Bug fixes, exception handling, new measurement analysis scripts.
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@ -2,23 +2,20 @@ function results = conductSpectralAnalysis(od_imgs, scan_parameter_values, optio
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%% Performs Fourier analysis on a set of optical density (OD) images.
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% Computes radial and angular spectral distributions, optionally plots
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% results, saves figures, and can render a video of the analysis.
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% results, and saves figures.
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%
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% Inputs:
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% od_imgs - cell array of OD images
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% scan_parameter_values - array of scan parameter values corresponding to each image
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% OPTIONS -
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% saveDirectory - directory to save files
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% savefileName - base filename for saved figures/video
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% skipMovieRender - skip creating the video of analysis
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% saveDirectory - base directory to save results
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% skipSaveFigures - skip saving plots
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% skipSaveOD - skip saving OD images as .mat
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% skipPreprocessing - skip preprocessing of images before FFT
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% skipMasking - skip masking of OD images
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% skipIntensityThresholding- skip thresholding of intensity
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% skipBinarization - skip binarization of OD images
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% skipNormalization - skip normalization when plotting angular spectrum
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% skipLivePlot = skip live plotting of figures
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% skipLivePlot - skip live plotting of figures
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% pixel_size - physical pixel size of camera sensor (m)
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% magnification - imaging magnification
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% zoom_size - number of pixels to crop around FFT center
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@ -31,8 +28,13 @@ function results = conductSpectralAnalysis(od_imgs, scan_parameter_values, optio
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% Radial_WindowSize - window size for smoothing radial spectrum
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% scan_parameter - string, type of scan parameter (used in plot text)
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% font - font name for plots
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%
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% Outputs:
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% results - struct containing spectra and analysis results
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% Figures (if enabled) are saved into:
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% [saveDirectory]/Results/SpectralAnalysisSavedFigures/
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%% Unpack struct arguments
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%% ===== Unpack struct arguments =====
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pixel_size = options.pixel_size;
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magnification = options.magnification;
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zoom_size = options.zoom_size;
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@ -51,10 +53,7 @@ function results = conductSpectralAnalysis(od_imgs, scan_parameter_values, optio
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skipIntensityThresholding = options.skipIntensityThresholding;
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skipBinarization = options.skipBinarization;
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skipLivePlot = options.skipLivePlot;
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skipMovieRender = options.skipMovieRender;
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skipSaveFigures = options.skipSaveFigures;
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skipSaveOD = options.skipSaveOD;
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savefileName = options.savefileName;
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saveDirectory = options.saveDirectory;
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scan_parameter = options.scan_parameter;
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font = options.font;
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@ -70,33 +69,16 @@ function results = conductSpectralAnalysis(od_imgs, scan_parameter_values, optio
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S_k_all = cell(1, N_shots);
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S_k_smoothed_all = cell(1, N_shots);
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S_theta_norm_all = cell(1, N_shots);
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PS_all = cell(1, N_shots); % 2D FFT power spectrum |F(kx,ky)|^2
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% Optional save directory override
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if ~isempty(saveDirectory)
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savefileName = fullfile(saveDirectory, savefileName);
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end
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% Prepare video if enabled
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if ~skipMovieRender
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videoFile = VideoWriter([savefileName '.mp4'], 'MPEG-4');
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videoFile.Quality = 100;
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videoFile.FrameRate = 2;
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open(videoFile);
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end
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% Prepare folder to save figures
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if ~skipSaveFigures
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saveFolder = [savefileName '_SavedFigures'];
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saveFolder = fullfile(saveDirectory, "Results", "SpectralAnalysisSavedFigures");
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if ~exist(saveFolder, 'dir')
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mkdir(saveFolder);
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end
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end
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% Initialize lists for power spectra and radial spectra
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PS_all = cell(1, N_shots); % 2D FFT power spectrum |F(kx,ky)|^2
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%% ===== Main loop over images =====
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for k = 1:N_shots
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IMG = od_imgs{k};
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@ -253,29 +235,16 @@ function results = conductSpectralAnalysis(od_imgs, scan_parameter_values, optio
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ax.YMinorGrid = 'on';
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end
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%% ===== Save outputs =====
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if ~skipMovieRender
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frame = getframe(gcf);
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writeVideo(videoFile, frame);
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end
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%% ===== Save figures =====
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if ~skipSaveFigures
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fileNamePNG = fullfile(saveFolder, sprintf('fft_analysis_img_%03d.png', k));
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print(gcf, fileNamePNG, '-dpng', '-r100');
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end
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if ~skipSaveOD
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odDataStruct = struct();
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odDataStruct.IMG = IMG;
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odDataStruct.x = x;
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odDataStruct.y = y;
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odDataStruct.scan_parameter_value = scan_parameter_values(k);
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save(fullfile(saveFolder, sprintf('od_image_%03d.mat', k)), '-struct', 'odDataStruct');
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end
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if skipMovieRender && skipSaveFigures
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elseif ~skipLivePlot
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pause(0.5);
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end
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end
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% Package results into struct
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% Package results into struct
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results = struct();
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results.kx = kx;
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results.ky = ky;
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@ -290,7 +259,4 @@ function results = conductSpectralAnalysis(od_imgs, scan_parameter_values, optio
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results.S_theta_norm_all = S_theta_norm_all;
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results.angular_spectral_weight = angular_spectral_weight;
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if ~skipMovieRender
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close(videoFile);
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end
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end
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@ -31,17 +31,14 @@ function results = performAnalysis(options)
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options.skipBinarization (1,1) logical
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options.skipNormalization (1,1) logical
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options.skipLivePlot (1,1) logical
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options.skipMovieRender (1,1) logical
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options.skipSaveFigures (1,1) logical
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options.skipSaveOD (1,1) logical
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options.showProgressBar (1,1) logical
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options.savefileName (1,:) char
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options.measurementName (1,:) char
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options.folderPath (1,:) char
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options.baseDataFolder (1,:) char
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options.saveDirectory (1,:) char
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options.titleString (1,:) char
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options.font (1,:) char
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end
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% Collect OD images
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@ -68,7 +68,7 @@ function runInteractiveODImageViewer(od_imgs, scan_parameter_values, file_list,
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shortName = [fname, ext];
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% Update figure title with shot + filename
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if strcmp(options.scan_parameter, 'rot_mag_fin_pol_angle')
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if strcmp(options.scan_parameter, 'ps_rot_mag_fin_pol_angle')
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hFig.Name = sprintf('Shot %d | %s', idx, shortName);
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txtHandle.String = sprintf('%.1f^\\circ', scan_parameter_values(idx));
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else
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@ -1,4 +1,4 @@
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function [ordered_od_imgs, ordered_scan_parameter_values, ordered_file_list] = collectODImages(options)
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function [od_imgs, scan_parameter_values, file_list] = collectODImages(options)
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%% Applies cropping, background subtraction, and optional fringe removal, optional unshuffling on OD image dataset
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% Automatically reuses in-memory full dataset if available;
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% otherwise, reads and processes raw HDF5 data.
