Bugfixes and modifications of plotting routines.

Data-Analyzer/+Plotter/compareMultipleDatasets.m

@@ -72,7 +72,7 @@ function compareMultipleDatasets(scanValsCell, meanValsCell, stderrValsCell, var
 
     xlabel(opts.XLabel, 'Interpreter', 'latex', 'FontSize', axisFontSize);
     ylabel(opts.YLabel, 'Interpreter', 'latex', 'FontSize', axisFontSize);
-    title(opts.Title, 'Interpreter', 'latex', 'FontSize', titleFontSize);
+    title(opts.Title, 'FontName', opts.FontName, 'FontSize', titleFontSize);
     legend('Location', 'best'); 
     grid on;
 

Data-Analyzer/+Plotter/plotMeanWithSE.m

@@ -20,6 +20,7 @@ function plotMeanWithSE(scan_values, data_values, varargin)
     addParameter(p, 'SkipSaveFigures', false, @islogical);
     addParameter(p, 'SaveFileName', 'mean_with_se.fig', @ischar);
     addParameter(p, 'SaveDirectory', pwd, @ischar);
+    addParameter(p, 'HoldOn', false, @islogical);
     parse(p, varargin{:});
     opts = p.Results;
 
@@ -48,13 +49,19 @@ function plotMeanWithSE(scan_values, data_values, varargin)
     else
         fig = figure(opts.FigNum);
     end
-    clf(fig);
+    if ~opts.HoldOn
+        clf(fig);
+    end
     set(fig, 'Color', 'w', 'Position', [100 100 950 750]);
 
     % --- Plot error bars ---
     errorbar(unique_vals, mean_vals, stderr_vals, 'o--', ...
         'LineWidth', 1.8, 'MarkerSize', 6, 'CapSize', 5);
 
+    if opts.HoldOn
+        hold on;
+    end
+
     % --- Axis formatting ---
     set(gca, 'FontName', opts.FontName, 'FontSize', opts.FontSize);
     if ~isempty(opts.YLim)

Data-Analyzer/+Scripts/BECToDroplets/plotAnalysisResults.m

@@ -1,33 +1,43 @@
-% --- User chooses which dataset to load ---
+%% --- User chooses which dataset to load ---
-datasetIdx              = 1;   % <-- change this to 1, 2, 3, ...
+datasetIdx                = 1;   % <-- change this to 1, 2, 3, ...
-datasetName             = sprintf('Dataset_%d', datasetIdx);
+datasetName               = sprintf('Dataset_%d', datasetIdx);
 
-% Detect the folder where this script is located and set that as the Base Directory
+% --- Base directory selection ---
-thisScriptPath          = mfilename('fullpath');
+useLocalBaseDir           = false;  % <-- set true to use script location, false to use manual path
-[thisScriptDir, ~, ~]   = fileparts(thisScriptPath);
-baseDir                 = thisScriptDir;           % override if needed
 
-% Build path to dataset file
+if useLocalBaseDir
-dataFile                = fullfile(baseDir, "Results", "SavedData", datasetName + ".mat");
+    % Use folder where this script is located
-data                    = load(dataFile);
+    thisScriptPath        = mfilename('fullpath');
+    [thisScriptDir, ~, ~] = fileparts(thisScriptPath);
+    baseDir               = fullfile(thisScriptDir, 'Results');
+else
+    % Use manually specified folder
+    baseDir               = 'E:\Results - Experiment\202507\BECToDroplets\';
+end
 
-% Access dataset struct dynamically
+% --- Build paths ---
-datasetStruct           = data.(datasetName);
+dataFile                  = fullfile(baseDir, 'SavedData', [datasetName '.mat']);
-compiled_results        = datasetStruct.results;
+figSaveDir                = fullfile(baseDir, 'SavedFigures', datasetName);
-scan_parameter_values   = datasetStruct.scan_parameter_values;
-scan_reference_values   = datasetStruct.scan_reference_values;
 
-% Load the original options used during analysis
+% --- Load dataset ---
-options                 = datasetStruct.options;   % exact options used for this dataset
+data                      = load(dataFile);
-options.font            = 'Bahnschrift';           % override if needed
-options.skipSaveFigures = false;                   % override if needed
 
-%% ------------------ Create dataset-specific figure folder ------------------
+% --- Ensure figure folder exists ---
-figSaveDir = fullfile(baseDir,'Results', 'SavedFigures', datasetName);
 if ~exist(figSaveDir, 'dir')
     mkdir(figSaveDir);
 end
 
+% --- Access dataset struct dynamically ---
+datasetStruct             = data.(datasetName);
+compiled_results          = datasetStruct.results;
+scan_parameter_values     = datasetStruct.scan_parameter_values;
+scan_reference_values     = datasetStruct.scan_reference_values;
+
+% --- Load options used during analysis ---
+options                   = datasetStruct.options;
+options.font              = 'Bahnschrift';   % override if needed
+options.skipSaveFigures   = false;           % override if needed
+
 %% ------------------ 1. Mean ± Std Plots ------------------
 % Plot Radial Spectral Contrast
 Plotter.plotMeanWithSE(scan_parameter_values, compiled_results.spectral_analysis_results.radial_spectral_contrast, ...
@@ -63,7 +73,76 @@ Plotter.plotMeanWithSE(scan_parameter_values, compiled_results.custom_g_results.
     'SaveDirectory', figSaveDir, ...
     'SkipSaveFigures', options.skipSaveFigures);
 
