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github
|
philippboehmsturm/antx-master
|
ft_datatype_raw.m
|
.m
|
antx-master/xspm8/external/fieldtrip/utilities/ft_datatype_raw.m
| 10,365 |
utf_8
|
4db6184c0320dfb990e48ca6db1e95a2
|
function data = ft_datatype_raw(data, varargin)
% FT_DATATYPE_RAW describes the FieldTrip MATLAB structure for raw data
%
% The raw datatype represents sensor-level time-domain data typically
% obtained after calling FT_DEFINETRIAL and FT_PREPROCESSING. It contains
% one or multiple segments of data, each represented as Nchan X Ntime
% arrays.
%
% An example of a raw data structure with 151 MEG channels is
%
% label: {151x1 cell} the channel labels (e.g. 'MRC13')
% time: {1x266 cell} the timeaxis [1*Ntime double] per trial
% trial: {1x266 cell} the numeric data [151*Ntime double] per trial
% sampleinfo: [266x2 double] the begin and endsample of each trial relative to the recording on disk
% trialinfo: [266x1 double] optional trigger or condition codes for each trial
% hdr: [1x1 struct] the full header information of the original dataset on disk
% grad: [1x1 struct] information about the sensor array (for EEG it is called elec)
% cfg: [1x1 struct] the configuration used by the function that generated this data structure
%
% Required fields:
% - time, trial, label
%
% Optional fields:
% - sampleinfo, trialinfo, grad, elec, hdr, cfg
%
% Deprecated fields:
% - fsample
%
% Obsoleted fields:
% - offset
%
% Revision history:
%
% (2011/latest) The description of the sensors has changed, see FT_DATATYPE_SENS
% for further information.
%
% (2010v2) The trialdef field has been replaced by the sampleinfo and
% trialinfo fields. The sampleinfo corresponds to trl(:,1:2), the trialinfo
% to trl(4:end).
%
% (2010v1) In 2010/Q3 it shortly contained the trialdef field which was a copy
% of the trial definition (trl) is generated by FT_DEFINETRIAL.
%
% (2007) It used to contain the offset field, which correcponds to trl(:,3).
% Since the offset field is redundant with the time axis, the offset field is
% from now on not present any more. It can be recreated if needed.
%
% (2003) The initial version was defined
%
% See also FT_DATATYPE, FT_DATATYPE_COMP, FT_DATATYPE_TIMELOCK, FT_DATATYPE_FREQ,
% FT_DATATYPE_SPIKE, FT_DATATYPE_SENS
% Copyright (C) 2011, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_datatype_raw.m 7216 2012-12-17 19:45:33Z roboos $
% get the optional input arguments, which should be specified as key-value pairs
version = ft_getopt(varargin, 'version', 'latest');
hassampleinfo = ft_getopt(varargin, 'hassampleinfo', 'ifmakessense'); % can be yes/no/ifmakessense
hastrialinfo = ft_getopt(varargin, 'hastrialinfo', 'ifmakessense'); % can be yes/no/ifmakessense
if isequal(hassampleinfo, 'ifmakessense')
hassampleinfo = 'yes';
if isfield(data, 'sampleinfo') && size(data.sampleinfo,1)~=numel(data.trial)
% it does not make sense, so don't keep it
hassampleinfo = 'no';
end
if isfield(data, 'sampleinfo')
numsmp = data.sampleinfo(:,2)-data.sampleinfo(:,1)+1;
for i=1:length(data.trial)
if size(data.trial{i},2)~=numsmp(i);
% it does not make sense, so don't keep it
hassampleinfo = 'no';
break;
end
end
end
if strcmp(hassampleinfo, 'no')
% the actual removal will be done further down
warning('removing inconsistent sampleinfo');
end
end
if isequal(hastrialinfo, 'ifmakessense')
hastrialinfo = 'yes';
if isfield(data, 'trialinfo') && size(data.trialinfo,1)~=numel(data.trial)
% it does not make sense, so don't keep it
hastrialinfo = 'no';
end
if strcmp(hastrialinfo, 'no')
% the actual removal will be done further down
warning('removing inconsistent sampleinfo');
end
end
% convert it into true/false
hassampleinfo = istrue(hassampleinfo);
hastrialinfo = istrue(hastrialinfo);
if strcmp(version, 'latest')
version = '2011';
end
if isempty(data)
return;
end
switch version
case '2011'
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if isfield(data, 'grad')
% ensure that the gradiometer balancing is specified
if ~isfield(data.grad, 'balance') || ~isfield(data.grad.balance, 'current')
data.grad.balance.current = 'none';
end
% ensure the new style sensor description
data.grad = ft_datatype_sens(data.grad);
end
if isfield(data, 'elec')
data.elec = ft_datatype_sens(data.elec);
end
if ~isfield(data, 'fsample')
data.fsample = 1/mean(diff(data.time{1}));
end
if isfield(data, 'offset')
data = rmfield(data, 'offset');
end
% the trialdef field should be renamed into sampleinfo
if isfield(data, 'trialdef')
data.sampleinfo = data.trialdef;
data = rmfield(data, 'trialdef');
end
if (hassampleinfo && ~isfield(data, 'sampleinfo')) || (hastrialinfo && ~isfield(data, 'trialinfo'))
% try to reconstruct the sampleinfo and trialinfo
data = fixsampleinfo(data);
end
if ~hassampleinfo && isfield(data, 'sampleinfo')
data = rmfield(data, 'sampleinfo');
end
if ~hastrialinfo && isfield(data, 'trialinfo')
data = rmfield(data, 'trialinfo');
end
case '2010v2'
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if ~isfield(data, 'fsample')
data.fsample = 1/mean(diff(data.time{1}));
end
if isfield(data, 'offset')
data = rmfield(data, 'offset');
end
% the trialdef field should be renamed into sampleinfo
if isfield(data, 'trialdef')
data.sampleinfo = data.trialdef;
data = rmfield(data, 'trialdef');
end
if (hassampleinfo && ~isfield(data, 'sampleinfo')) || (hastrialinfo && ~isfield(data, 'trialinfo'))
% try to reconstruct the sampleinfo and trialinfo
data = fixsampleinfo(data);
end
if ~hassampleinfo && isfield(data, 'sampleinfo')
data = rmfield(data, 'sampleinfo');
end
if ~hastrialinfo && isfield(data, 'trialinfo')
data = rmfield(data, 'trialinfo');
end
case {'2010v1' '2010'}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if ~isfield(data, 'fsample')
data.fsample = 1/mean(diff(data.time{1}));
end
if isfield(data, 'offset')
data = rmfield(data, 'offset');
end
if ~isfield(data, 'trialdef') && hascfg
% try to find it in the nested configuration history
data.trialdef = ft_findcfg(data.cfg, 'trl');
end
case '2007'
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if ~isfield(data, 'fsample')
data.fsample = 1/mean(diff(data.time{1}));
end
if isfield(data, 'offset')
data = rmfield(data, 'offset');
end
case '2003'
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if ~isfield(data, 'fsample')
data.fsample = 1/mean(diff(data.time{1}));
end
if ~isfield(data, 'offset')
data.offset = zeros(length(data.time),1);
for i=1:length(data.time);
data.offset(i) = round(data.time{i}(1)*data.fsample);
end
end
otherwise
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
error('unsupported version "%s" for raw datatype', version);
end
% Numerical inaccuracies in the binary representations of floating point
% values may accumulate. The following code corrects for small inaccuracies
% in the time axes of the trials. See http://bugzilla.fcdonders.nl/show_bug.cgi?id=1390
data = fixtimeaxes(data);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function data = fixtimeaxes(data)
if ~isfield(data, 'fsample')
fsample = 1/mean(diff(data.time{1}));
else
fsample = data.fsample;
end
begtime = zeros(1, length(data.time));
endtime = zeros(1, length(data.time));
numsample = zeros(1, length(data.time));
for i=1:length(data.time)
begtime(i) = data.time{i}(1);
endtime(i) = data.time{i}(end);
numsample(i) = length(data.time{i});
end
% compute the differences over trials and the tolerance
tolerance = 0.01*(1/fsample);
begdifference = abs(begtime-begtime(1));
enddifference = abs(endtime-endtime(1));
% check whether begin and/or end are identical, or close to identical
begidentical = all(begdifference==0);
endidentical = all(enddifference==0);
begsimilar = all(begdifference < tolerance);
endsimilar = all(enddifference < tolerance);
% Compute the offset of each trial relative to the first trial, and express
% that in samples. Non-integer numbers indicate that there is a slight skew
% in the time over trials. This works in case of variable length trials.
offset = fsample * (begtime-begtime(1));
skew = abs(offset - round(offset));
% try to determine all cases where a correction is needed
% note that this does not yet address all possible cases where a fix might be needed
needfix = false;
needfix = needfix || ~begidentical && begsimilar;
needfix = needfix || ~endidentical && endsimilar;
needfix = needfix || ~all(skew==0) && all(skew<0.01);
% if the skew is less than 1% it will be corrected
if needfix
warning_once('correcting numerical inaccuracy in the time axes');
for i=1:length(data.time)
% reconstruct the time axis of each trial, using the begin latency of
% the first trial and the integer offset in samples of each trial
data.time{i} = begtime(1) + ((1:numsample(i)) - 1 + round(offset(i)))/fsample;
end
end
|
github
|
philippboehmsturm/antx-master
|
ft_version.m
|
.m
|
antx-master/xspm8/external/fieldtrip/utilities/ft_version.m
| 20,525 |
utf_8
|
9447155468f1f54b38bd39fd011d3d94
|
function [v,ftpath] = ft_version(cmd)
% FT_VERSION provides functionality for displaying version information on
% the current version of FieldTrip being used, as well us for updating the
% FieldTrip installation.
%
% To understand the different options this function provides, a little bit
% of background knowledge is needed about how FieldTrip deals with
% versions. FieldTrip does not use a fixed release system, but instead
% the 'release' version available from the FTP server is updated daily,
% through an automatic script. This release version is based on the
% development version used internally by the developers, which is updated
% more frequently. Development updates are tracked using Subversion (SVN),
% a system that assigns a revision number to each change to the code. The
% release version of FieldTrip contains a signature file (signature.md5),
% that contains, for each file in the release, the latest revision number
% for that file, along with an MD5 hash of the file's contents. A similar
% signature file is located on the FieldTrip webserver, which is updated
% whenever a developer makes a change to the codebase.
%
% This function uses both the local signature file (dating from whenever
% you downloaded FieldTrip) and the remote signature file (reflecting the
% latest version available--this updates more frequently than the daily FTP
% release) to determine (1) the version of FieldTrip you are using, (2)
% whether you have made local changes to your FieldTrip installation (by
% comparing the actual MD5 hashes of files to the ones stored in your local
% signature file), (3) whether there are new updates available (by
% comparing the local and remote signature files).
%
% Usage:
% ft_version info - display the latest revision number
% present in your installation
% ft_version full - display full revision information about
% your installation; this includes checking
% for local and/or remote changes
% ft_version update - also displays full revision information;
% additionally provides the option of
% downloading new or updated files from the
% code repository
% [v,ftpath] = ft_version - also get information about the root of
% your FieldTrip installation
% 'Hidden' options:
% ft_version signature - generate a new signature file, without
% revision information about the files
% ft_version fullsignature - generate a new signature file, including
% revision information; this can only be
% used when you are using an SVN
% installation of FieldTrip
% Copyright (C) 2012, Eelke Spaak
%
% This file is part of FieldTrip, see http://www.ru.nl/donders/fieldtrip
% 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: ft_version.m 7383 2013-01-23 13:19:28Z eelspa $
if nargin<1
cmd = 'info';
end
[ftpath, ~] = fileparts(mfilename('fullpath'));
ftpath = ftpath(1:end-10); % strip away '/utilities'
signaturefile = fullfile(ftpath, 'signature.md5');
remotesignature = 'http://fieldtrip.fcdonders.nl/signature.md5';
repository = 'http://fieldtrip.googlecode.com/svn/trunk/';
% are we dealing with an SVN working copy of fieldtrip?
issvn = isdir(fullfile(ftpath, '.svn'));
switch cmd
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'info'
% show the latest revision present in this copy of fieldtrip
if issvn
% use svn system call to determine latest revision
olddir = pwd();
cd(ftpath);
[status,output] = system('svn info');
cd(olddir);
if status > 0
error('you seem to have an SVN working copy of FieldTrip, yet ''svn info'' does not work as expected');
end
rev = regexp(output, 'Revision: (.*)', 'tokens', 'dotexceptnewline');
rev = rev{1}{1};
else
% determine latest revision from the signature file
fp = fopen(signaturefile, 'r');
line = fgetl(fp); % just get first line, file should be ordered newest-first
fclose(fp);
rev = regexp(line, '[^\t]*\t([^\t])*\t.*', 'tokens');
rev = rev{1}{1};
end
if nargout > 0
v = rev;
elseif issvn
fprintf('\nThis is FieldTrip, version r%s (svn).\n\n', rev);
else
fprintf('\nThis is FieldTrip, version r%s.\n\n', rev);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'full'
% show the latest revision present in this version of FieldTrip
% and also check for possible remote and local changes
if issvn
% use svn status
olddir = pwd();
cd(ftpath);
[status,output] = system('svn status');
cd(olddir);
if status > 0
error('you seem to have an SVN working copy of FieldTrip, yet ''svn status'' does not work as expected');
end
if numel(output) > 1
modFlag = 'M';
else
modFlag = 'U';
end
fprintf('\nThis is FieldTrip, version r%s%s (svn).\n\n', ft_version(), modFlag);
% simply print the output of the svn status command
if numel(output) > 1
fprintf('This is the SVN status of your working copy:\n');
fprintf(output);
fprintf('\n');
end
else
% fetch remote hash table
str = urlread(remotesignature);
[remHashes, remFiles, remRevs] = parseHashTable(str);
% fetch local hash table
str = fileread(signaturefile);
[locHashes, locFiles, locRevs] = parseHashTable(str);
% determine changes
[remoteDeleted, remoteNew, remoteChanges,...
localDeleted, localChanges] = findChanges(locHashes, locFiles,...
remHashes, remFiles, ftpath);
% print detailed version information
if any(localChanges)
modFlag = 'M'; % M for modified
else
modFlag = 'U'; % U for unmodified
end
fprintf('This is FieldTrip, version r%s%s.\n', ft_version(), modFlag);
if any(localChanges)
fprintf('\nthe following files have been locally modified:\n');
inds = find(localChanges);
for k = 1:numel(inds)
fprintf(' r%sm %s\n', locRevs{inds(k)}, locFiles{inds(k)});
end
end
if any(localDeleted)
fprintf('\nthe following files have been locally deleted:\n');
inds = find(localDeleted);
for k = 1:numel(inds)
fprintf(' r%sd %s\n', locRevs{inds(k)}, locFiles{inds(k)});
end
end
if any(remoteChanges)
fprintf('\na new version is available for the following files:\n');
inds = find(remoteChanges);
for k = 1:numel(inds)
locInd = strcmp(locFiles, remFiles{inds(k)});
fprintf(' r%s-->r%s %s\n',...
locRevs{locInd}, remRevs{inds(k)}, remFiles{inds(k)});
end
end
if any(remoteDeleted)
fprintf('\nthe following files are no longer part of FieldTrip:\n');
files = locFiles(remoteDeleted);
for k = 1:numel(files)
fprintf(' %s\n', files{k});
end
end
if any(remoteNew)
fprintf('\nthe following new files are available:\n');
files = remFiles(remoteNew);
revs = remRevs(remoteNew);
for k = 1:numel(files)
fprintf(' r%sa %s\n', revs{k}, files{k});
end
end
fprintf('\n');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'update'
% get the remote changes, check that there are no conflicting local
% changes and update the files
if issvn
fprintf('\nThis is an SVN working copy of FieldTrip, invoking ''svn update''...\n');
olddir = pwd();
cd(ftpath);
system('svn update');
cd(olddir);
fprintf('\n');
else
% fetch remote hash table
str = urlread(remotesignature);
[remHashes, remFiles, remRevs] = parseHashTable(str);
% fetch local hash table
str = fileread(signaturefile);
[locHashes, locFiles, locRevs] = parseHashTable(str);
% determine changes
[remoteDeleted, remoteNew, remoteChanges,...
localDeleted, localChanges] = findChanges(locHashes, locFiles,...
remHashes, remFiles, ftpath);
% index all possible deletions and additions
locFilesDelete = [];
remFilesDownload = [];
olddir = pwd();
cd(ftpath);
% keep track of whether local additions will possibly be overwritten
overwriteFlag = 0;
% first display information on what would be changed
if any(remoteNew)
fprintf('\nthe following new files will be added:\n');
inds = find(remoteNew);
for k = 1:numel(inds)
if exist(remFiles{inds(k)}, 'file')
msg = '!';
overwriteFlag = 1;
else
msg = ' ';
end
% give this change a number and remember it
remFilesDownload(end+1) = inds(k);
locFilesDelete(end+1) = nan;
fprintf('%s %3d. r%s %s\n', msg, numel(locFilesDelete), remRevs{inds(k)}, remFiles{inds(k)});
end
end
if any(remoteDeleted)
fprintf('\nthe following files will be deleted:\n');
inds = find(remoteDeleted);
for k = 1:numel(inds)
if localChanges(inds(k))
msg = '!';
overwriteFlag = 1;
else
msg = ' ';
end
% give this change a number and remember it
remFilesDownload(end+1) = nan;
locFilesDelete(end+1) = inds(k);
fprintf('%s %3d. %s\n', msg, numel(locFilesDelete), locFiles{inds(k)});
end
end
if any(remoteChanges)
fprintf('\nthe following files will be updated:\n');
inds = find(remoteChanges);
for k = 1:numel(inds)
locInd = strcmp(locFiles, remFiles{inds(k)});
if localChanges(locInd)
msg = '!';
overwriteFlag = 1;
else
msg = ' ';
end
% give this change a number and remember it
remFilesDownload(end+1) = inds(k);
locFilesDelete(end+1) = nan;
fprintf('%s %3d. r%s-->r%s %s\n',...
msg, numel(locFilesDelete), locRevs{locInd},...
remRevs{inds(k)}, remFiles{inds(k)});
end
end
assert(numel(remFilesDownload) == numel(locFilesDelete));
if overwriteFlag
fprintf(['\n!!NOTE: if you choose to include changes marked with a leading !,\n'...
' they will overwrite local changes or additions!\n']);
end
% prompt the user which changes should be incorporated
while (true) % use while (true) as poor man's do{}while()
changesToInclude = input(['\nwhich changes do you want to include?\n'...
'([vector] for specific changes, ''all'', or [] for none)\n? '],'s');
% check integrity of entered data
if strcmp(changesToInclude, 'all')
changesToInclude = 1:numel(remFilesDownload);
else
[changesToInclude,status] = str2num(changesToInclude);
end
if status && isnumeric(changesToInclude) && all(changesToInclude > 0)...
&& (all(changesToInclude <= numel(remFilesDownload)) || ...
changesToInclude == Inf)
changesToInclude = unique(changesToInclude);
break;
end
end
% include only those changes requested in the actual update
locFilesDelete = locFilesDelete(changesToInclude);
locFilesDelete(isnan(locFilesDelete)) = [];
remFilesDownload = remFilesDownload(changesToInclude);
remFilesDownload(isnan(remFilesDownload)) = [];
% delete all local files that should be deleted
for k = 1:numel(locFilesDelete)
ind = locFilesDelete(k);
fprintf('deleting file %s...\n', locFiles{ind});
delete(locFiles{ind});
% also remove entry from the hash table cell arrays
locFiles(ind) = [];
locHashes(ind) = [];
locRevs(ind) = [];
end
% add new files and/or update changed files
for k = 1:numel(remFilesDownload)
ind = remFilesDownload(k);
fprintf('downloading file %s...\n', remFiles{ind});
newFile = urlread([repository remFiles{ind}]);
fp = fopen(remFiles{ind}, 'w');
fwrite(fp, newFile);
fclose(fp);
% update local hash table
locInd = strcmp(locFiles, remFiles{ind});
if any(locInd)
% file was already present, update hash
locHashes{locInd} = remHashes{ind};
locRevs{locInd} = remRevs{ind};
else
% new file, add hash
locFiles{end} = remFiles{ind};
locHashes{end} = remHashes{ind};
locRevs{end} = remRevs{ind};
end
end
cd(olddir);
if ~isempty(changesToInclude)
% output new hash table
fp = fopen(signaturefile,'w');
outputHashTable(fp, locHashes, locFiles, locRevs);
fclose(fp);
fprintf('update finished.\n');
else
fprintf('nothing updated.\n');
end
ft_version();
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'signature'
if exist(signaturefile, 'file')
error(sprintf([signaturefile ' already exists.\nIf you are sure you want to re-create '...
'the signature file, you will have to manually delete it.\nNote that this means '...
'that local edits cannot be tracked anymore, and might be overwritten without notice!']));
end
fprintf('\nwriting signature file to signature-local.md5 (this might take a few minutes)...');
hashFile = fopen(signaturefile, 'w');
hashAll(hashFile, ftpath, ftpath);
fclose(hashFile);
fprintf('done.\n\n');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'fullsignature'
if exist(signaturefile, 'file')
error(sprintf([signaturefile ' already exists.\nIf you are sure you want to re-create '...
'the signature file, you will have to manually delete it.\nNote that this means '...
'that local edits cannot be tracked anymore, and might be overwritten without notice!']));
end
if ~issvn
error('you can only generate a full signature with revision info if you are using an SVN working copy of FieldTrip');
end
fprintf('\nwriting signature file to signature-local.md5 (this might take a few minutes)...');
hashFile = fopen(fullfile(ftpath, 'signature-local.md5'), 'w');
hashAll(hashFile, ftpath, ftpath, 1);
fclose(hashFile);
fprintf('done.\n\n');
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% locHashes and locFiles represent the hashes and filenames of entries in
% the local hash table, respectively. remHashes and remFiles represent the
% hashes and filenames of entries in the remote hash table, respectively.
% ftpath is the FT root path. Returned are logical index vectors into the
% remFiles cell array (for remoteChanges and remoteNew) or into the
% locFiles cell array (rest).
function [remoteDeleted, remoteNew, remoteChanges,...
localDeleted, localChanges] = findChanges(locHashes, locFiles,...
remHashes, remFiles, ftpath)
fprintf('\ncomparing local and remote (latest) hashes, this might take a minute...\n');
remoteDeleted = false(size(locFiles));
localChanges = false(size(locFiles));
remoteChanges = false(size(remFiles));
localDeleted = false(size(locFiles));
% note: no keeping track of local additions (not desirable probably)
% compare them by looping over all files in local table
for k = 1:numel(locFiles)
ind = strcmp(remFiles, locFiles{k});
if sum(ind) > 1
% this should never happen; means remote table is corrupt
warning('more than one entry found in remote hash table for file %s', locFiles{k});
end
if ~any(ind)
% file not found in remote table, should be deleted locally
remoteDeleted(k) = 1;
continue;
end
if ~strcmp(remHashes{ind}, locHashes{k})
% hash remote different from hash in local table
remoteChanges(ind) = 1;
end
if ~exist(fullfile(ftpath, locFiles{k}), 'file')
localDeleted(k) = 1;
continue;
end
if (nargout > 4) % only check for local changes if requested, slow step
if ~strcmp(CalcMD5(fullfile(ftpath, locFiles{k}), 'File'), locHashes{k})
% hash of actual file different from hash in local table
localChanges(k) = 1;
end
end
end
% only remote additions have not yet been determined, do so now
remoteNew = false(size(remFiles));
[dummy,inds] = setdiff(remFiles, locFiles);
remoteNew(inds) = 1;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% If str is a tab-separated string, with records separated by newlines,
% parseHashTable(str) will return the three columns in the file: the first
% column will be returned as hashes; the second as revs, the third as
% files.
function [hashes,files,revs] = parseHashTable(str)
lines = regexp(str, '\n', 'split');
if isempty(lines{end})
lines = lines(1:end-1);
end
hashes = cell(1, numel(lines));
files = cell(1, numel(lines));
revs = cell(1, numel(lines));
for k = 1:numel(lines)
tmp = regexp(lines{k}, '\t', 'split');
hashes{k} = tmp{1};
revs{k} = tmp{2};
files{k} = tmp{3};
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function hashAll(filePointer, path, basepath, withRev)
if nargin < 4
withRev = 0;
end
% these files are always excluded from the update and hashing routines
file_excludes = {'.', '..', '.svn', 'test', 'signature.md5', 'signature-local.md5'};
list = dir(path);
for k = 1:numel(list)
if ~any(strcmp(list(k).name, file_excludes))
filename = [path '/' list(k).name];
if (list(k).isdir)
hashAll(filePointer, filename, basepath, withRev);
else
md5 = CalcMD5(filename,'File');
if withRev
[status, output] = system(['svn info ' filename]);
rev = regexp(output, 'Last Changed Rev: (.*)', 'tokens', 'dotexceptnewline');
if ~isempty(rev) && ~isempty(rev{1})
rev = rev{1}{1};
else
rev = 'UNKNOWN';
end
else
rev = 'UNKNOWN';
end
filename = filename((numel(basepath)+2):end); % strip off the base path
fprintf(filePointer, '%s\t%s\t%s\n',md5,rev,filename);
end
end
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function outputHashTable(filePointer, hashes, files, revs)
% sort the entries (highest revs should always be at the top)
numRevs = cellfun(@str2double, revs);
[sortedRevs,inds] = sort(numRevs, 'descend');
lastnan = find(isnan(sortedRevs), 1, 'last'); % put nans (=UNKNOWN) at the end
inds = [inds(lastnan+1:end) inds(1:lastnan)];
hashes = hashes(inds);
files = files(inds);
revs = revs(inds);
for k = 1:numel(hashes)
fprintf(filePointer, '%s\t%s\t%s\n', hashes{k}, revs{k}, files{k});
end
end
|
github
|
philippboehmsturm/antx-master
|
ft_transform_geometry.m
|
.m
|
antx-master/xspm8/external/fieldtrip/utilities/ft_transform_geometry.m
| 3,961 |
utf_8
|
2753b4ed40defdf48f32d8603dccba02
|
function [output] = ft_transform_geometry(transform, input)
% FT_TRANSFORM_GEOMETRY applies a homogeneous coordinate transformation to
% a structure with geometric information. These objects include:
% - volume conductor geometry, consisting of a mesh, a set of meshes, a
% single sphere, or multiple spheres.
% - gradiometer of electrode structure containing sensor positions and
% coil orientations (for MEG).
% - headshape description containing positions in 3D space.
% - sourcemodel description containing positions and optional orientations
% in 3D space.
%
% The units in which the transformation matrix is expressed are assumed to
% be the same units as the units in which the geometric object is
% expressed. Depending on the input object, the homogeneous transformation
% matrix should be limited to a rigid-body translation plus rotation
% (MEG-gradiometer array), or to a rigid-body translation plus rotation
% plus a global rescaling (volume conductor geometry).
%
% Use as
% output = ft_transform_geometry(transform, input)
% Copyright (C) 2011, Jan-Mathijs Schoffelen
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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/>.
%
% $Id: ft_transform_geometry.m$
checkrotation = (ft_datatype(input, 'volume') && ~strcmp(ft_voltype(input), 'unknown')) || ft_senstype(input, 'meg');
checkscaling = ~strcmp(ft_voltype(input), 'unknown');
% determine the rotation matrix
rotation = eye(4);
rotation(1:3,1:3) = transform(1:3,1:3);
if any(abs(transform(4,:)-[0 0 0 1])>100*eps)
error('invalid transformation matrix');
end
if checkrotation
% allow for some numerical imprecision
if abs(det(rotation)-1)>100*eps
error('only a rigid body transformation without rescaling is allowed');
end
end
if checkscaling
% FIXME build in a check for uniform rescaling probably do svd or so
% FIXME insert check for nonuniform scaling, should give an error
end
tfields = {'pos' 'pnt' 'o' 'chanpos' 'coilpos' 'elecpos', 'nas', 'lpa', 'rpa', 'zpoint'}; % apply rotation plus translation
rfields = {'ori' 'nrm' 'coilori'}; % only apply rotation
mfields = {'transform'}; % plain matrix multiplication
recfields = {'fid' 'bnd'}; % recurse into these fields
% the field 'r' is not included here, because it applies to a volume
% conductor model, and scaling is not allowed, so r will not change.
fnames = fieldnames(input);
for k = 1:numel(fnames)
if any(strcmp(fnames{k}, tfields))
input.(fnames{k}) = apply(transform, input.(fnames{k}));
elseif any(strcmp(fnames{k}, rfields))
input.(fnames{k}) = apply(rotation, input.(fnames{k}));
elseif any(strcmp(fnames{k}, mfields))
input.(fnames{k}) = transform*input.(fnames{k});
elseif any(strcmp(fnames{k}, recfields))
for j = 1:numel(input.(fnames{k}))
input.(fnames{k})(j) = ft_transform_geometry(transform, input.(fnames{k})(j));
end
else
% do nothing
end
end
output = input;
return;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that applies the homogeneous transformation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [new] = apply(transform, old)
old(:,4) = 1;
new = old * transform';
new = new(:,1:3);
|
github
|
philippboehmsturm/antx-master
|
nansum.m
|
.m
|
antx-master/xspm8/external/fieldtrip/utilities/private/nansum.m
| 185 |
utf_8
|
4859ec062780c478011dd7a8d94684a0
|
% NANSUM provides a replacement for MATLAB's nanmean.
%
% For usage see SUM.
function y = nansum(x, dim)
if nargin == 1
dim = 1;
end
idx = isnan(x);
x(idx) = 0;
y = sum(x, dim);
end
|
github
|
philippboehmsturm/antx-master
|
nanstd.m
|
.m
|
antx-master/xspm8/external/fieldtrip/utilities/private/nanstd.m
| 231 |
utf_8
|
0ff62b1c345b5ad76a9af59cf07c2983
|
% NANSTD provides a replacement for MATLAB's nanstd that is almost
% compatible.
%
% For usage see STD. Note that the three-argument call with FLAG is not
% supported.
function Y = nanstd(varargin)
Y = sqrt(nanvar(varargin{:}));
|
github
|
philippboehmsturm/antx-master
|
warning_once.m
|
.m
|
antx-master/xspm8/external/fieldtrip/utilities/private/warning_once.m
| 3,832 |
utf_8
|
07dc728273934663973f4c716e7a3a1c
|
function [ws warned] = warning_once(varargin)
%
% Use as one of the following
% warning_once(string)
% warning_once(string, timeout)
% warning_once(id, string)
% warning_once(id, string, timeout)
% where timeout should be inf if you don't want to see the warning ever
% again. The default timeout value is 60 seconds.
%
% It can be used instead of the MATLAB built-in function WARNING, thus as
% s = warning_once(...)
% or as
% warning_once(s)
% where s is a structure with fields 'identifier' and 'state', storing the
% state information. In other words, warning_once accepts as an input the
% same structure it returns as an output. This returns or restores the
% states of warnings to their previous values.
%
% It can also be used as
% [s w] = warning_once(...)
% where w is a boolean that indicates whether a warning as been thrown or not.
%
% Please note that you can NOT use it like this
% warning_once('the value is %d', 10)
% instead you should do
% warning_once(sprintf('the value is %d', 10))
% Copyright (C) 2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: warning_once.m 7123 2012-12-06 21:21:38Z roboos $
persistent stopwatch previous
if nargin < 1
error('You need to specify at least a warning message');
end
warned = false;
if isstruct(varargin{1})
warning(varargin{1});
return;
end
% put the arguments we will pass to warning() in this cell array
warningArgs = {};
if nargin==3
% calling syntax (id, msg, timeout)
warningArgs = varargin(1:2);
timeout = varargin{3};
fname = [warningArgs{1} '_' warningArgs{2}];
elseif nargin==2 && isnumeric(varargin{2})
% calling syntax (msg, timeout)
warningArgs = varargin(1);
timeout = varargin{2};
fname = warningArgs{1};
elseif nargin==2 && ~isnumeric(varargin{2})
% calling syntax (id, msg)
warningArgs = varargin(1:2);
timeout = 60;
fname = [warningArgs{1} '_' warningArgs{2}];
elseif nargin==1
% calling syntax (msg)
warningArgs = varargin(1);
timeout = 60; % default timeout in seconds
fname = [warningArgs{1}];
end
if isempty(timeout)
error('Timeout ill-specified');
end
if isempty(stopwatch)
stopwatch = tic;
end
if isempty(previous)
previous = struct;
end
now = toc(stopwatch); % measure time since first function call
fname = decomma(fixname(fname)); % make a nice string that is allowed as structure fieldname
if length(fname) > 63 % MATLAB max name
fname = fname(1:63);
end
if ~isfield(previous, fname) || ...
(isfield(previous, fname) && now>previous.(fname).timeout)
% warning never given before or timed out
ws = warning(warningArgs{:});
previous.(fname).timeout = now+timeout;
previous.(fname).ws = ws;
warned = true;
else
% the warning has been issued before, but has not timed out yet
ws = previous.(fname).ws;
end
end % function
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% helper functions
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function name = decomma(name)
name(name==',')=[];
end % function
|
github
|
philippboehmsturm/antx-master
|
nanmean.m
|
.m
|
antx-master/xspm8/external/fieldtrip/utilities/private/nanmean.m
| 165 |
utf_8
|
e6c473a49d8be6e12960af55ced45e54
|
% NANMEAN provides a replacement for MATLAB's nanmean.
%
% For usage see MEAN.
function y = nanmean(x, dim)
N = sum(~isnan(x), dim);
y = nansum(x, dim) ./ N;
end
|
github
|
philippboehmsturm/antx-master
|
nanvar.m
|
.m
|
antx-master/xspm8/external/fieldtrip/utilities/private/nanvar.m
| 1,093 |
utf_8
|
d9641af3bba1e2c6e3512199221e686c
|
% NANVAR provides a replacement for MATLAB's nanvar that is almost
% compatible.
%
% For usage see VAR. Note that the weight-vector is not supported. If you
% need it, please file a ticket at our bugtracker.
function Y = nanvar(X, w, dim)
switch nargin
case 1
% VAR(x)
% Normalize by n-1 when no dim is given.
Y = nanvar_base(X);
n = nannumel(X);
w = 0;
case 2
% VAR(x, 1)
% VAR(x, w)
% In this case, the default of normalizing by n is expected.
Y = nanvar_base(X);
n = nannumel(X);
case 3
% VAR(x, w, dim)
% if w=0 normalize by n-1, if w=1 normalize by n.
Y = nanvar_base(X, dim);
n = nannumel(X, dim);
otherwise
error ('Too many input arguments!')
end
% Handle different forms of normalization:
if numel(w) == 0
% empty weights vector defaults to 0
w = 0;
end
if numel(w) ~= 1
error('Weighting vector w is not implemented! Please file a bug.');
end
if ~isreal(X)
Y = real(Y) + imag(Y);
n = real(n);
end
if w == 1
Y = Y ./ n;
end
if w == 0
Y = Y ./ max(1, (n - 1)); % don't divide by zero!
end
|
github
|
philippboehmsturm/antx-master
|
ft_plot_montage.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/ft_plot_montage.m
| 6,823 |
utf_8
|
5669e1d67db8e541768e7c780f85ff2e
|
function ft_plot_montage(dat, varargin)
% FT_PLOT_MONTAGE makes a montage of a 3-D array by selecting slices at
% regular distances and combining them in one large 2-D image.
%
% Use as
% ft_plot_montage(dat, ...)
% where dat is a 3-D array.
%
% Additional options should be specified in key-value pairs and can be
% 'transform' = 4x4 homogeneous transformation matrix specifying the mapping from
% voxel space to the coordinate system in which the data are plotted.
% 'location' = 1x3 vector specifying a point on the plane which will be plotted
% the coordinates are expressed in the coordinate system in which the
% data will be plotted. location defines the origin of the plane
% 'orientation' = 1x3 vector specifying the direction orthogonal through the plane
% which will be plotted (default = [0 0 1])
% 'srange' =
% 'slicesize' =
% 'nslice' =
%
% See also FT_PLOT_ORTHO, FT_PLOT_SLICE, FT_SOURCEPLOT
% undocumented, these are passed on to FT_PLOT_SLICE
% 'intersectmesh' = triangulated mesh through which the intersection of the plane will be plotted (e.g. cortical sheet)
% 'intersectcolor' = color for the intersection
% Copyrights (C) 2012, Jan-Mathijs Schoffelen
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_plot_montage.m 7139 2012-12-11 12:25:35Z jansch $
transform = ft_getopt(varargin, 'transform', eye(4));
loc = ft_getopt(varargin, 'location');
ori = ft_getopt(varargin, 'orientation');
srange = ft_getopt(varargin, 'slicerange');
slicesize = ft_getopt(varargin, 'slicesize');
nslice = ft_getopt(varargin, 'nslice');
% the intersectmesh and intersectcolor options are passed on to FT_PLOT_SLICE
dointersect = ~isempty(ft_getopt(varargin, 'intersectmesh'));
% set the location if empty
if isempty(loc) && (isempty(transform) || all(all(transform-eye(4)==0)==1))
% go to the middle of the volume if the data seem to be in voxel coordinates
loc = size(dat)./2;
elseif isempty(loc)
% otherwise take the origin of the coordinate system
loc = [0 0 0];
end
% check compatibility of inputs
if size(loc, 1) == 1 && isempty(nslice)
nslice = 20;
elseif size(loc, 1) == 1 && ~isempty(nslice)
% this is not a problem, slice spacing will be determined
elseif size(loc, 1) > 1 && isempty(nslice)
% this is not a problem, number of slices is determined by loc
nslice = size(loc, 1);
elseif size(loc, 1) > 1 && ~isempty(nslice)
if size(loc, 1) ~= nslice
error('you should either specify a set of locations or a single location with a number of slices');
end
end
% set the orientation if empty
if isempty(ori),
ori = [0 0 1];
end
% ensure the ori to have unit norm
for k = 1:size(ori,1)
ori(k,:) = ori(k,:)./norm(ori(k,:));
end
% determine the slice range
if size(loc, 1) == 1 && nslice > 1,
if isempty(srange) || (ischar(srange) && strcmp(srange, 'auto'))
srange = [-50 70];
else
end
loc = repmat(loc, [nslice 1]) + linspace(srange(1),srange(2),nslice)'*ori;
end
% ensure that the ori has the same size as the loc
if size(ori,1)==1 && size(loc,1)>1,
ori = repmat(ori, size(loc,1), 1);
end
div = [ceil(sqrt(nslice)) ceil(sqrt(nslice))];
optarg = varargin;
corners = [inf -inf inf -inf inf -inf]; % get the corners for the axis specification
for k = 1:nslice
% define 'x' and 'y' axis in projection plane, the definition of x and y is more or less arbitrary
[x, y] = projplane(ori(k,:)); % z = ori
% get the transformation matrix to project onto the xy-plane
T = [x(:) y(:) ori(k,:)' loc(k,:)'; 0 0 0 1];
optarg = ft_setopt(optarg, 'location', loc(k,:));
optarg = ft_setopt(optarg, 'orientation', ori(k,:));
ix = mod(k-1, div(1));
iy = floor((k-1)/div(1));
h(k) = ft_plot_slice(dat, optarg{:}); % FIXME is it safe to pass all optinoal inputs?
xtmp = get(h(k), 'xdata');
ytmp = get(h(k), 'ydata');
ztmp = get(h(k), 'zdata');
siz = size(xtmp);
if k==1 && isempty(slicesize)
slicesize = siz;
end
% project the positions onto the xy-plane
pos = [xtmp(:) ytmp(:) ztmp(:)];
pos = warp_apply(inv(T), pos);
xtmp = reshape(pos(:,1), siz);
ytmp = reshape(pos(:,2), siz);
ztmp = reshape(pos(:,3), siz);
% add some offset in the x and y directions to create the montage
offset(1) = iy*(slicesize(1)-1);
offset(2) = ix*(slicesize(2)-1);
% update the specification of the corners of the montage plot
if ~isempty(xtmp)
c1 = offset(1) + min(xtmp(:));
c2 = offset(1) + max(xtmp(:));
c3 = offset(2) + min(ytmp(:));
c4 = offset(2) + max(ytmp(:));
c5 = min(ztmp(:));
c6 = max(ztmp(:));
end
corners = [min(corners(1),c1) max(corners(2),c2) min(corners(3),c3) max(corners(4),c4) min(corners(5),c5) max(corners(6),c6)];
% update the positions
set(h(k), 'ydata', offset(1) + xtmp);
set(h(k), 'xdata', offset(2) + ytmp);
set(h(k), 'zdata', 0 * ztmp);
if dointersect,
if ~exist('pprevious', 'var'), pprevious = []; end
p = setdiff(findobj(gcf, 'type', 'patch'), pprevious);
for kk = 1:numel(p)
xtmp = get(p(kk), 'xdata');
ytmp = get(p(kk), 'ydata');
ztmp = get(p(kk), 'zdata');
siz2 = size(xtmp);
pos = [xtmp(:) ytmp(:) ztmp(:)];
pos = warp_apply(inv(T), pos);
xtmp = reshape(pos(:,1), siz2);
ytmp = reshape(pos(:,2), siz2);
ztmp = reshape(pos(:,3), siz2);
% update the positions
set(p(kk), 'ydata', offset(1) + xtmp);
set(p(kk), 'xdata', offset(2) + ytmp);
set(p(kk), 'zdata', 0 * ztmp);
end
pprevious = [pprevious(:);p(:)];
end
drawnow;
end
set(gcf, 'color', [0 0 0]);
set(gca, 'zlim', [0 1]);
%axis equal;
axis off;
view([0 90]);
axis(corners([3 4 1 2]));
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [x, y] = projplane(z)
[u, s, v] = svd([eye(3) z(:)]);
x = u(:, 2)';
y = u(:, 3)';
|
github
|
philippboehmsturm/antx-master
|
ft_plot_slice.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/ft_plot_slice.m
| 13,140 |
utf_8
|
48a01c38f54d164d078bb54e122bd0e0
|
function [h, T2] = ft_plot_slice(dat, varargin)
% FT_PLOT_SLICE cuts a 2-D slice from a 3-D volume and interpolates if needed
%
% Use as
% ft_plot_slice(dat, ...)
% ft_plot_ortho(dat, mask, ...)
% where dat and mask are equal-sized 3-D arrays.
%
% Additional options should be specified in key-value pairs and can be
% 'transform' = 4x4 homogeneous transformation matrix specifying the mapping from
% voxel space to the coordinate system in which the data are plotted.
% 'location' = 1x3 vector specifying a point on the plane which will be plotted
% the coordinates are expressed in the coordinate system in which the
% data will be plotted. location defines the origin of the plane
% 'orientation' = 1x3 vector specifying the direction orthogonal through the plane
% which will be plotted (default = [0 0 1])
% 'resolution' = number (default = 1)
% 'datmask' = 3D-matrix with the same size as the data matrix, serving as opacitymap
% If the second input argument to the function contains a matrix, this
% will be used as the mask
% 'opacitylim' = 1x2 vector specifying the limits for opacity masking
% 'interpmethod' = string specifying the method for the interpolation, see INTERPN (default = 'nearest')
% 'style' = string, 'flat' or '3D'
% 'colormap' = string, see COLORMAP
% 'colorlim' = 1x2 vector specifying the min and max for the colorscale
%
% See also FT_PLOT_ORTHO, FT_PLOT_MONTAGE, FT_SOURCEPLOT
% undocumented
% 'intersectmesh' = triangulated mesh through which the intersection of the plane will be plotted (e.g. cortical sheet)
% 'intersectcolor' = color for the intersection
% Copyrights (C) 2010, Jan-Mathijs Schoffelen
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_plot_slice.m 7308 2013-01-14 14:53:49Z jansch $
persistent previous_dim X Y Z
% parse first input argument(s). it is either
% (dat, varargin)
% (dat, msk, varargin)
% (dat, [], varargin)
if numel(varargin)>0 && (isempty(varargin{1}) || isnumeric(varargin{1}))
M = varargin{1};
varargin = varargin(2:end);
end
% get the optional input arguments
transform = ft_getopt(varargin, 'transform');
loc = ft_getopt(varargin, 'location');
ori = ft_getopt(varargin, 'orientation', [0 0 1]);
resolution = ft_getopt(varargin, 'resolution', 1);
mask = ft_getopt(varargin, 'datmask');
opacitylim = ft_getopt(varargin, 'opacitylim');
interpmethod = ft_getopt(varargin, 'interpmethod', 'nearest');
cmap = ft_getopt(varargin, 'colormap');
clim = ft_getopt(varargin, 'colorlim');
doscale = ft_getopt(varargin, 'doscale', true); % only scale when necessary (time consuming), i.e. when plotting as grayscale image & when the values are not between 0 and 1
h = ft_getopt(varargin, 'surfhandle', []);
mesh = ft_getopt(varargin, 'intersectmesh');
intersectcolor = ft_getopt(varargin, 'intersectcolor', 'yrgbmyrgbm');
intersectlinewidth = ft_getopt(varargin, 'intersectlinewidth', 2);
intersectlinestyle = ft_getopt(varargin, 'intersectlinestyle');
% convert from yes/no/true/false/0/1 into a proper boolean
doscale = istrue(doscale);
if ~isa(dat, 'double')
dat = cast(dat, 'double');
end
if exist('M', 'var') && isempty(mask)
warning_once('using the mask from the input and not from the varargin list');
mask = M; clear M;
end
% norm normalise the ori vector
ori = ori./sqrt(sum(ori.^2));
% dimensionality of the input data
dim = size(dat);
if isempty(previous_dim),
previous_dim = [0 0 0];
end
% set the location if empty
if isempty(loc) && (isempty(transform) || all(all(transform-eye(4)==0)==1))
loc = dim./2;
elseif isempty(loc)
loc = [0 0 0];
end
% set the transformation matrix if empty
if isempty(transform)
transform = eye(4);
end
% check whether the mesh is ok
dointersect = ~isempty(mesh);
if ~iscell(mesh)
mesh = {mesh};
end
if dointersect
for k = 1:numel(mesh)
if isfield(mesh{k}, 'pos')
% use pos instead of pnt
mesh{k}.pnt = mesh{k}.pos;
mesh{k} = rmfield(mesh{k}, 'pos');
end
if ~isfield(mesh{k}, 'pnt') || ~isfield(mesh{k}, 'tri')
error('the triangulated mesh should be a structure with pnt and tri');
end
end
end
% check whether the mask is ok
domask = ~isempty(mask);
if domask
if ~isequal(size(dat), size(mask))
error('the mask data should have the same dimensions as the functional data');
end
end
% determine whether interpolation is needed
dointerp = false;
dointerp = dointerp || sum(sum(transform-eye(4)))~=0;
dointerp = dointerp || ~all(round(loc)==loc);
dointerp = dointerp || sum(ori)~=1;
dointerp = dointerp || ~(resolution==round(resolution));
% determine the caller function and toggle dointerp to true, if
% ft_plot_slice has been called from ft_plot_montage
% this is necessary for the correct allocation of the persistent variables
st = dbstack;
if ~dointerp && numel(st)>1 && strcmp(st(2).name, 'ft_plot_montage'), dointerp = true; end
% determine the corner points of the volume in voxel and in plotting space
[corner_vox, corner_head] = cornerpoints(dim+1, transform);
if dointerp
%--------cut a slice using interpn
% get voxel indices
if all(dim==previous_dim)
% for speeding up the plotting on subsequent calls
% use persistent variables X Y Z
else
[X, Y, Z] = ndgrid(1:dim(1), 1:dim(2), 1:dim(3));
end
% define 'x' and 'y' axis in projection plane, the definition of x and y is more or less arbitrary
[x, y] = projplane(ori); % z = ori
% project the corner points onto the projection plane
corner_proj = nan(size(corner_head));
for i=1:8
corner = corner_head(i, :);
corner = corner - loc(:)';
corner_x = dot(corner, x);
corner_y = dot(corner, y);
corner_z = 0;
corner_proj(i, :) = [corner_x corner_y corner_z];
end
% determine a tight grid of points in the projection plane
xplane = floor(min(corner_proj(:, 1))):resolution:ceil(max(corner_proj(:, 1)));
yplane = floor(min(corner_proj(:, 2))):resolution:ceil(max(corner_proj(:, 2)));
zplane = 0;
[X2, Y2, Z2] = ndgrid(xplane, yplane, zplane); %2D cartesian grid of projection plane in plane voxels
siz = size(squeeze(X2));
pos = [X2(:) Y2(:) Z2(:)]; clear X2 Y2 Z2;
if false
% this is for debugging
ft_plot_mesh(warp_apply(T2, pos))
ft_plot_mesh(corner_head)
axis on
grid on
xlabel('x')
ylabel('y')
zlabel('z')
end
% get the transformation matrix from plotting space to voxel space
% T1 = inv(transform);
% get the transformation matrix to get the projection plane at the right location and orientation into plotting space
T2 = [x(:) y(:) ori(:) loc(:); 0 0 0 1];
% get the transformation matrix from projection plane to voxel space
% M = T1*T2;
M = transform\T2;
% get the positions of the pixels of the desires plane in voxel space
pos = warp_apply(M, pos);
Xi = reshape(pos(:, 1), siz);
Yi = reshape(pos(:, 2), siz);
Zi = reshape(pos(:, 3), siz);
V = interpn(X, Y, Z, dat, Xi, Yi, Zi, interpmethod);
[V, Xi, Yi, Zi] = tight(V, Xi, Yi, Zi);
siz = size(Xi);
if domask,
Vmask = tight(interpn(X, Y, Z, mask, Xi, Yi, Zi, interpmethod));
end
if ~isempty(Xi)
% now adjust the Xi, Yi and Zi, to allow for the surface object
% convention, where the data point value is defined in the center of each
% square, i.e. the number of elements in each of the dimensions of Xi, Yi
% Zi should be 1 more than the functional data, and they should be displaced
% by half a voxel distance
dx2 = mean(diff(Xi,[],2),2); dx1 = mean(diff(Xi,[],1),1);
dy2 = mean(diff(Yi,[],2),2); dy1 = mean(diff(Yi,[],1),1);
dz2 = mean(diff(Zi,[],2),2); dz1 = mean(diff(Zi,[],1),1);
Xi = [Xi-0.5*dx2*ones(1,siz(2)) Xi(:,end)+0.5*dx2; Xi(end,:)+0.5*dx1 Xi(end,end)+0.5*(dx1(end)+dx2(end))];
Yi = [Yi-0.5*dy2*ones(1,siz(2)) Yi(:,end)+0.5*dy2; Yi(end,:)+0.5*dy1 Yi(end,end)+0.5*(dy1(end)+dy2(end))];
Zi = [Zi-0.5*dz2*ones(1,siz(2)) Zi(:,end)+0.5*dz2; Zi(end,:)+0.5*dz1 Zi(end,end)+0.5*(dz1(end)+dz2(end))];
end
else
%-------cut a slice without interpolation
[x, y] = projplane(ori);
T2 = [x(:) y(:) ori(:) loc(:); 0 0 0 1];
% the '+1' and '-0.5' are needed due to the difference between handling
% of image and surf. Surf color data is defined in the center of each
% square, hence needs axes and coordinate adjustment
if all(ori==[1 0 0]), xplane = loc(1); yplane = 1:(dim(2)+1); zplane = 1:(dim(3)+1); end
if all(ori==[0 1 0]), xplane = 1:(dim(1)+1); yplane = loc(2); zplane = 1:(dim(3)+1); end
if all(ori==[0 0 1]), xplane = 1:(dim(1)+1); yplane = 1:(dim(2)+1); zplane = loc(3); end
[Xi, Yi, Zi] = ndgrid(xplane-0.5, yplane-0.5, zplane-0.5); % coordinate is centre of the voxel, 1-based
siz = size(squeeze(Xi))-1;
Xi = reshape(Xi, siz+1); if numel(xplane)==1, xplane = xplane([1 1]); end;
Yi = reshape(Yi, siz+1); if numel(yplane)==1, yplane = yplane([1 1]); end;
Zi = reshape(Zi, siz+1); if numel(zplane)==1, zplane = zplane([1 1]); end;
V = reshape(dat(xplane(1:end-1), yplane(1:end-1), zplane(1:end-1)), siz);
if domask,
Vmask = reshape(mask(xplane(1:end-1), yplane(1:end-1), zplane(1:end-1)), siz);
end
end
if isempty(cmap),
% treat as gray value: scale and convert to rgb
if doscale
dmin = min(dat(:));
dmax = max(dat(:));
V = (V-dmin)./(dmax-dmin);
clear dmin dmax
end
V(isnan(V)) = 0;
% convert anatomy into RGB values
V = cat(3, V, V, V);
end
if isempty(h),
% get positions of the plane in plotting space
posh = warp_apply(transform, [Xi(:) Yi(:) Zi(:)], 'homogeneous', 1e-8);
if ~isempty(posh)
Xh = reshape(posh(:, 1), siz+1);
Yh = reshape(posh(:, 2), siz+1);
Zh = reshape(posh(:, 3), siz+1);
else
% emulate old behavior, that allowed empty data to be plotted
Xh = [];
Yh = [];
Zh = [];
end
% create surface object
h = surface(Xh, Yh, Zh, V);
else
% update the colordata in the surface object
set(h, 'Cdata', V);
end
set(h, 'linestyle', 'none');
if domask,
set(h, 'FaceAlpha', 'flat');
set(h, 'AlphaDataMapping', 'scaled');
set(h, 'AlphaData', Vmask);
if ~isempty(opacitylim)
alim(opacitylim)
end
end
if dointersect
% determine three points on the plane
inplane = eye(3) - (eye(3) * ori') * ori;
v1 = loc + inplane(1,:);
v2 = loc + inplane(2,:);
v3 = loc + inplane(3,:);
for k = 1:numel(mesh)
[xmesh, ymesh, zmesh] = intersect_plane(mesh{k}.pnt, mesh{k}.tri, v1, v2, v3);
% draw each individual line segment of the intersection
if ~isempty(xmesh),
p(k) = patch(xmesh', ymesh', zmesh', nan(1, size(xmesh,1)));
if ~isempty(intersectcolor), set(p(k), 'EdgeColor', intersectcolor(k)); end
if ~isempty(intersectlinewidth), set(p(k), 'LineWidth', intersectlinewidth); end
if ~isempty(intersectlinestyle), set(p(k), 'LineStyle', intersectlinestyle); end
end
end
end
if ~isempty(cmap)
colormap(cmap);
end
if ~isempty(clim)
caxis(clim);
end
% update the axes to ensure that the whole volume fits
ax = [min(corner_head) max(corner_head)];
axis(ax([1 4 2 5 3 6])-0.5); % reorder into [xmin xmax ymin ymaz zmin zmax]
st = dbstack;
if numel(st)>1,
% ft_plot_slice has been called from another function
% assume the axis settings to be handled there
else
axis equal
axis vis3d
end
% store for future reference
previous_dim = dim;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [x, y] = projplane(z)
[u, s, v] = svd([eye(3) z(:)]);
x = u(:, 2)';
y = u(:, 3)';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [V, Xi, Yi, Zi] = tight(V, Xi, Yi, Zi)
% cut off the nans at the edges
x = sum(~isfinite(V), 1)<size(V, 1);
y = sum(~isfinite(V), 2)<size(V, 2);
V = V(y, x);
if nargin>1, Xi = Xi(y, x); end
if nargin>2, Yi = Yi(y, x); end
if nargin>3, Zi = Zi(y, x); end
|
github
|
philippboehmsturm/antx-master
|
ft_select_range.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/ft_select_range.m
| 14,023 |
utf_8
|
b3a594296f089050fedf2d5771d5715b
|
function ft_select_range(handle, eventdata, varargin)
% FT_SELECT_RANGE is a helper function that can be used as callback function
% in a figure. It allows the user to select a horizontal or a vertical
% range, or one or multiple boxes.
%
% The callback function (and it's arguments) specified in callback is called
% on a left-click inside a selection, or using the right-click context-menu.
% The callback function will have as its first-to-last input argument the range of
% all selections. The last input argument is either empty, or, when using the context
% menu, a label of the item clicked.
% Context menus are shown as the labels presented in the input. When activated,
% the callback function is called, with the last input argument being the label of
% the selection option.
%
% Input arguments:
% event = string, event used as hook.
% callback = function handle or cell-array containing function handle and additional input arguments
% contextmenu = cell-array containing labels shown in right-click menu
% multiple = boolean, allowing multiple selection boxes or not
% xrange = boolean, xrange variable or not
% yrange = boolean, yrange variable or not
% clear = boolean
%
%
% Example use:
% x = randn(10,1);
% y = randn(10,1);
% figure; plot(x, y, '.');
%
% The following example allows multiple horizontal and vertical selections to be made
% set(gcf, 'WindowButtonDownFcn', {@ft_select_range, 'event', 'WindowButtonDownFcn', 'multiple', true, 'callback', @disp});
% set(gcf, 'WindowButtonMotionFcn', {@ft_select_range, 'event', 'WindowButtonMotionFcn', 'multiple', true, 'callback', @disp});
% set(gcf, 'WindowButtonUpFcn', {@ft_select_range, 'event', 'WindowButtonUpFcn', 'multiple', true, 'callback', @disp});
%
% The following example allows a single horizontal selection to be made
% set(gcf, 'WindowButtonDownFcn', {@ft_select_range, 'event', 'WindowButtonDownFcn', 'multiple', false, 'xrange', true, 'yrange', false, 'callback', @disp});
% set(gcf, 'WindowButtonMotionFcn', {@ft_select_range, 'event', 'WindowButtonMotionFcn', 'multiple', false, 'xrange', true, 'yrange', false, 'callback', @disp});
% set(gcf, 'WindowButtonUpFcn', {@ft_select_range, 'event', 'WindowButtonUpFcn', 'multiple', false, 'xrange', true, 'yrange', false, 'callback', @disp});
%
% The following example allows a single point to be selected
% set(gcf, 'WindowButtonDownFcn', {@ft_select_range, 'event', 'WindowButtonDownFcn', 'multiple', false, 'xrange', false, 'yrange', false, 'callback', @disp});
% set(gcf, 'WindowButtonMotionFcn', {@ft_select_range, 'event', 'WindowButtonMotionFcn', 'multiple', false, 'xrange', false, 'yrange', false, 'callback', @disp});
% set(gcf, 'WindowButtonUpFcn', {@ft_select_range, 'event', 'WindowButtonUpFcn', 'multiple', false, 'xrange', false, 'yrange', false, 'callback', @disp});
% Copyright (C) 2009-2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_select_range.m 7366 2013-01-21 13:22:17Z roboos $
% get the optional arguments
event = ft_getopt(varargin, 'event');
callback = ft_getopt(varargin, 'callback');
multiple = ft_getopt(varargin, 'multiple', false);
xrange = ft_getopt(varargin, 'xrange', true);
yrange = ft_getopt(varargin, 'yrange', true);
clear = ft_getopt(varargin, 'clear', false);
contextmenu = ft_getopt(varargin, 'contextmenu'); % this will be displayed following a right mouse click
% convert 'yes/no' string to boolean value
multiple = istrue(multiple);
xrange = istrue(xrange);
yrange = istrue(yrange);
clear = istrue(clear);
p = handle;
while ~isequal(p, 0)
handle = p;
p = get(handle, 'parent');
end
if ishandle(handle)
userData = getappdata(handle, 'select_range_m');
else
userData = [];
end
if isempty(userData)
userData.range = []; % this is a Nx4 matrix with the selection range
userData.box = []; % this is a Nx1 vector with the line handle
end
p = get(gca, 'CurrentPoint');
p = p(1,1:2);
abc = axis;
xLim = abc(1:2);
yLim = abc(3:4);
% limit cursor coordinates
if p(1)<xLim(1), p(1)=xLim(1); end;
if p(1)>xLim(2), p(1)=xLim(2); end;
if p(2)<yLim(1), p(2)=yLim(1); end;
if p(2)>yLim(2), p(2)=yLim(2); end;
% determine whether the user is currently making a selection
selecting = numel(userData.range)>0 && any(isnan(userData.range(end,:)));
pointonly = ~xrange && ~yrange;
if pointonly && multiple
warning('multiple selections are not possible for a point');
multiple = false;
end
% setup contextmenu
if ~isempty(contextmenu)
if isempty(get(handle,'uicontextmenu'))
hcmenu = uicontextmenu;
hcmenuopt = nan(1,numel(contextmenu));
for icmenu = 1:numel(contextmenu)
hcmenuopt(icmenu) = uimenu(hcmenu, 'label', contextmenu{icmenu}, 'callback', {@evalcontextcallback, callback{:}, []}); % empty matrix is placeholder, will be updated to userdata.range
end
end
if ~exist('hcmenuopt','var')
hcmenuopt = get(get(handle,'uicontextmenu'),'children'); % uimenu handles, used for switchen on/off and updating
end
% setting associations for all clickable objects
% this out to be pretty fast, if this is still to slow in some cases, the code below has to be reused
if ~exist('hcmenu','var')
hcmenu = get(handle,'uicontextmenu');
end
set(findobj(handle,'hittest','on'), 'uicontextmenu',hcmenu);
% to be used if above is too slow
% associations only done once. this might be an issue in some cases, cause when a redraw is performed in the original figure (e.g. databrowser), a specific assocations are lost (lines/patches/text)
% set(get(handle,'children'),'uicontextmenu',hcmenu);
% set(findobj(handle,'type','text'), 'uicontextmenu',hcmenu);
% set(findobj(handle,'type','patch'),'uicontextmenu',hcmenu);
% set(findobj(handle,'type','line'), 'uicontextmenu',hcmenu); % fixme: add other often used object types that ft_select_range is called upon
end
% get last-used-mouse-button
lastmousebttn = get(gcf,'selectiontype');
switch lower(event)
case lower('WindowButtonDownFcn')
switch lastmousebttn
case 'normal' % left click
if inSelection(p, userData.range)
% the user has clicked in one of the existing selections
evalCallback(callback, userData.range);
if clear
delete(userData.box(ishandle(userData.box)));
userData.range = [];
userData.box = [];
set(handle, 'Pointer', 'crosshair');
if ~isempty(contextmenu) && ~pointonly
set(hcmenuopt,'enable','off')
end
end
else
if ~multiple
% start with a new selection
delete(userData.box(ishandle(userData.box)));
userData.range = [];
userData.box = [];
end
% add a new selection range
userData.range(end+1,1:4) = nan;
userData.range(end,1) = p(1);
userData.range(end,3) = p(2);
% add a new selection box
xData = [nan nan nan nan nan];
yData = [nan nan nan nan nan];
userData.box(end+1) = line(xData, yData);
end
end
case lower('WindowButtonUpFcn')
switch lastmousebttn
case 'normal' % left click
if selecting
% select the other corner of the box
userData.range(end,2) = p(1);
userData.range(end,4) = p(2);
end
if multiple && ~isempty(userData.range) && ~diff(userData.range(end,1:2)) && ~diff(userData.range(end,3:4))
% start with a new selection
delete(userData.box(ishandle(userData.box)));
userData.range = [];
userData.box = [];
end
if ~isempty(userData.range)
% ensure that the selection is sane
if diff(userData.range(end,1:2))<0
userData.range(end,1:2) = userData.range(end,[2 1]);
end
if diff(userData.range(end,3:4))<0
userData.range(end,3:4) = userData.range(end,[4 3]);
end
if pointonly
% only select a single point
userData.range(end,2) = userData.range(end,1);
userData.range(end,4) = userData.range(end,3);
elseif ~xrange
% only select along the y-axis
userData.range(end,1:2) = [-inf inf];
elseif ~yrange
% only select along the x-axis
userData.range(end,3:4) = [-inf inf];
end
% update contextmenu callbacks
if ~isempty(contextmenu)
updateContextCallback(hcmenuopt, callback, userData.range)
end
end
if pointonly && ~multiple
evalCallback(callback, userData.range);
if clear
delete(userData.box(ishandle(userData.box)));
userData.range = [];
userData.box = [];
set(handle, 'Pointer', 'crosshair');
end
end
end
case lower('WindowButtonMotionFcn')
if selecting && ~pointonly
% update the selection box
if xrange
x1 = userData.range(end,1);
x2 = p(1);
else
x1 = xLim(1);
x2 = xLim(2);
end
if yrange
y1 = userData.range(end,3);
y2 = p(2);
else
y1 = yLim(1);
y2 = yLim(2);
end
xData = [x1 x2 x2 x1 x1];
yData = [y1 y1 y2 y2 y1];
set(userData.box(end), 'xData', xData);
set(userData.box(end), 'yData', yData);
set(userData.box(end), 'Color', [0 0 0]);
set(userData.box(end), 'EraseMode', 'xor');
set(userData.box(end), 'LineStyle', '--');
set(userData.box(end), 'LineWidth', 1.5);
set(userData.box(end), 'Visible', 'on');
else
% update the cursor
if inSelection(p, userData.range)
set(handle, 'Pointer', 'hand');
if ~isempty(contextmenu)
set(hcmenuopt,'enable','on')
end
else
set(handle, 'Pointer', 'crosshair');
if ~isempty(contextmenu)
set(hcmenuopt,'enable','off')
end
end
end
otherwise
error('unexpected event "%s"', event);
end % switch event
% put the modified selections back into the figure
if ishandle(handle)
setappdata(handle, 'select_range_m', userData);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function retval = inSelection(p, range)
if isempty(range)
retval = false;
else
retval = (p(1)>=range(:,1) & p(1)<=range(:,2) & p(2)>=range(:,3) & p(2)<=range(:,4));
retval = any(retval);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function evalCallback(callback, val)
% no context menu item was clicked, set to empty
cmenulab = [];
if ~isempty(callback)
if isa(callback, 'cell')
% the callback specifies a function and additional arguments
funhandle = callback{1};
funargs = callback(2:end);
feval(funhandle, funargs{:}, val, cmenulab);
else
% the callback only specifies a function
funhandle = callback;
feval(funhandle, val);
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function updateContextCallback(hcmenuopt, callback, val)
if ~isempty(callback)
if isa(callback, 'cell')
% the callback specifies a function and additional arguments
funhandle = callback{1};
funargs = callback(2:end);
callback = {funhandle, funargs{:}, val};
else
% the callback only specifies a function
funhandle = callback;
callback = {funhandle, val};
end
for icmenu = 1:numel(hcmenuopt)
set(hcmenuopt(icmenu),'callback',{@evalContextCallback, callback{:}})
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function evalContextCallback(hcmenuopt, eventdata, varargin)
% delete selection box if present
% get parent (uimenu -> uicontextmenu -> parent)
parent = get(get(hcmenuopt,'parent'),'parent'); % fixme: isn't the parent handle always input provided in the callback?
userData = getappdata(parent, 'select_range_m');
if ishandle(userData.box)
if any(~isnan([get(userData.box,'ydata') get(userData.box,'xdata')]))
delete(userData.box(ishandle(userData.box)));
userData.range = [];
userData.box = [];
set(parent, 'Pointer', 'crosshair');
setappdata(parent, 'select_range_m', userData);
end
end
% get contextmenu name
cmenulab = get(hcmenuopt,'label');
if numel(varargin)>1
% the callback specifies a function and additional arguments
funhandle = varargin{1};
funargs = varargin(2:end);
feval(funhandle, funargs{:}, cmenulab);
else
% the callback only specifies a function
funhandle = varargin{1};
feval(funhandle, val, cmenulab);
end
|
github
|
philippboehmsturm/antx-master
|
ft_select_channel.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/ft_select_channel.m
| 5,763 |
utf_8
|
65f75d2a28a115832e61158855e728ff
|
function ft_select_channel(handle, eventdata, varargin)
% FT_SELECT_CHANNEL is a helper function that can be used as callback function
% in a figure. It allows the user to select a channel. The channel labels
% are returned.
