45 G', ...
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'B = 2.40 G', 'B = 2.35 G', 'B = 2.30 G', ...
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'B = 2.20 G'};
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%% ===== Analysis Options =====
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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 = 'StripesToDroplets';
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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 = 1.0500; % μm⁻¹
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options.k_max = 2.7000; % μm⁻¹
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options.N_angular_bins = 360;
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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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% Processing 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 = false;
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options.showProgressBar = true;
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options.font = 'Bahnschrift';
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% ===== Initialize container =====
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cumulantData = struct(); % will be indexed as cumulantData(thetaIdx, dataSourceIdx)
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% ===== Specify theta values to analyze =====
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desiredTheta = [pi/6, pi/3]; % you can add more angles here
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%% ===== Loop over data sources =====
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for d = 1:numel(dataSourcesList)
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dataSources = {dataSourcesList{d}};
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[options.selectedPath, options.folderPath] = Helper.selectDataSourcePath(dataSources, options);
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% --- Read all images for this data source once ---
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[od_imgs, scan_parameter_values, scan_reference_values, file_list] = ...
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Helper.collectODImages(options);
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spectral_analysis_results = Analyzer.extractFullAngularSpectralDistribution(od_imgs, options);
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results = Analyzer.recenterSpectralCurves( ...
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spectral_analysis_results.S_theta_norm_all, ...
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spectral_analysis_results.theta_vals/pi, ...
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scan_reference_values, ...
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'SearchRange', [0 90]);
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mask = results.x_values >= 0 & results.x_values <= 1;
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results.x_values = results.x_values(mask);
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for i = 1:numel(results.curves)
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results.curves{i} = results.curves{i}(:, mask);
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end
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% --- Loop over theta values for this data source ---
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for t = 1:numel(desiredTheta)
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th = desiredTheta(t);
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thetaVals = results.x_values * pi;
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[~, thIdx] = min(abs(thetaVals - th));
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N_params = numel(results.curves);
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meanVals = zeros(1, N_params);
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varVals = zeros(1, N_params);
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for i = 1:N_params
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reps_values = results.curves{i}(:, thIdx);
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kappa = Calculator.computeCumulants(reps_values, 2);
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meanVals(i) = kappa(1);
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varVals(i) = kappa(2);
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end
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% --- Store cumulants ---
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cumulantData(t,d).theta = th;
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cumulantData(t,d).label = curveLabels{d};
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cumulantData(t,d).mean = meanVals;
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cumulantData(t,d).variance = varVals;
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cumulantData(t,d).scan_vals = scan_reference_values;
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end
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end
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%% ===== Plot Mean and Variance per theta =====
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N_theta = size(cumulantData,1); % number of theta values
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N_data = size(cumulantData,2); % number of data sources
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% --- Colormap (trimmed coolwarm) ---
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fullCmap = Colormaps.coolwarm(256);
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blueSide = fullCmap(1:100,:);
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redSide = fullCmap(157:end,:);
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trimmedCmap = [blueSide; redSide];
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cmap = trimmedCmap(round(linspace(1,size(trimmedCmap,1),N_data)), :);
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for t = 1:N_theta
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fig = figure('Color','w','Position',[100 100 1200 550]);
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tName = sprintf('\\theta = %.0f°', round(rad2deg(cumulantData(t,1).theta)));
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sgtitle(['Cumulants at ', tName], 'FontName', options.font, 'FontSize', 18);
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tLayout = tiledlayout(1,2,'TileSpacing','Compact','Padding','Compact');
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% --- Mean (κ₁) ---
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ax1 = nexttile; hold(ax1,'on');
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for d = 1:N_data
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plot(ax1, cumulantData(t,d).scan_vals, cumulantData(t,d).mean, '-o', ...
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'Color', cmap(d,:), 'LineWidth', 2, 'MarkerSize', 8, ...
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'MarkerFaceColor', cmap(d,:), 'DisplayName', cumulantData(t,d).label);
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end
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xlabel(ax1, '\alpha (degrees)', 'FontName', options.font, 'FontSize', 14);
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ylabel(ax1, '\kappa_1', 'FontName', options.font, 'FontSize', 14);
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title(ax1, 'Mean', 'FontName', options.font, 'FontSize', 16);
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grid(ax1,'on'); legend(ax1,'Location','northwest','FontSize',12);
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set(ax1,'FontName',options.font,'FontSize',14);
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% --- Variance (κ₂) ---
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ax2 = nexttile; hold(ax2,'on');
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for d = 1:N_data
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plot(ax2, cumulantData(t,d).scan_vals, cumulantData(t,d).variance, '-o', ...
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'Color', cmap(d,:), 'LineWidth', 2, 'MarkerSize', 8, ...
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'MarkerFaceColor', cmap(d,:), 'DisplayName', cumulantData(t,d).label);
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end
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xlabel(ax2, '\alpha (degrees)', 'FontName', options.font, 'FontSize', 14);
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ylabel(ax2, '\kappa_2', 'FontName', options.font, 'FontSize', 14);
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title(ax2, 'Variance', 'FontName', options.font, 'FontSize', 16);
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grid(ax2,'on'); legend(ax2,'Location','northwest','FontSize',12);
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set(ax2,'FontName',options.font,'FontSize',14);
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% --- Save figure ---
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saveFileNameFig = fullfile(options.saveDirectory, ...
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sprintf('StripesToDroplets_MeanVariance_theta_%d.fig', round(rad2deg(cumulantData(t,1).theta))));
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savefig(fig, saveFileNameFig);
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end
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% --- Save all cumulant data ---
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saveFileNameMat = fullfile(options.saveDirectory, 'StripesToDroplets_MeanVariance_AllThetaData.mat');
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save(saveFileNameMat, 'cumulantData', 'options');
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