-%% ------------------ 2. g²(θ) across transition ------------------
+%% ------------------ 2. PDF of Radial Spectral Contrast across transition ------------------
+
+% Ensure row vectors
+contrast  = compiled_results.spectral_analysis_results.radial_spectral_contrast(:)';
+params    = scan_parameter_values(:)';
+reference = scan_reference_values(:)';
+
+% Preallocate a cell array to hold grouped results
+grouped_contrast = cell(size(reference));  % 1x21
+
+% Loop over each unique reference value
+for i = 1:length(reference)
+    ref_val = reference(i);
+    
+    % Find indices where the scan param matches this reference
+    idx = params == ref_val;
+    
+    % Store corresponding contrast values
+    grouped_contrast{i} = contrast(idx);
+end
+
+Plotter.plotPDF(grouped_contrast, ...
+    scan_reference_values, ...
+    'Title', options.titleString, ...
+    'XLabel', 'B (G)', ...
+    'YLabel', 'Radial Spectral Contrast', ...
+    'FigNum', 4, ...
+    'FontName', options.font, ...
+    'SkipSaveFigures', options.skipSaveFigures, ...
+    'SaveFileName', 'PDF_MaxG2AcrossTransition.fig', ...
+    'SaveDirectory', figSaveDir, ...
+    'NumberOfBins', 20, ... 
+    'NormalizeHistogram', true, ... 
+    'DataRange', [0 0.1], ...
+    'Colormap', @Colormaps.coolwarm, ...
+    'XLim', [min(scan_reference_values) max(scan_reference_values)]);
+
+%% ------------------ 3. Cumulants across transition ------------------
+
+maxOrder        = 4;  % Set the order of cumulants you want
+numGroups       = length(grouped_contrast);
+
+% Preallocate matrix to store cumulants
+% Each row corresponds to a group (i.e., a scan_reference_value)
+% Each column corresponds to a cumulant order (1 to maxOrder)
+cumulant_matrix = NaN(numGroups, maxOrder);
+
+for i = 1:numGroups
+    data_i = grouped_contrast{i};
+    cumulant_matrix(i, :) = Calculator.computeCumulants(data_i, maxOrder);
+end
+
+mean_rsc   = cumulant_matrix(:, 1);
+var_rsc    = cumulant_matrix(:, 2);
+skew_rsc   = cumulant_matrix(:, 3);
+binder_rsc = cumulant_matrix(:, 4);
+
+Plotter.plotCumulants(scan_reference_values, ...
+    {mean_rsc, var_rsc, skew_rsc, binder_rsc}, ...
+    'Title', 'Cumulants of Radial Spectral Contrast', ...
+    'XLabel', 'B (G)', ...
+    'FigNum', 5, ...
+    'FontName', options.font, ...
+    'MarkerSize', 6, ...
+    'LineWidth', 1.5, ...
+    'SkipSaveFigures', options.skipSaveFigures, ...
+    'SaveFileName', 'CumulantOfPeakOffsetAngularCorrelation.fig', ...
+    'SaveDirectory', figSaveDir);
+
+%% ------------------ 4. g²(θ) across transition ------------------
 Plotter.plotG2(compiled_results.full_g2_results.g2_mean, ...
     compiled_results.full_g2_results.g2_error, ...
     compiled_results.full_g2_results.theta_values, ...
@@ -72,13 +151,14 @@ Plotter.plotG2(compiled_results.full_g2_results.g2_mean, ...
     'Title', options.titleString, ...
     'XLabel', '$\delta\theta / \pi$', ...
     'YLabel', '$g^{(2)}(\delta\theta)$', ...
-    'FigNum', 4, ...
+    'FigNum', 6, ...
     'FontName', options.font, ...
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveFileName', 'G2ThetaAcrossTransition.fig', ...
     'SaveDirectory', figSaveDir, ...
     'Colormap', @Colormaps.coolwarm);
-%% ------------------ 3. Feature extraction of g²(θ) across transition ------------------
+
+%% ------------------ 5. Feature extraction of g²(θ) across transition ------------------
 
 Plotter.plotG2Curves(compiled_results.full_g2_results, ...
     'Title', options.titleString, ...
@@ -86,7 +166,7 @@ Plotter.plotG2Curves(compiled_results.full_g2_results, ...
     'YLabel', 'g^{(2)}(\theta)', ...
     'HighlightEvery', 10, ...              % highlight every 10th repetition
     'FontName', options.font, ...
-    'FigNum', 5, ...
+    'FigNum', 7, ...
     'TileTitlePrefix', 'B', ...       % user-defined tile prefix
     'TileTitleSuffix', 'G', ...       % user-defined suffix (e.g., Gauss symbol)...
     'SkipSaveFigures', options.skipSaveFigures, ...
@@ -101,7 +181,7 @@ Plotter.plotG2Features(g2_analysis_results, ...
     'Title', options.titleString, ...
     'XLabel', 'B (G)', ...
     'FontName', options.font, ...
-    'FigNum', 6, ...
+    'FigNum', 8, ...
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveFileName', 'G2Features.fig', ...
     'SaveDirectory', figSaveDir);
@@ -111,18 +191,18 @@ Plotter.plotG2Cumulants(g2_analysis_results, ...
     'Title', options.titleString, ...
     'XLabel', 'B (G)', ...
     'FontName', options.font, ...
-    'FigNum', 7, ...
+    'FigNum', 9, ...
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveFileName', 'G2Cumulants.fig', ...
     'SaveDirectory', figSaveDir);
 
-%% ------------------ 4. PDF of max g² across transition ------------------
+%% ------------------ 6. PDF of max g² across transition ------------------
 Plotter.plotPDF(compiled_results.custom_g_results.max_g2_all_per_scan_parameter_value, ...
     scan_reference_values, ...
     'Title', options.titleString, ...
     'XLabel', 'B (G)', ...
     'YLabel', '$\mathrm{max}[g^{(2)}]$', ...
-    'FigNum', 8, ...
+    'FigNum', 10, ...
     'FontName', options.font, ...
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveFileName', 'PDF_MaxG2AcrossTransition.fig', ...
@@ -134,12 +214,12 @@ Plotter.plotPDF(compiled_results.custom_g_results.max_g2_all_per_scan_parameter_
     'XLim', [min(scan_reference_values) max(scan_reference_values)]);
 
 
-%% ------------------ 5. Cumulants across transition ------------------
+%% ------------------ 7. Cumulants across transition ------------------
 Plotter.plotCumulants(scan_reference_values, ...
     {compiled_results.custom_g_results.mean_max_g2, compiled_results.custom_g_results.var_max_g2, compiled_results.custom_g_results.skew_max_g2_angle, compiled_results.custom_g_results.fourth_order_cumulant_max_g2}, ...
     'Title', 'Cumulants of Peak Offset Angular Correlation', ...
     'XLabel', 'B (G)', ...
-    'FigNum', 9, ...
+    'FigNum', 11, ...
     'FontName', options.font, ...
     'MarkerSize', 6, ...
     'LineWidth', 1.5, ...
@@ -147,15 +227,13 @@ Plotter.plotCumulants(scan_reference_values, ...
     'SaveFileName', 'CumulantOfPeakOffsetAngularCorrelation.fig', ...
     'SaveDirectory', figSaveDir);
 