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@ -17,17 +17,29 @@ function [ordered_od_imgs, ordered_scan_parameter_values, ordered_file_list] = c
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% .scan_reference_values: reference values for unshuffling
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%
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% Outputs:
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% ordered_od_imgs : cell array of processed OD images (ordered)
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% ordered_scan_parameter_values: vector of scan parameter values (ordered)
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% ordered_file_list : cell array of file names (ordered)
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% od_imgs : cell array of processed OD images
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% scan_parameter_values: vector of scan parameter values
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% file_list : cell array of file names
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% --- Early exit if processed data already exist ---
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if evalin('base', 'exist(''od_imgs'',''var'') && exist(''scan_parameter_values'',''var'') && exist(''file_list'',''var'')')
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fprintf('\nReusing processed OD images, scan parameters, and file list from memory.\n');
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ordered_od_imgs = evalin('base','od_imgs');
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ordered_scan_parameter_values = evalin('base','scan_parameter_values');
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ordered_file_list = evalin('base','file_list');
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return; % ✅ skip rest of the function
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% --- Early exit if processed data already exist AND options match ---
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reuseVarsExist = evalin('base', ...
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'exist(''od_imgs'',''var'') && exist(''scan_parameter_values'',''var'') && exist(''file_list'',''var'') && exist(''prior_options'',''var'')');
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if reuseVarsExist
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prior_options = evalin('base','prior_options');
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% Define which fields are critical for reuse
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critical_fields = {'folderPath','cam','angle','ImagingMode','PulseDuration','center','span','fraction','removeFringes','skipUnshuffling','scan_reference_values'};
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if ~haveOptionsChanged(options, prior_options, critical_fields)
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fprintf('\nReusing processed OD images, scan parameters, and file list from memory (options unchanged).\n');
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od_imgs = evalin('base','od_imgs');
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scan_parameter_values = evalin('base','scan_parameter_values');
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file_list = evalin('base','file_list');
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return; % ✅ skip rest of the function
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else
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fprintf('\nProcessed-data-related options changed. Reprocessing full OD image dataset...\n');
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end
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end
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% --- Check if the full OD dataset and scan parameters exist in workspace ---
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@ -37,12 +49,29 @@ function [ordered_od_imgs, ordered_scan_parameter_values, ordered_file_list] = c
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evalin('base', 'exist(''raw_file_list'', ''var'')');
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if fullDataExists
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% Both required datasets exist, use them directly
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fprintf('\nReusing full OD image dataset and scan parameters from memory.\n');
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full_od_imgs = evalin('base', 'full_od_imgs');
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full_bkg_imgs = evalin('base', 'full_bkg_imgs');
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raw_scan_parameter_values = evalin('base', 'raw_scan_parameter_values');
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raw_file_list = evalin('base', 'raw_file_list');
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% Both required datasets exist, check if raw-data options changed
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prior_options = evalin('base','prior_options');
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% Define critical fields that affect raw-data computation
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critical_raw_fields = {'folderPath','cam','angle','ImagingMode','PulseDuration'};
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if ~haveOptionsChanged(options, prior_options, critical_raw_fields)
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fprintf('\nReusing full OD image dataset and scan parameters from memory.\n');
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full_od_imgs = evalin('base', 'full_od_imgs');
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full_bkg_imgs = evalin('base', 'full_bkg_imgs');
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raw_scan_parameter_values = evalin('base', 'raw_scan_parameter_values');
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raw_file_list = evalin('base', 'raw_file_list');
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else
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fprintf('\nRaw-data-related options changed. Recomputing full OD image dataset...\n');
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[full_od_imgs, full_bkg_imgs, raw_scan_parameter_values, raw_file_list] = Helper.processRawData(options);
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% Save raw full dataset for reuse
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assignin('base', 'full_od_imgs', full_od_imgs);
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assignin('base', 'full_bkg_imgs', full_bkg_imgs);
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assignin('base', 'raw_scan_parameter_values', raw_scan_parameter_values);
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assignin('base', 'raw_file_list', raw_file_list);
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fprintf('\nCompleted recomputing OD images. Stored in workspace for reuse.\n');
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end
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else
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% Either dataset is missing, process raw HDF5 files completely
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fprintf('\nFull OD image dataset or scan parameters not found in memory.\n');
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@ -53,9 +82,9 @@ function [ordered_od_imgs, ordered_scan_parameter_values, ordered_file_list] = c
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assignin('base', 'full_bkg_imgs', full_bkg_imgs);
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assignin('base', 'raw_scan_parameter_values', raw_scan_parameter_values);
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assignin('base', 'raw_file_list', raw_file_list);
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fprintf('\nCompleted computing OD images. Stored in workspace for reuse.\n');
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fprintf('\nCompleted computing OD images and will be stored in workspace for reuse.\n');