%
% Use as
% label = ft_select_channel(h, eventdata, ...)
% The first two arguments are automatically passed by Matlab to any
% callback function.
%
% Additional options should be specified in key-value pairs and can be
% 'callback' = function handle to be executed after channels have been selected
%
% You can pass additional arguments to the callback function in a cell-array
% like {@function_handle,arg1,arg2}
%
% Example
% % create a figure
% lay = ft_prepare_layout([])
% ft_plot_lay(lay)
%
% % add the required guidata
% info = guidata(gcf)
% info.x = lay.pos(:,1);
% info.y = lay.pos(:,2);
% info.label = lay.label
% guidata(gcf, info)
%
% % add this function as the callback to make a single selection
% set(gcf, 'WindowButtonDownFcn', {@ft_select_channel, 'callback', @disp})
%
% % or to make multiple selections
% set(gcf, 'WindowButtonDownFcn', {@ft_select_channel, 'multiple', true, 'callback', @disp, 'event', 'WindowButtonDownFcn'})
% set(gcf, 'WindowButtonUpFcn', {@ft_select_channel, 'multiple', true, 'callback', @disp, 'event', 'WindowButtonDownFcn'})
% set(gcf, 'WindowButtonMotionFcn', {@ft_select_channel, 'multiple', true, 'callback', @disp, 'event', 'WindowButtonDownFcn'})
%
% Subsequently you can click in the figure and you'll see that the disp
% function is executed as callback and that it displays the selected
% channels.
% Copyright (C) 2009, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_select_channel.m 7123 2012-12-06 21:21:38Z roboos $
% get optional input arguments
multiple = ft_getopt(varargin, 'multiple', false);
callback = ft_getopt(varargin, 'callback');
if istrue(multiple)
% the selection is done using select_range, which will subsequently call select_channel_multiple
set(gcf, 'WindowButtonDownFcn', {@ft_select_range, 'multiple', true, 'callback', {@select_channel_multiple, callback}, 'event', 'WindowButtonDownFcn'});
set(gcf, 'WindowButtonUpFcn', {@ft_select_range, 'multiple', true, 'callback', {@select_channel_multiple, callback}, 'event', 'WindowButtonUpFcn'});
set(gcf, 'WindowButtonMotionFcn', {@ft_select_range, 'multiple', true, 'callback', {@select_channel_multiple, callback}, 'event', 'WindowButtonMotionFcn'});
else
% the selection is done using select_channel_single
pos = get(gca, 'CurrentPoint');
pos = pos(1,1:2);
select_channel_single(pos, callback)
end % if multiple
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION to assist in the selection of a single channel
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function select_channel_single(pos, callback)
info = guidata(gcf);
x = info.x;
y = info.y;
label = info.label;
% compute a tolerance measure
distance = sqrt(abs(sum([x y]'.*[x y]',1)));
distance = triu(distance, 1);
distance = distance(:);
distance = distance(distance>0);
distance = median(distance);
tolerance = 0.3*distance;
% compute the distance between the clicked point and all channels
dx = x - pos(1);
dy = y - pos(2);
dd = sqrt(dx.^2 + dy.^2);
[d, i] = min(dd);
if d<tolerance
label = label{i};
fprintf('channel "%s" selected\n', label);
else
label = {};
fprintf('no channel selected\n');
end
% execute the original callback with the selected channel as input argument
if ~isempty(callback)
if isa(callback, 'cell')
% the callback specifies a function and additional arguments
funhandle = callback{1};
funargs = callback(2:end);
feval(funhandle, label, funargs{:});
else
% the callback only specifies a function
funhandle = callback;
feval(funhandle, label);
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION to assist in the selection of multiple channels
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function select_channel_multiple(callback,range,cmenulab) % last input is context menu label, see ft_select_range
info = guidata(gcf);
x = info.x(:);
y = info.y(:);
label = info.label(:);
% determine which channels ly in the selected range
select = false(size(label));
for i=1:size(range,1)
select = select | (x>=range(i, 1) & x<=range(i, 2) & y>=range(i, 3) & y<=range(i, 4));
end
label = label(select);
% execute the original callback with the selected channels as input argument
if any(select)
if ~isempty(callback)
if isa(callback, 'cell')
% the callback specifies a function and additional arguments
funhandle = callback{1};
funargs = callback(2:end);
feval(funhandle, label, funargs{:});
else
% the callback only specifies a function
funhandle = callback;
feval(funhandle, label);
end
end
end
|
github
|
philippboehmsturm/antx-master
|
ft_datatype_sens.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/private/ft_datatype_sens.m
| 8,876 |
utf_8
|
9cca02c1384fde3f0c40f1a5a3a0253a
|
function [sens] = ft_datatype_sens(sens, varargin)
% FT_DATATYPE_SENS describes the FieldTrip structure that represents
% an EEG, ECoG, or MEG sensor array. This structure is commonly called
% "elec" for EEG and "grad" for MEG, or more general "sens" for either
% one.
%
% The structure for MEG gradiometers and/or magnetometers contains
% sens.label = Mx1 cell-array with channel labels
% sens.chanpos = Mx3 matrix with channel positions
% sens.chanori = Mx3 matrix with channel orientations, used for synthetic planar gradient computation
% sens.tra = MxN matrix to combine coils into channels
% sens.coilpos = Nx3 matrix with coil positions
% sens.coilori = Nx3 matrix with coil orientations
% sens.balance = structure containing info about the balancing, See FT_APPLY_MONTAGE
%
% The structure for EEG or ECoG channels contains
% sens.label = Mx1 cell-array with channel labels
% sens.chanpos = Mx3 matrix with channel positions
% sens.tra = MxN matrix to combine electrodes into channels
% sens.elecpos = Nx3 matrix with electrode positions
% In case sens.tra is not present in the EEG sensor array, the channels
% are assumed to be average referenced.
%
% The following fields are optional
% sens.type = string with the MEG or EEG acquisition system, see FT_SENSTYPE
% sens.chantype = Mx1 cell-array with the type of the channel, see FT_CHANTYPE
% sens.chanunit = Mx1 cell-array with the units of the channel signal, e.g. 'T', 'fT' or 'fT/cm'
% sens.fid = structure with fiducial information
%
% Revision history:
%
% (2011v2/latest) The chantype and chanunit have been added for MEG.
%
% (2011v1) To facilitate determining the position of channels (e.g. for plotting)
% in case of balanced MEG or bipolar EEG, an explicit distinction has been made
% between chanpos+chanori and coilpos+coilori (for MEG) and chanpos and elecpos
% (for EEG). The pnt and ori fields are removed
%
% (2010) Added support for bipolar or otherwise more complex linear combinations
% of EEG electrodes using sens.tra, similar to MEG.
%
% (2009) Noice reduction has been added for MEG systems in the balance field.
%
% (2006) The optional fields sens.type and sens.unit were added.
%
% (2003) The initial version was defined, which looked like this for EEG
% sens.pnt = Mx3 matrix with electrode positions
% sens.label = Mx1 cell-array with channel labels
% and like this for MEG
% sens.pnt = Nx3 matrix with coil positions
% sens.ori = Nx3 matrix with coil orientations
% sens.tra = MxN matrix to combine coils into channels
% sens.label = Mx1 cell-array with channel labels
%
% See also FT_READ_SENS, FT_SENSTYPE, FT_CHANTYPE, FT_APPLY_MONTAGE, CTF2GRAD, FIF2GRAD,
% BTI2GRAD, YOKOGAWA2GRAD, ITAB2GRAD
% Copyright (C) 2011, Robert Oostenveld & Jan-Mathijs Schoffelen
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_datatype_sens.m 7248 2012-12-21 11:37:13Z roboos $
% these are for remembering the type on subsequent calls with the same input arguments
persistent previous_argin previous_argout
current_argin = [{sens} varargin];
if isequal(current_argin, previous_argin)
% don't do the whole cheking again, but return the previous output from cache
sens = previous_argout{1};
end
% get the optional input arguments, which should be specified as key-value pairs
version = ft_getopt(varargin, 'version', 'latest');
if strcmp(version, 'latest')
version = '2011v2';
end
if isempty(sens)
return;
end
switch version
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case '2011v2'
% This speeds up subsequent calls to ft_senstype and channelposition.
% However, if it is not more precise than MEG or EEG, don't keep it in
% the output (see further down).
if ~isfield(sens, 'type')
sens.type = ft_senstype(sens);
end
% there are many cases which deal with either eeg or meg
ismeg = ft_senstype(sens, 'meg');
if isfield(sens, 'pnt')
if ismeg
% sensor description is a MEG sensor-array, containing oriented coils
sens.coilpos = sens.pnt; sens = rmfield(sens, 'pnt');
sens.coilori = sens.ori; sens = rmfield(sens, 'ori');
else
% sensor description is something else, EEG/ECoG etc
sens.elecpos = sens.pnt; sens = rmfield(sens, 'pnt');
end
end
if ~isfield(sens, 'chanpos')
if ismeg
% sensor description is a MEG sensor-array, containing oriented coils
[chanpos, chanori, lab] = channelposition(sens, 'channel', 'all');
% the channel order can be different in the two representations
[selsens, selpos] = match_str(sens.label, lab);
sens.chanpos = nan(length(sens.label), 3);
sens.chanori = nan(length(sens.label), 3);
% insert the determined position/orientation on the appropriate rows
sens.chanpos(selsens,:) = chanpos(selpos,:);
sens.chanori(selsens,:) = chanori(selpos,:);
if length(selsens)~=length(sens.label)
warning('cannot determine the position and orientation for all channels');
end
else
% sensor description is something else, EEG/ECoG etc
% note that chanori will be all NaNs
[chanpos, chanori, lab] = channelposition(sens, 'channel', 'all');
% the channel order can be different in the two representations
[selsens, selpos] = match_str(sens.label, lab);
sens.chanpos = nan(length(sens.label), 3);
% insert the determined position/orientation on the appropriate rows
sens.chanpos(selsens,:) = chanpos(selpos,:);
if length(selsens)~=length(sens.label)
warning('cannot determine the position and orientation for all channels');
end
end
end
if ~isfield(sens, 'chantype') || all(strcmp(sens.chantype, 'unknown'))
if ismeg
sens.chantype = ft_chantype(sens);
else
% FIXME for EEG we have not yet figured out how to deal with this
end
end
if ~isfield(sens, 'chanunit') || all(strcmp(sens.chanunit, 'unknown'))
if ismeg
sens.chanunit = ft_chanunit(sens);
else
% FIXME for EEG we have not yet figured out how to deal with this
end
end
if ~isfield(sens, 'unit')
sens = ft_convert_units(sens);
end
if any(strcmp(sens.type, {'meg', 'eeg', 'magnetometer', 'electrode', 'unknown'}))
% this is not sufficiently informative, so better remove it
% see also http://bugzilla.fcdonders.nl/show_bug.cgi?id=1806
sens = rmfield(sens, 'type');
end
if size(sens.chanpos,1)~=length(sens.label) || ...
isfield(sens, 'tra') && size(sens.tra,1)~=length(sens.label) || ...
isfield(sens, 'tra') && isfield(sens, 'elecpos') && size(sens.tra,2)~=size(sens.elecpos,1) || ...
isfield(sens, 'tra') && isfield(sens, 'coilpos') && size(sens.tra,2)~=size(sens.coilpos,1) || ...
isfield(sens, 'tra') && isfield(sens, 'coilori') && size(sens.tra,2)~=size(sens.coilori,1) || ...
isfield(sens, 'chanpos') && size(sens.chanpos,1)~=length(sens.label) || ...
isfield(sens, 'chanori') && size(sens.chanori,1)~=length(sens.label)
error('inconsistent number of channels in sensor description');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
otherwise
error('converting to version %s is not supported', version);
end % switch
% this makes the display with the "disp" command look better
sens = sortfieldnames(sens);
% remember the current input and output arguments, so that they can be
% reused on a subsequent call in case the same input argument is given
current_argout = {sens};
previous_argin = current_argin;
previous_argout = current_argout;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function b = sortfieldnames(a)
fn = sort(fieldnames(a));
for i=1:numel(fn)
b.(fn{i}) = a.(fn{i});
end
|
github
|
philippboehmsturm/antx-master
|
ptriside.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/private/ptriside.m
| 1,257 |
utf_8
|
f52f0beb3731b653116c217b37b673d2
|
function [side] = ptriside(v1, v2, v3, r, tolerance)
% PTRISIDE determines the side of a plane on which a set of points lie. it
% returns 0 for the points that lie on the plane
%
% [side] = ptriside(v1, v2, v3, r)
%
% the side of points r is determined relative to the plane spanned by
% vertices v1, v2 and v3. v1,v2 and v3 should be 1x3 vectors. r should be a
% Nx3 matrix
% Copyright (C) 2002, Robert Oostenveld
%
% $Log: ptriside.m,v $
% Revision 1.3 2003/03/11 15:35:20 roberto
% converted all files from DOS to UNIX
%
% Revision 1.2 2003/03/04 21:46:19 roberto
% added CVS log entry and synchronized all copyright labels
%
if nargin<5
tolerance = 100*eps;
end
n = size(r,1);
a = r - ones(n,1)*v1;
b = v2 - v1;
c = v3 - v1;
d = crossproduct(b, c);
val = dotproduct(a, d);
side = zeros(n, 1);
side(val > tolerance) = 1;
side(val < -tolerance) = -1;
%if val>tolerance
% side=1;
%elseif val<-tolerance
% side=-1;
%else
% side=0;
%end
% subfunction without overhead to speed up
function c = crossproduct(a, b)
c(1) = a(2)*b(3)-a(3)*b(2);
c(2) = a(3)*b(1)-a(1)*b(3);
c(3) = a(1)*b(2)-a(2)*b(1);
% subfunction without overhead to speed up, input a can be a matrix
function d = dotproduct(a, b)
d = a(:,1)*b(1)+a(:,2)*b(2)+a(:,3)*b(3);
|
github
|
philippboehmsturm/antx-master
|
ft_convert_units.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/private/ft_convert_units.m
| 7,014 |
utf_8
|
b6713ad4580d1dac67d2d43489f0dc55
|
function [obj] = ft_convert_units(obj, target)
% FT_CONVERT_UNITS changes the geometrical dimension to the specified SI unit.
% The units of the input object is determined from the structure field
% object.unit, or is estimated based on the spatial extend of the structure,
% e.g. a volume conduction model of the head should be approximately 20 cm large.
%
% Use as
% [object] = ft_convert_units(object, target)
%
% The following input objects are supported
% simple dipole position
% electrode definition
% gradiometer array definition
% volume conductor definition
% dipole grid definition
% anatomical mri
% segmented mri
%
% Possible target units are 'm', 'dm', 'cm ' or 'mm'. If no target units
% are specified, this function will only determine the native geometrical
% units of the object.
%
% See FT_ESTIMATE_UNITS, FT_READ_VOL, FT_READ_SENS
% Copyright (C) 2005-2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_convert_units.m 7337 2013-01-16 15:52:00Z johzum $
% This function consists of three parts:
% 1) determine the input units
% 2) determine the requested scaling factor to obtain the output units
% 3) try to apply the scaling to the known geometrical elements in the input object
if isstruct(obj) && numel(obj)>1
% deal with a structure array
for i=1:numel(obj)
if nargin>1
tmp(i) = ft_convert_units(obj(i), target);
else
tmp(i) = ft_convert_units(obj(i));
end
end
obj = tmp;
return
end
% determine the unit-of-dimension of the input object
if isfield(obj, 'unit') && ~isempty(obj.unit)
% use the units specified in the object
unit = obj.unit;
else
% try to determine the units by looking at the size of the object
if isfield(obj, 'chanpos') && ~isempty(obj.chanpos)
siz = norm(idrange(obj.chanpos));
unit = ft_estimate_units(siz);
elseif isfield(obj, 'pnt') && ~isempty(obj.pnt)
siz = norm(idrange(obj.pnt));
unit = ft_estimate_units(siz);
elseif isfield(obj, 'pos') && ~isempty(obj.pos)
siz = norm(idrange(obj.pos));
unit = ft_estimate_units(siz);
elseif isfield(obj, 'transform') && ~isempty(obj.transform)
% construct the corner points of the volume in voxel and in head coordinates
[pos_voxel, pos_head] = cornerpoints(obj.dim, obj.transform);
siz = norm(idrange(pos_head));
unit = ft_estimate_units(siz);
elseif isfield(obj, 'fid') && isfield(obj.fid, 'pnt') && ~isempty(obj.fid.pnt)
siz = norm(idrange(obj.fid.pnt));
unit = ft_estimate_units(siz);
elseif ft_voltype(obj, 'infinite')
% this is an infinite medium volume conductor, which does not care about units
unit = 'm';
elseif ft_voltype(obj,'singlesphere')
siz = obj.r;
unit = ft_estimate_units(siz);
elseif ft_voltype(obj,'localspheres')
siz = median(obj.r);
unit = ft_estimate_units(siz);
elseif ft_voltype(obj,'concentricspheres')
siz = max(obj.r);
unit = ft_estimate_units(siz);
elseif isfield(obj, 'bnd') && isstruct(obj.bnd) && isfield(obj.bnd(1), 'pnt') && ~isempty(obj.bnd(1).pnt)
siz = norm(idrange(obj.bnd(1).pnt));
unit = ft_estimate_units(siz);
elseif isfield(obj, 'nas') && isfield(obj, 'lpa') && isfield(obj, 'rpa')
pnt = [obj.nas; obj.lpa; obj.rpa];
siz = norm(idrange(pnt));
unit = ft_estimate_units(siz);
else
error('cannot determine geometrical units');
end % recognized type of volume conduction model or sensor array
end % determine input units
if nargin<2 || isempty(target)
% just remember the units in the output and return
obj.unit = unit;
return
elseif strcmp(unit, target)
% no conversion is needed
obj.unit = unit;
return
end
% compue the scaling factor from the input units to the desired ones
scale = scalingfactor(unit, target);
% give some information about the conversion
fprintf('converting units from ''%s'' to ''%s''\n', unit, target)
% volume conductor model
if isfield(obj, 'r'), obj.r = scale * obj.r; end
if isfield(obj, 'o'), obj.o = scale * obj.o; end
if isfield(obj, 'bnd'), for i=1:length(obj.bnd), obj.bnd(i).pnt = scale * obj.bnd(i).pnt; end, end
% gradiometer array
if isfield(obj, 'pnt1'), obj.pnt1 = scale * obj.pnt1; end
if isfield(obj, 'pnt2'), obj.pnt2 = scale * obj.pnt2; end
if isfield(obj, 'prj'), obj.prj = scale * obj.prj; end
% gradiometer array, electrode array, head shape or dipole grid
if isfield(obj, 'pnt'), obj.pnt = scale * obj.pnt; end
if isfield(obj, 'chanpos'), obj.chanpos = scale * obj.chanpos; end
if isfield(obj, 'coilpos'), obj.coilpos = scale * obj.coilpos; end
if isfield(obj, 'elecpos'), obj.elecpos = scale * obj.elecpos; end
% gradiometer array that combines multiple coils in one channel
if isfield(obj, 'tra') && isfield(obj, 'chanunit')
% find the gradiometer channels that are expressed as unit of field strength divided by unit of distance, e.g. T/cm
for i=1:length(obj.chanunit)
tok = tokenize(obj.chanunit{i}, '/');
if length(tok)==1
% assume that it is T or so
elseif length(tok)==2
% assume that it is T/cm or so
obj.tra(i,:) = obj.tra(i,:) / scale;
obj.chanunit{i} = [tok{1} '/' target];
else
error('unexpected units %s', obj.chanunit{i});
end
end % for
end % if
% fiducials
if isfield(obj, 'fid') && isfield(obj.fid, 'pnt'), obj.fid.pnt = scale * obj.fid.pnt; end
% dipole grid
if isfield(obj, 'pos'), obj.pos = scale * obj.pos; end
% anatomical MRI or functional volume
if isfield(obj, 'transform'),
H = diag([scale scale scale 1]);
obj.transform = H * obj.transform;
end
if isfield(obj, 'transformorig'),
H = diag([scale scale scale 1]);
obj.transformorig = H * obj.transformorig;
end
% remember the unit
obj.unit = target;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% IDRANGE interdecile range for more robust range estimation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function r = idrange(x)
keeprow=true(size(x,1),1);
for l=1:size(x,2)
keeprow = keeprow & isfinite(x(:,l));
end
sx = sort(x(keeprow,:), 1);
ii = round(interp1([0, 1], [1, size(x(keeprow,:), 1)], [.1, .9])); % indices for 10 & 90 percentile
r = diff(sx(ii, :));
|
github
|
philippboehmsturm/antx-master
|
ft_apply_montage.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/private/ft_apply_montage.m
| 13,440 |
utf_8
|
4d1063ba5c92c5b8e6c094a1e2b611dd
|
function [input] = ft_apply_montage(input, montage, varargin)
% FT_APPLY_MONTAGE changes the montage of an electrode or gradiometer array. A
% montage can be used for EEG rereferencing, MEG synthetic gradients, MEG
% planar gradients or unmixing using ICA. This function applies the montage
% to the inputor array. The inputor array can subsequently be used for
% forward computation and source reconstruction of the data.
%
% Use as
% [sens] = ft_apply_montage(sens, montage, ...)
% [data] = ft_apply_montage(data, montage, ...)
% [freq] = ft_apply_montage(freq, montage, ...)
% [montage] = ft_apply_montage(montage1, montage2, ...)
%
% A montage is specified as a structure with the fields
% montage.tra = MxN matrix
% montage.labelnew = Mx1 cell-array
% montage.labelorg = Nx1 cell-array
%
% As an example, a bipolar montage could look like this
% bipolar.labelorg = {'1', '2', '3', '4'}
% bipolar.labelnew = {'1-2', '2-3', '3-4'}
% bipolar.tra = [
% +1 -1 0 0
% 0 +1 -1 0
% 0 0 +1 -1
% ];
%
% Additional options should be specified in key-value pairs and can be
% 'keepunused' string, 'yes' or 'no' (default = 'no')
% 'inverse' string, 'yes' or 'no' (default = 'no')
%
% If the first input is a montage, then the second input montage will be
% applied to the first. In effect, the output montage will first do
% montage1, then montage2.
%
% See also FT_READ_SENS, FT_TRANSFORM_SENS
% Copyright (C) 2008-2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_apply_montage.m 7393 2013-01-23 14:33:27Z jorhor $
% get optional input arguments
keepunused = ft_getopt(varargin, 'keepunused', 'no');
inverse = ft_getopt(varargin, 'inverse', 'no');
feedback = ft_getopt(varargin, 'feedback', 'text');
bname = ft_getopt(varargin, 'balancename', '');
if ~isfield(input, 'label') && isfield(input, 'labelnew')
% the input data structure is also a montage
inputlabel = input.labelnew;
else
% the input should describe the channel labels
inputlabel = input.label;
end
% check the consistency of the input inputor array or data
if ~all(isfield(montage, {'tra', 'labelorg', 'labelnew'}))
error('the second input argument does not correspond to a montage');
end
% check the consistency of the montage
if size(montage.tra,1)~=length(montage.labelnew)
error('the number of channels in the montage is inconsistent');
elseif size(montage.tra,2)~=length(montage.labelorg)
error('the number of channels in the montage is inconsistent');
end
if strcmp(inverse, 'yes')
% apply the inverse montage, i.e. undo a previously applied montage
tmp.labelnew = montage.labelorg; % swap around
tmp.labelorg = montage.labelnew; % swap around
tmp.tra = full(montage.tra);
if rank(tmp.tra) < length(tmp.tra)
warning('the linear projection for the montage is not full-rank, the resulting data will have reduced dimensionality');
tmp.tra = pinv(tmp.tra);
else
tmp.tra = inv(tmp.tra);
end
montage = tmp;
end
% use default transfer from sensors to channels if not specified
if isfield(input, 'pnt') && ~isfield(input, 'tra')
nchan = size(input.pnt,1);
input.tra = eye(nchan);
elseif isfield(input, 'chanpos') && ~isfield(input, 'tra')
nchan = size(input.chanpos,1);
input.tra = eye(nchan);
end
% select and keep the columns that are non-empty, i.e. remove the empty columns
selcol = find(~all(montage.tra==0, 1));
montage.tra = montage.tra(:,selcol);
montage.labelorg = montage.labelorg(selcol);
clear selcol
% select and remove the columns corresponding to channels that are not present in the original data
remove = setdiff(montage.labelorg, intersect(montage.labelorg, inputlabel));
selcol = match_str(montage.labelorg, remove);
% we cannot just remove the colums, all rows that depend on it should also be removed
selrow = false(length(montage.labelnew),1);
for i=1:length(selcol)
selrow = selrow & (montage.tra(:,selcol(i))~=0);
end
% convert from indices to logical vector
selcol = indx2logical(selcol, length(montage.labelorg));
% remove rows and columns
montage.labelorg = montage.labelorg(~selcol);
montage.labelnew = montage.labelnew(~selrow);
montage.tra = montage.tra(~selrow, ~selcol);
clear remove selcol selrow i
% add columns for the channels that are present in the data but not involved in the montage, and stick to the original order in the data
[add, ix] = setdiff(inputlabel, montage.labelorg);
add = inputlabel(sort(ix));
m = size(montage.tra,1);
n = size(montage.tra,2);
k = length(add);
if strcmp(keepunused, 'yes')
% add the channels that are not rereferenced to the input and output
montage.tra((m+(1:k)),(n+(1:k))) = eye(k);
montage.labelorg = cat(1, montage.labelorg(:), add(:));
montage.labelnew = cat(1, montage.labelnew(:), add(:));
else
% add the channels that are not rereferenced to the input montage only
montage.tra(:,(n+(1:k))) = zeros(m,k);
montage.labelorg = cat(1, montage.labelorg(:), add(:));
end
clear add m n k
% determine whether all channels are unique
m = size(montage.tra,1);
n = size(montage.tra,2);
if length(unique(montage.labelnew))~=m
error('not all output channels of the montage are unique');
end
if length(unique(montage.labelorg))~=n
error('not all input channels of the montage are unique');
end
% determine whether all channels that have to be rereferenced are available
if length(intersect(inputlabel, montage.labelorg))~=length(montage.labelorg)
error('not all channels that are required in the montage are available in the data');
end
% reorder the columns of the montage matrix
[selinput, selmontage] = match_str(inputlabel, montage.labelorg);
montage.tra = double(montage.tra(:,selmontage));
montage.labelorg = montage.labelorg(selmontage);
% making the tra matrix sparse will speed up subsequent multiplications
% but should not result in a sparse matrix
if size(montage.tra,1)>1
montage.tra = sparse(montage.tra);
end
inputtype = 'unknown';
if isfield(input, 'labelorg') && isfield(input, 'labelnew')
inputtype = 'montage';
elseif isfield(input, 'tra')
inputtype = 'sens';
elseif isfield(input, 'trial')
inputtype = 'raw';
elseif isfield(input, 'fourierspctrm')
inputtype = 'freq';
end
switch inputtype
case 'montage'
% apply the montage on top of the other montage
if isa(input.tra, 'single')
% sparse matrices and single precision do not match
input.tra = full(montage.tra) * input.tra;
else
input.tra = montage.tra * input.tra;
end
input.labelnew = montage.labelnew;
case 'sens'
% apply the montage to an electrode or gradiometer description
sens = input;
clear input
% apply the montage to the inputor array
if isa(sens.tra, 'single')
% sparse matrices and single precision do not match
sens.tra = full(montage.tra) * sens.tra;
else
sens.tra = montage.tra * sens.tra;
end
% The montage operates on the coil weights in sens.tra, but the output
% channels can be different. If possible, we want to keep the original
% channel positions and orientations.
[sel1, sel2] = match_str(montage.labelnew, inputlabel);
keepchans = length(sel1)==length(montage.labelnew);
if isfield(sens, 'chanpos')
if keepchans
sens.chanpos = sens.chanpos(sel2,:);
else
sens.chanpos = nan(numel(montage.labelnew),3);
%input = rmfield(input, 'chanpos');
end
end
if isfield(sens, 'chanori')
if keepchans
sens.chanori = sens.chanori(sel2,:);
else
sens.chanori = nan(numel(montage.labelnew),3);
%input = rmfield(input, 'chanori');
end
end
sens.label = montage.labelnew;
% keep track of the order of the balancing and which one is the current one
if strcmp(inverse, 'yes')
if isfield(sens, 'balance')% && isfield(sens.balance, 'previous')
if isfield(sens.balance, 'previous') && numel(sens.balance.previous)>=1
sens.balance.current = sens.balance.previous{1};
sens.balance.previous = sens.balance.previous(2:end);
elseif isfield(sens.balance, 'previous')
sens.balance.current = 'none';
sens.balance = rmfield(sens.balance, 'previous');
else
sens.balance.current = 'none';
end
end
elseif ~strcmp(inverse, 'yes') && ~isempty(bname)
if isfield(sens, 'balance'),
% check whether a balancing montage with name bname already exist,
% and if so, how many
mnt = fieldnames(sens.balance);
sel = strmatch(bname, mnt);
if numel(sel)==0,
% bname can stay the same
elseif numel(sel)==1
% the original should be renamed to 'bname1' and the new one should
% be 'bname2'
sens.balance.([bname, '1']) = sens.balance.(bname);
sens.balance = rmfield(sens.balance, bname);
if isfield(sens.balance, 'current') && strcmp(sens.balance.current, bname)
sens.balance.current = [bname, '1'];
end
if isfield(sens.balance, 'previous')
sel2 = strmatch(bname, sens.balance.previous);
if ~isempty(sel2)
sens.balance.previous{sel2} = [bname, '1'];
end
end
bname = [bname, '2'];
else
bname = [bname, num2str(length(sel)+1)];
end
end
if isfield(sens, 'balance') && isfield(sens.balance, 'current')
if ~isfield(sens.balance, 'previous')
sens.balance.previous = {};
end
sens.balance.previous = [{sens.balance.current} sens.balance.previous];
sens.balance.current = bname;
sens.balance.(bname) = montage;
end
end
% rename the output variable
input = sens;
clear sens
case 'raw';
% apply the montage to the raw data that was preprocessed using fieldtrip
data = input;
clear input
Ntrials = numel(data.trial);
ft_progress('init', feedback, 'processing trials');
for i=1:Ntrials
ft_progress(i/Ntrials, 'processing trial %d from %d\n', i, Ntrials);
if isa(data.trial{i}, 'single')
% sparse matrices and single precision do not match
data.trial{i} = full(montage.tra) * data.trial{i};
else
data.trial{i} = montage.tra * data.trial{i};
end
end
ft_progress('close');
data.label = montage.labelnew;
% rename the output variable
input = data;
clear data
case 'freq'
% apply the montage to the spectrally decomposed data
freq = input;
clear input
if strcmp(freq.dimord, 'rpttap_chan_freq')
siz = size(freq.fourierspctrm);
nrpt = siz(1);
nchan = siz(2);
nfreq = siz(3);
output = zeros(nrpt, size(montage.tra,1), nfreq);
for foilop=1:nfreq
output(:,:,foilop) = freq.fourierspctrm(:,:,foilop) * montage.tra';
end
elseif strcmp(freq.dimord, 'rpttap_chan_freq_time')
siz = size(freq.fourierspctrm);
nrpt = siz(1);
nchan = siz(2);
nfreq = siz(3);
ntime = siz(4);
output = zeros(nrpt, size(montage.tra,1), nfreq, ntime);
for foilop=1:nfreq
for toilop = 1:ntime
output(:,:,foilop,toilop) = freq.fourierspctrm(:,:,foilop,toilop) * montage.tra';
end
end
else
error('unsupported dimord in frequency data (%s)', freq.dimord);
end
% replace the Fourier spectrum
freq.fourierspctrm = output;
freq.label = montage.labelnew;
% rename the output variable
input = freq;
clear freq
otherwise
error('unrecognized input');
end % switch inputtype
% check whether the input contains chantype and/or chanunit and remove these
% as they may have been invalidated by the transform (e.g. with megplanar)
[sel1, sel2] = match_str(montage.labelnew, inputlabel);
keepchans = (length(sel1)==length(montage.labelnew));
if isfield(input, 'chantype')
if keepchans
% reorder them according to the montage
sens.chantype = input.chantype(sel2,:);
else
input = rmfield(input, 'chantype');
end
end
if isfield(input, 'chanunit')
if keepchans
% reorder them according to the montage
sens.chanunit = input.chanunit(sel2,:);
else
input = rmfield(input, 'chanunit');
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% HELPER FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function y = indx2logical(x, n)
y = false(1,n);
y(x) = true;
|
github
|
philippboehmsturm/antx-master
|
select3dtool.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/private/select3dtool.m
| 2,713 |
utf_8
|
fdf7d572638e6ebd059c63f233d26704
|
function select3dtool(arg)
%SELECT3DTOOL A simple tool for interactively obtaining 3-D coordinates
%
% SELECT3DTOOL(FIG) Specify figure handle
%
% Example:
% surf(peaks);
% select3dtool;
% % click on surface
if nargin<1
arg = gcf;
end
if ~ishandle(arg)
feval(arg);
return;
end
%% initialize gui %%
fig = arg;
figure(fig);
uistate = uiclearmode(fig);
[tool, htext] = createUI;
hmarker1 = line('marker','o','markersize',10,'markerfacecolor','k','erasemode','xor','visible','off');
hmarker2 = line('marker','o','markersize',10,'markerfacecolor','r','erasemode','xor','visible','off');
state.uistate = uistate;
state.text = htext;
state.tool = tool;
state.fig = fig;
state.marker1 = hmarker1;
state.marker2 = hmarker2;
setappdata(fig,'select3dtool',state);
setappdata(state.tool,'select3dhost',fig);
set(fig,'windowbuttondownfcn','select3dtool(''click'')');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function off
state = getappdata(gcbf,'select3dtool');
if ~isempty(state)
delete(state.tool);
end
fig = getappdata(gcbf,'select3dhost');
if ~isempty(fig) & ishandle(fig)
state = getappdata(fig,'select3dtool');
uirestore(state.uistate);
delete(state.marker1);
delete(state.marker2);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function click
[p v vi] = select3d;
state = getappdata(gcbf,'select3dtool');
if ~ishandle(state.text)
state.text = createUI;
end
if ~ishandle(state.marker1)
state.marker1 = [];
end
if ~ishandle(state.marker2)
state.marker2 = [];
end
setappdata(state.fig,'select3dtool',state);
if isempty(v)
v = [nan nan nan];
vi = nan;
set(state.marker2,'visible','off');
else
set(state.marker2,'visible','on','xdata',v(1),'ydata',v(2),'zdata',v(3));
end
if isempty(p)
p = [nan nan nan];
set(state.marker1,'visible','off');
else
set(state.marker1,'visible','on','xdata',p(1),'ydata',p(2),'zdata',p(3));
end
% Update tool and markers
set(state.text,'string',createString(p(1),p(2),p(3),v(1),v(2),v(3),vi));
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [fig, h] = createUI
pos = [200 200 200 200];
% Create selection tool %
fig = figure('handlevisibility','off','menubar','none','resize','off',...
'numbertitle','off','name','Select 3-D Tool','position',pos,'deletefcn','select3dtool(''off'')');
h = uicontrol('style','text','parent',fig,'string',createString(0,0,0,0,0,0,0),...
'units','norm','position',[0 0 1 1],'horizontalalignment','left');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [str] = createString(px,py,pz,vx,vy,vz,vi)
str = sprintf(' Position:\n X %f\n Y: %f\n Z: %f \n\n Vertex:\n X: %f\n Y: %f\n Z: %f \n\n Vertex Index:\n %d',px,py,pz,vx,vy,vz,vi);
|
github
|
philippboehmsturm/antx-master
|
warning_once.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/private/warning_once.m
| 3,832 |
utf_8
|
07dc728273934663973f4c716e7a3a1c
|
function [ws warned] = warning_once(varargin)
%
% Use as one of the following
% warning_once(string)
% warning_once(string, timeout)
% warning_once(id, string)
% warning_once(id, string, timeout)
% where timeout should be inf if you don't want to see the warning ever
% again. The default timeout value is 60 seconds.
%
% It can be used instead of the MATLAB built-in function WARNING, thus as
% s = warning_once(...)
% or as
% warning_once(s)
% where s is a structure with fields 'identifier' and 'state', storing the
% state information. In other words, warning_once accepts as an input the
% same structure it returns as an output. This returns or restores the
% states of warnings to their previous values.
%
% It can also be used as
% [s w] = warning_once(...)
% where w is a boolean that indicates whether a warning as been thrown or not.
%
% Please note that you can NOT use it like this
% warning_once('the value is %d', 10)
% instead you should do
% warning_once(sprintf('the value is %d', 10))
% Copyright (C) 2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: warning_once.m 7123 2012-12-06 21:21:38Z roboos $
persistent stopwatch previous
if nargin < 1
error('You need to specify at least a warning message');
end
warned = false;
if isstruct(varargin{1})
warning(varargin{1});
return;
end
% put the arguments we will pass to warning() in this cell array
warningArgs = {};
if nargin==3
% calling syntax (id, msg, timeout)
warningArgs = varargin(1:2);
timeout = varargin{3};
fname = [warningArgs{1} '_' warningArgs{2}];
elseif nargin==2 && isnumeric(varargin{2})
% calling syntax (msg, timeout)
warningArgs = varargin(1);
timeout = varargin{2};
fname = warningArgs{1};
elseif nargin==2 && ~isnumeric(varargin{2})
% calling syntax (id, msg)
warningArgs = varargin(1:2);
timeout = 60;
fname = [warningArgs{1} '_' warningArgs{2}];
elseif nargin==1
% calling syntax (msg)
warningArgs = varargin(1);
timeout = 60; % default timeout in seconds
fname = [warningArgs{1}];
end
if isempty(timeout)
error('Timeout ill-specified');
end
if isempty(stopwatch)
stopwatch = tic;
end
if isempty(previous)
previous = struct;
end
now = toc(stopwatch); % measure time since first function call
fname = decomma(fixname(fname)); % make a nice string that is allowed as structure fieldname
if length(fname) > 63 % MATLAB max name
fname = fname(1:63);
end
if ~isfield(previous, fname) || ...
(isfield(previous, fname) && now>previous.(fname).timeout)
% warning never given before or timed out
ws = warning(warningArgs{:});
previous.(fname).timeout = now+timeout;
previous.(fname).ws = ws;
warned = true;
else
% the warning has been issued before, but has not timed out yet
ws = previous.(fname).ws;
end
end % function
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% helper functions
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function name = decomma(name)
name(name==',')=[];
end % function
|
github
|
philippboehmsturm/antx-master
|
mesh2edge.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/private/mesh2edge.m
| 3,404 |
utf_8
|
cf32ba7233084e32af5fc6057ab2bba5
|
function [newbnd] = mesh2edge(bnd)
% MESH2EDGE finds the edge lines from a triangulated mesh or the edge surfaces
% from a tetrahedral or hexahedral mesh.
%
% Use as
% [bnd] = mesh2edge(bnd)
% Copyright (C) 2013, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: mesh2edge.m 7372 2013-01-23 09:15:52Z roboos $
if isfield(bnd, 'tri')
% make a list of all edges
edge1 = bnd.tri(:, [1 2]);
edge2 = bnd.tri(:, [2 3]);
edge3 = bnd.tri(:, [3 1]);
edge = cat(1, edge1, edge2, edge3);
elseif isfield(bnd, 'tet')
% make a list of all triangles that form the tetraheder
tri1 = bnd.tet(:, [1 2 3]);
tri2 = bnd.tet(:, [2 3 4]);
tri3 = bnd.tet(:, [3 4 1]);
tri4 = bnd.tet(:, [4 1 2]);
edge = cat(1, tri1, tri2, tri3, tri4);
elseif isfield(bnd, 'hex')
% make a list of all "squares" that form the cube/hexaheder
% FIXME should be checked, this is impossible without a drawing
square1 = bnd.hex(:, [1 2 3 4]);
square2 = bnd.hex(:, [5 6 7 8]);
square3 = bnd.hex(:, [1 2 6 5]);
square4 = bnd.hex(:, [2 3 7 6]);
square5 = bnd.hex(:, [3 4 8 7]);
square6 = bnd.hex(:, [4 1 5 8]);
edge = cat(1, square1, square2, square3, square4, square5, square6);
end % isfield(bnd)
% soort all polygons in the same direction
% keep the original as "edge" and the sorted one as "sedge"
sedge = sort(edge, 2);
% % find the edges that are not shared -> count the number of occurences
% n = size(sedge,1);
% occurences = ones(n,1);
% for i=1:n
% for j=(i+1):n
% if all(sedge(i,:)==sedge(j,:))
% occurences(i) = occurences(i)+1;
% occurences(j) = occurences(j)+1;
% end
% end
% end
%
% % make the selection in the original, not the sorted version of the edges
% % otherwise the orientation of the edges might get flipped
% edge = edge(occurences==1,:);
% find the edges that are not shared
indx = findsingleoccurringrows(sedge);
edge = edge(indx, :);
% the naming of the output edges depends on what they represent
newbnd.pnt = bnd.pnt;
if isfield(bnd, 'tri')
newbnd.line = edge;
elseif isfield(bnd, 'tet')
newbnd.tri = edge;
elseif isfield(bnd, 'hex')
newbnd.poly = edge;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION, see http://bugzilla.fcdonders.nl/show_bug.cgi?id=1833#c12
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function indx = findsingleoccurringrows(X)
[X, indx] = sortrows(X);
sel = any(diff([X(1,:)-1; X],1),2) & any(diff([X; X(end,:)+1],1),2);
indx = indx(sel);
function indx = finduniquerows(X)
[X, indx] = sortrows(X);
sel = any(diff([X(1,:)-1; X],1),2);
indx = indx(sel);
|
github
|
philippboehmsturm/antx-master
|
intersect_plane.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/private/intersect_plane.m
| 2,894 |
utf_8
|
a79090a28892db20b0e30635228e2ac4
|
function [X, Y, Z, pnt1, dhk1, pnt2, dhk2] = intersect_plane(pnt, dhk, v1, v2, v3)
% INTERSECT_PLANE intersection between a triangulated surface and a plane
% it returns the coordinates of the vertices which form a contour
% % Use as
% [X, Y, Z] = intersect_plane(pnt, dhk, v1, v2, v3)
%
% where the intersecting plane is spanned by the vertices v1, v2, v3
% and the return values are each Nx2 for the N line segments.
% Copyright (C) 2002-2012, Robert Oostenveld
%
% $Id: intersect_plane.m 7123 2012-12-06 21:21:38Z roboos $
npnt = size(pnt,1);
ndhk = size(dhk,1);
% side = zeros(npnt,1);
% for i=1:npnt
% side(i) = ptriside(v1, v2, v3, pnt(i,:));
% end
side = ptriside(v1, v2, v3, pnt);
% find the triangles which have vertices on both sides of the plane
indx = find(abs(sum(side(dhk),2))~=3);
cnt1 = zeros(length(indx), 3);
cnt2 = zeros(length(indx), 3);
for i=1:length(indx)
cur = dhk(indx(i),:);
tmp = side(cur);
l1 = pnt(cur(1),:);
l2 = pnt(cur(2),:);
l3 = pnt(cur(3),:);
if tmp(1)==tmp(2)
% plane intersects two sides of the triangle
cnt1(i,:) = ltrisect(v1, v2, v3, l3, l1);
cnt2(i,:) = ltrisect(v1, v2, v3, l3, l2);
elseif tmp(1)==tmp(3)
cnt1(i,:) = ltrisect(v1, v2, v3, l2, l1);
cnt2(i,:) = ltrisect(v1, v2, v3, l2, l3);
elseif tmp(2)==tmp(3)
cnt1(i,:) = ltrisect(v1, v2, v3, l1, l2);
cnt2(i,:) = ltrisect(v1, v2, v3, l1, l3);
elseif tmp(1)==0 && tmp(2)==0
% two vertices of the triangle lie on the plane
cnt1(i,:) = l1;
cnt2(i,:) = l2;
elseif tmp(1)==0 && tmp(3)==0
cnt1(i,:) = l1;
cnt2(i,:) = l3;
elseif tmp(2)==0 && tmp(3)==0
cnt1(i,:) = l2;
cnt2(i,:) = l3;
elseif tmp(1)==0 && tmp(2)~=tmp(3)
% one vertex of the triangle lies on the plane
cnt1(i,:) = l1;
cnt2(i,:) = ltrisect(v1, v2, v3, l2, l3);
elseif tmp(2)==0 && tmp(3)~=tmp(1)
cnt1(i,:) = l2;
cnt2(i,:) = ltrisect(v1, v2, v3, l3, l1);
elseif tmp(3)==0 && tmp(1)~=tmp(2)
cnt1(i,:) = l3;
cnt2(i,:) = ltrisect(v1, v2, v3, l1, l2);
elseif tmp(1)==0
cnt1(i,:) = l1;
cnt2(i,:) = l1;
elseif tmp(2)==0
cnt1(i,:) = l2;
cnt2(i,:) = l2;
elseif tmp(3)==0
cnt1(i,:) = l3;
cnt2(i,:) = l3;
end
end
X = [cnt1(:,1) cnt2(:,1)];
Y = [cnt1(:,2) cnt2(:,2)];
Z = [cnt1(:,3) cnt2(:,3)];
if nargout>3
% also output the two meshes on either side of the plane
indx1 = find(side==1);
pnt1 = pnt(indx1,:);
sel1 = sum(ismember(dhk, indx1), 2)==3;
dhk1 = dhk(sel1,:);
dhk1 = tri_reindex(dhk1);
indx2 = find(side==-1);
pnt2 = pnt(indx2,:);
sel2 = sum(ismember(dhk, indx2), 2)==3;
dhk2 = dhk(sel2,:);
dhk2 = tri_reindex(dhk2);
end
function [newtri] = tri_reindex(tri)
%this function reindexes tri such that they run from 1:number of unique vertices
newtri = tri;
[srt, indx] = sort(tri(:));
tmp = cumsum(double(diff([0;srt])>0));
newtri(indx) = tmp;
|
github
|
philippboehmsturm/antx-master
|
inside_contour.m
|
.m
|
antx-master/xspm8/external/fieldtrip/plotting/private/inside_contour.m
| 1,106 |
utf_8
|
37d10e5d9a05c79551aac24c328e34aa
|
function bool = inside_contour(pos, contour);
npos = size(pos,1);
ncnt = size(contour,1);
x = pos(:,1);
y = pos(:,2);
minx = min(x);
miny = min(y);
maxx = max(x);
maxy = max(y);
bool = true(npos,1);
bool(x<minx) = false;
bool(y<miny) = false;
bool(x>maxx) = false;
bool(y>maxy) = false;
% the summed angle over the contour is zero if the point is outside, and 2*pi if the point is inside the contour
% leave some room for inaccurate f
critval = 0.1;
% the remaining points have to be investigated with more attention
sel = find(bool);
for i=1:length(sel)
contourx = contour(:,1) - pos(sel(i),1);
contoury = contour(:,2) - pos(sel(i),2);
angle = atan2(contoury, contourx);
% angle = unwrap(angle);
angle = my_unwrap(angle);
total = sum(diff(angle));
bool(sel(i)) = (abs(total)>critval);
end
function x = my_unwrap(x)
% this is a faster implementation of the MATLAB unwrap function
% with hopefully the same functionality
d = diff(x);
indx = find(abs(d)>pi);
for i=indx(:)'
if d(i)>0
x((i+1):end) = x((i+1):end) - 2*pi;
else
x((i+1):end) = x((i+1):end) + 2*pi;
end
end
|
github
|
philippboehmsturm/antx-master
|
ft_specest_mtmconvol.m
|
.m
|
antx-master/xspm8/external/fieldtrip/specest/ft_specest_mtmconvol.m
| 18,784 |
utf_8
|
72b84d395f1269a44bba64c70c978ee4
|
function [spectrum,ntaper,freqoi,timeoi] = ft_specest_mtmconvol(dat, time, varargin)
% FT_SPECEST_MTMCONVOL performs wavelet convolution in the time domain
% by multiplication in the frequency domain
%
% Use as
% [spectrum,freqoi,timeoi] = specest_mtmconvol(dat,time,...)
% where
% dat = matrix of chan*sample
% time = vector, containing time in seconds for each sample
% spectrum = matrix of ntaper*chan*freqoi*timeoi of fourier coefficients
% ntaper = vector containing the number of tapers per freqoi
% freqoi = vector of frequencies in spectrum
% timeoi = vector of timebins in spectrum
%
% Optional arguments should be specified in key-value pairs and can include:
% taper = 'dpss', 'hanning' or many others, see WINDOW (default = 'dpss')
% pad = number, indicating time-length of data to be padded out to in seconds
% padtype = string, indicating type of padding to be used (see ft_preproc_padding, default: zero)
% timeoi = vector, containing time points of interest (in seconds)
% timwin = vector, containing length of time windows (in seconds)
% freqoi = vector, containing frequencies (in Hz)
% tapsmofrq = number, the amount of spectral smoothing through multi-tapering. Note: 4 Hz smoothing means plus-minus 4 Hz, i.e. a 8 Hz smoothing box
% dimord = 'tap_chan_freq_time' (default) or 'chan_time_freqtap' for
% memory efficiency
% verbose = output progress to console (0 or 1, default 1)
% taperopt = additional taper options to be used in the WINDOW function, see WINDOW
% polyorder = number, the order of the polynomial to fitted to and removed from the data
% prior to the fourier transform (default = 0 -> remove DC-component)
%
% See also FT_FREQANALYSIS, FT_SPECEST_MTMFFT, FT_SPECEST_TFR, FT_SPECEST_HILBERT, FT_SPECEST_WAVELET
% Copyright (C) 2010, Donders Institute for Brain, Cognition and Behaviour
%
% $Id: ft_specest_mtmconvol.m 7123 2012-12-06 21:21:38Z roboos $
% these are for speeding up computation of tapers on subsequent calls
persistent previous_argin previous_wltspctrm
% get the optional input arguments
taper = ft_getopt(varargin, 'taper', 'dpss');
pad = ft_getopt(varargin, 'pad');
padtype = ft_getopt(varargin, 'padtype', 'zero');
timeoi = ft_getopt(varargin, 'timeoi', 'all');
timwin = ft_getopt(varargin, 'timwin');
freqoi = ft_getopt(varargin, 'freqoi', 'all');
tapsmofrq = ft_getopt(varargin, 'tapsmofrq');
dimord = ft_getopt(varargin, 'dimord', 'tap_chan_freq_time');
fbopt = ft_getopt(varargin, 'feedback');
verbose = ft_getopt(varargin, 'verbose', true);
polyorder = ft_getopt(varargin, 'polyorder', 0);
tapopt = ft_getopt(varargin, 'taperopt');
if isempty(fbopt),
fbopt.i = 1;
fbopt.n = 1;
end
% throw errors for required input
if isempty(tapsmofrq) && strcmp(taper, 'dpss')
error('you need to specify tapsmofrq when using dpss tapers')
end
if isempty(timwin)
error('you need to specify timwin')
elseif (length(timwin) ~= length(freqoi) && ~strcmp(freqoi,'all'))
error('timwin should be of equal length as freqoi')
end
% Set n's
[nchan,ndatsample] = size(dat);
% Remove polynomial fit from the data -> default is demeaning
if polyorder >= 0
dat = ft_preproc_polyremoval(dat, polyorder, 1, ndatsample);
end
% Determine fsample and set total time-length of data
fsample = 1./mean(diff(time));
dattime = ndatsample / fsample; % total time in seconds of input data
% Zero padding
if round(pad * fsample) < ndatsample
error('the padding that you specified is shorter than the data');
end
if isempty(pad) % if no padding is specified padding is equal to current data length
pad = dattime;
end
postpad = round((pad - dattime) * fsample);
endnsample = round(pad * fsample); % total number of samples of padded data
endtime = pad; % total time in seconds of padded data
% Set freqboi and freqoi
if isnumeric(freqoi) % if input is a vector
freqboi = round(freqoi ./ (fsample ./ endnsample)) + 1; % is equivalent to: round(freqoi .* endtime) + 1;
freqboi = unique(freqboi);
freqoi = (freqboi-1) ./ endtime; % boi - 1 because 0 Hz is included in fourier output
elseif strcmp(freqoi,'all')
freqboilim = round([0 fsample/2] ./ (fsample ./ endnsample)) + 1;
freqboi = freqboilim(1):1:freqboilim(2);
freqoi = (freqboi-1) ./ endtime;
end
% check for freqoi = 0 and remove it, there is no wavelet for freqoi = 0
if freqoi(1)==0
freqoi(1) = [];
freqboi(1) = [];
if length(timwin) == (length(freqoi) + 1)
timwin(1) = [];
end
end
nfreqboi = length(freqboi);
nfreqoi = length(freqoi);
% Set timeboi and timeoi
offset = round(time(1)*fsample);
if isnumeric(timeoi) % if input is a vector
timeboi = round(timeoi .* fsample - offset) + 1;
ntimeboi = length(timeboi);
timeoi = round(timeoi .* fsample) ./ fsample;
elseif strcmp(timeoi,'all') % if input was 'all'
timeboi = 1:length(time);
ntimeboi = length(timeboi);
timeoi = time;
end
% set number of samples per time-window (timwin is in seconds)
timwinsample = round(timwin .* fsample);
% determine whether tapers need to be recomputed
current_argin = {time, postpad, taper, timwinsample, tapsmofrq, freqoi, timeoi, tapopt}; % reasoning: if time and postpad are equal, it's the same length trial, if the rest is equal then the requested output is equal
if isequal(current_argin, previous_argin)
% don't recompute tapers
wltspctrm = previous_wltspctrm;
ntaper = cellfun(@size,wltspctrm,repmat({1},[1 nfreqoi])');
else
% recompute tapers per frequency, multiply with wavelets and compute their fft
wltspctrm = cell(nfreqoi,1);
ntaper = zeros(nfreqoi,1);
for ifreqoi = 1:nfreqoi
switch taper
case 'dpss'
% create a sequence of DPSS tapers, ensure that the input arguments are double precision
tap = double_dpss(timwinsample(ifreqoi), timwinsample(ifreqoi) .* (tapsmofrq(ifreqoi) ./ fsample))';
% remove the last taper because the last slepian taper is always messy
tap = tap(1:(end-1), :);
% give error/warning about number of tapers
if isempty(tap)
error('%.3f Hz: datalength to short for specified smoothing\ndatalength: %.3f s, smoothing: %.3f Hz, minimum smoothing: %.3f Hz',freqoi(ifreqoi), timwinsample(ifreqoi)/fsample,tapsmofrq(ifreqoi),fsample/timwinsample(ifreqoi));
elseif size(tap,1) == 1
disp([num2str(freqoi(ifreqoi)) ' Hz: WARNING: using only one taper for specified smoothing'])
end
case 'sine'
% create and remove the last taper
tap = sine_taper(timwinsample(ifreqoi), timwinsample(ifreqoi) .* (tapsmofrq(ifreqoi) ./ fsample))';
tap = tap(1:(end-1), :);
case 'sine_old'
% to provide compatibility with the tapers being scaled (which was default
% behavior prior to 29apr2011) yet this gave different magnitude of power
% when comparing with slepian multi tapers
tap = sine_taper_scaled(timwinsample(ifreqoi), timwinsample(ifreqoi) .* (tapsmofrq(ifreqoi) ./ fsample))';
tap = tap(1:(end-1), :); % remove the last taper
case 'alpha'
tap = alpha_taper(timwinsample(ifreqoi), freqoi(ifreqoi)./ fsample)';
tap = tap./norm(tap)';
case 'hanning'
tap = hanning(timwinsample(ifreqoi))';
tap = tap./norm(tap, 'fro');
otherwise
% create a single taper according to the window specification as a replacement for the DPSS (Slepian) sequence
if isempty(tapopt) % some windowing functions don't support nargin>1, and window.m doesn't check it
tap = window(taper, timwinsample(ifreqoi))';
else
tap = window(taper, timwinsample(ifreqoi),tapopt)';
end
tap = tap ./ norm(tap,'fro'); % make it explicit that the frobenius norm is being used
end
% set number of tapers
ntaper(ifreqoi) = size(tap,1);
% Wavelet construction
tappad = ceil(endnsample ./ 2) - floor(timwinsample(ifreqoi) ./ 2);
prezero = zeros(1,tappad);
postzero = zeros(1,round(endnsample) - ((tappad-1) + timwinsample(ifreqoi))-1);
% phase consistency: cos must always be 1 and sin must always be centered in upgoing flank, so the centre of the wavelet (untapered) has angle = 0
anglein = (-(timwinsample(ifreqoi)-1)/2 : (timwinsample(ifreqoi)-1)/2)' .* ((2.*pi./fsample) .* freqoi(ifreqoi));
wltspctrm{ifreqoi} = complex(zeros(size(tap,1),round(endnsample)));
for itap = 1:ntaper(ifreqoi)
try % this try loop tries to fit the wavelet into wltspctrm, when its length is smaller than ndatsample, the rest is 'filled' with zeros because of above code
% if a wavelet is longer than ndatsample, it doesn't fit and it is kept at zeros, which is translated to NaN's in the output
% construct the complex wavelet
coswav = horzcat(prezero, tap(itap,:) .* cos(anglein)', postzero);
sinwav = horzcat(prezero, tap(itap,:) .* sin(anglein)', postzero);
wavelet = complex(coswav, sinwav);
% store the fft of the complex wavelet
wltspctrm{ifreqoi}(itap,:) = fft(wavelet,[],2);
% % debug plotting
% figure('name',['taper #' num2str(itap) ' @ ' num2str(freqoi(ifreqoi)) 'Hz' ],'NumberTitle','off');
% subplot(2,1,1);
% hold on;
% plot(real(wavelet));
% plot(imag(wavelet),'color','r');
% legend('real','imag');
% tline = length(wavelet)/2;
% if mod(tline,2)==0
% line([tline tline],[-max(abs(wavelet)) max(abs(wavelet))],'color','g','linestyle','--')
% else
% line([ceil(tline) ceil(tline)],[-max(abs(wavelet)) max(abs(wavelet))],'color','g','linestyle','--');
% line([floor(tline) floor(tline)],[-max(abs(wavelet)) max(abs(wavelet))],'color','g','linestyle','--');
% end;
% subplot(2,1,2);
% plot(angle(wavelet),'color','g');
% if mod(tline,2)==0,
% line([tline tline],[-pi pi],'color','r','linestyle','--')
% else
% line([ceil(tline) ceil(tline)],[-pi pi],'color','r','linestyle','--')
% line([floor(tline) floor(tline)],[-pi pi],'color','r','linestyle','--')
% end
end
end
end
end
% Switch between memory efficient representation or intuitive default representation
switch dimord
case 'tap_chan_freq_time' % default
% compute fft, major speed increases are possible here, depending on which matlab is being used whether or not it helps, which mainly focuses on orientation of the to be fft'd matrix
datspectrum = transpose(fft(transpose(ft_preproc_padding(dat, padtype, 0, postpad)))); % double explicit transpose to speedup fft
spectrum = cell(max(ntaper), nfreqoi);
for ifreqoi = 1:nfreqoi
str = sprintf('frequency %d (%.2f Hz), %d tapers', ifreqoi,freqoi(ifreqoi),ntaper(ifreqoi));
[st, cws] = dbstack;
if length(st)>1 && strcmp(st(2).name, 'ft_freqanalysis') && verbose
% specest_mtmconvol has been called by ft_freqanalysis, meaning that ft_progress has been initialised
ft_progress(fbopt.i./fbopt.n, ['trial %d, ',str,'\n'], fbopt.i);
elseif verbose
fprintf([str, '\n']);
end
for itap = 1:max(ntaper)
% compute indices that will be used to extracted the requested fft output
nsamplefreqoi = timwin(ifreqoi) .* fsample;
reqtimeboiind = find((timeboi >= (nsamplefreqoi ./ 2)) & (timeboi < ndatsample - (nsamplefreqoi ./2)));
reqtimeboi = timeboi(reqtimeboiind);
% compute datspectrum*wavelet, if there are reqtimeboi's that have data
% create a matrix of NaNs if there is no taper for this current frequency-taper-number
if itap > ntaper(ifreqoi)
spectrum{itap,ifreqoi} = complex(nan(nchan,ntimeboi));
else
dum = fftshift(transpose(ifft(transpose(datspectrum .* repmat(wltspctrm{ifreqoi}(itap,:),[nchan 1])))),2); % double explicit transpose to speedup fft
tmp = complex(nan(nchan,ntimeboi));
tmp(:,reqtimeboiind) = dum(:,reqtimeboi);
tmp = tmp .* sqrt(2 ./ timwinsample(ifreqoi));
spectrum{itap,ifreqoi} = tmp;
end
end
end
spectrum = reshape(vertcat(spectrum{:}),[nchan max(ntaper) nfreqoi ntimeboi]); % collecting in a cell-array and later reshaping provides significant speedups
spectrum = permute(spectrum, [2 1 3 4]);
case 'chan_time_freqtap' % memory efficient representation
% create tapfreqind
freqtapind = cell(1,nfreqoi);
tempntaper = [0; cumsum(ntaper(:))];
for ifreqoi = 1:nfreqoi
freqtapind{ifreqoi} = tempntaper(ifreqoi)+1:tempntaper(ifreqoi+1);
end
% start fft'ing
datspectrum = transpose(fft(transpose(ft_preproc_padding(dat, padtype, 0, postpad)))); % double explicit transpose to speedup fft
spectrum = complex(zeros([nchan ntimeboi sum(ntaper)]));
for ifreqoi = 1:nfreqoi
str = sprintf('frequency %d (%.2f Hz), %d tapers', ifreqoi,freqoi(ifreqoi),ntaper(ifreqoi));
[st, cws] = dbstack;
if length(st)>1 && strcmp(st(2).name, 'ft_freqanalysis') && verbose
% specest_mtmconvol has been called by ft_freqanalysis, meaning that ft_progress has been initialised
ft_progress(fbopt.i./fbopt.n, ['trial %d, ',str,'\n'], fbopt.i);
elseif verbose
fprintf([str, '\n']);
end
for itap = 1:ntaper(ifreqoi)
% compute indices that will be used to extracted the requested fft output
nsamplefreqoi = timwin(ifreqoi) .* fsample;
reqtimeboiind = find((timeboi >= (nsamplefreqoi ./ 2)) & (timeboi < (ndatsample - (nsamplefreqoi ./2))));
reqtimeboi = timeboi(reqtimeboiind);
% compute datspectrum*wavelet, if there are reqtimeboi's that have data
dum = fftshift(transpose(ifft(transpose(datspectrum .* repmat(wltspctrm{ifreqoi}(itap,:),[nchan 1])))),2); % double explicit transpose to speedup fft
tmp = complex(nan(nchan,ntimeboi),nan(nchan,ntimeboi));
tmp(:,reqtimeboiind) = dum(:,reqtimeboi);
tmp = tmp .* sqrt(2 ./ timwinsample(ifreqoi));
spectrum(:,:,freqtapind{ifreqoi}(itap)) = tmp;
end
end % for nfreqoi
end % switch dimord
% remember the current input arguments, so that they can be
% reused on a subsequent call in case the same input argument is given
previous_argin = current_argin;
previous_wltspctrm = wltspctrm;
% % below code does the exact same as above, but without the trick of converting to cell-arrays for speed increases. however, when there is a huge variability in number of tapers per freqoi
% % than this approach can benefit from the fact that the array can be precreated containing nans
% % compute fft, major speed increases are possible here, depending on which matlab is being used whether or not it helps, which mainly focuses on orientation of the to be fft'd matrix
% datspectrum = transpose(fft(transpose([dat repmat(postpad,[nchan, 1])]))); % double explicit transpose to speedup fft
% spectrum = complex(nan([max(ntaper) nchan nfreqoi ntimeboi]),nan([max(ntaper) nchan nfreqoi ntimeboi])); % assumes fixed number of tapers
% for ifreqoi = 1:nfreqoi
% fprintf('processing frequency %d (%.2f Hz), %d tapers\n', ifreqoi,freqoi(ifreqoi),ntaper(ifreqoi));
% for itap = 1:max(ntaper)
% % compute indices that will be used to extracted the requested fft output
% nsamplefreqoi = timwin(ifreqoi) .* fsample;
% reqtimeboiind = find((timeboi >= (nsamplefreqoi ./ 2)) & (timeboi < ndatsample - (nsamplefreqoi ./2)));
% reqtimeboi = timeboi(reqtimeboiind);
%
% % compute datspectrum*wavelet, if there are reqtimeboi's that have data
% % create a matrix of NaNs if there is no taper for this current frequency-taper-number
% if itap <= ntaper(ifreqoi)
% dum = fftshift(transpose(ifft(transpose(datspectrum .* repmat(wltspctrm{ifreqoi}(itap,:),[nchan 1])))),2); % double explicit transpose to speedup fft
% tmp = complex(nan(nchan,ntimeboi));
% tmp(:,reqtimeboiind) = dum(:,reqtimeboi);
% tmp = tmp .* sqrt(2 ./ timwinsample(ifreqoi));
% spectrum(itap,:,ifreqoi,:) = tmp;
% else
% break
% end
% end
% end
% Below the code used to implement variable amount of tapers in a different way, kept here for testing, please do not remove
% % build tapfreq vector
% tapfreq = [];
% for ifreqoi = 1:nfreqoi
% tapfreq = [tapfreq ones(1,ntaper(ifreqoi)) * ifreqoi];
% end
% tapfreq = tapfreq(:);
%
% % compute fft, major speed increases are possible here, depending on which matlab is being used whether or not it helps, which mainly focuses on orientation of the to be fft'd matrix
% %spectrum = complex(nan([numel(tapfreq),nchan,ntimeboi]));
% datspectrum = fft([dat repmat(postpad,[nchan, 1])],[],2);
% spectrum = cell(numel(tapfreq), nchan, ntimeboi);
% for ifreqoi = 1:nfreqoi
% fprintf('processing frequency %d (%.2f Hz), %d tapers\n', ifreqoi,freqoi(ifreqoi),ntaper(ifreqoi));
% for itap = 1:ntaper(ifreqoi)
% tapfreqind = sum(ntaper(1:ifreqoi-1)) + itap;
% for ichan = 1:nchan
% % compute indices that will be used to extracted the requested fft output
% nsamplefreqoi = timwin(ifreqoi) .* fsample;
% reqtimeboiind = find((timeboi >= (nsamplefreqoi ./ 2)) & (timeboi < ndatsample - (nsamplefreqoi ./2)));
% reqtimeboi = timeboi(reqtimeboiind);
%
% % compute datspectrum*wavelet, if there are reqtimeboi's that have data
% if ~isempty(reqtimeboi)
% dum = fftshift(ifft(datspectrum(ichan,:) .* wltspctrm{ifreqoi}(itap,:),[],2)); % fftshift is necessary because of post zero-padding, not necessary when pre-padding
% %spectrum(tapfreqind,ichan,reqtimeboiind) = dum(reqtimeboi);
% tmp = complex(nan(1,ntimeboi));
% tmp(reqtimeboiind) = dum(reqtimeboi);
% spectrum{tapfreqind,ichan} = tmp;
% end
% end
% end
% end
% spectrum = reshape(vertcat(spectrum{:}),[numel(tapfreq) nchan ntimeboi]);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION ensure that the first two input arguments are of double
% precision this prevents an instability (bug) in the computation of the
% tapers for Matlab 6.5 and 7.0
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [tap] = double_dpss(a, b, varargin)
tap = dpss(double(a), double(b), varargin{:});
|
github
|
philippboehmsturm/antx-master
|
ft_specest_mtmfft.m
|
.m
|
antx-master/xspm8/external/fieldtrip/specest/ft_specest_mtmfft.m
| 12,992 |
utf_8
|
9d6c9a46538d0cfc46ac075583838972
|
function [spectrum,ntaper,freqoi] = ft_specest_mtmfft(dat, time, varargin)
% FT_SPECEST_MTMFFT computes a fast Fourier transform using multitapering with
% the DPSS sequence or using a variety of single tapers
%
% Use as
% [spectrum,freqoi] = specest_mtmfft(dat,time...)
