405 lines
15 KiB
Matlab
405 lines
15 KiB
Matlab
%% ===== BEC-Droplets-Stripes Settings =====
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% Specify data location to run analysis on
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dataSources = {
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struct('sequence', 'TwoDGas', ...
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'date', '2025/06/23', ...
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'runs', [300]) % specify run numbers as a string in "" or just as a numeric value
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};
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options = struct();
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% File paths
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options.baseDataFolder = '//DyLabNAS/Data';
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options.FullODImagesFolder = 'E:/Data - Experiment/FullODImages/202506';
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options.measurementName = 'DropletsToStripes';
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scriptFullPath = mfilename('fullpath');
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options.saveDirectory = fileparts(scriptFullPath);
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% Camera / imaging settings
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options.cam = 4; % 1 - ODT_1_Axis_Camera; 2 - ODT_2_Axis_Camera; 3 - Horizontal_Axis_Camera;, 4 - Vertical_Axis_Camera;
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options.angle = 0; % angle by which image will be rotated
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options.center = [1410, 2030];
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options.span = [200, 200];
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options.fraction = [0.1, 0.1];
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options.pixel_size = 5.86e-6; % in meters
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options.magnification = 23.94;
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options.ImagingMode = 'HighIntensity';
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options.PulseDuration = 5e-6; % in s
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% Fourier analysis settings
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options.theta_min = deg2rad(0);
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options.theta_max = deg2rad(180);
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options.N_radial_bins = 500;
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options.Radial_Sigma = 2;
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options.Radial_WindowSize = 5; % odd number
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options.k_min = 1.2771; % μm⁻¹
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options.k_max = 2.5541; % μm⁻¹
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options.N_angular_bins = 360;
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options.Angular_Threshold = 75;
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options.Angular_Sigma = 2;
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options.Angular_WindowSize = 5;
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options.zoom_size = 50;
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%
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options.maximumShift = 8;
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options.Radial_Theta = deg2rad(45);
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options.Radial_Minimum = 2;
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options.Radial_Maximum = 6;
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options.skipLivePlot = false;
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% Flags
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options.skipUnshuffling = false;
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options.skipNormalization = false;
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options.skipFringeRemoval = true;
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options.skipPreprocessing = true;
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options.skipMasking = true;
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options.skipIntensityThresholding = true;
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options.skipBinarization = true;
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options.skipFullODImagesFolderUse = false;
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options.skipSaveData = false;
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options.skipSaveFigures = true;
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options.skipSaveProcessedOD = true;
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options.skipLivePlot = false;
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options.showProgressBar = true;
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% Extras
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options.font = 'Bahnschrift';
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switch options.measurementName
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case 'BECToDroplets'
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options.scan_parameter = 'rot_mag_field';
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options.flipSortOrder = true;
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options.scanParameterUnits = 'gauss';
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options.titleString = 'BEC to Droplets';
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case 'BECToStripes'
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options.scan_parameter = 'rot_mag_field';
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options.flipSortOrder = true;
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options.scanParameterUnits = 'gauss';
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options.titleString = 'BEC to Stripes';
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case 'DropletsToStripes'
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options.scan_parameter = 'ps_rot_mag_fin_pol_angle';
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options.flipSortOrder = false;
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options.scanParameterUnits = 'degrees';
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options.titleString = 'Droplets to Stripes';
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case 'StripesToDroplets'
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options.scan_parameter = 'ps_rot_mag_fin_pol_angle';
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options.flipSortOrder = false;
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options.scanParameterUnits = 'degrees';
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options.titleString = 'Stripes to Droplets';
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end
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%% ===== Collect Images and Launch Viewer =====
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[options.selectedPath, options.folderPath] = Helper.selectDataSourcePath(dataSources, options);
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[od_imgs, scan_parameter_values, scan_reference_values, file_list] = Helper.collectODImages(options);
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%% Conduct spectral analysis
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spectral_analysis_results = Analyzer.extractFullAngularSpectralDistribution(od_imgs, options);
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%% ------------------ 1. Plot of all Angular Spectral Distribution Curves ------------------
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Plotter.plotSpectralCurves( ...
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spectral_analysis_results.S_theta_norm_all, ...