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end
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nFiles = size(full_od_imgs, 3);
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% --- Preallocate arrays for processed images ---
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@ -64,20 +93,20 @@ function [ordered_od_imgs, ordered_scan_parameter_values, ordered_file_list] = c
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% --- Process each image: crop and subtract background ---
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for k = 1:nFiles
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od_img = full_od_imgs(:,:,k); % original full OD image, never modified
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bkg_img = full_bkg_imgs(:,:,k); % original full background image, never modified
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if any(isnan(od_img(:)))
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full_od_img = full_od_imgs(:,:,k); % original full OD image, never modified
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full_bkg_img = full_bkg_imgs(:,:,k); % original full background image, never modified
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if any(isnan(full_od_img(:)))
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absimages(:,:,k) = nan(options.span(1)+1, options.span(2)+1, 'single');
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continue
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end
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if any(isnan(bkg_img(:)))
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if any(isnan(full_bkg_img(:)))
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refimages(:,:,k) = nan(options.span(1)+1, options.span(2)+1, 'single');
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continue
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end
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% Crop image around the region of interest
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cropped_absimage = Helper.cropODImage(od_img, options.center, options.span);
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cropped_refimage = Helper.cropODImage(bkg_img, options.center, options.span);
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cropped_absimage = Helper.cropODImage(full_od_img, options.center, options.span);
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cropped_refimage = Helper.cropODImage(full_bkg_img, options.center, options.span);
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% Subtract background offset based on fraction
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processed_absimage = Helper.subtractBackgroundOffset(cropped_absimage, options.fraction);
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@ -93,10 +122,10 @@ function [ordered_od_imgs, ordered_scan_parameter_values, ordered_file_list] = c
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fprintf('\nApplying fringe removal to processed images...\n');
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optrefimages = Helper.removeFringesInImage(absimages, refimages);
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absimages_fringe_removed = absimages - optrefimages;
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processed_od_imgs = arrayfun(@(i) absimages_fringe_removed(:,:,i), 1:nFiles, 'UniformOutput', false);
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od_imgs = arrayfun(@(i) absimages_fringe_removed(:,:,i), 1:nFiles, 'UniformOutput', false);
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fprintf('\nFringe removal completed.\n');
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else
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processed_od_imgs = arrayfun(@(i) absimages(:,:,i), 1:nFiles, 'UniformOutput', false);
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od_imgs = arrayfun(@(i) absimages(:,:,i), 1:nFiles, 'UniformOutput', false);
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end
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% --- Optional unshuffling based on scan reference values ---
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@ -108,12 +137,12 @@ function [ordered_od_imgs, ordered_scan_parameter_values, ordered_file_list] = c
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n_reps = n_total / n_values;
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ordered_scan_parameter_values = zeros(1, n_total);
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ordered_od_imgs = cell(1, n_total);
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ordered_file_list = cell(1, n_total);
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ordered_od_imgs = cell(1, n_total);
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ordered_file_list = cell(1, n_total);
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counter = 1;
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temp_scan_values = raw_scan_parameter_values;
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temp_od_imgs = processed_od_imgs;
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temp_od_imgs = od_imgs;
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temp_file_list = raw_file_list;
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for rep = 1:n_reps
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@ -129,18 +158,51 @@ function [ordered_od_imgs, ordered_scan_parameter_values, ordered_file_list] = c
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counter = counter + 1;
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end
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end
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od_imgs = ordered_od_imgs;
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scan_parameter_values = ordered_scan_parameter_values;
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file_list = ordered_file_list;
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fprintf('\nImage reordering completed.\n');
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else
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% No unshuffling: keep original order
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ordered_od_imgs = processed_od_imgs;
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ordered_scan_parameter_values = raw_scan_parameter_values;
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ordered_file_list = raw_file_list;
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scan_parameter_values = raw_scan_parameter_values;
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file_list = raw_file_list;
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end
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% --- Save processed dataset for reuse ---
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assignin('base', 'od_imgs', ordered_od_imgs);
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assignin('base', 'scan_parameter_values', ordered_scan_parameter_values);
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assignin('base', 'file_list', ordered_file_list);
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% --- Save processed dataset and options for reuse ---
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assignin('base', 'od_imgs', od_imgs);
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assignin('base', 'scan_parameter_values', scan_parameter_values);
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assignin('base', 'file_list', file_list);
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assignin('base', 'prior_options', options);
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% --- Optionally save OD images as figures ---
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if ~options.skipSaveFigures
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odFolder = fullfile(saveDirectory, "Results", "ODImages");
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if ~exist(odFolder, 'dir')
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mkdir(odFolder);
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end