% where
% dat = matrix of chan*sample
% time = vector, containing time in seconds for each sample
% spectrum = matrix of taper*chan*freqoi of fourier coefficients
% ntaper = vector containing number of tapers per element of freqoi
% freqoi = vector of frequencies in spectrum
%
% Optional arguments should be specified in key-value pairs and can include:
% taper = 'dpss', 'hanning' or many others, see WINDOW (default = 'dpss')
% pad = number, total length of data after zero padding (in seconds)
% padtype = string, indicating type of padding to be used (see ft_preproc_padding, default: zero)
% freqoi = vector, containing frequencies of interest
% tapsmofrq = the amount of spectral smoothing through multi-tapering. Note: 4 Hz smoothing means plus-minus 4 Hz, i.e. a 8 Hz smoothing box
% dimord = 'tap_chan_freq_time' (default) or 'chan_time_freqtap' for memory efficiency (only when use variable number slepian tapers)
% polyorder = number, the order of the polynomial to fitted to and removed from the data
% prior to the fourier transform (default = 0 -> remove DC-component)
% taperopt = additional taper options to be used in the WINDOW function, see WINDOW
% verbose = output progress to console (0 or 1, default 1)
%
%
% See also FT_FREQANALYSIS, FT_SPECEST_MTMCONVOL, FT_SPECEST_TFR, FT_SPECEST_HILBERT, FT_SPECEST_WAVELET
% Copyright (C) 2010, Donders Institute for Brain, Cognition and Behaviour
%
% $Id: ft_specest_mtmfft.m 7123 2012-12-06 21:21:38Z roboos $
% these are for speeding up computation of tapers on subsequent calls
persistent previous_argin previous_tap
% get the optional input arguments
taper = ft_getopt(varargin, 'taper'); if isempty(taper), error('You must specify a taper'); end
pad = ft_getopt(varargin, 'pad');
padtype = ft_getopt(varargin, 'padtype', 'zero');
freqoi = ft_getopt(varargin, 'freqoi', 'all');
tapsmofrq = ft_getopt(varargin, 'tapsmofrq');
dimord = ft_getopt(varargin, 'dimord', 'tap_chan_freq');
fbopt = ft_getopt(varargin, 'feedback');
verbose = ft_getopt(varargin, 'verbose', true);
polyorder = ft_getopt(varargin, 'polyorder', 0);
tapopt = ft_getopt(varargin, 'taperopt');
if isempty(fbopt),
fbopt.i = 1;
fbopt.n = 1;
end
% throw errors for required input
if isempty(tapsmofrq) && strcmp(taper, 'dpss')
error('you need to specify tapsmofrq when using dpss tapers')
end
% Set n's
[nchan,ndatsample] = size(dat);
% Remove polynomial fit from the data -> default is demeaning
if polyorder >= 0
dat = ft_preproc_polyremoval(dat, polyorder, 1, ndatsample);
end
% Determine fsample and set total time-length of data
fsample = 1./mean(diff(time));
dattime = ndatsample / fsample; % total time in seconds of input data
% Zero padding
if round(pad * fsample) < ndatsample
error('the padding that you specified is shorter than the data');
end
if isempty(pad) % if no padding is specified padding is equal to current data length
pad = dattime;
end
postpad = ceil((pad - dattime) * fsample);
endnsample = round(pad * fsample); % total number of samples of padded data
endtime = pad; % total time in seconds of padded data
% Set freqboi and freqoi
if isnumeric(freqoi) % if input is a vector
freqboi = round(freqoi ./ (fsample ./ endnsample)) + 1; % is equivalent to: round(freqoi .* endtime) + 1;
freqboi = unique(freqboi);
freqoi = (freqboi-1) ./ endtime; % boi - 1 because 0 Hz is included in fourier output
elseif strcmp(freqoi,'all') % if input was 'all'
freqboilim = round([0 fsample/2] ./ (fsample ./ endnsample)) + 1;
freqboi = freqboilim(1):1:freqboilim(2);
freqoi = (freqboi-1) ./ endtime;
end
nfreqboi = length(freqboi);
nfreqoi = length(freqoi);
if strcmp(taper, 'dpss') && numel(tapsmofrq)~=1 && (numel(tapsmofrq)~=nfreqoi)
error('tapsmofrq needs to contain a smoothing parameter for every frequency when requesting variable number of slepian tapers')
end
% determine whether tapers need to be recomputed
current_argin = {time, postpad, taper, tapsmofrq, freqoi, tapopt}; % reasoning: if time and postpad are equal, it's the same length trial, if the rest is equal then the requested output is equal
if isequal(current_argin, previous_argin)
% don't recompute tapers
tap = previous_tap;
else
% recompute tapers
switch taper
case 'dpss'
if numel(tapsmofrq)==1
% create a sequence of DPSS tapers, ensure that the input arguments are double precision
tap = double_dpss(ndatsample,ndatsample*(tapsmofrq./fsample))';
% remove the last taper because the last slepian taper is always messy
tap = tap(1:(end-1), :);
% give error/warning about number of tapers
if isempty(tap)
error('datalength to short for specified smoothing\ndatalength: %.3f s, smoothing: %.3f Hz, minimum smoothing: %.3f Hz',ndatsample/fsample,tapsmofrq,fsample/ndatsample);
elseif size(tap,1) == 1
warning_once('using only one taper for specified smoothing');
end
elseif numel(tapsmofrq)>1
tap = cell(1,nfreqoi);
for ifreqoi = 1:nfreqoi
% create a sequence of DPSS tapers, ensure that the input arguments are double precision
currtap = double_dpss(ndatsample, ndatsample .* (tapsmofrq(ifreqoi) ./ fsample))';
% remove the last taper because the last slepian taper is always messy
currtap = currtap(1:(end-1), :);
% give error/warning about number of tapers
if isempty(currtap)
error('%.3f Hz: datalength to short for specified smoothing\ndatalength: %.3f s, smoothing: %.3f Hz, minimum smoothing: %.3f Hz',freqoi(ifreqoi), ndatsample/fsample,tapsmofrq(ifreqoi),fsample/ndatsample(ifreqoi));
elseif size(currtap,1) == 1
disp([num2str(freqoi(ifreqoi)) ' Hz: WARNING: using only one taper for specified smoothing'])
end
tap{ifreqoi} = currtap;
end
end
case 'sine'
tap = sine_taper(ndatsample, ndatsample*(tapsmofrq./fsample))';
tap = tap(1:(end-1), :); % remove the last taper
case 'sine_old'
% to provide compatibility with the tapers being scaled (which was default
% behavior prior to 29apr2011) yet this gave different magnitude of power
% when comparing with slepian multi tapers
tap = sine_taper_scaled(ndatsample, ndatsample*(tapsmofrq./fsample))';
tap = tap(1:(end-1), :); % remove the last taper
case 'alpha'
error('not yet implemented');
case 'hanning'
tap = hanning(ndatsample)';
tap = tap./norm(tap, 'fro');
otherwise
% create the taper and ensure that it is normalized
if isempty(tapopt) % some windowing functions don't support nargin>1, and window.m doesn't check it
tap = window(taper, ndatsample)';
else
tap = window(taper, ndatsample, tapopt)';
end
tap = tap ./ norm(tap,'fro');
end % switch taper
end % isequal currargin
% set ntaper
if ~(strcmp(taper,'dpss') && numel(tapsmofrq)>1) % variable number of slepian tapers not requested
ntaper = repmat(size(tap,1),nfreqoi,1);
else % variable number of slepian tapers requested
ntaper = cellfun(@size,tap,repmat({1},[1 nfreqoi]));
end
% determine phase-shift so that for all frequencies angle(t=0) = 0
timedelay = time(1);
if timedelay ~= 0
angletransform = complex(zeros(1,nfreqoi));
for ifreqoi = 1:nfreqoi
missedsamples = round(timedelay * fsample);
% determine angle of freqoi if oscillation started at 0
% the angle of wavelet(cos,sin) = 0 at the first point of a cycle, with sine being in upgoing flank, which is the same convention as in mtmconvol
anglein = (missedsamples) .* ((2.*pi./fsample) .* freqoi(ifreqoi));
coswav = cos(anglein);
sinwav = sin(anglein);
angletransform(ifreqoi) = angle(complex(coswav,sinwav));
end
angletransform = repmat(angletransform,[nchan,1]);
end
% compute fft
if ~(strcmp(taper,'dpss') && numel(tapsmofrq)>1) % ariable number of slepian tapers not requested
str = sprintf('nfft: %d samples, datalength: %d samples, %d tapers',endnsample,ndatsample,ntaper(1));
[st, cws] = dbstack;
if length(st)>1 && strcmp(st(2).name, 'ft_freqanalysis')
% specest_mtmfft has been called by ft_freqanalysis, meaning that ft_progress has been initialised
ft_progress(fbopt.i./fbopt.n, ['processing trial %d/%d ',str,'\n'], fbopt.i, fbopt.n);
else
fprintf([str, '\n']);
end
spectrum = cell(ntaper(1),1);
for itap = 1:ntaper(1)
dum = transpose(fft(transpose(ft_preproc_padding(dat .* repmat(tap(itap,:),[nchan, 1]), padtype, 0, postpad)))); % double explicit transpose to speedup fft
dum = dum(:,freqboi);
% phase-shift according to above angles
if timedelay ~= 0
dum = dum .* exp(-1i*angletransform);
end
dum = dum .* sqrt(2 ./ endnsample);
spectrum{itap} = dum;
end
spectrum = reshape(vertcat(spectrum{:}),[nchan ntaper(1) nfreqboi]);% collecting in a cell-array and later reshaping provides significant speedups
spectrum = permute(spectrum, [2 1 3]);
else % variable number of slepian tapers requested
switch dimord
case 'tap_chan_freq' % default
% start fft'ing
spectrum = complex(zeros([max(ntaper) nchan nfreqoi]));
for ifreqoi = 1:nfreqoi
str = sprintf('nfft: %d samples, datalength: %d samples, frequency %d (%.2f Hz), %d tapers',endnsample,ndatsample,ifreqoi,freqoi(ifreqoi),ntaper(ifreqoi));
[st, cws] = dbstack;
if length(st)>1 && strcmp(st(2).name, 'ft_freqanalysis') && verbose
% specest_mtmconvol has been called by ft_freqanalysis, meaning that ft_progress has been initialised
ft_progress(fbopt.i./fbopt.n, ['processing trial %d, ',str,'\n'], fbopt.i);
elseif verbose
fprintf([str, '\n']);
end
for itap = 1:ntaper(ifreqoi)
dum = transpose(fft(transpose(ft_preproc_padding(dat .* repmat(tap{ifreqoi}(itap,:),[nchan, 1]), padtype, 0, postpad)))); % double explicit transpose to speedup fft
dum = dum(:,freqboi(ifreqoi));
% phase-shift according to above angles
if timedelay ~= 0
dum = dum .* exp(-1i*angletransform(:,ifreqoi));
end
dum = dum .* sqrt(2 ./ endnsample);
currtapind = itap + ((ifreqoi-1) * max(ntaper));
spectrum(currtapind,:,ifreqoi) = dum;
end
end % for nfreqoi
case 'chan_freqtap' % memory efficient representation
% create tapfreqind
freqtapind = cell(1,nfreqoi);
tempntaper = [0; cumsum(ntaper(:))];
for ifreqoi = 1:nfreqoi
freqtapind{ifreqoi} = tempntaper(ifreqoi)+1:tempntaper(ifreqoi+1);
end
% start fft'ing
spectrum = complex(zeros([nchan sum(ntaper)]));
for ifreqoi = 1:nfreqoi
str = sprintf('nfft: %d samples, datalength: %d samples, frequency %d (%.2f Hz), %d tapers',endnsample,ndatsample,ifreqoi,freqoi(ifreqoi),ntaper(ifreqoi));
[st, cws] = dbstack;
if length(st)>1 && strcmp(st(2).name, 'ft_freqanalysis') && verbose
% specest_mtmconvol has been called by ft_freqanalysis, meaning that ft_progress has been initialised
ft_progress(fbopt.i./fbopt.n, ['processing trial %d, ',str,'\n'], fbopt.i);
elseif verbose
fprintf([str, '\n']);
end
for itap = 1:ntaper(ifreqoi)
dum = transpose(fft(transpose(ft_preproc_padding(dat .* repmat(tap{ifreqoi}(itap,:),[nchan, 1]),[nchan, 1]), padtype, 0, postpad))); % double explicit transpose to speedup fft
dum = dum(:,freqboi(ifreqoi));
% phase-shift according to above angles
if timedelay ~= 0
dum = dum .* exp(-1i*angletransform(:,ifreqoi));
end
dum = dum .* sqrt(2 ./ endnsample);
spectrum(:,freqtapind{ifreqoi}(itap)) = dum;
end
end % for nfreqoi
end % switch dimord
end
% remember the current input arguments, so that they can be
% reused on a subsequent call in case the same input argument is given
previous_argin = current_argin;
previous_tap = tap;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION ensure that the first two input arguments are of double
% precision this prevents an instability (bug) in the computation of the
% tapers for Matlab 6.5 and 7.0
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [tap] = double_dpss(a, b, varargin)
tap = dpss(double(a), double(b), varargin{:});
|
github
|
philippboehmsturm/antx-master
|
postpad.m
|
.m
|
antx-master/xspm8/external/fieldtrip/specest/private/postpad.m
| 2,013 |
utf_8
|
2c9539d77ff0f85c9f89108f4dc811e0
|
% Copyright (C) 1994, 1995, 1996, 1997, 1998, 2000, 2002, 2004, 2005,
% 2006, 2007, 2008, 2009 John W. Eaton
%
% This file is part of Octave.
%
% Octave 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.
%
% Octave 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 Octave; see the file COPYING. If not, see
% <http://www.gnu.org/licenses/>.
% -*- texinfo -*-
% @deftypefn {Function File} {} postpad (@var{x}, @var{l}, @var{c})
% @deftypefnx {Function File} {} postpad (@var{x}, @var{l}, @var{c}, @var{dim})
% @seealso{prepad, resize}
% @end deftypefn
% Author: Tony Richardson <[email protected]>
% Created: June 1994
function y = postpad (x, l, c, dim)
if nargin < 2 || nargin > 4
%print_usage ();
error('wrong number of input arguments, should be between 2 and 4');
end
if nargin < 3 || isempty(c)
c = 0;
else
if ~isscalar(c)
error ('postpad: third argument must be empty or a scalar');
end
end
nd = ndims(x);
sz = size(x);
if nargin < 4
% Find the first non-singleton dimension
dim = 1;
while dim < nd+1 && sz(dim)==1
dim = dim + 1;
end
if dim > nd
dim = 1;
elseif ~(isscalar(dim) && dim == round(dim)) && dim > 0 && dim< nd+1
error('postpad: dim must be an integer and valid dimension');
end
end
if ~isscalar(l) || l<0
error ('second argument must be a positive scalar');
end
if dim > nd
sz(nd+1:dim) = 1;
end
d = sz(dim);
if d >= l
idx = cell(1,nd);
for i = 1:nd
idx{i} = 1:sz(i);
end
idx{dim} = 1:l;
y = x(idx{:});
else
sz(dim) = l-d;
y = cat(dim, x, c * ones(sz));
end
|
github
|
philippboehmsturm/antx-master
|
sftrans.m
|
.m
|
antx-master/xspm8/external/fieldtrip/specest/private/sftrans.m
| 7,947 |
utf_8
|
f64cb2e7d19bcdc6232b39d8a6d70e7c
|
% Copyright (C) 1999 Paul Kienzle
%
% This program 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 2 of the License, or
% (at your option) any later version.
%
% This program 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 this program; If not, see <http://www.gnu.org/licenses/>.
% usage: [Sz, Sp, Sg] = sftrans(Sz, Sp, Sg, W, stop)
%
% Transform band edges of a generic lowpass filter (cutoff at W=1)
% represented in splane zero-pole-gain form. W is the edge of the
% target filter (or edges if band pass or band stop). Stop is true for
% high pass and band stop filters or false for low pass and band pass
% filters. Filter edges are specified in radians, from 0 to pi (the
% nyquist frequency).
%
% Theory: Given a low pass filter represented by poles and zeros in the
% splane, you can convert it to a low pass, high pass, band pass or
% band stop by transforming each of the poles and zeros individually.
% The following table summarizes the transformation:
%
% Transform Zero at x Pole at x
% ---------------- ------------------------- ------------------------
% Low Pass zero: Fc x/C pole: Fc x/C
% S -> C S/Fc gain: C/Fc gain: Fc/C
% ---------------- ------------------------- ------------------------
% High Pass zero: Fc C/x pole: Fc C/x
% S -> C Fc/S pole: 0 zero: 0
% gain: -x gain: -1/x
% ---------------- ------------------------- ------------------------
% Band Pass zero: b ? sqrt(b^2-FhFl) pole: b ? sqrt(b^2-FhFl)
% S^2+FhFl pole: 0 zero: 0
% S -> C -------- gain: C/(Fh-Fl) gain: (Fh-Fl)/C
% S(Fh-Fl) b=x/C (Fh-Fl)/2 b=x/C (Fh-Fl)/2
% ---------------- ------------------------- ------------------------
% Band Stop zero: b ? sqrt(b^2-FhFl) pole: b ? sqrt(b^2-FhFl)
% S(Fh-Fl) pole: ?sqrt(-FhFl) zero: ?sqrt(-FhFl)
% S -> C -------- gain: -x gain: -1/x
% S^2+FhFl b=C/x (Fh-Fl)/2 b=C/x (Fh-Fl)/2
% ---------------- ------------------------- ------------------------
% Bilinear zero: (2+xT)/(2-xT) pole: (2+xT)/(2-xT)
% 2 z-1 pole: -1 zero: -1
% S -> - --- gain: (2-xT)/T gain: (2-xT)/T
% T z+1
% ---------------- ------------------------- ------------------------
%
% where C is the cutoff frequency of the initial lowpass filter, Fc is
% the edge of the target low/high pass filter and [Fl,Fh] are the edges
% of the target band pass/stop filter. With abundant tedious algebra,
% you can derive the above formulae yourself by substituting the
% transform for S into H(S)=S-x for a zero at x or H(S)=1/(S-x) for a
% pole at x, and converting the result into the form:
%
% H(S)=g prod(S-Xi)/prod(S-Xj)
%
% The transforms are from the references. The actual pole-zero-gain
% changes I derived myself.
%
% Please note that a pole and a zero at the same place exactly cancel.
% This is significant for High Pass, Band Pass and Band Stop filters
% which create numerous extra poles and zeros, most of which cancel.
% Those which do not cancel have a 'fill-in' effect, extending the
% shorter of the sets to have the same number of as the longer of the
% sets of poles and zeros (or at least split the difference in the case
% of the band pass filter). There may be other opportunistic
% cancellations but I will not check for them.
%
% Also note that any pole on the unit circle or beyond will result in
% an unstable filter. Because of cancellation, this will only happen
% if the number of poles is smaller than the number of zeros and the
% filter is high pass or band pass. The analytic design methods all
% yield more poles than zeros, so this will not be a problem.
%
% References:
%
% Proakis & Manolakis (1992). Digital Signal Processing. New York:
% Macmillan Publishing Company.
% Author: Paul Kienzle <[email protected]>
% 2000-03-01 [email protected]
% leave transformed Sg as a complex value since cheby2 blows up
% otherwise (but only for odd-order low-pass filters). bilinear
% will return Zg as real, so there is no visible change to the
% user of the IIR filter design functions.
% 2001-03-09 [email protected]
% return real Sg; don't know what to do for imaginary filters
function [Sz, Sp, Sg] = sftrans(Sz, Sp, Sg, W, stop)
if (nargin ~= 5)
usage('[Sz, Sp, Sg] = sftrans(Sz, Sp, Sg, W, stop)');
end;
C = 1;
p = length(Sp);
z = length(Sz);
if z > p || p == 0
error('sftrans: must have at least as many poles as zeros in s-plane');
end
if length(W)==2
Fl = W(1);
Fh = W(2);
if stop
% ---------------- ------------------------- ------------------------
% Band Stop zero: b ? sqrt(b^2-FhFl) pole: b ? sqrt(b^2-FhFl)
% S(Fh-Fl) pole: ?sqrt(-FhFl) zero: ?sqrt(-FhFl)
% S -> C -------- gain: -x gain: -1/x
% S^2+FhFl b=C/x (Fh-Fl)/2 b=C/x (Fh-Fl)/2
% ---------------- ------------------------- ------------------------
if (isempty(Sz))
Sg = Sg * real (1./ prod(-Sp));
elseif (isempty(Sp))
Sg = Sg * real(prod(-Sz));
else
Sg = Sg * real(prod(-Sz)/prod(-Sp));
end
b = (C*(Fh-Fl)/2)./Sp;
Sp = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)];
extend = [sqrt(-Fh*Fl), -sqrt(-Fh*Fl)];
if isempty(Sz)
Sz = [extend(1+rem([1:2*p],2))];
else
b = (C*(Fh-Fl)/2)./Sz;
Sz = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)];
if (p > z)
Sz = [Sz, extend(1+rem([1:2*(p-z)],2))];
end
end
else
% ---------------- ------------------------- ------------------------
% Band Pass zero: b ? sqrt(b^2-FhFl) pole: b ? sqrt(b^2-FhFl)
% S^2+FhFl pole: 0 zero: 0
% S -> C -------- gain: C/(Fh-Fl) gain: (Fh-Fl)/C
% S(Fh-Fl) b=x/C (Fh-Fl)/2 b=x/C (Fh-Fl)/2
% ---------------- ------------------------- ------------------------
Sg = Sg * (C/(Fh-Fl))^(z-p);
b = Sp*((Fh-Fl)/(2*C));
Sp = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)];
if isempty(Sz)
Sz = zeros(1,p);
else
b = Sz*((Fh-Fl)/(2*C));
Sz = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)];
if (p>z)
Sz = [Sz, zeros(1, (p-z))];
end
end
end
else
Fc = W;
if stop
% ---------------- ------------------------- ------------------------
% High Pass zero: Fc C/x pole: Fc C/x
% S -> C Fc/S pole: 0 zero: 0
% gain: -x gain: -1/x
% ---------------- ------------------------- ------------------------
if (isempty(Sz))
Sg = Sg * real (1./ prod(-Sp));
elseif (isempty(Sp))
Sg = Sg * real(prod(-Sz));
else
Sg = Sg * real(prod(-Sz)/prod(-Sp));
end
Sp = C * Fc ./ Sp;
if isempty(Sz)
Sz = zeros(1,p);
else
Sz = [C * Fc ./ Sz];
if (p > z)
Sz = [Sz, zeros(1,p-z)];
end
end
else
% ---------------- ------------------------- ------------------------
% Low Pass zero: Fc x/C pole: Fc x/C
% S -> C S/Fc gain: C/Fc gain: Fc/C
% ---------------- ------------------------- ------------------------
Sg = Sg * (C/Fc)^(z-p);
Sp = Fc * Sp / C;
Sz = Fc * Sz / C;
end
end
|
github
|
philippboehmsturm/antx-master
|
hanning.m
|
.m
|
antx-master/xspm8/external/fieldtrip/specest/private/hanning.m
| 2,015 |
utf_8
|
2dfc746c8c862dc8fe272cae2a733f20
|
function [tap] = hanning(n, str)
%HANNING Hanning window.
% HANNING(N) returns the N-point symmetric Hanning window in a column
% vector. Note that the first and last zero-weighted window samples
% are not included.
%
% HANNING(N,'symmetric') returns the same result as HANNING(N).
%
% HANNING(N,'periodic') returns the N-point periodic Hanning window,
% and includes the first zero-weighted window sample.
%
% NOTE: Use the HANN function to get a Hanning window which has the
% first and last zero-weighted samples.
%
% See also BARTLETT, BLACKMAN, BOXCAR, CHEBWIN, HAMMING, HANN, KAISER
% and TRIANG.
%
% This is a drop-in replacement to bypass the signal processing toolbox
% Copyright (c) 2010, Jan-Mathijs Schoffelen, DCCN Nijmegen
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: hanning.m 7123 2012-12-06 21:21:38Z roboos $
if nargin==1,
str = 'symmetric';
end
switch str,
case 'periodic'
% Includes the first zero sample
tap = [0; hanningX(n-1)];
case 'symmetric'
% Does not include the first and last zero sample
tap = hanningX(n);
end
function tap = hanningX(n)
% compute taper
N = n+1;
tap = 0.5*(1-cos((2*pi*(1:n))./N))';
% make symmetric
halfn = floor(n/2);
tap( (n+1-halfn):n ) = flipud(tap(1:halfn));
|
github
|
philippboehmsturm/antx-master
|
filtfilt.m
|
.m
|
antx-master/xspm8/external/fieldtrip/specest/private/filtfilt.m
| 3,297 |
iso_8859_1
|
d01a26a827bc3379f05bbc57f46ac0a9
|
% Copyright (C) 1999 Paul Kienzle
% Copyright (C) 2007 Francesco Potortì
% Copyright (C) 2008 Luca Citi
%
% This program 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 2 of the License, or
% (at your option) any later version.
%
% This program 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 this program; If not, see <http://www.gnu.org/licenses/>.
% usage: y = filtfilt(b, a, x)
%
% Forward and reverse filter the signal. This corrects for phase
% distortion introduced by a one-pass filter, though it does square the
% magnitude response in the process. That's the theory at least. In
% practice the phase correction is not perfect, and magnitude response
% is distorted, particularly in the stop band.
%%
% Example
% [b, a]=butter(3, 0.1); % 10 Hz low-pass filter
% t = 0:0.01:1.0; % 1 second sample
% x=sin(2*pi*t*2.3)+0.25*randn(size(t)); % 2.3 Hz sinusoid+noise
% y = filtfilt(b,a,x); z = filter(b,a,x); % apply filter
% plot(t,x,';data;',t,y,';filtfilt;',t,z,';filter;')
% Changelog:
% 2000 02 [email protected]
% - pad with zeros to load up the state vector on filter reverse.
% - add example
% 2007 12 [email protected]
% - use filtic to compute initial and final states
% - work for multiple columns as well
% 2008 12 [email protected]
% - fixed instability issues with IIR filters and noisy inputs
% - initial states computed according to Likhterov & Kopeika, 2003
% - use of a "reflection method" to reduce end effects
% - added some basic tests
% TODO: (pkienzle) My version seems to have similar quality to matlab,
% but both are pretty bad. They do remove gross lag errors, though.
function y = filtfilt(b, a, x)
if (nargin ~= 3)
usage('y=filtfilt(b,a,x)');
end
rotate = (size(x, 1)==1);
if rotate % a row vector
x = x(:); % make it a column vector
end
lx = size(x,1);
a = a(:).';
b = b(:).';
lb = length(b);
la = length(a);
n = max(lb, la);
lrefl = 3 * (n - 1);
if la < n, a(n) = 0; end
if lb < n, b(n) = 0; end
% Compute a the initial state taking inspiration from
% Likhterov & Kopeika, 2003. "Hardware-efficient technique for
% minimizing startup transients in Direct Form II digital filters"
kdc = sum(b) / sum(a);
if (abs(kdc) < inf) % neither NaN nor +/- Inf
si = fliplr(cumsum(fliplr(b - kdc * a)));
else
si = zeros(size(a)); % fall back to zero initialization
end
si(1) = [];
y = zeros(size(x));
for c = 1:size(x, 2) % filter all columns, one by one
v = [2*x(1,c)-x((lrefl+1):-1:2,c); x(:,c);
2*x(end,c)-x((end-1):-1:end-lrefl,c)]; % a column vector
% Do forward and reverse filtering
v = filter(b,a,v,si*v(1)); % forward filter
v = flipud(filter(b,a,flipud(v),si*v(end))); % reverse filter
y(:,c) = v((lrefl+1):(lx+lrefl));
end
if (rotate) % x was a row vector
y = rot90(y); % rotate it back
end
|
github
|
philippboehmsturm/antx-master
|
bilinear.m
|
.m
|
antx-master/xspm8/external/fieldtrip/specest/private/bilinear.m
| 4,339 |
utf_8
|
17250db27826cad87fa3384823e1242f
|
% Copyright (C) 1999 Paul Kienzle
%
% This program 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 2 of the License, or
% (at your option) any later version.
%
% This program 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 this program; If not, see <http://www.gnu.org/licenses/>.
% usage: [Zz, Zp, Zg] = bilinear(Sz, Sp, Sg, T)
% [Zb, Za] = bilinear(Sb, Sa, T)
%
% Transform a s-plane filter specification into a z-plane
% specification. Filters can be specified in either zero-pole-gain or
% transfer function form. The input form does not have to match the
% output form. 1/T is the sampling frequency represented in the z plane.
%
% Note: this differs from the bilinear function in the signal processing
% toolbox, which uses 1/T rather than T.
%
% Theory: Given a piecewise flat filter design, you can transform it
% from the s-plane to the z-plane while maintaining the band edges by
% means of the bilinear transform. This maps the left hand side of the
% s-plane into the interior of the unit circle. The mapping is highly
% non-linear, so you must design your filter with band edges in the
% s-plane positioned at 2/T tan(w*T/2) so that they will be positioned
% at w after the bilinear transform is complete.
%
% The following table summarizes the transformation:
%
% +---------------+-----------------------+----------------------+
% | Transform | Zero at x | Pole at x |
% | H(S) | H(S) = S-x | H(S)=1/(S-x) |
% +---------------+-----------------------+----------------------+
% | 2 z-1 | zero: (2+xT)/(2-xT) | zero: -1 |
% | S -> - --- | pole: -1 | pole: (2+xT)/(2-xT) |
% | T z+1 | gain: (2-xT)/T | gain: (2-xT)/T |
% +---------------+-----------------------+----------------------+
%
% With tedious algebra, you can derive the above formulae yourself by
% substituting the transform for S into H(S)=S-x for a zero at x or
% H(S)=1/(S-x) for a pole at x, and converting the result into the
% form:
%
% H(Z)=g prod(Z-Xi)/prod(Z-Xj)
%
% Please note that a pole and a zero at the same place exactly cancel.
% This is significant since the bilinear transform creates numerous
% extra poles and zeros, most of which cancel. Those which do not
% cancel have a 'fill-in' effect, extending the shorter of the sets to
% have the same number of as the longer of the sets of poles and zeros
% (or at least split the difference in the case of the band pass
% filter). There may be other opportunistic cancellations but I will
% not check for them.
%
% Also note that any pole on the unit circle or beyond will result in
% an unstable filter. Because of cancellation, this will only happen
% if the number of poles is smaller than the number of zeros. The
% analytic design methods all yield more poles than zeros, so this will
% not be a problem.
%
% References:
%
% Proakis & Manolakis (1992). Digital Signal Processing. New York:
% Macmillan Publishing Company.
% Author: Paul Kienzle <[email protected]>
function [Zz, Zp, Zg] = bilinear(Sz, Sp, Sg, T)
if nargin==3
T = Sg;
[Sz, Sp, Sg] = tf2zp(Sz, Sp);
elseif nargin~=4
usage('[Zz, Zp, Zg]=bilinear(Sz,Sp,Sg,T) or [Zb, Za]=blinear(Sb,Sa,T)');
end;
p = length(Sp);
z = length(Sz);
if z > p || p==0
error('bilinear: must have at least as many poles as zeros in s-plane');
end
% ---------------- ------------------------- ------------------------
% Bilinear zero: (2+xT)/(2-xT) pole: (2+xT)/(2-xT)
% 2 z-1 pole: -1 zero: -1
% S -> - --- gain: (2-xT)/T gain: (2-xT)/T
% T z+1
% ---------------- ------------------------- ------------------------
Zg = real(Sg * prod((2-Sz*T)/T) / prod((2-Sp*T)/T));
Zp = (2+Sp*T)./(2-Sp*T);
if isempty(Sz)
Zz = -ones(size(Zp));
else
Zz = [(2+Sz*T)./(2-Sz*T)];
Zz = postpad(Zz, p, -1);
end
if nargout==2, [Zz, Zp] = zp2tf(Zz, Zp, Zg); end
|
github
|
philippboehmsturm/antx-master
|
warning_once.m
|
.m
|
antx-master/xspm8/external/fieldtrip/specest/private/warning_once.m
| 3,832 |
utf_8
|
07dc728273934663973f4c716e7a3a1c
|
function [ws warned] = warning_once(varargin)
%
% Use as one of the following
% warning_once(string)
% warning_once(string, timeout)
% warning_once(id, string)
% warning_once(id, string, timeout)
% where timeout should be inf if you don't want to see the warning ever
% again. The default timeout value is 60 seconds.
%
% It can be used instead of the MATLAB built-in function WARNING, thus as
% s = warning_once(...)
% or as
% warning_once(s)
% where s is a structure with fields 'identifier' and 'state', storing the
% state information. In other words, warning_once accepts as an input the
% same structure it returns as an output. This returns or restores the
% states of warnings to their previous values.
%
% It can also be used as
% [s w] = warning_once(...)
% where w is a boolean that indicates whether a warning as been thrown or not.
%
% Please note that you can NOT use it like this
% warning_once('the value is %d', 10)
% instead you should do
% warning_once(sprintf('the value is %d', 10))
% Copyright (C) 2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: warning_once.m 7123 2012-12-06 21:21:38Z roboos $
persistent stopwatch previous
if nargin < 1
error('You need to specify at least a warning message');
end
warned = false;
if isstruct(varargin{1})
warning(varargin{1});
return;
end
% put the arguments we will pass to warning() in this cell array
warningArgs = {};
if nargin==3
% calling syntax (id, msg, timeout)
warningArgs = varargin(1:2);
timeout = varargin{3};
fname = [warningArgs{1} '_' warningArgs{2}];
elseif nargin==2 && isnumeric(varargin{2})
% calling syntax (msg, timeout)
warningArgs = varargin(1);
timeout = varargin{2};
fname = warningArgs{1};
elseif nargin==2 && ~isnumeric(varargin{2})
% calling syntax (id, msg)
warningArgs = varargin(1:2);
timeout = 60;
fname = [warningArgs{1} '_' warningArgs{2}];
elseif nargin==1
% calling syntax (msg)
warningArgs = varargin(1);
timeout = 60; % default timeout in seconds
fname = [warningArgs{1}];
end
if isempty(timeout)
error('Timeout ill-specified');
end
if isempty(stopwatch)
stopwatch = tic;
end
if isempty(previous)
previous = struct;
end
now = toc(stopwatch); % measure time since first function call
fname = decomma(fixname(fname)); % make a nice string that is allowed as structure fieldname
if length(fname) > 63 % MATLAB max name
fname = fname(1:63);
end
if ~isfield(previous, fname) || ...
(isfield(previous, fname) && now>previous.(fname).timeout)
% warning never given before or timed out
ws = warning(warningArgs{:});
previous.(fname).timeout = now+timeout;
previous.(fname).ws = ws;
warned = true;
else
% the warning has been issued before, but has not timed out yet
ws = previous.(fname).ws;
end
end % function
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% helper functions
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function name = decomma(name)
name(name==',')=[];
end % function
|
github
|
philippboehmsturm/antx-master
|
butter.m
|
.m
|
antx-master/xspm8/external/fieldtrip/specest/private/butter.m
| 3,559 |
utf_8
|
ad82b4c04911a5ea11fd6bd2cc5fd590
|
% Copyright (C) 1999 Paul Kienzle
%
% This program 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 2 of the License, or
% (at your option) any later version.
%
% This program 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 this program; If not, see <http://www.gnu.org/licenses/>.
% Generate a butterworth filter.
% Default is a discrete space (Z) filter.
%
% [b,a] = butter(n, Wc)
% low pass filter with cutoff pi*Wc radians
%
% [b,a] = butter(n, Wc, 'high')
% high pass filter with cutoff pi*Wc radians
%
% [b,a] = butter(n, [Wl, Wh])
% band pass filter with edges pi*Wl and pi*Wh radians
%
% [b,a] = butter(n, [Wl, Wh], 'stop')
% band reject filter with edges pi*Wl and pi*Wh radians
%
% [z,p,g] = butter(...)
% return filter as zero-pole-gain rather than coefficients of the
% numerator and denominator polynomials.
%
% [...] = butter(...,'s')
% return a Laplace space filter, W can be larger than 1.
%
% [a,b,c,d] = butter(...)
% return state-space matrices
%
% References:
%
% Proakis & Manolakis (1992). Digital Signal Processing. New York:
% Macmillan Publishing Company.
% Author: Paul Kienzle <[email protected]>
% Modified by: Doug Stewart <[email protected]> Feb, 2003
function [a, b, c, d] = butter (n, W, varargin)
if (nargin>4 || nargin<2) || (nargout>4 || nargout<2)
usage ('[b, a] or [z, p, g] or [a,b,c,d] = butter (n, W [, "ftype"][,"s"])');
end
% interpret the input parameters
if (~(length(n)==1 && n == round(n) && n > 0))
error ('butter: filter order n must be a positive integer');
end
stop = 0;
digital = 1;
for i=1:length(varargin)
switch varargin{i}
case 's', digital = 0;
case 'z', digital = 1;
case { 'high', 'stop' }, stop = 1;
case { 'low', 'pass' }, stop = 0;
otherwise, error ('butter: expected [high|stop] or [s|z]');
end
end
[r, c]=size(W);
if (~(length(W)<=2 && (r==1 || c==1)))
error ('butter: frequency must be given as w0 or [w0, w1]');
elseif (~(length(W)==1 || length(W) == 2))
error ('butter: only one filter band allowed');
elseif (length(W)==2 && ~(W(1) < W(2)))
error ('butter: first band edge must be smaller than second');
end
if ( digital && ~all(W >= 0 & W <= 1))
error ('butter: critical frequencies must be in (0 1)');
elseif ( ~digital && ~all(W >= 0 ))
error ('butter: critical frequencies must be in (0 inf)');
end
% Prewarp to the band edges to s plane
if digital
T = 2; % sampling frequency of 2 Hz
W = 2/T*tan(pi*W/T);
end
% Generate splane poles for the prototype butterworth filter
% source: Kuc
C = 1; % default cutoff frequency
pole = C*exp(1i*pi*(2*[1:n] + n - 1)/(2*n));
if mod(n,2) == 1, pole((n+1)/2) = -1; end % pure real value at exp(i*pi)
zero = [];
gain = C^n;
% splane frequency transform
[zero, pole, gain] = sftrans(zero, pole, gain, W, stop);
% Use bilinear transform to convert poles to the z plane
if digital
[zero, pole, gain] = bilinear(zero, pole, gain, T);
end
% convert to the correct output form
if nargout==2,
a = real(gain*poly(zero));
b = real(poly(pole));
elseif nargout==3,
a = zero;
b = pole;
c = gain;
else
% output ss results
[a, b, c, d] = zp2ss (zero, pole, gain);
end
|
github
|
philippboehmsturm/antx-master
|
avw_hdr_make.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/avw_hdr_make.m
| 4,182 |
utf_8
|
df97baf07b917c62db1cde33abfc8416
|
function [ avw ] = avw_hdr_make
% AVW_HDR_MAKE - Create Analyze format data header (avw.hdr)
%
% [ avw ] = avw_hdr_make
%
% avw.hdr - a struct, all fields returned from the header.
% For details, find a good description on the web
% or see the Analyze File Format pdf in the
% mri_toolbox doc folder or see avw_hdr_read.m
%
% See also, AVW_HDR_READ AVW_HDR_WRITE
% AVW_IMG_READ AVW_IMG_WRITE
%
% $Revision: 7123 $ $Date: 2009/01/14 09:24:45 $
% Licence: GNU GPL, no express or implied warranties
% History: 06/2002, [email protected]
% 02/2003, [email protected]
% date/time bug at lines 97-98
% identified by [email protected]
%
% The Analyze format is copyright
% (c) Copyright, 1986-1995
% Biomedical Imaging Resource, Mayo Foundation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
version = '[$Revision: 7123 $]';
fprintf('\nAVW_HDR_MAKE [v%s]\n',version(12:16)); tic;
% Comments
% The header format is flexible and can be extended for new
% user-defined data types. The essential structures of the header
% are the header_key and the image_dimension. See avw_hdr_read
% for more detail of the header structure
avw.hdr = make_header;
t=toc; fprintf('...done (%5.2f sec).\n',t);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ hdr ] = make_header
hdr.hk = header_key;
hdr.dime = image_dimension;
hdr.hist = data_history;
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [hk] = header_key
hk.sizeof_hdr = int32(348); % must be 348!
hk.data_type(1:10) = sprintf('%10s','');
hk.db_name(1:18) = sprintf('%18s','');
hk.extents = int32(16384);
hk.session_error = int16(0);
hk.regular = sprintf('%1s','r'); % might be uint8
hk.hkey_un0 = uint8(0);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ dime ] = image_dimension
dime.dim(1:8) = int16([4 256 256 256 1 0 0 0]);
dime.vox_units(1:4) = sprintf('%4s','mm');
dime.cal_units(1:8) = sprintf('%8s','');
dime.unused1 = int16(0);
dime.datatype = int16(2);
dime.bitpix = int16(8);
dime.dim_un0 = int16(0);
dime.pixdim(1:8) = single([0 1 1 1 1000 0 0 0]);
dime.vox_offset = single(0);
dime.funused1 = single(0);
dime.funused2 = single(0);
% Set default 8bit intensity scale (from MRIcro), otherwise funused3
dime.roi_scale = single(1);
dime.cal_max = single(0);
dime.cal_min = single(0);
dime.compressed = int32(0);
dime.verified = int32(0);
dime.glmax = int32(255);
dime.glmin = int32(0);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ hist ] = data_history
datime = clock;
hist.descrip(1:80) = sprintf('%-80s','mri_toolbox @ http://eeg.sf.net/');
hist.aux_file(1:24) = sprintf('%-24s','');
hist.orient = uint8(0); % sprintf( '%1s',''); % see notes in avw_hdr_read
hist.originator(1:10) = sprintf('%-10s','');
hist.generated(1:10) = sprintf('%-10s','mri_toolbx');
hist.scannum(1:10) = sprintf('%-10s','');
hist.patient_id(1:10) = sprintf('%-10s','');
hist.exp_date(1:10) = sprintf('%02d-%02d-%04d',datime(3),datime(2),datime(1));
hist.exp_time(1:10) = sprintf('%02d-%02d-%04.1f',datime(4),datime(5),datime(6));
hist.hist_un0(1:3) = sprintf( '%-3s','');
hist.views = int32(0);
hist.vols_added = int32(0);
hist.start_field = int32(0);
hist.field_skip = int32(0);
hist.omax = int32(0);
hist.omin = int32(0);
hist.smax = int32(0);
hist.smin = int32(0);
return
|
github
|
philippboehmsturm/antx-master
|
prepare_mesh_headshape.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/prepare_mesh_headshape.m
| 9,151 |
utf_8
|
390bfd19f99b4c31bf0dda1ebd8c6c37
|
function bnd = prepare_mesh_headshape(cfg)
% PREPARE_MESH_HEADSHAPE
%
% See also PREPARE_MESH_MANUAL, PREPARE_MESH_SEGMENTATION
% Copyrights (C) 2009, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: prepare_mesh_headshape.m 7381 2013-01-23 13:08:59Z johzum $
% get the surface describing the head shape
if isstruct(cfg.headshape) && isfield(cfg.headshape, 'pnt')
% use the headshape surface specified in the configuration
headshape = cfg.headshape;
elseif isnumeric(cfg.headshape) && size(cfg.headshape,2)==3
% use the headshape points specified in the configuration
headshape.pnt = cfg.headshape;
elseif ischar(cfg.headshape)
% read the headshape from file
headshape = ft_read_headshape(cfg.headshape);
else
error('cfg.headshape is not specified correctly')
end
% usually a headshape only describes a single surface boundaries, but there are cases
% that multiple surfaces are included, e.g. skin_surface, outer_skull_surface, inner_skull_surface
nbnd = numel(headshape);
if ~isfield(headshape, 'tri')
% generate a closed triangulation from the surface points
for i=1:nbnd
headshape(i).pnt = unique(headshape(i).pnt, 'rows');
headshape(i).tri = projecttri(headshape(i).pnt);
end
end
if ~isempty(cfg.numvertices) && ~strcmp(cfg.numvertices, 'same')
for i=1:nbnd
tri1 = headshape(i).tri;
pnt1 = headshape(i).pnt;
% The number of vertices is multiplied by 3 in order to have more
% points on the original mesh than on the sphere mesh (see below).
% The rationale for this is that every projection point on the sphere
% has three corresponding points on the mesh
if (cfg.numvertices>size(pnt1,1))
[tri1, pnt1] = refinepatch(headshape(i).tri, headshape(i).pnt, 3*cfg.numvertices);
else
[tri1, pnt1] = reducepatch(headshape(i).tri, headshape(i).pnt, 3*cfg.numvertices);
end
% remove double vertices
[pnt1, tri1] = remove_double_vertices(pnt1, tri1);
% replace the probably unevenly distributed triangulation with a regular one
% and retriangulate it to the desired accuracy
[pnt2, tri2] = mysphere(cfg.numvertices); % this is a regular triangulation
[pnt1, tri1] = retriangulate(pnt1, tri1, pnt2, tri2, 2);
[pnt1, tri1] = fairsurface(pnt1, tri1, 1);% this helps redistribute the superimposed points
% remove double vertices
[headshape(i).pnt,headshape(i).tri] = remove_double_vertices(pnt1, tri1);
fprintf('returning %d vertices, %d triangles\n', size(headshape(i).pnt,1), size(headshape(i).tri,1));
end
end
% the output should only describe one or multiple boundaries and should not
% include any other fields
bnd = rmfield(headshape, setdiff(fieldnames(headshape), {'pnt', 'tri'}));
function [tri1, pnt1] = refinepatch(tri, pnt, numvertices)
fprintf('the original mesh has %d vertices against the %d requested\n',size(pnt,1),numvertices/3);
fprintf('trying to refine the compartment...\n');
[pnt1, tri1] = refine(pnt, tri, 'updown', numvertices);
function [pnt, tri] = mysphere(N)
% This is a copy of MSPHERE without the confusing output message
% Returns a triangulated sphere with approximately M vertices
% that are nicely distributed over the sphere. The vertices are aligned
% along equally spaced horizontal contours according to an algorithm of
% Dave Russel.
%
% Use as
% [pnt, tri] = msphere(M)
%
% See also SPHERE, NSPHERE, ICOSAHEDRON, REFINE
% Copyright (C) 1994, Dave Rusin
storeM = [];
storelen = [];
increaseM = 0;
while (1)
% put a single vertex at the top
phi = [0];
th = [0];
M = round((pi/4)*sqrt(N)) + increaseM;
for k=1:M
newphi = (k/M)*pi;
Q = round(2*M*sin(newphi));
for j=1:Q
phi(end+1) = newphi;
th(end+1) = (j/Q)*2*pi;
% in case of even number of contours
if mod(M,2) & k>(M/2)
th(end) = th(end) + pi/Q;
end
end
end
% put a single vertex at the bottom
phi(end+1) = [pi];
th(end+1) = [0];
% store this vertex packing
storeM(end+1).th = th;
storeM(end ).phi = phi;
storelen(end+1) = length(phi);
if storelen(end)>N
break;
else
increaseM = increaseM+1;
% fprintf('increasing M by %d\n', increaseM);
end
end
% take the vertex packing that most closely matches the requirement
[m, i] = min(abs(storelen-N));
th = storeM(i).th;
phi = storeM(i).phi;
% convert from spherical to cartehsian coordinates
[x, y, z] = sph2cart(th, pi/2-phi, 1);
pnt = [x' y' z'];
tri = convhulln(pnt);
function [pntR, triR] = remove_double_vertices(pnt, tri)
% REMOVE_VERTICES removes specified vertices from a triangular mesh
% renumbering the vertex-indices for the triangles and removing all
% triangles with one of the specified vertices.
%
% Use as
% [pnt, tri] = remove_double_vertices(pnt, tri)
pnt1 = unique(pnt, 'rows');
keeppnt = find(ismember(pnt1,pnt,'rows'));
removepnt = setdiff([1:size(pnt,1)],keeppnt);
npnt = size(pnt,1);
ntri = size(tri,1);
if all(removepnt==0 | removepnt==1)
removepnt = find(removepnt);
end
% remove the vertices and determine the new numbering (indices) in numb
keeppnt = setdiff(1:npnt, removepnt);
numb = zeros(1,npnt);
numb(keeppnt) = 1:length(keeppnt);
% look for triangles referring to removed vertices
removetri = false(ntri,1);
removetri(ismember(tri(:,1), removepnt)) = true;
removetri(ismember(tri(:,2), removepnt)) = true;
removetri(ismember(tri(:,3), removepnt)) = true;
% remove the vertices and triangles
pntR = pnt(keeppnt, :);
triR = tri(~removetri,:);
% renumber the vertex indices for the triangles
triR = numb(triR);
function [pnt1, tri1] = fairsurface(pnt, tri, N)
% FAIRSURFACE modify the mesh in order to reduce overlong edges, and
% smooth out "rough" areas. This is a non-shrinking smoothing algorithm.
% The procedure uses an elastic model : At each vertex, the neighbouring
% triangles and vertices connected directly are used. Each edge is
% considered elastic and can be lengthened or shortened, depending
% on their length. Displacement are done in 3D, so that holes and
% bumps are attenuated.
%
% Use as
% [pnt, tri] = fairsurface(pnt, tri, N);
% where N is the number of smoothing iterations.
%
% This implements:
% G.Taubin, A signal processing approach to fair surface design, 1995
% This function corresponds to spm_eeg_inv_ElastM
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
% Christophe Phillips & Jeremie Mattout
% spm_eeg_inv_ElastM.m 1437 2008-04-17 10:34:39Z christophe
%
% $Id: prepare_mesh_headshape.m 7381 2013-01-23 13:08:59Z johzum $
ts = [];
ts.XYZmm = pnt';
ts.tri = tri';
ts.nr(1) = size(pnt,1);
ts.nr(2) = size(tri,1);
% Connection vertex-to-vertex
%--------------------------------------------------------------------------
M_con = sparse([ts.tri(1,:)';ts.tri(1,:)';ts.tri(2,:)';ts.tri(3,:)';ts.tri(2,:)';ts.tri(3,:)'], ...
[ts.tri(2,:)';ts.tri(3,:)';ts.tri(1,:)';ts.tri(1,:)';ts.tri(3,:)';ts.tri(2,:)'], ...
ones(ts.nr(2)*6,1),ts.nr(1),ts.nr(1));
kpb = .1; % Cutt-off frequency
lam = .5; mu = lam/(lam*kpb-1); % Parameters for elasticity.
XYZmm = ts.XYZmm;
% smoothing iterations
%--------------------------------------------------------------------------
for j=1:N
XYZmm_o = zeros(3,ts.nr(1)) ;
XYZmm_o2 = zeros(3,ts.nr(1)) ;
for i=1:ts.nr(1)
ln = find(M_con(:,i));
d_i = sqrt(sum((XYZmm(:,ln)-XYZmm(:,i)*ones(1,length(ln))).^2));
if sum(d_i)==0
w_i = zeros(size(d_i));
else
w_i = d_i/sum(d_i);
end
XYZmm_o(:,i) = XYZmm(:,i) + ...
lam * sum((XYZmm(:,ln)-XYZmm(:,i)*ones(1,length(ln))).*(ones(3,1)*w_i),2);
end
for i=1:ts.nr(1)
ln = find(M_con(:,i));
d_i = sqrt(sum((XYZmm(:,ln)-XYZmm(:,i)*ones(1,length(ln))).^2));
if sum(d_i)==0
w_i = zeros(size(d_i));
else
w_i = d_i/sum(d_i);
end
XYZmm_o2(:,i) = XYZmm_o(:,i) + ...
mu * sum((XYZmm_o(:,ln)-XYZmm_o(:,i)*ones(1,length(ln))).*(ones(3,1)*w_i),2);
end
XYZmm = XYZmm_o2;
end
% collect output results
%--------------------------------------------------------------------------
pnt1 = XYZmm';
tri1 = tri;
if 0
% this is some test/demo code
bnd = [];
[bnd.pnt, bnd.tri] = icosahedron162;
scale = 1+0.3*randn(size(pnt,1),1);
bnd.pnt = bnd.pnt .* [scale scale scale];
figure
ft_plot_mesh(bnd)
[bnd.pnt, bnd.tri] = fairsurface(bnd.pnt, bnd.tri, 10);
figure
ft_plot_mesh(bnd)
end
|
github
|
philippboehmsturm/antx-master
|
normals.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/normals.m
| 2,582 |
utf_8
|
c474f14b83010d46459376013fa6e047
|
function [nrm] = normals(pnt, dhk, opt);
% NORMALS compute the surface normals of a triangular mesh
% for each triangle or for each vertex
%
% [nrm] = normals(pnt, dhk, opt)
% where opt is either 'vertex' or 'triangle'
% Copyright (C) 2002-2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: normals.m 7123 2012-12-06 21:21:38Z roboos $
if nargin<3
opt='vertex';
elseif (opt(1)=='v' | opt(1)=='V')
opt='vertex';
elseif (opt(1)=='t' | opt(1)=='T')
opt='triangle';
else
error('invalid optional argument');
end
npnt = size(pnt,1);
ndhk = size(dhk,1);
% shift to center
pnt(:,1) = pnt(:,1)-mean(pnt(:,1),1);
pnt(:,2) = pnt(:,2)-mean(pnt(:,2),1);
pnt(:,3) = pnt(:,3)-mean(pnt(:,3),1);
% compute triangle normals
% nrm_dhk = zeros(ndhk, 3);
% for i=1:ndhk
% v2 = pnt(dhk(i,2),:) - pnt(dhk(i,1),:);
% v3 = pnt(dhk(i,3),:) - pnt(dhk(i,1),:);
% nrm_dhk(i,:) = cross(v2, v3);
% end
% vectorized version of the previous part
v2 = pnt(dhk(:,2),:) - pnt(dhk(:,1),:);
v3 = pnt(dhk(:,3),:) - pnt(dhk(:,1),:);
nrm_dhk = cross(v2, v3);
if strcmp(opt, 'vertex')
% compute vertex normals
nrm_pnt = zeros(npnt, 3);
for i=1:ndhk
nrm_pnt(dhk(i,1),:) = nrm_pnt(dhk(i,1),:) + nrm_dhk(i,:);
nrm_pnt(dhk(i,2),:) = nrm_pnt(dhk(i,2),:) + nrm_dhk(i,:);
nrm_pnt(dhk(i,3),:) = nrm_pnt(dhk(i,3),:) + nrm_dhk(i,:);
end
% normalise the direction vectors to have length one
nrm = nrm_pnt ./ (sqrt(sum(nrm_pnt.^2, 2)) * ones(1,3));
else
% normalise the direction vectors to have length one
nrm = nrm_dhk ./ (sqrt(sum(nrm_dhk.^2, 2)) * ones(1,3));
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% fast cross product to replace the Matlab standard version
function [c] = cross(a,b)
c = [a(:,2).*b(:,3)-a(:,3).*b(:,2) a(:,3).*b(:,1)-a(:,1).*b(:,3) a(:,1).*b(:,2)-a(:,2).*b(:,1)];
|
github
|
philippboehmsturm/antx-master
|
rejectvisual_trial.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/rejectvisual_trial.m
| 9,172 |
utf_8
|
806a4d411be2efeca6ab8e316737ed41
|
function [chansel, trlsel, cfg] = rejectvisual_trial(cfg, data);
% SUBFUNCTION for ft_rejectvisual
% determine the initial selection of trials and channels
nchan = length(data.label);
ntrl = length(data.trial);
cfg.channel = ft_channelselection(cfg.channel, data.label);
trlsel = true(1,ntrl);
chansel = false(1,nchan);
chansel(match_str(data.label, cfg.channel)) = 1;
% compute the sampling frequency from the first two timepoints
fsample = 1/mean(diff(data.time{1}));
% compute the offset from the time axes
offset = zeros(ntrl,1);
for i=1:ntrl
offset(i) = time2offset(data.time{i}, fsample);
end
if (isfield(cfg, 'preproc') && ~isempty(cfg.preproc))
ft_progress('init', cfg.feedback, 'filtering data');
for i=1:ntrl
ft_progress(i/ntrl, 'filtering data in trial %d of %d\n', i, ntrl);
[data.trial{i}, label, time, cfg.preproc] = preproc(data.trial{i}, data.label, data.time{i}, cfg.preproc);
end
ft_progress('close');
end
% select the specified latency window from the data
% this is done AFTER the filtering to prevent edge artifacts
for i=1:ntrl
begsample = nearest(data.time{i}, cfg.latency(1));
endsample = nearest(data.time{i}, cfg.latency(2));
data.time{i} = data.time{i}(begsample:endsample);
data.trial{i} = data.trial{i}(:,begsample:endsample);
end
h = figure;
axis([0 1 0 1]);
axis off
% the info structure will be attached to the figure
% and passed around between the callback functions
if strcmp(cfg.plotlayout,'1col') % hidden config option for plotting trials differently
info = [];
info.ncols = 1;
info.nrows = nchan;
info.chanlop = 1;
info.trlop = 1;
info.ltrlop = 0;
info.quit = 0;
info.ntrl = ntrl;
info.nchan = nchan;
info.data = data;
info.cfg = cfg;
info.offset = offset;
info.chansel = chansel;
info.trlsel = trlsel;
% determine the position of each subplot within the axis
for row=1:info.nrows
for col=1:info.ncols
indx = (row-1)*info.ncols + col;
if indx>info.nchan
continue
end
info.x(indx) = (col-0.9)/info.ncols;
info.y(indx) = 1 - (row-0.45)/(info.nrows+1);
end
end
info.label = info.data.label;
elseif strcmp(cfg.plotlayout,'square')
info = [];
info.ncols = ceil(sqrt(nchan));
info.nrows = ceil(sqrt(nchan));
info.chanlop = 1;
info.trlop = 1;
info.ltrlop = 0;
info.quit = 0;
info.ntrl = ntrl;
info.nchan = nchan;
info.data = data;
info.cfg = cfg;
info.offset = offset;
info.chansel = chansel;
info.trlsel = trlsel;
% determine the position of each subplot within the axis
for row=1:info.nrows
for col=1:info.ncols
indx = (row-1)*info.ncols + col;
if indx>info.nchan
continue
end
info.x(indx) = (col-0.9)/info.ncols;
info.y(indx) = 1 - (row-0.45)/(info.nrows+1);
end
end
info.label = info.data.label;
end
info.ui.quit = uicontrol(h,'units','pixels','position',[ 5 5 40 18],'String','quit','Callback',@stop);
info.ui.prev = uicontrol(h,'units','pixels','position',[ 50 5 25 18],'String','<','Callback',@prev);
info.ui.next = uicontrol(h,'units','pixels','position',[ 75 5 25 18],'String','>','Callback',@next);
info.ui.prev10 = uicontrol(h,'units','pixels','position',[105 5 25 18],'String','<<','Callback',@prev10);
info.ui.next10 = uicontrol(h,'units','pixels','position',[130 5 25 18],'String','>>','Callback',@next10);
info.ui.bad = uicontrol(h,'units','pixels','position',[160 5 50 18],'String','bad','Callback',@markbad);
info.ui.good = uicontrol(h,'units','pixels','position',[210 5 50 18],'String','good','Callback',@markgood);
info.ui.badnext = uicontrol(h,'units','pixels','position',[270 5 50 18],'String','bad>','Callback',@markbad_next);
info.ui.goodnext = uicontrol(h,'units','pixels','position',[320 5 50 18],'String','good>','Callback',@markgood_next);
set(gcf, 'WindowButtonUpFcn', @button);
set(gcf, 'KeyPressFcn', @key);
guidata(h,info);
interactive = 1;
while interactive && ishandle(h)
redraw(h);
info = guidata(h);
if info.quit == 0,
uiwait;
else
chansel = info.chansel;
trlsel = info.trlsel;
delete(h);
break
end
end % while interactive
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTIONS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function varargout = markbad_next(varargin)
markbad(varargin{:});
next(varargin{:});
function varargout = markgood_next(varargin)
markgood(varargin{:});
next(varargin{:});
function varargout = next(h, eventdata, handles, varargin)
info = guidata(h);
info.ltrlop = info.trlop;
if info.trlop < info.ntrl,
info.trlop = info.trlop + 1;
end;
guidata(h,info);
uiresume;
function varargout = prev(h, eventdata, handles, varargin)
info = guidata(h);
info.ltrlop = info.trlop;
if info.trlop > 1,
info.trlop = info.trlop - 1;
end;
guidata(h,info);
uiresume;
function varargout = next10(h, eventdata, handles, varargin)
info = guidata(h);
info.ltrlop = info.trlop;
if info.trlop < info.ntrl - 10,
info.trlop = info.trlop + 10;
else
info.trlop = info.ntrl;
end;
guidata(h,info);
uiresume;
function varargout = prev10(h, eventdata, handles, varargin)
info = guidata(h);
info.ltrlop = info.trlop;
if info.trlop > 10,
info.trlop = info.trlop - 10;
else
info.trlop = 1;
end;
guidata(h,info);
uiresume;
function varargout = markgood(h, eventdata, handles, varargin)
info = guidata(h);
info.trlsel(info.trlop) = 1;
fprintf(description_trial(info));
title(description_trial(info));
guidata(h,info);
% uiresume;
function varargout = markbad(h, eventdata, handles, varargin)
info = guidata(h);
info.trlsel(info.trlop) = 0;
fprintf(description_trial(info));
title(description_trial(info));
guidata(h,info);
% uiresume;
function varargout = key(h, eventdata, handles, varargin)
info = guidata(h);
switch lower(eventdata.Key)
case 'rightarrow'
if info.trlop ~= info.ntrl
next(h);
else
fprintf('at last trial\n');
end
case 'leftarrow'
if info.trlop ~= 1
prev(h);
else
fprintf('at first trial\n');
end
case 'g'
markgood(h);
case 'b'
markbad(h);
case 'q'
stop(h);
otherwise
fprintf('unknown key pressed\n');
end
function varargout = button(h, eventdata, handles, varargin)
pos = get(gca, 'CurrentPoint');
x = pos(1,1);
y = pos(1,2);
info = guidata(h);
dx = info.x - x;
dy = info.y - y;
dd = sqrt(dx.^2 + dy.^2);
[d, i] = min(dd);
if d<0.5/max(info.nrows, info.ncols) && i<=info.nchan
info.chansel(i) = ~info.chansel(i); % toggle
info.chanlop = i;
fprintf(description_channel(info));
guidata(h,info);
uiresume;
else
fprintf('button clicked\n');
return
end
function varargout = stop(h, eventdata, handles, varargin)
info = guidata(h);
info.quit = 1;
guidata(h,info);
uiresume;
function str = description_channel(info);
if info.chansel(info.chanlop)
str = sprintf('channel %s marked as GOOD\n', info.data.label{info.chanlop});
else
str = sprintf('channel %s marked as BAD\n', info.data.label{info.chanlop});
end
function str = description_trial(info);
if info.trlsel(info.trlop)
str = sprintf('trial %d marked as GOOD\n', info.trlop);
else
str = sprintf('trial %d marked as BAD\n', info.trlop);
end
function redraw(h)
if ~ishandle(h)
return
end
info = guidata(h);
fprintf(description_trial(info));
cla;
title('');
drawnow
hold on
dat = info.data.trial{info.trlop};
time = info.data.time{info.trlop};
if ~isempty(info.cfg.alim)
% use fixed amplitude limits for amplitude scaling
amax = info.cfg.alim;
else
% use automatic amplitude limits for scaling, these are different for each trial
amax = max(max(abs(dat(info.chansel,:))));
end
tmin = time(1);
tmax = time(end);
% scale the time values between 0.1 and 0.9
time = 0.1 + 0.8*(time-tmin)/(tmax-tmin);
% scale the amplitude values between -0.5 and 0.5, offset should not be removed
dat = dat ./ (2*amax);
for row=1:info.nrows
for col=1:info.ncols
chanindx = (row-1)*info.ncols + col;
if chanindx>info.nchan || ~info.chansel(chanindx)
continue
end
% scale the time values for this subplot
tim = (col-1)/info.ncols + time/info.ncols;
% scale the amplitude values for this subplot
amp = dat(chanindx,:)./info.nrows + 1 - row/(info.nrows+1);
plot(tim, amp, 'k')
end
end
% enable or disable buttons as appropriate
if info.trlop == 1
set(info.ui.prev, 'Enable', 'off');
set(info.ui.prev10, 'Enable', 'off');
else
set(info.ui.prev, 'Enable', 'on');
set(info.ui.prev10, 'Enable', 'on');
end
if info.trlop == info.ntrl
set(info.ui.next, 'Enable', 'off');
set(info.ui.next10, 'Enable', 'off');
else
set(info.ui.next, 'Enable', 'on');
set(info.ui.next10, 'Enable', 'on');
end
if info.ltrlop == info.trlop && info.trlop == info.ntrl
set(info.ui.badnext,'Enable', 'off');
set(info.ui.goodnext,'Enable', 'off');
else
set(info.ui.badnext,'Enable', 'on');
set(info.ui.goodnext,'Enable', 'on');
end
text(info.x, info.y, info.label);
title(description_trial(info));
hold off
|
github
|
philippboehmsturm/antx-master
|
wizard_base.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/wizard_base.m
| 11,679 |
utf_8
|
d5e26be7986669db7dbb81191ca5a328
|
function h = wizard_gui(filename)
% This is the low level wizard function. It evaluates the matlab content
% in the workspace of the calling function. To prevent overwriting
% variables in the BASE workspace, this function should be called from a
% wrapper function. The wrapper function whoudl pause execution untill the
% wizard figure is deleted.
