% EEG_GETDATACT - get EEG data from a specified dataset or
% component activity
%
% Usage:
% >> signal = eeg_getdatact( EEG );
% >> signal = eeg_getdatact( EEG, 'key', 'val');
%
% Inputs:
% EEG - Input dataset
%
% Optional input:
% 'channel' - [integer array] read only specific channels.
% Default is to read all data channels.
% 'component' - [integer array] read only specific components
% 'projchan' - [integer or cell array] channel(s) onto which the component
% should be projected.
% 'rmcomps' - [integer array] remove selected components from data
% channels. This is only to be used with channel data not
% when selecting components.
% 'trialindices' - [integer array] only read specific trials. Default is
% to read all trials.
% 'samples' - [integer array] only read specific samples. Default is
% to read all samples.
% 'reshape' - ['2d'|'3d'] reshape data. Default is '3d' when possible.
% 'verbose' - ['on'|'off'] verbose mode. Default is 'on'.
%
% Outputs:
% signal - EEG data or component activity
%
% Author: Arnaud Delorme, SCCN & CERCO, CNRS, 2008-
%
% See also: EEG_CHECKSET
% Copyright (C) 15 Feb 2002 Arnaud Delorme, Salk Institute, arno@salk.edu
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
%
% 1. Redistributions of source code must retain the above copyright notice,
% this list of conditions and the following disclaimer.
%
% 2. Redistributions in binary form must reproduce the above copyright notice,
% this list of conditions and the following disclaimer in the documentation
% and/or other materials provided with the distribution.
%
% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
% AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
% IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
% ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
% LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
% CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
% SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
% INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
% CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
% ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
% THE POSSIBILITY OF SUCH DAMAGE.
function [data, boundaries] = eeg_getdatact( EEG, varargin)
data = [];
if nargin < 1
help eeg_getdatact;
return;
end
% reading data from several datasets and concatenating it
% -------------------------------------------------------
if iscell(EEG) || (~ischar(EEG) && length(EEG) > 1)
% decode some arguments
% ---------------------
trials = cell(1,length(EEG));
rmcomps = cell(1,length(EEG));
for iArg = length(varargin)-1:-2:1
if strcmpi(varargin{iArg}, 'trialindices')
trials = varargin{iArg+1};
varargin(iArg:iArg+1) = [];
elseif strcmpi(varargin{iArg}, 'rmcomps')
rmcomps = varargin{iArg+1};
varargin(iArg:iArg+1) = [];
end
end
if isnumeric(rmcomps), rmtmp = rmcomps; rmcomps = cell(1,length(EEG)); rmcomps(:) = { rmtmp }; end
% concatenate datasets
% --------------------
data = [];
boundaries = [];
for dat = 1:length(EEG)
if iscell(EEG)
[tmpdata, datboundaries] = eeg_getdatact(EEG{dat}, 'trialindices', trials{dat}, 'rmcomps', rmcomps{dat}, varargin{:} );
else [tmpdata, datboundaries] = eeg_getdatact(EEG(dat), 'trialindices', trials{dat}, 'rmcomps', rmcomps{dat}, varargin{:} );
end
if isempty(data)
data = tmpdata;
boundaries = datboundaries;
else
if (isstruct(EEG) && all([EEG.trials] == 1)) || size(tmpdata,3) == 1 || size(data,2) ~= size(tmpdata,2) % continuous data (if same number of data points, consider 1 trial dataset)
if size(tmpdata,3) ~= 1 || size(data,3) ~= 1, error('Trying to concatenate continuous and epoched datasets'); end
if size(data,1) ~= size(tmpdata,1), error('Datasets to be concatenated do not have the same number of channels'); end
% adding boundaries
if ~isempty(datboundaries)
boundaries = [boundaries datboundaries size(data,2)];
else
boundaries = [boundaries size(data,2)];
end
data(:,end+1:end+size(tmpdata,2)) = tmpdata; % concatenating trials
else
if size(data,1) ~= size(tmpdata,1), error('Datasets to be concatenated do not have the same number of channels'); end
if size(data,2) ~= size(tmpdata,2), error('Datasets to be concatenated do not have the same number of time points'); end
data(:,:,end+1:end+size(tmpdata,3)) = tmpdata; % concatenating trials
end
end
end
return;
end
% if string load dataset
% ----------------------
if ischar(EEG)
EEG = pop_loadset('filename', EEG, 'loadmode', 'info');
end
opt = finputcheck(varargin, { ...