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spectral_analysis_results.theta_vals/pi, ... % correct θ values
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scan_reference_values, ... % correct scan params
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'Title', options.titleString, ...
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'XLabel', '\theta / \pi', ...
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'YLabel', 'S(\theta)', ...
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'HighlightEvery', 10, ... % highlight every 10th repetition
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'FontName', options.font, ...
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'FigNum', 1, ...
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'TileTitlePrefix', '\alpha', ... % user-defined tile prefix
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'TileTitleSuffix', '^\circ', ... % user-defined suffix (e.g., degrees symbol)
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SpectralCurves.fig', ...
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'SaveDirectory', options.saveDirectory);
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%% ------------------ 2. Plot of all Angular Spectral Distribution Curves shifted ------------------
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% --- Recenter curves first ---
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results = Analyzer.recenterSpectralCurves(spectral_analysis_results.S_theta_norm_all, ...
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spectral_analysis_results.theta_vals/pi, ...
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scan_reference_values, ...
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'SearchRange', [0 90]); % degrees
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% --- Restrict to desired theta range (e.g., 0 to 0.5*pi) ---
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thetaMin = 0; % in units of pi (since you divided by pi)
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thetaMax = 1; % corresponds to pi/2
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mask = results.x_values >= thetaMin & results.x_values <= thetaMax;
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results.x_values = results.x_values(mask);
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% Apply the same mask to each curve set
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for i = 1:numel(results.curves)
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results.curves{i} = results.curves{i}(:, mask);
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results.curves_mean{i} = results.curves_mean{i}(mask);
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results.curves_error{i}= results.curves_error{i}(mask);
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end
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Plotter.plotSpectralCurvesRecentered( ...
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results, ...
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scan_reference_values, ... % correct scan params
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'Title', options.titleString, ...
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'XLabel', '\theta / \pi', ...
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'YLabel', 'S(\theta)', ...
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'HighlightEvery', 10, ... % highlight every 10th repetition
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'FontName', options.font, ...
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'FigNum', 2, ...
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'TileTitlePrefix', '\alpha', ... % user-defined tile prefix
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'TileTitleSuffix', '^\circ', ... % user-defined suffix (e.g., degrees symbol)
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SpectralCurves.fig', ...
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'SaveDirectory', options.saveDirectory);
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%% ------------------ 3. Plot cumulants from shifted Angular Spectral Distribution Curves ------------------
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Plotter.plotSpectralDistributionCumulants(results, ...
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'Title', options.titleString, ...
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'XLabel', '\alpha (degrees)', ...
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'FontName', options.font, ...
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'FontSize', 14, ...
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'FigNum', 3, ...
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'SkipSaveFigures', false, ...
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'SaveFileName', 'SpectralCumulants.fig');
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%% ------------------ 4. Fit shifted Angular Spectral Distribution Curves ------------------
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[fitResults, rawCurves] = Analyzer.fitTwoGaussianCurves(...
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spectral_analysis_results.S_theta_norm_all, ...
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spectral_analysis_results.theta_vals, ...
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'MaxTheta', pi/2, ...
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'ResidualThreshold', 0.15, ...
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'PositionThreshold', pi/15, ...
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'AmplitudeThreshold', 0.15);
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%{
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% --- Function call ---
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plotTwoGaussianFitsOnRaw(fitResults, rawCurves, 8, 12); % 8×12 subplots per page
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% --- Function definition ---
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function plotTwoGaussianFitsOnRaw(fitResults, rawCurves, nRows, nCols)
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% plotTwoGaussianFitsOnRaw - Plots raw curves and overlays valid two-Gaussian fits.
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%
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% Inputs:
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% fitResults - struct array from fitTwoGaussianCurves (may contain fits)
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% rawCurves - struct array with fields:
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% .x - raw curve
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% .theta - corresponding theta values
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% nRows - number of subplot rows per page (default: 4)
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% nCols - number of subplot columns per page (default: 6)
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if nargin < 3, nRows = 4; end
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if nargin < 4, nCols = 6; end
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Ncurves = numel(rawCurves);
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plotsPerPage = nRows * nCols;
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pageNum = 1;
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for k = 1:Ncurves
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% --- New figure/page if needed ---
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if mod(k-1, plotsPerPage) == 0
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figure('Name', sprintf('Curves Page %d', pageNum), ...