% Copyright (C) 2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: wizard_base.m 7123 2012-12-06 21:21:38Z roboos $
% create a new figure
h = figure('Name','Wizard',...
'NumberTitle','off',...
'MenuBar','none',...
'KeyPressFcn', @cb_keyboard,...
'resizeFcn', @cb_resize,...
'closeRequestFcn', @cb_cancel);
% movegui(h,'center');
% set(h, 'ToolBar', 'figure');
if nargin>0
filename = which(filename);
[p, f, x] = fileparts(filename);
data = [];
data.path = p;
data.file = f;
data.ext = x;
data.current = 0;
data.script = script_parse(filename);
guidata(h, data); % attach the data to the GUI figure
else
data = [];
data.path = [];
data.file = [];
data.ext = [];
data.current = 0;
data.script = script_parse([]);
guidata(h, data); % attach the data to the GUI figure
cb_load(h);
end
cb_show(h); % show the GUI figure
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_keyboard(h, eventdata)
h = parentfig(h);
dbstack
if isequal(eventdata.Key, 'o') && isequal(eventdata.Modifier, {'control'})
cb_load(h);
elseif isequal(eventdata.Key, 's') && isequal(eventdata.Modifier, {'control'})
cb_save(h);
elseif isequal(eventdata.Key, 'e') && isequal(eventdata.Modifier, {'control'})
cb_edit(h);
elseif isequal(eventdata.Key, 'p') && isequal(eventdata.Modifier, {'control'})
cb_prev(h);
elseif isequal(eventdata.Key, 'n') && isequal(eventdata.Modifier, {'control'})
cb_next(h);
elseif isequal(eventdata.Key, 'q') && isequal(eventdata.Modifier, {'control'})
cb_cancel(h);
elseif isequal(eventdata.Key, 'x') && isequal(eventdata.Modifier, {'control'})
% FIXME this does not work
cb_done(h);
elseif isequal(eventdata.Key, 'n') && any(strcmp(eventdata.Modifier, 'shift')) && any(strcmp(eventdata.Modifier, 'control'))
% FIXME this does not always work correctly
cb_skip(h);
end
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_show(h, eventdata)
h = parentfig(h);
data = guidata(h);
clf(h);
if data.current<1
% introduction, construct the GUI elements
ui_next = uicontrol(h, 'tag', 'ui_next', 'KeyPressFcn', @cb_keyboard, 'style', 'pushbutton', 'string', 'next >', 'callback', @cb_next);
ui_help = uicontrol(h, 'tag', 'ui_help', 'KeyPressFcn', @cb_keyboard, 'style', 'text', 'max', 10, 'horizontalAlignment', 'left', 'FontName', '', 'backgroundColor', get(h, 'color'));
% display the introduction text
title = cat(2, data.file, ' - introduction');
tmp = {data.script.title};
help = sprintf('%s\n', tmp{:});
help = sprintf('This wizard will help you through the following steps:\n\n%s', help);
set(ui_help, 'string', help);
set(h, 'Name', title);
elseif data.current>length(data.script)
% finalization, construct the GUI elements
ui_prev = uicontrol(h, 'tag', 'ui_prev', 'KeyPressFcn', @cb_keyboard, 'style', 'pushbutton', 'string', '< prev', 'callback', @cb_prev);
ui_next = uicontrol(h, 'tag', 'ui_next', 'KeyPressFcn', @cb_keyboard, 'style', 'pushbutton', 'string', 'finish', 'callback', @cb_done);
ui_help = uicontrol(h, 'tag', 'ui_help', 'KeyPressFcn', @cb_keyboard, 'style', 'text', 'max', 10, 'horizontalAlignment', 'left', 'FontName', '', 'backgroundColor', get(h, 'color'));
% display the finalization text
title = cat(2, data.file, ' - finish');
help = sprintf('If you click finish, the variables created by the script will be exported to the Matlab workspace\n');
set(ui_help, 'string', help);
set(h, 'Name', title);
else
% normal wizard step, construct the GUI elements
ui_prev = uicontrol(h, 'tag', 'ui_prev', 'KeyPressFcn', @cb_keyboard, 'style', 'pushbutton', 'string', '< prev', 'callback', @cb_prev);
ui_next = uicontrol(h, 'tag', 'ui_next', 'KeyPressFcn', @cb_keyboard, 'style', 'pushbutton', 'string', 'next >', 'callback', @cb_next);
ui_help = uicontrol(h, 'tag', 'ui_help', 'KeyPressFcn', @cb_keyboard, 'style', 'text', 'max', 10, 'horizontalAlignment', 'left', 'FontName', '', 'backgroundColor', get(h, 'color'));
ui_code = uicontrol(h, 'tag', 'ui_code', 'KeyPressFcn', @cb_keyboard, 'style', 'edit', 'max', 10, 'horizontalAlignment', 'left', 'FontName', 'Courier', 'backgroundColor', 'white');
% display the current wizard content
help = data.script(data.current).help;
code = data.script(data.current).code;
title = cat(2, data.file, ' - ', data.script(data.current).title);
set(ui_help, 'string', help);
set(ui_code, 'string', code);
set(h, 'Name', title);
end
cb_resize(h);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_resize(h, eventdata)
h = parentfig(h);
ui_prev = findobj(h, 'tag', 'ui_prev');
ui_next = findobj(h, 'tag', 'ui_next');
ui_help = findobj(h, 'tag', 'ui_help');
ui_code = findobj(h, 'tag', 'ui_code');
siz = get(h, 'position');
x = siz(3);
y = siz(4);
w = (y-40-20)/2;
if ~isempty(ui_prev)
set(ui_prev, 'position', [x-150 10 60 20]);
end
if ~isempty(ui_next)
set(ui_next, 'position', [x-080 10 60 20]);
end
if ~isempty(ui_code) && ~isempty(ui_help)
set(ui_code, 'position', [10 40 x-20 w]);
set(ui_help, 'position', [10 50+w x-20 w]);
else
set(ui_help, 'position', [10 40 x-20 y-50]);
end
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_prev(h, eventdata)
h = parentfig(h);
cb_disable(h);
data = guidata(h);
if data.current>0
data.current = data.current - 1;
end
guidata(h, data);
cb_show(h);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_next(h, eventdata)
h = parentfig(h);
cb_disable(h);
data = guidata(h);
if data.current>0
title = cat(2, data.file, ' - busy');
set(h, 'Name', title);
ui_code = findobj(h, 'tag', 'ui_code');
code = get(ui_code, 'string');
try
for i=1:size(code,1)
evalin('caller', code(i,:));
end
catch
lasterr;
end
data.script(data.current).code = code;
end
data.current = data.current+1;
guidata(h, data);
cb_show(h);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_skip(h, eventdata)
h = parentfig(h);
cb_disable(h);
data = guidata(h);
data.current = data.current+1;
guidata(h, data);
cb_show(h);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_disable(h, eventdata)
h = parentfig(h);
ui_prev = findobj(h, 'tag', 'ui_prev');
ui_next = findobj(h, 'tag', 'ui_next');
ui_help = findobj(h, 'tag', 'ui_help');
ui_code = findobj(h, 'tag', 'ui_code');
set(ui_prev, 'Enable', 'off');
set(ui_next, 'Enable', 'off');
set(ui_help, 'Enable', 'off');
set(ui_code, 'Enable', 'off');
drawnow
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_enable(h, eventdata)
h = parentfig(h);
ui_prev = findobj(h, 'tag', 'ui_prev');
ui_next = findobj(h, 'tag', 'ui_next');
ui_help = findobj(h, 'tag', 'ui_help');
ui_code = findobj(h, 'tag', 'ui_code');
set(ui_prev, 'Enable', 'on');
set(ui_next, 'Enable', 'on');
set(ui_help, 'Enable', 'on');
set(ui_code, 'Enable', 'on');
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_edit(h, eventdata)
h = parentfig(h);
data = guidata(h);
filename = fullfile(data.path, [data.file data.ext]);
edit(filename);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_load(h, eventdata)
h = parentfig(h);
cb_disable(h);
[f, p] = uigetfile('*.m', 'Load script from an M-file');
if ~isequal(f,0)
data = guidata(h);
filename = fullfile(p, f);
[p, f, x] = fileparts(filename);
str = script_parse(filename);
data.script = str;
data.current = 0;
data.path = p;
data.file = f;
data.ext = x;
guidata(h, data);
cb_show(h);
end
cb_enable(h);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_save(h, eventdata)
cb_disable(h);
data = guidata(h);
filename = fullfile(data.path, [data.file data.ext]);
[f, p] = uiputfile('*.m', 'Save script to an M-file', filename);
if ~isequal(f,0)
filename = fullfile(p, f);
[p, f, x] = fileparts(filename);
fid = fopen(filename, 'wt');
script = data.script;
for k=1:length(script)
fprintf(fid, '%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n');
for i=1:size(script(k).help, 1)
fprintf(fid, '%% %s\n', deblank(script(k).help(i,:)));
end
for i=1:size(script(k).code, 1)
fprintf(fid, '%s\n', deblank(script(k).code(i,:)));
end
end
fclose(fid);
data.path = p;
data.file = f;
data.ext = x;
guidata(h, data);
cb_show(h);
end
cb_enable(h);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_done(h, eventdata)
h = parentfig(h);
cb_disable(h);
assignin('caller', 'wizard_ok', 1);
delete(h);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_cancel(h, eventdata)
h = parentfig(h);
cb_disable(h);
assignin('caller', 'wizard_ok', 0);
delete(h);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function script = script_parse(filename)
if isempty(filename)
script.title = '';
script.help = '';
script.code = '';
return
end
fid = fopen(filename);
str = {};
while ~feof(fid)
str{end+1} = fgetl(fid);
end
str = str(:);
fclose(fid);
i = 1; % line number
k = 1; % block number
script = [];
while i<=length(str)
script(k).title = {};
script(k).help = {};
script(k).code = {};
while i<=length(str) && ~isempty(regexp(str{i}, '^%%%%', 'once'))
% skip the seperator lines
i = i+1;
end
while i<=length(str) && ~isempty(regexp(str{i}, '^%', 'once'))
script(k).help{end+1} = str{i}(2:end);
i = i+1;
end
while i<=length(str) && isempty(regexp(str{i}, '^%%%%', 'once'))
script(k).code{end+1} = str{i};
i = i+1;
end
k = k+1;
end
sel = false(size(script));
for k=1:length(script)
sel(k) = isempty(script(k).help) && isempty(script(k).code);
if length(script(k).help)>0
script(k).title = char(script(k).help{1});
else
script(k).title = '<unknown>';
end
script(k).help = char(script(k).help(:));
script(k).code = char(script(k).code(:));
end
script(sel) = [];
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function h = parentfig(h)
while get(h, 'parent')
h = get(h, 'parent');
end
return
|
github
|
philippboehmsturm/antx-master
|
spikesort.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/spikesort.m
| 5,888 |
utf_8
|
07eeb9336688a2791adebdd3a8441a50
|
function [numA, numB, indA, indB] = spikesort(numA, numB, varargin);
% SPIKESORT uses a variation on the cocktail sort algorithm in combination
% with a city block distance to achieve N-D trial pairing between spike
% counts. The sorting is not guaranteed to result in the optimal pairing. A
% linear pre-sorting algorithm is used to create good initial starting
% positions.
%
% The goal of this function is to achieve optimal trial-pairing prior to
% stratifying the spike numbers in two datasets by random removal of some
% spikes in the trial and channel with the largest numnber of spikes.
% Pre-sorting based on the city-block distance between the spike count
% ensures that as few spikes as possible are lost.
%
% Use as
% [srtA, srtB, indA, indB] = spikesort(numA, numB, ...)
%
% Optional arguments should be specified as key-value pairs and can include
% 'presort' number representing the column, 'rowwise' or 'global'
%
% Example
% numA = reshape(randperm(100*3), 100, 3);
% numB = reshape(randperm(100*3), 100, 3);
% [srtA, srtB, indA, indB] = spikesort(numA, numB);
% % check that the order is correct, the following should be zero
% numA(indA,:) - srtA
% numB(indB,:) - srtB
%
% See also COCKTAILSORT
% Copyright (C) 2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: spikesort.m 7123 2012-12-06 21:21:38Z roboos $
% this can be used for printing detailled user feedback
fb = false;
% get the options
presort = ft_getopt(varargin, 'presort');
if any(size(numA)~=size(numB))
error('input dimensions should be the same');
end
bottom = 1;
top = size(numA,1);
swapped = true;
dist = zeros(1,top); % this will hold the distance between the trials in each pair
distswap = zeros(1,2); % this will hold the distance for two trials after swapping
% this is to keep track of the row-ordering during sorting
sel = 1:size(numA,2);
numA(:,end+1) = 1:top;
numB(:,end+1) = 1:top;
% compute the initial distance between the trial pairs using city block distance metric
for i=1:top
dist(i) = sum(abs(numA(i,sel)-numB(i,sel)));
end
if fb
fprintf('initial cost = %d\n', sum(dist));
end
if isnumeric(presort)
% start by pre-sorting on the first column only
[dum, indA] = sort(numA(:,presort));
[dum, indB] = sort(numB(:,presort));
numA = numA(indA,:);
numB = numB(indB,:);
elseif strcmp(presort, 'rowwise')
full = cityblock(numA(:,sel), numB(:,sel));
link = zeros(1,top);
for i=1:top
d = full(i,:);
d(link(1:(i-1))) = inf;
[m, ind] = min(d);
link(i) = ind;
end
indA = 1:top;
indB = link;
numB = numB(link,:);
elseif strcmp(presort, 'global')
full = cityblock(numA(:,sel), numB(:,sel));
link = zeros(1,top);
while ~all(link)
[m, i] = min(full(:));
[j, k] = ind2sub(size(full), i);
full(j,:) = inf;
full(:,k) = inf;
link(j) = k;
end
indA = 1:top;
indB = link;
numB = numB(link,:);
end
% compute the initial distance between the trial pairs
% using city block distance metric
for i=1:top
dist(i) = sum(abs(numA(i,sel)-numB(i,sel)));
end
if fb
fprintf('cost after pre-sort = %d\n', sum(dist));
end
while swapped
swapped = false;
for i=bottom:(top-1)
% compute the distances between the trials after swapping
% using city block distance metric
distswap(1) = sum(abs(numA(i,sel)-numB(i+1,sel)));
distswap(2) = sum(abs(numA(i+1,sel)-numB(i,sel)));
costNow = sum(dist([i i+1]));
costSwp = sum(distswap);
if costNow>costSwp % test whether the two elements are in the correct order
numB([i i+1], :) = numB([i+1 i], :); % let the two elements change places
dist([i i+1]) = distswap; % update the distance vector
swapped = true;
end
end
% decreases `top` because the element with the largest value in the unsorted
% part of the list is now on the position top
top = top - 1;
for i=top:-1:(bottom+1)
% compute the distances between the trials after swapping
% using city block distance metric
distswap(1) = sum(abs(numA(i,sel)-numB(i-1,sel)));
distswap(2) = sum(abs(numA(i-1,sel)-numB(i,sel)));
costNow = sum(dist([i i-1]));
costSwp = sum(distswap);
if costNow>costSwp
numB([i i-1], :) = numB([i-1 i], :); % let the two elements change places
dist([i i-1]) = distswap; % update the distance vector
swapped = true;
end
end
% increases `bottom` because the element with the smallest value in the unsorted
% part of the list is now on the position bottom
bottom = bottom + 1;
end % while swapped
if fb
fprintf('final cost = %d\n', sum(dist));
end
indA = numA(:,end);
numA = numA(:,sel);
indB = numB(:,end);
numB = numB(:,sel);
end % function spikesort
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function d = cityblock(a, b)
d = zeros(size(a,1), size(b,1));
for i=1:size(a,1)
for j=1:size(b,1)
d(i,j) = sum(abs(a(i,:)-b(j,:)));
end
end
end % function cityblock
|
github
|
philippboehmsturm/antx-master
|
nansum.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/nansum.m
| 185 |
utf_8
|
4859ec062780c478011dd7a8d94684a0
|
% NANSUM provides a replacement for MATLAB's nanmean.
%
% For usage see SUM.
function y = nansum(x, dim)
if nargin == 1
dim = 1;
end
idx = isnan(x);
x(idx) = 0;
y = sum(x, dim);
end
|
github
|
philippboehmsturm/antx-master
|
shiftpredict.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/shiftpredict.m
| 8,738 |
utf_8
|
09de5132a8fd351c7122d799783ae0ff
|
function [prb, cohobs, mcohrnd] = shiftpredict(cfg, dat, datindx, refindx, trltapcnt);
% SHIFTPREDICT implements a shift-predictor for testing significance
% of coherence within a single condition. This function is a subfunction
% for SOURCESTATISTICS_SHIFTPREDICT and FREQSTATISTICS_SHIFTPREDICT.
%
% cfg.method
% cfg.numrandomization
% cfg.method
% cfg.method
% cfg.loopdim
% cfg.feedback
% cfg.method
% cfg.loopdim
% cfg.correctm
% cfg.tail
% TODO this function should be reimplemented as statfun_shiftpredict for the general statistics framework
% Copyright (C) 2005, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: shiftpredict.m 7123 2012-12-06 21:21:38Z roboos $
nsgn = size(dat,1);
ntap = size(dat,2); % total number of tapers over all trials
nfrq = size(dat,3);
if nargin<4
% assume that each trial consists of a single taper only
ntrl = size(dat,2);
trltapcnt = ones(1,ntrl);
fprintf('assuming one taper per trial\n');
else
% each trial contains multiple tapers
ntrl = length(trltapcnt);
trltapcnt = trltapcnt(:)';
fprintf('number of tapers varies from %d to %d\n', min(trltapcnt), max(trltapcnt));
end
% allocate memory to hold the probabilities
if version('-release')>=14
prb_pos = zeros(length(refindx),length(datindx),nfrq, 'single');
prb_neg = zeros(length(refindx),length(datindx),nfrq, 'single');
else
prb_pos = zeros(length(refindx),length(datindx),nfrq);
prb_neg = zeros(length(refindx),length(datindx),nfrq);
end
% compute the power per taper, per trial, and in total
pow_tap = (abs(dat).^2);
pow_trl = zeros(nsgn,ntrl,nfrq);
for i=1:ntrl
% this is the taper selection if the number of tapers per trial is different
tapbeg = 1 + sum([0 trltapcnt(1:(i-1))]);
tapend = sum([0 trltapcnt(1:(i ))]);
% this would be the taper selection if the number of tapers per trial is identical
% tapbeg = 1 + (i-1)*ntap;
% tapend = (i )*ntap;
% average the power per trial over the tapers in that trial
pow_trl(:,i,:) = mean(pow_tap(:,tapbeg:tapend,:),2);
end
pow_tot = reshape(mean(pow_trl,2), nsgn, nfrq);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% normalise the data, also see the COMPUTECOH subfunction
switch cfg.method
case {'abscoh', 'imagcoh', 'absimagcoh', 'atanh', 'atanh_randphase'}
% normalise, so that the complex conjugate multiplication immediately results in coherence
if ~all(trltapcnt==trltapcnt(1))
error('all trials should have the same number of tapers');
end
for i=1:nsgn
for k=1:nfrq
dat(i,:,k) = dat(i,:,k) ./ sqrt(pow_tot(i,k)*ntrl*trltapcnt(1));
end
end
case {'amplcorr', 'absamplcorr'}
% normalize so that the multiplication immediately results in correlation
% this uses the amplitude, which is the sqrt of the power per trial
dat = sqrt(pow_trl);
% each signal should have zero mean
fa = reshape(mean(dat,2), nsgn, nfrq); % mean over trials
for i=1:ntrl
dat(:,i,:) = (dat(:,i,:) - fa);
end
% each signal should have unit variance
fs = reshape(sqrt(sum(dat.^2,2)/ntrl), nsgn, nfrq); % standard deviation over trials
for i=1:ntrl
dat(:,i,:) = dat(:,i,:)./fs;
end
% also normalize for the number of trials
dat = dat./sqrt(ntrl);
otherwise
error('unknown method for shift-predictor')
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% create the random shuffling index vectors
nrnd = cfg.numrandomization;
randsel = [];
switch cfg.method
case {'abscoh', 'imagcoh', 'absimagcoh', 'atanh'}
for i=1:nrnd
% the number of tapers is identical for each trial
randsel(i,:) = randblockshift(1:sum(trltapcnt), trltapcnt(1));
end
case {'amplcorr', 'absamplcorr'}
for i=1:nrnd
randsel(i,:) = randperm(ntrl);
end
case {'atanh_randphase'},
for i=1:nrnd
rndphs = exp(j.*2.*pi.*rand(length(unique(cfg.origtrl))));
randsel(i,:) = rndphs(cfg.origtrl);
end
end
% select the subset of reference signals
if all(refindx(:)'==1:size(dat,1))
% only make a shallow copy to save memory
datref = dat;
else
% make a deep copy of the selected data
datref = dat(refindx,:,:);
end
% select the subset of target signals
if all(datindx(:)'==1:size(dat,1))
% only make a shallow copy to save memory
dat = dat;
else
% make a deep copy of the selected data
dat = dat(datindx,:,:);
end
% compute the observed coherence
cohobs = computecoh(datref, dat, cfg.method, cfg.loopdim);
mcohrnd = zeros(size(cohobs));
progress('init', cfg.feedback, 'Computing shift-predicted coherence');
for i=1:nrnd
progress(i/nrnd, 'Computing shift-predicted coherence %d/%d\n', i, nrnd);
% randomize the reference signal and re-compute coherence
if all(isreal(randsel(i,:))),
datrnd = datref(:,randsel(i,:),:);
else
datrnd = datref.*conj(repmat(randsel(i,:), [size(datref,1) 1 size(datref,3)]));
end
cohrnd = computecoh(datrnd, dat, cfg.method, cfg.loopdim);
mcohrnd = cohrnd + mcohrnd;
% compare the observed coherence with the randomized one
if strcmp(cfg.correctm, 'yes')
prb_pos = prb_pos + (cohobs<max(cohrnd(:)));
prb_neg = prb_neg + (cohobs>min(cohrnd(:)));
else
prb_pos = prb_pos + (cohobs<cohrnd);
prb_neg = prb_neg + (cohobs>cohrnd);
end
end
progress('close');
mcohrnd = mcohrnd./nrnd;
if cfg.tail==1
clear prb_neg % not needed any more, free some memory
prb = prb_pos./nrnd;
elseif cfg.tail==-1
clear prb_pos % not needed any more, free some memory
prb = prb_neg./nrnd;
else
prb_neg = prb_neg./nrnd;
prb_pos = prb_pos./nrnd;
% for each observation select the tail that corresponds with the lowest probability
prb = min(prb_neg, prb_pos);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
% this assumes that the data is properly normalised
% and assumes that all trials have the same number of tapers
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function coh = computecoh(datref, dat, method, loopdim)
nref = size(datref,1);
nsgn = size(dat,1);
nfrq = size(dat,3);
coh = zeros(nref,nsgn,nfrq);
switch loopdim
case 3
% for each frequency, simultaneously compute coherence between all reference and target signals
for i=1:nfrq
switch method
case 'abscoh'
coh(:,:,i) = abs( datref(:,:,i) * dat(:,:,i)');
case 'imagcoh'
coh(:,:,i) = imag(datref(:,:,i) * dat(:,:,i)');
case 'absimagcoh'
coh(:,:,i) = abs(imag(datref(:,:,i) * dat(:,:,i)'));
case {'atanh' 'atanh_randphase'}
coh(:,:,i) = atanh(abs(datref(:,:,i)* dat(:,:,i)'));
case 'amplcorr'
coh(:,:,i) = datref(:,:,i) * dat(:,:,i)';
case 'absamplcorr'
coh(:,:,i) = abs( datref(:,:,i) * dat(:,:,i)');
otherwise
error('unsupported method');
end
end
case 1
% for each reference and target signal, simultaneously compute coherence over all frequencies
for i=1:nref
for k=1:nsgn
switch method
case 'abscoh'
coh(i,k,:) = abs( sum(datref(i,:,:) .* conj(dat(k,:,:)), 2));
case 'imagcoh'
coh(i,k,:) = imag(sum(datref(i,:,:) .* conj(dat(k,:,:)), 2));
case 'absimagcoh'
coh(i,k,:) = abs(imag(sum(datref(i,:,:) .* conj(dat(k,:,:)), 2)));
case {'atanh' 'atanh_randphase'}
coh(i,k,:) = atanh(abs(sum(datref(i,:,:).* conj(dat(k,:,:)), 2)));
case 'amplcorr'
coh(i,k,:) = sum(datref(i,:,:) .* conj(dat(k,:,:)), 2);
case 'absamplcorr'
coh(i,k,:) = abs( sum(datref(i,:,:) .* conj(dat(k,:,:)), 2));
otherwise
error('unsupported method');
end
end
end
otherwise
error('unsupported loopdim');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that shuffles in blocks
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [out] = randblockshift(n, k);
n = n(:);
nbin = length(n)/k;
n = reshape(n, [k nbin]);
n = n(:,randperm(nbin));
out = n(:);
|
github
|
philippboehmsturm/antx-master
|
volumeedit.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/volumeedit.m
| 12,966 |
utf_8
|
f4a7c8f761e54de2e765c80d04d462bb
|
function [dataout] = volumeedit(data, varargin)
% VOLUMEEDIT allows for editing of a (booleanized) volume, in order to
% remove unwanted voxels. Interaction proceeds with the keyboard and the
% mouse.
% Copyright (C) 2013, Jan-Mathijs Schoffelen
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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/>.
%
% $Id:$
revision = '$Id: ft_sourceplot.m 7192 2012-12-13 22:32:56Z roboos $';
datain = data;
data = data~=0;
dim = size(data);
xi = round(dim(1)/2);
yi = round(dim(2)/2);
zi = round(dim(3)/2);
xi = max(xi, 1); xi = min(xi, dim(1));
yi = max(yi, 1); yi = min(yi, dim(2));
zi = max(zi, 1); zi = min(zi, dim(3));
% enforce the size of the subplots to be isotropic
xdim = dim(1) + dim(2);
ydim = dim(2) + dim(3);
xsize(1) = 0.82*dim(1)/xdim;
xsize(2) = 0.82*dim(2)/xdim;
ysize(1) = 0.82*dim(3)/ydim;
ysize(2) = 0.82*dim(2)/ydim;
% create figure
h = figure;
set(h, 'color', [1 1 1]);
set(h, 'visible', 'on');
set(h, 'windowbuttondownfcn', @cb_buttonpress);
set(h, 'windowbuttonupfcn', @cb_buttonrelease);
set(h, 'windowkeypressfcn', @cb_keyboard);
% axis handles
h1 = axes('position',[0.07 0.07+ysize(2)+0.05 xsize(1) ysize(1)]);
h2 = axes('position',[0.07+xsize(1)+0.05 0.07+ysize(2)+0.05 xsize(2) ysize(1)]);
h3 = axes('position',[0.07 0.07 xsize(1) ysize(2)]);
% slice handles
hs1 = imagesc(squeeze(data(xi,:,:)),'parent',h1); colormap gray;
hs2 = imagesc(data(:,:,zi)', 'parent',h2); colormap gray;
hs3 = imagesc(squeeze(data(:,yi,:)),'parent',h3); colormap gray;
set(h1, 'tag', 'jk', 'clim', [0 1]);
set(h2, 'tag', 'ji', 'clim', [0 1]);
set(h3, 'tag', 'ik', 'clim', [0 1]);
% crosshair handles
hch1 = crosshair([zi yi], 'parent', h1, 'color', 'y');
hch2 = crosshair([xi yi], 'parent', h2, 'color', 'y');
hch3 = crosshair([zi xi], 'parent', h3, 'color', 'y');
% erasercontour
he1(1,:) = line(zi-3.5+[0 0 7 7 0],yi-3.5+[0 7 7 0 0],'color','r','parent',h1);
he2(1,:) = line(xi-3.5+[0 0 7 7 0],yi-3.5+[0 7 7 0 0],'color','r','parent',h2);
he3(1,:) = line(zi-3.5+[0 0 7 7 0],xi-3.5+[0 7 7 0 0],'color','r','parent',h3);
% create structure to be passed to gui
opt.data = data~=0;
opt.handlesaxes = [h1 h2 h3];
opt.handlescross = [hch1(:)';hch2(:)';hch3(:)'];
opt.handlesslice = [hs1 hs2 hs3];
opt.handleseraser = [he1(:)';he2(:)';he3(:)'];
opt.ijk = [xi yi zi];
opt.dim = dim;
opt.quit = 0;
opt.mask = true(dim);
opt.radius = 3;
setappdata(h, 'opt', opt);
cb_redraw(h);
while opt.quit==0
uiwait(h);
opt = getappdata(h, 'opt'); % needed to update the opt.quit
end
opt = getappdata(h, 'opt');
delete(h);
dataout = datain;
dataout(opt.mask==0) = 0;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_keyboard(h, eventdata)
if isempty(eventdata)
% determine the key that corresponds to the uicontrol element that was activated
key = get(h, 'userdata');
else
% determine the key that was pressed on the keyboard
key = parseKeyboardEvent(eventdata);
end
% get focus back to figure
if ~strcmp(get(h, 'type'), 'figure')
set(h, 'enable', 'off');
drawnow;
set(h, 'enable', 'on');
end
h = getparent(h);
opt = getappdata(h, 'opt');
curr_ax = get(h, 'currentaxes');
tag = get(curr_ax, 'tag');
switch tag
case 'jk'
xy = [2 3];
case 'ji'
xy = [2 1];
case 'ik'
xy = [1 3];
otherwise
end
switch key
case 'leftarrow'
opt.ijk(xy(2)) = opt.ijk(xy(2)) - 1;
setappdata(h, 'opt', opt);
cb_redraw(h);
case 'rightarrow'
opt.ijk(xy(2)) = opt.ijk(xy(2)) + 1;
setappdata(h, 'opt', opt);
cb_redraw(h);
case 'uparrow'
opt.ijk(xy(1)) = opt.ijk(xy(1)) - 1;
setappdata(h, 'opt', opt);
cb_redraw(h);
case 'downarrow'
opt.ijk(xy(1)) = opt.ijk(xy(1)) + 1;
setappdata(h, 'opt', opt);
cb_redraw(h);
case 'd'
% delete current voxel
cb_eraser(h);
cb_redraw(h);
case 'q'
setappdata(h, 'opt', opt);
cb_cleanup(h);
case 'r'
% select the radius of the eraser box
response = inputdlg(sprintf('radius of eraser box (in voxels)'), 'specify', 1, {num2str(opt.radius)});
if ~isempty(response)
response = str2double(tokenize(response{1},' '));
opt.radius = round(response);
opt.radius = min(opt.radius, 100);
opt.radius = max(opt.radius, 1);
setappdata(h, 'opt', opt);
cb_erasercontour(h);
end
case 'control+control'
% do nothing
case 'shift+shift'
% do nothing
case 'alt+alt'
% do nothing
otherwise
setappdata(h, 'opt', opt);
%cb_help(h);
end
uiresume(h);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_eraser(h, eventdata)
h = getparent(h);
opt = getappdata(h, 'opt');
n = opt.radius;
if numel(n)==1, n = [n n n]; end
xi = opt.ijk(1)+(-n(1):n(1));
yi = opt.ijk(2)+(-n(2):n(2));
zi = opt.ijk(3)+(-n(3):n(3));
opt.mask(xi,yi,zi) = false;
opt.data = opt.data & opt.mask;
setappdata(h, 'opt', opt);
uiresume(h);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_erasercontour(h, eventdata)
h = getparent(h);
opt = getappdata(h, 'opt');
ijk = opt.ijk;
n = opt.radius*2+1;
if numel(n)==1, n = [n n n]; end
set(opt.handleseraser(1),'xdata',ijk(3)-n(3)/2+[0 0 n(3) n(3) 0]);
set(opt.handleseraser(1),'ydata',ijk(2)-n(2)/2+[0 n(2) n(2) 0 0]);
set(opt.handleseraser(2),'xdata',ijk(1)-n(1)/2+[0 0 n(1) n(1) 0]);
set(opt.handleseraser(2),'ydata',ijk(2)-n(2)/2+[0 n(2) n(2) 0 0]);
set(opt.handleseraser(3),'xdata',ijk(3)-n(3)/2+[0 0 n(3) n(3) 0]);
set(opt.handleseraser(3),'ydata',ijk(1)-n(1)/2+[0 n(1) n(1) 0 0]);
uiresume(h);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_redraw(h, eventdata)
h = getparent(h);
opt = getappdata(h, 'opt');
curr_ax = get(h, 'currentaxes');
xi = opt.ijk(1);
yi = opt.ijk(2);
zi = opt.ijk(3);
dat1 = squeeze(opt.data(xi,:,:));
dat2 = opt.data(:,:,zi)';
dat3 = squeeze(opt.data(:,yi,:));
set(opt.handlesslice(1), 'CData', dat1);
set(opt.handlesslice(2), 'CData', dat2);
set(opt.handlesslice(3), 'CData', dat3);
crosshair([zi yi], 'handle', opt.handlescross(1,:));
crosshair([xi yi], 'handle', opt.handlescross(2,:));
crosshair([zi xi], 'handle', opt.handlescross(3,:));
cb_erasercontour(h);
set(h, 'currentaxes', curr_ax);
setappdata(h, 'opt', opt);
uiresume
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_buttonpress(h, eventdata)
h = getparent(h);
opt = getappdata(h, 'opt');
cb_getposition(h);
opt = getappdata(h, 'opt');
seltype = get(h, 'selectiontype');
switch seltype
case 'normal'
% just update to new position, nothing else to be done here
cb_redraw(h);
case 'alt'
cb_eraser(h);
set(h, 'windowbuttonmotionfcn', @cb_tracemouse);
opt = getappdata(h, 'opt');
cb_redraw(h);
otherwise
end
setappdata(h, 'opt', opt);
uiresume;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_buttonrelease(h, eventdata)
seltype = get(h, 'selectiontype');
switch seltype
case 'normal'
% just update to new position, nothing else to be done here
case 'alt'
set(h, 'windowbuttonmotionfcn', '');
otherwise
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_tracemouse(h, eventdata)
h = getparent(h);
cb_getposition(h);
opt = getappdata(h, 'opt');
n = opt.radius;
if numel(n)==1, n = [n n n]; end
xi = opt.ijk(1)+(-n(1):n(1)); xi(xi>opt.dim(1)) = []; xi(xi<1) = [];
yi = opt.ijk(2)+(-n(2):n(2)); yi(yi>opt.dim(2)) = []; yi(yi<1) = [];
zi = opt.ijk(3)+(-n(3):n(3)); zi(zi>opt.dim(3)) = []; zi(zi<1) = [];
opt.mask(xi,yi,zi) = 0;
opt.data = opt.data & opt.mask;
setappdata(h, 'opt', opt);
cb_redraw(h);
uiresume;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_getposition(h, eventdata)
h = getparent(h);
opt = getappdata(h, 'opt');
curr_ax = get(h, 'currentaxes');
pos = get(curr_ax, 'currentpoint');
tag = get(curr_ax, 'tag');
switch tag
case 'jk'
opt.ijk([3,2]) = round(pos(1,1:2));
case 'ji'
opt.ijk([1,2]) = round(pos(1,1:2));
case 'ik'
opt.ijk([3,1]) = round(pos(1,1:2));
otherwise
end
opt.ijk = min(opt.ijk, opt.dim);
opt.ijk = max(opt.ijk, [1 1 1]);
setappdata(h, 'opt', opt);
uiresume;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_cleanup(h, eventdata)
opt = getappdata(h, 'opt');
opt.quit = true;
setappdata(h, 'opt', opt);
uiresume
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function h = getparent(h)
p = h;
while p~=0
h = p;
p = get(h, 'parent');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function key = parseKeyboardEvent(eventdata)
key = eventdata.Key;
% handle possible numpad events (different for Windows and UNIX systems)
% NOTE: shift+numpad number does not work on UNIX, since the shift
% modifier is always sent for numpad events
if isunix()
shiftInd = match_str(eventdata.Modifier, 'shift');
if ~isnan(str2double(eventdata.Character)) && ~isempty(shiftInd)
% now we now it was a numpad keystroke (numeric character sent AND
% shift modifier present)
key = eventdata.Character;
eventdata.Modifier(shiftInd) = []; % strip the shift modifier
end
elseif ispc()
if strfind(eventdata.Key, 'numpad')
key = eventdata.Character;
end
end
if ~isempty(eventdata.Modifier)
key = [eventdata.Modifier{1} '+' key];
end
|
github
|
philippboehmsturm/antx-master
|
postpad.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/postpad.m
| 2,013 |
utf_8
|
2c9539d77ff0f85c9f89108f4dc811e0
|
% Copyright (C) 1994, 1995, 1996, 1997, 1998, 2000, 2002, 2004, 2005,
% 2006, 2007, 2008, 2009 John W. Eaton
%
% This file is part of Octave.
%
% Octave 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.
%
% Octave 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 Octave; see the file COPYING. If not, see
% <http://www.gnu.org/licenses/>.
% -*- texinfo -*-
% @deftypefn {Function File} {} postpad (@var{x}, @var{l}, @var{c})
% @deftypefnx {Function File} {} postpad (@var{x}, @var{l}, @var{c}, @var{dim})
% @seealso{prepad, resize}
% @end deftypefn
% Author: Tony Richardson <[email protected]>
% Created: June 1994
function y = postpad (x, l, c, dim)
if nargin < 2 || nargin > 4
%print_usage ();
error('wrong number of input arguments, should be between 2 and 4');
end
if nargin < 3 || isempty(c)
c = 0;
else
if ~isscalar(c)
error ('postpad: third argument must be empty or a scalar');
end
end
nd = ndims(x);
sz = size(x);
if nargin < 4
% Find the first non-singleton dimension
dim = 1;
while dim < nd+1 && sz(dim)==1
dim = dim + 1;
end
if dim > nd
dim = 1;
elseif ~(isscalar(dim) && dim == round(dim)) && dim > 0 && dim< nd+1
error('postpad: dim must be an integer and valid dimension');
end
end
if ~isscalar(l) || l<0
error ('second argument must be a positive scalar');
end
if dim > nd
sz(nd+1:dim) = 1;
end
d = sz(dim);
if d >= l
idx = cell(1,nd);
for i = 1:nd
idx{i} = 1:sz(i);
end
idx{dim} = 1:l;
y = x(idx{:});
else
sz(dim) = l-d;
y = cat(dim, x, c * ones(sz));
end
|
github
|
philippboehmsturm/antx-master
|
statistics_wrapper.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/statistics_wrapper.m
| 27,008 |
utf_8
|
75f15bd59bcd26d5103082e24f4a0568
|
function [stat, cfg] = statistics_wrapper(cfg, varargin)
% STATISTICS_WRAPPER performs the selection of the biological data for
% timelock, frequency or source data and sets up the design vector or
% matrix.
%
% The specific configuration options for selecting timelock, frequency
% of source data are described in FT_TIMELOCKSTATISTICS, FT_FREQSTATISTICS and
% FT_SOURCESTATISTICS, respectively.
%
% After selecting the data, control is passed on to a data-independent
% statistical subfunction that computes test statistics plus their associated
% significance probabilities and critical values under some null-hypothesis. The statistical
% subfunction that is called is FT_STATISTICS_xxx, where cfg.method='xxx'. At
% this moment, we have implemented two statistical subfunctions:
% FT_STATISTICS_ANALYTIC, which calculates analytic significance probabilities and critical
% values (exact or asymptotic), and FT_STATISTICS_MONTECARLO, which calculates
% Monte-Carlo approximations of the significance probabilities and critical values.
%
% The specific configuration options for the statistical test are
% described in FT_STATISTICS_xxx.
% This function depends on PREPARE_TIMEFREQ_DATA which has the following options:
% cfg.avgoverchan
% cfg.avgoverfreq
% cfg.avgovertime
% cfg.channel
% cfg.channelcmb
% cfg.datarepresentation (set in STATISTICS_WRAPPER cfg.datarepresentation = 'concatenated')
% cfg.frequency
% cfg.latency
% cfg.precision
% cfg.previous (set in STATISTICS_WRAPPER cfg.previous = [])
% cfg.version (id and name set in STATISTICS_WRAPPER)
% Copyright (C) 2005-2006, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: statistics_wrapper.m 7393 2013-01-23 14:33:27Z jorhor $
% check if the input cfg is valid for this function
cfg = ft_checkconfig(cfg, 'renamed', {'approach', 'method'});
cfg = ft_checkconfig(cfg, 'required', {'method'});
cfg = ft_checkconfig(cfg, 'forbidden', {'transform'});
% set the defaults
if ~isfield(cfg, 'channel'), cfg.channel = 'all'; end
if ~isfield(cfg, 'latency'), cfg.latency = 'all'; end
if ~isfield(cfg, 'frequency'), cfg.frequency = 'all'; end
if ~isfield(cfg, 'roi'), cfg.roi = []; end
if ~isfield(cfg, 'avgoverchan'), cfg.avgoverchan = 'no'; end
if ~isfield(cfg, 'avgovertime'), cfg.avgovertime = 'no'; end
if ~isfield(cfg, 'avgoverfreq'), cfg.avgoverfreq = 'no'; end
if ~isfield(cfg, 'avgoverroi'), cfg.avgoverroi = 'no'; end
% determine the type of the input and hence the output data
if ~exist('OCTAVE_VERSION')
[s, i] = dbstack;
if length(s)>1
[caller_path, caller_name, caller_ext] = fileparts(s(2).name);
else
caller_path = '';
caller_name = '';
caller_ext = '';
end
% evalin('caller', 'mfilename') does not work for Matlab 6.1 and 6.5
istimelock = strcmp(caller_name,'ft_timelockstatistics');
isfreq = strcmp(caller_name,'ft_freqstatistics');
issource = strcmp(caller_name,'ft_sourcestatistics');
else
% cannot determine the calling function in Octave, try looking at the
% data instead
istimelock = isfield(varargin{1},'time') && ~isfield(varargin{1},'freq') && isfield(varargin{1},'avg');
isfreq = isfield(varargin{1},'time') && isfield(varargin{1},'freq');
issource = isfield(varargin{1},'pos') || isfield(varargin{1},'transform');
end
if (istimelock+isfreq+issource)~=1
error('Could not determine the type of the input data');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% collect the biological data (the dependent parameter)
% and the experimental design (the independent parameter)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if issource
% test that all source inputs have the same dimensions and are spatially aligned
for i=2:length(varargin)
if isfield(varargin{1}, 'dim') && (length(varargin{i}.dim)~=length(varargin{1}.dim) || ~all(varargin{i}.dim==varargin{1}.dim))
error('dimensions of the source reconstructions do not match, use NORMALISEVOLUME first');
end
if isfield(varargin{1}, 'pos') && (length(varargin{i}.pos(:))~=length(varargin{1}.pos(:)) || ~all(varargin{i}.pos(:)==varargin{1}.pos(:)))
error('grid locations of the source reconstructions do not match, use NORMALISEVOLUME first');
end
if isfield(varargin{1}, 'transform') && ~all(varargin{i}.transform(:)==varargin{1}.transform(:))
error('spatial coordinates of the source reconstructions do not match, use NORMALISEVOLUME first');
end
end
Nsource = length(varargin);
Nvoxel = length(varargin{1}.inside) + length(varargin{1}.outside);
if ~isempty(cfg.roi)
if ischar(cfg.roi)
cfg.roi = {cfg.roi};
end
% the source representation should specify the position of each voxel in MNI coordinates
x = varargin{1}.pos(:,1); % this is from left (negative) to right (positive)
% determine the mask to restrict the subsequent analysis
% process each of the ROIs, and optionally also left and/or right seperately
roimask = {};
roilabel = {};
for i=1:length(cfg.roi)
if islogical(cfg.roi{i})
tmp = cfg.roi{i};
else
tmpcfg.roi = cfg.roi{i};
tmpcfg.inputcoord = cfg.inputcoord;
tmpcfg.atlas = cfg.atlas;
tmp = volumelookup(tmpcfg, varargin{1});
end
if strcmp(cfg.avgoverroi, 'no') && ~isfield(cfg, 'hemisphere')
% no reason to deal with seperated left/right hemispheres
cfg.hemisphere = 'combined';
end
if strcmp(cfg.hemisphere, 'left')
tmp(x>=0) = 0; % exclude the right hemisphere
roimask{end+1} = tmp;
roilabel{end+1} = ['Left ' cfg.roi{i}];
elseif strcmp(cfg.hemisphere, 'right')
tmp(x<=0) = 0; % exclude the right hemisphere
roimask{end+1} = tmp;
roilabel{end+1} = ['Right ' cfg.roi{i}];
elseif strcmp(cfg.hemisphere, 'both')
% deal seperately with the voxels on the left and right side of the brain
tmpL = tmp; tmpL(x>=0) = 0; % exclude the right hemisphere
tmpR = tmp; tmpR(x<=0) = 0; % exclude the left hemisphere
roimask{end+1} = tmpL;
roimask{end+1} = tmpR;
roilabel{end+1} = ['Left ' cfg.roi{i}];
roilabel{end+1} = ['Right ' cfg.roi{i}];
clear tmpL tmpR
elseif strcmp(cfg.hemisphere, 'combined')
% all voxels of the ROI can be combined
roimask{end+1} = tmp;
if ischar(cfg.roi{i})
roilabel{end+1} = cfg.roi{i};
else
roilabel{end+1} = ['ROI ' num2str(i)];
end
else
error('incorrect specification of cfg.hemisphere');
end
clear tmp
end % for each roi
% note that avgoverroi=yes is implemented differently at a later stage
% avgoverroi=no is implemented using the inside/outside mask
if strcmp(cfg.avgoverroi, 'no')
for i=2:length(roimask)
% combine them all in the first mask
roimask{1} = roimask{1} | roimask{i};
end
roimask = roimask{1}; % only keep the combined mask
% the source representation should have an inside and outside vector containing indices
sel = find(~roimask);
varargin{1}.inside = setdiff(varargin{1}.inside, sel);
varargin{1}.outside = union(varargin{1}.outside, sel);
clear roimask roilabel
end % if avgoverroi=no
end
% get the source parameter on which the statistic should be evaluated
if strcmp(cfg.parameter, 'mom') && isfield(varargin{1}, 'avg') && isfield(varargin{1}.avg, 'csdlabel') && isfield(varargin{1}, 'cumtapcnt')
[dat, cfg] = get_source_pcc_mom(cfg, varargin{:});
elseif strcmp(cfg.parameter, 'mom') && isfield(varargin{1}, 'avg') && ~isfield(varargin{1}.avg, 'csdlabel')
[dat, cfg] = get_source_lcmv_mom(cfg, varargin{:});
elseif isfield(varargin{1}, 'trial')
[dat, cfg] = get_source_trial(cfg, varargin{:});
else
[dat, cfg] = get_source_avg(cfg, varargin{:});
end
cfg.dimord = 'voxel';
% note that avgoverroi=no is implemented differently at an earlier stage
if strcmp(cfg.avgoverroi, 'yes')
tmp = zeros(length(roimask), size(dat,2));
for i=1:length(roimask)
% the data only reflects those points that are inside the brain,
% the atlas-based mask reflects points inside and outside the brain
roi = roimask{i}(varargin{1}.inside);
tmp(i,:) = mean(dat(roi,:), 1);
end
% replace the original data with the average over each ROI
dat = tmp;
clear tmp roi roimask
% remember the ROIs
cfg.dimord = 'roi';
end
elseif isfreq || istimelock
% get the ERF/TFR data by means of PREPARE_TIMEFREQ_DATA
cfg.datarepresentation = 'concatenated';
[cfg, data] = prepare_timefreq_data(cfg, varargin{:});
cfg = rmfield(cfg, 'datarepresentation');
dim = size(data.biol);
if length(dim)<3
% seems to be singleton frequency and time dimension
dim(3)=1;
dim(4)=1;
elseif length(dim)<4
% seems to be singleton time dimension
dim(4)=1;
end
cfg.dimord = 'chan_freq_time';
% the dimension of the original data (excluding the replication dimension) has to be known for clustering
cfg.dim = dim(2:end);
% all dimensions have to be concatenated except the replication dimension and the data has to be transposed
dat = transpose(reshape(data.biol, dim(1), prod(dim(2:end))));
% remove to save some memory
data.biol = [];
% add gradiometer/electrode information to the configuration
if ~isfield(cfg,'neighbours') && isfield(cfg, 'correctm') && strcmp(cfg.correctm, 'cluster')
error('You need to specify a neighbourstructure');
%cfg.neighbours = ft_neighbourselection(cfg,varargin{1});
end
end
% get the design from the information in cfg and data.
if ~isfield(cfg,'design')
warning('Please think about how you would create cfg.design. Soon the call to prepare_design will be deprecated')
cfg.design = data.design;
[cfg] = prepare_design(cfg);
end
if size(cfg.design,2)~=size(dat,2)
cfg.design = transpose(cfg.design);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% compute the statistic, using the data-independent statistical subfunction
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% determine the function handle to the intermediate-level statistics function
if exist(['ft_statistics_' cfg.method])
statmethod = str2func(['ft_statistics_' cfg.method]);
else
error(sprintf('could not find the corresponding function for cfg.method="%s"\n', cfg.method));
end
fprintf('using "%s" for the statistical testing\n', func2str(statmethod));
% check that the design completely describes the data
if size(dat,2) ~= size(cfg.design,2)
error('the size of the design matrix does not match the number of observations in the data');
end
% determine the number of output arguments
try
% the nargout function in Matlab 6.5 and older does not work on function handles
num = nargout(statmethod);
catch
num = 1;
end
design=cfg.design;
cfg=rmfield(cfg,'design'); % to not confuse lower level functions with both cfg.design and design input
% perform the statistical test
if strcmp(func2str(statmethod),'ft_statistics_montecarlo') % because ft_statistics_montecarlo (or to be precise, clusterstat) requires to know whether it is getting source data,
% the following (ugly) work around is necessary
if num>1
[stat, cfg] = statmethod(cfg, dat, design, 'issource',issource);
else
[stat] = statmethod(cfg, dat, design, 'issource', issource);
end
else
if num>1
[stat, cfg] = statmethod(cfg, dat, design);
else
[stat] = statmethod(cfg, dat, design);
end
end
if isstruct(stat)
% the statistical output contains multiple elements, e.g. F-value, beta-weights and probability
statfield = fieldnames(stat);
else
% only the probability was returned as a single matrix, reformat into a structure
dum = stat; stat = []; % this prevents a Matlab warning that appears from release 7.0.4 onwards
stat.prob = dum;
statfield = fieldnames(stat);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% add descriptive information to the output and rehape into the input format
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if issource
if ~isfield(varargin{1},'dim') % FIX ME; this is added temporarily (20110427) to cope with ft_sourceanalysis output not having a dim field since r3273
varargin{1}.dim = [Nvoxel 1];
end
if isempty(cfg.roi) || strcmp(cfg.avgoverroi, 'no')
% remember the definition of the volume, assume that they are identical for all input arguments
try stat.dim = varargin{1}.dim; end
try stat.xgrid = varargin{1}.xgrid; end
try stat.ygrid = varargin{1}.ygrid; end
try stat.zgrid = varargin{1}.zgrid; end
try stat.inside = varargin{1}.inside; end
try stat.outside = varargin{1}.outside; end
try stat.pos = varargin{1}.pos; end
try stat.transform = varargin{1}.transform; end
try stat.freq = varargin{1}.freq; end
try stat.time = varargin{1}.time; end
else
stat.inside = 1:length(roilabel);
stat.outside = [];
stat.label = roilabel(:);
end
for i=1:length(statfield)
tmp = getsubfield(stat, statfield{i});
if isfield(varargin{1}, 'inside') && numel(tmp)==length(varargin{1}.inside)
% the statistic was only computed on voxels that are inside the brain
% sort the inside and outside voxels back into their original place
if islogical(tmp)
tmp(varargin{1}.inside) = tmp;
tmp(varargin{1}.outside) = false;
else
tmp(varargin{1}.inside) = tmp;
tmp(varargin{1}.outside) = nan;
end
extradim = 1;
elseif isfield(varargin{1}, 'inside') && isfield(varargin{1}, 'freq') && isfield(varargin{1}, 'time') && numel(tmp)==length(varargin{1}.inside)*length(varargin{1}.freq)*length(varargin{1}.time)
% the statistic is a higher dimensional matrix (here as a function of freq) computed only on the
% inside voxels
newtmp = zeros(length(varargin{1}.inside)+length(varargin{1}.outside), length(varargin{1}.freq), length(varargin{1}.time));
if islogical(tmp)
newtmp(varargin{1}.inside, :, :) = reshape(tmp, length(varargin{1}.inside), length(varargin{1}.freq), []);
newtmp(varargin{1}.outside, :, :) = false;
else
newtmp(varargin{1}.inside, :, :) = reshape(tmp, length(varargin{1}.inside), length(varargin{1}.freq), []);
newtmp(varargin{1}.outside, :, :) = nan;
end
tmp = newtmp; clear newtmp;
extradim = length(varargin{1}.freq);
elseif isfield(varargin{1}, 'inside') && isfield(varargin{1}, 'freq') && numel(tmp)==length(varargin{1}.inside)*length(varargin{1}.freq)
% the statistic is a higher dimensional matrix (here as a function of freq) computed only on the
% inside voxels
newtmp = zeros(length(varargin{1}.inside)+length(varargin{1}.outside), length(varargin{1}.freq));
if islogical(tmp)
newtmp(varargin{1}.inside, :) = reshape(tmp, length(varargin{1}.inside), []);
newtmp(varargin{1}.outside, :) = false;
else
newtmp(varargin{1}.inside, :) = reshape(tmp, length(varargin{1}.inside), []);
newtmp(varargin{1}.outside, :) = nan;
end
tmp = newtmp; clear newtmp;
extradim = length(varargin{1}.freq);
elseif isfield(varargin{1}, 'inside') && isfield(varargin{1}, 'time') && numel(tmp)==length(varargin{1}.inside)*length(varargin{1}.time)
% the statistic is a higher dimensional matrix (here as a function of time) computed only on the
% inside voxels
newtmp = zeros(length(varargin{1}.inside)+length(varargin{1}.outside), length(varargin{1}.time));
if islogical(tmp)
newtmp(varargin{1}.inside, :) = reshape(tmp, length(varargin{1}.inside), []);
newtmp(varargin{1}.outside, :) = false;
else
newtmp(varargin{1}.inside, :) = reshape(tmp, length(varargin{1}.inside), []);
newtmp(varargin{1}.outside, :) = nan;
end
tmp = newtmp; clear newtmp;
extradim = length(varargin{1}.time);
else
extradim = 1;
end
if numel(tmp)==prod(varargin{1}.dim)
% reshape the statistical volumes into the original format
stat = setsubfield(stat, statfield{i}, reshape(tmp, varargin{1}.dim));
else
stat = setsubfield(stat, statfield{i}, tmp);
end
end
else
haschan = isfield(data, 'label'); % this one remains relevant, even after averaging over channels
haschancmb = isfield(data, 'labelcmb'); % this one remains relevant, even after averaging over channels
hasfreq = strcmp(cfg.avgoverfreq, 'no') && ~any(isnan(data.freq));
hastime = strcmp(cfg.avgovertime, 'no') && ~any(isnan(data.time));
stat.dimord = '';
if haschan
stat.dimord = [stat.dimord 'chan_'];
stat.label = data.label;
chandim = dim(2);
elseif haschancmb
stat.dimord = [stat.dimord 'chancmb_'];
stat.labelcmb = data.labelcmb;
chandim = dim(2);
end
if hasfreq
stat.dimord = [stat.dimord 'freq_'];
stat.freq = data.freq;
freqdim = dim(3);
end
if hastime
stat.dimord = [stat.dimord 'time_'];
stat.time = data.time;
timedim = dim(4);
end
if ~isempty(stat.dimord)
% remove the last '_'
stat.dimord = stat.dimord(1:(end-1));
end
for i=1:length(statfield)
try
% reshape the fields that have the same dimension as the input data
if strcmp(stat.dimord, 'chan')
stat = setfield(stat, statfield{i}, reshape(getfield(stat, statfield{i}), [chandim 1]));
elseif strcmp(stat.dimord, 'chan_time')
stat = setfield(stat, statfield{i}, reshape(getfield(stat, statfield{i}), [chandim timedim]));
elseif strcmp(stat.dimord, 'chan_freq')
stat = setfield(stat, statfield{i}, reshape(getfield(stat, statfield{i}), [chandim freqdim]));
elseif strcmp(stat.dimord, 'chan_freq_time')
stat = setfield(stat, statfield{i}, reshape(getfield(stat, statfield{i}), [chandim freqdim timedim]));
elseif strcmp(stat.dimord, 'chancmb_time')
stat = setfield(stat, statfield{i}, reshape(getfield(stat, statfield{i}), [chandim timedim]));
elseif strcmp(stat.dimord, 'chancmb_freq')
stat = setfield(stat, statfield{i}, reshape(getfield(stat, statfield{i}), [chandim freqdim]));
elseif strcmp(stat.dimord, 'chancmb_freq_time')
stat = setfield(stat, statfield{i}, reshape(getfield(stat, statfield{i}), [chandim freqdim timedim]));
elseif strcmp(stat.dimord, 'time')
stat = setfield(stat, statfield{i}, reshape(getfield(stat, statfield{i}), [1 timedim]));
elseif strcmp(stat.dimord, 'freq')
stat = setfield(stat, statfield{i}, reshape(getfield(stat, statfield{i}), [1 freqdim]));
elseif strcmp(stat.dimord, 'freq_time')
stat = setfield(stat, statfield{i}, reshape(getfield(stat, statfield{i}), [freqdim timedim]));
end
end
end
end
return % statistics_wrapper main()
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION for extracting the data of interest
% data resemples PCC beamed source reconstruction, multiple trials are coded in mom
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [dat, cfg] = get_source_pcc_mom(cfg, varargin)
Nsource = length(varargin);
Nvoxel = length(varargin{1}.inside) + length(varargin{1}.outside);
Ninside = length(varargin{1}.inside);
dim = varargin{1}.dim;
for i=1:Nsource
dipsel = find(strcmp(varargin{i}.avg.csdlabel, 'scandip'));
ntrltap = sum(varargin{i}.cumtapcnt);
dat{i} = zeros(Ninside, ntrltap);
for j=1:Ninside
k = varargin{1}.inside(j);
dat{i}(j,:) = reshape(varargin{i}.avg.mom{k}(dipsel,:), 1, ntrltap);
end
end
% concatenate the data matrices of the individual input arguments
dat = cat(2, dat{:});
% remember the dimension of the source data
cfg.dim = dim;
% remember which voxels are inside the brain
cfg.inside = varargin{1}.inside;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION for extracting the data of interest
% data resemples LCMV beamed source reconstruction, mom contains timecourse
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [dat, cfg] = get_source_lcmv_mom(cfg, varargin)
Nsource = length(varargin);
Nvoxel = length(varargin{1}.inside) + length(varargin{1}.outside);
Ntime = length(varargin{1}.avg.mom{varargin{1}.inside(1)});
Ninside = length(varargin{1}.inside);
dim = [varargin{1}.dim Ntime];
dat = zeros(Ninside*Ntime, Nsource);
for i=1:Nsource
% collect the 4D data of this input argument
tmp = nan(Ninside, Ntime);
for j=1:Ninside
k = varargin{1}.inside(j);
tmp(j,:) = reshape(varargin{i}.avg.mom{k}, 1, dim(4));
end
dat(:,i) = tmp(:);
end
% remember the dimension of the source data
cfg.dim = dim;
% remember which voxels are inside the brain
cfg.inside = varargin{1}.inside;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION for extracting the data of interest
% data contains single-trial or single-subject source reconstructions
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [dat, cfg] = get_source_trial(cfg, varargin)
Nsource = length(varargin);
Nvoxel = length(varargin{1}.inside) + length(varargin{1}.outside);
for i=1:Nsource
Ntrial(i) = length(varargin{i}.trial);
end
k = 1;
for i=1:Nsource
for j=1:Ntrial(i)
tmp = getsubfield(varargin{i}.trial(j), cfg.parameter);
if ~iscell(tmp),
%dim = size(tmp);
dim = [Nvoxel 1];
else
dim = [Nvoxel size(tmp{varargin{i}.inside(1)})];
end
if i==1 && j==1 && numel(tmp)~=Nvoxel,
warning('the input-data contains more entries than the number of voxels in the volume, the data will be concatenated');
dat = zeros(prod(dim), sum(Ntrial)); %FIXME this is old code should be removed
elseif i==1 && j==1 && iscell(tmp),
warning('the input-data contains more entries than the number of voxels in the volume, the data will be concatenated');
dat = zeros(Nvoxel*numel(tmp{varargin{i}.inside(1)}), sum(Ntrial));
elseif i==1 && j==1,
dat = zeros(Nvoxel, sum(Ntrial));
end
if ~iscell(tmp),
dat(:,k) = tmp(:);
else
Ninside = length(varargin{i}.inside);
%tmpvec = (varargin{i}.inside-1)*prod(size(tmp{varargin{i}.inside(1)}));
tmpvec = varargin{i}.inside;
insidevec = [];
for m = 1:numel(tmp{varargin{i}.inside(1)})
insidevec = [insidevec; tmpvec(:)+(m-1)*Nvoxel];
end
insidevec = insidevec(:)';
tmpdat = reshape(permute(cat(3,tmp{varargin{1}.inside}), [3 1 2]), [Ninside numel(tmp{varargin{1}.inside(1)})]);
dat(insidevec, k) = tmpdat(:);
end
% add original dimensionality of the data to the configuration, is required for clustering
%FIXME: this was obviously wrong, because often trial-data is one-dimensional, so no dimensional information is present
%cfg.dim = dim(2:end);
k = k+1;
end
end
if isfield(varargin{1}, 'inside')
fprintf('only selecting voxels inside the brain for statistics (%.1f%%)\n', 100*length(varargin{1}.inside)/prod(dim));
for j=prod(dim(2:end)):-1:1
dat((j-1).*dim(1) + varargin{1}.outside, :) = [];
end
end
% remember the dimension of the source data
if ~isfield(cfg, 'dim')
warning('for clustering on trial-based data you explicitly have to specify cfg.dim');
end
% remember which voxels are inside the brain
cfg.inside = varargin{1}.inside;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION for extracting the data of interest
% get the average source reconstructions, the repetitions are in multiple input arguments
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [dat, cfg] = get_source_avg(cfg, varargin)
Nsource = length(varargin);
Nvoxel = length(varargin{1}.inside) + length(varargin{1}.outside);
dim = varargin{1}.dim;
inside = false(prod(dim),1);
inside(varargin{1}.inside) = true;
tmp = getsubfield(varargin{1}, cfg.parameter);
if size(tmp,2)>1
if isfield(varargin{1}, 'freq')
Nvoxel = Nvoxel*numel(varargin{1}.freq);
dim = [dim numel(varargin{1}.freq)];
inside = repmat(inside, [1 numel(varargin{1}.freq)]);
end
if isfield(varargin{1}, 'time')
Nvoxel = Nvoxel*numel(varargin{1}.time);
dim = [dim numel(varargin{1}.time)];
if isfield(varargin{1},'freq')
inside = repmat(inside, [1 1 numel(varargin{1}.time)]);
else
inside = repmat(inside, [1 numel(varargin{1}.time)]);
end
end
end
dat = zeros(Nvoxel, Nsource);
for i=1:Nsource
tmp = getsubfield(varargin{i}, cfg.parameter);
dat(:,i) = tmp(:);
end
inside = find(inside(:));
if isfield(varargin{1}, 'inside')
fprintf('only selecting voxels inside the brain for statistics (%.1f%%)\n', 100*length(varargin{1}.inside)/prod(varargin{1}.dim));
dat = dat(inside,:);
end
% remember the dimension of the source data
cfg.dim = dim;
% remember which voxels are inside the brain
cfg.inside = inside(:);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION for creating a design matrix
% should be called in the code above, or in prepare_design
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [cfg] = get_source_design_pcc_mom(cfg, varargin)
% should be implemented
function [cfg] = get_source_design_lcmv_mom(cfg, varargin)
% should be implemented
function [cfg] = get_source_design_trial(cfg, varargin)
% should be implemented
function [cfg] = get_source_design_avg(cfg, varargin)
% should be implemented
|
github
|
philippboehmsturm/antx-master
|
arrow.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/arrow.m
| 58,174 |
utf_8
|
975de6e9378e741d3d2c993ad5c36e21
|
function [h,yy,zz] = arrow(varargin)
% ARROW Draw a line with an arrowhead.
%
% ARROW(Start,Stop) draws a line with an arrow from Start to Stop (points
% should be vectors of length 2 or 3, or matrices with 2 or 3
% columns), and returns the graphics handle of the arrow(s).
%
% ARROW uses the mouse (click-drag) to create an arrow.
%
% ARROW DEMO & ARROW DEMO2 show 3-D & 2-D demos of the capabilities of ARROW.
%
% ARROW may be called with a normal argument list or a property-based list.
% ARROW(Start,Stop,Length,BaseAngle,TipAngle,Width,Page,CrossDir) is
% the full normal argument list, where all but the Start and Stop
% points are optional. If you need to specify a later argument (e.g.,
% Page) but want default values of earlier ones (e.g., TipAngle),
% pass an empty matrix for the earlier ones (e.g., TipAngle=[]).
%
% ARROW('Property1',PropVal1,'Property2',PropVal2,...) creates arrows with the
% given properties, using default values for any unspecified or given as
% 'default' or NaN. Some properties used for line and patch objects are
% used in a modified fashion, others are passed directly to LINE, PATCH,
% or SET. For a detailed properties explanation, call ARROW PROPERTIES.
%
% Start The starting points. B
% Stop The end points. /|\ ^
% Length Length of the arrowhead in pixels. /|||\ |
% BaseAngle Base angle in degrees (ADE). //|||\\ L|
% TipAngle Tip angle in degrees (ABC). ///|||\\\ e|
% Width Width of the base in pixels. ////|||\\\\ n|
% Page Use hardcopy proportions. /////|D|\\\\\ g|
% CrossDir Vector || to arrowhead plane. //// ||| \\\\ t|
% NormalDir Vector out of arrowhead plane. /// ||| \\\ h|
% Ends Which end has an arrowhead. //<----->|| \\ |
% ObjectHandles Vector of handles to update. / base ||| \ V
% E angle||<-------->C
% ARROW(H,'Prop1',PropVal1,...), where H is a |||tipangle
% vector of handles to previously-created arrows |||
% and/or line objects, will update the previously- |||
% created arrows according to the current view -->|A|<-- width
% and any specified properties, and will convert
% two-point line objects to corresponding arrows. ARROW(H) will update
% the arrows if the current view has changed. Root, figure, or axes
% handles included in H are replaced by all descendant Arrow objects.
%
% A property list can follow any specified normal argument list, e.g.,
% ARROW([1 2 3],[0 0 0],36,'BaseAngle',60) creates an arrow from (1,2,3) to
% the origin, with an arrowhead of length 36 pixels and 60-degree base angle.
