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 * fixed SVN properties (http://www.fil.ion.ucl.ac.uk/spm/local/svn/devel.html#tsvn)
 * replaced tabs by 4 space characters
 * unified help section

SVN r1131
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@SPMcentral
SPMcentral committed Feb 6, 2008
1 parent a6fe436 commit 5e612c4
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26 changes: 13 additions & 13 deletions Contents.m
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Expand Up @@ -27,7 +27,7 @@
%_______________________________________________________________________
% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience

% $Id: Contents.m 123 2005-05-06 12:15:13Z john $
% $Id: Contents.m 1131 2008-02-06 11:17:09Z spm $

%=======================================================================
% PROGRAMMERS NOTE:
Expand All @@ -41,7 +41,7 @@
%=======================================================================
%%% Extract LastRevision number from 'Id' tag in SPM files
% mext = {'.m','.c','.h','.man','.xml', ... %- source code
% '.dll','.mexmac','.mexsol','.mexglx'}; %- MEX
% '.dll','.mexmac','.mexsol','.mexglx'}; %- MEX
% spmdir = spm('Dir');
% d = dir(fullfile(spmdir,'*'));
% f = {d(~[d.isdir]).name};
Expand All @@ -51,17 +51,17 @@
% for i=1:length(f)
% [pathstr, name, ext] = fileparts(f{i});
% if ismember(ext,mext)
% fid = fopen(fullfile(spmdir,f{i}),'r');
% if fid == -1, continue; end
% V = 'none';
% while 1
% tline = fgetl(fid);
% if ~ischar(tline), break, end
% tok = regexp(tline, pat, 'tokens');
% if ~isempty(tok), V = tok{1}{2}; break; end
% end
% fclose(fid);
% fprintf('%% %s %s%s\n',f{i},blanks(L-length(f{i})),V);
% fid = fopen(fullfile(spmdir,f{i}),'r');
% if fid == -1, continue; end
% V = 'none';
% while 1
% tline = fgetl(fid);
% if ~ischar(tline), break, end
% tok = regexp(tline, pat, 'tokens');
% if ~isempty(tok), V = tok{1}{2}; break; end
% end
% fclose(fid);
% fprintf('%% %s %s%s\n',f{i},blanks(L-length(f{i})),V);
% end
% end
%=======================================================================
340 changes: 170 additions & 170 deletions MEEGpreprocessing/ft2spm.m
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@@ -1,170 +1,170 @@
function ft2spm(ftdata, filename, ctf)
% Converter from Fieldtrip (http://www.ru.nl/fcdonders/fieldtrip/)
% data structures to SPM8 file format
%_______________________________________________________________________
% Copyright (C) 2007 Wellcome Trust Centre for Neuroimaging

% Vladimir Litvak
% $Id$


disp('Warning: Converting the data to SPM8 format which is in development and');
disp('may not work with some (or most) SPM functions. If you need something that works,');
disp('set your SPM version to SPM5');

% If preprocessing format
if iscell(ftdata.time)

if length(ftdata.time)>1
% Initial checks
if any(diff(cellfun('length', ftdata.time))~=0)
error('SPM can only handle data with equal trial lengths.');
else
times=cell2mat(ftdata.time(:));
if any(diff(times(:, 1))~=0) || any(diff(times(:, end))~=0)
error('SPM can only handle data the same trial borders.');
end
end
end

Ntrials=length(ftdata.trial);
Nchannels = size(ftdata.trial{1},1);
Nsamples = size(ftdata.trial{1},2);

data = zeros(Nchannels, Nsamples, Ntrials);

spm_progress_bar('Init', Ntrials, 'converting data to SPM format'); drawnow;
for n=1:Ntrials
spm_progress_bar('Set', n); drawnow;
data(:,:,n) = ftdata.trial{n};
end
spm_progress_bar('Clear');

ftdata.time = ftdata.time{1};
else % timelockanalysis format
rptind=strmatch('rpt', tokenize(ftdata.dimord, '_'));
if isempty(rptind)
rptind=strmatch('subj', tokenize(ftdata.dimord, '_'));
end

timeind=strmatch('time', tokenize(ftdata.dimord, '_'));
chanind=strmatch('chan', tokenize(ftdata.dimord, '_'));

if ~isempty(rptind)
if isfield(ftdata, 'trial')
Ntrials = size(ftdata.trial, rptind);
data =permute(ftdata.trial, [chanind, timeind, rptind]);
else
Ntrials = size(ftdata.individual, rptind);
data =permute(ftdata.individual, [chanind, timeind, rptind]);
end
else
Ntrials = 1;
data =permute(ftdata.avg, [chanind, timeind]);
end

Nchannels = size(ftdata.trial, chanind);
Nsamples = size(ftdata.trial, timeind);
end

% sampling rate in Hz
D.Fsample = ftdata.fsample;

D.timeOnset = ftdata.time(1);

% Number of time bins in peri-stimulus time
D.Nsamples = Nsamples;