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'NumberTitle', 'off', 'Color', 'w');
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pageNum = pageNum + 1;
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end
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% --- Select subplot ---
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subplot(nRows, nCols, mod(k-1, plotsPerPage)+1);
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hold on; grid on; box on;
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% --- Plot raw curve ---
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xRaw = rawCurves(k).x;
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thetaRaw = rawCurves(k).theta;
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if ~isempty(xRaw) && ~isempty(thetaRaw) && all(isfinite(xRaw))
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plot(thetaRaw, xRaw, 'k.-', 'LineWidth', 1, 'DisplayName', 'Raw data');
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end
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% --- Overlay fit if valid ---
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if k <= numel(fitResults)
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fit = fitResults(k);
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if isfield(fit, 'isValid') && fit.isValid ...
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&& ~isempty(fit.yFit) && ~isempty(fit.thetaFine)
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plot(fit.thetaFine, fit.yFit, 'r-', 'LineWidth', 1.2, 'DisplayName', 'Two-Gaussian fit');
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end
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end
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% --- Formatting ---
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xlabel('\theta (rad)');
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ylabel('Normalized amplitude');
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title(sprintf('Curve %d', k), 'FontSize', 10);
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% --- Legend once per page ---
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if mod(k-1, plotsPerPage) == 0
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legend('Location', 'best', 'FontSize', 8);
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end
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hold off;
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end
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end
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%}
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%% ------------------ 5. Plot fit parameters - amplitude ------------------
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Plotter.plotFitParameterPDF(fitResults, scan_reference_values, 'A2', ...
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'Title', options.titleString, ...
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'XLabel', '\alpha (degrees)', ...
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'YLabel', 'Secondary peak amplitude', ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'FigNum', 4, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SecondaryPeakAmplitudePDF.fig', ...
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'PlotType', 'histogram', ...
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'NumberOfBins', 20, ...
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'NormalizeHistogram', true, ...
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'Colormap', @Colormaps.coolwarm, ...
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'XLim', [min(scan_reference_values), max(scan_reference_values)], ...
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'YLim', [0, 1.6]);
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%% ------------------ 6. Plot fit parameters - position ------------------
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Plotter.plotFitParameterPDF(fitResults, scan_reference_values, 'mu2', ...
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'Title', options.titleString, ...
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'XLabel', '\alpha (degrees)', ...
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'YLabel', 'Secondary peak position (\theta, rad)', ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'FigNum', 5, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SecondaryPeakPositionPDF.fig', ...
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'PlotType', 'histogram', ...
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'NumberOfBins', 20, ...
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'NormalizeHistogram', true, ...
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'Colormap', @Colormaps.coolwarm, ...
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'XLim', [min(scan_reference_values), max(scan_reference_values)], ...
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'YLim', [0, 1.6]);
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%% ------------------ 7. Plot fit parameters - width ------------------
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Plotter.plotFitParameterPDF(fitResults, scan_reference_values, 'sigma2', ...
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'Title', options.titleString, ...
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'XLabel', '\alpha (degrees)', ...
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'YLabel', 'Secondary peak width (\sigma, rad)', ...
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'FontName', options.font, ...
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'FontSize', 16, ...
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'FigNum', 6, ...
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'SkipSaveFigures', options.skipSaveFigures, ...
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'SaveFileName', 'SecondaryPeakWidthPDF.fig', ...
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'PlotType', 'histogram', ...
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'NumberOfBins', 20, ...
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'NormalizeHistogram', true, ...
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'Colormap', @Colormaps.coolwarm, ...
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'XLim', [min(scan_reference_values), max(scan_reference_values)], ...
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'YLim', [0, 1.6]);
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%% ------------------ 8. Plot fit parameters of mean shifted Angular Spectral Distribution Curves ------------------
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% --- Recenter curves first ---
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results = Analyzer.recenterSpectralCurves(spectral_analysis_results.S_theta_norm_all, ...
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spectral_analysis_results.theta_vals/pi, ...
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scan_reference_values, ...