%
% The basic arguments or properties can generally be vectorized to create
% multiple arrows with the same call. This is done by passing a property
% with one row per arrow, or, if all arrows are to have the same property
% value, just one row may be specified.
%
% You may want to execute AXIS(AXIS) before calling ARROW so it doesn't change
% the axes on you; ARROW determines the sizes of arrow components BEFORE the
% arrow is plotted, so if ARROW changes axis limits, arrows may be malformed.
%
% This version of ARROW uses features of MATLAB 5 and is incompatible with
% earlier MATLAB versions (ARROW for MATLAB 4.2c is available separately);
% some problems with perspective plots still exist.
% Copyright (c)1995-2002, Dr. Erik A. Johnson <[email protected]>, 11/15/02
% Revision history:
% 11/15/02 EAJ Accomodate how MATLAB 6.5 handles NaN and logicals
% 7/28/02 EAJ Tried (but failed) work-around for MATLAB 6.x / OpenGL bug
% if zero 'Width' or not double-ended
% 11/10/99 EAJ Add logical() to eliminate zero index problem in MATLAB 5.3.
% 11/10/99 EAJ Corrected warning if axis limits changed on multiple axes.
% 11/10/99 EAJ Update e-mail address.
% 2/10/99 EAJ Some documentation updating.
% 2/24/98 EAJ Fixed bug if Start~=Stop but both colinear with viewpoint.
% 8/14/97 EAJ Added workaround for MATLAB 5.1 scalar logical transpose bug.
% 7/21/97 EAJ Fixed a few misc bugs.
% 7/14/97 EAJ Make arrow([],'Prop',...) do nothing (no old handles)
% 6/23/97 EAJ MATLAB 5 compatible version, release.
% 5/27/97 EAJ Added Line Arrows back in. Corrected a few bugs.
% 5/26/97 EAJ Changed missing Start/Stop to mouse-selected arrows.
% 5/19/97 EAJ MATLAB 5 compatible version, beta.
% 4/13/97 EAJ MATLAB 5 compatible version, alpha.
% 1/31/97 EAJ Fixed bug with multiple arrows and unspecified Z coords.
% 12/05/96 EAJ Fixed one more bug with log plots and NormalDir specified
% 10/24/96 EAJ Fixed bug with log plots and NormalDir specified
% 11/13/95 EAJ Corrected handling for 'reverse' axis directions
% 10/06/95 EAJ Corrected occasional conflict with SUBPLOT
% 4/24/95 EAJ A major rewrite.
% Fall 94 EAJ Original code.
% Things to be done:
% - segment parsing, computing, and plotting into separate subfunctions
% - change computing from Xform to Camera paradigms
% + this will help especially with 3-D perspective plots
% + if the WarpToFill section works right, remove warning code
% + when perpsective works properly, remove perspective warning code
% - add cell property values and struct property name/values (like get/set)
% - get rid of NaN as the "default" data label
% + perhaps change userdata to a struct and don't include (or leave
% empty) the values specified as default; or use a cell containing
% an empty matrix for a default value
% - add functionality of GET to retrieve current values of ARROW properties
% Many thanks to Keith Rogers <[email protected]> for his many excellent
% suggestions and beta testing. Check out his shareware package MATDRAW
% (at ftp://ftp.mathworks.com/pub/contrib/v5/graphics/matdraw/) -- he has
% permission to distribute ARROW with MATDRAW.
% Permission is granted to distribute ARROW with the toolboxes for the book
% "Solving Solid Mechanics Problems with MATLAB 5", by F. Golnaraghi et al.
% (Prentice Hall, 1999).
% global variable initialization
global ARROW_PERSP_WARN ARROW_STRETCH_WARN ARROW_AXLIMITS
if isempty(ARROW_PERSP_WARN ), ARROW_PERSP_WARN =1; end;
if isempty(ARROW_STRETCH_WARN), ARROW_STRETCH_WARN=1; end;
% Handle callbacks
if (nargin>0 & ischar(varargin{1}) & strcmp(lower(varargin{1}),'callback')),
arrow_callback(varargin{2:end}); return;
end;
% Are we doing the demo?
c = sprintf('\n');
if (nargin==1 & ischar(varargin{1})),
arg1 = lower(varargin{1});
if strncmp(arg1,'prop',4), arrow_props;
elseif strncmp(arg1,'demo',4)
clf reset
demo_info = arrow_demo;
if ~strncmp(arg1,'demo2',5),
hh=arrow_demo3(demo_info);
else,
hh=arrow_demo2(demo_info);
end;
if (nargout>=1), h=hh; end;
elseif strncmp(arg1,'fixlimits',3),
arrow_fixlimits(ARROW_AXLIMITS);
ARROW_AXLIMITS=[];
elseif strncmp(arg1,'help',4),
disp(help(mfilename));
else,
error([upper(mfilename) ' got an unknown single-argument string ''' deblank(arg1) '''.']);
end;
return;
end;
% Check # of arguments
if (nargout>3), error([upper(mfilename) ' produces at most 3 output arguments.']); end;
% find first property number
firstprop = nargin+1;
for k=1:length(varargin), if ~isnumeric(varargin{k}), firstprop=k; break; end; end;
lastnumeric = firstprop-1;
% check property list
if (firstprop<=nargin),
for k=firstprop:2:nargin,
curarg = varargin{k};
if ~ischar(curarg) | sum(size(curarg)>1)>1,
error([upper(mfilename) ' requires that a property name be a single string.']);
end;
end;
if (rem(nargin-firstprop,2)~=1),
error([upper(mfilename) ' requires that the property ''' ...
varargin{nargin} ''' be paired with a property value.']);
end;
end;
% default output
if (nargout>0), h=[]; end;
if (nargout>1), yy=[]; end;
if (nargout>2), zz=[]; end;
% set values to empty matrices
start = [];
stop = [];
len = [];
baseangle = [];
tipangle = [];
wid = [];
page = [];
crossdir = [];
ends = [];
ax = [];
oldh = [];
ispatch = [];
defstart = [NaN NaN NaN];
defstop = [NaN NaN NaN];
deflen = 16;
defbaseangle = 90;
deftipangle = 16;
defwid = 0;
defpage = 0;
defcrossdir = [NaN NaN NaN];
defends = 1;
defoldh = [];
defispatch = 1;
% The 'Tag' we'll put on our arrows
ArrowTag = 'Arrow';
% check for oldstyle arguments
if (firstprop==2),
% assume arg1 is a set of handles
oldh = varargin{1}(:);
if isempty(oldh), return; end;
elseif (firstprop>9),
error([upper(mfilename) ' takes at most 8 non-property arguments.']);
elseif (firstprop>2),
s = str2mat('start','stop','len','baseangle','tipangle','wid','page','crossdir');
for k=1:firstprop-1, eval([deblank(s(k,:)) '=varargin{k};']); end;
end;
% parse property pairs
extraprops={};
for k=firstprop:2:nargin,
prop = varargin{k};
val = varargin{k+1};
prop = [lower(prop(:)') ' '];
if strncmp(prop,'start' ,5), start = val;
elseif strncmp(prop,'stop' ,4), stop = val;
elseif strncmp(prop,'len' ,3), len = val(:);
elseif strncmp(prop,'base' ,4), baseangle = val(:);
elseif strncmp(prop,'tip' ,3), tipangle = val(:);
elseif strncmp(prop,'wid' ,3), wid = val(:);
elseif strncmp(prop,'page' ,4), page = val;
elseif strncmp(prop,'cross' ,5), crossdir = val;
elseif strncmp(prop,'norm' ,4), if (ischar(val)), crossdir=val; else, crossdir=val*sqrt(-1); end;
elseif strncmp(prop,'end' ,3), ends = val;
elseif strncmp(prop,'object',6), oldh = val(:);
elseif strncmp(prop,'handle',6), oldh = val(:);
elseif strncmp(prop,'type' ,4), ispatch = val;
elseif strncmp(prop,'userd' ,5), %ignore it
else,
% make sure it is a valid patch or line property
eval('get(0,[''DefaultPatch'' varargin{k}]);err=0;','err=1;'); errstr=lasterr;
if (err), eval('get(0,[''DefaultLine'' varargin{k}]);err=0;','err=1;'); end;
if (err),
errstr(1:max(find(errstr==setstr(13)|errstr==setstr(10)))) = '';
error([upper(mfilename) ' got ' errstr]);
end;
extraprops={extraprops{:},varargin{k},val};
end;
end;
% Check if we got 'default' values
start = arrow_defcheck(start ,defstart ,'Start' );
stop = arrow_defcheck(stop ,defstop ,'Stop' );
len = arrow_defcheck(len ,deflen ,'Length' );
baseangle = arrow_defcheck(baseangle,defbaseangle,'BaseAngle' );
tipangle = arrow_defcheck(tipangle ,deftipangle ,'TipAngle' );
wid = arrow_defcheck(wid ,defwid ,'Width' );
crossdir = arrow_defcheck(crossdir ,defcrossdir ,'CrossDir' );
page = arrow_defcheck(page ,defpage ,'Page' );
ends = arrow_defcheck(ends ,defends ,'' );
oldh = arrow_defcheck(oldh ,[] ,'ObjectHandles');
ispatch = arrow_defcheck(ispatch ,defispatch ,'' );
% check transpose on arguments
[m,n]=size(start ); if any(m==[2 3])&(n==1|n>3), start = start'; end;
[m,n]=size(stop ); if any(m==[2 3])&(n==1|n>3), stop = stop'; end;
[m,n]=size(crossdir); if any(m==[2 3])&(n==1|n>3), crossdir = crossdir'; end;
% convert strings to numbers
if ~isempty(ends) & ischar(ends),
endsorig = ends;
[m,n] = size(ends);
col = lower([ends(:,1:min(3,n)) ones(m,max(0,3-n))*' ']);
ends = nan(m,1);
oo = ones(1,m);
ii=find(all(col'==['non']'*oo)'); if ~isempty(ii), ends(ii)=ones(length(ii),1)*0; end;
ii=find(all(col'==['sto']'*oo)'); if ~isempty(ii), ends(ii)=ones(length(ii),1)*1; end;
ii=find(all(col'==['sta']'*oo)'); if ~isempty(ii), ends(ii)=ones(length(ii),1)*2; end;
ii=find(all(col'==['bot']'*oo)'); if ~isempty(ii), ends(ii)=ones(length(ii),1)*3; end;
if any(isnan(ends)),
ii = min(find(isnan(ends)));
error([upper(mfilename) ' does not recognize ''' deblank(endsorig(ii,:)) ''' as a valid ''Ends'' value.']);
end;
else,
ends = ends(:);
end;
if ~isempty(ispatch) & ischar(ispatch),
col = lower(ispatch(:,1));
patchchar='p'; linechar='l'; defchar=' ';
mask = col~=patchchar & col~=linechar & col~=defchar;
if any(mask),
error([upper(mfilename) ' does not recognize ''' deblank(ispatch(min(find(mask)),:)) ''' as a valid ''Type'' value.']);
end;
ispatch = (col==patchchar)*1 + (col==linechar)*0 + (col==defchar)*defispatch;
else,
ispatch = ispatch(:);
end;
oldh = oldh(:);
% check object handles
if ~all(ishandle(oldh)), error([upper(mfilename) ' got invalid object handles.']); end;
% expand root, figure, and axes handles
if ~isempty(oldh),
ohtype = get(oldh,'Type');
mask = strcmp(ohtype,'root') | strcmp(ohtype,'figure') | strcmp(ohtype,'axes');
if any(mask),
oldh = num2cell(oldh);
for ii=find(mask)',
oldh(ii) = {findobj(oldh{ii},'Tag',ArrowTag)};
end;
oldh = cat(1,oldh{:});
if isempty(oldh), return; end; % no arrows to modify, so just leave
end;
end;
% largest argument length
[mstart,junk]=size(start); [mstop,junk]=size(stop); [mcrossdir,junk]=size(crossdir);
argsizes = [length(oldh) mstart mstop ...
length(len) length(baseangle) length(tipangle) ...
length(wid) length(page) mcrossdir length(ends) ];
args=['length(ObjectHandle) '; ...
'#rows(Start) '; ...
'#rows(Stop) '; ...
'length(Length) '; ...
'length(BaseAngle) '; ...
'length(TipAngle) '; ...
'length(Width) '; ...
'length(Page) '; ...
'#rows(CrossDir) '; ...
'#rows(Ends) '];
if (any(imag(crossdir(:))~=0)),
args(9,:) = '#rows(NormalDir) ';
end;
if isempty(oldh),
narrows = max(argsizes);
else,
narrows = length(oldh);
end;
if (narrows<=0), narrows=1; end;
% Check size of arguments
ii = find((argsizes~=0)&(argsizes~=1)&(argsizes~=narrows));
if ~isempty(ii),
s = args(ii',:);
while ((size(s,2)>1)&((abs(s(:,size(s,2)))==0)|(abs(s(:,size(s,2)))==abs(' ')))),
s = s(:,1:size(s,2)-1);
end;
s = [ones(length(ii),1)*[upper(mfilename) ' requires that '] s ...
ones(length(ii),1)*[' equal the # of arrows (' num2str(narrows) ').' c]];
s = s';
s = s(:)';
s = s(1:length(s)-1);
error(setstr(s));
end;
% check element length in Start, Stop, and CrossDir
if ~isempty(start),
[m,n] = size(start);
if (n==2),
start = [start nan(m,1)];
elseif (n~=3),
error([upper(mfilename) ' requires 2- or 3-element Start points.']);
end;
end;
if ~isempty(stop),
[m,n] = size(stop);
if (n==2),
stop = [stop nan(m,1)];
elseif (n~=3),
error([upper(mfilename) ' requires 2- or 3-element Stop points.']);
end;
end;
if ~isempty(crossdir),
[m,n] = size(crossdir);
if (n<3),
crossdir = [crossdir nan(m,3-n)];
elseif (n~=3),
if (all(imag(crossdir(:))==0)),
error([upper(mfilename) ' requires 2- or 3-element CrossDir vectors.']);
else,
error([upper(mfilename) ' requires 2- or 3-element NormalDir vectors.']);
end;
end;
end;
% fill empty arguments
if isempty(start ), start = [Inf Inf Inf]; end;
if isempty(stop ), stop = [Inf Inf Inf]; end;
if isempty(len ), len = Inf; end;
if isempty(baseangle ), baseangle = Inf; end;
if isempty(tipangle ), tipangle = Inf; end;
if isempty(wid ), wid = Inf; end;
if isempty(page ), page = Inf; end;
if isempty(crossdir ), crossdir = [Inf Inf Inf]; end;
if isempty(ends ), ends = Inf; end;
if isempty(ispatch ), ispatch = Inf; end;
% expand single-column arguments
o = ones(narrows,1);
if (size(start ,1)==1), start = o * start ; end;
if (size(stop ,1)==1), stop = o * stop ; end;
if (length(len )==1), len = o * len ; end;
if (length(baseangle )==1), baseangle = o * baseangle ; end;
if (length(tipangle )==1), tipangle = o * tipangle ; end;
if (length(wid )==1), wid = o * wid ; end;
if (length(page )==1), page = o * page ; end;
if (size(crossdir ,1)==1), crossdir = o * crossdir ; end;
if (length(ends )==1), ends = o * ends ; end;
if (length(ispatch )==1), ispatch = o * ispatch ; end;
ax = o * gca;
% if we've got handles, get the defaults from the handles
if ~isempty(oldh),
for k=1:narrows,
oh = oldh(k);
ud = get(oh,'UserData');
ax(k) = get(oh,'Parent');
ohtype = get(oh,'Type');
if strcmp(get(oh,'Tag'),ArrowTag), % if it's an arrow already
if isinf(ispatch(k)), ispatch(k)=strcmp(ohtype,'patch'); end;
% arrow UserData format: [start' stop' len base tip wid page crossdir' ends]
start0 = ud(1:3);
stop0 = ud(4:6);
if (isinf(len(k))), len(k) = ud( 7); end;
if (isinf(baseangle(k))), baseangle(k) = ud( 8); end;
if (isinf(tipangle(k))), tipangle(k) = ud( 9); end;
if (isinf(wid(k))), wid(k) = ud(10); end;
if (isinf(page(k))), page(k) = ud(11); end;
if (isinf(crossdir(k,1))), crossdir(k,1) = ud(12); end;
if (isinf(crossdir(k,2))), crossdir(k,2) = ud(13); end;
if (isinf(crossdir(k,3))), crossdir(k,3) = ud(14); end;
if (isinf(ends(k))), ends(k) = ud(15); end;
elseif strcmp(ohtype,'line')|strcmp(ohtype,'patch'), % it's a non-arrow line or patch
convLineToPatch = 1; %set to make arrow patches when converting from lines.
if isinf(ispatch(k)), ispatch(k)=convLineToPatch|strcmp(ohtype,'patch'); end;
x=get(oh,'XData'); x=x(~isnan(x(:))); if isempty(x), x=NaN; end;
y=get(oh,'YData'); y=y(~isnan(y(:))); if isempty(y), y=NaN; end;
z=get(oh,'ZData'); z=z(~isnan(z(:))); if isempty(z), z=NaN; end;
start0 = [x(1) y(1) z(1) ];
stop0 = [x(end) y(end) z(end)];
else,
error([upper(mfilename) ' cannot convert ' ohtype ' objects.']);
end;
ii=find(isinf(start(k,:))); if ~isempty(ii), start(k,ii)=start0(ii); end;
ii=find(isinf(stop( k,:))); if ~isempty(ii), stop( k,ii)=stop0( ii); end;
end;
end;
% convert Inf's to NaN's
start( isinf(start )) = NaN;
stop( isinf(stop )) = NaN;
len( isinf(len )) = NaN;
baseangle( isinf(baseangle)) = NaN;
tipangle( isinf(tipangle )) = NaN;
wid( isinf(wid )) = NaN;
page( isinf(page )) = NaN;
crossdir( isinf(crossdir )) = NaN;
ends( isinf(ends )) = NaN;
ispatch( isinf(ispatch )) = NaN;
% set up the UserData data (here so not corrupted by log10's and such)
ud = [start stop len baseangle tipangle wid page crossdir ends];
% Set Page defaults
page = ~isnan(page) & trueornan(page);
% Get axes limits, range, min; correct for aspect ratio and log scale
axm = zeros(3,narrows);
axr = zeros(3,narrows);
axrev = zeros(3,narrows);
ap = zeros(2,narrows);
xyzlog = zeros(3,narrows);
limmin = zeros(2,narrows);
limrange = zeros(2,narrows);
oldaxlims = zeros(narrows,7);
oneax = all(ax==ax(1));
if (oneax),
T = zeros(4,4);
invT = zeros(4,4);
else,
T = zeros(16,narrows);
invT = zeros(16,narrows);
end;
axnotdone = logical(ones(size(ax)));
while (any(axnotdone)),
ii = min(find(axnotdone));
curax = ax(ii);
curpage = page(ii);
% get axes limits and aspect ratio
axl = [get(curax,'XLim'); get(curax,'YLim'); get(curax,'ZLim')];
oldaxlims(min(find(oldaxlims(:,1)==0)),:) = [curax reshape(axl',1,6)];
% get axes size in pixels (points)
u = get(curax,'Units');
axposoldunits = get(curax,'Position');
really_curpage = curpage & strcmp(u,'normalized');
if (really_curpage),
curfig = get(curax,'Parent');
pu = get(curfig,'PaperUnits');
set(curfig,'PaperUnits','points');
pp = get(curfig,'PaperPosition');
set(curfig,'PaperUnits',pu);
set(curax,'Units','pixels');
curapscreen = get(curax,'Position');
set(curax,'Units','normalized');
curap = pp.*get(curax,'Position');
else,
set(curax,'Units','pixels');
curapscreen = get(curax,'Position');
curap = curapscreen;
end;
set(curax,'Units',u);
set(curax,'Position',axposoldunits);
% handle non-stretched axes position
str_stretch = { 'DataAspectRatioMode' ; ...
'PlotBoxAspectRatioMode' ; ...
'CameraViewAngleMode' };
str_camera = { 'CameraPositionMode' ; ...
'CameraTargetMode' ; ...
'CameraViewAngleMode' ; ...
'CameraUpVectorMode' };
notstretched = strcmp(get(curax,str_stretch),'manual');
manualcamera = strcmp(get(curax,str_camera),'manual');
if ~arrow_WarpToFill(notstretched,manualcamera,curax),
% give a warning that this has not been thoroughly tested
if 0 & ARROW_STRETCH_WARN,
ARROW_STRETCH_WARN = 0;
strs = {str_stretch{1:2},str_camera{:}};
strs = [char(ones(length(strs),1)*sprintf('\n ')) char(strs)]';
warning([upper(mfilename) ' may not yet work quite right ' ...
'if any of the following are ''manual'':' strs(:).']);
end;
% find the true pixel size of the actual axes
texttmp = text(axl(1,[1 2 2 1 1 2 2 1]), ...
axl(2,[1 1 2 2 1 1 2 2]), ...
axl(3,[1 1 1 1 2 2 2 2]),'');
set(texttmp,'Units','points');
textpos = get(texttmp,'Position');
delete(texttmp);
textpos = cat(1,textpos{:});
textpos = max(textpos(:,1:2)) - min(textpos(:,1:2));
% adjust the axes position
if (really_curpage),
% adjust to printed size
textpos = textpos * min(curap(3:4)./textpos);
curap = [curap(1:2)+(curap(3:4)-textpos)/2 textpos];
else,
% adjust for pixel roundoff
textpos = textpos * min(curapscreen(3:4)./textpos);
curap = [curap(1:2)+(curap(3:4)-textpos)/2 textpos];
end;
end;
if ARROW_PERSP_WARN & ~strcmp(get(curax,'Projection'),'orthographic'),
ARROW_PERSP_WARN = 0;
warning([upper(mfilename) ' does not yet work right for 3-D perspective projection.']);
end;
% adjust limits for log scale on axes
curxyzlog = [strcmp(get(curax,'XScale'),'log'); ...
strcmp(get(curax,'YScale'),'log'); ...
strcmp(get(curax,'ZScale'),'log')];
if (any(curxyzlog)),
ii = find([curxyzlog;curxyzlog]);
if (any(axl(ii)<=0)),
error([upper(mfilename) ' does not support non-positive limits on log-scaled axes.']);
else,
axl(ii) = log10(axl(ii));
end;
end;
% correct for 'reverse' direction on axes;
curreverse = [strcmp(get(curax,'XDir'),'reverse'); ...
strcmp(get(curax,'YDir'),'reverse'); ...
strcmp(get(curax,'ZDir'),'reverse')];
ii = find(curreverse);
if ~isempty(ii),
axl(ii,[1 2])=-axl(ii,[2 1]);
end;
% compute the range of 2-D values
curT = get(curax,'Xform');
lim = curT*[0 1 0 1 0 1 0 1;0 0 1 1 0 0 1 1;0 0 0 0 1 1 1 1;1 1 1 1 1 1 1 1];
lim = lim(1:2,:)./([1;1]*lim(4,:));
curlimmin = min(lim')';
curlimrange = max(lim')' - curlimmin;
curinvT = inv(curT);
if (~oneax),
curT = curT.';
curinvT = curinvT.';
curT = curT(:);
curinvT = curinvT(:);
end;
% check which arrows to which cur corresponds
ii = find((ax==curax)&(page==curpage));
oo = ones(1,length(ii));
axr(:,ii) = diff(axl')' * oo;
axm(:,ii) = axl(:,1) * oo;
axrev(:,ii) = curreverse * oo;
ap(:,ii) = curap(3:4)' * oo;
xyzlog(:,ii) = curxyzlog * oo;
limmin(:,ii) = curlimmin * oo;
limrange(:,ii) = curlimrange * oo;
if (oneax),
T = curT;
invT = curinvT;
else,
T(:,ii) = curT * oo;
invT(:,ii) = curinvT * oo;
end;
axnotdone(ii) = zeros(1,length(ii));
end;
oldaxlims(oldaxlims(:,1)==0,:)=[];
% correct for log scales
curxyzlog = xyzlog.';
ii = find(curxyzlog(:));
if ~isempty(ii),
start( ii) = real(log10(start( ii)));
stop( ii) = real(log10(stop( ii)));
if (all(imag(crossdir)==0)), % pulled (ii) subscript on crossdir, 12/5/96 eaj
crossdir(ii) = real(log10(crossdir(ii)));
end;
end;
% correct for reverse directions
ii = find(axrev.');
if ~isempty(ii),
start( ii) = -start( ii);
stop( ii) = -stop( ii);
crossdir(ii) = -crossdir(ii);
end;
% transpose start/stop values
start = start.';
stop = stop.';
% take care of defaults, page was done above
ii=find(isnan(start(:) )); if ~isempty(ii), start(ii) = axm(ii)+axr(ii)/2; end;
ii=find(isnan(stop(:) )); if ~isempty(ii), stop(ii) = axm(ii)+axr(ii)/2; end;
ii=find(isnan(crossdir(:) )); if ~isempty(ii), crossdir(ii) = zeros(length(ii),1); end;
ii=find(isnan(len )); if ~isempty(ii), len(ii) = ones(length(ii),1)*deflen; end;
ii=find(isnan(baseangle )); if ~isempty(ii), baseangle(ii) = ones(length(ii),1)*defbaseangle; end;
ii=find(isnan(tipangle )); if ~isempty(ii), tipangle(ii) = ones(length(ii),1)*deftipangle; end;
ii=find(isnan(wid )); if ~isempty(ii), wid(ii) = ones(length(ii),1)*defwid; end;
ii=find(isnan(ends )); if ~isempty(ii), ends(ii) = ones(length(ii),1)*defends; end;
% transpose rest of values
len = len.';
baseangle = baseangle.';
tipangle = tipangle.';
wid = wid.';
page = page.';
crossdir = crossdir.';
ends = ends.';
ax = ax.';
% given x, a 3xN matrix of points in 3-space;
% want to convert to X, the corresponding 4xN 2-space matrix
%
% tmp1=[(x-axm)./axr; ones(1,size(x,1))];
% if (oneax), X=T*tmp1;
% else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=T.*tmp1;
% tmp2=zeros(4,4*N); tmp2(:)=tmp1(:);
% X=zeros(4,N); X(:)=sum(tmp2)'; end;
% X = X ./ (ones(4,1)*X(4,:));
% for all points with start==stop, start=stop-(verysmallvalue)*(up-direction);
ii = find(all(start==stop));
if ~isempty(ii),
% find an arrowdir vertical on screen and perpendicular to viewer
% transform to 2-D
tmp1 = [(stop(:,ii)-axm(:,ii))./axr(:,ii);ones(1,length(ii))];
if (oneax), twoD=T*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=T(:,ii).*tmp1;
tmp2=zeros(4,4*length(ii)); tmp2(:)=tmp1(:);
twoD=zeros(4,length(ii)); twoD(:)=sum(tmp2)'; end;
twoD=twoD./(ones(4,1)*twoD(4,:));
% move the start point down just slightly
tmp1 = twoD + [0;-1/1000;0;0]*(limrange(2,ii)./ap(2,ii));
% transform back to 3-D
if (oneax), threeD=invT*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=invT(:,ii).*tmp1;
tmp2=zeros(4,4*length(ii)); tmp2(:)=tmp1(:);
threeD=zeros(4,length(ii)); threeD(:)=sum(tmp2)'; end;
start(:,ii) = (threeD(1:3,:)./(ones(3,1)*threeD(4,:))).*axr(:,ii)+axm(:,ii);
end;
% compute along-arrow points
% transform Start points
tmp1=[(start-axm)./axr;ones(1,narrows)];
if (oneax), X0=T*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=T.*tmp1;
tmp2=zeros(4,4*narrows); tmp2(:)=tmp1(:);
X0=zeros(4,narrows); X0(:)=sum(tmp2)'; end;
X0=X0./(ones(4,1)*X0(4,:));
% transform Stop points
tmp1=[(stop-axm)./axr;ones(1,narrows)];
if (oneax), Xf=T*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=T.*tmp1;
tmp2=zeros(4,4*narrows); tmp2(:)=tmp1(:);
Xf=zeros(4,narrows); Xf(:)=sum(tmp2)'; end;
Xf=Xf./(ones(4,1)*Xf(4,:));
% compute pixel distance between points
D = sqrt(sum(((Xf(1:2,:)-X0(1:2,:)).*(ap./limrange)).^2));
D = D + (D==0); %eaj new 2/24/98
% compute and modify along-arrow distances
len1 = len;
len2 = len - (len.*tan(tipangle/180*pi)-wid/2).*tan((90-baseangle)/180*pi);
slen0 = zeros(1,narrows);
slen1 = len1 .* ((ends==2)|(ends==3));
slen2 = len2 .* ((ends==2)|(ends==3));
len0 = zeros(1,narrows);
len1 = len1 .* ((ends==1)|(ends==3));
len2 = len2 .* ((ends==1)|(ends==3));
% for no start arrowhead
ii=find((ends==1)&(D<len2));
if ~isempty(ii),
slen0(ii) = D(ii)-len2(ii);
end;
% for no end arrowhead
ii=find((ends==2)&(D<slen2));
if ~isempty(ii),
len0(ii) = D(ii)-slen2(ii);
end;
len1 = len1 + len0;
len2 = len2 + len0;
slen1 = slen1 + slen0;
slen2 = slen2 + slen0;
% note: the division by D below will probably not be accurate if both
% of the following are true:
% 1. the ratio of the line length to the arrowhead
% length is large
% 2. the view is highly perspective.
% compute stoppoints
tmp1=X0.*(ones(4,1)*(len0./D))+Xf.*(ones(4,1)*(1-len0./D));
if (oneax), tmp3=invT*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=invT.*tmp1;
tmp2=zeros(4,4*narrows); tmp2(:)=tmp1(:);
tmp3=zeros(4,narrows); tmp3(:)=sum(tmp2)'; end;
stoppoint = tmp3(1:3,:)./(ones(3,1)*tmp3(4,:)).*axr+axm;
% compute tippoints
tmp1=X0.*(ones(4,1)*(len1./D))+Xf.*(ones(4,1)*(1-len1./D));
if (oneax), tmp3=invT*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=invT.*tmp1;
tmp2=zeros(4,4*narrows); tmp2(:)=tmp1(:);
tmp3=zeros(4,narrows); tmp3(:)=sum(tmp2)'; end;
tippoint = tmp3(1:3,:)./(ones(3,1)*tmp3(4,:)).*axr+axm;
% compute basepoints
tmp1=X0.*(ones(4,1)*(len2./D))+Xf.*(ones(4,1)*(1-len2./D));
if (oneax), tmp3=invT*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=invT.*tmp1;
tmp2=zeros(4,4*narrows); tmp2(:)=tmp1(:);
tmp3=zeros(4,narrows); tmp3(:)=sum(tmp2)'; end;
basepoint = tmp3(1:3,:)./(ones(3,1)*tmp3(4,:)).*axr+axm;
% compute startpoints
tmp1=X0.*(ones(4,1)*(1-slen0./D))+Xf.*(ones(4,1)*(slen0./D));
if (oneax), tmp3=invT*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=invT.*tmp1;
tmp2=zeros(4,4*narrows); tmp2(:)=tmp1(:);
tmp3=zeros(4,narrows); tmp3(:)=sum(tmp2)'; end;
startpoint = tmp3(1:3,:)./(ones(3,1)*tmp3(4,:)).*axr+axm;
% compute stippoints
tmp1=X0.*(ones(4,1)*(1-slen1./D))+Xf.*(ones(4,1)*(slen1./D));
if (oneax), tmp3=invT*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=invT.*tmp1;
tmp2=zeros(4,4*narrows); tmp2(:)=tmp1(:);
tmp3=zeros(4,narrows); tmp3(:)=sum(tmp2)'; end;
stippoint = tmp3(1:3,:)./(ones(3,1)*tmp3(4,:)).*axr+axm;
% compute sbasepoints
tmp1=X0.*(ones(4,1)*(1-slen2./D))+Xf.*(ones(4,1)*(slen2./D));
if (oneax), tmp3=invT*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=invT.*tmp1;
tmp2=zeros(4,4*narrows); tmp2(:)=tmp1(:);
tmp3=zeros(4,narrows); tmp3(:)=sum(tmp2)'; end;
sbasepoint = tmp3(1:3,:)./(ones(3,1)*tmp3(4,:)).*axr+axm;
% compute cross-arrow directions for arrows with NormalDir specified
if (any(imag(crossdir(:))~=0)),
ii = find(any(imag(crossdir)~=0));
crossdir(:,ii) = cross((stop(:,ii)-start(:,ii))./axr(:,ii), ...
imag(crossdir(:,ii))).*axr(:,ii);
end;
% compute cross-arrow directions
basecross = crossdir + basepoint;
tipcross = crossdir + tippoint;
sbasecross = crossdir + sbasepoint;
stipcross = crossdir + stippoint;
ii = find(all(crossdir==0)|any(isnan(crossdir)));
if ~isempty(ii),
numii = length(ii);
% transform start points
tmp1 = [basepoint(:,ii) tippoint(:,ii) sbasepoint(:,ii) stippoint(:,ii)];
tmp1 = (tmp1-axm(:,[ii ii ii ii])) ./ axr(:,[ii ii ii ii]);
tmp1 = [tmp1; ones(1,4*numii)];
if (oneax), X0=T*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=T(:,[ii ii ii ii]).*tmp1;
tmp2=zeros(4,16*numii); tmp2(:)=tmp1(:);
X0=zeros(4,4*numii); X0(:)=sum(tmp2)'; end;
X0=X0./(ones(4,1)*X0(4,:));
% transform stop points
tmp1 = [(2*stop(:,ii)-start(:,ii)-axm(:,ii))./axr(:,ii);ones(1,numii)];
tmp1 = [tmp1 tmp1 tmp1 tmp1];
if (oneax), Xf=T*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=T(:,[ii ii ii ii]).*tmp1;
tmp2=zeros(4,16*numii); tmp2(:)=tmp1(:);
Xf=zeros(4,4*numii); Xf(:)=sum(tmp2)'; end;
Xf=Xf./(ones(4,1)*Xf(4,:));
% compute perpendicular directions
pixfact = ((limrange(1,ii)./limrange(2,ii)).*(ap(2,ii)./ap(1,ii))).^2;
pixfact = [pixfact pixfact pixfact pixfact];
pixfact = [pixfact;1./pixfact];
[dummyval,jj] = max(abs(Xf(1:2,:)-X0(1:2,:)));
jj1 = ((1:4)'*ones(1,length(jj))==ones(4,1)*jj);
jj2 = ((1:4)'*ones(1,length(jj))==ones(4,1)*(3-jj));
jj3 = jj1(1:2,:);
Xf(jj1)=Xf(jj1)+(Xf(jj1)-X0(jj1)==0); %eaj new 2/24/98
Xp = X0;
Xp(jj2) = X0(jj2) + ones(sum(jj2(:)),1);
Xp(jj1) = X0(jj1) - (Xf(jj2)-X0(jj2))./(Xf(jj1)-X0(jj1)) .* pixfact(jj3);
% inverse transform the cross points
if (oneax), Xp=invT*Xp;
else, tmp1=[Xp;Xp;Xp;Xp]; tmp1=invT(:,[ii ii ii ii]).*tmp1;
tmp2=zeros(4,16*numii); tmp2(:)=tmp1(:);
Xp=zeros(4,4*numii); Xp(:)=sum(tmp2)'; end;
Xp=(Xp(1:3,:)./(ones(3,1)*Xp(4,:))).*axr(:,[ii ii ii ii])+axm(:,[ii ii ii ii]);
basecross(:,ii) = Xp(:,0*numii+(1:numii));
tipcross(:,ii) = Xp(:,1*numii+(1:numii));
sbasecross(:,ii) = Xp(:,2*numii+(1:numii));
stipcross(:,ii) = Xp(:,3*numii+(1:numii));
end;
% compute all points
% compute start points
axm11 = [axm axm axm axm axm axm axm axm axm axm axm];
axr11 = [axr axr axr axr axr axr axr axr axr axr axr];
st = [stoppoint tippoint basepoint sbasepoint stippoint startpoint stippoint sbasepoint basepoint tippoint stoppoint];
tmp1 = (st - axm11) ./ axr11;
tmp1 = [tmp1; ones(1,size(tmp1,2))];
if (oneax), X0=T*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=[T T T T T T T T T T T].*tmp1;
tmp2=zeros(4,44*narrows); tmp2(:)=tmp1(:);
X0=zeros(4,11*narrows); X0(:)=sum(tmp2)'; end;
X0=X0./(ones(4,1)*X0(4,:));
% compute stop points
tmp1 = ([start tipcross basecross sbasecross stipcross stop stipcross sbasecross basecross tipcross start] ...
- axm11) ./ axr11;
tmp1 = [tmp1; ones(1,size(tmp1,2))];
if (oneax), Xf=T*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=[T T T T T T T T T T T].*tmp1;
tmp2=zeros(4,44*narrows); tmp2(:)=tmp1(:);
Xf=zeros(4,11*narrows); Xf(:)=sum(tmp2)'; end;
Xf=Xf./(ones(4,1)*Xf(4,:));
% compute lengths
len0 = len.*((ends==1)|(ends==3)).*tan(tipangle/180*pi);
slen0 = len.*((ends==2)|(ends==3)).*tan(tipangle/180*pi);
le = [zeros(1,narrows) len0 wid/2 wid/2 slen0 zeros(1,narrows) -slen0 -wid/2 -wid/2 -len0 zeros(1,narrows)];
aprange = ap./limrange;
aprange = [aprange aprange aprange aprange aprange aprange aprange aprange aprange aprange aprange];
D = sqrt(sum(((Xf(1:2,:)-X0(1:2,:)).*aprange).^2));
Dii=find(D==0); if ~isempty(Dii), D=D+(D==0); le(Dii)=zeros(1,length(Dii)); end; %should fix DivideByZero warnings
tmp1 = X0.*(ones(4,1)*(1-le./D)) + Xf.*(ones(4,1)*(le./D));
% inverse transform
if (oneax), tmp3=invT*tmp1;
else, tmp1=[tmp1;tmp1;tmp1;tmp1]; tmp1=[invT invT invT invT invT invT invT invT invT invT invT].*tmp1;
tmp2=zeros(4,44*narrows); tmp2(:)=tmp1(:);
tmp3=zeros(4,11*narrows); tmp3(:)=sum(tmp2)'; end;
pts = tmp3(1:3,:)./(ones(3,1)*tmp3(4,:)) .* axr11 + axm11;
% correct for ones where the crossdir was specified
ii = find(~(all(crossdir==0)|any(isnan(crossdir))));
if ~isempty(ii),
D1 = [pts(:,1*narrows+ii)-pts(:,9*narrows+ii) ...
pts(:,2*narrows+ii)-pts(:,8*narrows+ii) ...
pts(:,3*narrows+ii)-pts(:,7*narrows+ii) ...
pts(:,4*narrows+ii)-pts(:,6*narrows+ii) ...
pts(:,6*narrows+ii)-pts(:,4*narrows+ii) ...
pts(:,7*narrows+ii)-pts(:,3*narrows+ii) ...
pts(:,8*narrows+ii)-pts(:,2*narrows+ii) ...
pts(:,9*narrows+ii)-pts(:,1*narrows+ii)]/2;
ii = ii'*ones(1,8) + ones(length(ii),1)*[1:4 6:9]*narrows;
ii = ii(:)';
pts(:,ii) = st(:,ii) + D1;
end;
% readjust for reverse directions
iicols=(1:narrows)'; iicols=iicols(:,ones(1,11)); iicols=iicols(:).';
tmp1=axrev(:,iicols);
ii = find(tmp1(:)); if ~isempty(ii), pts(ii)=-pts(ii); end;
% readjust for log scale on axes
tmp1=xyzlog(:,iicols);
ii = find(tmp1(:)); if ~isempty(ii), pts(ii)=10.^pts(ii); end;
% compute the x,y,z coordinates of the patches;
ii = narrows*(0:10)'*ones(1,narrows) + ones(11,1)*(1:narrows);
ii = ii(:)';
x = zeros(11,narrows);
y = zeros(11,narrows);
z = zeros(11,narrows);
x(:) = pts(1,ii)';
y(:) = pts(2,ii)';
z(:) = pts(3,ii)';
% do the output
if (nargout<=1),
% % create or modify the patches
newpatch = trueornan(ispatch) & (isempty(oldh)|~strcmp(get(oldh,'Type'),'patch'));
newline = ~trueornan(ispatch) & (isempty(oldh)|~strcmp(get(oldh,'Type'),'line'));
if isempty(oldh), H=zeros(narrows,1); else, H=oldh; end;
% % make or modify the arrows
for k=1:narrows,
if all(isnan(ud(k,[3 6])))&arrow_is2DXY(ax(k)), zz=[]; else, zz=z(:,k); end;
% work around a MATLAB 6.x OpenGL bug -- 7/28/02
xx=x(:,k); yy=y(:,k);
mask=any([ones(1,2+size(zz,2));diff([xx yy zz],[],1)],2);
xx=xx(mask); yy=yy(mask); if ~isempty(zz), zz=zz(mask); end;
% plot the patch or line
xyz = {'XData',xx,'YData',yy,'ZData',zz,'Tag',ArrowTag};
if newpatch(k)|newline(k),
if newpatch(k),
H(k) = patch(xyz{:});
else,
H(k) = line(xyz{:});
end;
if ~isempty(oldh), arrow_copyprops(oldh(k),H(k)); end;
else,
if ispatch(k), xyz={xyz{:},'CData',[]}; end;
set(H(k),xyz{:});
end;
end;
if ~isempty(oldh), delete(oldh(oldh~=H)); end;
% % additional properties
set(H,'Clipping','off');
set(H,{'UserData'},num2cell(ud,2));
if (length(extraprops)>0), set(H,extraprops{:}); end;
% handle choosing arrow Start and/or Stop locations if unspecified
[H,oldaxlims,errstr] = arrow_clicks(H,ud,x,y,z,ax,oldaxlims);
if ~isempty(errstr), error([upper(mfilename) ' got ' errstr]); end;
% set the output
if (nargout>0), h=H; end;
% make sure the axis limits did not change
if isempty(oldaxlims),
ARROW_AXLIMITS = [];
else,
lims = get(oldaxlims(:,1),{'XLim','YLim','ZLim'})';
lims = reshape(cat(2,lims{:}),6,size(lims,2));
mask = arrow_is2DXY(oldaxlims(:,1));
oldaxlims(mask,6:7) = lims(5:6,mask)';
ARROW_AXLIMITS = oldaxlims(find(any(oldaxlims(:,2:7)'~=lims)),:);
if ~isempty(ARROW_AXLIMITS),
warning(arrow_warnlimits(ARROW_AXLIMITS,narrows));
end;
end;
else,
% don't create the patch, just return the data
h=x;
yy=y;
zz=z;
end;
function out = arrow_defcheck(in,def,prop)
% check if we got 'default' values
out = in;
if ~ischar(in), return; end;
if size(in,1)==1 & strncmp(lower(in),'def',3),
out = def;
elseif ~isempty(prop),
error([upper(mfilename) ' does not recognize ''' in(:)' ''' as a valid ''' prop ''' string.']);
end;
function [H,oldaxlims,errstr] = arrow_clicks(H,ud,x,y,z,ax,oldaxlims)
% handle choosing arrow Start and/or Stop locations if necessary
errstr = '';
if isempty(H)|isempty(ud)|isempty(x), return; end;
% determine which (if any) need Start and/or Stop
needStart = all(isnan(ud(:,1:3)'))';
needStop = all(isnan(ud(:,4:6)'))';
mask = any(needStart|needStop);
if ~any(mask), return; end;
ud(~mask,:)=[]; ax(:,~mask)=[];
x(:,~mask)=[]; y(:,~mask)=[]; z(:,~mask)=[];
% make them invisible for the time being
set(H,'Visible','off');
% save the current axes and limits modes; set to manual for the time being
oldAx = gca;
limModes=get(ax(:),{'XLimMode','YLimMode','ZLimMode'});
set(ax(:),{'XLimMode','YLimMode','ZLimMode'},{'manual','manual','manual'});
% loop over each arrow that requires attention
jj = find(mask);
for ii=1:length(jj),
h = H(jj(ii));
axes(ax(ii));
% figure out correct call
if needStart(ii), prop='Start'; else, prop='Stop'; end;
[wasInterrupted,errstr] = arrow_click(needStart(ii)&needStop(ii),h,prop,ax(ii));
% handle errors and control-C
if wasInterrupted,
delete(H(jj(ii:end)));
H(jj(ii:end))=[];
oldaxlims(jj(ii:end),:)=[];
break;
end;
end;
% restore the axes and limit modes
axes(oldAx);
set(ax(:),{'XLimMode','YLimMode','ZLimMode'},limModes);
function [wasInterrupted,errstr] = arrow_click(lockStart,H,prop,ax)
% handle the clicks for one arrow
fig = get(ax,'Parent');
% save some things
oldFigProps = {'Pointer','WindowButtonMotionFcn','WindowButtonUpFcn'};
oldFigValue = get(fig,oldFigProps);
oldArrowProps = {'EraseMode'};
oldArrowValue = get(H,oldArrowProps);
set(H,'EraseMode','background'); %because 'xor' makes shaft invisible unless Width>1
global ARROW_CLICK_H ARROW_CLICK_PROP ARROW_CLICK_AX ARROW_CLICK_USE_Z
ARROW_CLICK_H=H; ARROW_CLICK_PROP=prop; ARROW_CLICK_AX=ax;
ARROW_CLICK_USE_Z=~arrow_is2DXY(ax)|~arrow_planarkids(ax);
set(fig,'Pointer','crosshair');
% set up the WindowButtonMotion so we can see the arrow while moving around
set(fig,'WindowButtonUpFcn','set(gcf,''WindowButtonUpFcn'','''')', ...
'WindowButtonMotionFcn','');
if ~lockStart,
set(H,'Visible','on');
set(fig,'WindowButtonMotionFcn',[mfilename '(''callback'',''motion'');']);
end;
% wait for the button to be pressed
[wasKeyPress,wasInterrupted,errstr] = arrow_wfbdown(fig);
% if we wanted to click-drag, set the Start point
if lockStart & ~wasInterrupted,
pt = arrow_point(ARROW_CLICK_AX,ARROW_CLICK_USE_Z);
feval(mfilename,H,'Start',pt,'Stop',pt);
set(H,'Visible','on');
ARROW_CLICK_PROP='Stop';
set(fig,'WindowButtonMotionFcn',[mfilename '(''callback'',''motion'');']);
% wait for the mouse button to be released
eval('waitfor(fig,''WindowButtonUpFcn'','''');','wasInterrupted=1;');
if wasInterrupted, errstr=lasterr; end;
end;
if ~wasInterrupted, feval(mfilename,'callback','motion'); end;
% restore some things
set(gcf,oldFigProps,oldFigValue);
set(H,oldArrowProps,oldArrowValue);
function arrow_callback(varargin)
% handle redrawing callbacks
if nargin==0, return; end;
str = varargin{1};
if ~ischar(str), error([upper(mfilename) ' got an invalid Callback command.']); end;
s = lower(str);
if strcmp(s,'motion'),
% motion callback
global ARROW_CLICK_H ARROW_CLICK_PROP ARROW_CLICK_AX ARROW_CLICK_USE_Z
feval(mfilename,ARROW_CLICK_H,ARROW_CLICK_PROP,arrow_point(ARROW_CLICK_AX,ARROW_CLICK_USE_Z));
drawnow;
else,
error([upper(mfilename) ' does not recognize ''' str(:).' ''' as a valid Callback option.']);
end;
function out = arrow_point(ax,use_z)
% return the point on the given axes
if nargin==0, ax=gca; end;
if nargin<2, use_z=~arrow_is2DXY(ax)|~arrow_planarkids(ax); end;
out = get(ax,'CurrentPoint');
out = out(1,:);
if ~use_z, out=out(1:2); end;
function [wasKeyPress,wasInterrupted,errstr] = arrow_wfbdown(fig)
% wait for button down ignoring object ButtonDownFcn's
if nargin==0, fig=gcf; end;
errstr = '';
% save ButtonDownFcn values
objs = findobj(fig);
buttonDownFcns = get(objs,'ButtonDownFcn');
mask=~strcmp(buttonDownFcns,''); objs=objs(mask); buttonDownFcns=buttonDownFcns(mask);
set(objs,'ButtonDownFcn','');
% save other figure values
figProps = {'KeyPressFcn','WindowButtonDownFcn'};
figValue = get(fig,figProps);
% do the real work
set(fig,'KeyPressFcn','set(gcf,''KeyPressFcn'','''',''WindowButtonDownFcn'','''');', ...
'WindowButtonDownFcn','set(gcf,''WindowButtonDownFcn'','''')');
lasterr('');
wasInterrupted=0; eval('waitfor(fig,''WindowButtonDownFcn'','''');','wasInterrupted=1;');
wasKeyPress = ~wasInterrupted & strcmp(get(fig,'KeyPressFcn'),'');
if wasInterrupted, errstr=lasterr; end;
% restore ButtonDownFcn and other figure values
set(objs,'ButtonDownFcn',buttonDownFcns);
set(fig,figProps,figValue);
function [out,is2D] = arrow_is2DXY(ax)
% check if axes are 2-D X-Y plots
% may not work for modified camera angles, etc.
out = logical(zeros(size(ax))); % 2-D X-Y plots
is2D = out; % any 2-D plots
views = get(ax(:),{'View'});
views = cat(1,views{:});
out(:) = abs(views(:,2))==90;
is2D(:) = out(:) | all(rem(views',90)==0)';
function out = arrow_planarkids(ax)
% check if axes descendents all have empty ZData (lines,patches,surfaces)
out = logical(ones(size(ax)));
allkids = get(ax(:),{'Children'});
for k=1:length(allkids),
kids = get([findobj(allkids{k},'flat','Type','line')
findobj(allkids{k},'flat','Type','patch')
findobj(allkids{k},'flat','Type','surface')],{'ZData'});
for j=1:length(kids),
if ~isempty(kids{j}), out(k)=logical(0); break; end;
end;
end;
function arrow_fixlimits(axlimits)
% reset the axis limits as necessary
if isempty(axlimits), disp([upper(mfilename) ' does not remember any axis limits to reset.']); end;
for k=1:size(axlimits,1),
if any(get(axlimits(k,1),'XLim')~=axlimits(k,2:3)), set(axlimits(k,1),'XLim',axlimits(k,2:3)); end;
if any(get(axlimits(k,1),'YLim')~=axlimits(k,4:5)), set(axlimits(k,1),'YLim',axlimits(k,4:5)); end;
if any(get(axlimits(k,1),'ZLim')~=axlimits(k,6:7)), set(axlimits(k,1),'ZLim',axlimits(k,6:7)); end;
end;
function out = arrow_WarpToFill(notstretched,manualcamera,curax)
% check if we are in "WarpToFill" mode.
out = strcmp(get(curax,'WarpToFill'),'on');
% 'WarpToFill' is undocumented, so may need to replace this by
% out = ~( any(notstretched) & any(manualcamera) );
function out = arrow_warnlimits(axlimits,narrows)
% create a warning message if we've changed the axis limits
msg = '';
switch (size(axlimits,1))
case 1, msg='';
case 2, msg='on two axes ';
otherwise, msg='on several axes ';
end;
msg = [upper(mfilename) ' changed the axis limits ' msg ...
'when adding the arrow'];
if (narrows>1), msg=[msg 's']; end;
out = [msg '.' sprintf('\n') ' Call ' upper(mfilename) ...
' FIXLIMITS to reset them now.'];
function arrow_copyprops(fm,to)
% copy line properties to patches
props = {'EraseMode','LineStyle','LineWidth','Marker','MarkerSize',...
'MarkerEdgeColor','MarkerFaceColor','ButtonDownFcn', ...
'Clipping','DeleteFcn','BusyAction','HandleVisibility', ...
'Selected','SelectionHighlight','Visible'};
lineprops = {'Color', props{:}};
patchprops = {'EdgeColor',props{:}};
patch2props = {'FaceColor',patchprops{:}};
fmpatch = strcmp(get(fm,'Type'),'patch');
topatch = strcmp(get(to,'Type'),'patch');
set(to( fmpatch& topatch),patch2props,get(fm( fmpatch& topatch),patch2props)); %p->p
set(to(~fmpatch&~topatch),lineprops, get(fm(~fmpatch&~topatch),lineprops )); %l->l
set(to( fmpatch&~topatch),lineprops, get(fm( fmpatch&~topatch),patchprops )); %p->l
set(to(~fmpatch& topatch),patchprops, get(fm(~fmpatch& topatch),lineprops) ,'FaceColor','none'); %l->p
function arrow_props
% display further help info about ARROW properties
c = sprintf('\n');
disp([c ...
'ARROW Properties: Default values are given in [square brackets], and other' c ...
' acceptable equivalent property names are in (parenthesis).' c c ...
' Start The starting points. For N arrows, B' c ...
' this should be a Nx2 or Nx3 matrix. /|\ ^' c ...
' Stop The end points. For N arrows, this /|||\ |' c ...
' should be a Nx2 or Nx3 matrix. //|||\\ L|' c ...
' Length Length of the arrowhead (in pixels on ///|||\\\ e|' c ...
' screen, points on a page). [16] (Len) ////|||\\\\ n|' c ...
' BaseAngle Angle (degrees) of the base angle /////|D|\\\\\ g|' c ...
' ADE. For a simple stick arrow, use //// ||| \\\\ t|' c ...
' BaseAngle=TipAngle. [90] (Base) /// ||| \\\ h|' c ...
' TipAngle Angle (degrees) of tip angle ABC. //<----->|| \\ |' c ...
' [16] (Tip) / base ||| \ V' c ...
' Width Width of the base in pixels. Not E angle ||<-------->C' c ...
' the ''LineWidth'' prop. [0] (Wid) |||tipangle' c ...
' Page If provided, non-empty, and not NaN, |||' c ...
' this causes ARROW to use hardcopy |||' c ...
' rather than onscreen proportions. A' c ...
' This is important if screen aspect --> <-- width' c ...
' ratio and hardcopy aspect ratio are ----CrossDir---->' c ...
' vastly different. []' c...
' CrossDir A vector giving the direction towards which the fletches' c ...
' on the arrow should go. [computed such that it is perpen-' c ...
' dicular to both the arrow direction and the view direction' c ...
' (i.e., as if it was pasted on a normal 2-D graph)] (Note' c ...
' that CrossDir is a vector. Also note that if an axis is' c ...
' plotted on a log scale, then the corresponding component' c ...
' of CrossDir must also be set appropriately, i.e., to 1 for' c ...
' no change in that direction, >1 for a positive change, >0' c ...
' and <1 for negative change.)' c ...
' NormalDir A vector normal to the fletch direction (CrossDir is then' c ...
' computed by the vector cross product [Line]x[NormalDir]). []' c ...
' (Note that NormalDir is a vector. Unlike CrossDir,' c ...
' NormalDir is used as is regardless of log-scaled axes.)' c ...
' Ends Set which end has an arrowhead. Valid values are ''none'',' c ...
' ''stop'', ''start'', and ''both''. [''stop''] (End)' c...
' ObjectHandles Vector of handles to previously-created arrows to be' c ...
' updated or line objects to be converted to arrows.' c ...
' [] (Object,Handle)' c ]);
function out = arrow_demo
% demo
% create the data
[x,y,z] = peaks;
[ddd,out.iii]=max(z(:));
out.axlim = [min(x(:)) max(x(:)) min(y(:)) max(y(:)) min(z(:)) max(z(:))];
% modify it by inserting some NaN's
[m,n] = size(z);
m = floor(m/2);
n = floor(n/2);
z(1:m,1:n) = nan(m,n);
% graph it
clf('reset');
out.hs=surf(x,y,z);
out.x=x; out.y=y; out.z=z;
xlabel('x'); ylabel('y');
function h = arrow_demo3(in)
% set the view
axlim = in.axlim;
axis(axlim);
zlabel('z');
%set(in.hs,'FaceColor','interp');
view(viewmtx(-37.5,30,20));
title(['Demo of the capabilities of the ARROW function in 3-D']);
% Normal blue arrow
h1 = feval(mfilename,[axlim(1) axlim(4) 4],[-.8 1.2 4], ...
'EdgeColor','b','FaceColor','b');
% Normal white arrow, clipped by the surface
h2 = feval(mfilename,axlim([1 4 6]),[0 2 4]);
t=text(-2.4,2.7,7.7,'arrow clipped by surf');
% Baseangle<90
h3 = feval(mfilename,[3 .125 3.5],[1.375 0.125 3.5],30,50);
t2=text(3.1,.125,3.5,'local maximum');
% Baseangle<90, fill and edge colors different
h4 = feval(mfilename,axlim(1:2:5)*.5,[0 0 0],36,60,25, ...
'EdgeColor','b','FaceColor','c');
t3=text(axlim(1)*.5,axlim(3)*.5,axlim(5)*.5-.75,'origin');
set(t3,'HorizontalAlignment','center');
% Baseangle>90, black fill
h5 = feval(mfilename,[-2.9 2.9 3],[-1.3 .4 3.2],30,120,[],6, ...
'EdgeColor','r','FaceColor','k','LineWidth',2);
% Baseangle>90, no fill
h6 = feval(mfilename,[-2.9 2.9 1.3],[-1.3 .4 1.5],30,120,[],6, ...
'EdgeColor','r','FaceColor','none','LineWidth',2);
% Stick arrow
h7 = feval(mfilename,[-1.6 -1.65 -6.5],[0 -1.65 -6.5],[],16,16);
t4=text(-1.5,-1.65,-7.25,'global mininum');
set(t4,'HorizontalAlignment','center');
% Normal, black fill
h8 = feval(mfilename,[-1.4 0 -7.2],[-1.4 0 -3],'FaceColor','k');
t5=text(-1.5,0,-7.75,'local minimum');
set(t5,'HorizontalAlignment','center');
% Gray fill, crossdir specified, 'LineStyle' --
h9 = feval(mfilename,[-3 2.2 -6],[-3 2.2 -.05],36,[],27,6,[],[0 -1 0], ...
'EdgeColor','k','FaceColor',.75*[1 1 1],'LineStyle','--');
% a series of normal arrows, linearly spaced, crossdir specified
h10y=(0:4)'/3;
h10 = feval(mfilename,[-3*ones(size(h10y)) h10y -6.5*ones(size(h10y))], ...
[-3*ones(size(h10y)) h10y -.05*ones(size(h10y))], ...
12,[],[],[],[],[0 -1 0]);
% a series of normal arrows, linearly spaced
h11x=(1:.33:2.8)';
h11 = feval(mfilename,[h11x -3*ones(size(h11x)) 6.5*ones(size(h11x))], ...
[h11x -3*ones(size(h11x)) -.05*ones(size(h11x))]);
% series of magenta arrows, radially oriented, crossdir specified
h12x=2; h12y=-3; h12z=axlim(5)/2; h12xr=1; h12zr=h12z; ir=.15;or=.81;
h12t=(0:11)'/6*pi;
h12 = feval(mfilename, ...
[h12x+h12xr*cos(h12t)*ir h12y*ones(size(h12t)) ...
h12z+h12zr*sin(h12t)*ir],[h12x+h12xr*cos(h12t)*or ...
h12y*ones(size(h12t)) h12z+h12zr*sin(h12t)*or], ...
10,[],[],[],[], ...
[-h12xr*sin(h12t) zeros(size(h12t)) h12zr*cos(h12t)],...
'FaceColor','none','EdgeColor','m');
% series of normal arrows, tangentially oriented, crossdir specified
or13=.91; h13t=(0:.5:12)'/6*pi;
locs = [h12x+h12xr*cos(h13t)*or13 h12y*ones(size(h13t)) h12z+h12zr*sin(h13t)*or13];
h13 = feval(mfilename,locs(1:end-1,:),locs(2:end,:),6);
% arrow with no line ==> oriented downwards
h14 = feval(mfilename,[3 3 .100001],[3 3 .1],30);
t6=text(3,3,3.6,'no line'); set(t6,'HorizontalAlignment','center');
% arrow with arrowheads at both ends
h15 = feval(mfilename,[-.5 -3 -3],[1 -3 -3],'Ends','both','FaceColor','g', ...
'Length',20,'Width',3,'CrossDir',[0 0 1],'TipAngle',25);
h=[h1;h2;h3;h4;h5;h6;h7;h8;h9;h10;h11;h12;h13;h14;h15];
function h = arrow_demo2(in)
axlim = in.axlim;
dolog = 1;
if (dolog), set(in.hs,'YData',10.^get(in.hs,'YData')); end;
shading('interp');
view(2);
title(['Demo of the capabilities of the ARROW function in 2-D']);
hold on; [C,H]=contour(in.x,in.y,in.z,20,'-'); hold off;
for k=H',
set(k,'ZData',(axlim(6)+1)*ones(size(get(k,'XData'))),'Color','k');
if (dolog), set(k,'YData',10.^get(k,'YData')); end;
end;
if (dolog), axis([axlim(1:2) 10.^axlim(3:4)]); set(gca,'YScale','log');
else, axis(axlim(1:4)); end;
% Normal blue arrow
start = [axlim(1) axlim(4) axlim(6)+2];
stop = [in.x(in.iii) in.y(in.iii) axlim(6)+2];
if (dolog), start(:,2)=10.^start(:,2); stop(:,2)=10.^stop(:,2); end;
h1 = feval(mfilename,start,stop,'EdgeColor','b','FaceColor','b');
% three arrows with varying fill, width, and baseangle
start = [-3 -3 10; -3 -1.5 10; -1.5 -3 10];
stop = [-.03 -.03 10; -.03 -1.5 10; -1.5 -.03 10];
if (dolog), start(:,2)=10.^start(:,2); stop(:,2)=10.^stop(:,2); end;
h2 = feval(mfilename,start,stop,24,[90;60;120],[],[0;0;4],'Ends',str2mat('both','stop','stop'));
set(h2(2),'EdgeColor',[0 .35 0],'FaceColor',[0 .85 .85]);
set(h2(3),'EdgeColor','r','FaceColor',[1 .5 1]);
h=[h1;h2];
function out = trueornan(x)
if isempty(x),
out=x;
else,
out = isnan(x);
out(~out) = x(~out);
end;
|
github
|
philippboehmsturm/antx-master
|
csp.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/csp.m
| 1,702 |
utf_8
|
3eb6c73192bc8163344c9b5e70a04877
|
function [W] = csp(C1, C2, m)
% CSP calculates the common spatial pattern (CSP) projection.
%
% Use as:
% [W] = csp(C1, C2, m)
%
% This function implements the intents of the CSP algorithm described in [1].
% Specifically, CSP finds m spatial projections that maximize the variance (or
% band power) in one condition (described by the [p x p] channel-covariance
% matrix C1), and simultaneously minimizes the variance in the other (C2):
%
% W C1 W' = D
%
% and
%
% W (C1 + C2) W' = I,
%
% Where D is a diagonal matrix with decreasing values on it's diagonal, and I
% is the identity matrix of matching shape.
% The resulting [m x p] matrix can be used to project a zero-centered [p x n]
% trial matrix X:
%
% S = W X.
%
%
% Although the CSP is the de facto standard method for feature extraction for
% motor imagery induced event-related desynchronization, it is not strictly
% necessary [2].
%
% [1] Zoltan J. Koles. The quantitative extraction and topographic mapping of
% the abnormal components in the clinical EEG. Electroencephalography and
% Clinical Neurophysiology, 79(6):440--447, December 1991.
%
% [2] Jason Farquhar. A linear feature space for simultaneous learning of
% spatio-spectral filters in BCI. Neural Networks, 22:1278--1285, 2009.
% Copyright (c) 2012, Boris Reuderink
P = whiten(C1 + C2, 1e-14); % decorrelate over conditions
[B, Lamb, B2] = svd(P * C1 * P'); % rotation to decorrelate within condition.
W = B' * P;
% keep m projections at ends
keep = circshift(1:size(W, 1) <= m, [0, -m/2]);
W = W(keep,:);
function P = whiten(C, rtol)
[U, l, U2] = svd(C);
l = diag(l);
keep = l > max(l) * rtol;
P = diag(l(keep).^(-.5)) * U(:,keep)';
|
github
|
philippboehmsturm/antx-master
|
read_besa_src.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/read_besa_src.m
| 2,719 |
utf_8
|
a2ac15bf2e94b068fdb5b6361310a7dd
|
function [src] = read_besa_src(filename);
% READ_BESA_SRC reads a beamformer source reconstruction from a BESA file
%
% Use as
% [src] = read_besa_src(filename)
%
% The output structure contains a minimal representation of the contents
% of the file.
% Copyright (C) 2005, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_besa_src.m 7123 2012-12-06 21:21:38Z roboos $
src = [];
fid = fopen(filename, 'rt');
% read the header information
line = fgetl(fid);
while isempty(strmatch('BESA_SA_IMAGE', line)), line = fgetl(fid); check_feof(fid, filename); end
% while isempty(strmatch('sd' , line)), line = fgetl(fid); check_feof(fid, filename); end % this line contains condition information
while isempty(strmatch('Grid dimen' , line)), line = fgetl(fid); check_feof(fid, filename); end
while isempty(strmatch('X:' , line)), line = fgetl(fid); check_feof(fid, filename); end; linex = line;
while isempty(strmatch('Y:' , line)), line = fgetl(fid); check_feof(fid, filename); end; liney = line;
while isempty(strmatch('Z:' , line)), line = fgetl(fid); check_feof(fid, filename); end; linez = line;
tok = tokenize(linex, ' ');
src.X = [str2num(tok{2}) str2num(tok{3}) str2num(tok{4})];
tok = tokenize(liney, ' ');
src.Y = [str2num(tok{2}) str2num(tok{3}) str2num(tok{4})];
tok = tokenize(linez, ' ');
src.Z = [str2num(tok{2}) str2num(tok{3}) str2num(tok{4})];
nx = src.X(3);
ny = src.Y(3);
nz = src.Z(3);
src.vol = zeros(nx, ny, nz);
for i=1:nz
% search up to the next slice
while isempty(strmatch(sprintf('Z: %d', i-1), line)), line = fgetl(fid); check_feof(fid, filename); end;
% read all the values for this slice
buf = fscanf(fid, '%f', [nx ny]);
src.vol(:,:,i) = buf;
end
fclose(fid);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function check_feof(fid, filename)
if feof(fid)
error(sprintf('could not read all information from file ''%s''', filename));
end
|
github
|
philippboehmsturm/antx-master
|
splint.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/splint.m
| 6,074 |
utf_8
|
ef61b12d46539bcc2f66afb96daba8f2
|
function [V2, L2, L1] = splint(elc1, V1, elc2)
% SPLINT computes the spherical spline interpolation and the surface laplacian
% of an EEG potential distribution
%
% Use as
% [V2, L2, L1] = splint(elc1, V1, elc2)
% where
% elc1 electrode positions where potential is known
% elc2 electrode positions where potential is not known
% V1 known potential
% and
% V2 potential at electrode locations in elc2
% L2 laplacian of potential at electrode locations in elc2
% L1 laplacian of potential at electrode locations in elc1
%
% See also LAPINT, LAPINTMAT, LAPCAL
% This implements
% F. Perrin, J. Pernier, O. Bertrand, and J. F. Echallier.
