263 lines
12 KiB
Matlab
263 lines
12 KiB
Matlab
function results = conductSpectralAnalysis(od_imgs, scan_parameter_values, options)
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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, 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 - base directory to save results
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% skipSaveFigures - skip saving plots
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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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% 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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% k_min, k_max - min/max wavenumber for spectral contrast
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% N_angular_bins - number of angular bins for S(θ)
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% Angular_Threshold - threshold parameter for angular spectrum
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% Angular_Sigma - Gaussian smoothing width for angular spectrum
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% theta_min, theta_max - angular range for radial spectrum integration
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% N_radial_bins - number of radial bins for S(k)
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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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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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k_min = options.k_min;
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k_max = options.k_max;
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N_angular_bins = options.N_angular_bins;
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Angular_Threshold = options.Angular_Threshold;
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Angular_Sigma = options.Angular_Sigma;
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theta_min = options.theta_min;
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theta_max = options.theta_max;
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N_radial_bins = options.N_radial_bins;
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Radial_WindowSize = options.Radial_WindowSize;
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skipNormalization = options.skipNormalization;
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skipPreprocessing = options.skipPreprocessing;
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skipMasking = options.skipMasking;
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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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skipSaveFigures = options.skipSaveFigures;
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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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%% ===== Initialization =====
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N_shots = length(od_imgs); % total number of images
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fft_imgs = cell(1, N_shots); % FFT of each image
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angular_spectral_distribution = cell(1, N_shots); % S(θ) angular spectrum
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radial_spectral_contrast = zeros(1, N_shots); % radial contrast metric
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angular_spectral_weight = zeros(1, N_shots); % integrated angular weight
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S_theta_all = cell(1, N_shots);
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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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% Prepare folder to save figures
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if ~skipSaveFigures
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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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%% ===== 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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% Skip FFT if image is empty or has low intensity
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if ~(max(IMG(:)) > 1)
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IMGFFT = NaN(size(IMG));
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else
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% Compute FFT with optional preprocessing
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[IMGFFT, ~] = Calculator.computeFourierTransform(IMG, skipPreprocessing, skipMasking, skipIntensityThresholding, skipBinarization);
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end
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% Image size
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[Ny, Nx] = size(IMG);
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% Real-space pixel size (meters)
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dx = pixel_size / magnification;
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dy = dx; % assume square pixels
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% Real-space axes in µm
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x = ((1:Nx) - ceil(Nx/2)) * dx * 1E6;
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y = ((1:Ny) - ceil(Ny/2)) * dy * 1E6;
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% Reciprocal space increments
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dvx = 1 / (Nx * dx);
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dvy = 1 / (Ny * dy);
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% Frequency axes
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vx = (-floor(Nx/2):ceil(Nx/2)-1) * dvx;
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vy = (-floor(Ny/2):ceil(Ny/2)-1) * dvy;
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% Wavenumber axes (µm⁻¹)
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kx_full = 2 * pi * vx * 1E-6;
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ky_full = 2 * pi * vy * 1E-6;
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% Crop FFT image around center
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mid_x = floor(Nx/2);
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mid_y = floor(Ny/2);
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fft_imgs{k} = IMGFFT(mid_y-zoom_size:mid_y+zoom_size, mid_x-zoom_size:mid_x+zoom_size);
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% Crop wavenumber axes to match cropped FFT
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kx = kx_full(mid_x - zoom_size : mid_x + zoom_size);
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ky = ky_full(mid_y - zoom_size : mid_y + zoom_size);
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%% ===== Spectral analysis =====
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% Angular spectrum
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[theta_vals, S_theta] = Calculator.computeAngularSpectralDistribution(fft_imgs{k}, kx, ky, k_min, k_max, N_angular_bins, Angular_Threshold, Angular_Sigma, []);
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% Radial spectrum
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[k_rho_vals, S_k] = Calculator.computeRadialSpectralDistribution(fft_imgs{k}, kx, ky, theta_min, theta_max, N_radial_bins);
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% Smooth radial spectrum
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S_k_smoothed = movmean(S_k, Radial_WindowSize);
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% Store results
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angular_spectral_distribution{k} = S_theta;
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radial_spectral_contrast(k) = Calculator.computeRadialSpectralContrast(k_rho_vals, S_k_smoothed, k_min, k_max);
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% Normalize angular spectrum and compute weight
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S_theta_norm = S_theta / max(S_theta);
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angular_spectral_weight(k) = trapz(theta_vals, S_theta_norm);
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% Store results
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S_theta_all{k} = S_theta;
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S_k_all{k} = S_k;
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S_k_smoothed_all{k} = S_k_smoothed;
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S_theta_norm_all{k} = S_theta_norm;
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PS_all{k} = abs(fft_imgs{k}).^2;
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%% ===== Plotting =====
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if ~skipLivePlot
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figure(1); clf
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set(gcf,'Position',[500 100 1000 800])
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tiledlayout(2, 2, 'TileSpacing', 'compact', 'Padding', 'compact');
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% OD image
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ax1 = nexttile;
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imagesc(x, y, IMG)
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hold on;
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Helper.drawODOverlays(x(1), y(1), x(end), y(end));
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Helper.drawODOverlays(x(end), y(1), x(1), y(end));
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hold off;
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axis equal tight;
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set(gca, 'FontSize', 14, 'YDir', 'normal')
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colormap(ax1, Colormaps.inferno());
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hcb = colorbar;
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ylabel(hcb, 'Optical Density', 'Rotation', -90, 'FontSize', 14, 'FontName', font);
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xlabel('x (\mum)', 'Interpreter', 'tex', 'FontSize', 14, 'FontName', font);
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ylabel('y (\mum)', 'Interpreter', 'tex', 'FontSize', 14, 'FontName', font);
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title('OD Image', 'FontSize', 16, 'FontWeight', 'bold', 'Interpreter', 'tex', 'FontName', font);
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% Annotate scan parameter
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if strcmp(scan_parameter, 'ps_rot_mag_fin_pol_angle')
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text(0.975, 0.975, sprintf('%.1f^\\circ', scan_parameter_values(k)), ...