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'SearchRange', [0 90]); % degrees
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% --- Restrict to desired theta range (e.g., 0 to 0.5*pi) ---
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thetaMin = 0; % in units of pi (since you divided by pi)
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thetaMax = 1; % corresponds to pi/2
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mask = results.x_values >= thetaMin & results.x_values <= thetaMax;
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results.x_values = results.x_values(mask);
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% Apply the same mask to each curve set
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for i = 1:numel(results.curves)
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results.curves_mean{i} = results.curves_mean{i}(mask);
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end
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% --- Fit two-Gaussian model to mean curves ---
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[fitResultsMean, ~] = Analyzer.fitTwoGaussianCurves(...
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results.curves_mean, ...
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results.x_values*pi, ...
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'MaxTheta', pi/2, ...
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'ResidualThreshold', 0.15, ...
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'PositionThreshold', pi/15, ...
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'AmplitudeThreshold', 0.15, ...
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'RecenterCurves', false);
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% --- Prepare parameter values ---
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N_params = numel(fitResultsMean);
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amp2_vals = nan(1, N_params);
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mu2_vals = nan(1, N_params);
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sigma2_vals = nan(1, N_params);
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for i = 1:N_params
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pFit = fitResultsMean(i).pFit;
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if all(~isnan(pFit))
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% Successful fit → use fitted values
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amp2_vals(i) = pFit(4);
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mu2_vals(i) = pFit(5);
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sigma2_vals(i) = pFit(6);
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else
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% Fit failed → leave as NaN (skipped automatically)
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continue;
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end
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end
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% --- Plot using plotMeanWithSE ---
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Plotter.plotMeanWithSE(scan_reference_values, amp2_vals, ...
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'Title', options.titleString, ...
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'XLabel', '\alpha (degrees)', ...
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'YLabel', 'Secondary peak amplitude', ...
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'FigNum', 7, ...
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'FontName', options.font, ...
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'FontSize', 16);
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% --- Plot using plotMeanWithSE ---
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Plotter.plotMeanWithSE(scan_reference_values, mu2_vals, ...
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'Title', options.titleString, ...
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'XLabel', '\alpha (degrees)', ...
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'YLabel', 'Secondary peak position (\theta, rad)', ...
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'FigNum', 8, ...
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'FontName', options.font, ...
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'FontSize', 16);
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Plotter.plotMeanWithSE(scan_reference_values, sigma2_vals, ...
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'Title', options.titleString, ...
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'XLabel', '\alpha (degrees)', ...
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'YLabel', 'Secondary peak width (\sigma, rad)', ...
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'FigNum', 9, ...
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'FontName', options.font, ...
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'FontSize', 16);
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%% Inspect individual realizations of a single parameter
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% --- Recenter curves first ---
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results = Analyzer.recenterSpectralCurves( ...
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spectral_analysis_results.S_theta_norm_all, ...
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spectral_analysis_results.theta_vals/pi, ...
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scan_reference_values, ...
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'SearchRange', [0 90]); % degrees
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% --- Restrict to desired theta range (e.g., 0 to 0.5*pi) ---
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thetaMin = 0; % in units of pi (since you divided by pi)
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thetaMax = 1; % corresponds to pi/2
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mask = results.x_values >= thetaMin & results.x_values <= thetaMax;
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results.x_values = results.x_values(mask);
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% --- Apply the same mask to each curve set (1x10 cell, each 60x180) ---
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for i = 1:numel(results.curves)
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results.curves{i} = results.curves{i}(:, mask);
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end
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% --- Convert selected curve set (e.g., 5th) into 1x60 cell array of 1xN row vectors ---
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paramIdx = 1; % <-- choose which scan point or curve set to analyze
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curves_matrix = results.curves{paramIdx}; % 60xN numeric
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curves_cell = num2cell(curves_matrix, 2); % 1x60 cell array
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curves_cell = cellfun(@(x) x(:).', curves_cell, 'UniformOutput', false); % ensure 1xN row vectors
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% --- Fit two-Gaussian model to these curves ---
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[fitResults, rawCurves] = Analyzer.fitTwoGaussianCurves(...
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curves_cell, ...
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results.x_values*pi, ...
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'MaxTheta', pi/2, ...
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'ResidualThreshold', 0.15, ...
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'PositionThreshold', pi/15, ...
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'AmplitudeThreshold', 0.15, ...
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'RecenterCurves', false);
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