89 lines
3.4 KiB
Matlab
89 lines
3.4 KiB
Matlab
function plotG2Cumulants(results, varargin)
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%% plotG2Cumulants
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% Author: Karthik
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% Date: 2025-09-12
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% Version: 1.0
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%
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% Description:
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% Plot first four cumulants of g²(θ) vs scan parameter
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%
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% Inputs:
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% img - original 2D image
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% patchProps - struct array from detectPatches
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% results - struct array from extractAndClassifyShapes
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% params - parameter struct
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% xStart, yStart - offsets for cropped regions
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% figTitle - title string (e.g., 'BayesOpt Candidate')
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%
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% Notes:
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% Optional notes, references.
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% --- Parse name-value pairs ---
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p = inputParser;
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addParameter(p, 'Title', 'g² Cumulants', @(x) ischar(x) || isstring(x));
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addParameter(p, 'XLabel', 'Scan Parameter', @(x) ischar(x) || isstring(x));
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addParameter(p, 'FontName', 'Arial', @ischar);
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addParameter(p, 'FontSize', 14, @isnumeric);
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addParameter(p, 'FigNum', [], @(x) isempty(x) || (isnumeric(x) && isscalar(x)));
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addParameter(p, 'SkipSaveFigures', false, @islogical);
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addParameter(p, 'SaveFileName', 'G2Cumulants.fig', @ischar);
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addParameter(p, 'SaveDirectory', pwd, @ischar);
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parse(p, varargin{:});
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opts = p.Results;
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% --- Extract cumulant data from full distribution ---
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N_params = numel(results.g2_cumulants);
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N_theta = size(results.g2_cumulants{1},1);
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xvals = results.summaries.scanParamVal;
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kappa = zeros(N_theta, N_params, 4); % θ × scan × cumulant
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for i = 1:N_params
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cumul_mat = results.g2_cumulants{i}; % [N_theta × 4]
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kappa(:,i,:) = cumul_mat;
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end
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% --- Select specific theta indices: 0, pi/6, pi/3, pi/2, 2*pi/3, pi ---
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thetaVals = results.theta_values; % assume radians
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desiredTheta = [pi/12 pi/6 pi/3 pi/2 2*pi/3 5*pi/6];
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[~, thIdx] = arrayfun(@(t) min(abs(thetaVals - t)), desiredTheta);
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% --- Legend labels ---
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thetaLabels = {'\pi/12','\pi/6','\pi/3','\pi/2','2\pi/3','5\pi/6'};
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% --- Colormap (sky) ---
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cmap = Colormaps.coolwarm(numel(thIdx));
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% --- Create figure ---
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if isempty(opts.FigNum), fig = figure; else, fig = figure(opts.FigNum); end
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clf(fig);
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set(fig,'Color','w','Position',[100 100 950 750]);
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t = tiledlayout(2,2,'TileSpacing','Compact','Padding','Compact');
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title(t, opts.Title, 'FontName', opts.FontName, 'FontSize', opts.FontSize+4);
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cumulLabels = {'\kappa_1','\kappa_2','\kappa_3','\kappa_4'};
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cumulTitles = {'Mean','Variance','Skewness','Binder Cumulant'};
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for k = 1:4
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ax = nexttile; hold(ax,'on');
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for idx = 1:numel(thIdx)
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th = thIdx(idx);
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plot(ax, xvals, squeeze(kappa(th,:,k)), '-o', ...
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'Color', cmap(idx,:), 'LineWidth', 2, 'MarkerSize', 8, 'MarkerFaceColor', cmap(idx,:));
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end
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ylabel(ax, cumulLabels{k}, 'FontName', opts.FontName, 'FontSize', opts.FontSize);
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xlabel(ax, opts.XLabel, 'FontName', opts.FontName, 'FontSize', opts.FontSize);
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title(ax, cumulTitles{k}, 'FontName', opts.FontName, 'FontSize', opts.FontSize+2);
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grid(ax,'on'); set(ax,'FontName',opts.FontName,'FontSize',opts.FontSize);
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% --- Add legend ---
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legend(ax, thetaLabels, 'Location', 'best', 'FontSize', opts.FontSize-2);
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end
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% --- Save figure ---
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if ~opts.SkipSaveFigures
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if ~exist(opts.SaveDirectory,'dir'), mkdir(opts.SaveDirectory); end
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savefig(fig, fullfile(opts.SaveDirectory, opts.SaveFileName));
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end
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end
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