876 bids taskid

src/bids_importer/lib/FindFiles.m

@@ -0,0 +1,188 @@
+classdef FindFiles
+    %FINDFILES Search for files in a directory based on extension, filters, and depth.
+    %
+    % Usage:
+    %   ff = FindFiles("/data", ".nii");
+    %   disp(ff.files)
+    %
+    %   % With max depth + filters + exclude
+    %   ff = FindFiles("/data", ".tsv.gz", "exclude", "._", "filters", {"task-rest","physio"}, "maxdepth", 2);
+
+    properties
+        directory   (1,1) string
+        extension   (1,1) string
+        exclude             % [] | string | cellstr
+        maxdepth            % [] | integer
+        filters             % [] | string | cellstr
+        files               % char | cellstr (mirrors python behavior)
+    end
+
+    methods
+        function obj = FindFiles(directory, extension, varargin)
+            % FindFiles(directory, extension, 'exclude', ..., 'maxdepth', ..., 'filters', ...)
+            %
+            % directory: folder to search
+            % extension: like ".nii" or ".csv" or ".tsv.gz"
+
+            p = inputParser;
+            p.addRequired("directory", @(x) ischar(x) || isstring(x));
+            p.addRequired("extension", @(x) ischar(x) || isstring(x));
+            p.addParameter("exclude", [], @(x) isempty(x) || ischar(x) || isstring(x) || iscell(x));
+            p.addParameter("maxdepth", [], @(x) isempty(x) || (isscalar(x) && isnumeric(x) && x>=0));
+            p.addParameter("filters", [], @(x) isempty(x) || ischar(x) || isstring(x) || iscell(x));
+            p.parse(directory, extension, varargin{:});
+
+            obj.directory = string(p.Results.directory);
+            obj.extension = string(p.Results.extension);
+            obj.exclude   = p.Results.exclude;
+            obj.maxdepth  = p.Results.maxdepth;
+            obj.filters   = p.Results.filters;
+
+            % --- collect files recursively ---
+            pattern = "*" + obj.extension; % e.g. "*.nii" or "*.tsv.gz"
+            file_list = FindFiles.find_files(obj.directory, pattern, obj.maxdepth);
+
+            % remove macOS resource fork files "._*"
+            keep = true(1, numel(file_list));
+            for i = 1:numel(file_list)
+                [~, nm, ext] = fileparts(file_list{i});
+                base = [nm ext];
+                if startsWith(base, "._")
+                    keep(i) = false;
+                end
+            end
+            file_list = file_list(keep);
+
+            % sort
+            file_list = sort(file_list);
+
+            % --- apply filters/exclude like python (using get_file_from_substring) ---
+            if ~isempty(obj.exclude) || ~isempty(obj.filters)
+                filt = obj.filters;
+                if isempty(filt)
+                    filt = {};  % no filters means "everything", but python only filters when provided.
+                end
+
+                % If filters are empty but exclude exists, we still want exclusion applied.
+                % We'll emulate that by filtering with an empty filt (= match all),
+                % then applying exclusion.
+                if isempty(filt)
+                    % match all files
+                    if isempty(obj.exclude)
+                        out = file_list;
+                    else
+                        out = apply_exclude_only(file_list, obj.exclude);
+                    end
+                else
+                    out = get_file_from_substring(filt, file_list, 'error', obj.exclude);
+                end
+
+                obj.files = out;
+            else
+                obj.files = file_list;
+            end
+        end
+    end
+
+    methods (Static)
+        function files = find_files(directory, pattern, maxdepth)
+            %FINDFILES Recursively find files matching pattern with optional max depth.
+            %
+            % directory: string/char
+            % pattern: e.g. "*.nii", "*.csv", "*.tsv.gz"
+            % maxdepth: [] for unlimited, or non-negative integer
+            %
+            % Returns cell array of full paths.