-%% ------------------ 6. PCA ------------------
+%% ------------------ 8. PCA ------------------
 Plotter.plotPCAResults(compiled_results.pca_results, scan_parameter_values, scan_reference_values, ...
-    'FigNumRange', [10,11,12,13,14,15], ...
+    'FigNumRange', [12,13,14,15,16,17], ...
     'FontName', options.font, ...
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveDirectory', figSaveDir);
 
-
-
 %%
 %{
 

Data-Analyzer/+Scripts/BECToDroplets/runFullAnalysis.m

@@ -3,15 +3,15 @@
 % Specify data location to run analysis on
 dataSources = {
     struct('sequence', 'StructuralPhaseTransition', ...
-           'date', '2025/08/13', ...
+           'date', '2025/07/25', ...
-           'runs', [62]) % specify run numbers as a string in "" or just as a numeric value
+           'runs', [25]) % specify run numbers as a string in "" or just as a numeric value
 };
 
 options = struct();
 
 % File paths
 options.baseDataFolder     = '//DyLabNAS/Data';
-options.FullODImagesFolder = 'E:/Data - Experiment/FullODImages/202508';
+options.FullODImagesFolder = 'E:/Data - Experiment/FullODImages/202507';
 options.measurementName    = 'BECToDroplets';
 scriptFullPath             = mfilename('fullpath');
 options.saveDirectory      = fileparts(scriptFullPath);
@@ -23,7 +23,7 @@ options.center             = [1420, 2050];
 options.span               = [200, 200];
 options.fraction           = [0.1, 0.1];
 options.pixel_size         = 5.86e-6;       % in meters
-options.magnification      = 24.6;
+options.magnification      = 23.94;
 options.ImagingMode        = 'HighIntensity';
 options.PulseDuration      = 5e-6;          % in s
 

Data-Analyzer/+Scripts/BECToDropletsToStripes/plotAnalysisResults.m

@@ -1,26 +1,42 @@
-% --- User chooses which dataset to load ---
+%% --- User chooses which dataset to load ---
-datasetIdx              = 4;   % <-- change this to 1, 2, 3, ...
+datasetIdx                = 6;   % <-- change this to 1, 2, 3, ...
-datasetName             = sprintf('Dataset_%d', datasetIdx);
+datasetName               = sprintf('Dataset_%d', datasetIdx);
 
-% Detect the folder where this script is located and set that as the Base Directory
+% --- Base directory selection ---
-thisScriptPath          = mfilename('fullpath');
+useLocalBaseDir           = false;  % <-- set true to use script location, false to use manual path
-[thisScriptDir, ~, ~]   = fileparts(thisScriptPath);
-baseDir                 = thisScriptDir;           % override if needed
 
-% Build path to dataset file
+if useLocalBaseDir
-dataFile                = fullfile(baseDir, "Results", "SavedData", datasetName + ".mat");
+    % Use folder where this script is located
-data                    = load(dataFile);
+    thisScriptPath        = mfilename('fullpath');
+    [thisScriptDir, ~, ~] = fileparts(thisScriptPath);
+    baseDir               = fullfile(thisScriptDir, 'Results');
+else
+    % Use manually specified folder
+    baseDir               = 'E:\Results - Experiment\202508\BECToDropletsToStripes\';
+end
 
-% Access dataset struct dynamically
+% --- Build paths ---
-datasetStruct           = data.(datasetName);
+dataFile                  = fullfile(baseDir, 'SavedData', [datasetName '.mat']);
-compiled_results        = datasetStruct.results;
+figSaveDir                = fullfile(baseDir, 'SavedFigures', datasetName);
-scan_parameter_values   = datasetStruct.scan_parameter_values;
-scan_reference_values   = datasetStruct.scan_reference_values;
 
-% Load the original options used during analysis
+% --- Load dataset ---
-options                 = datasetStruct.options;   % exact options used for this dataset
+data                      = load(dataFile);
-options.font            = 'Bahnschrift';           % override if needed
+
-options.skipSaveFigures = false;                   % override if needed
+% --- Ensure figure folder exists ---
+if ~exist(figSaveDir, 'dir')
+    mkdir(figSaveDir);
+end
+
+% --- Access dataset struct dynamically ---
+datasetStruct             = data.(datasetName);
+compiled_results          = datasetStruct.results;
+scan_parameter_values     = datasetStruct.scan_parameter_values;
+scan_reference_values     = datasetStruct.scan_reference_values;
+
+% --- Load options used during analysis ---
+options                   = datasetStruct.options;
+options.font              = 'Bahnschrift';   % override if needed
+options.skipSaveFigures   = false;           % override if needed
 
 %% ------------------ Create dataset-specific figure folder ------------------
 figSaveDir = fullfile(baseDir,'Results', 'SavedFigures', datasetName);
@@ -147,6 +163,8 @@ Plotter.plotCumulants(scan_reference_values, ...
     'SaveFileName', 'CumulantOfPeakOffsetAngularCorrelation.fig', ...
     'SaveDirectory', figSaveDir);
 
+%{
+
 %% ------------------ 6. PCA ------------------
 Plotter.plotPCAResults(compiled_results.pca_results, scan_parameter_values, scan_reference_values, ...
     'FigNumRange', [10,11,12,13,14,15], ...
@@ -154,12 +172,7 @@ Plotter.plotPCAResults(compiled_results.pca_results, scan_parameter_values, scan
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveDirectory', figSaveDir);
 
-
+%% ------------------ 7. Average of Spectra Plots ------------------
-
-%%
-%{
-
-%% ------------------ 6. Average of Spectra Plots ------------------
 
 Plotter.plotAverageSpectra(scan_parameter_values, ...
      spectral_analysis_results, ...
@@ -171,7 +184,7 @@ Plotter.plotAverageSpectra(scan_parameter_values, ...
      'SaveDirectory', figSaveDir, ...
      'SkipSaveFigures', options.skipSaveFigures);
 