% Names of channels in order of the data
D.channels = struct('label', ftdata.label);
[D.channels.modality] = deal('Other');


% name of SPM mat file
[filepath, filename] = fileparts(filename);
D.fname = filename;
D.path = filepath;

megchans=match_str(ftdata.label, ft_channelselection('MEG', ftdata.label));
if isfield(ftdata, 'hdr') && isfield(ftdata.hdr, 'grad') && ~isempty(megchans) % MEG
[D.channels(megchans).type] = deal('MEG');
[D.channels(megchans).units] = deal('fT');
% This is a rule of thumb. Look at the distribution of values
% at one timepoint across channels and trials. Assumes that in MEG
% datasets most channels will be MEG.
if (median(abs(reshape(data(:,fix(end/2),:), 1,[])))<1e-10)
data(megchans, :, :)=1e15*data(megchans, :, :);
warning('Detected MEG data and converted to the units to fT');
end

if ~isempty(ftdata.hdr.grad)
D.sensors.pnt = ftdata.hdr.grad.pnt;
D.sensors.ori = ftdata.hdr.grad.ori;
D.sensors.type = cell(size(D.sensors.pnt, 1), 1);
[D.sensors.type{:}] = deal('MEG');
[sel1, sel2] = match_str({D.channels.label}, ftdata.hdr.grad.label);
tra = num2cell(ftdata.hdr.grad.tra(sel2, :), 2);
[D.channels(sel1).tra] = deal(tra{:});
end
else %EEG
[D.channels.type] = deal('EEG');
[D.channels.units] = deal('\muV');
if (median(abs(reshape(data(:,fix(end/2),:), 1,[])))<1e-2)
data=1e6*data;
warning('Scaled the data for CTF EEG.');
else
warning('Assuming that units are uV. Units may not be correct for EEG data.');
end
end

% In the case of epoched data preprocessed in SPM codes and times are taken
% from the trl table
if issubfield(ftdata, 'cfg.trl') && Ntrials>1
trl = getsubfield(ftdata, 'cfg.trl');
D.trials = struct('onset', num2cell(trl(:,1)./D.Fsample));
if size(trl, 2)<4
[D.trials.label] = deal('Undefined');
else
for i = 1:Ntrials
D.trials(i).label = num2str(trl(i,4));
end
end
%If there is no trl (data is continuous or not from SPM GUI)
elseif issubfield(ftdata.cfg, 'cfg.event')
% If data comes from FT spm codes are added to events
event = getsubfield(ftdata, 'cfg.event');
if ~isfield(event, 'spmcode')
event=spm_eeg_recode_events(event);
end
for i = 1:Ntrials
D.trials(i).label = num2str(event(i).spmcode);
D.trials(i).onset = event(i).sample./D.Fsample + D.timeOnset;
D.trials(i).events.type = event(i).type;
D.trials(i).events.value = event(i).value;
D.trials(i).events.time = event(i).sample./D.Fsample;
end
else
% If there is no information about events the codes are 1s
warning('No event information found in the FT data');
[D.trials(1:Ntrials).label]=deal('Undefined');
end

D.data.fnamedat = [spm_str_manip(D.fname, 'r') '.dat'];

D.data.scale = ones(Nchannels, 1, Ntrials);
D.data.datatype = 'float32';

fpd = fopen(fullfile(D.path, D.data.fnamedat), 'w');

for i = 1:Ntrials
d = squeeze(data(:, :, i));
D.data.scale(:, 1, i) = spm_eeg_write(fpd, d, 2, D.data.datatype);
end

fclose(fpd);

%D = meeg(D);
D = rmfield(D, 'path');

save(fullfile(filepath, filename), 'D');

function ft2spm(ftdata, filename, ctf)
% Converter from Fieldtrip (http://www.ru.nl/fcdonders/fieldtrip/)
% data structures to SPM8 file format
%_______________________________________________________________________
% Copyright (C) 2007 Wellcome Trust Centre for Neuroimaging

% Vladimir Litvak
% $Id: ft2spm.m 1131 2008-02-06 11:17:09Z spm $


disp('Warning: Converting the data to SPM8 format which is in development and');
disp('may not work with some (or most) SPM functions. If you need something that works,');
disp('set your SPM version to SPM5');

% If preprocessing format
if iscell(ftdata.time)

if length(ftdata.time)>1
% Initial checks
if any(diff(cellfun('length', ftdata.time))~=0)
error('SPM can only handle data with equal trial lengths.');
else
times=cell2mat(ftdata.time(:));
if any(diff(times(:, 1))~=0) || any(diff(times(:, end))~=0)
error('SPM can only handle data the same trial borders.');
end
end
end