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for k = 1:length(od_imgs)
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img = od_imgs{k};
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fileName = fullfile(odFolder, sprintf('OD_img_%03d.png', k));
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imwrite(mat2gray(img), fileName);
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end
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end
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fprintf('\nOD image dataset ready for further analysis.\n');
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end
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% --- Local helper function to compare options ---
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function changed = haveOptionsChanged(options, prior_options, critical_fields)
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changed = false;
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for f = critical_fields
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fname = f{1};
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if isfield(options, fname) && isfield(prior_options, fname)
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if ~isequal(options.(fname), prior_options.(fname))
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changed = true; return
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end
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elseif xor(isfield(options, fname), isfield(prior_options, fname))
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changed = true; return
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end
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end
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end
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@ -25,20 +25,12 @@ function plotAverageSpectra(scan_parameter_values, spectral_analysis_results, va
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addParameter(p, 'FigNum', 1, @(x) isnumeric(x) && isscalar(x));
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addParameter(p, 'ColormapPS', Colormaps.coolwarm(), @(x) isnumeric(x) || ismatrix(x));
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addParameter(p, 'Font', 'Arial', @ischar);
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addParameter(p, 'SaveFileName', 'figure.fig', @ischar);
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addParameter(p, 'SaveFileName', 'avgspectra.fig', @ischar);
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addParameter(p, 'SaveDirectory', pwd, @ischar);
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addParameter(p, 'SkipSaveFigures', false, @islogical);
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parse(p, varargin{:});
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opts = p.Results;
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scanParam = opts.ScanParameterName;
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figNum = opts.FigNum;
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colormapPS = opts.ColormapPS;
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fontName = opts.Font;
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saveFileName = opts.SaveFileName;
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saveDirectory = opts.SaveDirectory;
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skipSaveFigures = opts.SkipSaveFigures;
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% --- Unique scan parameters ---
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[uniqueParams, ~, idx] = unique(scan_parameter_values);
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nParams = numel(uniqueParams);
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@ -67,7 +59,7 @@ function plotAverageSpectra(scan_parameter_values, spectral_analysis_results, va
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avgS_theta = avgS_theta / nShots;
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% ==== Plot ====
|
||||
fig = figure(figNum); clf;
|
||||
fig = figure(opts.FigNum); clf;
|
||||
set(fig, 'Color', 'w', 'Position', [400 200 1200 400]);
|
||||
tLayout = tiledlayout(1,3,'TileSpacing','compact','Padding','compact');
|
||||
|
||||
@ -79,14 +71,14 @@ function plotAverageSpectra(scan_parameter_values, spectral_analysis_results, va
|
||||
imagesc(kx, ky, log(1 + avgPS));
|
||||
axis image;
|
||||
set(gca, 'FontSize', axisFontSize, 'YDir', 'normal');
|
||||
xlabel('k_x [\mum^{-1}]','Interpreter','tex','FontSize',axisFontSize,'FontName',fontName);
|
||||
ylabel('k_y [\mum^{-1}]','Interpreter','tex','FontSize',axisFontSize,'FontName',fontName);
|
||||
xlabel('k_x [\mum^{-1}]','Interpreter','tex','FontSize',axisFontSize,'FontName',opts.Font);
|
||||
ylabel('k_y [\mum^{-1}]','Interpreter','tex','FontSize',axisFontSize,'FontName',opts.Font);
|
||||
title('Average Power Spectrum','FontSize',titleFontSize,'FontWeight','bold');
|
||||
colormap(colormapPS);
|
||||
colormap(opts.ColormapPS);
|
||||
colorbar;
|
||||
|
||||
% --- Annotate scan parameter ---
|
||||
if strcmp(scanParam,'ps_rot_mag_fin_pol_angle')
|
||||
if strcmp(opts.ScanParameterName,'ps_rot_mag_fin_pol_angle')
|
||||
txt = sprintf('%.1f^\\circ', currentParam);
|
||||
else
|
||||
txt = sprintf('%.2f G', currentParam);
|
||||
@ -119,8 +111,8 @@ function plotAverageSpectra(scan_parameter_values, spectral_analysis_results, va
|
||||
|
||||
% --- Save figure ---
|
||||
saveFigure(fig, ...
|
||||
'SaveFileName', saveFileName, ...
|
||||
'SaveDirectory', saveDirectory, ...
|
||||
'SkipSaveFigures', skipSaveFigures);
|
||||
'SaveFileName', opts.SaveFileName, ...
|
||||
'SaveDirectory', opts.SaveDirectory, ...
|
||||
'SkipSaveFigures', opts.SkipSaveFigures);
|
||||
end
|
||||
end
|
||||
|
||||
@ -10,10 +10,10 @@ dataSources = {
|
||||
options = struct();
|
||||
|
||||
% File / paths
|
||||
options.baseDataFolder = '//DyLabNAS/Data';
|
||||
options.savefileName = 'BECToDroplets';
|
||||
scriptFullPath = mfilename('fullpath');
|
||||
options.saveDirectory = fileparts(scriptFullPath);
|
||||
options.baseDataFolder = '//DyLabNAS/Data';
|
||||
options.measurementName = 'BECToDroplets';
|
||||
scriptFullPath = mfilename('fullpath');
|
||||
options.saveDirectory = fileparts(scriptFullPath);
|
||||
|
||||
% Camera / imaging
|
||||
options.cam = 5;
|
||||
@ -45,7 +45,7 @@ options.zoom_size = 50;
|
||||
% Scan parameter
|
||||
options.scan_parameter = 'rot_mag_field';
|
||||
|
||||
switch options.savefileName
|
||||
switch options.measurementName
|
||||
case 'BECToDroplets'
|
||||
options.scan_reference_values = [2.40, 2.39, 2.38, 2.37, 2.35, 2.34, 2.32, 2.30, 2.28, 2.26, 2.24, 2.22, 2.2, 2.15, 2.10, 2.05, 2, 1.95, 1.90, 1.85, 1.8];
|
||||
options.titleString = 'BEC to Droplets';
|
||||
|
||||
@ -10,10 +10,10 @@ dataSources = {
|
||||
options = struct();
|
||||
|
||||
% File / paths
|
||||
options.baseDataFolder = '//DyLabNAS/Data';
|
||||
options.savefileName = 'BECToDroplets';
|
||||
scriptFullPath = mfilename('fullpath');
|
||||
options.saveDirectory = fileparts(scriptFullPath);
|
||||
options.baseDataFolder = '//DyLabNAS/Data';
|
||||
options.measurementName = 'BECToDroplets';
|
||||
scriptFullPath = mfilename('fullpath');
|
||||
options.saveDirectory = fileparts(scriptFullPath);
|
||||
|
||||
% Camera / imaging
|
||||
options.cam = 5;
|
||||
@ -45,7 +45,7 @@ options.zoom_size = 50;
|
||||
% Scan parameter
|
||||
options.scan_parameter = 'rot_mag_field';
|
||||
|
||||
switch options.savefileName
|
||||
switch options.measurementName
|
||||
case 'BECToDroplets'
|
||||
options.scan_reference_values = [2.40, 2.39, 2.38, 2.37, 2.35, 2.34, 2.32, 2.30, 2.28, 2.26, 2.24, 2.22, 2.2, 2.15, 2.10, 2.05, 2, 1.95, 1.90, 1.85, 1.8];
|
||||
options.titleString = 'BEC to Droplets';
|
||||
|
||||
@ -0,0 +1,163 @@
|
||||
idx = 1;
|
||||
compiled_results = results_all{idx}.results;
|
||||
options.skipSaveFigures = false;
|
||||
|
||||
%% ------------------ 1. Mean ± Std Plots ------------------
|
||||
% Plot Radial Spectral Contrast
|
||||
Plotter.plotMeanWithSE(scan_parameter_values, compiled_results.spectral_analysis_results.radial_spectral_contrast, ...
