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besa2fieldtrip.m
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Thu, Mar 13, 07:14

besa2fieldtrip.m
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function data = besa2fieldtrip(input)
% BESA2FIELDTRIP reads and converts various BESA datafiles into a FieldTrip
% data structure, which subsequently can be used for statistical analysis
% or other analysis methods implemented in Fieldtrip.
%
% Use as
% [data] = besa2fieldtrip(filename)
% where the filename should point to a BESA datafile (or data that
% was exported by BESA). The output is a MATLAB structure that is
% compatible with FieldTrip.
%
% The format of the output structure depends on the type of datafile:
% *.avr is converted to a structure similar to the output of FT_TIMELOCKANALYSIS
% *.mul is converted to a structure similar to the output of FT_TIMELOCKANALYSIS
% *.swf is converted to a structure similar to the output of FT_TIMELOCKANALYSIS (*)
% *.tfc is converted to a structure similar to the output of FT_FREQANALYSIS (*)
% *.dat is converted to a structure similar to the output of FT_SOURCANALYSIS
% *.dat combined with a *.gen or *.generic is converted to a structure similar to the output of FT_PREPROCESSING
%
% Note (*): If the BESA toolbox by Karsten Hochstatter is found on your
% MATLAB path, the readBESAxxx functions will be used (where xxx=tfc/swf),
% alternatively the private functions from FieldTrip will be used.
%
% See also EEGLAB2FIELDTRIP, SPM2FIELDTRIP
% Copyright (C) 2005-2010, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.
%
% FieldTrip is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% FieldTrip is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with FieldTrip. If not, see <http://www.gnu.org/licenses/>.
%
% $Id$
% these are used by the ft_preamble/ft_postamble function and scripts
ft_revision = '$Id$';
ft_nargin = nargin;
ft_nargout = nargout;
% do the general setup of the function
ft_defaults
ft_preamble callinfo
if isstruct(input) && numel(input)>1
% use a recursive call to convert multiple inputs
data = cell(size(input));
for i=1:numel(input)
data{i} = besa2fieldtrip(input(i));
end
return
end
if isstruct(input)
fprintf('besa2fieldtrip: converting structure\n');
%---------------------TFC-------------------------------------------------%
if strcmp(input.structtype, 'besa_tfc')
%fprintf('BESA tfc\n');
data.time = input.latencies;
data.freq = input.frequencies;
temp_chans = char(input.channellabels');
Nchan = size(temp_chans,1);
%{
if strcmp(input.type, 'COHERENCE_SQUARED')
% it contains coherence between channel pairs
fprintf('reading coherence between %d channel pairs\n', Nchan);
for i=1:Nchan
tmp = tokenize(deblank(temp_chans(i,:)), '-');
data.labelcmb{i,1} = deblank(tmp{1});
data.labelcmb{i,2} = deblank(tmp{2});
data.label{i,1} = deblank(temp_chans(i,:));
end
data.cohspctrm = input.data;
else
%}
% it contains power on channels
fprintf('reading power on %d channels\n', Nchan);
for i=1:Nchan
data.label{i,1} = deblank(temp_chans(i,:));
end
data.powspctrm = input.data;
data.dimord = 'chan_freq_time';
data.condition = input.condition; %not original Fieldtrip fieldname
%end
clear temp;
%--------------------Image------------------------------------------------%
elseif strcmp(input.structtype, 'besa_image')
%fprintf('BESA image\n');
data.avg.pow = input.data;
xTemp = input.xcoordinates;
yTemp = input.ycoordinates;
zTemp = input.zcoordinates;
data.xgrid = xTemp;
data.ygrid = yTemp;
data.zgrid = zTemp;
nx = size(data.xgrid,2);
ny = size(data.ygrid,2);
nz = size(data.zgrid,2);
% Number of points in each dimension
data.dim = [nx ny nz];
% Array with all possible positions (x,y,z)
data.pos = WritePosArray(xTemp,yTemp,zTemp,nx,ny,nz);
data.inside = 1:prod(data.dim);%as in Fieldtrip - not correct
data.outside = [];
%--------------------Source Waveform--------------------------------------%
elseif strcmp(input.structtype, 'besa_sourcewaveforms')
%fprintf('BESA source waveforms\n');
data.label = input.labels'; %not the same as Fieldtrip!
data.dimord = 'chan_time';
data.fsample = input.samplingrate;
data.time = input.latencies / 1000.0;
data.avg = input.waveforms';
data.cfg.filename = input.datafile;
%--------------------Data Export------------------------------------------%
elseif strcmp(input.structtype, 'besa_channels')
%fprintf('BESA data export\n');
if isfield(input, 'datatype')
switch input.ft_datatype
case {'Raw_Data', 'Epoched_Data', 'Segment'}
data.fsample = input.samplingrate;
data.label = input.channellabels';
for k=1:size(input.data,2)
data.time{1,k} = input.data(k).latencies / 1000.0';
data.trial{1,k} = input.data(k).amplitudes';
end
otherwise
fprintf('ft_datatype other than Raw_Data, Epoched or Segment');
end
else
fprintf('workspace created with earlier MATLAB version');
end
%--------------------else-------------------------------------------------%
else
ft_error('unrecognized format of the input structure');
end
elseif ischar(input)
fprintf('besa2fieldtrip: reading from file\n');
% This function can either use the reading functions included in FieldTrip
% (with contributions from Karsten, Vladimir and Robert), or the official
% released functions by Karsten Hoechstetter from BESA. The functions in the
% official toolbox have precedence.
