101 lines
4.2 KiB
Matlab
101 lines
4.2 KiB
Matlab
function results = extractCustomCorrelation(angular_spectral_distribution, scan_parameter_values, N_shots, N_angular_bins)
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%% Extracts correlation of a single (highest) peak with possible secondary peak (50-70°)
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% Computes correlations and cumulants grouped by unique scan parameter.
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% ===== Convert spectral distributions to matrix =====
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delta_nkr_all = zeros(N_shots, N_angular_bins);
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for k = 1:N_shots
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delta_nkr_all(k, :) = angular_spectral_distribution{k};
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end
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% ===== Determine unique scan parameter values =====
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if isnumeric(scan_parameter_values) && isvector(scan_parameter_values)
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[unique_scan_parameter_values, ~, idx] = unique(scan_parameter_values(:), 'stable');
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elseif iscell(scan_parameter_values)
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params = cell2mat(scan_parameter_values);
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[unique_scan_parameter_values, ~, idx] = unique(params, 'rows', 'stable');
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else
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error('Unsupported format for scan_parameter_values.');
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end
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N_unique = size(unique_scan_parameter_values, 1);
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% ===== Angular settings =====
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angle_range = 180;
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angle_per_bin = angle_range / N_angular_bins;
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max_peak_bin = round(180 / angle_per_bin);
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window_size = 10;
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angle_threshold = 100;
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% ===== Preallocate result arrays based on unique values =====
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mean_max_g2_values = zeros(1, N_unique);
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skew_max_g2_angle_values = zeros(1, N_unique);
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var_max_g2_values = zeros(1, N_unique);
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fourth_order_cumulant_max_g2_angle_values = zeros(1, N_unique);
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max_g2_all_per_scan_parameter_value = cell(1, N_unique);
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std_error_g2_values = zeros(1, N_unique);
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% ===== Compute correlations and cumulants per unique parameter =====
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for i = 1:N_unique
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group_idx = find(idx == i); % all repetitions for this unique value
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group_data = delta_nkr_all(group_idx, :);
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N_reps = size(group_data, 1);
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g2_values = zeros(1, N_reps);
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for j = 1:N_reps
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profile = group_data(j, :);
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% Find highest peak in 0–180° range
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restricted_profile = profile(1:max_peak_bin);
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[~, peak_idx_rel] = max(restricted_profile);
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peak_idx = peak_idx_rel;
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peak_angle = (peak_idx - 1) * angle_per_bin;
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% Determine offsets for secondary peak correlation
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if peak_angle < angle_threshold
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offsets = round(50 / angle_per_bin) : round(70 / angle_per_bin);
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else
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offsets = -round(70 / angle_per_bin) : -round(50 / angle_per_bin);
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end
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ref_window = mod((peak_idx - window_size):(peak_idx + window_size) - 1, N_angular_bins) + 1;
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ref = profile(ref_window);
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correlations = zeros(size(offsets));
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for k_off = 1:length(offsets)
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shifted_idx = mod(peak_idx + offsets(k_off) - 1, N_angular_bins) + 1;
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sec_window = mod((shifted_idx - window_size):(shifted_idx + window_size) - 1, N_angular_bins) + 1;
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sec = profile(sec_window);
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correlations(k_off) = mean(ref .* sec) / mean(ref.^2);
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end
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[max_corr, ~] = max(correlations);
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g2_values(j) = max_corr;
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end
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% Store all repetitions for this unique parameter
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max_g2_all_per_scan_parameter_value{i} = g2_values;
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% Compute cumulants
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kappa = Calculator.computeCumulants(g2_values(:), 4);
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mean_max_g2_values(i) = kappa(1);
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var_max_g2_values(i) = kappa(2);
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skew_max_g2_angle_values(i) = kappa(3);
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fourth_order_cumulant_max_g2_angle_values(i) = kappa(4);
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N_eff = sum(~isnan(g2_values));
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std_error_g2_values(i) = sqrt(kappa(2)) / sqrt(N_eff);
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end
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% ===== Package results into struct =====
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results = struct();
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results.mean_max_g2 = mean_max_g2_values;
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results.var_max_g2 = var_max_g2_values;
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results.skew_max_g2_angle = skew_max_g2_angle_values;
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results.fourth_order_cumulant_max_g2 = fourth_order_cumulant_max_g2_angle_values;
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results.std_error_g2 = std_error_g2_values;
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results.max_g2_all_per_scan_parameter_value = max_g2_all_per_scan_parameter_value;
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results.scan_parameter_values = unique_scan_parameter_values;
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end |