|
||||
'Title', options.titleString, ...
|
||||
'XLabel', 'B (G)', ...
|
||||
'YLabel', 'Radial Spectral Contrast', ...
|
||||
'FigNum', 1, ...
|
||||
'FontName', options.font, ...
|
||||
'SaveFileName', 'RadialSpectralContrast.fig', ...
|
||||
'SaveDirectory', [options.saveDirectory '/Results'], ...
|
||||
'SkipSaveFigures', options.skipSaveFigures);
|
||||
|
||||
% Plot Angular Spectral Weight
|
||||
Plotter.plotMeanWithSE(scan_parameter_values, compiled_results.spectral_analysis_results.angular_spectral_weight, ...
|
||||
'Title', options.titleString, ...
|
||||
'XLabel', 'B (G)', ...
|
||||
'YLabel', 'Angular Spectral Weight', ...
|
||||
'FigNum', 2, ...
|
||||
'FontName', options.font, ...
|
||||
'SaveFileName', 'AngularSpectralWeight.fig', ...
|
||||
'SaveDirectory', [options.saveDirectory '/Results'], ...
|
||||
'SkipSaveFigures', options.skipSaveFigures);
|
||||
|
||||
% Plot Peak Offset Angular Correlation
|
||||
Plotter.plotMeanWithSE(options.scan_reference_values, compiled_results.custom_g_results.max_g2_all_per_scan_parameter_value, ...
|
||||
'Title', options.titleString, ...
|
||||
'XLabel', 'B (G)', ...
|
||||
'YLabel', '$\mathrm{max}[g^{(2)}_{[50,70]}(\delta\theta)]$', ...
|
||||
'FigNum', 3, ...
|
||||
'YLim', [0 1], ...
|
||||
'FontName', options.font, ...
|
||||
'SaveFileName', 'PeakOffsetAngularCorrelation.fig', ...
|
||||
'SaveDirectory', [options.saveDirectory '/Results'], ...
|
||||
'SkipSaveFigures', options.skipSaveFigures);
|
||||
|
||||
%% ------------------ 2. g²(θ) across transition ------------------
|
||||
Plotter.plotG2(compiled_results.full_g2_results.g2_all, ...
|
||||
compiled_results.full_g2_results.g2_error_all, ...
|
||||
compiled_results.full_g2_results.theta_values, ...
|
||||
options.scan_reference_values, ...
|
||||
'rot_mag_field', ...
|
||||
'Title', options.titleString, ...
|
||||
'XLabel', '$\delta\theta / \pi$', ...
|
||||
'YLabel', '$g^{(2)}(\delta\theta)$', ...
|
||||
'FigNum', 4, ...
|
||||
'FontName', options.font, ...
|
||||
'SkipSaveFigures', options.skipSaveFigures, ...
|
||||
'SaveFileName', 'G2ThetaAcrossTransition.fig', ...
|
||||
'SaveDirectory', [options.saveDirectory '/Results'], ...
|
||||
'Colormap', @Colormaps.coolwarm);
|
||||
|
||||
%% ------------------ 3. PDF of max g² across transition ------------------
|
||||
Plotter.plotPDF(compiled_results.custom_g_results.max_g2_all_per_scan_parameter_value, options.scan_reference_values, ...
|
||||
'Title', options.titleString, ...
|
||||
'XLabel', 'B (G)', ...
|
||||
'YLabel', '$\mathrm{max}[g^{(2)}]$', ...
|
||||
'FigNum', 5, ...
|
||||
'FontName', options.font, ...
|
||||
'SkipSaveFigures', options.skipSaveFigures, ...
|
||||
'SaveFileName', 'PDF_MaxG2AcrossTransition.fig', ...
|
||||
'SaveDirectory', [options.saveDirectory '/Results'], ...
|
||||
'NumPoints', 200, ...
|
||||
'DataRange', [0 1.5], ...
|
||||
'Colormap', @Colormaps.coolwarm, ...
|
||||
'XLim', [min(options.scan_reference_values) max(options.scan_reference_values)]);
|
||||
|
||||
|
||||
%% ------------------ 4. Cumulants across transition ------------------
|
||||
Plotter.plotCumulants(options.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', 6, ...
|
||||
'FontName', options.font, ...
|
||||
'MarkerSize', 6, ...
|
||||
'LineWidth', 1.5, ...