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'Color', 'white', 'FontWeight', 'bold', 'FontSize', 14, ...
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'Interpreter', 'tex', 'Units', 'normalized', ...
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'HorizontalAlignment', 'right', 'VerticalAlignment', 'top');
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else
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text(0.975, 0.975, sprintf('%.2f G', scan_parameter_values(k)), ...
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'Color', 'white', 'FontWeight', 'bold', 'FontSize', 14, ...
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'Interpreter', 'tex', 'Units', 'normalized', ...
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'HorizontalAlignment', 'right', 'VerticalAlignment', 'top');
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end
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% FFT power spectrum
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ax2 = nexttile;
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imagesc(kx, ky, log(1 + PS_all{k}));
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hold on;
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Helper.drawPSOverlays(kx, ky, k_min, k_max)
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% Restrict axes strictly to image limits
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xlim([min(kx), max(kx)]);
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ylim([min(ky), max(ky)]);
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axis image; % preserves aspect ratio
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set(gca, 'FontSize', 14, 'YDir', 'normal')
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xlabel('k_x [\mum^{-1}]', 'Interpreter', 'tex', 'FontSize', 14, 'FontName', font);
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ylabel('k_y [\mum^{-1}]', 'Interpreter', 'tex', 'FontSize', 14, 'FontName', font);
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title('Power Spectrum - S(k_x,k_y)', 'Interpreter', 'tex', ...
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'FontSize', 16, 'FontWeight', 'bold', 'FontName', font);
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colorbar;
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colormap(ax2, Colormaps.coolwarm());
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% Radial distribution
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nexttile;
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plot(k_rho_vals, S_k_smoothed, 'LineWidth', 2);
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set(gca, 'FontSize', 14, 'YScale', 'log', 'XLim', [min(k_rho_vals), max(k_rho_vals)]);
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xlabel('k_\rho [\mum^{-1}]', 'Interpreter', 'tex', 'FontSize', 14, 'FontName', font);
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ylabel('Magnitude (a.u.)', 'Interpreter', 'tex', 'FontSize', 14, 'FontName', font);
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title('Radial Spectral Distribution - S(k_\rho)', 'Interpreter', 'tex', ...
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'FontSize', 16, 'FontWeight', 'bold', 'FontName', font);
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grid on;
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% Angular distribution
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nexttile;
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if ~skipNormalization
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plot(theta_vals/pi, S_theta_norm, 'LineWidth', 2);
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set(gca, 'FontSize', 14, 'YLim', [0, 1]);
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else
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plot(theta_vals/pi, S_theta, 'LineWidth', 2);
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set(gca, 'FontSize', 14, 'YScale', 'log', 'YLim', [1E4, 1E7]);
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end
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xlabel('\theta/\pi [rad]', 'Interpreter', 'tex', 'FontSize', 14, 'FontName', font);
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ylabel('Magnitude (a.u.)', 'Interpreter', 'tex', 'FontSize', 14, 'FontName', font);
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title('Angular Spectral Distribution - S(\theta)', 'Interpreter', 'tex', ...
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'FontSize', 16, 'FontWeight', 'bold', 'FontName', font);
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grid on;
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ax = gca;
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ax.MinorGridLineStyle = ':';
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ax.MinorGridColor = [0.7 0.7 0.7];
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ax.MinorGridAlpha = 0.5;
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ax.XMinorGrid = 'on';
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ax.YMinorGrid = 'on';
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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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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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results = struct();
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results.kx = kx;
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results.ky = ky;
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results.PS_all = PS_all;
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results.theta_vals = theta_vals;
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results.S_theta_all = S_theta_all;
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results.k_rho_vals = k_rho_vals;
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results.S_k_all = S_k_all;
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results.angular_spectral_distribution = angular_spectral_distribution;
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results.S_k_smoothed_all = S_k_smoothed_all;
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results.radial_spectral_contrast = radial_spectral_contrast;
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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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end
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