% Spherical splines for scalp potential and curernt density mapping.
% Electroencephalogr Clin Neurophysiol, 72:184-187, 1989.
% including their corrections in
% F. Perrin, J. Pernier, O. Bertrand, and J. F. Echallier.
% Corrigenda: EEG 02274, Electroencephalography and Clinical
% Neurophysiology 76:565.
% Copyright (C) 2003, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: splint.m 7123 2012-12-06 21:21:38Z roboos $
N = size(elc1,1); % number of known electrodes
M = size(elc2,1); % number of unknown electrodes
T = size(V1,2); % number of timepoints in the potential
Z = V1; % potential on known electrodes, can be matrix
% remember the actual size of the sphere
sphere1_scale = mean(sqrt(sum(elc1.^2,2)));
sphere2_scale = mean(sqrt(sum(elc2.^2,2)));
% scale all electrodes towards a unit sphere
elc1 = elc1 ./ repmat(sqrt(sum(elc1.^2,2)), 1, 3);
elc2 = elc2 ./ repmat(sqrt(sum(elc2.^2,2)), 1, 3);
% compute cosine of angle between all known electrodes
CosEii = zeros(N, N);
for i=1:N
for j=1:N
CosEii(i,j) = 1 - sum((elc1(i,:) - elc1(j,:)).^2)/2;
end
end
% compute matrix G of Perrin 1989
[gx, hx] = gh(CosEii);
G = gx;
% Note that the two simultaneous equations (2) of Perrin
% G*C + T*c0 = Z
% T'*C = 0
% with C = [c1 c2 c3 ...] can be rewritten into a single linear system
% H * [c0 c1 c2 ... cN]' = [0 z1 z2 ... zN]'
% with
% H = [ 0 1 1 1 1 1 1 . ]
% [ 1 g11 g12 . . . . . ]
% [ 1 g21 g22 . . . . . ]
% [ 1 g31 g32 . . . . . ]
% [ 1 g41 g42 . . . . . ]
% [ . . . . . . . . ]
% that subsequently can be solved using a singular value decomposition
% or another linear solver
% rewrite the linear system according to the comment above and solve it for C
% different from Perrin, this solution for C includes the c0 term
H = ones(N+1,N+1); H(1,1) = 0; H(2:end,2:end) = G;
% C = pinv(H)*[zeros(1,T); Z]; % solve with SVD
C = H \ [zeros(1,T); Z]; % solve by Gaussian elimination
% compute surface laplacian on all known electrodes by matrix multiplication
L1 = hx * C(2:end, :);
% undo the initial scaling of the sphere to get back to real units for the laplacian
L1 = L1 / (sphere1_scale^2);
if all(size(elc1)==size(elc2)) & all(elc1(:)==elc2(:))
warning('using shortcut for splint');
% do not recompute gx and hx
else
% compute cosine of angle between all known and unknown electrodes
CosEji = zeros(M, N);
for j=1:M
for i=1:N
CosEji(j,i) = 1 - sum((elc2(j,:) - elc1(i,:)).^2)/2;
end
end
[gx, hx] = gh(CosEji);
end
% compute interpolated potential on all unknown electrodes by matrix multiplication
V2 = [ones(M,1) gx] * C;
% compute surface laplacian on all unknown electrodes by matrix multiplication
L2 = hx * C(2:end, :);
% undo the initial scaling of the sphere to get back to real units for the laplacian
L2 = L2 / (sphere2_scale^2);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% this subfunction implements equations (3) and (5b) of Perrin 1989
% for simultaneous computation of multiple values
% also implemented as MEX file, but without the adaptive N
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [gx, hx] = gh(x)
M = 4; % constant in denominator
% N is the number of terms for series expansion
% N=9 works fine for 32 electrodes, but for 128 electrodes it should be larger
if max(size(x))<=32
N = 9;
elseif max(size(x))<=64
N = 14;
elseif max(size(x))<=128
N = 20;
else
N = 32;
end
p = zeros(1,N);
gx = zeros(size(x));
hx = zeros(size(x));
x(find(x>1)) = 1; % to avoid rounding off errors
x(find(x<-1)) = -1; % to avoid rounding off errors
% using Matlab function to compute legendre polynomials
% P = zeros(size(x,1), size(x,2), N);
% for k=1:N
% tmp = legendre(k,x);
% P(:,:,k) = squeeze(tmp(1,:,:));
% end
if (size(x,1)==size(x,2)) & all(all(x==x'))
issymmetric = 1;
else
issymmetric = 0;
end
for i=1:size(x,1)
if issymmetric
jloop = i:size(x,2);
else
jloop = 1:size(x,2);
end
for j=jloop
% using faster "Numerical Recipies in C" plgndr function (mex file)
for k=1:N
p(k) = plgndr(k,0,x(i,j));
end
% p = squeeze(P(i, j ,:))';
gx(i,j) = sum((2*(1:N)+1) ./ ((1:N).*((1:N)+1)).^M .* p) / (4*pi);
hx(i,j) = -sum((2*(1:N)+1) ./ ((1:N).*((1:N)+1)).^(M-1) .* p) / (4*pi);
if issymmetric
gx(j,i) = gx(i,j);
hx(j,i) = hx(i,j);
end
% fprintf('computing laplacian %f%% done\n', 100*(((i-1)*size(x,2)+j) / prod(size(x))));
end
end
|
github
|
philippboehmsturm/antx-master
|
find_nearest.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/find_nearest.m
| 6,055 |
utf_8
|
a825f646f8070b85d3838ae337adee3d
|
function [nearest, distance] = find_nearest(pnt1, pnt2, npart, gridflag)
% FIND_NEAREST finds the nearest vertex in a cloud of points and
% does this efficiently for many target vertices at once (by means
% of partitioning).
%
% Use as
% [nearest, distance] = find_nearest(pnt1, pnt2, npart)
% Copyright (C) 2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: find_nearest.m 7123 2012-12-06 21:21:38Z roboos $
% this can be used for printing detailled user feedback
fb = false;
if nargin<4
gridflag = 0;
end
npnt1 = size(pnt1,1);
npnt2 = size(pnt2,1);
if ~gridflag
% check whether pnt2 is gridded
if all(pnt2(1,:)==1)
% it might be gridded, test in more detail
dim = max(pnt2, [], 1);
[X, Y, Z] = ndgrid(1:dim(1), 1:dim(2), 1:dim(3));
gridflag = all(pnt2(:)==[X(:);Y(:);Z(:)]);
end
end
if gridflag
% it is gridded, that can be treated much faster
if fb, fprintf('pnt2 is gridded\n'); end
sub = round(pnt1);
sub(sub(:)<1) = 1;
sub(sub(:,1)>dim(1),1) = dim(1);
sub(sub(:,2)>dim(2),2) = dim(2);
sub(sub(:,3)>dim(3),3) = dim(3);
ind = sub2ind(dim, sub(:,1), sub(:,2), sub(:,3));
nearest = ind(:);
distance = sqrt(sum((pnt1-pnt2(ind,:)).^2, 2));
return
end
if npart<1
npart = 1;
end
nearest = ones(size(pnt1,1),1) * -1;
distance = ones(size(pnt1,1),1) * inf;
sel = find(nearest<0);
while ~isempty(sel)
if fb, fprintf('nsel = %d, npart = %d\n', length(sel), npart); end
[pnear, pdist] = find_nearest_partition(pnt1(sel,:), pnt2, npart);
better = pdist<=distance(sel);
nearest(sel(better)) = pnear(better);
distance(sel(better)) = distance(better);
sel = find(nearest<0);
npart = floor(npart/2);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [nearest, distance] = find_nearest_partition(pnt1, pnt2, npart)
% this can be used for printing detailled user feedback
fb = false;
if isempty(fb)
fb = 0;
end
npnt1 = size(pnt1,1);
npnt2 = size(pnt2,1);
% this will contain the output
nearest = zeros(npnt1, 1);
distance = zeros(npnt1, 1);
if npnt1==0
return
end
minpnt1 = min(pnt1,1);
minpnt2 = min(pnt2,1);
maxpnt1 = max(pnt1,1);
maxpnt2 = max(pnt2,1);
pmin = min([minpnt1; minpnt2]) - eps;
pmax = max([maxpnt1; maxpnt2]) + eps;
dx = (pmax(1)-pmin(1))/npart;
dy = (pmax(2)-pmin(2))/npart;
dz = (pmax(3)-pmin(3))/npart;
% determine the lower boundaries of each partition along the x, y, and z-axis
limx = pmin(1) + (0:(npart-1)) * dx;
limy = pmin(2) + (0:(npart-1)) * dy;
limz = pmin(3) + (0:(npart-1)) * dz;
% determine the lower boundaries of each of the N^3 partitions
[X, Y, Z] = ndgrid(limx, limy, limz);
partlim = [X(:) Y(:) Z(:)];
% determine for each vertex to which partition it belongs
binx = ceil((pnt1(:,1)- pmin(1))/dx);
biny = ceil((pnt1(:,2)- pmin(2))/dy);
binz = ceil((pnt1(:,3)- pmin(3))/dz);
ind1 = (binx-1)*npart^0 + (biny-1)*npart^1 +(binz-1)*npart^2 + 1;
binx = ceil((pnt2(:,1)- pmin(1))/dx);
biny = ceil((pnt2(:,2)- pmin(2))/dy);
binz = ceil((pnt2(:,3)- pmin(3))/dz);
ind2 = (binx-1)*npart^0 + (biny-1)*npart^1 +(binz-1)*npart^2 + 1;
% use the brute force approach within each partition
for p=1:(npart^3)
sel1 = (ind1==p);
sel2 = (ind2==p);
nsel1 = sum(sel1);
nsel2 = sum(sel2);
if nsel1==0 || nsel2==0
continue
end
pnt1s = pnt1(sel1, :);
pnt2s = pnt2(sel2, :);
[pnear, pdist] = find_nearest_brute_force(pnt1s, pnt2s);
% determine the points that are sufficiently far from the partition edge
seln = true(nsel1, 1);
if npart>1
if partlim(p,1)>pmin(1), seln = seln & (pdist < (pnt1s(:,1) - partlim(p,1))); end
if partlim(p,1)>pmin(2), seln = seln & (pdist < (pnt1s(:,2) - partlim(p,2))); end
if partlim(p,1)>pmin(3), seln = seln & (pdist < (pnt1s(:,3) - partlim(p,3))); end
if partlim(p,1)<pmin(1), seln = seln & (pdist < (partlim(p,1)) + dx - pnt1s(:,1)); end
if partlim(p,2)<pmin(2), seln = seln & (pdist < (partlim(p,2)) + dx - pnt1s(:,2)); end
if partlim(p,3)<pmin(3), seln = seln & (pdist < (partlim(p,3)) + dx - pnt1s(:,3)); end
end
% the results have to be re-indexed
dum1 = find(sel1);
dum2 = find(sel2);
nearest(dum1( seln)) = dum2(pnear( seln));
nearest(dum1(~seln)) = -dum2(pnear(~seln)); % negative means that it is not certain
distance(dum1) = pdist;
end
% handle the points that ly in empty target partitions
sel = (nearest==0);
if any(sel)
if fb, fprintf('%d points in empty target partition\n', sum(sel)); end
pnt1s = pnt1(sel, :);
[pnear, pdist] = find_nearest_brute_force(pnt1s, pnt2);
nearest(sel) = pnear;
distance(sel) = pdist;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [nearest, distance] = find_nearest_brute_force(pnt1, pnt2)
% implementation 1 -- brute force
npnt1 = size(pnt1,1);
npnt2 = size(pnt2,1);
nearest = zeros(npnt1, 1);
distance = zeros(npnt1, 1);
if npnt1==0 || npnt2==0
return
end
for i=1:npnt1
% compute squared distance
tmp = (pnt2(:,1) - pnt1(i,1)).^2 + (pnt2(:,2) - pnt1(i,2)).^2 + (pnt2(:,3) - pnt1(i,3)).^2;
[distance(i), nearest(i)] = min(tmp);
end
distance = sqrt(distance);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function plotpnt(pnt, varargin)
x = pnt(:,1);
y = pnt(:,2);
z = pnt(:,3);
plot3(x, y, z, varargin{:});
|
github
|
philippboehmsturm/antx-master
|
read_besa_avr.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/read_besa_avr.m
| 3,929 |
utf_8
|
91f2ee59d1af564811511e0e7f201ba4
|
function [avr] = read_besa_avr(filename)
% READ_BESA_AVR reads average EEG data in BESA format
%
% Use as
% [avr] = read_besa_avr(filename)
%
% This will return a structure with the header information in
% avr.npnt
% avr.tsb
% avr.di
% avr.sb
% avr.sc
% avr.Nchan (optional)
% avr.label (optional)
% and the ERP data is contained in the Nchan X Nsamples matrix
% avr.data
% Copyright (C) 2003-2006, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_besa_avr.m 7123 2012-12-06 21:21:38Z roboos $
fid = fopen(filename, 'rt');
% the first line contains header information
headstr = fgetl(fid);
ok = 0;
if ~ok
try
buf = sscanf(headstr, 'Npts= %d TSB= %f DI= %f SB= %f SC= %f Nchan= %f SegmentName= %s\n');
avr.npnt = buf(1);
avr.tsb = buf(2);
avr.di = buf(3);
avr.sb = buf(4);
avr.sc = buf(5);
avr.Nchan = buf(6);
avr.SegmentName = buf(7);
ok = 1;
catch
ok = 0;
end
end
if ~ok
try
buf = fscanf(headstr, 'Npts= %d TSB= %f DI= %f SB= %f SC= %f Nchan= %f\n');
avr.npnt = buf(1);
avr.tsb = buf(2);
avr.di = buf(3);
avr.sb = buf(4);
avr.sc = buf(5);
avr.Nchan = buf(6);
ok = 1;
catch
ok = 0;
end
end
if ~ok
try
buf = sscanf(headstr, 'Npts= %d TSB= %f DI= %f SB= %f SC= %f\n');
avr.npnt = buf(1);
avr.tsb = buf(2);
avr.di = buf(3);
avr.sb = buf(4);
avr.sc = buf(5);
ok = 1;
catch
ok = 0;
end
end
if ~ok
error('Could not interpret the header information.');
end
% rewind to the beginning of the file, skip the header line
fseek(fid, 0, 'bof');
fgetl(fid);
% the second line may contain channel names
chanstr = fgetl(fid);
chanstr = deblank(fliplr(deblank(fliplr(chanstr))));
if (chanstr(1)>='A' && chanstr(1)<='Z') || (chanstr(1)>='a' && chanstr(1)<='z')
haschan = 1;
avr.label = str2cell(strrep(deblank(chanstr), '''', ''))';
else
[root, name] = fileparts(filename);
haschan = 0;
elpfile = fullfile(root, [name '.elp']);
elafile = fullfile(root, [name '.ela']);
if exist(elpfile, 'file')
% read the channel names from the accompanying ELP file
lbl = importdata(elpfile);
avr.label = strrep(lbl.textdata(:,2) ,'''', '');
elseif exist(elafile, 'file')
% read the channel names from the accompanying ELA file
lbl = importdata(elafile);
lbl = strrep(lbl ,'MEG ', ''); % remove the channel type
lbl = strrep(lbl ,'EEG ', ''); % remove the channel type
avr.label = lbl;
else
warning('Could not create channels labels.');
end
end
% seek to the beginning of the data
fseek(fid, 0, 'bof');
fgetl(fid); % skip the header line
if haschan
fgetl(fid); % skip the channel name line
end
buf = fscanf(fid, '%f');
nchan = length(buf)/avr.npnt;
avr.data = reshape(buf, avr.npnt, nchan)';
fclose(fid);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION to cut a string into pieces at the spaces
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function c = str2cell(s)
c = {};
[t, r] = strtok(s, ' ');
while ~isempty(t)
c{end+1} = t;
[t, r] = strtok(r, ' ');
end
|
github
|
philippboehmsturm/antx-master
|
sftrans.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/sftrans.m
| 7,947 |
utf_8
|
f64cb2e7d19bcdc6232b39d8a6d70e7c
|
% Copyright (C) 1999 Paul Kienzle
%
% This program 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 2 of the License, or
% (at your option) any later version.
%
% This program 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 this program; If not, see <http://www.gnu.org/licenses/>.
% usage: [Sz, Sp, Sg] = sftrans(Sz, Sp, Sg, W, stop)
%
% Transform band edges of a generic lowpass filter (cutoff at W=1)
% represented in splane zero-pole-gain form. W is the edge of the
% target filter (or edges if band pass or band stop). Stop is true for
% high pass and band stop filters or false for low pass and band pass
% filters. Filter edges are specified in radians, from 0 to pi (the
% nyquist frequency).
%
% Theory: Given a low pass filter represented by poles and zeros in the
% splane, you can convert it to a low pass, high pass, band pass or
% band stop by transforming each of the poles and zeros individually.
% The following table summarizes the transformation:
%
% Transform Zero at x Pole at x
% ---------------- ------------------------- ------------------------
% Low Pass zero: Fc x/C pole: Fc x/C
% S -> C S/Fc gain: C/Fc gain: Fc/C
% ---------------- ------------------------- ------------------------
% High Pass zero: Fc C/x pole: Fc C/x
% S -> C Fc/S pole: 0 zero: 0
% gain: -x gain: -1/x
% ---------------- ------------------------- ------------------------
% Band Pass zero: b ? sqrt(b^2-FhFl) pole: b ? sqrt(b^2-FhFl)
% S^2+FhFl pole: 0 zero: 0
% S -> C -------- gain: C/(Fh-Fl) gain: (Fh-Fl)/C
% S(Fh-Fl) b=x/C (Fh-Fl)/2 b=x/C (Fh-Fl)/2
% ---------------- ------------------------- ------------------------
% Band Stop zero: b ? sqrt(b^2-FhFl) pole: b ? sqrt(b^2-FhFl)
% S(Fh-Fl) pole: ?sqrt(-FhFl) zero: ?sqrt(-FhFl)
% S -> C -------- gain: -x gain: -1/x
% S^2+FhFl b=C/x (Fh-Fl)/2 b=C/x (Fh-Fl)/2
% ---------------- ------------------------- ------------------------
% Bilinear zero: (2+xT)/(2-xT) pole: (2+xT)/(2-xT)
% 2 z-1 pole: -1 zero: -1
% S -> - --- gain: (2-xT)/T gain: (2-xT)/T
% T z+1
% ---------------- ------------------------- ------------------------
%
% where C is the cutoff frequency of the initial lowpass filter, Fc is
% the edge of the target low/high pass filter and [Fl,Fh] are the edges
% of the target band pass/stop filter. With abundant tedious algebra,
% you can derive the above formulae yourself by substituting the
% transform for S into H(S)=S-x for a zero at x or H(S)=1/(S-x) for a
% pole at x, and converting the result into the form:
%
% H(S)=g prod(S-Xi)/prod(S-Xj)
%
% The transforms are from the references. The actual pole-zero-gain
% changes I derived myself.
%
% Please note that a pole and a zero at the same place exactly cancel.
% This is significant for High Pass, Band Pass and Band Stop filters
% which create numerous extra poles and zeros, most of which cancel.
% Those which do not cancel have a 'fill-in' effect, extending the
% shorter of the sets to have the same number of as the longer of the
% sets of poles and zeros (or at least split the difference in the case
% of the band pass filter). There may be other opportunistic
% cancellations but I will not check for them.
%
% Also note that any pole on the unit circle or beyond will result in
% an unstable filter. Because of cancellation, this will only happen
% if the number of poles is smaller than the number of zeros and the
% filter is high pass or band pass. The analytic design methods all
% yield more poles than zeros, so this will not be a problem.
%
% References:
%
% Proakis & Manolakis (1992). Digital Signal Processing. New York:
% Macmillan Publishing Company.
% Author: Paul Kienzle <[email protected]>
% 2000-03-01 [email protected]
% leave transformed Sg as a complex value since cheby2 blows up
% otherwise (but only for odd-order low-pass filters). bilinear
% will return Zg as real, so there is no visible change to the
% user of the IIR filter design functions.
% 2001-03-09 [email protected]
% return real Sg; don't know what to do for imaginary filters
function [Sz, Sp, Sg] = sftrans(Sz, Sp, Sg, W, stop)
if (nargin ~= 5)
usage('[Sz, Sp, Sg] = sftrans(Sz, Sp, Sg, W, stop)');
end;
C = 1;
p = length(Sp);
z = length(Sz);
if z > p || p == 0
error('sftrans: must have at least as many poles as zeros in s-plane');
end
if length(W)==2
Fl = W(1);
Fh = W(2);
if stop
% ---------------- ------------------------- ------------------------
% Band Stop zero: b ? sqrt(b^2-FhFl) pole: b ? sqrt(b^2-FhFl)
% S(Fh-Fl) pole: ?sqrt(-FhFl) zero: ?sqrt(-FhFl)
% S -> C -------- gain: -x gain: -1/x
% S^2+FhFl b=C/x (Fh-Fl)/2 b=C/x (Fh-Fl)/2
% ---------------- ------------------------- ------------------------
if (isempty(Sz))
Sg = Sg * real (1./ prod(-Sp));
elseif (isempty(Sp))
Sg = Sg * real(prod(-Sz));
else
Sg = Sg * real(prod(-Sz)/prod(-Sp));
end
b = (C*(Fh-Fl)/2)./Sp;
Sp = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)];
extend = [sqrt(-Fh*Fl), -sqrt(-Fh*Fl)];
if isempty(Sz)
Sz = [extend(1+rem([1:2*p],2))];
else
b = (C*(Fh-Fl)/2)./Sz;
Sz = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)];
if (p > z)
Sz = [Sz, extend(1+rem([1:2*(p-z)],2))];
end
end
else
% ---------------- ------------------------- ------------------------
% Band Pass zero: b ? sqrt(b^2-FhFl) pole: b ? sqrt(b^2-FhFl)
% S^2+FhFl pole: 0 zero: 0
% S -> C -------- gain: C/(Fh-Fl) gain: (Fh-Fl)/C
% S(Fh-Fl) b=x/C (Fh-Fl)/2 b=x/C (Fh-Fl)/2
% ---------------- ------------------------- ------------------------
Sg = Sg * (C/(Fh-Fl))^(z-p);
b = Sp*((Fh-Fl)/(2*C));
Sp = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)];
if isempty(Sz)
Sz = zeros(1,p);
else
b = Sz*((Fh-Fl)/(2*C));
Sz = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)];
if (p>z)
Sz = [Sz, zeros(1, (p-z))];
end
end
end
else
Fc = W;
if stop
% ---------------- ------------------------- ------------------------
% High Pass zero: Fc C/x pole: Fc C/x
% S -> C Fc/S pole: 0 zero: 0
% gain: -x gain: -1/x
% ---------------- ------------------------- ------------------------
if (isempty(Sz))
Sg = Sg * real (1./ prod(-Sp));
elseif (isempty(Sp))
Sg = Sg * real(prod(-Sz));
else
Sg = Sg * real(prod(-Sz)/prod(-Sp));
end
Sp = C * Fc ./ Sp;
if isempty(Sz)
Sz = zeros(1,p);
else
Sz = [C * Fc ./ Sz];
if (p > z)
Sz = [Sz, zeros(1,p-z)];
end
end
else
% ---------------- ------------------------- ------------------------
% Low Pass zero: Fc x/C pole: Fc x/C
% S -> C S/Fc gain: C/Fc gain: Fc/C
% ---------------- ------------------------- ------------------------
Sg = Sg * (C/Fc)^(z-p);
Sp = Fc * Sp / C;
Sz = Fc * Sz / C;
end
end
|
github
|
philippboehmsturm/antx-master
|
filtfilt.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/filtfilt.m
| 3,297 |
iso_8859_1
|
d01a26a827bc3379f05bbc57f46ac0a9
|
% Copyright (C) 1999 Paul Kienzle
% Copyright (C) 2007 Francesco Potortì
% Copyright (C) 2008 Luca Citi
%
% This program 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 2 of the License, or
% (at your option) any later version.
%
% This program 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 this program; If not, see <http://www.gnu.org/licenses/>.
% usage: y = filtfilt(b, a, x)
%
% Forward and reverse filter the signal. This corrects for phase
% distortion introduced by a one-pass filter, though it does square the
% magnitude response in the process. That's the theory at least. In
% practice the phase correction is not perfect, and magnitude response
% is distorted, particularly in the stop band.
%%
% Example
% [b, a]=butter(3, 0.1); % 10 Hz low-pass filter
% t = 0:0.01:1.0; % 1 second sample
% x=sin(2*pi*t*2.3)+0.25*randn(size(t)); % 2.3 Hz sinusoid+noise
% y = filtfilt(b,a,x); z = filter(b,a,x); % apply filter
% plot(t,x,';data;',t,y,';filtfilt;',t,z,';filter;')
% Changelog:
% 2000 02 [email protected]
% - pad with zeros to load up the state vector on filter reverse.
% - add example
% 2007 12 [email protected]
% - use filtic to compute initial and final states
% - work for multiple columns as well
% 2008 12 [email protected]
% - fixed instability issues with IIR filters and noisy inputs
% - initial states computed according to Likhterov & Kopeika, 2003
% - use of a "reflection method" to reduce end effects
% - added some basic tests
% TODO: (pkienzle) My version seems to have similar quality to matlab,
% but both are pretty bad. They do remove gross lag errors, though.
function y = filtfilt(b, a, x)
if (nargin ~= 3)
usage('y=filtfilt(b,a,x)');
end
rotate = (size(x, 1)==1);
if rotate % a row vector
x = x(:); % make it a column vector
end
lx = size(x,1);
a = a(:).';
b = b(:).';
lb = length(b);
la = length(a);
n = max(lb, la);
lrefl = 3 * (n - 1);
if la < n, a(n) = 0; end
if lb < n, b(n) = 0; end
% Compute a the initial state taking inspiration from
% Likhterov & Kopeika, 2003. "Hardware-efficient technique for
% minimizing startup transients in Direct Form II digital filters"
kdc = sum(b) / sum(a);
if (abs(kdc) < inf) % neither NaN nor +/- Inf
si = fliplr(cumsum(fliplr(b - kdc * a)));
else
si = zeros(size(a)); % fall back to zero initialization
end
si(1) = [];
y = zeros(size(x));
for c = 1:size(x, 2) % filter all columns, one by one
v = [2*x(1,c)-x((lrefl+1):-1:2,c); x(:,c);
2*x(end,c)-x((end-1):-1:end-lrefl,c)]; % a column vector
% Do forward and reverse filtering
v = filter(b,a,v,si*v(1)); % forward filter
v = flipud(filter(b,a,flipud(v),si*v(end))); % reverse filter
y(:,c) = v((lrefl+1):(lx+lrefl));
end
if (rotate) % x was a row vector
y = rot90(y); % rotate it back
end
|
github
|
philippboehmsturm/antx-master
|
nanstd.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/nanstd.m
| 231 |
utf_8
|
0ff62b1c345b5ad76a9af59cf07c2983
|
% NANSTD provides a replacement for MATLAB's nanstd that is almost
% compatible.
%
% For usage see STD. Note that the three-argument call with FLAG is not
% supported.
function Y = nanstd(varargin)
Y = sqrt(nanvar(varargin{:}));
|
github
|
philippboehmsturm/antx-master
|
avw_img_write.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/avw_img_write.m
| 29,939 |
utf_8
|
f83bd0814830119805ffef580d768cdc
|
function avw_img_write(avw, fileprefix, IMGorient, machine, verbose)
% avw_img_write - write Analyze image files (*.img)
%
% avw_img_write(avw,fileprefix,[IMGorient],[machine],[verbose])
%
% avw.img - a 3D matrix of image data (double precision).
% avw.hdr - a struct with image data parameters. If
% not empty, this function calls avw_hdr_write.
%
% fileprefix - a string, the filename without the .img
% extension. If empty, may use avw.fileprefix
%
% IMGorient - optional int, force writing of specified
% orientation, with values:
%
% [], if empty, will use avw.hdr.hist.orient field
% 0, transverse/axial unflipped (default, radiological)
% 1, coronal unflipped
% 2, sagittal unflipped
% 3, transverse/axial flipped, left to right
% 4, coronal flipped, anterior to posterior
% 5, sagittal flipped, superior to inferior
%
% This function will set avw.hdr.hist.orient and write the
% image data in a corresponding order. This function is
% in alpha development, so it has not been exhaustively
% tested (07/2003). See avw_img_read for more information
% and documentation on the orientation option.
% Orientations 3-5 are NOT recommended! They are part
% of the Analyze format, but only used in Analyze
% for faster raster graphics during movies.
%
% machine - a string, see machineformat in fread for details.
% The default here is 'ieee-le'.
%
% verbose - the default is to output processing information to the command
% window. If verbose = 0, this will not happen.
%
% Tip: to change the data type, set avw.hdr.dime.datatype to:
%
% 1 Binary ( 1 bit per voxel)
% 2 Unsigned character ( 8 bits per voxel)
% 4 Signed short ( 16 bits per voxel)
% 8 Signed integer ( 32 bits per voxel)
% 16 Floating point ( 32 bits per voxel)
% 32 Complex, 2 floats ( 64 bits per voxel), not supported
% 64 Double precision ( 64 bits per voxel)
% 128 Red-Green-Blue (128 bits per voxel), not supported
%
% See also: avw_write, avw_hdr_write,
% avw_read, avw_hdr_read, avw_img_read, avw_view
%
% $Revision: 7123 $ $Date: 2009/01/14 09:24:45 $
% Licence: GNU GPL, no express or implied warranties
% History: 05/2002, [email protected]
% The Analyze format is copyright
% (c) Copyright, 1986-1995
% Biomedical Imaging Resource, Mayo Foundation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%------------------------------------------------------------------------
% Check inputs
if ~exist('avw','var'),
doc avw_img_write;
error('...no input avw.');
elseif isempty(avw),
error('...empty input avw.');
elseif ~isfield(avw,'img'),
error('...empty input avw.img');
end
if ~exist('fileprefix','var'),
if isfield(avw,'fileprefix'),
if ~isempty(avw.fileprefix),
fileprefix = avw.fileprefix;
else
fileprefix = [];
end
else
fileprefix = [];
end
end
if isempty(fileprefix),
[fileprefix, pathname, filterindex] = uiputfile('*.hdr','Specify an output Analyze .hdr file');
if pathname, cd(pathname); end
if ~fileprefix,
doc avw_img_write;
error('no output .hdr file specified');
end
end
if findstr('.hdr',fileprefix),
% fprintf('AVW_IMG_WRITE: Removing .hdr extension from ''%s''\n',fileprefix);
fileprefix = strrep(fileprefix,'.hdr','');
end
if findstr('.img',fileprefix),
% fprintf('AVW_IMG_WRITE: Removing .img extension from ''%s''\n',fileprefix);
fileprefix = strrep(fileprefix,'.img','');
end
if ~exist('IMGorient','var'), IMGorient = ''; end
if ~exist('machine','var'), machine = 'ieee-le'; end
if ~exist('verbose','var'), verbose = 1; end
if isempty(IMGorient), IMGorient = ''; end
if isempty(machine), machine = 'ieee-le'; end
if isempty(verbose), verbose = 1; end
%------------------------------------------------------------------------
% MAIN
if verbose,
version = '[$Revision: 7123 $]';
fprintf('\nAVW_IMG_WRITE [v%s]\n',version(12:16)); tic;
end
fid = fopen(sprintf('%s.img',fileprefix),'w',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.img\n',fileprefix);
error(msg);
else
avw = write_image(fid,avw,fileprefix,IMGorient,machine,verbose);
end
if verbose,
t=toc; fprintf('...done (%5.2f sec).\n\n',t);
end
% MUST write header after the image, to ensure any
% orientation changes during image write are saved
% in the header
avw_hdr_write(avw,fileprefix,machine,verbose);
return
function avw_hdr_write(avw, fileprefix, machine, verbose)
% AVW_HDR_WRITE - Write Analyze header file (*.hdr)
%
% avw_hdr_write(avw,[fileprefix],[machine],[verbose])
%
% eg, avw_hdr_write(avw,'test');
%
% avw - a struct with .hdr field, which itself is a struct,
% containing all fields of an Analyze header.
% For details, see avw_hdr_read.m
%
% fileprefix - a string, the filename without the .hdr extension.
% If empty, may use avw.fileprefix
%
% machine - a string, see machineformat in fread for details.
% The default here is 'ieee-le'.
%
% verbose - the default is to output processing information to the command
% window. If verbose = 0, this will not happen.
%
% See also, AVW_HDR_READ AVW_HDR_MAKE
% AVW_IMG_READ AVW_IMG_WRITE
%
% $Revision: 7123 $ $Date: 2009/01/14 09:24:45 $
% Licence: GNU GPL, no express or implied warranties
% History: 05/2002, [email protected]
% 02/2003, [email protected]
% - more specific data history var sizes
% - 02/2003 confirmed, Darren
%
% The Analyze format and c code below is copyright
% (c) Copyright, 1986-1995
% Biomedical Imaging Resource, Mayo Foundation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if ~exist('verbose','var'), verbose = 1; end
if ~exist('machine','var'), machine = 'ieee-le'; end
if verbose,
version = '[$Revision: 7123 $]';
fprintf('AVW_HDR_WRITE [v%s]\n',version(12:16)); tic;
end
%----------------------------------------------------------------------------
% Check inputs
if ~exist('avw','var'),
warning('...no input avw - calling avw_hdr_make\n');
avw = avw_hdr_make;
elseif isempty(avw),
warning('...empty input avw - calling avw_hdr_make\n');
avw = avw_hdr_make;
elseif ~isfield(avw,'hdr'),
warning('...empty input avw.hdr - calling avw_hdr_make\n');
avw = avw_hdr_make;
end
if ~isequal(avw.hdr.hk.sizeof_hdr,348),
msg = sprintf('...avw.hdr.hk.sizeof_hdr must be 348!\n');
error(msg);
end
quit = 0;
if ~exist('fileprefix','var'),
if isfield(avw,'fileprefix'),
if ~isempty(avw.fileprefix),
fileprefix = avw.fileprefix;
else,
quit = 1;
end
else
quit = 1;
end
if quit,
helpwin avw_hdr_write;
error('...no input fileprefix - see help avw_hdr_write\n\n');
return;
end
end
if findstr('.hdr',fileprefix),
% fprintf('AVW_HDR_WRITE: Removing .hdr extension from ''%s''\n',fileprefix);
fileprefix = strrep(fileprefix,'.hdr','');
end
%----------------------------------------------------------------------------
% MAIN
if verbose, tic; end
% % force volume to 4D if necessary; conforms to AVW standard. i lifted this
% % code from mri_toolbox/avw_hdr_read.m and modified it just a little bit
% % (using minDim = 4; etc)
% minDim = 4;
% currDim = double(avw.hdr.dime.dim(1));
% if ( currDim < minDim )
% % fprintf( 'Warning %s: Forcing %d dimensions in avw.hdr.dime.dim\n', ...
% % mfilename, minDim );
% avw.hdr.dime.dim(1) = int16(minDim);
% avw.hdr.dime.dim(currDim+2:minDim+1) = int16(1);
% avw.hdr.dime.pixdim(1) = int16(minDim);
% avw.hdr.dime.pixdim(currDim+2:minDim+1) = int16(1);
% end;
fid = fopen(sprintf('%s.hdr',fileprefix),'w',machine);
if fid < 0,
msg = sprintf('Cannot write to file %s.hdr\n',fileprefix);
error(msg);
else
if verbose, fprintf('...writing %s Analyze header.\n',machine); end
write_header(fid,avw,verbose);
end
if verbose, t=toc; fprintf('...done (%5.2f sec).\n\n',t); end
return
%-----------------------------------------------------------------------------------
function avw = write_image(fid,avw,fileprefix,IMGorient,machine,verbose)
% short int bitpix; /* Number of bits per pixel; 1, 8, 16, 32, or 64. */
% short int datatype /* Datatype for this image set */
% /*Acceptable values for datatype are*/
% #define DT_NONE 0
% #define DT_UNKNOWN 0 /*Unknown data type*/
% #define DT_BINARY 1 /*Binary ( 1 bit per voxel)*/
% #define DT_UNSIGNED_CHAR 2 /*Unsigned character ( 8 bits per voxel)*/
% #define DT_SIGNED_SHORT 4 /*Signed short (16 bits per voxel)*/
% #define DT_SIGNED_INT 8 /*Signed integer (32 bits per voxel)*/
% #define DT_FLOAT 16 /*Floating point (32 bits per voxel)*/
% #define DT_COMPLEX 32 /*Complex,2 floats (64 bits per voxel)/*
% #define DT_DOUBLE 64 /*Double precision (64 bits per voxel)*/
% #define DT_RGB 128 /*A Red-Green-Blue datatype*/
% #define DT_ALL 255 /*Undocumented*/
switch double(avw.hdr.dime.datatype),
case 1,
avw.hdr.dime.bitpix = int16( 1); precision = 'bit1';
case 2,
avw.hdr.dime.bitpix = int16( 8); precision = 'uchar';
case 4,
avw.hdr.dime.bitpix = int16(16); precision = 'int16';
case 8,
avw.hdr.dime.bitpix = int16(32); precision = 'int32';
case 16,
avw.hdr.dime.bitpix = int16(32); precision = 'single';
case 32,
error('...complex datatype not yet supported.\n');
case 64,
avw.hdr.dime.bitpix = int16(64); precision = 'double';
case 128,
error('...RGB datatype not yet supported.\n');
otherwise
warning('...unknown datatype, using type 16 (32 bit floats).\n');
avw.hdr.dime.datatype = int16(16);
avw.hdr.dime.bitpix = int16(32); precision = 'single';
end
% write the .img file, depending on the .img orientation
if verbose,
fprintf('...writing %s precision Analyze image (%s).\n',precision,machine);
end
fseek(fid,0,'bof');
% The standard image orientation is axial unflipped
if isempty(avw.hdr.hist.orient),
msg = [ '...avw.hdr.hist.orient ~= 0.\n',...
' This function assumes the input avw.img is\n',...
' in axial unflipped orientation in memory. This is\n',...
' created by the avw_img_read function, which converts\n',...
' any input file image to axial unflipped in memory.\n'];
warning(msg)
end
if isempty(IMGorient),
if verbose,
fprintf('...no IMGorient specified, using avw.hdr.hist.orient value.\n');
end
IMGorient = double(avw.hdr.hist.orient);
end
if ~isfinite(IMGorient),
if verbose,
fprintf('...IMGorient is not finite!\n');
end
IMGorient = 99;
end
switch IMGorient,
case 0, % transverse/axial unflipped
% For the 'transverse unflipped' type, the voxels are stored with
% Pixels in 'x' axis (varies fastest) - from patient right to left
% Rows in 'y' axis - from patient posterior to anterior
% Slices in 'z' axis - from patient inferior to superior
if verbose, fprintf('...writing axial unflipped\n'); end
avw.hdr.hist.orient = uint8(0);
SliceDim = double(avw.hdr.dime.dim(4)); % z
RowDim = double(avw.hdr.dime.dim(3)); % y
PixelDim = double(avw.hdr.dime.dim(2)); % x
SliceSz = double(avw.hdr.dime.pixdim(4));
RowSz = double(avw.hdr.dime.pixdim(3));
PixelSz = double(avw.hdr.dime.pixdim(2));
x = 1:PixelDim;
for z = 1:SliceDim,
for y = 1:RowDim,
fwrite(fid,avw.img(x,y,z),precision);
end
end
case 1, % coronal unflipped
% For the 'coronal unflipped' type, the voxels are stored with
% Pixels in 'x' axis (varies fastest) - from patient right to left
% Rows in 'z' axis - from patient inferior to superior
% Slices in 'y' axis - from patient posterior to anterior
if verbose, fprintf('...writing coronal unflipped\n'); end
avw.hdr.hist.orient = uint8(1);
SliceDim = double(avw.hdr.dime.dim(3)); % y
RowDim = double(avw.hdr.dime.dim(4)); % z
PixelDim = double(avw.hdr.dime.dim(2)); % x
SliceSz = double(avw.hdr.dime.pixdim(3));
RowSz = double(avw.hdr.dime.pixdim(4));
PixelSz = double(avw.hdr.dime.pixdim(2));
x = 1:PixelDim;
for y = 1:SliceDim,
for z = 1:RowDim,
fwrite(fid,avw.img(x,y,z),precision);
end
end
case 2, % sagittal unflipped
% For the 'sagittal unflipped' type, the voxels are stored with
% Pixels in 'y' axis (varies fastest) - from patient posterior to anterior
% Rows in 'z' axis - from patient inferior to superior
% Slices in 'x' axis - from patient right to left
if verbose, fprintf('...writing sagittal unflipped\n'); end
avw.hdr.hist.orient = uint8(2);
SliceDim = double(avw.hdr.dime.dim(2)); % x
RowDim = double(avw.hdr.dime.dim(4)); % z
PixelDim = double(avw.hdr.dime.dim(3)); % y
SliceSz = double(avw.hdr.dime.pixdim(2));
RowSz = double(avw.hdr.dime.pixdim(4));
PixelSz = double(avw.hdr.dime.pixdim(3));
y = 1:PixelDim;
for x = 1:SliceDim,
for z = 1:RowDim,
fwrite(fid,avw.img(x,y,z),precision);
end
end
case 3, % transverse/axial flipped
% For the 'transverse flipped' type, the voxels are stored with
% Pixels in 'x' axis (varies fastest) - from patient right to left
% Rows in 'y' axis - from patient anterior to posterior*
% Slices in 'z' axis - from patient inferior to superior
if verbose,
fprintf('...writing axial flipped (+Y from Anterior to Posterior)\n');
end
avw.hdr.hist.orient = uint8(3);
SliceDim = double(avw.hdr.dime.dim(4)); % z
RowDim = double(avw.hdr.dime.dim(3)); % y
PixelDim = double(avw.hdr.dime.dim(2)); % x
SliceSz = double(avw.hdr.dime.pixdim(4));
RowSz = double(avw.hdr.dime.pixdim(3));
PixelSz = double(avw.hdr.dime.pixdim(2));
x = 1:PixelDim;
for z = 1:SliceDim,
for y = RowDim:-1:1, % flipped in Y
fwrite(fid,avw.img(x,y,z),precision);
end
end
case 4, % coronal flipped
% For the 'coronal flipped' type, the voxels are stored with
% Pixels in 'x' axis (varies fastest) - from patient right to left
% Rows in 'z' axis - from patient inferior to superior
% Slices in 'y' axis - from patient anterior to posterior
if verbose,
fprintf('...writing coronal flipped (+Z from Superior to Inferior)\n');
end
avw.hdr.hist.orient = uint8(4);
SliceDim = double(avw.hdr.dime.dim(3)); % y
RowDim = double(avw.hdr.dime.dim(4)); % z
PixelDim = double(avw.hdr.dime.dim(2)); % x
SliceSz = double(avw.hdr.dime.pixdim(3));
RowSz = double(avw.hdr.dime.pixdim(4));
PixelSz = double(avw.hdr.dime.pixdim(2));
x = 1:PixelDim;
for y = 1:SliceDim,
for z = RowDim:-1:1,
fwrite(fid,avw.img(x,y,z),precision);
end
end
case 5, % sagittal flipped
% For the 'sagittal flipped' type, the voxels are stored with
% Pixels in 'y' axis (varies fastest) - from patient posterior to anterior
% Rows in 'z' axis - from patient superior to inferior
% Slices in 'x' axis - from patient right to left
if verbose,
fprintf('...writing sagittal flipped (+Z from Superior to Inferior)\n');
end
avw.hdr.hist.orient = uint8(5);
SliceDim = double(avw.hdr.dime.dim(2)); % x
RowDim = double(avw.hdr.dime.dim(4)); % z
PixelDim = double(avw.hdr.dime.dim(3)); % y
SliceSz = double(avw.hdr.dime.pixdim(2));
RowSz = double(avw.hdr.dime.pixdim(4));
PixelSz = double(avw.hdr.dime.pixdim(3));
y = 1:PixelDim;
for x = 1:SliceDim,
for z = RowDim:-1:1, % superior to inferior
fwrite(fid,avw.img(x,y,z),precision);
end
end
otherwise, % transverse/axial unflipped
% For the 'transverse unflipped' type, the voxels are stored with
% Pixels in 'x' axis (varies fastest) - from patient right to left
% Rows in 'y' axis - from patient posterior to anterior
% Slices in 'z' axis - from patient inferior to superior
if verbose,
fprintf('...unknown orientation specified, assuming default axial unflipped\n');
end
avw.hdr.hist.orient = uint8(0);
SliceDim = double(avw.hdr.dime.dim(4)); % z
RowDim = double(avw.hdr.dime.dim(3)); % y
PixelDim = double(avw.hdr.dime.dim(2)); % x
SliceSz = double(avw.hdr.dime.pixdim(4));
RowSz = double(avw.hdr.dime.pixdim(3));
PixelSz = double(avw.hdr.dime.pixdim(2));
x = 1:PixelDim;
for z = 1:SliceDim,
for y = 1:RowDim,
fwrite(fid,avw.img(x,y,z),precision);
end
end
end
fclose(fid);
% Update the header
avw.hdr.dime.dim(2:4) = int16([PixelDim,RowDim,SliceDim]);
avw.hdr.dime.pixdim(2:4) = single([PixelSz,RowSz,SliceSz]);
return
%----------------------------------------------------------------------------
function write_header(fid,avw,verbose)
header_key(fid,avw.hdr.hk);
image_dimension(fid,avw.hdr.dime);
data_history(fid,avw.hdr.hist);
% check the file size is 348 bytes
fbytes = ftell(fid);
fclose(fid);
if ~isequal(fbytes,348),
msg = sprintf('...file size is not 348 bytes!\n');
warning(msg);
end
return
%----------------------------------------------------------------------------
function header_key(fid,hk)
% Original header structures - ANALYZE 7.5
% struct header_key /* header key */
% { /* off + size */
% int sizeof_hdr /* 0 + 4 */
% char data_type[10]; /* 4 + 10 */
% char db_name[18]; /* 14 + 18 */
% int extents; /* 32 + 4 */
% short int session_error; /* 36 + 2 */
% char regular; /* 38 + 1 */
% char hkey_un0; /* 39 + 1 */
% }; /* total=40 bytes */
fseek(fid,0,'bof');
fwrite(fid, hk.sizeof_hdr(1), 'int32'); % must be 348!
data_type = sprintf('%-10s',hk.data_type); % ensure it is 10 chars
fwrite(fid, hk.data_type(1:10), 'uchar');
db_name = sprintf('%-18s',hk.db_name); % ensure it is 18 chars
fwrite(fid, db_name(1:18), 'uchar');
fwrite(fid, hk.extents(1), 'int32');
fwrite(fid, hk.session_error(1),'int16');
regular = sprintf('%1s',hk.regular); % ensure it is 1 char
fwrite(fid, regular(1), 'uchar'); % might be uint8
%hkey_un0 = sprintf('%1s',hk.hkey_un0); % ensure it is 1 char
%fwrite(fid, hkey_un0(1), 'uchar');
fwrite(fid, hk.hkey_un0(1), 'uint8');
% >Would you set hkey_un0 as char or uint8?
% Really doesn't make any difference. As far as anyone here can remember,
% this was just to pad to an even byte boundary for that structure. I guess
% I'd suggest setting it to a uint8 value of 0 (i.e, truly zero-valued) so
% that it doesn't look like anything important!
% Denny <[email protected]>
return
%----------------------------------------------------------------------------
function image_dimension(fid,dime)
%struct image_dimension
% { /* off + size */
% short int dim[8]; /* 0 + 16 */
% char vox_units[4]; /* 16 + 4 */
% char cal_units[8]; /* 20 + 8 */
% short int unused1; /* 28 + 2 */
% short int datatype; /* 30 + 2 */
% short int bitpix; /* 32 + 2 */
% short int dim_un0; /* 34 + 2 */
% float pixdim[8]; /* 36 + 32 */
% /*
% pixdim[] specifies the voxel dimensions:
% pixdim[1] - voxel width
% pixdim[2] - voxel height
% pixdim[3] - interslice distance
% ..etc
% */
% float vox_offset; /* 68 + 4 */
% float roi_scale; /* 72 + 4 */
% float funused1; /* 76 + 4 */
% float funused2; /* 80 + 4 */
% float cal_max; /* 84 + 4 */
% float cal_min; /* 88 + 4 */
% int compressed; /* 92 + 4 */
% int verified; /* 96 + 4 */
% int glmax; /* 100 + 4 */
% int glmin; /* 104 + 4 */
% }; /* total=108 bytes */
fwrite(fid, dime.dim(1:8), 'int16');
fwrite(fid, dime.vox_units(1:4),'uchar');
fwrite(fid, dime.cal_units(1:8),'uchar');
fwrite(fid, dime.unused1(1), 'int16');
fwrite(fid, dime.datatype(1), 'int16');
fwrite(fid, dime.bitpix(1), 'int16');
fwrite(fid, dime.dim_un0(1), 'int16');
fwrite(fid, dime.pixdim(1:8), 'float32');
fwrite(fid, dime.vox_offset(1), 'float32');
% Ensure compatibility with SPM (according to MRIcro)
if dime.roi_scale == 0, dime.roi_scale = 0.00392157; end
fwrite(fid, dime.roi_scale(1), 'float32');
fwrite(fid, dime.funused1(1), 'float32');
fwrite(fid, dime.funused2(1), 'float32');
fwrite(fid, dime.cal_max(1), 'float32');
fwrite(fid, dime.cal_min(1), 'float32');
fwrite(fid, dime.compressed(1), 'int32');
fwrite(fid, dime.verified(1), 'int32');
fwrite(fid, dime.glmax(1), 'int32');
fwrite(fid, dime.glmin(1), 'int32');
return
%----------------------------------------------------------------------------
function data_history(fid,hist)
% Original header structures - ANALYZE 7.5
%struct data_history
% { /* off + size */
% char descrip[80]; /* 0 + 80 */
% char aux_file[24]; /* 80 + 24 */
% char orient; /* 104 + 1 */
% char originator[10]; /* 105 + 10 */
% char generated[10]; /* 115 + 10 */
% char scannum[10]; /* 125 + 10 */
% char patient_id[10]; /* 135 + 10 */
% char exp_date[10]; /* 145 + 10 */
% char exp_time[10]; /* 155 + 10 */
% char hist_un0[3]; /* 165 + 3 */
% int views /* 168 + 4 */
% int vols_added; /* 172 + 4 */
% int start_field; /* 176 + 4 */
% int field_skip; /* 180 + 4 */
% int omax; /* 184 + 4 */
% int omin; /* 188 + 4 */
% int smax; /* 192 + 4 */
% int smin; /* 196 + 4 */
% }; /* total=200 bytes */
descrip = sprintf('%-80s', hist.descrip); % 80 chars
aux_file = sprintf('%-24s', hist.aux_file); % 24 chars
originator = sprintf('%-10s', hist.originator); % 10 chars
generated = sprintf('%-10s', hist.generated); % 10 chars
scannum = sprintf('%-10s', hist.scannum); % 10 chars
patient_id = sprintf('%-10s', hist.patient_id); % 10 chars
exp_date = sprintf('%-10s', hist.exp_date); % 10 chars
exp_time = sprintf('%-10s', hist.exp_time); % 10 chars
hist_un0 = sprintf( '%-3s', hist.hist_un0); % 3 chars
% ---
% The following should not be necessary, but I actually
% found one instance where it was, so this totally anal
% retentive approach became necessary, despite the
% apparently elegant solution above to ensuring that variables
% are the right length.
if length(descrip) < 80,
paddingN = 80-length(descrip);
padding = char(repmat(double(' '),1,paddingN));
descrip = [descrip,padding];
end
if length(aux_file) < 24,
paddingN = 24-length(aux_file);
padding = char(repmat(double(' '),1,paddingN));
aux_file = [aux_file,padding];
end
if length(originator) < 10,
paddingN = 10-length(originator);
padding = char(repmat(double(' '),1,paddingN));
originator = [originator, padding];
end
if length(generated) < 10,
paddingN = 10-length(generated);
padding = char(repmat(double(' '),1,paddingN));
generated = [generated, padding];
end
if length(scannum) < 10,
paddingN = 10-length(scannum);
padding = char(repmat(double(' '),1,paddingN));
scannum = [scannum, padding];
end
if length(patient_id) < 10,
paddingN = 10-length(patient_id);
padding = char(repmat(double(' '),1,paddingN));
patient_id = [patient_id, padding];
end
if length(exp_date) < 10,
paddingN = 10-length(exp_date);
padding = char(repmat(double(' '),1,paddingN));
exp_date = [exp_date, padding];
end
if length(exp_time) < 10,
paddingN = 10-length(exp_time);
padding = char(repmat(double(' '),1,paddingN));
exp_time = [exp_time, padding];
end
if length(hist_un0) < 10,
paddingN = 10-length(hist_un0);
padding = char(repmat(double(' '),1,paddingN));
hist_un0 = [hist_un0, padding];
end
% -- if you thought that was anal, try this;
% -- lets check for unusual ASCII char values!
if find(double(descrip)>128),
indexStrangeChar = find(double(descrip)>128);
descrip(indexStrangeChar) = ' ';
end
if find(double(aux_file)>128),
indexStrangeChar = find(double(aux_file)>128);
aux_file(indexStrangeChar) = ' ';
end
if find(double(originator)>128),
indexStrangeChar = find(double(originator)>128);
originator(indexStrangeChar) = ' ';
end
if find(double(generated)>128),
indexStrangeChar = find(double(generated)>128);
generated(indexStrangeChar) = ' ';
end
if find(double(scannum)>128),
indexStrangeChar = find(double(scannum)>128);
scannum(indexStrangeChar) = ' ';
end
if find(double(patient_id)>128),
indexStrangeChar = find(double(patient_id)>128);
patient_id(indexStrangeChar) = ' ';
end
if find(double(exp_date)>128),
indexStrangeChar = find(double(exp_date)>128);
exp_date(indexStrangeChar) = ' ';
end
if find(double(exp_time)>128),
indexStrangeChar = find(double(exp_time)>128);
exp_time(indexStrangeChar) = ' ';
end
if find(double(hist_un0)>128),
indexStrangeChar = find(double(hist_un0)>128);
hist_un0(indexStrangeChar) = ' ';
end
% --- finally, we write the fields
fwrite(fid, descrip(1:80), 'uchar');
fwrite(fid, aux_file(1:24), 'uchar');
%orient = sprintf( '%1s', hist.orient); % 1 char
%fwrite(fid, orient(1), 'uchar');
fwrite(fid, hist.orient(1), 'uint8'); % see note below on char
fwrite(fid, originator(1:10), 'uchar');
fwrite(fid, generated(1:10), 'uchar');
fwrite(fid, scannum(1:10), 'uchar');
fwrite(fid, patient_id(1:10), 'uchar');
fwrite(fid, exp_date(1:10), 'uchar');
fwrite(fid, exp_time(1:10), 'uchar');
fwrite(fid, hist_un0(1:3), 'uchar');
fwrite(fid, hist.views(1), 'int32');
fwrite(fid, hist.vols_added(1), 'int32');
fwrite(fid, hist.start_field(1),'int32');
fwrite(fid, hist.field_skip(1), 'int32');
fwrite(fid, hist.omax(1), 'int32');
fwrite(fid, hist.omin(1), 'int32');
fwrite(fid, hist.smax(1), 'int32');
fwrite(fid, hist.smin(1), 'int32');
return
% Note on using char:
% The 'char orient' field in the header is intended to
% hold simply an 8-bit unsigned integer value, not the ASCII representation
% of the character for that value. A single 'char' byte is often used to
% represent an integer value in Analyze if the known value range doesn't
% go beyond 0-255 - saves a byte over a short int, which may not mean
% much in today's computing environments, but given that this format
% has been around since the early 1980's, saving bytes here and there on
% older systems was important! In this case, 'char' simply provides the
% byte of storage - not an indicator of the format for what is stored in
% this byte. Generally speaking, anytime a single 'char' is used, it is
% probably meant to hold an 8-bit integer value, whereas if this has
% been dimensioned as an array, then it is intended to hold an ASCII
% character string, even if that was only a single character.
% Denny <[email protected]>
% See other notes in avw_hdr_read
|
github
|
philippboehmsturm/antx-master
|
bilinear.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/bilinear.m
| 4,339 |
utf_8
|
17250db27826cad87fa3384823e1242f
|
% Copyright (C) 1999 Paul Kienzle
%
% This program 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 2 of the License, or
% (at your option) any later version.
%
% This program 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 this program; If not, see <http://www.gnu.org/licenses/>.
% usage: [Zz, Zp, Zg] = bilinear(Sz, Sp, Sg, T)
% [Zb, Za] = bilinear(Sb, Sa, T)
%
% Transform a s-plane filter specification into a z-plane
% specification. Filters can be specified in either zero-pole-gain or
% transfer function form. The input form does not have to match the
% output form. 1/T is the sampling frequency represented in the z plane.
%
% Note: this differs from the bilinear function in the signal processing
% toolbox, which uses 1/T rather than T.
%
% Theory: Given a piecewise flat filter design, you can transform it
% from the s-plane to the z-plane while maintaining the band edges by
% means of the bilinear transform. This maps the left hand side of the
% s-plane into the interior of the unit circle. The mapping is highly
% non-linear, so you must design your filter with band edges in the
% s-plane positioned at 2/T tan(w*T/2) so that they will be positioned
% at w after the bilinear transform is complete.
%
% The following table summarizes the transformation:
%
% +---------------+-----------------------+----------------------+
% | Transform | Zero at x | Pole at x |
% | H(S) | H(S) = S-x | H(S)=1/(S-x) |
% +---------------+-----------------------+----------------------+
% | 2 z-1 | zero: (2+xT)/(2-xT) | zero: -1 |
% | S -> - --- | pole: -1 | pole: (2+xT)/(2-xT) |
% | T z+1 | gain: (2-xT)/T | gain: (2-xT)/T |
% +---------------+-----------------------+----------------------+
%
% With tedious algebra, you can derive the above formulae yourself by
% substituting the transform for S into H(S)=S-x for a zero at x or
% H(S)=1/(S-x) for a pole at x, and converting the result into the
% form:
%
% H(Z)=g prod(Z-Xi)/prod(Z-Xj)
%
% Please note that a pole and a zero at the same place exactly cancel.
% This is significant since the bilinear transform creates numerous
% extra poles and zeros, most of which cancel. Those which do not
% cancel have a 'fill-in' effect, extending the shorter of the sets to
% have the same number of as the longer of the sets of poles and zeros
% (or at least split the difference in the case of the band pass
% filter). There may be other opportunistic cancellations but I will
% not check for them.
%
% Also note that any pole on the unit circle or beyond will result in
% an unstable filter. Because of cancellation, this will only happen
% if the number of poles is smaller than the number of zeros. The
% analytic design methods all yield more poles than zeros, so this will
% not be a problem.
%
% References:
%
% Proakis & Manolakis (1992). Digital Signal Processing. New York:
% Macmillan Publishing Company.
% Author: Paul Kienzle <[email protected]>
function [Zz, Zp, Zg] = bilinear(Sz, Sp, Sg, T)
if nargin==3
T = Sg;
[Sz, Sp, Sg] = tf2zp(Sz, Sp);
elseif nargin~=4
usage('[Zz, Zp, Zg]=bilinear(Sz,Sp,Sg,T) or [Zb, Za]=blinear(Sb,Sa,T)');
end;
p = length(Sp);
z = length(Sz);
if z > p || p==0
error('bilinear: must have at least as many poles as zeros in s-plane');
end
% ---------------- ------------------------- ------------------------
% Bilinear zero: (2+xT)/(2-xT) pole: (2+xT)/(2-xT)
% 2 z-1 pole: -1 zero: -1
% S -> - --- gain: (2-xT)/T gain: (2-xT)/T
% T z+1
% ---------------- ------------------------- ------------------------
Zg = real(Sg * prod((2-Sz*T)/T) / prod((2-Sp*T)/T));
Zp = (2+Sp*T)./(2-Sp*T);
if isempty(Sz)
Zz = -ones(size(Zp));
else
Zz = [(2+Sz*T)./(2-Sz*T)];
Zz = postpad(Zz, p, -1);
end
if nargout==2, [Zz, Zp] = zp2tf(Zz, Zp, Zg); end
|
github
|
philippboehmsturm/antx-master
|
select_channel_list.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/select_channel_list.m
| 5,910 |
utf_8
|
51149b83e6eca7c0510e5a740c7f87e7
|
function [select] = select_channel_list(label, select, titlestr);
% SELECT_CHANNEL_LIST presents a dialog for selecting multiple elements
% from a cell array with strings, such as the labels of EEG channels.
% The dialog presents two columns with an add and remove mechanism.
%
% select = select_channel_list(label, initial, titlestr)
%
% with
% initial indices of channels that are initially selected
% label cell array with channel labels (strings)
% titlestr title for dialog (optional)
% and
% select indices of selected channels
%
% If the user presses cancel, the initial selection will be returned.