-%% ------------------ 7. Compare quantities ------------------
+%% ------------------ 8. Compare quantities ------------------
 % Load Droplets → Stripes data
 Data = load(dtsFile, ...
     'unique_scan_parameter_values', ...
@@ -211,7 +224,7 @@ compareMultipleDatasets(scanValsCell, meanValsCell, stderrValsCell, ...
     'SaveDirectory', figSaveDir, ...
     'SaveFileName', 'AngularCorrelation_Comparison.fig');
 
-%% ------------------ 8. Heatmaps ------------------
+%% ------------------ 9. Heatmaps ------------------
 
 BFields = [2.35, 2.15, 2.0, 1.85, 1.7, 1.55, 1.4, 1.35];
 

Data-Analyzer/+Scripts/BECToDropletsToStripes/plotComparisonOfAnalysisResults.m

@@ -0,0 +1,147 @@
+%% ------------------ 1. Compare radial spectral contrast across datasets ------------------
+datasetIdxList = 1:6;
+
+% --- Base directory selection ---
+useLocalBaseDir = false;  % <-- set true to use script location, false to use manual path
+
+if useLocalBaseDir
+    % Use folder where this script is located
+    thisScriptPath        = mfilename('fullpath');
+    [thisScriptDir, ~, ~] = fileparts(thisScriptPath);
+    baseDir               = fullfile(thisScriptDir, 'Results');
+else
+    % Use manually specified folder
+    baseDir               = 'E:\Results - Experiment\202508\BECToDropletsToStripes\';
+end
+
+% Prepare storage
+scanValsCell   = cell(1, numel(datasetIdxList));
+meanValsCell   = cell(1, numel(datasetIdxList));
+stderrValsCell = cell(1, numel(datasetIdxList));
+labelsCell     = {'2.25 G', '2.20 G', '2.15 G', '2.10 G', '2.05 G', '2.00 G'};
+
+% --- Load options from first dataset to set plotting defaults ---
+datasetIdx  = datasetIdxList(1);
+datasetName = sprintf('Dataset_%d', datasetIdx);
+dataFile    = fullfile(baseDir, 'SavedData', [datasetName '.mat']);
+data        = load(dataFile);
+datasetStruct = data.(datasetName);
+options = datasetStruct.options;
+options.font            = 'Bahnschrift';
+options.skipSaveFigures = false;
+
+% --- Ensure combined figure folder exists ---
+combinedSaveDir = fullfile(baseDir, 'SavedFigures', 'Combined');
+if ~exist(combinedSaveDir, 'dir')
+    mkdir(combinedSaveDir);
+end
+
+% --- Loop over datasets to extract mean ± SE ---
+for i = 1:numel(datasetIdxList)
+    datasetIdx  = datasetIdxList(i);
+    datasetName = sprintf('Dataset_%d', datasetIdx);
+
+    % Build paths for this dataset
+    dataFile   = fullfile(baseDir, 'SavedData', [datasetName '.mat']);
+    
+    % Load dataset
+    data          = load(dataFile);
+    datasetStruct = data.(datasetName);
+
+    % Extract values
+    scanVals = datasetStruct.scan_parameter_values;
+    dataVals = datasetStruct.results.spectral_analysis_results.radial_spectral_contrast;
+
+    % --- Compute mean and standard error ---
+    [unique_vals, ~, idx] = unique(scanVals);
+    mean_vals   = zeros(size(unique_vals));
+    stderr_vals = zeros(size(unique_vals));
+    for k = 1:length(unique_vals)
+        if iscell(dataVals)
+            group = dataVals{idx == k};
+        else
+            group = dataVals(idx == k);
+        end
+        if iscell(group)
+            groupVals = [group{:}];
+        else
+            groupVals = group;
+        end
+        mean_vals(k)   = mean(groupVals);
+        stderr_vals(k) = std(groupVals) / sqrt(length(groupVals));
+    end
+
+    % Store results
+    scanValsCell{i}   = unique_vals;
+    meanValsCell{i}   = mean_vals;
+    stderrValsCell{i} = stderr_vals;
+end
+
+% --- Call compare function ---
+Plotter.compareMultipleDatasets(scanValsCell, meanValsCell, stderrValsCell, ...
+    'FigNum', 16, ...
+    'FontName', options.font, ...
+    'Labels', labelsCell, ...
+    'Title', 'Radial Spectral Contrast Across Datasets', ...
+    'XLabel', 'B (G)', ...
+    'YLabel', 'Radial Spectral Contrast', ...
+    'SaveDirectory', combinedSaveDir, ...
+    'SaveFileName', 'RadialSpectralContrast_Combined.fig', ...
+    'SkipSaveFigures', false);
+
+%% ------------------ 2. Compare max g2 across datasets ------------------
+
+% Prepare storage
+maxG2ValsCell   = cell(1, numel(datasetIdxList));
+maxG2MeanCell   = cell(1, numel(datasetIdxList));
+maxG2StderrCell = cell(1, numel(datasetIdxList));
+
+for i = 1:numel(datasetIdxList)
+    datasetIdx  = datasetIdxList(i);
+    datasetName = sprintf('Dataset_%d', datasetIdx);
+
+    % Load dataset
+    dataFile      = fullfile(baseDir, 'SavedData', [datasetName '.mat']);
+    data          = load(dataFile);
+    datasetStruct = data.(datasetName);
+
+    % Extract values
+    scanVals = datasetStruct.scan_parameter_values;
+    dataVals = datasetStruct.results.custom_g_results.max_g2_all_per_scan_parameter_value;
+
+    % --- Compute mean and standard error ---
+    [unique_vals, ~, idx] = unique(scanVals);
+    mean_vals   = zeros(size(unique_vals));
+    stderr_vals = zeros(size(unique_vals));
+    for k = 1:length(unique_vals)
+        if iscell(dataVals)
+            group = dataVals{idx == k};
+        else
+            group = dataVals(idx == k);
+        end
+        if iscell(group)
+            groupVals = [group{:}];
+        else
+            groupVals = group;
+        end
+        mean_vals(k)   = mean(groupVals);
+        stderr_vals(k) = std(groupVals) / sqrt(length(groupVals));
+    end
+
+    % Store results
+    maxG2ValsCell{i}   = unique_vals;
+    maxG2MeanCell{i}   = mean_vals;
+    maxG2StderrCell{i} = stderr_vals;
+end
+
+% --- Call compare function ---
+Plotter.compareMultipleDatasets(maxG2ValsCell, maxG2MeanCell, maxG2StderrCell, ...
+    'FigNum', 17, ...
+    'FontName', options.font, ...
+    'Labels', labelsCell, ...
+    'Title', 'Peak Offset Angular Correlation Across Datasets', ...
+    'XLabel', 'B (G)', ...
+    'YLabel', '$\mathrm{max}[g^{(2)}_{[50,70]}(\delta\theta)]$', ...
+    'SaveDirectory', combinedSaveDir, ...
+    'SaveFileName', 'MaxG2_Combined.fig', ...
+    'SkipSaveFigures', false);