hasbesa = ft_hastoolbox('besa',1, 1);
type = ft_filetype(input);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if strcmp(type, 'besa_avr') && hasbesa
fprintf('reading ERP/ERF\n');
% this should be similar to the output of TIMELOCKANALYSIS
tmp = readBESAavr(input);
% convert into a TIMELOCKANALYSIS compatible data structure
data = [];
data.label = [];
if isfield(tmp, 'ChannelLabels')
data.label = fixlabels(tmp.ChannelLabels);
end
data.avg = tmp.Data;
data.time = tmp.Time / 1000; % convert to seconds
data.fsample = 1000/tmp.DI;
data.dimord = 'chan_time';
elseif strcmp(type, 'besa_avr') && ~hasbesa
fprintf('reading ERP/ERF\n');
% this should be similar to the output of TIMELOCKANALYSIS
tmp = read_besa_avr(input);
% convert into a TIMELOCKANALYSIS compatible data structure
data = [];
data.label = fixlabels(tmp.label);
data.avg = tmp.data;
data.time = (0:(tmp.npnt-1)) * tmp.di + tmp.tsb;
data.time = data.time / 1000; % convert to seconds
data.fsample = 1000/tmp.di;
data.dimord = 'chan_time';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
elseif strcmp(type, 'besa_mul') && hasbesa
fprintf('reading ERP/ERF\n');
% this should be similar to the output of TIMELOCKANALYSIS
tmp = readBESAmul(input);
% convert into a TIMELOCKANALYSIS compatible data structure
data = [];
data.label = tmp.ChannelLabels(:);
data.avg = tmp.data';
data.time = (0:(tmp.Npts-1)) * tmp.DI + tmp.TSB;
data.time = data.time / 1000; %convert to seconds
data.fsample = 1000/tmp.DI;
data.dimord = 'chan_time';
elseif strcmp(type, 'besa_mul') && ~hasbesa
fprintf('reading ERP/ERF\n');
% this should be similar to the output of TIMELOCKANALYSIS
tmp = read_besa_mul(input);
% convert into a TIMELOCKANALYSIS compatible data structure
data = [];
data.label = tmp.label(:);
data.avg = tmp.data;
data.time = (0:(tmp.TimePoints-1)) * tmp.SamplingInterval_ms_ + tmp.BeginSweep_ms_;
data.time = data.time / 1000; % convert to seconds
data.fsample = 1000/tmp.SamplingInterval_ms_;
data.dimord = 'chan_time';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
elseif strcmp(type, 'besa_sb')
if hasbesa
fprintf('reading preprocessed channel data using BESA toolbox\n');
else
ft_error('this data format requires the BESA toolbox');
end
[p, f, x] = fileparts(input);
input = fullfile(p, [f '.dat']);
[time,buf,ntrial] = readBESAsb(input);
time = time/1000; % convert from ms to sec
nchan = size(buf,1);
ntime = size(buf,3);
% convert into a PREPROCESSING compatible data structure
data = [];
data.trial = {};
data.time = {};
for i=1:ntrial
data.trial{i} = reshape(buf(:,i,:), [nchan, ntime]);
data.time{i} = time;
end
data.label = {};
for i=1:size(buf,1)
data.label{i,1} = sprintf('chan%03d', i);
end
data.fsample = 1./mean(diff(time)); % time is already in seconds
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
elseif strcmp(type, 'besa_tfc') && hasbesa
fprintf('reading time-frequency representation using BESA toolbox\n');
% this should be similar to the output of FREQANALYSIS
tfc = readBESAtfc(input);
Nchan = size(tfc.ChannelLabels,1);
% convert into a FREQANALYSIS compatible data structure
data = [];
data.time = tfc.Time(:)';
data.freq = tfc.Frequency(:)';
if isfield(tfc, 'DataType') && strcmp(tfc.DataType, 'COHERENCE_SQUARED')
% it contains coherence between channel pairs
fprintf('reading coherence between %d channel pairs\n', Nchan);
for i=1:Nchan
tmp = tokenize(deblank(tfc.ChannelLabels(i,:)), '-');
data.labelcmb{i,1} = tmp{1};
data.labelcmb{i,2} = tmp{2};
end
data.cohspctrm = permute(tfc.Data, [1 3 2]);
else
% it contains power on channels
fprintf('reading power on %d channels\n', Nchan);
for i=1:Nchan
data.label{i,1} = deblank(tfc.ChannelLabels(i,:));
end
data.powspctrm = permute(tfc.Data, [1 3 2]);
end
data.dimord = 'chan_freq_time';
data.condition = tfc.ConditionName;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
elseif strcmp(type, 'besa_tfc') && ~hasbesa
fprintf('reading time-frequency representation\n');
% this should be similar to the output of FREQANALYSIS
[ChannelLabels, Time, Frequency, Data, Info] = read_besa_tfc(input);
Nchan = size(ChannelLabels,1);
% convert into a FREQANALYSIS compatible data structure
data = [];
data.time = Time * 1e-3; % convert to seconds;
data.freq = Frequency;
if isfield(Info, 'DataType') && strcmp(Info.DataType, 'COHERENCE_SQUARED')