|
||||
'SkipSaveFigures', options.skipSaveFigures, ...
|
||||
'SaveFileName', 'CumulantOfPeakOffsetAngularCorrelation.fig', ...
|
||||
'SaveDirectory', [options.saveDirectory '/Results']);
|
||||
%{
|
||||
|
||||
%% ------------------ 6. Average of Spectra Plots ------------------
|
||||
|
||||
Plotter.plotAverageSpectra(scan_parameter_values, ...
|
||||
spectral_analysis_results, ...
|
||||
'ScanParameterName', scan_parameter, ...
|
||||
'FigNum', 7, ...
|
||||
'ColormapPS', Colormaps.coolwarm(), ...
|
||||
'Font', 'Bahnschrift', ...
|
||||
'SaveFileName', 'avgSpectra.fig', ...
|
||||
'SaveDirectory', [options.saveDirectory '/Results'], ...
|
||||
'SkipSaveFigures', options.skipSaveFigures);
|
||||
|
||||
%% ------------------ 7. Compare quantities ------------------
|
||||
% Load Droplets → Stripes data
|
||||
Data = load(dtsFile, ...
|
||||
'unique_scan_parameter_values', ...
|
||||
'mean_max_g2_values', ...
|
||||
'std_error_g2_values');
|
||||
dts_scan_parameter_values = Data.unique_scan_parameter_values;
|
||||
dts_mean_mg2 = Data.mean_max_g2_values;
|
||||
dts_stderr_mg2 = Data.std_error_g2_values;
|
||||
|
||||
% Load Stripes → Droplets data
|
||||
Data = load(stdFile, ...
|
||||
'unique_scan_parameter_values', ...
|
||||
'mean_max_g2_values', ...
|
||||
'std_error_g2_values');
|
||||
std_scan_parameter_values = Data.unique_scan_parameter_values;
|
||||
std_mean_mg2 = Data.mean_max_g2_values;
|
||||
std_stderr_mg2 = Data.std_error_g2_values;
|
||||
|
||||
% Prepare cell arrays for multiple datasets
|
||||
scanValsCell = {dts_scan_parameter_values, std_scan_parameter_values};
|
||||
meanValsCell = {dts_mean_mg2, std_mean_mg2};
|
||||
stderrValsCell = {dts_stderr_mg2, std_stderr_mg2};
|
||||
|
||||
% Compare datasets
|
||||
compareMultipleDatasets(scanValsCell, meanValsCell, stderrValsCell, ...
|
||||
'FigNum', 8, ...
|
||||
'FontName', 'Bahnschrift', ...
|
||||
'MarkerSize', 6, ...
|
||||
'LineWidth', 1.5, ...
|
||||
'CapSize', 5, ...
|
||||
'YLim', [0 1], ...
|
||||
'Labels', {'Droplets → Stripes', 'Stripes → Droplets'}, ...
|
||||
'Title', 'AngularCorrelation_Comparison', ...
|
||||
'XLabel', 'B (G)', ...
|
||||
'YLabel', '$\mathrm{max}[g^{(2)}_{[50,70]}(\delta\theta)]$', ...
|
||||
'SkipSaveFigures', options.skipSaveFigures, ...
|
||||
'SaveDirectory', [options.saveDirectory '/Results'], ...
|
||||
'SaveFileName', 'AngularCorrelation_Comparison.fig');
|
||||
|
||||
%% ------------------ 8. Heatmaps ------------------
|
||||
|
||||
BFields = [2.35, 2.15, 2.0, 1.85, 1.7, 1.55, 1.4, 1.35];
|
||||
|
||||
% Heatmap of mean_max_g2_values
|
||||
Plotter.plotHeatmap(compiled_results, options.scan_groups, BFields, 'mean_max_g2_values', ...
|
||||
'Colormap', @sky, ...
|
||||
'CLim', [0 1], ...
|
||||
'XLabel', '\alpha (degrees)', ...
|
||||
'YLabel', 'BField (G)', ...
|
||||
'Title', '$\mathrm{max}[g^{(2)}_{[50,70]}(\delta\theta)]$', ...
|
||||
'FigNum', 9, ...
|
||||
'SaveFileName', 'Heatmap_MaxG2.fig', ...
|
||||
'SaveDirectory', options.resultsDir);
|
||||
|
||||
% Heatmap of radial_spectral_contrast
|
||||
Plotter.plotHeatmap(compiled_results, options.scan_groups, BFields, 'radial_spectral_contrast', ...
|
||||
'Colormap', @sky, ...
|
||||
'CLim', [0 0.008], ...
|
||||
'XLabel', '\alpha (degrees)', ...
|
||||
'YLabel', 'BField (G)', ...
|
||||
'Title', 'Radial Spectral Contrast', ...
|
||||
'FigNum', 10, ...
|
||||
'SaveFileName', 'Heatmap_RadialSpectralContrast.fig', ...
|
||||
'SaveDirectory', options.resultsDir);
|
||||
%}
|
||||
116
Data-Analyzer/+Scripts/BECToDropletsToStripes/plotImages.m
Normal file
116
Data-Analyzer/+Scripts/BECToDropletsToStripes/plotImages.m
Normal file
@ -0,0 +1,116 @@
|
||||
%% ===== BEC-Droplets-Stripes Settings =====
|
||||
|
||||
% Specify data location to run analysis on
|
||||
dataSources = {
|
||||
struct('sequence', 'StructuralPhaseTransition', ...
|
||||
'date', '2025/08/16', ...