Data-Analyzer/+Scripts/BECToStripes/plotAnalysisResults.m

@@ -1,33 +1,44 @@
-% --- User chooses which dataset to load ---
+%% --- User chooses which dataset to load ---
-datasetIdx              = 1;   % <-- change this to 1, 2, 3, ...
+datasetIdx                = 1;   % <-- change this to 1, 2, 3, ...
-datasetName             = sprintf('Dataset_%d', datasetIdx);
+datasetName               = sprintf('Dataset_%d', datasetIdx);
 
-% Detect the folder where this script is located and set that as the Base Directory
+% --- Base directory selection ---
-thisScriptPath          = mfilename('fullpath');
+useLocalBaseDir           = false;  % <-- set true to use script location, false to use manual path
-[thisScriptDir, ~, ~]   = fileparts(thisScriptPath);
-baseDir                 = thisScriptDir;           % override if needed
 
-% Build path to dataset file
+if useLocalBaseDir
-dataFile                = fullfile(baseDir, "Results", "SavedData", datasetName + ".mat");
+    % Use folder where this script is located
-data                    = load(dataFile);
+    thisScriptPath        = mfilename('fullpath');
+    [thisScriptDir, ~, ~] = fileparts(thisScriptPath);
+    baseDir               = fullfile(thisScriptDir, 'Results');
+else
+    % Use manually specified folder
+    baseDir               = 'E:\Results - Experiment\202507\BECToStripes\';
+end
 
-% Access dataset struct dynamically
+% --- Build paths ---
-datasetStruct           = data.(datasetName);
+dataFile                  = fullfile(baseDir, 'SavedData', [datasetName '.mat']);
-compiled_results        = datasetStruct.results;
+figSaveDir                = fullfile(baseDir, 'SavedFigures', datasetName);
-scan_parameter_values   = datasetStruct.scan_parameter_values;
-scan_reference_values   = datasetStruct.scan_reference_values;
 
-% Load the original options used during analysis
+% --- Load dataset ---
-options                 = datasetStruct.options;   % exact options used for this dataset
+data                      = load(dataFile);
-options.font            = 'Bahnschrift';           % override if needed
-options.skipSaveFigures = false;                   % override if needed
 
-%% ------------------ Create dataset-specific figure folder ------------------
+% --- Ensure figure folder exists ---
-figSaveDir = fullfile(baseDir,'Results', 'SavedFigures', datasetName);
 if ~exist(figSaveDir, 'dir')
     mkdir(figSaveDir);
 end
 
+% --- Access dataset struct dynamically ---
+datasetStruct             = data.(datasetName);
+compiled_results          = datasetStruct.results;
+scan_parameter_values     = datasetStruct.scan_parameter_values;
+scan_reference_values     = datasetStruct.scan_reference_values;
+
+% --- Load options used during analysis ---
+options                   = datasetStruct.options;
+options.font              = 'Bahnschrift';   % override if needed
+options.skipSaveFigures   = false;           % override if needed
+
+
 %% ------------------ 1. Mean ± Std Plots ------------------
 % Plot Radial Spectral Contrast
 Plotter.plotMeanWithSE(scan_parameter_values, compiled_results.spectral_analysis_results.radial_spectral_contrast, ...
@@ -63,7 +74,76 @@ Plotter.plotMeanWithSE(scan_parameter_values, compiled_results.custom_g_results.
     'SaveDirectory', figSaveDir, ...
     'SkipSaveFigures', options.skipSaveFigures);
 