+
+            directory = char(directory);
+            pattern   = char(pattern);
+
+            if nargin < 3
+                maxdepth = [];
+            end
+
+            if ~isfolder(directory)
+                error('FindFiles:NotAFolder', 'Directory does not exist: %s', directory);
+            end
+
+            files = {};
+            rootDepth = count_seps(directory);
+
+            % BFS stack of directories
+            stack = {directory};
+
+            while ~isempty(stack)
+                current = stack{1};
+                stack(1) = [];
+
+                curDepth = count_seps(current) - rootDepth;
+                if ~isempty(maxdepth) && curDepth > maxdepth
+                    continue;
+                end
+
+                listing = dir(current);
+
+                for i = 1:numel(listing)
+                    item = listing(i);
+
+                    if item.isdir
+                        nm = item.name;
+                        if strcmp(nm, '.') || strcmp(nm, '..')
+                            continue;
+                        end
+                        stack{end+1} = fullfile(current, nm); %#ok<AGROW>
+                    else
+                        if FindFiles.match_pattern(item.name, pattern)
+                            files{end+1} = fullfile(current, item.name); %#ok<AGROW>
+                        end
+                    end
+                end
+            end
+        end
+
+        function tf = match_pattern(filename, pattern)
+            % Simple glob match supporting '*' wildcard.
+            % pattern like "*.nii" or "*.tsv.gz"
+            %
+            % Convert glob -> regex
+            expr = regexptranslate('wildcard', pattern);
+            tf = ~isempty(regexp(filename, ['^' expr '$'], 'once'));
+        end
+    end
+end
+
+% ---- local helpers (same file is okay in modern MATLAB; otherwise split) ----
+
+function n = count_seps(p)
+    % count path separators to approximate depth
+    p = char(p);
+    n = sum(p == filesep);
+end
+
+function out = apply_exclude_only(file_list, exclude)
+    % Apply exclude to a cell array of paths; return char if single like python helper.
+
+    if ischar(exclude) || isstring(exclude)
+        exclude = {char(exclude)};
+    elseif iscell(exclude)
+        % ok
+    else
+        exclude = {};
+    end
+
+    keep = true(1, numel(file_list));
+    for i = 1:numel(file_list)
+        f = file_list{i};
+        for ex = 1:numel(exclude)
+            if contains(f, exclude{ex})
+                keep(i) = false;
+                break;
+            end
+        end
+    end
+    out = file_list(keep);
+
+    if numel(out) == 1
+        out = out{1};
+    end
+end

src/bids_importer/lib/build_pspm_eye_channels.m

@@ -0,0 +1,150 @@
+function data = build_pspm_eye_channels(eye_data_cell)
+%BUILD_PSPM_EYE_CHANNELS Build PsPM eye-tracking channels from imported BIDS-like entries.
+%
+%   data = BUILD_PSPM_EYE_CHANNELS(eye_data_cell)
+%
+%   Converts eye-tracking data/metadata entries (typically parsed from BIDS
+%   physio JSON/TSV pairs) into a PsPM-style channel cell array containing
+%   pupil size and gaze coordinate signals for right and/or left eye.
+%
+%   The function:
+%     - Normalizes input entries to a consistent right/left representation
+%       (via NORMALIZE_EYE_ENTRIES).
+%     - Creates up to 6 channels total (3 signals × 2 eyes) in a stable
+%       order: right eye first, then left eye.
+%     - For each created channel:
+%         * Copies the data vector from the corresponding table column.
+%         * Sets hdr.chantype to '<signal>_<side>' (e.g., 'pupil_r').
+%         * Populates additional header fields using FILL_EYE_CHANNEL_HEADER
+%           (e.g., sampling rate, units, description, gaze range).