|
||||
'runs', [8]) % specify run numbers as a string in "" or just as a numeric value
|
||||
};
|
||||
|
||||
options = struct();
|
||||
|
||||
% File / paths
|
||||
options.baseDataFolder = '//DyLabNAS/Data';
|
||||
options.measurementName = 'DropletsToStripes';
|
||||
scriptFullPath = mfilename('fullpath');
|
||||
options.saveDirectory = fileparts(scriptFullPath);
|
||||
|
||||
% Camera / imaging
|
||||
options.cam = 5;
|
||||
options.angle = 0;
|
||||
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.removeFringes = false;
|
||||
options.ImagingMode = 'HighIntensity';
|
||||
options.PulseDuration = 5e-6; % in s
|
||||
|
||||
% Fourier analysis settings
|
||||
options.theta_min = deg2rad(0);
|
||||
options.theta_max = deg2rad(180);
|
||||
options.N_radial_bins = 500;
|
||||
options.Radial_Sigma = 2;
|
||||
options.Radial_WindowSize = 5; % odd number
|
||||
|
||||
options.k_min = 1.2771; % μm⁻¹
|
||||
options.k_max = 2.5541; % μm⁻¹
|
||||
options.N_angular_bins = 180;
|
||||
options.Angular_Threshold = 75;
|
||||
options.Angular_Sigma = 2;
|
||||
options.Angular_WindowSize = 5;
|
||||
options.zoom_size = 50;
|
||||
|
||||
% Scan parameter
|
||||
options.scan_parameter = 'ps_rot_mag_fin_pol_angle';
|
||||
|
||||
switch options.measurementName
|
||||
case 'BECToDroplets'
|
||||
options.scan_reference_values = [2.40, 2.39, 2.38, 2.37, 2.35, 2.34, 2.32, 2.30, 2.28, 2.26, 2.24, 2.22, 2.2, 2.15, 2.10, 2.05, 2, 1.95, 1.90, 1.85, 1.8];
|
||||
options.titleString = 'BEC to Droplets';
|
||||
case 'BECToStripes'
|
||||
options.scan_reference_values = [2.45, 2.44, 2.43, 2.42, 2.4, 2.39, 2.38, 2.37, 2.36, 2.35, 2.34, 2.32, 2.3, 2.28, 2.25, 2.2, 2.15, 2.10, 2.0, 1.90, 1.8];
|
||||
options.titleString = 'BEC to Stripes';
|
||||
case 'DropletsToStripes'
|
||||
options.scan_reference_values = [0, 5, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 35, 40];
|
||||
options.titleString = 'Droplets to Stripes';
|
||||
case 'StripesToDroplets'
|
||||
options.scan_reference_values = fliplr([0, 5, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 35, 40]);
|
||||
options.titleString = 'Stripes to Droplets';
|
||||
end
|
||||
|
||||
% Flags
|
||||
options.skipNormalization = false;
|
||||
options.skipUnshuffling = false;
|
||||
options.skipPreprocessing = true;
|
||||
options.skipMasking = true;
|
||||
options.skipIntensityThresholding = true;
|
||||
options.skipBinarization = true;
|
||||
options.skipSaveFigures = false;
|
||||
options.skipLivePlot = false;
|
||||
options.showProgressBar = true;
|
||||
|
||||
% Extras
|
||||
options.font = 'Bahnschrift';
|
||||
|
||||
%% ===== Build Paths from Data Sources =====
|
||||
|
||||
allPaths = {}; % initialize
|
||||
|
||||
for i = 1:length(dataSources)
|
||||
ds = dataSources{i};
|
||||
|
||||
% Split the date string into year/month/day
|
||||
dateParts = strsplit(ds.date, '/');
|
||||
|
||||
for run = ds.runs
|
||||
runStr = sprintf('%04d', run); % 4-digit run number
|
||||
fullPath = fullfile(options.baseDataFolder, ds.sequence, dateParts{:}, runStr);
|
||||
|
||||
if isfolder(fullPath) % only include valid directories
|
||||
allPaths{end+1} = fullPath;
|
||||
else
|
||||
warning('Path does not exist: %s', fullPath);
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
% Let user select a single path
|
||||
set(0,'DefaultUicontrolFontSize',10); % increase default font size
|
||||
[selectedIndex, tf] = listdlg('PromptString','Select a path to analyze:', ...
|
||||
'SelectionMode','single', ...
|
||||
'ListString', allPaths, ...
|
||||
'ListSize',[400, 300]); % width x height in pixels
|
||||
if tf
|
||||
options.folderPath = allPaths{selectedIndex}; % ✅ store in options
|
||||
fprintf('Path set to selection: %s\n', options.folderPath);
|
||||
else
|
||||
error('No path selected. Aborting.');
|
||||
end
|
||||
|
||||
%% ===== Collect Images and Launch Viewer =====
|
||||
|
||||
[od_imgs, scan_parameter_values, file_list] = Helper.collectODImages(options);
|
||||
|
||||
Analyzer.runInteractiveODImageViewer(od_imgs, scan_parameter_values, file_list, options);
|
||||
@ -0,0 +1,78 @@
|
||||
%% ===== BEC-Droplets-Stripes Settings =====
|
||||
|
||||
% Specify data location to run analysis on
|
||||
dataSources = {
|
||||
struct('sequence', 'StructuralPhaseTransition', ...
|
||||
'date', '2025/08/16', ...