-%% ------------------ 2. g²(θ) across transition ------------------
+%% ------------------ 2. PDF of Radial Spectral Contrast across transition ------------------
+
+% Ensure row vectors
+contrast  = compiled_results.spectral_analysis_results.radial_spectral_contrast(:)';
+params    = scan_parameter_values(:)';
+reference = scan_reference_values(:)';
+
+% Preallocate a cell array to hold grouped results
+grouped_contrast = cell(size(reference));  % 1x21
+
+% Loop over each unique reference value
+for i = 1:length(reference)
+    ref_val = reference(i);
+    
+    % Find indices where the scan param matches this reference
+    idx = params == ref_val;
+    
+    % Store corresponding contrast values
+    grouped_contrast{i} = contrast(idx);
+end
+
+Plotter.plotPDF(grouped_contrast, ...
+    scan_reference_values, ...
+    'Title', options.titleString, ...
+    'XLabel', 'B (G)', ...
+    'YLabel', 'Radial Spectral Contrast', ...
+    'FigNum', 4, ...
+    'FontName', options.font, ...
+    'SkipSaveFigures', options.skipSaveFigures, ...
+    'SaveFileName', 'PDF_MaxG2AcrossTransition.fig', ...
+    'SaveDirectory', figSaveDir, ...
+    'NumberOfBins', 20, ... 
+    'NormalizeHistogram', true, ... 
+    'DataRange', [0 0.1], ...
+    'Colormap', @Colormaps.coolwarm, ...
+    'XLim', [min(scan_reference_values) max(scan_reference_values)]);
+
+%% ------------------ 3. Cumulants across transition ------------------
+
+maxOrder        = 4;  % Set the order of cumulants you want
+numGroups       = length(grouped_contrast);
+
+% Preallocate matrix to store cumulants
+% Each row corresponds to a group (i.e., a scan_reference_value)
+% Each column corresponds to a cumulant order (1 to maxOrder)
+cumulant_matrix = NaN(numGroups, maxOrder);
+
+for i = 1:numGroups
+    data_i = grouped_contrast{i};
+    cumulant_matrix(i, :) = Calculator.computeCumulants(data_i, maxOrder);
+end
+
+mean_rsc   = cumulant_matrix(:, 1);
+var_rsc    = cumulant_matrix(:, 2);
+skew_rsc   = cumulant_matrix(:, 3);
+binder_rsc = cumulant_matrix(:, 4);
+
+Plotter.plotCumulants(scan_reference_values, ...
+    {mean_rsc, var_rsc, skew_rsc, binder_rsc}, ...
+    'Title', 'Cumulants of Radial Spectral Contrast', ...
+    'XLabel', 'B (G)', ...
+    'FigNum', 5, ...
+    'FontName', options.font, ...
+    'MarkerSize', 6, ...
+    'LineWidth', 1.5, ...
+    'SkipSaveFigures', options.skipSaveFigures, ...
+    'SaveFileName', 'CumulantOfPeakOffsetAngularCorrelation.fig', ...
+    'SaveDirectory', figSaveDir);
+
+%% ------------------ 4. g²(θ) across transition ------------------
 Plotter.plotG2(compiled_results.full_g2_results.g2_mean, ...
     compiled_results.full_g2_results.g2_error, ...
     compiled_results.full_g2_results.theta_values, ...
@@ -72,13 +152,14 @@ Plotter.plotG2(compiled_results.full_g2_results.g2_mean, ...
     'Title', options.titleString, ...
     'XLabel', '$\delta\theta / \pi$', ...
     'YLabel', '$g^{(2)}(\delta\theta)$', ...
-    'FigNum', 4, ...
+    'FigNum', 6, ...
     'FontName', options.font, ...
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveFileName', 'G2ThetaAcrossTransition.fig', ...
     'SaveDirectory', figSaveDir, ...
     'Colormap', @Colormaps.coolwarm);
-%% ------------------ 3. Feature extraction of g²(θ) across transition ------------------
+
+%% ------------------ 5. Feature extraction of g²(θ) across transition ------------------
 
 Plotter.plotG2Curves(compiled_results.full_g2_results, ...
     'Title', options.titleString, ...
@@ -86,7 +167,7 @@ Plotter.plotG2Curves(compiled_results.full_g2_results, ...
     'YLabel', 'g^{(2)}(\theta)', ...
     'HighlightEvery', 10, ...              % highlight every 10th repetition
     'FontName', options.font, ...
-    'FigNum', 5, ...
+    'FigNum', 7, ...
     'TileTitlePrefix', 'B', ...       % user-defined tile prefix
     'TileTitleSuffix', 'G', ...       % user-defined suffix (e.g., Gauss symbol)...
     'SkipSaveFigures', options.skipSaveFigures, ...
@@ -101,7 +182,7 @@ Plotter.plotG2Features(g2_analysis_results, ...
     'Title', options.titleString, ...
     'XLabel', 'B (G)', ...
     'FontName', options.font, ...
-    'FigNum', 6, ...
+    'FigNum', 8, ...
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveFileName', 'G2Features.fig', ...
     'SaveDirectory', figSaveDir);
@@ -111,18 +192,18 @@ Plotter.plotG2Cumulants(g2_analysis_results, ...
     'Title', options.titleString, ...
     'XLabel', 'B (G)', ...
     'FontName', options.font, ...
-    'FigNum', 7, ...
+    'FigNum', 9, ...
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveFileName', 'G2Cumulants.fig', ...
     'SaveDirectory', figSaveDir);
 
-%% ------------------ 4. PDF of max g² across transition ------------------
+%% ------------------ 6. PDF of max g² across transition ------------------
 Plotter.plotPDF(compiled_results.custom_g_results.max_g2_all_per_scan_parameter_value, ...
     scan_reference_values, ...
     'Title', options.titleString, ...
     'XLabel', 'B (G)', ...
     'YLabel', '$\mathrm{max}[g^{(2)}]$', ...
-    'FigNum', 8, ...
+    'FigNum', 10, ...
     'FontName', options.font, ...
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveFileName', 'PDF_MaxG2AcrossTransition.fig', ...
@@ -134,12 +215,12 @@ Plotter.plotPDF(compiled_results.custom_g_results.max_g2_all_per_scan_parameter_
     'XLim', [min(scan_reference_values) max(scan_reference_values)]);
 
 
-%% ------------------ 5. Cumulants across transition ------------------
+%% ------------------ 7. Cumulants across transition ------------------
 Plotter.plotCumulants(scan_reference_values, ...
     {compiled_results.custom_g_results.mean_max_g2, compiled_results.custom_g_results.var_max_g2, compiled_results.custom_g_results.skew_max_g2_angle, compiled_results.custom_g_results.fourth_order_cumulant_max_g2}, ...
     'Title', 'Cumulants of Peak Offset Angular Correlation', ...
     'XLabel', 'B (G)', ...
-    'FigNum', 9, ...
+    'FigNum', 11, ...
     'FontName', options.font, ...
     'MarkerSize', 6, ...
     'LineWidth', 1.5, ...
@@ -147,15 +228,13 @@ Plotter.plotCumulants(scan_reference_values, ...
     'SaveFileName', 'CumulantOfPeakOffsetAngularCorrelation.fig', ...
     'SaveDirectory', figSaveDir);
 
-%% ------------------ 6. PCA ------------------
+%% ------------------ 8. PCA ------------------
 Plotter.plotPCAResults(compiled_results.pca_results, scan_parameter_values, scan_reference_values, ...
-    'FigNumRange', [10,11,12,13,14,15], ...
+    'FigNumRange', [12,13,14,15,16,17], ...
     'FontName', options.font, ...
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveDirectory', figSaveDir);
 
-
-
 %%
 %{
 

Data-Analyzer/+Scripts/BECToStripes/runFullAnalysis.m

@@ -1,17 +1,17 @@
-%% ===== BEC-Droplets Settings =====
+%% ===== BEC-Stripes Settings =====
 
 % Specify data location to run analysis on
 dataSources = {
     struct('sequence', 'StructuralPhaseTransition', ...
-           'date', '2025/08/15', ...
+           'date', '2025/07/26', ...
-           'runs', [3]) % specify run numbers as a string in "" or just as a numeric value
+           'runs', [8]) % specify run numbers as a string in "" or just as a numeric value
 };
 
 options = struct();
 