'channel' 'integer' {} [];
'verbose' 'string' { 'on','off' } 'on';
'reshape' 'string' { '2d','3d' } '3d';
'projchan' {'integer','cell' } { {} {} } [];
'component' 'integer' {} [];
'samples' 'integer' {} [];
'interp' 'struct' { } struct([]);
'trialindices' {'integer','cell'} { {} {} } [];
'rmcomps' {'integer','cell'} { {} {} } [] }, 'eeg_getdatact');
if ischar(opt), error(opt); end
channelNotDefined = 0;
if isempty(opt.channel)
opt.channel = [1:EEG.nbchan];
channelNotDefined = 1;
elseif isequal(opt.channel, [1:EEG.nbchan]) && ~isempty(opt.interp)
channelNotDefined = 1;
end
if iscell( opt.trialindices), opt.trialindices = opt.trialindices{1}; end
if isempty(opt.trialindices), opt.trialindices = [1:EEG.trials]; end
if iscell(opt.rmcomps ), opt.rmcomps = opt.rmcomps{1}; end
if (~isempty(opt.rmcomps) || ~isempty(opt.component)) && isempty(EEG.icaweights)
error('No ICA weight in dataset');
end
if strcmpi(EEG.data, 'in set file')
EEGTMP = pop_loadset('filename', EEG.filename, 'filepath', EEG.filepath, 'verbose', 'off');
EEG.data = EEGTMP.data;
end
% get data boundaries if continuous data
% --------------------------------------
boundaries = [];
if nargout > 1 && EEG.trials == 1 && ~isempty(EEG.event) && isfield(EEG.event, 'type') && ischar(EEG.event(1).type)
if ~isempty(opt.samples)
disp('WARNING: eeg_getdatact.m, boundaries are not accurate when selecting data samples');
end
tmpevent = EEG.event;
tmpbound = strmatch('boundary', lower({ tmpevent.type }));
if ~isempty(tmpbound)
boundaries = [tmpevent(tmpbound).latency ]-0.5;
end
end
% getting channel or component activation
% ---------------------------------------
filename = fullfile(EEG.filepath, [ EEG.filename(1:end-4) '.icaact' ] );
if ~isempty(opt.component) && ~isempty(EEG.icaact)
data = EEG.icaact(opt.component,:,:);
elseif ~isempty(opt.component) && exist(filename)
% reading ICA file
% ----------------
data = repmat(single(0), [ length(opt.component) EEG.pnts EEG.trials ]);
fid = fopen( filename, 'r', 'ieee-le'); %little endian (see also pop_saveset)
if fid == -1, error( ['file ' filename ' could not be open' ]); end
for ind = 1:length(opt.component)
fseek(fid, (opt.component(ind)-1)*EEG.pnts*EEG.trials*4, -1);
data(ind,:) = fread(fid, [EEG.trials*EEG.pnts 1], 'float32')';
end
fclose(fid);
elseif ~isempty(opt.component)
if isempty(EEG.icaact)
data = eeg_getdatact( EEG );
data = (EEG.icaweights(opt.component,:)*EEG.icasphere)*data(EEG.icachansind,:);
else
data = EEG.icaact(opt.component,:,:);
end
else
if isnumeric(EEG.data) % channel
data = EEG.data;
else % channel but no data loaded string
[~,EEG.data,ext] = fileparts(EEG.data); % remove path if present
EEG.data = [ EEG.data ext];
filename = fullfile(EEG.filepath, EEG.data);
fid = fopen( filename, 'r', 'ieee-le'); %little endian (see also pop_saveset)
if fid == -1
filename = fullfile(EEG.data);
fid = fopen( filename, 'r', 'ieee-le'); %little endian (see also pop_saveset)
if fid == -1
filename = fullfile(EEG.filepath, [EEG.filename(1:end-3) 'fdt' ]);
fid = fopen( filename, 'r', 'ieee-le'); %little endian (see also pop_saveset)
if fid == -1
error( ['file ' filename ' not found. If you have renamed/moved' 10 ...
