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Slepi/Code/Utilities/spm12/spm_eeg_reduce.m
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spm_eeg_reduce.m
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function D = spm_eeg_reduce(S)
% Apply data reduction to M/EEG dataset
% FORMAT D = spm_eeg_reduce(S)
% S - input structure
%
% fields of S:
% S.D - MEEG object or filename of M/EEG mat-file with
%
% S.channels - cell array of channel names. Can include generic
% wildcards: 'All', 'EEG', 'MEG' etc
% S.conditions - cell array of condition trial names.
% S.method - name for the spectral estimation to use. This
% corresponds to the name of a plug-in function that comes
% after 'spm_eeg_reduce_' prefix.
% S.keepothers - keep the other (not involved) channels
% S.settings - plug-in specific settings
% S.timewin - time windows or interest
% S.prefix - prefix for the output file (default - 'R')
%
% Output:
% D - M/EEG object
%__________________________________________________________________________
% Copyright (C) 2012 Wellcome Trust Centre for Neuroimaging
% Vladimir Litvak
% $Id: spm_eeg_reduce.m 6252 2014-10-30 16:06:30Z vladimir $
SVNrev = '$Rev: 6252 $';
%-Startup
%--------------------------------------------------------------------------
spm('FnBanner', mfilename, SVNrev);
spm('FigName','M/EEG reduce'); spm('Pointer','Watch');
%-Configure the analysis
%--------------------------------------------------------------------------
if ~isfield(S, 'channels'), S.channels = 'all'; end
if ~isfield(S, 'conditions'), S.conditions.all = 1; end
if ~isfield(S, 'timewin'), S.timewin = [-Inf Inf]; end
if ~isfield(S, 'keepothers'), S.keepothers = true; end
if ~isfield(S, 'prefix'), S.prefix = 'R'; end
D = spm_eeg_load(S.D);
badind = D.badchannels;
chanind = setdiff(D.selectchannels(S.channels), badind);
% if isempty(chanind)
% error('No channels selected.');
% end
%%%%%%%%%
% MWW
samples = {};
for i = 1:size(S.timewin, 1)
samples{i} = D.indsample(S.timewin(i, 1)):D.indsample(S.timewin(i, 2));
end
if isfield(S.conditions, 'all')
trials = 1:D.ntrials;
else
trials = D.indtrial(S.conditions, 'GOOD');
if isempty(trials)
error('No trials matched the selection, check the specified condition labels');
end
end
%%%%%%%%%%
if ~isfield(S, 'method')
S.method = 'pca';
S.settings.ncomp = min(length(floor(chanind)/2), 100);
end
if isfield(S, 'settings')
S1 = S.settings;
else
S1 = [];
end
S1.D = D;
S1.chanind = chanind;
S1.trials = trials;
S1.samples = samples;
montage = feval(['spm_eeg_reduce_' S.method], S1);
% This is to discard bad channels but keep other channels (like non MEEG).
if ~isempty(badind)
montage.labelorg = [montage.labelorg(:); D.chanlabels(badind)']; % added semicolon - MWW
montage.tra(end, end+length(badind)) = 0;
if isfield(montage, 'chantypeorg')
montage.chantypeorg = [montage.chantypeorg(:); lower(D.chantype(badind))'];
end
if isfield(montage, 'chanunitorg')
montage.chanunitorg = [montage.chanunitorg(:); D.units(badind)'];
end
end
S1 = [];
S1.D = D;
S1.montage = montage;
S1.keepothers = S.keepothers;
S1.prefix = S.prefix;
S1.updatehistory = 0;
D = spm_eeg_montage(S1);
D = chantype(D, 1:length(montage.labelnew), montage.chantypenew);
%-Save new M/EEG dataset(s)
%--------------------------------------------------------------------------
D = D.history('spm_eeg_reduce', S);
save(D);
%-Cleanup
%--------------------------------------------------------------------------
spm('FigName','M/EEG reduce: done'); spm('Pointer','Arrow');
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