 % File paths
 options.baseDataFolder     = '//DyLabNAS/Data';
-options.FullODImagesFolder = 'E:/Data - Experiment/FullODImages/202508';
+options.FullODImagesFolder = 'E:/Data - Experiment/FullODImages/202507';
 options.measurementName    = 'BECToStripes';
 scriptFullPath             = mfilename('fullpath');
 options.saveDirectory      = fileparts(scriptFullPath);
@@ -23,7 +23,7 @@ options.center             = [1420, 2050];
 options.span               = [200, 200];
 options.fraction           = [0.1, 0.1];
 options.pixel_size         = 5.86e-6;       % in meters
-options.magnification      = 24.6;
+options.magnification      = 23.94;
 options.ImagingMode        = 'HighIntensity';
 options.PulseDuration      = 5e-6;          % in s
 

Data-Analyzer/+Scripts/BECToStripesToDroplets/plotAnalysisResults.m

@@ -1,33 +1,43 @@
-% --- User chooses which dataset to load ---
+%% --- User chooses which dataset to load ---
-datasetIdx              = 6;   % <-- change this to 1, 2, 3, ...
+datasetIdx                = 1;   % <-- change this to 1, 2, 3, ...
-datasetName             = sprintf('Dataset_%d', datasetIdx);
+datasetName               = sprintf('Dataset_%d', datasetIdx);
 
-% Detect the folder where this script is located and set that as the Base Directory
+% --- Base directory selection ---
-thisScriptPath          = mfilename('fullpath');
+useLocalBaseDir           = false;  % <-- set true to use script location, false to use manual path
-[thisScriptDir, ~, ~]   = fileparts(thisScriptPath);
-baseDir                 = thisScriptDir;           % override if needed
 
-% Build path to dataset file
+if useLocalBaseDir
-dataFile                = fullfile(baseDir, "Results", "SavedData", datasetName + ".mat");
+    % Use folder where this script is located
-data                    = load(dataFile);
+    thisScriptPath        = mfilename('fullpath');
+    [thisScriptDir, ~, ~] = fileparts(thisScriptPath);
+    baseDir               = fullfile(thisScriptDir, 'Results');
+else
+    % Use manually specified folder
+    baseDir               = 'E:\Results - Experiment\202508\BECToStripesToDroplets\';
+end
 
-% Access dataset struct dynamically
+% --- Build paths ---
-datasetStruct           = data.(datasetName);
+dataFile                  = fullfile(baseDir, 'SavedData', [datasetName '.mat']);
-compiled_results        = datasetStruct.results;
+figSaveDir                = fullfile(baseDir, 'SavedFigures', datasetName);
-scan_parameter_values   = datasetStruct.scan_parameter_values;
-scan_reference_values   = datasetStruct.scan_reference_values;
 
-% Load the original options used during analysis
+% --- Load dataset ---
-options                 = datasetStruct.options;   % exact options used for this dataset
+data                      = load(dataFile);
-options.font            = 'Bahnschrift';           % override if needed
-options.skipSaveFigures = false;                   % override if needed
 
-%% ------------------ Create dataset-specific figure folder ------------------
+% --- Ensure figure folder exists ---
-figSaveDir = fullfile(baseDir,'Results', 'SavedFigures', datasetName);
 if ~exist(figSaveDir, 'dir')
     mkdir(figSaveDir);
 end
 
+% --- Access dataset struct dynamically ---
+datasetStruct             = data.(datasetName);
+compiled_results          = datasetStruct.results;
+scan_parameter_values     = datasetStruct.scan_parameter_values;
+scan_reference_values     = datasetStruct.scan_reference_values;
+
+% --- Load options used during analysis ---
+options                   = datasetStruct.options;
+options.font              = 'Bahnschrift';   % override if needed
+options.skipSaveFigures   = false;           % override if needed
+
 %% ------------------ 1. Mean ± Std Plots ------------------
 % Plot Radial Spectral Contrast
 Plotter.plotMeanWithSE(scan_parameter_values, compiled_results.spectral_analysis_results.radial_spectral_contrast, ...
@@ -146,6 +156,9 @@ Plotter.plotCumulants(scan_reference_values, ...
     'SaveFileName', 'CumulantOfPeakOffsetAngularCorrelation.fig', ...
     'SaveDirectory', figSaveDir);
 
+%%
+%{
+
 %% ------------------ 6. PCA ------------------
 Plotter.plotPCAResults(compiled_results.pca_results, scan_parameter_values, scan_reference_values, ...
     'FigNumRange', [10,11,12,13,14,15], ...
@@ -153,10 +166,7 @@ Plotter.plotPCAResults(compiled_results.pca_results, scan_parameter_values, scan
     'SkipSaveFigures', options.skipSaveFigures, ...
     'SaveDirectory', figSaveDir);
 
-%%
+%% ------------------ 7. Average of Spectra Plots ------------------
-%{
-
-%% ------------------ 6. Average of Spectra Plots ------------------
 
 Plotter.plotAverageSpectra(scan_parameter_values, ...
      spectral_analysis_results, ...
@@ -168,7 +178,7 @@ Plotter.plotAverageSpectra(scan_parameter_values, ...
      'SaveDirectory', figSaveDir, ...
      'SkipSaveFigures', options.skipSaveFigures);
 
-%% ------------------ 7. Compare quantities ------------------
+%% ------------------ 8. Compare quantities ------------------
 % Load Droplets → Stripes data
 Data = load(dtsFile, ...
     'unique_scan_parameter_values', ...
@@ -208,7 +218,7 @@ compareMultipleDatasets(scanValsCell, meanValsCell, stderrValsCell, ...
     'SaveDirectory', figSaveDir, ...
     'SaveFileName', 'AngularCorrelation_Comparison.fig');
 
-%% ------------------ 8. Heatmaps ------------------
+%% ------------------ 9. Heatmaps ------------------
 
 BFields = [2.35, 2.15, 2.0, 1.85, 1.7, 1.55, 1.4, 1.35];
 