+%
+%   Inputs
+%   ------
+%   eye_data_cell : cell array
+%       Cell array of eye entries. Each entry is expected (typically) to
+%       contain:
+%         - RecordedEye           : 'right'/'left' recommended (used by the
+%                                  normalization step)
+%         - Columns               : table containing some/all of:
+%                                  'pupil_size', 'x_coordinate', 'y_coordinate'
+%         - SamplingFrequency     : numeric (optional)
+%         - pupil_size.Description: string/char (optional)
+%         - pupil_size.Units      : string/char (optional)
+%         - SampleCoordinateUnits : string/char (optional) OR
+%           x_coordinate.Units / y_coordinate.Units (optional)
+%         - GazeRange.xmin/xmax/ymin/ymax (optional)
+%
+%   Output
+%   ------
+%   data : cell array
+%       Cell array of PsPM channels. Each channel is a struct with fields:
+%         - data{i}.data   : numeric column vector (samples x 1)
+%         - data{i}.header : struct with at least:
+%                            * chantype (e.g., 'gaze_x_r')
+%                            and potentially:
+%                            * sr, units, Description, range
+%
+%   Channel mapping
+%   ---------------
+%   The following columns (if present) are mapped to channels:
+%     - 'pupil_size'   -> chantype 'pupil_<side>'
+%     - 'x_coordinate' -> chantype 'gaze_x_<side>'
+%     - 'y_coordinate' -> chantype 'gaze_y_<side>'
+%
+%   Warnings / edge cases
+%   ---------------------
+%   - If eye_data_cell is empty: warns and returns {}.
+%   - If no valid right/left entries are found: warns and returns {}.
+%   - If only one eye is present: warns once per encountered side.
+%   - If an entry lacks a valid Columns table: warns and skips that eye.
+%   - If a required column is missing: warns and skips that channel.
+%
+%   See also
+%   --------
+%   NORMALIZE_EYE_ENTRIES, FILL_EYE_CHANNEL_HEADER
+    data = {};
+
+    if isempty(eye_data_cell)
+        fprintf('No eye data available\n');
+        return
+    end
+
+    eyes = normalize_eye_entries(eye_data_cell);
+
+    if isempty(eyes.r) && isempty(eyes.l)
+        warning('No valid right/left eye entries found.');
+        return
+    end
+
+    sig = struct( ...
+        'col',  {'pupil_size', 'x_coordinate', 'y_coordinate'}, ...
+        'name', {'pupil',      'gaze_x',       'gaze_y'} ...
+    );
+
+    order = {'r', 'l'};
+    ch = 0;
+
+    for s = 1:numel(order)
+        side = order{s};
+        entry = eyes.(side);
+
+        if isempty(entry)
+            continue
+        end
+
+        [meta, T] = split_eye_entry(entry);
+
+        if ~istable(T)
+            warning('Eye "%s" has no valid sample table; skipping.', side);
+            continue
+        end
+
+        for k = 1:numel(sig)
+            if ~ismember(sig(k).col, T.Properties.VariableNames)
+                warning('Missing column "%s" for eye "%s"; skipping channel.', sig(k).col, side);
+                continue
+            end
+
+            ch = ch + 1;
+            data{ch}.data = T{:, sig(k).col};
+            data{ch}.header.chantype = sprintf('%s_%s', sig(k).name, side);
+            data{ch}.header = fill_eye_channel_header(data{ch}.header, meta, sig(k).name);
+        end
+    end
+end
+
+
+function [meta, T] = split_eye_entry(entry)
+% Try to separate metadata struct from samples table.
+
+    meta = entry;
+    T = [];
+
+    % Preferred structure: entry.meta + entry.table
+    if isstruct(entry)
+        if isfield(entry, 'meta') && isstruct(entry.meta)
+            meta = entry.meta;
+        end
+
+        if isfield(entry, 'table') && istable(entry.table)
+            T = entry.table;
+            return
+        end
+
+        if isfield(entry, 'data') && istable(entry.data)
+            T = entry.data;
+            return
+        end
+
+        if isfield(entry, 'tsv') && istable(entry.tsv)
+            T = entry.tsv;
+            return
+        end
+    end
+
+    % Backward-compatible fallback: if entry.Columns is already a table
+    if isstruct(entry) && isfield(entry, 'Columns') && istable(entry.Columns)
+        T = entry.Columns;
+        return
+    end
+end