'the .set file, you must also rename/move the associated data file.' ]);
end
end
end
if strcmpi(opt.verbose, 'on')
fprintf('Reading float file ''%s''...\n', filename);
end
% old format = .fdt; new format = .dat (transposed)
% -------------------------------------------------
datformat = 0;
if length(filename) > 3
if strcmpi(filename(end-2:end), 'dat')
datformat = 1;
end
end
EEG.datfile = EEG.data;
% reading data file
% -----------------
eeglab_options;
if length(opt.channel) == EEG.nbchan && option_memmapdata
fclose(fid);
data = mmo(filename, [EEG.nbchan EEG.pnts EEG.trials], false);
%data = memmapdata(filename, [EEG.nbchan EEG.pnts EEG.trials]);
else
if datformat
if length(opt.channel) == EEG.nbchan || ~isempty(opt.interp)
data = fread(fid, [EEG.trials*EEG.pnts EEG.nbchan], 'float32')';
else
data = repmat(single(0), [ length(opt.channel) EEG.pnts EEG.trials ]);
for ind = 1:length(opt.channel)
fseek(fid, (opt.channel(ind)-1)*EEG.pnts*EEG.trials*4, -1);
data(ind,:) = fread(fid, [EEG.trials*EEG.pnts 1], 'float32')';
end
opt.channel = [1:size(data,1)];
end
else
data = fread(fid, [EEG.nbchan Inf], 'float32');
end
fclose(fid);
end
end
% subtracting components from data
% --------------------------------
if ~isempty(opt.rmcomps)
if strcmpi(opt.verbose, 'on')
fprintf('Removing %d artifactual components\n', length(opt.rmcomps));
end
rmcomps = eeg_getdatact( EEG, 'component', opt.rmcomps); % loaded from file
rmchan = [];
rmchanica = [];
for index = 1:length(opt.channel)
tmpicaind = find(opt.channel(index) == EEG.icachansind);
if ~isempty(tmpicaind)
rmchan = [ rmchan index ];
rmchanica = [ rmchanica tmpicaind ];
end
end
data(rmchan,:) = data(rmchan,:) - EEG.icawinv(rmchanica,opt.rmcomps)*rmcomps(:,:);
%EEG = eeg_checkset(EEG, 'loaddata');
%EEG = pop_subcomp(EEG, opt.rmcomps);
%data = EEG.data(opt.channel,:,:);
%if strcmpi(EEG.subject, 'julien') & strcmpi(EEG.condition, 'oddball') & strcmpi(EEG.group, 'after')
% jjjjf
%end
end
if ~isempty(opt.interp)
EEG.data = data;
EEG.event = [];
EEG.epoch = [];
EEG = eeg_interp(EEG, opt.interp, 'spherical');
data = EEG.data;
if channelNotDefined, opt.channel = [1:EEG.nbchan]; end
end
if ~isequal(opt.channel, [1:EEG.nbchan])
data = data(intersect(opt.channel,[1:EEG.nbchan]),:,:);
end
end
% projecting components on data channels
% --------------------------------------
if ~isempty(opt.projchan)
if iscell(opt.projchan)
opt.projchan = std_chaninds(EEG, opt.projchan);
end
finalChanInds = [];
for iChan = 1:length(opt.projchan)
tmpInd = find(EEG.icachansind == opt.projchan(iChan));
if isempty(tmpInd)
error(sprintf('Warning: can not backproject component on channel %d (not used for ICA)\n', opt.projchan(iChan)));
end
finalChanInds = [ finalChanInds tmpInd ];
end
data = EEG.icawinv(finalChanInds, opt.component)*data(:,:);
end
if size(data,2)*size(data,3) ~= EEG.pnts*EEG.trials
disp('WARNING: The file size on disk does not correspond to the dataset, file has been truncated');
end
try
if EEG.trials == 1, EEG.pnts = size(data,2); end
if strcmpi(opt.reshape, '3d')
data = reshape(data, size(data,1), EEG.pnts, EEG.trials);
else data = reshape(data, size(data,1), EEG.pnts*EEG.trials);
end
catch
error('The file size on disk does not correspond to the dataset information.');
end
% select trials
% -------------
if length(opt.trialindices) ~= EEG.trials
data = data(:,:,opt.trialindices);
end
if ~isempty(opt.samples)
data = data(:,opt.samples,:);
end
Datasets
Models
