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Process for linear regression of single-trial data #834

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177 changes: 177 additions & 0 deletions toolbox/process/functions/process_CNRL_getRegressors.m
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Original file line number Diff line number Diff line change
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function varargout = process_CNRL_getRegressors( varargin ) %#ok<STOUT>


eval(macro_method);
end


%% ===== GET DESCRIPTION =====
function sProcess = GetDescription()
% Description the process
sProcess.Comment = 'CNRL_Regressors';
sProcess.Category = 'Custom';
sProcess.SubGroup = 'CNRL';
sProcess.Index = 10013;
sProcess.Description = 'Get Regressors';
% Definition of the input accepted by this process
sProcess.InputTypes = {'data'};
sProcess.OutputTypes = {'matrix'};
sProcess.nInputs = 1;
sProcess.nMinFiles = 1;
sProcess.isSeparator = 1;

sProcess.options.intercept.Comment = 'Include Intercept in Model';
sProcess.options.intercept.Type = 'checkbox';
sProcess.options.intercept.Value = 2;

% === SELECT: ROWS
sProcess.options.columns.Comment = 'Regressor Description (one for each regressor, comma-seperated)';
sProcess.options.columns.Type = 'text';
sProcess.options.columns.Value = '';
sProcess.options.columns.InputTypes = {'data'};

end


%% ===== FORMAT COMMENT =====
function Comment = FormatComment(sProcess)
Comment = sProcess.Comment;
end


%% ===== RUN =====
function OutputFiles = Run(sProcess, sInputs)

if sProcess.options.intercept.Value
Description= {'Intercept'};
intercept_column=1;
else
Description= {};
intercept_column=0;
end

reg_titles = strsplit(sProcess.options.columns.Value, ',');
reg_titles = erase(reg_titles, ' ');

for i=1:length(reg_titles)
Description{end+1} = reg_titles{i};

end

% sort input files by condition/subject
[iGroups, ~] = process_average('SortFiles',sInputs, 3);

OutputFiles = cell(1,length(iGroups));

for i = 1:length(iGroups)

sInput = sInputs(iGroups{i});


OutEvents = zeros(length(sInput),3);
OutEvents(:,1) = ones(length(sInput),1);
for iInput = 1:length(sInput)

[FileMat, ~] = in_bst(sInput(iInput).FileName, [-0.01, 0.01]);

% === EVENTS ===
if isfield(FileMat, 'Events') && ~isempty(FileMat.Events)
if length(reg_titles) == length(FileMat.Events)
for j=1:length(reg_titles)
OutEvents(iInput,intercept_column+j) = str2double(FileMat.Events(j).label);
end
else
disp(['Not enough events in trial ' num2str(iInput)]);
end
else
disp(['No events in trial ' num2str(iInput)]);
end
end

% ===== GET OPTIONS =====
[~, iStudy, ~] = bst_process('GetOutputStudy', sProcess, sInput);

OutputFiles{i} = CNRL_import_matrix(iStudy,OutEvents',Description,1);
end

end

function OutputFile = CNRL_import_matrix(iStudy, Value, Description, sfreq)
% IMPORT_MATRIX: Imports a 2D matrix as a "matrix" file.
%
% USAGE: OutputFile = import_matrix(iStudy, Value=[ask], sfreq=[ask])
%
% INPUT:
% - iStudy : Index of the study where to import the SourceFiles
% - Value : 2D matrix to import as a "matrix" object in the database
% If not specified: ask for selecting a variable in the workspace
% - sfreq : Sampling frequency of the signals (Hertz)

% @=============================================================================
% This function is part of the Brainstorm software:
% https://neuroimage.usc.edu/brainstorm
%
% Copyright (c) University of Southern California & McGill University
% This software is distributed under the terms of the GNU General Public License
% as published by the Free Software Foundation. Further details on the GPLv3
% license can be found at http://www.gnu.org/copyleft/gpl.html.
%
% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE
% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY
% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF
% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY
% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE.
%
% For more information type "brainstorm license" at command prompt.
% =============================================================================@
%
% Authors: Francois Tadel, 2015

% Parse inputs
if (nargin < 3) || isempty(sfreq)
sfreq = [];
end
if (nargin < 2) || isempty(Value)
Value = [];
end
OutputFile = [];

% Ask for a variable in the workspace
if isempty(Value)
Value = in_matlab_var([], 'numeric');
if isempty(Value)
OutputFile = [];
return
end
end
% Build time vector
if (size(Value,2) == 1)
Time = 0;
elseif (size(Value,2) == 2)
Time = [0 1];
else
% Ask for the sampling frequency
if isempty(sfreq)
res = java_dialog('input', sprintf('Matrix size: [%d signals x %d samples].\nEnter the sampling frequency of the signal:\n\n', size(Value,1), size(Value,2)), 'Import data matrix', [], '1000');
if isempty(res) || isempty(str2num(res)) || (str2num(res) < 0)
return;
end
sfreq = str2num(res);
end
% Create time vector
Time = (0:(size(Value,2)-1)) ./ sfreq;
end

% Create a "matrix" structure
sMat = db_template('matrixmat');
sMat.Value = Value;
sMat.Time = Time;
sMat.Comment = sprintf('Imported matrix [%dx%d]', size(Value,1), size(Value,2));
sMat.Description = Description;
% Add history entry
sMat = bst_history('add', sMat, 'process', 'Imported matrix');

% Add structure to database
OutputFile = db_add(iStudy, sMat);

end
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