% it contains coherence between channel pairs
fprintf('reading coherence between %d channel pairs\n', Nchan);
for i=1:Nchan
tmp = tokenize(deblank(ChannelLabels(i,:)), '-');
data.labelcmb{i,1} = tmp{1};
data.labelcmb{i,2} = tmp{2};
end
data.cohspctrm = permute(Data, [1 3 2]);
else
% it contains power on channels
fprintf('reading power on %d channels\n', Nchan);
for i=1:Nchan
data.label{i} = deblank(ChannelLabels(i,:));
end
data.powspctrm = permute(Data, [1 3 2]);
end
data.dimord = 'chan_freq_time';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
elseif strcmp(type, 'besa_swf') && hasbesa
fprintf('reading source waveform using BESA toolbox\n');
swf = readBESAswf(input);
% convert into a TIMELOCKANALYSIS compatible data structure
data = [];
data.label = fixlabels(swf.waveName);
data.avg = swf.data;
data.time = swf.Time * 1e-3; % convert to seconds
data.fsample = 1/mean(diff(data.time));
data.dimord = 'chan_time';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
elseif strcmp(type, 'besa_swf') && ~hasbesa
fprintf('reading source waveform\n');
% hmm, I guess that this should be similar to the output of TIMELOCKANALYSIS
tmp = read_besa_swf(input);
% convert into a TIMELOCKANALYSIS compatible data structure
data = [];
data.label = fixlabels(tmp.label);
data.avg = tmp.data;
data.time = (0:(tmp.npnt-1)) * tmp.di + tmp.tsb;
data.time = data.time / 1000; % convert to seconds
data.fsample = 1000/tmp.di;
data.dimord = 'chan_time';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
elseif strcmp(type, 'besa_src') && hasbesa
src = readBESAimage(input);
data.xgrid = src.Coordinates.X;
data.ygrid = src.Coordinates.Y;
data.zgrid = src.Coordinates.Z;
data.avg.pow = src.Data;
data.dim = size(src.Data);
[X, Y, Z] = ndgrid(data.xgrid, data.ygrid, data.zgrid);
data.pos = [X(:) Y(:) Z(:)];
% cannot determine which voxels are inside the brain volume
data.inside = 1:prod(data.dim);
data.outside = [];
elseif strcmp(type, 'besa_src') && ~hasbesa
src = read_besa_src(input);
data.xgrid = linspace(src.X(1), src.X(2), src.X(3));
data.ygrid = linspace(src.Y(1), src.Y(2), src.Y(3));
data.zgrid = linspace(src.Z(1), src.Z(2), src.Z(3));
data.avg.pow = src.vol;
data.dim = size(src.vol);
[X, Y, Z] = ndgrid(data.xgrid, data.ygrid, data.zgrid);
data.pos = [X(:) Y(:) Z(:)];
% cannot determine which voxels are inside the brain volume
data.inside = 1:prod(data.dim);
data.outside = [];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
elseif strcmp(type, 'besa_pdg')
% hmmm, I have to think about this one...
ft_error('sorry, pdg is not yet supported');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
else
ft_error('unrecognized file format for importing BESA data');
end
end % isstruct || ischar
% construct and add a configuration to the output
cfg = [];
if isstruct(input) && isfield(input, 'datafile')
cfg.filename = input.datafile;
elseif isstruct(input) && ~isfield(input, 'datafile')
cfg.filename = 'Unknown';
elseif ischar(input)
cfg.filename = input;
end
% do the general cleanup and bookkeeping at the end of the function
ft_postamble callinfo
ft_postamble history data
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that fixes the channel labels, should be a cell-array
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [newlabels] = fixlabels(labels)
if iscell(labels) && length(labels)>1
% seems to be ok
newlabels = labels;
elseif iscell(labels) && length(labels)==1
% could be a cell with a single long string in it
if length(tokenize(labels{1}, ' '))>1
% seems like a long string that accidentaly ended up in a single
cell
newlabels = tokenize(labels{1}, ' ');
else
% seems to be ok
newlabels = labels;
end
elseif ischar(labels) && any(size(labels)==1)
newlabels = tokenize(labels(:)', ' '); % also ensure that it is a row-string
elseif ischar(labels) && ~any(size(labels)==1)
for i=1:size(labels)
newlabels{i} = strtrim(labels(i,:));
end
end
% convert to column
newlabels = newlabels(:);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [PArray] = WritePosArray(x,y,z,mx,my,mz)
A1 = repmat(x,1,my*mz);
A21 = repmat(y,mx,mz);
A2 = reshape(A21,1,mx*my*mz);
A31 = repmat(z,mx*my,1);
A3 = reshape(A31,1,mx*my*mz);
PArray = [A1;A2;A3]';

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