% STD_PREPARE_NEIGHBORS - prepare Fieldtrip channel neighbor structure.
% Only prepare the structure if necessary based
% on statistical options in STUDY.etc.statistics.
% Use the 'force' option to force preparing the
% matrix.
%
% Usage:
% >> [STUDY neighbors] = std_prepare_neighbors( STUDY, ALLEEG, 'key', val)
%
% Inputs:
% STUDY - an EEGLAB STUDY set of loaded EEG structures
% ALLEEG - ALLEEG vector of one or more loaded EEG dataset structures
%
% Optional inputs:
% 'force' - ['on'|'off'] force generating the structure irrespective
% of the statistics options selected. Default is 'off'.
% 'channels' - [cell] list of channels to include in the matrix
% 'method' - [string] method for preparing. See ft_prepare_neighbors
% 'neighbordist' - [float] max distance. See ft_prepare_neighbors
%
% Note: other ft_prepare_neighbors fields such as template, layout may
% also be used as optional keywords.
%
% Outputs:
% STUDY - an EEGLAB STUDY set of loaded EEG structures
% neighbors - Fieldtrip channel neighbour structure
% limostruct - structure compatible with LIMO (need to be saved in a file)
%
% Author: Arnaud Delorme, SCCN, UCSD, 2012-
%
% See also: STATCONDFIELDTRIP
% Copyright (C) Arnaud Delorme
%
% 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 [STUDY neighbors limostruct] = std_prepare_neighbors(STUDY, ALLEEG, varargin);
neighbors = [];
if nargin < 2
return;
end
[opt addopts] = finputcheck( varargin, { 'force' 'string' { 'on','off' } 'off';
'channels' 'cell' {} {} }, 'std_stat', 'ignore');
if strcmpi(opt.force, 'on') || (strcmpi(STUDY.etc.statistics.fieldtrip.mcorrect, 'cluster') && ...
strcmpi(STUDY.etc.statistics.mode, 'fieldtrip') && (strcmpi(STUDY.etc.statistics.groupstats, 'on') || strcmpi(STUDY.etc.statistics.condstats, 'on')))
EEG = eeg_emptyset;
EEG.chanlocs = eeg_mergelocs(ALLEEG.chanlocs);
if isempty(EEG.chanlocs)
disp('std_prepare_neighbors: cannot prepare channel neighbour structure because of empty channel structures');
return;
end
if ~isempty(STUDY.etc.statistics.fieldtrip.channelneighbor) && isempty(addopts) && ...
length(STUDY.etc.statistics.fieldtrip.channelneighbor) == length(EEG.chanlocs)
disp('Using stored channel neighbour structure');
neighbors = STUDY.etc.statistics.fieldtrip.channelneighbor;
else
if ~isempty(opt.channels)
indChans = eeg_chaninds(EEG, opt.channels);
EEG.chanlocs = EEG.chanlocs(indChans);
end
EEG.nbchan = length(EEG.chanlocs);
EEG.data = zeros(EEG.nbchan,100,1);
EEG.trials = 1;
EEG.pnts = 100;
EEG.xmin = 0;
EEG.srate = 1;
EEG.xmax = 99;
EEG = eeg_checkset(EEG);
tmpcfg = eeglab2fieldtrip(EEG, 'preprocessing', 'none');
% call the function that find channel neighbors
% ---------------------------------------------
addparams = eval( [ '{' STUDY.etc.statistics.fieldtrip.channelneighborparam '}' ]);
for index = 1:2:length(addparams)
tmpcfg = setfield(tmpcfg, addparams{index}, addparams{index+1});
end
for index = 1:2:length(addopts)
tmpcfg = setfield(tmpcfg, addopts{index}, addopts{index+1});
end
warning off;
if isfield(EEG.chanlocs, 'theta') && ~isempty(EEG.chanlocs(1).theta)
tmpcfg = rmfield(tmpcfg, 'cfg');
tmpcfg2 = tmpcfg;
tmpcfg = rmfield(tmpcfg, 'label'); % first input must not be data
tmpcfg2 = rmfield(tmpcfg2, 'method'); % second input must not be method
if isfield(tmpcfg, 'trialinfo')
tmpcfg = rmfield(tmpcfg, 'trialinfo'); % first input must not be data
end
% tmpcfg = rmfield(tmpcfg, 'label');
% --> removing label seems to make ft_prepare_neighbours to crash
cfg.neighbors = ft_prepare_neighbours(tmpcfg, tmpcfg2);
neighbors = cfg.neighbors;
else
neighbors = [];
end
warning on;
end
STUDY.etc.statistics.fieldtrip.channelneighbor = neighbors;
if nargout > 2
limostruct.expected_chanlocs = EEG.chanlocs;
if ~isempty(neighbors)
allLabels = { neighbors.label };
limostruct.channeighbstructmat = zeros(length(EEG.chanlocs));
for iN = 1:length(neighbors)
if ~isequal(neighbors(iN).label, limostruct.expected_chanlocs(iN).labels)
error('Wrong label');
else
[tmp posChan] = intersect( allLabels, neighbors(iN).neighblabel);
limostruct.channeighbstructmat(iN,posChan) = 1;
limostruct.channeighbstructmat(posChan,iN) = 1;
end
end
else
limostruct.channeighbstructmat = ones(length(EEG.chanlocs));
end
end
end
Datasets
Models