Ntrials=length(ftdata.trial);
Nchannels = size(ftdata.trial{1},1);
Nsamples = size(ftdata.trial{1},2);

data = zeros(Nchannels, Nsamples, Ntrials);

spm_progress_bar('Init', Ntrials, 'converting data to SPM format'); drawnow;
for n=1:Ntrials
spm_progress_bar('Set', n); drawnow;
data(:,:,n) = ftdata.trial{n};
end
spm_progress_bar('Clear');

ftdata.time = ftdata.time{1};
else % timelockanalysis format
rptind=strmatch('rpt', tokenize(ftdata.dimord, '_'));
if isempty(rptind)
rptind=strmatch('subj', tokenize(ftdata.dimord, '_'));
end

timeind=strmatch('time', tokenize(ftdata.dimord, '_'));
chanind=strmatch('chan', tokenize(ftdata.dimord, '_'));

if ~isempty(rptind)
if isfield(ftdata, 'trial')
Ntrials = size(ftdata.trial, rptind);
data =permute(ftdata.trial, [chanind, timeind, rptind]);
else
Ntrials = size(ftdata.individual, rptind);
data =permute(ftdata.individual, [chanind, timeind, rptind]);
end
else
Ntrials = 1;
data =permute(ftdata.avg, [chanind, timeind]);
end

Nchannels = size(ftdata.trial, chanind);
Nsamples = size(ftdata.trial, timeind);
end

% sampling rate in Hz
D.Fsample = ftdata.fsample;

D.timeOnset = ftdata.time(1);

% Number of time bins in peri-stimulus time
D.Nsamples = Nsamples;

% Names of channels in order of the data
D.channels = struct('label', ftdata.label);
[D.channels.modality] = deal('Other');


% name of SPM mat file
[filepath, filename] = fileparts(filename);
D.fname = filename;
D.path = filepath;

megchans=match_str(ftdata.label, ft_channelselection('MEG', ftdata.label));
if isfield(ftdata, 'hdr') && isfield(ftdata.hdr, 'grad') && ~isempty(megchans) % MEG
[D.channels(megchans).type] = deal('MEG');
[D.channels(megchans).units] = deal('fT');
% This is a rule of thumb. Look at the distribution of values
% at one timepoint across channels and trials. Assumes that in MEG
% datasets most channels will be MEG.
if (median(abs(reshape(data(:,fix(end/2),:), 1,[])))<1e-10)
data(megchans, :, :)=1e15*data(megchans, :, :);
warning('Detected MEG data and converted to the units to fT');
end

if ~isempty(ftdata.hdr.grad)
D.sensors.pnt = ftdata.hdr.grad.pnt;
D.sensors.ori = ftdata.hdr.grad.ori;
D.sensors.type = cell(size(D.sensors.pnt, 1), 1);
[D.sensors.type{:}] = deal('MEG');
[sel1, sel2] = match_str({D.channels.label}, ftdata.hdr.grad.label);
tra = num2cell(ftdata.hdr.grad.tra(sel2, :), 2);
[D.channels(sel1).tra] = deal(tra{:});
end
else %EEG
[D.channels.type] = deal('EEG');
[D.channels.units] = deal('\muV');
if (median(abs(reshape(data(:,fix(end/2),:), 1,[])))<1e-2)
data=1e6*data;
warning('Scaled the data for CTF EEG.');
else
warning('Assuming that units are uV. Units may not be correct for EEG data.');
end
end

% In the case of epoched data preprocessed in SPM codes and times are taken
% from the trl table
if issubfield(ftdata, 'cfg.trl') && Ntrials>1
trl = getsubfield(ftdata, 'cfg.trl');
D.trials = struct('onset', num2cell(trl(:,1)./D.Fsample));
if size(trl, 2)<4
[D.trials.label] = deal('Undefined');
else
for i = 1:Ntrials
D.trials(i).label = num2str(trl(i,4));
end
end
%If there is no trl (data is continuous or not from SPM GUI)
elseif issubfield(ftdata.cfg, 'cfg.event')
% If data comes from FT spm codes are added to events
event = getsubfield(ftdata, 'cfg.event');
if ~isfield(event, 'spmcode')
event=spm_eeg_recode_events(event);
end
for i = 1:Ntrials
D.trials(i).label = num2str(event(i).spmcode);
D.trials(i).onset = event(i).sample./D.Fsample + D.timeOnset;
D.trials(i).events.type = event(i).type;
D.trials(i).events.value = event(i).value;
D.trials(i).events.time = event(i).sample./D.Fsample;
end
else
% If there is no information about events the codes are 1s
warning('No event information found in the FT data');
[D.trials(1:Ntrials).label]=deal('Undefined');
end

D.data.fnamedat = [spm_str_manip(D.fname, 'r') '.dat'];

D.data.scale = ones(Nchannels, 1, Ntrials);
D.data.datatype = 'float32';

fpd = fopen(fullfile(D.path, D.data.fnamedat), 'w');

for i = 1:Ntrials
d = squeeze(data(:, :, i));
D.data.scale(:, 1, i) = spm_eeg_write(fpd, d, 2, D.data.datatype);
end

fclose(fpd);

%D = meeg(D);
D = rmfield(D, 'path');

save(fullfile(filepath, filename), 'D');

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