% Copyright (C) 2003, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: select_channel_list.m 7123 2012-12-06 21:21:38Z roboos $
if nargin<3
titlestr = 'Select';
end
pos = get(0,'DefaultFigurePosition');
pos(3:4) = [290 300];
dlg = dialog('Name', titlestr, 'Position', pos);
select = select(:)'; % ensure that it is a row array
userdata.label = label;
userdata.select = select;
userdata.unselect = setdiff(1:length(label), select);
set(dlg, 'userdata', userdata);
uicontrol(dlg, 'style', 'text', 'position', [ 10 240+20 80 20], 'string', 'unselected');
uicontrol(dlg, 'style', 'text', 'position', [200 240+20 80 20], 'string', 'selected ');
uicontrol(dlg, 'style', 'listbox', 'position', [ 10 40+20 80 200], 'min', 0, 'max', 2, 'tag', 'lbunsel')
uicontrol(dlg, 'style', 'listbox', 'position', [200 40+20 80 200], 'min', 0, 'max', 2, 'tag', 'lbsel')
uicontrol(dlg, 'style', 'pushbutton', 'position', [105 175+20 80 20], 'string', 'add all >' , 'callback', @label_addall);
uicontrol(dlg, 'style', 'pushbutton', 'position', [105 145+20 80 20], 'string', 'add >' , 'callback', @label_add);
uicontrol(dlg, 'style', 'pushbutton', 'position', [105 115+20 80 20], 'string', '< remove' , 'callback', @label_remove);
uicontrol(dlg, 'style', 'pushbutton', 'position', [105 85+20 80 20], 'string', '< remove all', 'callback', @label_removeall);
uicontrol(dlg, 'style', 'pushbutton', 'position', [ 55 10 80 20], 'string', 'Cancel', 'callback', 'close');
uicontrol(dlg, 'style', 'pushbutton', 'position', [155 10 80 20], 'string', 'OK', 'callback', 'uiresume');
label_redraw(dlg);
% wait untill the dialog is closed or the user presses OK/Cancel
uiwait(dlg);
if ishandle(dlg)
% the user pressed OK, return the selection from the dialog
userdata = get(dlg, 'userdata');
select = userdata.select;
close(dlg);
return
else
% the user pressed Cancel or closed the dialog, return the initial selection
return
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function label_redraw(h);
userdata = get(h, 'userdata');
set(findobj(h, 'tag', 'lbsel' ), 'string', userdata.label(userdata.select));
set(findobj(h, 'tag', 'lbunsel'), 'string', userdata.label(userdata.unselect));
% set the active element in the select listbox, based on the previous active element
tmp = min(get(findobj(h, 'tag', 'lbsel'), 'value'));
tmp = min(tmp, length(get(findobj(h, 'tag', 'lbsel'), 'string')));
if isempty(tmp) | tmp==0
tmp = 1;
end
set(findobj(h, 'tag', 'lbsel' ), 'value', tmp);
% set the active element in the unselect listbox, based on the previous active element
tmp = min(get(findobj(h, 'tag', 'lbunsel'), 'value'));
tmp = min(tmp, length(get(findobj(h, 'tag', 'lbunsel'), 'string')));
if isempty(tmp) | tmp==0
tmp = 1;
end
set(findobj(h, 'tag', 'lbunsel' ), 'value', tmp);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function label_addall(h, eventdata, handles, varargin);
h = get(h, 'parent');
userdata = get(h, 'userdata');
userdata.select = 1:length(userdata.label);
userdata.unselect = [];
set(findobj(h, 'tag', 'lbunsel' ), 'value', 1);
set(h, 'userdata', userdata);
label_redraw(h);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function label_removeall(h, eventdata, handles, varargin);
h = get(h, 'parent');
userdata = get(h, 'userdata');
userdata.unselect = 1:length(userdata.label);
userdata.select = [];
set(findobj(h, 'tag', 'lbsel' ), 'value', 1);
set(h, 'userdata', userdata);
label_redraw(h);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function label_add(h, eventdata, handles, varargin);
h = get(h, 'parent');
userdata = get(h, 'userdata');
if ~isempty(userdata.unselect)
add = userdata.unselect(get(findobj(h, 'tag', 'lbunsel' ), 'value'));
userdata.select = sort([userdata.select add]);
userdata.unselect = sort(setdiff(userdata.unselect, add));
set(h, 'userdata', userdata);
label_redraw(h);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function label_remove(h, eventdata, handles, varargin);
h = get(h, 'parent');
userdata = get(h, 'userdata');
if ~isempty(userdata.select)
remove = userdata.select(get(findobj(h, 'tag', 'lbsel' ), 'value'));
userdata.select = sort(setdiff(userdata.select, remove));
userdata.unselect = sort([userdata.unselect remove]);
set(h, 'userdata', userdata);
label_redraw(h);
end
|
github
|
philippboehmsturm/antx-master
|
artifact_viewer.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/artifact_viewer.m
| 6,725 |
utf_8
|
0045c4b5518e2d509c8d0d9892e389c2
|
function artifact_viewer(cfg, artcfg, zval, artval, zindx, inputdata);
% ARTIFACT_VIEWER is a subfunction that reads a segment of data
% (one channel only) and displays it together with the cummulated
% z-value
% Copyright (C) 2004-2006, Jan-Mathijs Schoffelen & Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: artifact_viewer.m 7123 2012-12-06 21:21:38Z roboos $
dat.cfg = cfg;
dat.artcfg = artcfg;
if nargin == 5
% no data is given
dat.hdr = ft_read_header(cfg.headerfile);
elseif nargin == 6
% data is given
dat.hdr = ft_fetch_header(inputdata); % used name inputdata iso data, because data is already used later in this function
dat.inputdata = inputdata; % to be able to get inputdata into h (by guidata)
end
dat.trlop = 1;
dat.zval = zval;
dat.artval = artval;
dat.zindx = zindx;
dat.stop = 0;
dat.numtrl = size(cfg.trl,1);
dat.trialok = zeros(1,dat.numtrl);
for trlop=1:dat.numtrl
dat.trialok(trlop) = ~any(artval{trlop});
end
h = gcf;
guidata(h,dat);
uicontrol(gcf,'units','pixels','position',[5 5 40 18],'String','stop','Callback',@stop);
uicontrol(gcf,'units','pixels','position',[50 5 25 18],'String','<','Callback',@prevtrial);
uicontrol(gcf,'units','pixels','position',[75 5 25 18],'String','>','Callback',@nexttrial);
uicontrol(gcf,'units','pixels','position',[105 5 25 18],'String','<<','Callback',@prev10trial);
uicontrol(gcf,'units','pixels','position',[130 5 25 18],'String','>>','Callback',@next10trial);
uicontrol(gcf,'units','pixels','position',[160 5 50 18],'String','<artfct','Callback',@prevartfct);
uicontrol(gcf,'units','pixels','position',[210 5 50 18],'String','artfct>','Callback',@nextartfct);
while ishandle(h),
dat = guidata(h);
if dat.stop == 0,
read_and_plot(h);
uiwait;
else
break
end
end
if ishandle(h)
close(h);
end
%------------
%subfunctions
%------------
function read_and_plot(h)
vlinecolor = [0 0 0];
dat = guidata(h);
% make a local copy of the relevant variables
trlop = dat.trlop;
zval = dat.zval{trlop};
artval = dat.artval{trlop};
zindx = dat.zindx{trlop};
cfg = dat.cfg;
artcfg = dat.artcfg;
hdr = dat.hdr;
trl = dat.artcfg.trl;
trlpadsmp = round(artcfg.trlpadding*hdr.Fs);
% determine the channel with the highest z-value
[dum, indx] = max(zval);
sgnind = zindx(indx);
iscontinuous = 1;
if isfield(dat, 'inputdata')
data = ft_fetch_data(dat.inputdata, 'header', hdr, 'begsample', trl(trlop,1), 'endsample', trl(trlop,2), 'chanindx', sgnind, 'checkboundary', strcmp(cfg.continuous,'no'));
else
data = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', trl(trlop,1), 'endsample', trl(trlop,2), 'chanindx', sgnind, 'checkboundary', strcmp(cfg.continuous,'no'));
end
% data = preproc(data, channel, hdr.Fs, artfctdef, [], fltpadding, fltpadding);
str = sprintf('trial %3d, channel %s', dat.trlop, hdr.label{sgnind});
fprintf('showing %s\n', str);
% plot z-values in lower subplot
subplot(2,1,2);
cla
hold on
xval = trl(trlop,1):trl(trlop,2);
if trlpadsmp
sel = 1:trlpadsmp;
h = plot(xval(sel), zval(sel)); set(h, 'color', [0.5 0.5 1]); % plot the trialpadding in another color
sel = trlpadsmp:(length(data)-trlpadsmp);
plot(xval(sel), zval(sel), 'b');
sel = (length(data)-trlpadsmp):length(data);
h = plot(xval(sel), zval(sel)); set(h, 'color', [0.5 0.5 1]); % plot the trialpadding in another color
vline(xval( 1)+trlpadsmp, 'color', vlinecolor);
vline(xval(end)-trlpadsmp, 'color', vlinecolor);
else
plot(xval, zval, 'b');
end
% draw a line at the threshold level
hline(artcfg.cutoff, 'color', 'r', 'linestyle', ':');
% make the artefact part red
zval(~artval) = nan;
plot(xval, zval, 'r-');
hold off
xlabel('samples');
ylabel('zscore');
% plot data of most aberrant channel in upper subplot
subplot(2,1,1);
cla
hold on
if trlpadsmp
sel = 1:trlpadsmp;
h = plot(xval(sel), data(sel)); set(h, 'color', [0.5 0.5 1]); % plot the trialpadding in another color
sel = trlpadsmp:(length(data)-trlpadsmp);
plot(xval(sel), data(sel), 'b');
sel = (length(data)-trlpadsmp):length(data);
h = plot(xval(sel), data(sel)); set(h, 'color', [0.5 0.5 1]); % plot the trialpadding in another color
vline(xval( 1)+trlpadsmp, 'color', vlinecolor);
vline(xval(end)-trlpadsmp, 'color', vlinecolor);
else
plot(xval, data, 'b');
end
data(~artval) = nan;
plot(xval, data, 'r-');
hold off
xlabel('samples');
ylabel('uV or Tesla');
title(str);
function varargout = nexttrial(h, eventdata, handles, varargin)
dat = guidata(h);
if dat.trlop < dat.numtrl,
dat.trlop = dat.trlop + 1;
end;
guidata(h,dat);
uiresume;
function varargout = next10trial(h, eventdata, handles, varargin)
dat = guidata(h);
if dat.trlop < dat.numtrl - 10,
dat.trlop = dat.trlop + 10;
else dat.trlop = dat.numtrl;
end;
guidata(h,dat);
uiresume;
function varargout = prevtrial(h, eventdata, handles, varargin)
dat = guidata(h);
if dat.trlop > 1,
dat.trlop = dat.trlop - 1;
else dat.trlop = 1;
end;
guidata(h,dat);
uiresume;
function varargout = prev10trial(h, eventdata, handles, varargin)
dat = guidata(h);
if dat.trlop > 10,
dat.trlop = dat.trlop - 10;
else dat.trlop = 1;
end;
guidata(h,dat);
uiresume;
function varargout = nextartfct(h, eventdata, handles, varargin)
dat = guidata(h);
artfctindx = find(dat.trialok == 0);
sel = find(artfctindx > dat.trlop);
if ~isempty(sel)
dat.trlop = artfctindx(sel(1));
else
dat.trlop = dat.trlop;
end
guidata(h,dat);
uiresume;
function varargout = prevartfct(h, eventdata, handles, varargin)
dat = guidata(h);
artfctindx = find(dat.trialok == 0);
sel = find(artfctindx < dat.trlop);
if ~isempty(sel)
dat.trlop = artfctindx(sel(end));
else
dat.trlop = dat.trlop;
end
guidata(h,dat);
uiresume;
function varargout = stop(h, eventdata, handles, varargin)
dat = guidata(h);
dat.stop = 1;
guidata(h,dat);
uiresume;
function vsquare(x1, x2, c)
abc = axis;
y1 = abc(3);
y2 = abc(4);
x = [x1 x2 x2 x1 x1];
y = [y1 y1 y2 y2 y1];
z = [-1 -1 -1 -1 -1];
h = patch(x, y, z, c);
set(h, 'edgecolor', c)
|
github
|
philippboehmsturm/antx-master
|
rejectvisual_summary.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/rejectvisual_summary.m
| 19,077 |
utf_8
|
37d0a7a58af84def37cd501806ceeca4
|
function [chansel, trlsel, cfg] = rejectvisual_summary(cfg, data)
% REJECTVISUAL_SUMMARY: subfunction for ft_rejectvisual
% determine the initial selection of trials and channels
nchan = length(data.label);
ntrl = length(data.trial);
cfg.channel = ft_channelselection(cfg.channel, data.label);
trlsel = true(1,ntrl);
chansel = false(1,nchan);
chansel(match_str(data.label, cfg.channel)) = 1;
% compute the sampling frequency from the first two timepoints
fsample = 1/mean(diff(data.time{1}));
% select the specified latency window from the data
% here it is done BEFORE filtering and metric computation
for i=1:ntrl
begsample = nearest(data.time{i}, cfg.latency(1));
endsample = nearest(data.time{i}, cfg.latency(2));
data.time{i} = data.time{i}(begsample:endsample);
data.trial{i} = data.trial{i}(:,begsample:endsample);
end
% compute the offset from the time axes
offset = zeros(ntrl,1);
for i=1:ntrl
offset(i) = time2offset(data.time{i}, fsample);
end
% set up guidata info
h = figure();
info = [];
info.data = data;
info.cfg = cfg;
info.metric = cfg.metric;
info.ntrl = ntrl;
info.nchan = nchan;
info.trlsel = trlsel;
info.chansel = chansel;
info.fsample = fsample;
info.offset = offset;
info.quit = 0;
guidata(h,info);
% set up display
interactive = 1;
info = guidata(h);
% make the figure large enough to hold stuff
set(h,'Position',[50 350 800 500]);
% define three plots
info.axes(1) = axes('position',[0.100 0.650 0.375 0.300]); % summary plot
info.axes(2) = axes('position',[0.575 0.650 0.375 0.300]); % channels
info.axes(3) = axes('position',[0.100 0.250 0.375 0.300]); % trials
% callback function (for toggling trials/channels) is set later, so that
% the user cannot try to toggle trials while nothing is present on the
% plots
% set up radio buttons for choosing metric
bgcolor = get(h,'color');
g = uibuttongroup('Position',[0.525 0.275 0.375 0.250 ],'bordertype','none','backgroundcolor',bgcolor);
r(1) = uicontrol('Units','normalized','parent',g,'position',[ 0.0 7/7 0.40 0.15 ],'Style','radio','backgroundcolor',bgcolor,'string','var','HandleVisibility','off');
r(2) = uicontrol('Units','normalized','parent',g,'position',[ 0.0 6/7 0.40 0.15 ],'Style','radio','backgroundcolor',bgcolor,'String','min','HandleVisibility','off');
r(3) = uicontrol('Units','normalized','parent',g,'position',[ 0.0 5/7 0.40 0.15 ],'Style','Radio','backgroundcolor',bgcolor,'String','max','HandleVisibility','off');
r(4) = uicontrol('Units','normalized','parent',g,'position',[ 0.0 4/7 0.40 0.15 ],'Style','Radio','backgroundcolor',bgcolor,'String','maxabs','HandleVisibility','off');
r(5) = uicontrol('Units','normalized','parent',g,'position',[ 0.0 3/7 0.40 0.15 ],'Style','Radio','backgroundcolor',bgcolor,'String','range','HandleVisibility','off');
r(6) = uicontrol('Units','normalized','parent',g,'position',[ 0.0 2/7 0.40 0.15 ],'Style','Radio','backgroundcolor',bgcolor,'String','kurtosis','HandleVisibility','off');
r(7) = uicontrol('Units','normalized','parent',g,'position',[ 0.0 1/7 0.40 0.15 ],'Style','Radio','backgroundcolor',bgcolor,'String','1/var','HandleVisibility','off');
r(8) = uicontrol('Units','normalized','parent',g,'position',[ 0.0 0/7 0.40 0.15 ],'Style','Radio','backgroundcolor',bgcolor,'String','zvalue','HandleVisibility','off');
r(9) = uicontrol('Units','normalized','parent',g,'position',[ 0.0 -1/7 0.40 0.15 ],'Style','Radio','backgroundcolor',bgcolor,'String','maxzvalue','HandleVisibility','off');
% pre-select appropriate metric, if defined
set(g,'SelectionChangeFcn',@change_metric);
for i=1:length(r)
if strcmp(get(r(i),'string'), cfg.metric)
set(g,'SelectedObject',r(i));
end
end
% editboxes for manually specifying which channels/trials to turn off
uicontrol(h,'Units','normalized','position',[0.64 0.44 0.14 0.05],'Style','text','HorizontalAlignment','left','backgroundcolor',get(h,'color'),'string','Toggle trial #:');
uicontrol(h,'Units','normalized','position',[0.64 0.40 0.12 0.05],'Style','edit','HorizontalAlignment','left','backgroundcolor',[1 1 1],'callback',@toggle_trials);
uicontrol(h,'Units','normalized','position',[0.64 0.31 0.14 0.05],'Style','text','HorizontalAlignment','left','backgroundcolor',get(h,'color'),'string','Toggle channel:');
uicontrol(h,'Units','normalized','position',[0.64 0.27 0.12 0.05],'Style','edit','HorizontalAlignment','left','backgroundcolor',[1 1 1],'callback',@toggle_channels);
% editbox for trial plotting
uicontrol(h,'Units','normalized','position',[0.500 0.165 0.10 0.05],'Style','text','HorizontalAlignment','left','backgroundcolor',get(h,'color'),'string','Plot trial:');
info.plottrltxt = uicontrol(h,'Units','normalized','position',[0.580 0.170 0.12 0.05],'Style','edit','HorizontalAlignment','left','backgroundcolor',[1 1 1],'callback',@display_trial);
info.badtrllbl = uicontrol(h,'Units','normalized','position',[0.795 0.44 0.195 0.05],'Style','text','HorizontalAlignment','left','backgroundcolor',get(h,'color'),'string',sprintf('Rejected trials: %i/%i',sum(info.trlsel==0),info.ntrl));
info.badtrltxt = uicontrol(h,'Units','normalized','position',[0.795 0.3975 0.23 0.05],'Style','text','HorizontalAlignment','left','backgroundcolor',get(h,'color'));
info.badchanlbl = uicontrol(h,'Units','normalized','position',[0.795 0.31 0.195 0.05],'Style','text','HorizontalAlignment','left','backgroundcolor',get(h,'color'),'string',sprintf('Rejected channels: %i/%i',sum(info.chansel==0),info.nchan));
info.badchantxt = uicontrol(h,'Units','normalized','position',[0.795 0.2625 0.23 0.05],'Style','text','HorizontalAlignment','left','backgroundcolor',get(h,'color'));
% instructions
instructions = sprintf('Drag the mouse over the channels/trials you wish to reject.');
uicontrol(h,'Units','normalized','position',[0.625 0.50 0.35 0.065],'Style','text','HorizontalAlignment','left','backgroundcolor',get(h,'color'),'string',instructions,'FontWeight','bold','ForegroundColor','b');
% "show rejected" button
% ui_tog = uicontrol(h,'Units','normalized','position',[0.55 0.200 0.25 0.05],'Style','checkbox','backgroundcolor',get(h,'color'),'string','Show rejected?','callback',@toggle_rejected);
% if strcmp(cfg.viewmode, 'toggle')
% set(ui_tog,'value',1);
% end
% logbox
info.output_box = uicontrol(h,'Units','normalized','position',[0.00 0.00 1.00 0.15],'Style','edit','HorizontalAlignment','left','Max',3,'Min',1,'Enable','inactive','FontName',get(0,'FixedWidthFontName'),'FontSize',9,'ForegroundColor',[0 0 0],'BackgroundColor',[1 1 1]);
% quit button
uicontrol(h,'Units','normalized','position',[0.80 0.175 0.10 0.05],'string','quit','callback',@quit);
guidata(h, info);
% disable trial plotting if cfg.layout not present
if ~isfield(info.cfg,'layout')
set(info.plottrltxt,'Enable','off');
update_log(info.output_box,sprintf('NOTE: "cfg.layout" parameter required for trial plotting!'));
end
% Compute initial metric...
compute_metric(h);
while interactive && ishandle(h)
redraw(h);
info = guidata(h);
if info.quit == 0
uiwait(h);
else
chansel = info.chansel;
trlsel = info.trlsel;
cfg = info.cfg;
delete(h);
break;
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTIONS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function compute_metric(h)
info = guidata(h);
update_log(info.output_box,'Computing metric...');
ft_progress('init', info.cfg.feedback, 'computing metric');
level = zeros(info.nchan, info.ntrl);
if strcmp(info.metric,'zvalue') || strcmp(info.metric, 'maxzvalue')
% cellmean and cellstd (see ft_denoise_pca) would work instead of for-loops,
% but they were too memory-intensive
runsum=zeros(info.nchan, 1);
runss=zeros(info.nchan,1);
runnum=0;
for i=1:info.ntrl
[dat] = preproc(info.data.trial{i}, info.data.label, offset2time(info.offset(i), info.fsample, size(info.data.trial{i},2)), info.cfg.preproc); % not entirely sure whether info.data.time{i} is correct, so making it on the fly
dat(info.chansel==0,:) = nan;
runsum=runsum+sum(dat,2);
runss=runss+sum(dat.^2,2);
runnum=runnum+size(dat,2);
end
mval=runsum/runnum;
sd=sqrt(runss/runnum - (runsum./runnum).^2);
end
for i=1:info.ntrl
ft_progress(i/info.ntrl, 'computing metric %d of %d\n', i, info.ntrl);
[dat, label, time, info.cfg.preproc] = preproc(info.data.trial{i}, info.data.label, offset2time(info.offset(i), info.fsample, size(info.data.trial{i},2)), info.cfg.preproc); % not entirely sure whether info.data.time{i} is correct, so making it on the fly
dat(info.chansel==0,:) = nan;
switch info.metric
case 'var'
level(:,i) = std(dat, [], 2).^2;
case 'min'
level(:,i) = min(dat, [], 2);
case 'max'
level(:,i) = max(dat, [], 2);
case 'maxabs'
level(:,i) = max(abs(dat), [], 2);
case 'range'
level(:,i) = max(dat, [], 2) - min(dat, [], 2);
case 'kurtosis'
level(:,i) = kurtosis(dat, [], 2);
case '1/var'
level(:,i) = 1./(std(dat, [], 2).^2);
case 'zvalue'
level(:,i) = mean( ( dat-repmat(mval,1,size(dat,2)) )./repmat(sd,1,size(dat,2)) ,2);
case 'maxzvalue'
level(:,i) = max( ( dat-repmat(mval,1,size(dat,2)) )./repmat(sd,1,size(dat,2)) , [], 2);
otherwise
error('unsupported method');
end
end
ft_progress('close');
update_log(info.output_box,'Done.');
% if metric calculated with channels off, then turning that channel on
% won't show anything. Because of this, keep track of which channels were
% off when calculated, so know when to recalculate.
info.metric_chansel = info.chansel;
% % reinsert the data for the selected channels
% dum = nan(info.nchan, info.ntrl);
% dum(info.chansel,:) = level;
% origlevel = dum;
% clear dum
% % store original levels for later
% info.origlevel = origlevel;
info.level = level;
guidata(h,info);
function redraw(h)
info = guidata(h);
% work with a copy of the data
level = info.level;
level(~info.chansel,:) = nan;
level(:,~info.trlsel) = nan;
[maxperchan maxpertrl maxperchan_all maxpertrl_all] = set_maxper(level, info.chansel, info.trlsel);
% make the three figures
if gcf~=h, figure(h); end
%datacursormode on;
set(h,'CurrentAxes',info.axes(1))
cla(info.axes(1));
% imagesc(level(chansel, trlsel));
imagesc(level);
axis xy;
% colorbar;
title(info.cfg.method);
ylabel('channel number');
xlabel('trial number');
set(h,'CurrentAxes',info.axes(2))
cla(info.axes(2));
set(info.axes(2),'ButtonDownFcn',@toggle_visual);
plot(maxperchan(info.chansel==1), find(info.chansel==1), '.');
if strcmp(info.cfg.viewmode, 'toggle') && (sum(info.chansel==0) > 0)
hold on;
plot(maxperchan_all(info.chansel==0), find(info.chansel==0), 'o');
hold off;
end
abc = axis;
axis([abc(1:2) 0 info.nchan]); % have to use 0 as lower limit because ylim([1 1]) (i.e. the single-channel case) is invalid
set(info.axes(2),'ButtonDownFcn',@toggle_visual); % needs to be here; call to axis resets this property
ylabel('channel number');
set(h,'CurrentAxes',info.axes(3))
cla(info.axes(3));
plot(find(info.trlsel==1), maxpertrl(info.trlsel==1), '.');
if strcmp(info.cfg.viewmode, 'toggle') && (sum(info.trlsel==0) > 0)
hold on;
plot(find(info.trlsel==0), maxpertrl_all(info.trlsel==0), 'o');
hold off;
end
abc = axis; axis([1 info.ntrl abc(3:4)]);
set(info.axes(3),'ButtonDownFcn',@toggle_visual); % needs to be here; call to axis resets this property
xlabel('trial number');
% put rejected trials/channels in their respective edit boxes
set(info.badchanlbl,'string',sprintf('Rejected channels: %i/%i',sum(info.chansel==0),info.nchan));
set(info.badtrllbl, 'string',sprintf('Rejected trials: %i/%i',sum(info.trlsel==0), info.ntrl));
if ~isempty(find(info.trlsel==0, 1))
set(info.badtrltxt,'String',num2str(find(info.trlsel==0)),'FontAngle','normal');
else
set(info.badtrltxt,'String','No trials rejected','FontAngle','italic');
end
if ~isempty(find(info.chansel==0, 1))
if isfield(info.data,'label')
chanlabels = info.data.label(info.chansel==0);
badchantxt = '';
for i=find(info.chansel==0)
if ~isempty(badchantxt)
badchantxt = [badchantxt ', ' info.data.label{i} '(' num2str(i) ')'];
else
badchantxt = [info.data.label{i} '(' num2str(i) ')'];
end
end
set(info.badchantxt,'String',badchantxt,'FontAngle','normal');
else
set(info.badtrltxt,'String',num2str(find(info.chansel==0)),'FontAngle','normal');
end
else
set(info.badchantxt,'String','No channels rejected','FontAngle','italic');
end
function toggle_trials(h, eventdata)
info = guidata(h);
% extract trials from string
rawtrls = get(h,'string');
if ~isempty(rawtrls)
spltrls = regexp(rawtrls,'\s+','split');
trls = [];
for n = 1:length(spltrls)
trls(n) = str2num(cell2mat(spltrls(n)));
end
else
update_log(info.output_box,sprintf('Please enter one or more trials'));
uiresume;
return;
end
toggle = trls;
try
info.trlsel(toggle) = ~info.trlsel(toggle);
catch
update_log(info.output_box,sprintf('ERROR: Trial value too large!'));
end
guidata(h, info);
uiresume;
% process input from the "toggle channels" textbox
function toggle_channels(h, eventdata)
info = guidata(h);
rawchans = get(h,'string');
if ~isempty(rawchans)
splchans = regexp(rawchans,'\s+','split');
chans = zeros(1,length(splchans));
% determine whether identifying channels via number or label
[junk junk junk procchans] = regexp(rawchans,'([A-Za-z]+|[0-9]{4,})');
clear junk;
if isempty(procchans)
% if using channel numbers
for n = 1:length(splchans)
chans(n) = str2num(splchans{n});
end
else
% if using channel labels
for n = 1:length(splchans)
try
chans(n) = find(ismember(info.data.label,splchans(n)));
catch
update_log(info.output_box,sprintf('ERROR: Please ensure the channel name is correct (case-sensitive)!'));
uiresume;
return;
end
end
end
else
update_log(info.output_box,sprintf('Please enter one or more channels'));
uiresume;
return;
end
toggle = chans;
try
info.chansel(toggle) = ~info.chansel(toggle);
% if levels data from channel being toggled was calculated from another
% metric, recalculate the metric
if info.metric_chansel(toggle) == 0
compute_metric(h)
end
catch
update_log(info.output_box,sprintf('ERROR: Channel value too large!'));
end
guidata(h, info);
uiresume;
function toggle_visual(h, eventdata)
% copied from select2d, without waitforbuttonpress command
point1 = get(gca,'CurrentPoint'); % button down detected
finalRect = rbbox; % return figure units
point2 = get(gca,'CurrentPoint'); % button up detected
point1 = point1(1,1:2); % extract x and y
point2 = point2(1,1:2);
x = sort([point1(1) point2(1)]);
y = sort([point1(2) point2(2)]);
g = get(gca,'Parent');
info = guidata(g);
[maxperchan maxpertrl] = set_maxper(info.level, info.chansel, info.trlsel);
% toggle channels
if gca == info.axes(2)
% if strcmp(info.cfg.viewmode, 'toggle')
chanlabels = 1:info.nchan;
% else
% perchan = max(info.level,[],2);
% maxperchan = perchan(info.chansel==1);
% chanlabels = find(info.chansel==1);
% end
toggle = find( ...
chanlabels >= y(1) & ...
chanlabels <= y(2) & ...
maxperchan(:)' >= x(1) & ...
maxperchan(:)' <= x(2));
info.chansel(toggle) = 0;
% if levels data from channel being toggled was calculated from another
% metric, recalculate the metric
if info.metric_chansel(toggle) == 0
compute_metric(h)
end
% toggle trials
elseif gca == info.axes(3)
% if strcmp(info.cfg.viewmode, 'toggle')
trllabels = 1:info.ntrl;
% else
% pertrl = max(info.level,[],1);
% maxpertrl = pertrl(info.trlsel==1);
% trllabels = find(info.trlsel==1);
% end
toggle = find( ...
trllabels >= x(1) & ...
trllabels <= x(2) & ...
maxpertrl(:)' >= y(1) & ...
maxpertrl(:)' <= y(2));
info.trlsel(toggle) = 0;
end
guidata(h, info);
uiresume;
% function display_trial(h, eventdata)
% info = guidata(h);
% rawtrls = get(h,'string');
% if ~isempty(rawtrls)
% spltrls = regexp(rawtrls,' ','split');
% trls = [];
% for n = 1:length(spltrls)
% trls(n) = str2num(cell2mat(spltrls(n)));
% end
% else
% update_log(info.output_box,sprintf('Please enter one or more trials'));
% uiresume;
% return;
% end
% if all(trls==0)
% % use visual selection
% update_log(info.output_box,sprintf('make visual selection of trials to be plotted seperately...'));
% [x, y] = select2d;
% maxpertrl = max(info.origlevel,[],1);
% toggle = find(1:ntrl>=x(1) & ...
% 1:ntrl<=x(2) & ...
% maxpertrl(:)'>=y(1) & ...
% maxpertrl(:)'<=y(2));
% else
% toggle = trls;
% end
% for i=1:length(trls)
% figure
% % the data being displayed here is NOT filtered
% %plot(data.time{toggle(i)}, data.trial{toggle(i)}(chansel,:));
% tmp = info.data.trial{toggle(i)}(info.chansel,:);
% tmp = tmp - repmat(mean(tmp,2), [1 size(tmp,2)]);
% plot(info.data.time{toggle(i)}, tmp);
% title(sprintf('trial %d', toggle(i)));
% end
function quit(h, eventdata)
info = guidata(h);
info.quit = 1;
guidata(h, info);
uiresume;
function change_metric(h, eventdata)
info = guidata(h);
info.metric = get(eventdata.NewValue, 'string');
guidata(h, info);
compute_metric(h);
uiresume;
function toggle_rejected(h, eventdata)
info = guidata(h);
toggle = get(h,'value');
if toggle == 0
info.cfg.viewmode = 'remove';
else
info.cfg.viewmode = 'toggle';
end
guidata(h, info);
uiresume;
function update_log(h, new_text)
new_text = [datestr(now,13) '# ' new_text];
curr_text = get(h, 'string');
size_curr_text = size(curr_text,2);
size_new_text = size(new_text,2);
if size_curr_text > size_new_text
new_text = [new_text blanks(size_curr_text-size_new_text)];
else
curr_text = [curr_text repmat(blanks(size_new_text-size_curr_text), size(curr_text,1), 1)];
end
set(h, 'String', [new_text; curr_text]);
drawnow;
function [maxperchan,maxpertrl,varargout] = set_maxper(level,chansel,trlsel)
level_all = level;
% determine the maximum value
level(~chansel,:) = nan;
level(:,~trlsel) = nan;
maxperchan = max(level,[],2);
maxpertrl = max(level,[],1);
maxperchan_all = max(level_all,[],2);
maxpertrl_all = max(level_all,[],1);
varargout(1) = {maxperchan_all};
varargout(2) = {maxpertrl_all};
function display_trial(h, eventdata)
info = guidata(h);
rawtrls = get(h,'string');
if isempty(rawtrls)
return;
else
spltrls = regexp(rawtrls,'\s+','split');
trls = [];
for n = 1:length(spltrls)
trls(n) = str2num(cell2mat(spltrls(n)));
end
end
cfg_mp = [];
cfg_mp.layout = info.cfg.layout;
cfg_mp.channel = info.data.label(info.chansel);
currfig = gcf;
for n = 1:length(trls)
figure()
cfg_mp.trials = trls(n);
cfg_mp.interactive = 'yes';
ft_multiplotER(cfg_mp, info.data);
title(sprintf('Trial %i',trls(n)));
end
figure(currfig);
return;
|
github
|
philippboehmsturm/antx-master
|
warning_once.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/warning_once.m
| 3,832 |
utf_8
|
07dc728273934663973f4c716e7a3a1c
|
function [ws warned] = warning_once(varargin)
%
% Use as one of the following
% warning_once(string)
% warning_once(string, timeout)
% warning_once(id, string)
% warning_once(id, string, timeout)
% where timeout should be inf if you don't want to see the warning ever
% again. The default timeout value is 60 seconds.
%
% It can be used instead of the MATLAB built-in function WARNING, thus as
% s = warning_once(...)
% or as
% warning_once(s)
% where s is a structure with fields 'identifier' and 'state', storing the
% state information. In other words, warning_once accepts as an input the
% same structure it returns as an output. This returns or restores the
% states of warnings to their previous values.
%
% It can also be used as
% [s w] = warning_once(...)
% where w is a boolean that indicates whether a warning as been thrown or not.
%
% Please note that you can NOT use it like this
% warning_once('the value is %d', 10)
% instead you should do
% warning_once(sprintf('the value is %d', 10))
% Copyright (C) 2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: warning_once.m 7123 2012-12-06 21:21:38Z roboos $
persistent stopwatch previous
if nargin < 1
error('You need to specify at least a warning message');
end
warned = false;
if isstruct(varargin{1})
warning(varargin{1});
return;
end
% put the arguments we will pass to warning() in this cell array
warningArgs = {};
if nargin==3
% calling syntax (id, msg, timeout)
warningArgs = varargin(1:2);
timeout = varargin{3};
fname = [warningArgs{1} '_' warningArgs{2}];
elseif nargin==2 && isnumeric(varargin{2})
% calling syntax (msg, timeout)
warningArgs = varargin(1);
timeout = varargin{2};
fname = warningArgs{1};
elseif nargin==2 && ~isnumeric(varargin{2})
% calling syntax (id, msg)
warningArgs = varargin(1:2);
timeout = 60;
fname = [warningArgs{1} '_' warningArgs{2}];
elseif nargin==1
% calling syntax (msg)
warningArgs = varargin(1);
timeout = 60; % default timeout in seconds
fname = [warningArgs{1}];
end
if isempty(timeout)
error('Timeout ill-specified');
end
if isempty(stopwatch)
stopwatch = tic;
end
if isempty(previous)
previous = struct;
end
now = toc(stopwatch); % measure time since first function call
fname = decomma(fixname(fname)); % make a nice string that is allowed as structure fieldname
if length(fname) > 63 % MATLAB max name
fname = fname(1:63);
end
if ~isfield(previous, fname) || ...
(isfield(previous, fname) && now>previous.(fname).timeout)
% warning never given before or timed out
ws = warning(warningArgs{:});
previous.(fname).timeout = now+timeout;
previous.(fname).ws = ws;
warned = true;
else
% the warning has been issued before, but has not timed out yet
ws = previous.(fname).ws;
end
end % function
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% helper functions
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function name = decomma(name)
name(name==',')=[];
end % function
|
github
|
philippboehmsturm/antx-master
|
rejectvisual_channel.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/rejectvisual_channel.m
| 10,456 |
utf_8
|
774bc8d49d85b915def3a1c7e08ec8e5
|
function [chansel, trlsel, cfg] = rejectvisual_channel(cfg, data);
% SUBFUNCTION for rejectvisual
% Copyright (C) 2006, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: rejectvisual_channel.m 7123 2012-12-06 21:21:38Z roboos $
% determine the initial selection of trials and channels
nchan = length(data.label);
ntrl = length(data.trial);
cfg.channel = ft_channelselection(cfg.channel, data.label);
trlsel = logical(ones(1,ntrl));
chansel = logical(zeros(1,nchan));
chansel(match_str(data.label, cfg.channel)) = 1;
% remove all non-wanted channels
nchan = sum(chansel);
data = ft_selectdata(data, 'channel', cfg.channel);
% compute the sampling frequency from the first two timepoints
fsample = 1/mean(diff(data.time{1}));
% compute the offset from the time axes
offset = zeros(ntrl,1);
for i=1:ntrl
offset(i) = time2offset(data.time{i}, fsample);
end
if (isfield(cfg, 'preproc') && ~isempty(cfg.preproc))
ft_progress('init', cfg.feedback, 'filtering data');
for i=1:ntrl
ft_progress(i/ntrl, 'filtering data in trial %d of %d\n', i, ntrl);
[data.trial{i}, label, time, cfg.preproc] = preproc(data.trial{i}, data.label, data.time{i}, cfg.preproc);
end
ft_progress('close');
end
% select the specified latency window from the data
% this is done AFTER the filtering to prevent edge artifacts
for i=1:ntrl
begsample = nearest(data.time{i}, cfg.latency(1));
endsample = nearest(data.time{i}, cfg.latency(2));
data.time{i} = data.time{i}(begsample:endsample);
data.trial{i} = data.trial{i}(:,begsample:endsample);
end
h = figure;
axis([0 1 0 1]);
axis off
% the info structure will be attached to the figure
% and passed around between the callback functions
if strcmp(cfg.plotlayout,'1col') % hidden config option for plotting trials differently
info = [];
info.ncols = 1;
info.nrows = ntrl;
info.trlop = 1;
info.chanlop = 1;
info.lchanlop= 0;
info.quit = 0;
info.ntrl = ntrl;
info.nchan = nchan;
info.data = data;
info.cfg = cfg;
info.offset = offset;
info.chansel = chansel;
info.trlsel = trlsel;
% determine the position of each subplot within the axis
for row=1:info.nrows
for col=1:info.ncols
indx = (row-1)*info.ncols + col;
if indx>info.ntrl
continue
end
info.x(indx) = (col-0.9)/info.ncols;
info.y(indx) = 1 - (row-0.45)/(info.nrows+1);
info.label{indx} = sprintf('trial %03d', indx);
end
end
elseif strcmp(cfg.plotlayout,'square')
info = [];
info.ncols = ceil(sqrt(ntrl));
info.nrows = ceil(sqrt(ntrl));
info.trlop = 1;
info.chanlop = 1;
info.lchanlop= 0;
info.quit = 0;
info.ntrl = ntrl;
info.nchan = nchan;
info.data = data;
info.cfg = cfg;
info.offset = offset;
info.chansel = chansel;
info.trlsel = trlsel;
% determine the position of each subplot within the axis
for row=1:info.nrows
for col=1:info.ncols
indx = (row-1)*info.ncols + col;
if indx>info.ntrl
continue
end
info.x(indx) = (col-0.9)/info.ncols;
info.y(indx) = 1 - (row-0.45)/(info.nrows+1);
info.label{indx} = sprintf('trial %03d', indx);
end
end
end
info.ui.quit = uicontrol(h,'units','pixels','position',[ 5 5 40 18],'String','quit','Callback',@stop);
info.ui.prev = uicontrol(h,'units','pixels','position',[ 50 5 25 18],'String','<','Callback',@prev);
info.ui.next = uicontrol(h,'units','pixels','position',[ 75 5 25 18],'String','>','Callback',@next);
info.ui.prev10 = uicontrol(h,'units','pixels','position',[105 5 25 18],'String','<<','Callback',@prev10);
info.ui.next10 = uicontrol(h,'units','pixels','position',[130 5 25 18],'String','>>','Callback',@next10);
info.ui.bad = uicontrol(h,'units','pixels','position',[160 5 50 18],'String','bad','Callback',@markbad);
info.ui.good = uicontrol(h,'units','pixels','position',[210 5 50 18],'String','good','Callback',@markgood);
info.ui.badnext = uicontrol(h,'units','pixels','position',[270 5 50 18],'String','bad>','Callback',@markbad_next);
info.ui.goodnext = uicontrol(h,'units','pixels','position',[320 5 50 18],'String','good>','Callback',@markgood_next);
set(gcf, 'WindowButtonUpFcn', @button);
set(gcf, 'KeyPressFcn', @key);
guidata(h,info);
interactive = 1;
while interactive && ishandle(h)
redraw(h);
info = guidata(h);
if info.quit == 0,
uiwait;
else
chansel = info.chansel;
trlsel = info.trlsel;
delete(h);
break
end
end % while interactive
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTIONS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function varargout = markbad_next(varargin)
markbad(varargin{:});
next(varargin{:});
function varargout = markgood_next(varargin)
markgood(varargin{:});
next(varargin{:});
function varargout = next(h, eventdata, handles, varargin)
info = guidata(h);
info.lchanlop = info.chanlop;
if info.chanlop < info.nchan,
info.chanlop = info.chanlop + 1;
end;
guidata(h,info);
uiresume;
function varargout = prev(h, eventdata, handles, varargin)
info = guidata(h);
info.lchanlop = info.chanlop;
if info.chanlop > 1,
info.chanlop = info.chanlop - 1;
end;
guidata(h,info);
uiresume;
function varargout = next10(h, eventdata, handles, varargin)
info = guidata(h);
info.lchanlop = info.chanlop;
if info.chanlop < info.nchan - 10,
info.chanlop = info.chanlop + 10;
else
info.chanlop = info.nchan;
end;
guidata(h,info);
uiresume;
function varargout = prev10(h, eventdata, handles, varargin)
info = guidata(h);
info.lchanlop = info.chanlop;
if info.chanlop > 10,
info.chanlop = info.chanlop - 10;
else
info.chanlop = 1;
end;
guidata(h,info);
uiresume;
function varargout = markgood(h, eventdata, handles, varargin)
info = guidata(h);
info.chansel(info.chanlop) = 1;
fprintf(description_channel(info));
title(description_channel(info));
guidata(h,info);
% uiresume;
function varargout = markbad(h, eventdata, handles, varargin)
info = guidata(h);
info.chansel(info.chanlop) = 0;
fprintf(description_channel(info));
title(description_channel(info));
guidata(h,info);
% uiresume;
function varargout = key(h, eventdata, handles, varargin)
info = guidata(h);
switch lower(eventdata.Key)
case 'rightarrow'
if info.chanlop ~= info.nchan
next(h);
else
fprintf('at last channel\n');
end
case 'leftarrow'
if info.chanlop ~= 1
prev(h);
else
fprintf('at last channel\n');
end
case 'g'
markgood(h);
case 'b'
markbad(h);
case 'q'
stop(h);
otherwise
fprintf('unknown key pressed\n');
end
function varargout = button(h, eventdata, handles, varargin)
pos = get(gca, 'CurrentPoint');
x = pos(1,1);
y = pos(1,2);
info = guidata(h);
dx = info.x - x;
dy = info.y - y;
dd = sqrt(dx.^2 + dy.^2);
[d, i] = min(dd);
if d<0.5/max(info.nrows, info.ncols) && i<=info.ntrl
info.trlsel(i) = ~info.trlsel(i); % toggle
info.trlop = i;
fprintf(description_trial(info));
guidata(h,info);
uiresume;
else
fprintf('button clicked\n');
return
end
function varargout = stop(h, eventdata, handles, varargin)
info = guidata(h);
info.quit = 1;
guidata(h,info);
uiresume;
function str = description_channel(info);
if info.chansel(info.chanlop)
str = sprintf('channel %s marked as GOOD\n', info.data.label{info.chanlop});
else
str = sprintf('channel %s marked as BAD\n', info.data.label{info.chanlop});
end
function str = description_trial(info);
if info.trlsel(info.trlop)
str = sprintf('trial %d marked as GOOD\n', info.trlop);
else
str = sprintf('trial %d marked as BAD\n', info.trlop);
end
function redraw(h)
if ~ishandle(h)
return
end
info = guidata(h);
fprintf(description_channel(info));
cla;
title('');
drawnow
hold on
% determine the maximum value for this channel over all trials
amax = -inf;
tmin = inf;
tmax = -inf;
for trlindx=find(info.trlsel)
tmin = min(info.data.time{trlindx}(1) , tmin);
tmax = max(info.data.time{trlindx}(end), tmax);
amax = max(max(abs(info.data.trial{trlindx}(info.chanlop,:))), amax);
end
if ~isempty(info.cfg.alim)
% use fixed amplitude limits for the amplitude scaling
amax = info.cfg.alim;
end
for row=1:info.nrows
for col=1:info.ncols
trlindx = (row-1)*info.ncols + col;
if trlindx>info.ntrl || ~info.trlsel(trlindx)
continue
end
% scale the time values between 0.1 and 0.9
time = info.data.time{trlindx};
time = 0.1 + 0.8*(time-tmin)/(tmax-tmin);
% scale the amplitude values between -0.5 and 0.5, offset should not be removed
dat = info.data.trial{trlindx}(info.chanlop,:);
dat = dat ./ (2*amax);
% scale the time values for this subplot
tim = (col-1)/info.ncols + time/info.ncols;
% scale the amplitude values for this subplot
amp = dat./info.nrows + 1 - row/(info.nrows+1);
plot(tim, amp, 'k')
end
end
% enable or disable buttons as appropriate
if info.chanlop == 1
set(info.ui.prev, 'Enable', 'off');
set(info.ui.prev10, 'Enable', 'off');
else
set(info.ui.prev, 'Enable', 'on');
set(info.ui.prev10, 'Enable', 'on');
end
if info.chanlop == info.nchan
set(info.ui.next, 'Enable', 'off');
set(info.ui.next10, 'Enable', 'off');
else
set(info.ui.next, 'Enable', 'on');
set(info.ui.next10, 'Enable', 'on');
end
if info.lchanlop == info.chanlop && info.chanlop == info.nchan
set(info.ui.badnext,'Enable', 'off');
set(info.ui.goodnext,'Enable', 'off');
else
set(info.ui.badnext,'Enable', 'on');
set(info.ui.goodnext,'Enable', 'on');
end
text(info.x, info.y, info.label);
title(description_channel(info));
hold off
|
github
|
philippboehmsturm/antx-master
|
triangulate_seg.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/triangulate_seg.m
| 4,749 |
utf_8
|
43f67dbe00353d8bb75b709aa97d7ce0
|
function [pnt, tri] = triangulate_seg(seg, npnt, origin)
% TRIANGULATE_SEG constructs a triangulation of the outer surface of a
% segmented volume. It starts at the center of the volume and projects the
% vertices of an evenly triangulated sphere onto the outer surface. The
% resulting surface is star-shaped from the origin of the sphere.
%
% Use as
% [pnt, tri] = triangulate_seg(seg, npnt, origin)
%
% Input arguments:
% seg = 3D-matrix (boolean) containing segmented volume. If not boolean
% seg = seg(~=0);
% npnt = requested number of vertices
% origin = 1x3 vector specifying the location of the origin of the sphere
% in voxel indices. This argument is optional. If undefined, the
% origin of the sphere will be in the centre of the volume.
%
% Output arguments:
% pnt = Nx3 matrix of vertex locations
% tri = Mx3 matrix of triangles
%
% Seg will be checked for holes, and filled if necessary. Also, seg will be
% checked to consist of a single boolean blob. If not, only the outer surface
% of the largest will be triangulated. SPM is used for both the filling and
% checking for multiple blobs.
%
% See also KSPHERE
% Copyright (C) 2005-2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: triangulate_seg.m 7123 2012-12-06 21:21:38Z roboos $
% impose it to be boolean
seg = (seg~=0);
dim = size(seg);
len = ceil(sqrt(sum(dim.^2))/2);
if ~any(seg(:))
error('the segmentation is empty')
end
% define the origin if it is not provided in the input arguments
if nargin<3
origin(1) = dim(1)/2;
origin(2) = dim(2)/2;
origin(3) = dim(3)/2;
end
% ensure that the seg consists of only one filled blob.
% if not filled: throw a warning and fill
% if more than one blob: throw a warning and use the biggest
ft_hastoolbox('SPM8', 1);
% look for holes
seg = volumefillholes(seg);
% look for >1 blob
[lab, num] = spm_bwlabel(double(seg), 26);
if num>1,
warning('the segmented volume consists of more than one compartment, using only the biggest one for the segmentation');
for k = 1:num
n(k) = sum(lab(:)==k);
end
[m,ix] = max(n);
seg(lab~=ix) = false;
end
% start with a unit sphere with evenly distributed vertices
[pnt, tri] = ksphere(npnt);
ishollow = false;
for i=1:npnt
% construct a sampled line from the center of the volume outward into the direction of the vertex
lin = (0:0.5:len)' * pnt(i,:);
lin(:,1) = lin(:,1) + origin(1);
lin(:,2) = lin(:,2) + origin(2);
lin(:,3) = lin(:,3) + origin(3);
% round the sampled line towards the nearest voxel indices, which allows
% a quick nearest-neighbour interpolation/lookup
lin = round(lin);
% exclude indices that do not lie within the volume
sel = lin(:,1)<1 | lin(:,1)>dim(1) | ...
lin(:,2)<1 | lin(:,2)>dim(2) | ...
lin(:,3)<1 | lin(:,3)>dim(3);
lin = lin(~sel,:);
sel = sub2ind(dim, lin(:,1), lin(:,2), lin(:,3));
% interpolate the segmented volume along the sampled line
int = seg(sel);
% the value along the line is expected to be 1 at first and then drop to 0
% anything else suggests that the segmentation is hollow
ishollow = any(diff(int)==1);
% find the last sample along the line that is inside the segmentation
sel = find(int, 1, 'last');
% this is a problem if sel is empty. If so, use the edge of the volume
if ~isempty(sel)
% take the last point inside and average with the first point outside
pnt(i,:) = lin(sel,:);
else
% take the edge
pnt(i,:) = lin(end,:);
end
end
if ishollow
% this should not have hapened, especially not after filling the holes
warning('the segmentation is not star-shaped, please check the surface mesh');
end
% undo the shift of the origin from where the projection is done
% pnt(:,1) = pnt(:,1) - origin(1);
% pnt(:,2) = pnt(:,2) - origin(2);
% pnt(:,3) = pnt(:,3) - origin(3);
% fast unconditional re-implementation of the standard Matlab function
function [s] = sub2ind(dim, i, j, k)
s = i + (j-1)*dim(1) + (k-1)*dim(1)*dim(2);
|
github
|
philippboehmsturm/antx-master
|
browse_simpleFFT.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/browse_simpleFFT.m
| 3,848 |
utf_8
|
8a1561f6249a7c96e15d8a38485f6df3
|
function browse_simpleFFT(cfg, data)
% BROWSE_SIMPLEFFT is a helper function for FT_DATABROWSER that shows a
% simple FFT of the data.
%
% Included are a button to switch between log and non-log space, and a selection button to deselect channels,
% for the purpose of zooming in on bad channels.
%
%
%
% See also BROWSE_MOVIEPLOTER, BROWSE_TOPOPLOTER, BROWSE_MULTIPLOTER, BROWSE_TOPOPLOTVAR, BROWSE_SIMPLEFFT
% Copyright (C) 2011, Roemer van der Meij
% call ft_freqanalysis on data
cfgfreq = [];
cfgfreq.method = 'mtmfft';
cfgfreq.taper = 'boxcar';
freqdata = ft_freqanalysis(cfgfreq,data);
% remove zero-bin for plotting
if freqdata.freq(1) == 0
freqdata.freq = freqdata.freq(2:end);
freqdata.powspctrm = freqdata.powspctrm(:,2:end);
end
%%% FIXME: call ft_singleplotER for everything below
% make figure window for fft
ffth = figure('name',cfg.figurename,'numbertitle','off','units','normalized');
% set button
butth = uicontrol('tag', 'simplefft_l2', 'parent', ffth, 'units', 'normalized', 'style', 'checkbox', 'string','log10 of power','position', [0.87, 0.6 , 0.12, 0.05], 'value',1,'callback',{@draw_simple_fft_cb},'backgroundcolor',[.8 .8 .8]);
uicontrol('tag', 'simplefft_l2_chansel', 'parent', ffth, 'units', 'normalized', 'style', 'pushbutton', 'string','select channels','position', [0.87, 0.45 , 0.12, 0.10],'callback',{@selectchan_fft_cb});
% put dat in fig (sparse)
fftopt = [];
fftopt.freqdata = freqdata;
fftopt.chancolors = cfg.chancolors;
fftopt.chansel = 1:numel(data.label);
fftopt.butth = butth;
setappdata(ffth, 'fftopt', fftopt);
% draw fig
draw_simple_fft_cb(butth)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function selectchan_fft_cb(h,eventdata)
ffth = get(h,'parent');
fftopt = getappdata(ffth, 'fftopt');
% open chansel dialog
chansel = select_channel_list(fftopt.opt.freq.label, fftopt.chansel, 'select channels for viewing power');
% output data
fftopt.chansel = chansel;
setappdata(ffth, 'fftopt', fftopt);
draw_simple_fft_cb(fftopt.butth)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function draw_simple_fft_cb(h,eventdata)
togglestate = get(h,'value');
ffth = get(h,'parent');
fftopt = getappdata(ffth, 'fftopt');
% clear axis (for switching)
cla
% switch log10 or nonlog10
if togglestate == 0
dat = fftopt.freqdata.powspctrm;
elseif togglestate == 1
dat = log10(fftopt.freqdata.powspctrm);
end
% select data and chanel colors
chancolors = fftopt.chancolors(fftopt.chansel,:);
dat = dat(fftopt.chansel,:);
% plot using specified colors
set(0,'currentFigure',ffth)
for ichan = 1:size(dat,1)
color = chancolors(ichan,:);
ft_plot_vector(fftopt.freqdata.freq, dat(ichan,:), 'box', false, 'color', color)
end
ylabel('log10(power)')
xlabel('frequency (hz)')
yrange = abs(max(max(dat)) - min(min(dat)));
axis([fftopt.freqdata.freq(1) fftopt.freqdata.freq(end) (min(min(dat)) - yrange.*.1) (max(max(dat)) + yrange*.1)])
% switch log10 or nonlog10
if togglestate == 0
ylabel('power')
axis([fftopt.freqdata.freq(1) fftopt.freqdata.freq(end) 0 (max(max(dat)) + yrange*.1)])
elseif togglestate == 1
ylabel('log10(power)')
axis([fftopt.freqdata.freq(1) fftopt.freqdata.freq(end) (min(min(dat)) - yrange.*.1) (max(max(dat)) + yrange*.1)])
end
set(gca,'Position', [0.13 0.11 0.725 0.815])
|
github
|
philippboehmsturm/antx-master
|
prepare_mesh_manual.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/prepare_mesh_manual.m
| 29,475 |
utf_8
|
0d8c0801202308a5c8afddd585a4e695
|
function bnd = prepare_mesh_manual(cfg, mri)
% PREPARE_MESH_MANUAL is called by PREPARE_MESH and opens a GUI to manually
% select points/polygons in an mri dataset.
%
% It allows:
% Visualization of 3d data in 3 different projections
% Adjustment of brightness for every slice
% Storage of the data points in an external .mat file
% Retrieval of previously saved data points
% Slice fast scrolling with keyboard arrows
% Polygons or points selection/deselection
%
% See also PREPARE_MESH_SEGMENTATION, PREPARE_MESH_HEADSHAPE
% Copyrights (C) 2009, Cristiano Micheli & Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: prepare_mesh_manual.m 7123 2012-12-06 21:21:38Z roboos $
% FIXME: control slice's cmap referred to abs values
% FIXME: clean structure slicedata
% FIXME: check function assign3dpoints
global obj
bnd.pnt = [];
bnd.tri = [];
hasheadshape = isfield(cfg, 'headshape');
hasbnd = isfield(cfg, 'bnd'); % FIXME why is this in cfg?
hasmri = nargin>1;
% check the consistency of the input arguments
if hasheadshape && hasbnd
error('you should not specify cfg.headshape and cfg.bnd simultaneously');
end
% check the consistency of the input arguments
if ~hasmri
% FIXME give a warning or so?
mri.anatomy = [];
mri.transform = eye(4);
else
% ensure that it is double precision
mri.anatomy = double(mri.anatomy);
end
if hasheadshape
if ~isempty(cfg.headshape)
% get the surface describing the head shape
if isstruct(cfg.headshape) && isfield(cfg.headshape, 'pnt')
% use the headshape surface specified in the configuration
headshape = cfg.headshape;
elseif isnumeric(cfg.headshape) && size(cfg.headshape,2)==3
% use the headshape points specified in the configuration
headshape.pnt = cfg.headshape;
elseif ischar(cfg.headshape)
% read the headshape from file
headshape = read_headshape(cfg.headshape);
else
headshape = [];
end
if ~isfield(headshape, 'tri')
for i=1:length(headshape)
% generate a closed triangulation from the surface points
headshape(i).pnt = unique(headshape(i).pnt, 'rows');
headshape(i).tri = projecttri(headshape(i).pnt);
end
end
% start with the headshape
bnd = headshape;
end
elseif hasbnd
if ~isempty(cfg.bnd)
% start with the prespecified boundaries
bnd = cfg.bnd;
end
else
% start with an empty boundary if not specified
bnd.pnt = [];
bnd.tri = [];
end
% creating the GUI
fig = figure;
% initialize some values
slicedata = []; points = bnd.pnt;
axs = floor(size(mri.anatomy,1)/2);
% initialize properties
set(fig, 'KeyPressFcn',@keypress);
set(fig, 'CloseRequestFcn', @cb_close);
setappdata(fig,'data',mri.anatomy);
setappdata(fig,'prop',{1,axs,0,[]});
setappdata(fig,'slicedata',slicedata);
setappdata(fig,'points',points);
setappdata(fig,'box',[]);
% add GUI elements
cb_creategui(gca);
cb_redraw(gca);
waitfor(fig);
% close sequence
global pnt
try
tmp = pnt;
clear global pnt
pnt = tmp;
clear tmp
[tri] = projecttri(pnt);
bnd.pnt = pnt;
bnd.tri = tri;
catch
bnd.pnt = [];
bnd.tri = [];
end
function cb_redraw(hObject, eventdata, handles);
fig = get(hObject, 'parent');
prop = getappdata(fig,'prop');
data = getappdata(fig,'data');
slicedata = getappdata(fig,'slicedata');
points = getappdata(fig,'points');
% draw image
try
cla
% i,j,k axes
if (prop{1}==1) %jk
imh=imagesc(squeeze(data(prop{2},:,:)));
xlabel('k');
ylabel('j');
colormap bone
elseif (prop{1}==2) %ik
imh=imagesc(squeeze(data(:,prop{2},:)));
xlabel('k');
ylabel('i');
colormap bone
elseif (prop{1}==3) %ij
imh=imagesc(squeeze(data(:,:,prop{2})));
xlabel('j');
ylabel('i');
colormap bone
end
axis equal; axis tight
brighten(prop{3});
title([ 'slice ' num2str(prop{2}) ])
catch
end
if ~ishold,hold on,end
% draw points and lines
for zz = 1:length(slicedata)
if(slicedata(zz).proj==prop{1})
if(slicedata(zz).slice==prop{2})
polygon = slicedata(zz).polygon;
for kk=1:length(polygon)
if ~isempty(polygon{kk})
[xs,ys]=deal(polygon{kk}(:,1),polygon{kk}(:,2));
plot(xs, ys, 'g.-');
end
end
end
end
end % end for
% draw other slices points
points = getappdata(fig,'points');
pnts = round(points);
if ~isempty(pnts)
% exclude polygons inside the same slice
indx = find(points(:,prop{1})==prop{2});
tmp = ones(1,size(points,1));
tmp(indx) = 0;
pnts = points(find(tmp),:);
% calculate indexes of other proj falling in current slice
indx2 = find(round(pnts(:,prop{1}))==prop{2});
rest = setdiff([1 2 3],prop{1});
% plot the points
for jj=1:length(indx2)
[x,y] = deal(pnts(indx2(jj),rest(1)),pnts(indx2(jj),rest(2)));
plot(y,x,'g*')
end
end
% add blue cross markers in case of box selection
box = getappdata(fig,'box');
point2mark = getappdata(fig,'point2mark');
if ~isempty(point2mark)
plot(point2mark.x,point2mark.y,'marker','+')
end
if ~isempty(box)
for kk=1:size(box,1)
proj = box(kk,1);
slice = box(kk,2);
rowmin = box(kk,3);
rowmax = box(kk,4);
colmin = box(kk,5);
colmax = box(kk,6);
aaa = get(findobj(fig, 'color', 'g'));
for ii=1:length(aaa)
if ispolygon(aaa(ii))
L = length(aaa(ii).YData);
for jj=1:L
cond = lt(aaa(ii).YData(jj),rowmax).*gt(aaa(ii).YData(jj),rowmin).* ...
lt(aaa(ii).XData(jj),colmax).*gt(aaa(ii).XData(jj),colmin);
if cond
plot(aaa(ii).XData(jj),aaa(ii).YData(jj),'marker','+')
end
end
elseif ispoint(aaa(ii))
cond = lt(aaa(ii).YData,rowmax).*gt(aaa(ii).YData,rowmin).* ...
lt(aaa(ii).XData,colmax).*gt(aaa(ii).XData,colmin);
% the test after cond takes care the box doesnt propagate in 3D
if (cond && (proj == prop{1}) && (slice == prop{2}))
plot(aaa(ii).XData,aaa(ii).YData,'marker','+')
end
end
end
end
end
if get(findobj(fig, 'tag', 'toggle axes'), 'value')
axis on
else
axis off
end
function cb_creategui(hObject, eventdata, handles)
fig = get(hObject, 'parent');
% define the position of each GUI element
position = {
[1] % view radio
[1 1] % del ins
[1] % label slice
[1 1] % slice
[1] % brightness
[1 1] % brightness
[1] % axis visible
[1 1] % view ij
[1 1] % jk ik
[1] % label mesh
[1 1] % view open mesh
[1 1] % save exit buttons
};
% define the style of each GUI element
style = {
{'radiobutton'}
{'radiobutton' 'radiobutton'}
{'text' }
{'pushbutton' 'pushbutton'}
{'text'}
{'pushbutton' 'pushbutton'}
{'checkbox'}
{'text' 'radiobutton'}
{'radiobutton' 'radiobutton'}
{'text' }
{'pushbutton' 'pushbutton'}
{'pushbutton' 'pushbutton'}
};
% define the descriptive string of each GUI element
string = {
{'View'}
{'Ins' 'Del'}
{'slice'}
{'<' '>'}
{'brightness'}
{'+' '-'}
{'axes'}
{'plane' 'jk'}
{'ik' 'ij'}
{'mesh'}
{'smooth' 'view'}
{'Cancel' 'OK'}
};
% define the value of each GUI element
prop = getappdata(fig,'prop');
value = {
{1}
{0 0}
{[]}
{[] []}
{[]}
{[] []}
{0}
{[] 1}
{0 0}
{[]}
{1 1}
{1 1}
};
% define a tag for each GUI element
tag = {
{'view'}
{'ins' 'del' }
{'slice'}
{'min' 'max'}
{'brightness'}
{'plus' 'minus'}
{'toggle axes'}
{'plane' 'one'}
{'two' 'three'}
{'mesh'}
{'smoothm' 'viewm'}
{'cancel' 'OK'}
};
% define the callback function of each GUI element
callback = {
{@which_task1}
{@which_task2 @which_task3}
{[]}
{@cb_btn @cb_btn}
{[]}
{@cb_btn @cb_btn}
{@cb_redraw}
{[] @cb_btnp1}
{@cb_btnp2 @cb_btnp3}
{[]}
{@smooth_mesh @view_mesh}
{@cancel_mesh @cb_btn}
};
visible = {
{'on'}
{'on' 'on'}
{'on'}
{'on' 'on'}
{'on'}
{'on' 'on'}
{'on'}
{'on' 'on'}
{'on' 'on'}
{'on'}
{'on' 'on'}
{'on' 'on'}
};
layoutgui(fig, [0.77 0.10 0.20 0.85], position, style, string, value, tag, callback,visible);
function h = layoutgui(fig, geometry, position, style, string, value, tag, callback,visible);
horipos = geometry(1); % lower left corner of the GUI part in the figure
vertpos = geometry(2); % lower left corner of the GUI part in the figure
width = geometry(3); % width of the GUI part in the figure
height = geometry(4); % height of the GUI part in the figure
horidist = 0.05;
vertdist = 0.05;
options = {'units', 'normalized', 'HorizontalAlignment', 'center'}; % 'VerticalAlignment', 'middle'
Nrow = size(position,1);
h = cell(Nrow,1);
for i=1:Nrow
if isempty(position{i})
continue;
end
position{i} = position{i} ./ sum(position{i});
Ncol = size(position{i},2);
ybeg = (Nrow-i )/Nrow + vertdist/2;
yend = (Nrow-i+1)/Nrow - vertdist/2;
for j=1:Ncol
xbeg = sum(position{i}(1:(j-1))) + horidist/2;
xend = sum(position{i}(1:(j ))) - horidist/2;
pos(1) = xbeg*width + horipos;
pos(2) = ybeg*height + vertpos;
pos(3) = (xend-xbeg)*width;
pos(4) = (yend-ybeg)*height;
h{i}{j} = uicontrol(fig, ...
options{:}, ...
'position', pos, ...
'style', style{i}{j}, ...
'string', string{i}{j}, ...
'tag', tag{i}{j}, ...
'value', value{i}{j}, ...
'callback', callback{i}{j}, ...
'visible', visible{i}{j} ...
);
end
end
function cb_btn(hObject, eventdata, handles)
fig = get(gca, 'parent');
prop = getappdata(fig,'prop');
slice = prop{2};
br = prop{3};
datdim = size(getappdata(fig,'data'));
% p1 = [];p2 = [];p3 = [];
p1 = get(findobj('string','jk'),'value');
p2 = get(findobj('string','ik'),'value');
p3 = get(findobj('string','ij'),'value');
set(findobj('string','-'),'Value',prop{3});
set(findobj('string','+'),'Value',prop{3});
beta = get(findobj('string','-'),'Value');
if (p1) %jk
setappdata(fig,'prop',{1,round(datdim(1)/2),br,prop{4}});
cb_redraw(gca);
elseif (p2) %ik
setappdata(fig,'prop',{2,round(datdim(2)/2),br,prop{4}});
cb_redraw(gca);
elseif (p3) %ij
setappdata(fig,'prop',{3,round(datdim(3)/2),br,prop{4}});
cb_redraw(gca);
end
if strcmp(get(hObject,'string'),'-')
beta=beta-0.05;
set(findobj('string','-'),'Value',beta);
set(findobj('string','+'),'Value',beta);
setappdata(fig,'prop',{prop{1},prop{2},beta,prop{4}});
cb_redraw(gca);
elseif strcmp(get(hObject,'string'),'+')
beta=beta+0.05;
set(findobj('string','+'),'Value',beta);
setappdata(fig,'prop',{prop{1},prop{2},beta,prop{4}});
cb_redraw(gca);
end
if strcmp(get(hObject,'string'),'<')
setappdata(fig,'prop',{prop{1},slice-1,0,prop{4}});
cb_redraw(gca);
end
if strcmp(get(hObject,'string'),'>')
setappdata(fig,'prop',{prop{1},slice+1,0,prop{4}});
cb_redraw(gca);
end
if strcmp(get(hObject,'string'),'OK')
close(fig)
end
function keypress(h, eventdata, handles, varargin)
fig = get(gca, 'parent');
prop = getappdata(fig,'prop');
dat = guidata(gcbf);
key = get(gcbf, 'CurrentCharacter');
slice = prop{2};
if key
switch key
case 28
setappdata(fig,'prop',{prop{1},slice-1,0,prop{4}});
cb_redraw(gca);
case 29
setappdata(fig,'prop',{prop{1},slice+1,0,prop{4}});
cb_redraw(gca);
otherwise
end
end
uiresume(h)
function build_polygon
fig = get(gca, 'parent');
prop = getappdata(fig,'prop');
data = getappdata(fig,'data');
ss = size(data);
proj = prop{1};
slice = prop{2};
thispolygon =1;
polygon{thispolygon} = zeros(0,2);
maskhelp = [ ...
'------------------------------------------------------------------------\n' ...
'specify polygons for masking the topographic interpolation\n' ...
'press the right mouse button to add another point to the current polygon\n' ...
'press backspace on the keyboard to remove the last point\n' ...
'press "c" on the keyboard to close this polygon and start with another\n' ...
'press "q" or ESC on the keyboard to continue\n' ...
];
again = 1;
if ~ishold,hold,end
fprintf(maskhelp);
fprintf('\n');
while again
for i=1:length(polygon)
fprintf('polygon %d has %d points\n', i, size(polygon{i},1));
end
[x, y, k] = ginput(1);
okflag = 0;
% check points do not fall out of image boundaries
if get(findobj('string','Ins'),'value')
if (proj == 1 && y<ss(2) && x<ss(3) && x>1 && y>1)
okflag = 1;
elseif (proj == 2 && y<ss(1) && x<ss(3) && x>1 && y>1)
okflag = 1;
elseif (proj == 3 && y<ss(1) && x<ss(2) && x>1 && y>1)
okflag = 1;
else
okflag = 0;
end
end
if okflag
switch lower(k)
case 1
polygon{thispolygon} = cat(1, polygon{thispolygon}, [x y]);
% add the last line segment to the figure
if size(polygon{thispolygon},1)>1
x = polygon{i}([end-1 end],1);
y = polygon{i}([end-1 end],2);
end
plot(x, y, 'g.-');
case 8 % backspace
if size(polygon{thispolygon},1)>0
% redraw existing polygons
cb_redraw(gca);
% remove the last point of current polygon
polygon{thispolygon} = polygon{thispolygon}(1:end-1,:);
for i=1:length(polygon)
x = polygon{i}(:,1);
y = polygon{i}(:,2);
if i~=thispolygon
% close the polygon in the figure
x(end) = x(1);
y(end) = y(1);
end
set(gca,'nextplot','new')
plot(x, y, 'g.-');
end
end
case 'c'
if size(polygon{thispolygon},1)>0
% close the polygon
polygon{thispolygon}(end+1,:) = polygon{thispolygon}(1,:);
% close the polygon in the figure
x = polygon{i}([end-1 end],1);
y = polygon{i}([end-1 end],2);
plot(x, y, 'g.-');
% switch to the next polygon
thispolygon = thispolygon + 1;
polygon{thispolygon} = zeros(0,2);
slicedata = getappdata(fig,'slicedata');
m = length(slicedata);
slicedata(m+1).proj = prop{1};
slicedata(m+1).slice = prop{2};
slicedata(m+1).polygon = polygon;
setappdata(fig,'slicedata',slicedata);
end
case {'q', 27}
if size(polygon{thispolygon},1)>0
% close the polygon
polygon{thispolygon}(end+1,:) = polygon{thispolygon}(1,:);
% close the polygon in the figure
x = polygon{i}([end-1 end],1);
y = polygon{i}([end-1 end],2);
plot(x, y, 'g.-');
end
again = 0;
%set(gcf,'WindowButtonDownFcn','');
slicedata = getappdata(fig,'slicedata');
m = length(slicedata);
if ~isempty(polygon{thispolygon})
slicedata(m+1).proj = prop{1};
slicedata(m+1).slice = prop{2};
slicedata(m+1).polygon = polygon;
setappdata(fig,'slicedata',slicedata);
end
otherwise
warning('invalid button (%d)', k);
end
end
assign_points3d
end
function cb_btn_dwn(hObject, eventdata, handles)
build_polygon
uiresume
function cb_btn_dwn2(hObject, eventdata, handles)
global obj
erase_points2d(obj)
uiresume
function erase_points2d (obj)
fig = get(gca, 'parent');
prop = getappdata(fig,'prop');
slicedata = getappdata(fig,'slicedata');
pntsslice = [];
% 2d slice selected box boundaries
if strcmp(get(obj,'string'),'box')
[x, y] = ft_select_box;
rowmin = min(y); rowmax = max(y);
colmin = min(x); colmax = max(x);
box = getappdata(fig,'box');
box = [box; prop{1} prop{2} rowmin rowmax colmin colmax];
setappdata(fig,'box',box);
else
% converts lines to points
pos = slicedata2pnts(prop{1},prop{2});
tmp = ft_select_point(pos);
point2mark.x = tmp(1); point2mark.y = tmp(2);
setappdata(fig,'point2mark',point2mark);
end
maskhelp = [ ...