Data-Analyzer/+Scripts/BECToStripesToDroplets/plotComparisonOfAnalysisResults.m

@@ -0,0 +1,147 @@
+%% ------------------ 1. Compare radial spectral contrast across datasets ------------------
+datasetIdxList = 1:6;
+
+% --- Base directory selection ---
+useLocalBaseDir = false;  % <-- set true to use script location, false to use manual path
+
+if useLocalBaseDir
+    % Use folder where this script is located
+    thisScriptPath        = mfilename('fullpath');
+    [thisScriptDir, ~, ~] = fileparts(thisScriptPath);
+    baseDir               = fullfile(thisScriptDir, 'Results');
+else
+    % Use manually specified folder
+    baseDir               = 'E:\Results - Experiment\202508\BECToDropletsToStripes\';
+end
+
+% Prepare storage
+scanValsCell   = cell(1, numel(datasetIdxList));
+meanValsCell   = cell(1, numel(datasetIdxList));
+stderrValsCell = cell(1, numel(datasetIdxList));
+labelsCell     = {'2.25 G', '2.20 G', '2.15 G', '2.10 G', '2.05 G', '2.00 G'};
+
+% --- Load options from first dataset to set plotting defaults ---
+datasetIdx  = datasetIdxList(1);
+datasetName = sprintf('Dataset_%d', datasetIdx);
+dataFile    = fullfile(baseDir, 'SavedData', [datasetName '.mat']);
+data        = load(dataFile);
+datasetStruct = data.(datasetName);
+options = datasetStruct.options;
+options.font            = 'Bahnschrift';
+options.skipSaveFigures = false;
+
+% --- Ensure combined figure folder exists ---
+combinedSaveDir = fullfile(baseDir, 'SavedFigures', 'Combined');
+if ~exist(combinedSaveDir, 'dir')
+    mkdir(combinedSaveDir);
+end
+
+% --- Loop over datasets to extract mean ± SE ---
+for i = 1:numel(datasetIdxList)
+    datasetIdx  = datasetIdxList(i);
+    datasetName = sprintf('Dataset_%d', datasetIdx);
+
+    % Build paths for this dataset
+    dataFile   = fullfile(baseDir, 'SavedData', [datasetName '.mat']);
+    
+    % Load dataset
+    data          = load(dataFile);
+    datasetStruct = data.(datasetName);
+
+    % Extract values
+    scanVals = datasetStruct.scan_parameter_values;
+    dataVals = datasetStruct.results.spectral_analysis_results.radial_spectral_contrast;
+
+    % --- Compute mean and standard error ---
+    [unique_vals, ~, idx] = unique(scanVals);
+    mean_vals   = zeros(size(unique_vals));
+    stderr_vals = zeros(size(unique_vals));
+    for k = 1:length(unique_vals)
+        if iscell(dataVals)
+            group = dataVals{idx == k};
+        else
+            group = dataVals(idx == k);
+        end
+        if iscell(group)
+            groupVals = [group{:}];
+        else
+            groupVals = group;
+        end
+        mean_vals(k)   = mean(groupVals);
+        stderr_vals(k) = std(groupVals) / sqrt(length(groupVals));
+    end
+
+    % Store results
+    scanValsCell{i}   = unique_vals;
+    meanValsCell{i}   = mean_vals;
+    stderrValsCell{i} = stderr_vals;
+end
+
+% --- Call compare function ---
+Plotter.compareMultipleDatasets(scanValsCell, meanValsCell, stderrValsCell, ...
+    'FigNum', 16, ...
+    'FontName', options.font, ...
+    'Labels', labelsCell, ...
+    'Title', 'Radial Spectral Contrast Across Datasets', ...
+    'XLabel', 'B (G)', ...
+    'YLabel', 'Radial Spectral Contrast', ...
+    'SaveDirectory', combinedSaveDir, ...
+    'SaveFileName', 'RadialSpectralContrast_Combined.fig', ...
+    'SkipSaveFigures', false);
+
+%% ------------------ 2. Compare max g2 across datasets ------------------
+
+% Prepare storage
+maxG2ValsCell   = cell(1, numel(datasetIdxList));
+maxG2MeanCell   = cell(1, numel(datasetIdxList));
+maxG2StderrCell = cell(1, numel(datasetIdxList));
+
+for i = 1:numel(datasetIdxList)
+    datasetIdx  = datasetIdxList(i);
+    datasetName = sprintf('Dataset_%d', datasetIdx);
+
+    % Load dataset
+    dataFile      = fullfile(baseDir, 'SavedData', [datasetName '.mat']);
+    data          = load(dataFile);
+    datasetStruct = data.(datasetName);
+
+    % Extract values
+    scanVals = datasetStruct.scan_parameter_values;
+    dataVals = datasetStruct.results.custom_g_results.max_g2_all_per_scan_parameter_value;
+
+    % --- Compute mean and standard error ---
+    [unique_vals, ~, idx] = unique(scanVals);
+    mean_vals   = zeros(size(unique_vals));
+    stderr_vals = zeros(size(unique_vals));
+    for k = 1:length(unique_vals)
+        if iscell(dataVals)
+            group = dataVals{idx == k};
+        else
+            group = dataVals(idx == k);
+        end
+        if iscell(group)
+            groupVals = [group{:}];
+        else
+            groupVals = group;
+        end
+        mean_vals(k)   = mean(groupVals);
+        stderr_vals(k) = std(groupVals) / sqrt(length(groupVals));
+    end
+
+    % Store results
+    maxG2ValsCell{i}   = unique_vals;
+    maxG2MeanCell{i}   = mean_vals;
+    maxG2StderrCell{i} = stderr_vals;
+end
+
+% --- Call compare function ---
+Plotter.compareMultipleDatasets(maxG2ValsCell, maxG2MeanCell, maxG2StderrCell, ...
+    'FigNum', 17, ...
+    'FontName', options.font, ...
+    'Labels', labelsCell, ...
+    'Title', 'Peak Offset Angular Correlation Across Datasets', ...
+    'XLabel', 'B (G)', ...
+    'YLabel', '$\mathrm{max}[g^{(2)}_{[50,70]}(\delta\theta)]$', ...
+    'SaveDirectory', combinedSaveDir, ...
+    'SaveFileName', 'MaxG2_Combined.fig', ...
+    'SkipSaveFigures', false);