% NEWTIMEFBASELN - Remove baseline power values for newtimef. This
% function assumes absolute power NOT log transformed power.
% This function only removes baseline. Data has to be
% averaged subsequently if necessary. This function
% works both for single trial data and for average data.
%
% Usage:
% >> [P,basesamples,basevals] = newtimefbaseln(P, tvals, baseline, 'key', val);
%
% Inputs:
% P - [3-D or 4-D array] Power array [freqs x times x trials] or
% [channels x freqs x times x trials
% tvals - [array] time values
% baseline - [] same format as for newtimef
%
% Optional inputs: 'powbase', 'basenorm', 'commonbase', 'verbose'
% and 'trialbase'. Same definition as for newtimef.
%
% Outputs:
% P - Baseline correct power (same size as input)
% baseln - Baseline sample time indices
% mbase - Baseline value
%
% Authors: Arnaud Delorme, SCCN, INC, UCSD, August 2016
% Copyright (C) Arnaud Delorme, SCCN, INC, UCSD, 2016, arno@sccn.ucsd.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 [PP, baseln, mbase] = newtimefbaseln(PPori, timesout, varargin)
if nargin < 3
help newtimefbaseln;
return;
end
[ g, timefreqopts ] = finputcheck(varargin, ...
{'powbase' 'real' [] NaN;
'basenorm' 'string' {'on','off'} 'off';
'baseline' 'real' [] 0;
'commonbase' 'string' {'on','off'} 'off';
'singletrials' 'string' {'on','off'} 'on';
'trialbase', 'string', {'on', 'off', 'full'}, 'off';
'verbose', 'string', {'on', 'off'}, 'on';
}, 'newtimefbaseln', 'ignore');
if ischar(g)
error(g);
return;
end
PP = PPori; if ~iscell(PP), PP = { PP }; end
% ---------------
% baseline length
% ---------------
if size(g.baseline,2) == 2
baseln = [];
for index = 1:size(g.baseline,1)
tmptime = find(timesout >= g.baseline(index,1) & timesout <= g.baseline(index,2));
baseln = union_bc(baseln, tmptime);
end
if isempty(baseln)
error( [ 'There are no sample points found in the default baseline.' 10 ...
'This may happen even though data time limits overlap with' 10 ...
'the baseline period (because of the time-freq. window width).' 10 ...
'Either disable the baseline, change the baseline limits.' ] );
end
else
if ~isempty(find(timesout < g.baseline))
baseln = find(timesout < g.baseline); % subtract means of pre-0 (centered) windows
else baseln = 1:length(timesout); % use all times as baseline
end
end
allMbase = cell(size(PP));
allPmean = cell(size(PP));
for ind = 1:length(PP(:))
P = PP{ind};
% -----------------------
% compute baseline values
% -----------------------
if isnan(g.powbase(1))
verboseprintf(g.verbose, 'Computing the mean baseline spectrum\n');
if strcmpi(g.singletrials, 'on') && strcmpi(g.trialbase, 'off')
if ndims(P) == 4, Pmean = mean(P, 4); % average power over trials (channels x freq x time x trials)
else Pmean = mean(P, 3); % average power over trials (freq x time x trials)
end
else
Pmean = P;
end
mbase = mean(Pmean(:,baseln,:,:),2);
mstd = std(Pmean(:,baseln,:,:),[],2);
else
verboseprintf(g.verbose, 'Using the input baseline spectrum\n');
mbase = g.powbase;
mstd = [];
if size(mbase,1) == 1 % if input was a row vector, flip to be a column
mbase = mbase';
end
end
PP{ind} = P;
baselength = length(baseln);
allMbase{ind} = mbase;
allMstd{ind} = mstd;
end
% ------------------------
% compute average baseline
% ------------------------
if strcmpi(g.commonbase, 'on')
meanBaseln = allMbase{1}/length(PP(:));
meanStd = allMstd{1}/length(PP(:));
for ind = 2:length(PP(:))
meanBaseln = meanBaseln + allMbase{ind}/length(PP(:));
meanStd = meanBaseln + allMstd{ ind}/length(PP(:));
end
for ind = 1:length(PP(:))
allMbase{ind} = meanBaseln;
allMstd{ind} = meanStd;
end
end
% -------------------------
% remove baseline (average)
% -------------------------
% original ERSP baseline removal
if ~strcmpi(g.trialbase, 'on') % full or off
for ind = 1:length(PP(:))
if ~isnan( g.baseline(1) ) && any(~isnan( allMbase{ind}(1) )) && strcmpi(g.basenorm, 'off')
PP{ind} = bsxfun(@rdivide, PP{ind}, allMbase{ind});
% PP{ind} = bsxfun(@rdivide, bsxfun(@minus, PP{ind}, allMbase{ind}), allMstd{ind});
% ERSP baseline normalized
elseif ~isnan( g.baseline(1) ) && ~isnan( allMbase{ind}(1) ) && strcmpi(g.basenorm, 'on')
PP{ind} = bsxfun(@rdivide, bsxfun(@minus, PP{ind}, allMbase{ind}), allMstd{ind});
end
end
end
for ind = 1:length(allMbase(:))
if ndims(allMbase{ind}) > 2
% The baseline is only used for plotting purposes
% It is different from version EEGLAB v14 (not to be used)
allMbase{ind} = mean(allMbase{ind},3);
end
end
mbase = allMbase;
if ~iscell(PPori)
PP = PP{1};
mbase = allMbase{1};
end
% print
function verboseprintf(verbose, varargin)
if strcmpi(verbose, 'on')
fprintf(varargin{:});
end
Datasets
Models