|
||||
'runs', [8]) % specify run numbers as a string in "" or just as a numeric value
|
||||
};
|
||||
|
||||
options = struct();
|
||||
|
||||
% File / paths
|
||||
options.baseDataFolder = '//DyLabNAS/Data';
|
||||
options.measurementName = 'DropletsToStripes';
|
||||
scriptFullPath = mfilename('fullpath');
|
||||
options.saveDirectory = fileparts(scriptFullPath);
|
||||
|
||||
% Camera / imaging
|
||||
options.cam = 5;
|
||||
options.angle = 0;
|
||||
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.removeFringes = false;
|
||||
options.ImagingMode = 'HighIntensity';
|
||||
options.PulseDuration = 5e-6; % in s
|
||||
|
||||
% Fourier analysis settings
|
||||
options.theta_min = deg2rad(0);
|
||||
options.theta_max = deg2rad(180);
|
||||
options.N_radial_bins = 500;
|
||||
options.Radial_Sigma = 2;
|
||||
options.Radial_WindowSize = 5; % odd number
|
||||
|
||||
options.k_min = 1.2771; % μm⁻¹
|
||||
options.k_max = 2.5541; % μm⁻¹
|
||||
options.N_angular_bins = 180;
|
||||
options.Angular_Threshold = 75;
|
||||
options.Angular_Sigma = 2;
|
||||
options.Angular_WindowSize = 5;
|
||||
options.zoom_size = 50;
|
||||
|
||||
% Scan parameter
|
||||
options.scan_parameter = 'ps_rot_mag_fin_pol_angle';
|
||||
|
||||
switch options.measurementName
|
||||
case 'BECToDroplets'
|
||||
options.scan_reference_values = [2.40, 2.39, 2.38, 2.37, 2.35, 2.34, 2.32, 2.30, 2.28, 2.26, 2.24, 2.22, 2.2, 2.15, 2.10, 2.05, 2, 1.95, 1.90, 1.85, 1.8];
|
||||
options.titleString = 'BEC to Droplets';
|
||||
case 'BECToStripes'
|
||||
options.scan_reference_values = [2.45, 2.44, 2.43, 2.42, 2.4, 2.39, 2.38, 2.37, 2.36, 2.35, 2.34, 2.32, 2.3, 2.28, 2.25, 2.2, 2.15, 2.10, 2.0, 1.90, 1.8];
|
||||
options.titleString = 'BEC to Stripes';
|
||||
case 'DropletsToStripes'
|
||||
options.scan_reference_values = [0, 5, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 35, 40];
|
||||
options.titleString = 'Droplets to Stripes';
|
||||
case 'StripesToDroplets'
|
||||
options.scan_reference_values = fliplr([0, 5, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 35, 40]);
|
||||
options.titleString = 'Stripes to Droplets';
|
||||
end
|
||||
|
||||
% Flags
|
||||
options.skipNormalization = false;
|
||||
options.skipUnshuffling = false;
|
||||
options.skipPreprocessing = true;
|
||||
options.skipMasking = true;
|
||||
options.skipIntensityThresholding = true;
|
||||
options.skipBinarization = true;
|
||||
options.skipSaveFigures = false;
|
||||
options.skipLivePlot = false;
|
||||
options.showProgressBar = true;
|
||||
|
||||
% Extras
|
||||
options.font = 'Bahnschrift';
|
||||
|
||||
%% ===== Run Batch Analysis =====
|
||||
results_all = Helper.batchAnalyze(dataSources, options);
|
||||
@ -10,10 +10,10 @@ dataSources = {
|
||||
options = struct();
|
||||
|
||||
% File / paths
|
||||
options.baseDataFolder = '//DyLabNAS/Data';
|
||||
options.savefileName = 'BECToDroplets';
|
||||
scriptFullPath = mfilename('fullpath');
|
||||
options.saveDirectory = fileparts(scriptFullPath);
|
||||
options.baseDataFolder = '//DyLabNAS/Data';
|
||||
options.measurementName = 'BECToDroplets';
|
||||
scriptFullPath ´= mfilename('fullpath');
|
||||
options.saveDirectory = fileparts(scriptFullPath);
|
||||
|
||||
% Camera / imaging
|
||||
options.cam = 5;
|
||||
@ -45,7 +45,7 @@ options.zoom_size = 50;
|
||||
% Scan parameter
|
||||
options.scan_parameter = 'rot_mag_field';
|
||||
|
||||
switch options.savefileName
|
||||
switch options.measurementName
|
||||
case 'BECToDroplets'
|
||||
options.scan_reference_values = [2.40, 2.39, 2.38, 2.37, 2.35, 2.34, 2.32, 2.30, 2.28, 2.26, 2.24, 2.22, 2.2, 2.15, 2.10, 2.05, 2, 1.95, 1.90, 1.85, 1.8];
|
||||
options.titleString = 'BEC to Droplets';
|
||||
|
||||
@ -10,10 +10,10 @@ dataSources = {
|
||||
options = struct();
|
||||
|
||||
% File / paths
|
||||
options.baseDataFolder = '//DyLabNAS/Data';
|
||||
options.savefileName = 'BECToStripes';
|
||||
scriptFullPath = mfilename('fullpath');
|
||||
options.saveDirectory = fileparts(scriptFullPath);
|
||||
options.baseDataFolder = '//DyLabNAS/Data';
|
||||
options.measurementName = 'BECToStripes';
|
||||
scriptFullPath = mfilename('fullpath');
|
||||
options.saveDirectory = fileparts(scriptFullPath);
|
||||
|
||||
% Camera / imaging
|
||||
options.cam = 5;
|
||||
@ -45,7 +45,7 @@ options.zoom_size = 50;
|
||||
% Scan parameter
|
||||
options.scan_parameter = 'rot_mag_field';
|
||||
|
||||
switch options.savefileName
|
||||
switch options.measurementName
|
||||
case 'BECToDroplets'
|
||||
options.scan_reference_values = [2.40, 2.39, 2.38, 2.37, 2.35, 2.34, 2.32, 2.30, 2.28, 2.26, 2.24, 2.22, 2.2, 2.15, 2.10, 2.05, 2, 1.95, 1.90, 1.85, 1.8];
|
||||
options.titleString = 'BEC to Droplets';
|
||||
|
||||
Loading…
Reference in New Issue
Block a user