'------------------------------------------------------------------------\n' ...
'Delete points:\n' ...
'press "c" on the keyboard to undo all selections\n' ...
'press "d" or DEL on the keyboard to delete all selections\n' ...
];
fprintf(maskhelp);
fprintf('\n');
again = 1;
if ~ishold,hold,end
cb_redraw(gca);
% waits for a key press
while again
[junk1, junk2, k] = ginput(1);
switch lower(k)
case 'c'
if strcmp(get(obj,'string'),'box')
% undoes all the selections, but only in the current slice
ind = [];
for ii=1:size(box,1)
if box(ii,1)==prop{1} && box(ii,2)==prop{2}
ind = [ind,ii];
end
end
box(ind,:) = [];
setappdata(fig,'box',box);
cb_redraw(gca);
again = 0;
set(gcf,'WindowButtonDownFcn','');
else
setappdata(fig,'point2mark',[]);
cb_redraw(gca);
again = 0;
set(gcf,'WindowButtonDownFcn','');
end
case {'d', 127}
if strcmp(get(obj,'string'),'box')
update_slicedata
% deletes only the points selected in the current slice
ind = [];
for ii=1:size(box,1)
if box(ii,1)==prop{1} && box(ii,2)==prop{2}
ind = [ind,ii];
end
end
box(ind,:) = [];
setappdata(fig,'box',box);
cb_redraw(gca);
again = 0;
set(gcf,'WindowButtonDownFcn','');
else
update_slicedata
setappdata(fig,'point2mark',[]);
cb_redraw(gca);
again = 0;
set(gcf,'WindowButtonDownFcn','');
end
otherwise
end
end
assign_points3d
function assign_points3d
fig = get(gca, 'parent');
slicedata = getappdata(fig,'slicedata');
points = [];
for zz = 1:length(slicedata)
slice = slicedata(zz).slice;
proj = slicedata(zz).proj;
polygon = slicedata(zz).polygon;
for kk=1:length(polygon)
if ~isempty(polygon{kk})
[xs,ys]=deal(polygon{kk}(:,1),polygon{kk}(:,2));
if (proj==1) %jk
tmp = [ slice*ones(length(xs),1),ys(:),xs(:) ];
points = [points; unique(tmp,'rows')];
elseif (proj==2) %ik
tmp = [ ys(:),slice*ones(length(xs),1),xs(:) ];
points = [points; unique(tmp,'rows')];
elseif (proj==3) %ij
tmp = [ ys(:),xs(:),slice*ones(length(xs),1) ];
points = [points; unique(tmp,'rows')];
end
end
end
end
setappdata(fig,'points',points);
function update_slicedata
fig = get(gca, 'parent');
prop = getappdata(fig,'prop');
slicedata = getappdata(fig,'slicedata');
box = getappdata(fig,'box');
point2mark = getappdata(fig,'point2mark');
% case of box selection
if ~isempty(box) && ~isempty(slicedata)
for zz = 1:length(slicedata)
slice = slicedata(zz).slice;
proj = slicedata(zz).proj;
polygon = slicedata(zz).polygon;
for uu=1:size(box,1)
if (box(uu,1)==proj) && (box(uu,2)==slice)
for kk=1:length(polygon)
if ~isempty(polygon{kk})
[xs,ys] = deal(polygon{kk}(:,1),polygon{kk}(:,2));
tmpind = lt(ys,ones(length(xs),1)*box(uu,4)).*gt(ys,ones(length(xs),1)*box(uu,3)).* ...
lt(xs,ones(length(xs),1)*box(uu,6)).*gt(xs,ones(length(xs),1)*box(uu,5));
slicedata(zz).polygon{kk} = [ xs(find(~tmpind)),ys(find(~tmpind)) ];
end
end
end
end
end
% case of point selection
else
if ~isempty(slicedata)
for zz = 1:length(slicedata)
slice = slicedata(zz).slice;
proj = slicedata(zz).proj;
polygon = slicedata(zz).polygon;
for kk=1:length(polygon)
if ~isempty(polygon{kk})
[xs,ys] = deal(polygon{kk}(:,1),polygon{kk}(:,2));
tmpind = eq(xs,point2mark.x).*eq(ys,point2mark.y);
slicedata(zz).polygon{kk} = [ xs(find(~tmpind)),ys(find(~tmpind)) ];
end
end
end
end
end
setappdata(fig,'slicedata',slicedata)
% FIXME: obsolete: replaced by headshape at the beginning
function smooth_mesh(hObject, eventdata, handles)
fig = get(gca,'parent');
disp('not yet implemented')
% FIXME: make it work for pre-loaded meshes
function view_mesh(hObject, eventdata, handles)
fig = get(gca, 'parent');
assign_points3d
pnt = getappdata(fig,'points');
pnt_ = pnt;
if ~isempty(pnt)
tri = projecttri(pnt);
bnd.pnt = pnt_;
bnd.tri = tri;
slicedata = getappdata(fig,'slicedata');
figure
ft_plot_mesh(bnd,'vertexcolor','k');
end
function cancel_mesh(hObject, eventdata, handles)
fig = get(gca, 'parent');
close(fig)
function cb_close(hObject, eventdata, handles)
% get the points from the figure
fig = hObject;
global pnt
pnt = getappdata(fig, 'points');
set(fig, 'CloseRequestFcn', @delete);
delete(fig);
function cb_btnp1(hObject, eventdata, handles)
set(findobj('string','jk'),'value',1);
set(findobj('string','ik'),'value',0);
set(findobj('string','ij'),'value',0);
cb_btn(hObject);
function cb_btnp2(hObject, eventdata, handles)
set(findobj('string','jk'),'value',0);
set(findobj('string','ik'),'value',1);
set(findobj('string','ij'),'value',0);
cb_btn(hObject);
function cb_btnp3(hObject, eventdata, handles)
set(findobj('string','jk'),'value',0);
set(findobj('string','ik'),'value',0);
set(findobj('string','ij'),'value',1);
cb_btn(hObject);
function which_task1(hObject, eventdata, handles)
set(gcf,'WindowButtonDownFcn','');
set(findobj('string','View'),'value',1);
set(findobj('string','Ins'), 'value',0);
set(findobj('string','Del'), 'value',0);
set(gcf,'WindowButtonDownFcn','');
change_panel
function which_task2(hObject, eventdata, handles)
set(findobj('string','View'),'value',0);
set(findobj('string','Ins'), 'value',1);
set(findobj('string','Del'), 'value',0);
set(gcf,'WindowButtonDownFcn',@cb_btn_dwn);
change_panel
function which_task3(hObject, eventdata, handles)
set(gcf,'WindowButtonDownFcn','');
set(findobj('string','View'),'value',0);
set(findobj('string','Ins'), 'value',0);
set(findobj('string','Del'), 'value',1);
change_panel
function change_panel
% affect panel visualization
w1 = get(findobj('string','View'),'value');
w2 = get(findobj('string','Ins'), 'value');
w3 = get(findobj('string','Del'), 'value');
if w1
set(findobj('tag','slice'),'string','slice');
set(findobj('tag','min'),'string','<');
set(findobj('tag','max'),'string','>');
set(findobj('tag','min'),'style','pushbutton');
set(findobj('tag','max'),'style','pushbutton');
set(findobj('tag','min'),'callback',@cb_btn);
set(findobj('tag','max'),'callback',@cb_btn);
set(findobj('tag','mesh'),'visible','on');
set(findobj('tag','openm'),'visible','on');
set(findobj('tag','viewm'),'visible','on');
set(findobj('tag','brightness'),'visible','on');
set(findobj('tag','plus'),'visible','on');
set(findobj('tag','minus'),'visible','on');
set(findobj('tag','toggle axes'),'visible','on');
set(findobj('tag','plane'),'visible','on');
set(findobj('tag','one'),'visible','on');
set(findobj('tag','two'),'visible','on');
set(findobj('tag','three'),'visible','on');
elseif w2
set(findobj('tag','slice'),'string','select points');
set(findobj('tag','min'),'string','close');
set(findobj('tag','max'),'string','next');
set(findobj('tag','min'),'style','pushbutton');
set(findobj('tag','max'),'style','pushbutton');
set(findobj('tag','min'),'callback',@tins_close);
set(findobj('tag','max'),'callback',@tins_next);
set(findobj('tag','mesh'),'visible','off');
set(findobj('tag','openm'),'visible','off');
set(findobj('tag','viewm'),'visible','off');
set(findobj('tag','brightness'),'visible','off');
set(findobj('tag','plus'),'visible','off');
set(findobj('tag','minus'),'visible','off');
set(findobj('tag','toggle axes'),'visible','off');
set(findobj('tag','plane'),'visible','off');
set(findobj('tag','one'),'visible','off');
set(findobj('tag','two'),'visible','off');
set(findobj('tag','three'),'visible','off');
elseif w3
set(findobj('tag','slice'),'string','select points');
set(findobj('tag','min'),'string','box');
set(findobj('tag','max'),'string','point');
set(findobj('tag','min'),'style','pushbutton');
set(findobj('tag','max'),'style','pushbutton');
set(findobj('tag','min'),'callback',@tdel_box);
set(findobj('tag','max'),'callback',@tdel_single);
set(findobj('tag','mesh'),'visible','off');
set(findobj('tag','openm'),'visible','off');
set(findobj('tag','viewm'),'visible','off');
set(findobj('tag','brightness'),'visible','off');
set(findobj('tag','plus'),'visible','off');
set(findobj('tag','minus'),'visible','off');
set(findobj('tag','toggle axes'),'visible','off');
set(findobj('tag','plane'),'visible','off');
set(findobj('tag','one'),'visible','off');
set(findobj('tag','two'),'visible','off');
set(findobj('tag','three'),'visible','off');
end
function tins_close(hObject, eventdata, handles)
set(gcf,'WindowButtonDownFcn','');
function tins_next(hObject, eventdata, handles)
set(gcf,'WindowButtonDownFcn','');
function tdel_box(hObject, eventdata, handles)
global obj
obj = gco;
set(gcf,'WindowButtonDownFcn',@cb_btn_dwn2);
function tdel_single(hObject, eventdata, handles)
global obj
obj = gco;
set(gcf,'WindowButtonDownFcn',@cb_btn_dwn2);
% accessory functions:
function [pnts] = slicedata2pnts(proj,slice)
fig = get(gca, 'parent');
slicedata = getappdata(fig,'slicedata');
pnts = [];
for i=1:length(slicedata)
if slicedata(i).slice==slice && slicedata(i).proj == proj
for j=1:length(slicedata(i).polygon)
if ~isempty(slicedata(i).polygon{j})
tmp = slicedata(i).polygon{j};
xs = tmp(:,1); ys = tmp(:,2);
pnts = [pnts;[unique([xs,ys],'rows')]];
end
end
end
end
function h = ispolygon(x)
h = length(x.XData)>1;
function h = ispoint(x)
h = length(x.XData)==1;
function [T,P] = points2param(pnt)
x = pnt(:,1); y = pnt(:,2); z = pnt(:,3);
[phi,theta,R] = cart2sph(x,y,z);
theta = theta + pi/2;
phi = phi + pi;
T = theta(:);
P = phi(:);
function [bnd2,a,Or] = spherical_harmonic_mesh(bnd, nl)
% SPHERICAL_HARMONIC_MESH realizes the smoothed version of a mesh contained in the first
% argument bnd. The boundary argument (bnd) contains typically 2 fields
% called .pnt and .tri referring to vertices and triangulation of a mesh.
% The degree of smoothing is given by the order in the second input: nl
%
% Use as
% bnd2 = spherical_harmonic_mesh(bnd, nl);
% nl = 12; % from van 't Ent paper
bnd2 = [];
% calculate midpoint
Or = mean(bnd.pnt);
% rescale all points
x = bnd.pnt(:,1) - Or(1);
y = bnd.pnt(:,2) - Or(2);
z = bnd.pnt(:,3) - Or(3);
X = [x(:), y(:), z(:)];
% convert points to parameters
[T,P] = points2param(X);
% basis function
B = shlib_B(nl, T, P);
Y = B'*X;
% solve the linear system
a = pinv(B'*B)*Y;
% build the surface
Xs = zeros(size(X));
for l = 0:nl-1
for m = -l:l
if m<0
Yml = shlib_Yml(l, abs(m), T, P);
Yml = (-1)^m*conj(Yml);
else
Yml = shlib_Yml(l, m, T, P);
end
indx = l^2 + l + m+1;
Xs = Xs + Yml*a(indx,:);
end
fprintf('%d of %d\n', l, nl);
end
% Just take the real part
Xs = real(Xs);
% reconstruct the matrices for plotting.
xs = reshape(Xs(:,1), size(x,1), size(x,2));
ys = reshape(Xs(:,2), size(x,1), size(x,2));
zs = reshape(Xs(:,3), size(x,1), size(x,2));
bnd2.pnt = [xs(:)+Or(1) ys(:)+Or(2) zs(:)+Or(3)];
[bnd2.tri] = projecttri(bnd.pnt);
function B = shlib_B(nl, theta, phi)
% function B = shlib_B(nl, theta, phi)
%
% Constructs the matrix of basis functions
% where b(i,l^2 + l + m) = Yml(theta, phi)
%
% See also: shlib_Yml.m, shlib_decomp.m, shlib_gen_shfnc.m
%
% Dr. A. I. Hanna (2006).
B = zeros(length(theta), nl^2+2*nl+1);
for l = 0:nl-1
for m = -l:l
if m<0
Yml = shlib_Yml(l, abs(m), theta, phi);
Yml = (-1)^m*conj(Yml);
else
Yml = shlib_Yml(l, m, theta, phi);
end
indx = l^2 + l + m+1;
B(:, indx) = Yml;
end
end
return;
function Yml = shlib_Yml(l, m, theta, phi)
% function Yml = shlib_Yml(l, m, theta, phi)
%
% A matlab function that takes a given order and degree, and the matrix of
% theta and phi and constructs a spherical harmonic from these. The
% analogue in the 1D case would be to give a particular frequency.
%
% Inputs:
% m - order of the spherical harmonic
% l - degree of the spherical harmonic
% theta - matrix of polar coordinates \theta \in [0, \pi]
% phi - matrix of azimuthal cooridinates \phi \in [0, 2\pi)
%
% Example:
%
% [x, y] = meshgrid(-1:.1:1);
% z = x.^2 + y.^2;
% [phi,theta,R] = cart2sph(x,y,z);
% Yml = spharm_aih(2,2, theta(:), phi(:));
%
% See also: shlib_B.m, shlib_decomp.m, shlib_gen_shfnc.m
%
% Dr. A. I. Hanna (2006)
Pml=legendre(l,cos(theta));
if l~=0
Pml=squeeze(Pml(m+1,:,:));
end
Pml = Pml(:);
% Yml = sqrt(((2*l+1)/4).*(factorial(l-m)/factorial(l+m))).*Pml.*exp(sqrt(-1).*m.*phi);
% new:
Yml = sqrt(((2*l+1)/(4*pi)).*(factorial(l-m)/factorial(l+m))).*Pml.*exp(sqrt(-1).*m.*phi);
return;
|
github
|
philippboehmsturm/antx-master
|
nanmean.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/nanmean.m
| 165 |
utf_8
|
e6c473a49d8be6e12960af55ced45e54
|
% NANMEAN provides a replacement for MATLAB's nanmean.
%
% For usage see MEAN.
function y = nanmean(x, dim)
N = sum(~isnan(x), dim);
y = nansum(x, dim) ./ N;
end
|
github
|
philippboehmsturm/antx-master
|
moviefunction.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/moviefunction.m
| 33,279 |
utf_8
|
c7d6d7c70dddcb8f371c2bd1260e6067
|
function moviefunction(cfg, data)
% we need cfg.plotfun to plot the data
% data needs to be 3D, N x time x freq (last can be singleton)
% N needs to correspond to number of vertices (channels, gridpoints, etc)
ft_defaults
ft_preamble help
ft_preamble callinfo
ft_preamble trackconfig
ft_preamble loadvar data
data = ft_checkdata(data, 'datatype', {'timelock', 'freq', 'source'});
% check if the input cfg is valid for this function
cfg = ft_checkconfig(cfg, 'renamedval', {'zlim', 'absmax', 'maxabs'});
cfg = ft_checkconfig(cfg, 'renamed', {'zparam', 'funparameter'});
cfg = ft_checkconfig(cfg, 'renamed', {'parameter', 'funparameter'});
cfg = ft_checkconfig(cfg, 'renamed', {'mask', 'maskparameter'});
cfg = ft_checkconfig(cfg, 'deprecated', {'xparam'});
cfg = ft_checkconfig(cfg, 'forbidden', {'yparam'});
% set data flags
opt = [];
opt.issource = ft_datatype(data, 'source');
opt.isfreq = ft_datatype(data, 'freq');
opt.istimelock = ft_datatype(data, 'timelock');
if opt.issource+opt.isfreq+opt.istimelock ~= 1
error('data cannot be definitely deteced as frequency, timelock or source data');
end
if opt.issource
% transfer anatomical information to opt
if isfield(data, 'sulc')
opt.anatomy.sulc = data.sulc;
end
if isfield(data, 'tri')
opt.anatomy.tri = data.tri;
else
error('source.tri missing, this function requires a triangulated cortical sheet as source model');
end
if isfield(data, 'pnt')
opt.anatomy.pnt = data.pnt;
elseif isfield(data, 'pos')
opt.anatomy.pos = data.pos;
else
error('source.pos or source.pnt is missing');
end
end
% set the defaults
cfg.xlim = ft_getopt(cfg, 'xlim', 'maxmin');
cfg.ylim = ft_getopt(cfg, 'ylim', 'maxmin');
cfg.zlim = ft_getopt(cfg, 'zlim', 'maxmin');
cfg.xparam = ft_getopt(cfg, 'xparam', 'time');
cfg.yparam = ft_getopt(cfg, 'yparam', '[]');
if isempty(cfg.yparam ) && isfield(data, 'freq')
cfg.yparam = 'freq';
else
cfg.yparam = [];
end
if opt.isfreq
cfg.funparameter = ft_getopt(cfg, 'funparameter', 'powspctrm'); % use power as default
elseif opt.istimelock
cfg.funparameter = ft_getopt(cfg, 'funparameter', 'avg'); % use power as default
elseif opt.issource
cfg.funparameter = ft_getopt(cfg, 'funparameter', 'avg.pow'); % use power as default
end
cfg.maskparameter = ft_getopt(cfg, 'maskparameter');
cfg.inputfile = ft_getopt(cfg, 'inputfile', []);
cfg.samperframe = ft_getopt(cfg, 'samperframe', 1);
cfg.framespersec = ft_getopt(cfg, 'framespersec', 5);
cfg.framesfile = ft_getopt(cfg, 'framesfile', []);
cfg.moviefreq = ft_getopt(cfg, 'moviefreq', []);
cfg.movietime = ft_getopt(cfg, 'movietime', []);
cfg.movierpt = ft_getopt(cfg, 'movierpt', 1);
cfg.interactive = ft_getopt(cfg, 'interactive', 'yes');
opt.record = ~istrue(cfg.interactive);
% read or create the layout that will be used for plotting:
if isfield(cfg, 'layout')
opt.layout = ft_prepare_layout(cfg);
% select the channels in the data that match with the layout:
[seldat, sellay] = match_str(data.label, opt.layout.label);
if isempty(seldat)
error('labels in data and labels in layout do not match');
end
% get the x and y coordinates and labels of the channels in the data
opt.chanx = opt.layout.pos(sellay,1);
opt.chany = opt.layout.pos(sellay,2);
else
if ~opt.issource
error('you need to specify a layout in case of freq or timelock data');
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% the actual computation is done in the middle part
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
opt.xvalues = data.(cfg.xparam);
opt.yvalues = [];
if ~isempty(cfg.yparam)
opt.yvalues = data.(cfg.yparam);
end
opt.dat = getsubfield(data, cfg.funparameter);
% check consistency of xparam and yparam
% NOTE: i set two different defaults for the 'chan_time' and the 'chan_freq_time' case
if isfield(data,'dimord')
% get dimord dimensions
dims = textscan(data.dimord,'%s', 'Delimiter', '_');
dims = dims{1};
% remove subject dimension
rpt_dim = strcmp('rpt', dims) | strcmp('subj', dims);
if sum(rpt_dim)~=0
dims(rpt_dim) = [];
opt.dat = squeeze(nanmean(opt.dat, find(rpt_dim)));
end
opt.ydim = find(strcmp(cfg.yparam, dims));
opt.xdim = find(strcmp(cfg.xparam, dims));
opt.zdim = setdiff(1:ndims(opt.dat), [opt.ydim opt.xdim]);
if opt.zdim ~=1
error('input data does not have the correct format of N x time (x freq)');
end
% and permute
opt.dat = permute(opt.dat, [opt.zdim(:)' opt.xdim opt.ydim]);
end
if opt.issource
if size(data.pos)~=size(opt.dat,1)
error('inconsistent number of vertices in the cortical mesh');
end
if ~isfield(data, 'tri')
error('source.tri missing, this function requires a triangulated cortical sheet as source model');
end
end
opt.xdim = 2;
if ~isempty(cfg.yparam)
opt.ydim = 3;
else
opt.ydim = [];
end
if ~isempty(cfg.maskparameter) && ischar(cfg.maskparameter)
opt.mask = double(getsubfield(data, cfg.maskparameter)~=0);
else
opt.mask =ones(size(opt.dat));
end
if length(opt.xvalues)~=size(opt.dat, opt.xdim)
error('inconsistent size of "%s" compared to "%s"', cfg.funparameter, cfg.xparam);
end
if ~isempty(opt.ydim) && length(opt.yvalues)~=size(opt.dat,opt.ydim)
error('inconsistent size of "%s" compared to "%s"', cfg.funparameter, cfg.yparam);
end
% TODO handle colorbar stuff here
% create GUI and plot stuff
opt = createGUI(opt);
if isempty(cfg.yparam)
set(opt.handles.label.yparam, 'Visible', 'off');
set(opt.handles.slider.yparam, 'Visible', 'off');
opt.yparam = '';
else
opt.yparam = [upper(cfg.yparam(1)) lower(cfg.yparam(2:end))];
set(opt.handles.label.yparam, 'String', opt.yparam);
end
opt.xparam = [upper(cfg.xparam(1)) lower(cfg.xparam(2:end))];
set(opt.handles.label.xparam, 'String', opt.xparam);
% set timer
opt.timer = timer;
set(opt.timer, 'timerfcn', {@cb_timer, opt.handles.figure}, 'period', 0.1, 'executionmode', 'fixedSpacing');
opt = prepareBrainplot(opt);
opt.speed = 1;
guidata(opt.handles.figure, opt);
% init first screen
cb_slider(opt.handles.figure);
%uicontrol(opt.handles.colorbar);
cb_colorbar(opt.handles.figure);
if opt.record
start(opt.timer);
end
end
%%
% **************************************************************
% ********************* CREATE GUI *****************************
% **************************************************************
function opt = createGUI(opt)
% main figure
opt.handles.figure = figure(...
'Units','characters',...
'Color',[0.941176470588235 0.941176470588235 0.941176470588235],...
'Colormap',[0 0 0.5625;0 0 0.625;0 0 0.6875;0 0 0.75;0 0 0.8125;0 0 0.875;0 0 0.9375;0 0 1;0 0.0625 1;0 0.125 1;0 0.1875 1;0 0.25 1;0 0.3125 1;0 0.375 1;0 0.4375 1;0 0.5 1;0 0.5625 1;0 0.625 1;0 0.6875 1;0 0.75 1;0 0.8125 1;0 0.875 1;0 0.9375 1;0 1 1;0.0625 1 1;0.125 1 0.9375;0.1875 1 0.875;0.25 1 0.8125;0.3125 1 0.75;0.375 1 0.6875;0.4375 1 0.625;0.5 1 0.5625;0.5625 1 0.5;0.625 1 0.4375;0.6875 1 0.375;0.75 1 0.3125;0.8125 1 0.25;0.875 1 0.1875;0.9375 1 0.125;1 1 0.0625;1 1 0;1 0.9375 0;1 0.875 0;1 0.8125 0;1 0.75 0;1 0.6875 0;1 0.625 0;1 0.5625 0;1 0.5 0;1 0.4375 0;1 0.375 0;1 0.3125 0;1 0.25 0;1 0.1875 0;1 0.125 0;1 0.0625 0;1 0 0;0.9375 0 0;0.875 0 0;0.8125 0 0;0.75 0 0;0.6875 0 0;0.625 0 0;0.5625 0 0],...
'IntegerHandle','off',...
'InvertHardcopy',get(0,'defaultfigureInvertHardcopy'),...
'Name','ft_movieplot',...
'Menu', 'none', ...
'Toolbar', 'figure', ...
'NumberTitle','off',...
'PaperPosition',get(0,'defaultfigurePaperPosition'),...
'Position',[103.8 14.0769230769231 180.2 50],...
'HandleVisibility','callback',...
'WindowButtonUpFcn', @cb_stopDrag, ...
'UserData',[],...
'Tag','mainFigure',...
'Visible','on');
% view panel (between different views can be switched)
opt.handles.panel.view = uipanel(...
'Parent',opt.handles.figure,...
'Title','View',...
'Tag','viewPanel',...
'Clipping','on',...
'Visible', 'off', ...
'Position',[0.842397336293008 -0.00307692307692308 0.155382907880133 1.00153846153846] );
% axes for switching to topo viewmode
opt.handles.axes.topo = axes(...
'Parent',opt.handles.panel.view,...
'Position',[0.0441176470588235 0.728706624605678 0.955882352941177 0.205047318611987],...
'CameraPosition',[0.5 0.5 9.16025403784439],...
'CameraPositionMode',get(0,'defaultaxesCameraPositionMode'),...
'Color',[0.941176470588235 0.941176470588235 0.941176470588235],...
'ColorOrder',get(0,'defaultaxesColorOrder'),...
'LooseInset',[0.115903614457831 0.107232704402516 0.0846987951807229 0.0731132075471698],...
'XColor',get(0,'defaultaxesXColor'),...
'YColor',get(0,'defaultaxesYColor'),...
'ZColor',get(0,'defaultaxesZColor'),...
'ButtonDownFcn',@(hObject,eventdata)test_movieplot_export('topoAxes_ButtonDownFcn',hObject,eventdata,guidata(hObject)),...
'Tag','topoAxes',...
'HandleVisibility', 'on', ...
'UserData',[]);
% axes for switching to multiplot viewmode
opt.handles.axes.multi = axes(...
'Parent',opt.handles.panel.view,...
'Position',[0.0441176470588235 0.413249211356467 0.955882352941177 0.205047318611987],...
'CameraPosition',[0.5 0.5 9.16025403784439],...
'CameraPositionMode',get(0,'defaultaxesCameraPositionMode'),...
'Color',[0.941176470588235 0.941176470588235 0.941176470588235],...
'ColorOrder',get(0,'defaultaxesColorOrder'),...
'LooseInset',[0.0302261898791314 0.128446186295888 0.0220883695270575 0.0875769452017415],...
'XColor',get(0,'defaultaxesXColor'),...
'YColor',get(0,'defaultaxesYColor'),...
'ZColor',get(0,'defaultaxesZColor'),...
'ButtonDownFcn',@(hObject,eventdata)test_movieplot_export('multiAxes_ButtonDownFcn',hObject,eventdata,guidata(hObject)),...
'Tag','multiAxes',...
'HandleVisibility', 'on', ...
'UserData',[]);
% axes for switching to singleplot viewmode
opt.handles.axes.single = axes(...
'Parent',opt.handles.panel.view,...
'Position',[0.0441176470588235 0.0977917981072555 0.955882352941177 0.205047318611987],...
'CameraPosition',[0.5 0.5 9.16025403784439],...
'CameraPositionMode',get(0,'defaultaxesCameraPositionMode'),...
'Color',[0.941176470588235 0.941176470588235 0.941176470588235],...
'ColorOrder',get(0,'defaultaxesColorOrder'),...
'LooseInset',[0.0302261898791314 0.128446186295888 0.0220883695270575 0.0875769452017415],...
'XColor',get(0,'defaultaxesXColor'),...
'YColor',get(0,'defaultaxesYColor'),...
'ZColor',get(0,'defaultaxesZColor'),...
'Tag','singleAxes',...
'HandleVisibility', 'on', ...
'UserData',[]);
% main control panel
opt.handles.panel.control = uipanel(...
'Parent',opt.handles.figure,...
'Title','Controls',...
'Tag','controlPanel',...
'Clipping','on',...
'Position',[0.660377358490566 -0.00307692307692308 0.177580466148724 0.153846153846154]);
% buttons
opt.handles.button.play = uicontrol(...
'Parent',opt.handles.panel.control,...
'Units','normalized',...
'Callback',@cb_playbutton,...
'Position',[0.0973193473193473 0.457831325301205 0.314685314685315 0.530120481927711],...
'String','Play',...
'Tag','playButton');
opt.handles.button.record = uicontrol(...
'Parent',opt.handles.panel.control,...
'Units','normalized',...
'Callback',@cb_recordbutton, ...
'Position',[0.551864801864802 0.457831325301205 0.321678321678322 0.530120481927711],...
'String','Record',...
'Tag','recordButton');
% speed control
opt.handles.slider.speed = uicontrol(...
'Parent',opt.handles.panel.control,...
'Units','normalized',...
'BackgroundColor',[0.9 0.9 0.9],...
'Callback',@cb_speed, ...
'Position',[0.0256410256410256 0.0843373493975904 0.493589743589744 0.204819277108434],...
'String',{ 'Slider' },...
'Style','slider',...
'Value',0.5,...
'Tag','speedSlider');
opt.MIN_SPEED = 0.01;
opt.AVG_SPEED = 1;
opt.MAX_SPEED = 100;
opt.handles.label.speed = uicontrol(...
'Parent',opt.handles.panel.control,...
'Units','normalized',...
'HorizontalAlignment','left',...
'Position',[0.532051282051282 0.108433734939759 0.448717948717949 0.168674698795181],...
'String','Speed 1.0x',...
'Style','text',...
'Value',0.5,...
'Tag','speedLabel');
% parameter control
opt.handles.panel.parameter = uipanel(...
'Parent',opt.handles.figure,...
'Title','Parameter',...
'Tag','parameterPanel',...
'Clipping','on',...
'Position',[-0.00110987791342952 -0.00307692307692308 0.658157602663707 0.155384615384615]);
opt.handles.slider.xparam = uicontrol(...
'Parent',opt.handles.panel.parameter,...
'Units','normalized',...
'BackgroundColor',[0.9 0.9 0.9],...
'Callback',@cb_slider,...
'Position',[0.0186757215619694 0.250000000000001 0.969439728353141 0.214285714285714],...
'String',{ 'Slider' },...
'Style','slider',...
'Tag','xparamslider');
opt.handles.label.xparam = uicontrol(...
'Parent',opt.handles.panel.parameter,...
'Units','normalized',...
'Position',[0.0186757215619694 0.0476190476190483 0.967741935483871 0.178571428571429],...
'String','xparamLabel',...
'Style','text',...
'Tag','xparamLabel');
opt.handles.slider.yparam = uicontrol(...
'Parent',opt.handles.panel.parameter,...
'Units','normalized',...
'BackgroundColor',[0.9 0.9 0.9],...
'Callback',@cb_slider,...
'Position',[0.0186757215619694 0.690476190476191 0.969439728353141 0.202380952380952],...
'String',{ 'Slider' },...
'Style','slider',...
'Tag','yparamSlider');
opt.handles.label.yparam = uicontrol(...
'Parent',opt.handles.panel.parameter,...
'Units','normalized',...
'Position',[0.0186757215619694 0.500000000000001 0.967741935483871 0.178571428571429],...
'String','yparamLabel',...
'Style','text',...
'Tag','text3');
opt.handles.buttongroup.color = uibuttongroup(...
'Parent',opt.handles.figure,...
'Title','Colormap',...
'Tag','colorGroup',...
'Clipping','on',...
'Position',[0.725860155382908 0.150769230769231 0.112097669256382 0.847692307692308],...
'SelectedObject',[],...
'SelectionChangeFcn',[],...
'OldSelectedObject',[]);
opt.handles.axes.colorbar = axes(...
'Parent',opt.handles.buttongroup.color,...
'Position',[-0.0103092783505155 0.157303370786517 1.04123711340206 0.771535580524345],...
'CameraPosition',[0.5 0.5 9.16025403784439],...
'CameraPositionMode',get(0,'defaultaxesCameraPositionMode'),...
'Color',[0.941176470588235 0.941176470588235 0.941176470588235],...
'ColorOrder',get(0,'defaultaxesColorOrder'),...
'LooseInset',[6.37540259335975e-007 1.19260520025353e-007 4.65894804899366e-007 8.13139909263772e-008],...
'XColor',get(0,'defaultaxesXColor'),...
'YColor',get(0,'defaultaxesYColor'),...
'ZColor',get(0,'defaultaxesZColor'),...
'ButtonDownFcn',@(hObject,eventdata)test_movieplot_export('colorbarAxes_ButtonDownFcn',hObject,eventdata,guidata(hObject)),...
'HandleVisibility', 'on', ...
'Tag','colorbarAxes', ...
'YLim', [0 1], ...
'YLimMode', 'manual', ...
'XLim', [0 1], ...
'XLimMode', 'manual');
% set colorbar
opt.handles.colorbar = colorbar('ButtonDownFcn', []);
set(opt.handles.colorbar, 'Parent', opt.handles.figure);
set(opt.handles.colorbar, 'Position', [0.7725 0.305 0.02 0.6]);
if (gcf~=opt.handles.figure)
close gcf; % sometimes there is a new window that opens up
end
% set lines
%YLim = get(opt.handles.colorbar, 'YLim');
opt.handles.lines.upperColor = line([-1 0], [32 32], ...
'Color', 'black', ...
'LineWidth', 4, ...
'ButtonDownFcn', @cb_startDrag, ...
'Parent', opt.handles.colorbar, ...
'Visible', 'off', ...
'Tag', 'upperColor');
opt.handles.lines.lowerColor = line([1 2], [32 32], ...
'Color', 'black', ...
'LineWidth', 4, ...
'ButtonDownFcn', @cb_startDrag, ...
'Parent', opt.handles.colorbar, ...
'Visible', 'off', ...
'Tag', 'lowerColor');
opt.handles.menu.colormap = uicontrol(...
'Parent',opt.handles.buttongroup.color,...
'Units','normalized',...
'BackgroundColor',[1 1 1],...
'Callback',@cb_colormap,...
'Position',[0.0721649484536082 0.951310861423221 0.865979381443299 0.0374531835205993],...
'String',{ 'jet'; 'hot'; 'cool' },...
'Style','popupmenu',...
'Value',1, ...
'Tag','colormapMenu');
opt.handles.checkbox.auto = uicontrol(...
'Parent',opt.handles.buttongroup.color,...
'Units','normalized',...
'Callback',@cb_colorbar,...
'Position',[0.103092783505155 0.0898876404494382 0.77319587628866 0.0430711610486891],...
'String','automatic',...
'Style','checkbox',...
'Value', 1, ... % TODO make this dependet on cfg.zlim
'Tag','autoCheck');
opt.handles.checkbox.symmetric = uicontrol(...
'Parent',opt.handles.buttongroup.color,...
'Units','normalized',...
'Callback',@cb_colorbar,...
'Position',[0.103092783505155 0.0449438202247191 0.77319587628866 0.0430711610486891],...
'String','symmetric',...
'Style','checkbox',...
'Value', 0, ... % TODO make this dependet on cfg.zlim
'Tag','symCheck');
% buttons
opt.handles.button.decrUpperColor = uicontrol(...
'Parent', opt.handles.buttongroup.color,...
'Units','normalized',...
'Enable', 'off', ...
'Callback',@cb_colorbar,...
'Position',[0.503092783505155 0.9149438202247191 0.17319587628866 0.0330711610486891],...
'String','-',...
'Tag','decrUpperColor');
opt.handles.button.incrLowerColor = uicontrol(...
'Parent', opt.handles.buttongroup.color,...
'Units','normalized',...
'Enable', 'off', ...
'Callback',@cb_colorbar,...
'Position',[0.303092783505155 0.1449438202247191 0.17319587628866 0.0330711610486891],...
'String','+',...
'Tag','incrLowerColor');
opt.handles.button.incrUpperColor = uicontrol(...
'Parent', opt.handles.buttongroup.color,...
'Units','normalized',...
'Enable', 'off', ...
'Callback',@cb_colorbar,...
'Position',[0.303092783505155 0.9149438202247191 0.17319587628866 0.0330711610486891],...
'String','+',...
'Tag','incrUpperColor');
opt.handles.button.decrLowerColor = uicontrol(...
'Parent', opt.handles.buttongroup.color,...
'Units','normalized',...
'Enable', 'off', ...
'Callback',@cb_colorbar,...
'Position',[0.503092783505155 0.1449438202247191 0.17319587628866 0.0330711610486891],...
'String','-',...
'Tag','decrLowerColor');
opt.handles.axes.movie = axes(...
'Parent',opt.handles.figure,...
'Position',[-0.00110987791342952 0.150769230769231 0.722530521642619 0.847692307692308],...
'CameraPosition',[0.5 0.5 9.16025403784439],...
'CameraPositionMode',get(0,'defaultaxesCameraPositionMode'),...
'CLim',get(0,'defaultaxesCLim'),...
'CLimMode','manual',...
'Color',[0.941176470588235 0.941176470588235 0.941176470588235],...
'ColorOrder',get(0,'defaultaxesColorOrder'),...
'LooseInset',[0.120510948905109 0.11 0.088065693430657 0.075],...
'XColor',get(0,'defaultaxesXColor'),...
'YColor',get(0,'defaultaxesYColor'),...
'ZColor',get(0,'defaultaxesZColor'),...
'HandleVisibility', 'on', ...
'ButtonDownFcn',@(hObject,eventdata)test_movieplot_export('movieAxes_ButtonDownFcn',hObject,eventdata,guidata(hObject)),...
'Tag','movieAxes');
% Disable axis labels
axis(opt.handles.axes.movie, 'equal');
axis(opt.handles.axes.colorbar, 'equal');
axis(opt.handles.axes.topo, 'equal');
axis(opt.handles.axes.multi, 'equal');
axis(opt.handles.axes.single, 'equal');
axis(opt.handles.axes.movie, 'off');
axis(opt.handles.axes.colorbar, 'off');
axis(opt.handles.axes.topo, 'off');
axis(opt.handles.axes.multi, 'off');
axis(opt.handles.axes.single, 'off');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function updateMovie(opt, valx, valy)
if ~opt.issource
set(opt.handles.grid, 'cdata', griddata(opt.chanx, opt.chany, opt.mask(:,valx,valy).*opt.dat(:,valx,valy), opt.xdata, opt.nanmask.*opt.ydata, 'v4'));
else
set(opt.handles.mesh, 'FaceVertexCData', squeeze(opt.dat(:,valx,valy)));
set(opt.handles.mesh, 'FaceVertexAlphaData', squeeze(opt.mask(:,valx,valy)));
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CALLBACK FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_speed(h, eventdata)
if ~ishandle(h)
return
end
opt = guidata(h);
val = get(opt.handles.slider.speed, 'value');
val = exp(log(opt.MAX_SPEED) * (val-.5)./0.5);
% make sure we can easily get back to normal speed
if abs(val-opt.AVG_SPEED) < 0.08
val = opt.AVG_SPEED;
set(opt.handles.slider.speed, 'value', 0.5);
end
opt.speed = val;
if val >=100
set(opt.handles.label.speed, 'String', ['Speed ' num2str(opt.speed, '%.1f'), 'x'])
elseif val >= 10
set(opt.handles.label.speed, 'String', ['Speed ' num2str(opt.speed, '%.2f'), 'x'])
else
set(opt.handles.label.speed, 'String', ['Speed ' num2str(opt.speed, '%.3f'), 'x'])
end
guidata(h, opt);
uiresume;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CALLBACK FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_timer(obj, info, h)
if ~ishandle(h)
return
end
opt = guidata(h);
delta = opt.speed/size(opt.dat,opt.xdim);
val = get(opt.handles.slider.xparam, 'value');
val = val + delta;
if opt.record
if val>1
% stop recording
stop(opt.timer);
% save movie
if isfield(opt, 'framesfile') && ~isempty(opt.framesfile)
save(opt.framesfile, 'F');
end
% play movie
if ~isfield(opt, 'framespersec')
opt.framespersec = 4;
opt.movierpt = 3;
end
% reset again
val = 0;
set(opt.handles.slider.xparam, 'value', val);
cb_slider(h);
cb_recordbutton(opt.handles.button.record);
movie(opt.F, opt.movierpt, opt.framespersec);
guidata(h, opt);
return;
end
end
if val>1
val = val-1;
end
set(opt.handles.slider.xparam, 'value', val);
cb_slider(h);
if opt.record
if ~isfield(opt, 'F') % init F
opt.F(1) = getframe(opt.handles.figure);
else
opt.F(end+1) = getframe(opt.handles.figure);
end
guidata(h, opt);
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CALLBACK FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_slider(h, eventdata)
opt = guidata(h);
valx = get(opt.handles.slider.xparam, 'value');
valx = round(valx*(size(opt.dat,opt.xdim)-1))+1;
valx = min(valx, size(opt.dat,opt.xdim));
valx = max(valx, 1);
set(opt.handles.label.xparam, 'String', [opt.xparam ' ' num2str(opt.xvalues(valx), '%.2f') 's']);
if ~isempty(opt.yvalues)
valy = get(opt.handles.slider.yparam, 'value');
valy = round(valy*(size(opt.dat, opt.ydim)-1))+1;
valy = min(valy, size(opt.dat, opt.ydim));
valy = max(valy, 1);
set(opt.handles.label.yparam, 'String', [opt.yparam ' ' num2str(opt.yvalues(valy), '%.2f') 'Hz']);
else
valy = 1;
end
updateMovie(opt, valx, valy);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CALLBACK FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_playbutton(h, eventdata)
if ~ishandle(h)
return
end
opt = guidata(h);
switch get(h, 'string')
case 'Play'
set(h, 'string', 'Stop');
start(opt.timer);
case 'Stop'
set(h, 'string', 'Play');
stop(opt.timer);
end
uiresume;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CALLBACK FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_recordbutton(h, eventdata)
if ~ishandle(h)
return
end
opt = guidata(h);
opt.record = ~opt.record; % switch state
if isfield(opt, 'F')
opt = rmfield(opt, 'F');
end
if opt.record
% FIXME open new window to play in there, so that frame getting works
set(h, 'string', 'Stop');
start(opt.timer);
else
% FIXME set handle back to old window
set(h, 'string', 'Record');
stop(opt.timer);
end
guidata(h, opt);
%
% % This function should open a new window, plot in there, extract every
% % frame, store the movie in opt and return again
%
% % this is not needed, no new window is needed
% %scrsz = get(0, 'ScreenSize');
% %f = figure('Position',[1 1 scrsz(3) scrsz(4)]);
%
% % FIXME disable buttons (apart from RECORD) when recording
% % if record is pressed, stop recording and immediately return
%
% % adapted from ft_movieplotTFR
%
% % frequency/time selection
% if ~isempty(opt.yvalues) && any(~isnan(yvalues))
% if ~isempty(cfg.movietime)
% indx = cfg.movietime;
% for iFrame = 1:floor(size(opt.dat, opt.xdim)/cfg.samperframe)
% indy = ((iFrame-1)*cfg.samperframe+1):iFrame*cfg.samperframe;
% updateMovie(opt, indx, indy);
% F(iFrame) = getframe;
% end
% elseif ~isempty(cfg.moviefreq)
% indy = cfg.moviefreq;
% for iFrame = 1:floor(size(opt.dat, opt.ydim)/cfg.samperframe)
% indx = ((iFrame-1)*cfg.samperframe+1):iFrame*cfg.samperframe;
% updateMovie(opt, indx, indy);
% F(iFrame) = getframe;
% end
% else
% error('Either moviefreq or movietime should contain a bin number')
% end
% else
% for iFrame = 1:floor(size(opt.dat, opt.xdim)/cfg.samperframe)
% indx = ((iFrame-1)*cfg.samperframe+1):iFrame*cfg.samperframe;
% updateMovie(opt, indx, 1);
% F(iFrame) = getframe;
% end
% end
%
% % save movie
% if ~isempty(cfg.framesfile)
% save(cfg.framesfile, 'F');
% end
% % play movie
% movie(F, cfg.movierpt, cfg.framespersec);
uiresume;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CALLBACK FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_colormap(h, eventdata)
maps = get(h, 'String');
val = get(h, 'Value');
while ~strcmp(get(h, 'Tag'), 'mainFigure')
h = get(h, 'Parent');
end
opt = guidata(h);
cmap = colormap(opt.handles.axes.movie, maps{val});
if get(opt.handles.checkbox.auto, 'Value')
colormap(opt.handles.axes.movie, cmap);
else
adjust_colorbar(opt);
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CALLBACK FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_colorbar(h, eventdata)
if strcmp(get(h, 'Tag'), 'mainFigure') % this is the init call
incr = false;
decr = false;
else
incr = strcmp(get(h, 'String'), '+');
decr = strcmp(get(h, 'String'), '-');
lower = strfind(get(h, 'Tag'), 'Lower')>0;
while ~strcmp(get(h, 'Tag'), 'mainFigure')
h = get(h, 'Parent');
end
end
opt = guidata(h);
[zmin zmax] = caxis(opt.handles.axes.movie);
yLim = get(opt.handles.colorbar, 'YLim');
if incr
yTick = linspace(zmin, zmax, yLim(end));
if get(opt.handles.checkbox.symmetric, 'Value')
zmin = zmin - mean(diff(yTick));
zmax = zmax + mean(diff(yTick));
elseif (lower)
zmin = zmin + mean(diff(yTick));
else
zmax = zmax + mean(diff(yTick));
end
elseif decr
yTick = linspace(zmin, zmax, yLim(end));
if get(opt.handles.checkbox.symmetric, 'Value')
zmin = zmin + mean(diff(yTick));
zmax = zmax - mean(diff(yTick));
elseif (lower)
zmin = zmin - mean(diff(yTick));
else
zmax = zmax - mean(diff(yTick));
end
elseif get(opt.handles.checkbox.auto, 'Value') % if automatic
set(opt.handles.lines.upperColor, 'Visible', 'off');
set(opt.handles.lines.lowerColor, 'Visible', 'off');
set(opt.handles.lines.upperColor, 'YData', [yLim(end)/2 yLim(end)/2]);
set(opt.handles.lines.lowerColor, 'YData', [yLim(end)/2 yLim(end)/2]);
set(opt.handles.button.incrUpperColor, 'Enable', 'off');
set(opt.handles.button.decrUpperColor, 'Enable', 'off');
set(opt.handles.button.incrLowerColor, 'Enable', 'off');
set(opt.handles.button.decrLowerColor, 'Enable', 'off');
if get(opt.handles.checkbox.symmetric, 'Value') % maxabs
zmax = max(abs(opt.dat(:)));
zmin = -zmax;
else % maxmin
zmin = min(opt.dat(:));
zmax = max(opt.dat(:));
end
else
set(opt.handles.lines.upperColor, 'Visible', 'on');
set(opt.handles.lines.lowerColor, 'Visible', 'on')
set(opt.handles.button.incrUpperColor, 'Enable', 'on');
set(opt.handles.button.decrLowerColor, 'Enable', 'on');
if get(opt.handles.checkbox.symmetric, 'Value') % maxabs
set(opt.handles.button.decrUpperColor, 'Enable', 'off');
set(opt.handles.button.incrLowerColor, 'Enable', 'off');
zmax = max(abs(caxis(opt.handles.axes.movie)));
zmin = -zmax;
else
set(opt.handles.button.decrUpperColor, 'Enable', 'on');
set(opt.handles.button.incrLowerColor, 'Enable', 'on');
[zmin zmax] = caxis(opt.handles.axes.movie);
end
end % incr, decr, automatic, else
maps = get(opt.handles.menu.colormap, 'String');
cmap = colormap(opt.handles.axes.movie, maps{get(opt.handles.menu.colormap, 'Value')});
adjust_colorbar(opt);
if (gcf~=opt.handles.figure)
close gcf; % sometimes there is a new window that opens up
end
caxis(opt.handles.axes.movie, [zmin zmax]);
yTick = linspace(zmin, zmax, yLim(end));
% truncate intelligently/-ish
yTick = yTick(get(opt.handles.colorbar, 'YTick'));
yTick = num2str(yTick', 5);
set(opt.handles.colorbar, 'YTickLabel', yTick, 'FontSize', 8);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CALLBACK FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function cb_startDrag(h, eventdata)
f = get(h, 'Parent');
while ~strcmp(get(f, 'Tag'), 'mainFigure')
f = get(f, 'Parent');
end
opt = guidata(f);
opt.handles.current.line = h;
if strfind(get(h, 'Tag'), 'Color')>0
opt.handles.current.axes = opt.handles.colorbar;
opt.handles.current.color = true;
else
disp('Figure out if it works for xparam and yparam');
keyboard
end
set(f, 'WindowButtonMotionFcn', @cb_dragLine);
guidata(h, opt);
end
function cb_dragLine(h, eventdata)
opt = guidata(h);
pt = get(opt.handles.current.axes, 'CurrentPoint');
yLim = get(opt.handles.colorbar, 'YLim');
% upper (lower) bar must not below (above) lower (upper) bar
if ~(opt.handles.current.line == opt.handles.lines.upperColor && ...
(any(pt(3)*[1 1]<get(opt.handles.lines.lowerColor, 'YData')) || ...
yLim(end) <= pt(3))) ...
&& ~(opt.handles.current.line == opt.handles.lines.lowerColor && ...
(any(pt(3)*[1 1]>get(opt.handles.lines.upperColor, 'YData')) || ...
yLim(1) >= pt(3)))
set(opt.handles.current.line, 'YData', pt(3)*[1 1]);
end
adjust_colorbar(opt);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function adjust_colorbar(opt)
% adjust colorbar
upper = get(opt.handles.lines.upperColor, 'YData');
lower = get(opt.handles.lines.lowerColor, 'YData');
if any(round(upper)==0) || any(round(lower)==0)
return;
end
maps = get(opt.handles.menu.colormap, 'String');
cmap = colormap(opt.handles.axes.movie, maps{get(opt.handles.menu.colormap, 'Value')});
cmap(round(lower(1)):round(upper(1)), :) = repmat(cmap(round(lower(1)), :), 1+round(upper(1))-round(lower(1)), 1);
colormap(opt.handles.axes.movie, cmap);
end
function cb_stopDrag(h, eventdata)
while ~strcmp(get(h, 'Tag'), 'mainFigure')
h = get(h, 'Parent');
end
set(h, 'WindowButtonMotionFcn', '');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function opt = prepareBrainplot(opt)
if opt.issource
if isfield(opt, 'sulc')
vdat = opt.sulc;
vdat(vdat>0.5) = 0.5;
vdat(vdat<-0.5)= -0.5;
vdat = vdat-min(vdat);
vdat = 0.35.*(vdat./max(vdat))+0.3;
vdat = repmat(vdat,[1 3]);
mesh = ft_plot_mesh(opt.anatomy, 'edgecolor', 'none', 'vertexcolor', vdat);
else
mesh = ft_plot_mesh(opt.anatomy, 'edgecolor', 'none', 'facecolor', [0.5 0.5 0.5]);
end
lighting gouraud
set(mesh, 'Parent', opt.handles.axes.movie);
% mesh = ft_plot_mesh(source, 'edgecolor', 'none', 'vertexcolor', 0*opt.dat(:,1,1), 'facealpha', 0*opt.mask(:,1,1));
opt.handles.mesh = ft_plot_mesh(opt.anatomy, 'edgecolor', 'none', 'vertexcolor', opt.dat(:,1,1));
set(opt.handles.mesh, 'AlphaDataMapping', 'scaled');
set(opt.handles.mesh, 'FaceAlpha', 'interp');
set(opt.handles.mesh, 'FaceVertexAlphaData', opt.mask(:,1,1));
lighting gouraud
cam1 = camlight('left');
set(cam1, 'Parent', opt.handles.axes.movie);
cam2 = camlight('right');
set(cam2, 'Parent', opt.handles.axes.movie);
set(opt.handles.mesh, 'Parent', opt.handles.axes.movie);
% cameratoolbar(opt.handles.figure, 'Show');
else
axes(opt.handles.axes.movie)
[dum, opt.handles.grid] = ft_plot_topo(opt.layout.pos(sellay,1), opt.layout.pos(sellay,2), zeros(numel(sellay),1), 'mask', opt.layout.mask, 'outline', opt.layout.outline, 'interpmethod', 'v4', 'interplim', 'mask', 'parent', opt.handles.axes.movie);
%[dum, opt.handles.grid] = ft_plot_topo(layout.pos(sellay,1), layout.pos(sellay,2), zeros(numel(sellay),1), 'mask',layout.mask, 'outline', layout.outline, 'interpmethod', 'v4', 'interplim', 'mask', 'parent', opt.handles.axes.movie);
% set(opt.handles.grid, 'Parent', opt.handles.axes.movie);
opt.xdata = get(opt.handles.grid, 'xdata');
opt.ydata = get(opt.handles.grid, 'ydata');
opt.nanmask = 1-get(opt.handles.grid, 'cdata');
if (gcf~=opt.handles.figure)
close gcf; % sometimes there is a new window that opens up
end
end
end
|
github
|
philippboehmsturm/antx-master
|
nanvar.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/nanvar.m
| 1,093 |
utf_8
|
d9641af3bba1e2c6e3512199221e686c
|
% NANVAR provides a replacement for MATLAB's nanvar that is almost
% compatible.
%
% For usage see VAR. Note that the weight-vector is not supported. If you
% need it, please file a ticket at our bugtracker.
function Y = nanvar(X, w, dim)
switch nargin
case 1
% VAR(x)
% Normalize by n-1 when no dim is given.
Y = nanvar_base(X);
n = nannumel(X);
w = 0;
case 2
% VAR(x, 1)
% VAR(x, w)
% In this case, the default of normalizing by n is expected.
Y = nanvar_base(X);
n = nannumel(X);
case 3
% VAR(x, w, dim)
% if w=0 normalize by n-1, if w=1 normalize by n.
Y = nanvar_base(X, dim);
n = nannumel(X, dim);
otherwise
error ('Too many input arguments!')
end
% Handle different forms of normalization:
if numel(w) == 0
% empty weights vector defaults to 0
w = 0;
end
if numel(w) ~= 1
error('Weighting vector w is not implemented! Please file a bug.');
end
if ~isreal(X)
Y = real(Y) + imag(Y);
n = real(n);
end
if w == 1
Y = Y ./ n;
end
if w == 0
Y = Y ./ max(1, (n - 1)); % don't divide by zero!
end
|
github
|
philippboehmsturm/antx-master
|
tinv.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/tinv.m
| 7,634 |
utf_8
|
8fe66ec125f91e1a7ac5f8d3cb2ac51a
|
function x = tinv(p,v);
% TINV Inverse of Student's T cumulative distribution function (cdf).
% X=TINV(P,V) returns the inverse of Student's T cdf with V degrees
% of freedom, at the values in P.
%
% The size of X is the common size of P and V. A scalar input
% functions as a constant matrix of the same size as the other input.
%
% This is an open source function that was assembled by Eric Maris using
% open source subfunctions found on the web.
% Subversion does not use the Log keyword, use 'svn log <filename>' or 'svn -v log | less' to get detailled information
if nargin < 2,
error('Requires two input arguments.');
end
[errorcode p v] = distchck(2,p,v);
if errorcode > 0
error('Requires non-scalar arguments to match in size.');
end
% Initialize X to zero.
x=zeros(size(p));
k = find(v < 0 | v ~= round(v));
if any(k)
tmp = NaN;
x(k) = tmp(ones(size(k)));
end
k = find(v == 1);
if any(k)
x(k) = tan(pi * (p(k) - 0.5));
end
% The inverse cdf of 0 is -Inf, and the inverse cdf of 1 is Inf.
k0 = find(p == 0);
if any(k0)
tmp = Inf;
x(k0) = -tmp(ones(size(k0)));
end
k1 = find(p ==1);
if any(k1)
tmp = Inf;
x(k1) = tmp(ones(size(k1)));
end
k = find(p >= 0.5 & p < 1);
if any(k)
z = betainv(2*(1-p(k)),v(k)/2,0.5);
x(k) = sqrt(v(k) ./ z - v(k));
end
k = find(p < 0.5 & p > 0);
if any(k)
z = betainv(2*(p(k)),v(k)/2,0.5);
x(k) = -sqrt(v(k) ./ z - v(k));
end
%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION distchck
%%%%%%%%%%%%%%%%%%%%%%%%%
function [errorcode,varargout] = distchck(nparms,varargin)
%DISTCHCK Checks the argument list for the probability functions.
errorcode = 0;
varargout = varargin;
if nparms == 1
return;
end
% Get size of each input, check for scalars, copy to output
isscalar = (cellfun('prodofsize',varargin) == 1);
% Done if all inputs are scalars. Otherwise fetch their common size.
if (all(isscalar)), return; end
n = nparms;
for j=1:n
sz{j} = size(varargin{j});
end
t = sz(~isscalar);
size1 = t{1};
% Scalars receive this size. Other arrays must have the proper size.
for j=1:n
sizej = sz{j};
if (isscalar(j))
t = zeros(size1);
t(:) = varargin{j};
varargout{j} = t;
elseif (~isequal(sizej,size1))
errorcode = 1;
return;
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION betainv
%%%%%%%%%%%%%%%%%%%%%%%%%%%
function x = betainv(p,a,b);
%BETAINV Inverse of the beta cumulative distribution function (cdf).
% X = BETAINV(P,A,B) returns the inverse of the beta cdf with
% parameters A and B at the values in P.
%
% The size of X is the common size of the input arguments. A scalar input
% functions as a constant matrix of the same size as the other inputs.
%
% BETAINV uses Newton's method to converge to the solution.
% Reference:
% [1] M. Abramowitz and I. A. Stegun, "Handbook of Mathematical
% Functions", Government Printing Office, 1964.
% B.A. Jones 1-12-93
if nargin < 3,
error('Requires three input arguments.');
end
[errorcode p a b] = distchck(3,p,a,b);
if errorcode > 0
error('Requires non-scalar arguments to match in size.');
end
% Initialize x to zero.
x = zeros(size(p));
% Return NaN if the arguments are outside their respective limits.
k = find(p < 0 | p > 1 | a <= 0 | b <= 0);
if any(k),
tmp = NaN;
x(k) = tmp(ones(size(k)));
end
% The inverse cdf of 0 is 0, and the inverse cdf of 1 is 1.
k0 = find(p == 0 & a > 0 & b > 0);
if any(k0),
x(k0) = zeros(size(k0));
end
k1 = find(p==1);
if any(k1),
x(k1) = ones(size(k1));
end
% Newton's Method.
% Permit no more than count_limit interations.
count_limit = 100;
count = 0;
k = find(p > 0 & p < 1 & a > 0 & b > 0);
pk = p(k);
% Use the mean as a starting guess.
xk = a(k) ./ (a(k) + b(k));
% Move starting values away from the boundaries.
if xk == 0,
xk = sqrt(eps);
end
if xk == 1,
xk = 1 - sqrt(eps);
end
h = ones(size(pk));
crit = sqrt(eps);
% Break out of the iteration loop for the following:
% 1) The last update is very small (compared to x).
% 2) The last update is very small (compared to 100*eps).
% 3) There are more than 100 iterations. This should NEVER happen.
while(any(abs(h) > crit * abs(xk)) & max(abs(h)) > crit ...
& count < count_limit),
count = count+1;
h = (betacdf(xk,a(k),b(k)) - pk) ./ betapdf(xk,a(k),b(k));
xnew = xk - h;
% Make sure that the values stay inside the bounds.
% Initially, Newton's Method may take big steps.
ksmall = find(xnew < 0);
klarge = find(xnew > 1);
if any(ksmall) | any(klarge)
xnew(ksmall) = xk(ksmall) /10;
xnew(klarge) = 1 - (1 - xk(klarge))/10;
end
xk = xnew;
end
% Return the converged value(s).
x(k) = xk;
if count==count_limit,
fprintf('\nWarning: BETAINV did not converge.\n');
str = 'The last step was: ';
outstr = sprintf([str,'%13.8f'],h);
fprintf(outstr);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION betapdf
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function y = betapdf(x,a,b)
%BETAPDF Beta probability density function.
% Y = BETAPDF(X,A,B) returns the beta probability density
% function with parameters A and B at the values in X.
%
% The size of Y is the common size of the input arguments. A scalar input
% functions as a constant matrix of the same size as the other inputs.
% References:
% [1] M. Abramowitz and I. A. Stegun, "Handbook of Mathematical
% Functions", Government Printing Office, 1964, 26.1.33.
if nargin < 3,
error('Requires three input arguments.');
end
[errorcode x a b] = distchck(3,x,a,b);
if errorcode > 0
error('Requires non-scalar arguments to match in size.');
end
% Initialize Y to zero.
y = zeros(size(x));
% Return NaN for parameter values outside their respective limits.
k1 = find(a <= 0 | b <= 0 | x < 0 | x > 1);
if any(k1)
tmp = NaN;
y(k1) = tmp(ones(size(k1)));
end
% Return Inf for x = 0 and a < 1 or x = 1 and b < 1.
% Required for non-IEEE machines.
k2 = find((x == 0 & a < 1) | (x == 1 & b < 1));
if any(k2)
tmp = Inf;
y(k2) = tmp(ones(size(k2)));
end
% Return the beta density function for valid parameters.
k = find(~(a <= 0 | b <= 0 | x <= 0 | x >= 1));
if any(k)
y(k) = x(k) .^ (a(k) - 1) .* (1 - x(k)) .^ (b(k) - 1) ./ beta(a(k),b(k));
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION betacdf
%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function p = betacdf(x,a,b);
%BETACDF Beta cumulative distribution function.
% P = BETACDF(X,A,B) returns the beta cumulative distribution
% function with parameters A and B at the values in X.
%
% The size of P is the common size of the input arguments. A scalar input
% functions as a constant matrix of the same size as the other inputs.
%
% BETAINC does the computational work.
% Reference:
% [1] M. Abramowitz and I. A. Stegun, "Handbook of Mathematical
% Functions", Government Printing Office, 1964, 26.5.
if nargin < 3,
error('Requires three input arguments.');
end
[errorcode x a b] = distchck(3,x,a,b);
if errorcode > 0
error('Requires non-scalar arguments to match in size.');
end
% Initialize P to 0.
p = zeros(size(x));
k1 = find(a<=0 | b<=0);
if any(k1)
tmp = NaN;
p(k1) = tmp(ones(size(k1)));
end
% If is X >= 1 the cdf of X is 1.
k2 = find(x >= 1);
if any(k2)
p(k2) = ones(size(k2));
end
k = find(x > 0 & x < 1 & a > 0 & b > 0);
if any(k)
p(k) = betainc(x(k),a(k),b(k));
end
% Make sure that round-off errors never make P greater than 1.
k = find(p > 1);
p(k) = ones(size(k));
|
github
|
philippboehmsturm/antx-master
|
prepare_timefreq_data.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/prepare_timefreq_data.m
| 23,749 |
utf_8
|
70b5b3af723b814cdf5e9ac09f3c3317
|
function [cfg, data] = prepare_timefreq_data(cfg, varargin);
% PREPARE_TIMEFREQ_DATA collects the overlapping data from multiple ERPs
% or ERFs according to the channel/time/freq-selection in the configuration
% and returns it with a dimord of 'repl_chan_freq_time'.
%
% Supported input data is from TIMELOCKANALYSIS, TIMELOCKGRANDAVERAGE,
% FREQANALYSIS or FREQDESCRIPTIVES.
%
% Use as
% [cfg, data] = prepare_timefreq_data(cfg, varargin)
% where the configuration can contain
% cfg.channel = cell-array of size Nx1, see CHANNELSELECTION, or
% cfg.channelcmb = cell-array of size Nx2, see CHANNELCOMBINATION
% cfg.latency = [begin end], can be 'all' (default)
% cfg.frequency = [begin end], can be 'all' (default)
% cfg.avgoverchan = 'yes' or 'no' (default)
% cfg.avgovertime = 'yes' or 'no' (default)
% cfg.avgoverfreq = 'yes' or 'no' (default)
% cfg.datarepresentation = 'cell-array' or 'concatenated'
% cfg.precision = 'single' or 'double' (default)
%
% If the data contains both power- and cross-spectra, they will be concatenated
% and treated together. In that case you should specify cfg.channelcmb instead
% of cfg.channel.
%
% This function can serve as a subfunction for TIMEFREQRANDOMIZATION,
% TIMEFREQCLUSTER and other statistical functions, so that those functions
% do not have to do the bookkeeping themselves.
% KNOWN BUGS AND LIMITATIONS
% copying of data is not memory efficient for cell-array output
% cfg.precision is not used for cell-array output
% Copyright (C) 2004, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: prepare_timefreq_data.m 7123 2012-12-06 21:21:38Z roboos $
% set the defaults
if ~isfield(cfg, 'channel'), cfg.channel = 'all'; end
if ~isfield(cfg, 'channelcmb'), cfg.channelcmb = []; end
if ~isfield(cfg, 'latency'), cfg.latency = 'all'; end
if ~isfield(cfg, 'frequency'), cfg.frequency = 'all'; end
if ~isfield(cfg, 'avgoverchan'), cfg.avgoverchan = 'no'; end
if ~isfield(cfg, 'avgovertime'), cfg.avgovertime = 'no'; end
if ~isfield(cfg, 'avgoverfreq'), cfg.avgoverfreq = 'no'; end
if ~isfield(cfg, 'datarepresentation'), cfg.datarepresentation = 'cell-array'; end
if ~isfield(cfg, 'precision'), cfg.precision = 'double'; end
% initialize
containsdof = false;
% count the number of input datasets
Nvarargin = length(varargin);
remember = {};
% initialize
swapmemfile;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% collect information over all data sets required for a consistent selection
% this is the first time that the data will be swapped from file into memory
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for c=1:Nvarargin
% swap the data into memory
varargin{c} = swapmemfile(varargin{c});
% for backward compatibility with old data structures
varargin{c} = fixdimord(varargin{c});
% reformat the data, and combine cross and power spectra
[remember{c}, hascrsspctrm] = forcedimord(varargin{c});
% keep a small part of the data in memory
if hascrsspctrm
remember{c} = rmfield(remember{c}, 'dat');
remember{c} = rmfield(remember{c}, 'crs');
else
remember{c} = rmfield(remember{c}, 'dat');
end
% swap the data out of memory
varargin{c} = swapmemfile(varargin{c});
end
if hascrsspctrm
% by default this should be empty
cfg.channel = [];
if isempty(cfg.channelcmb)
% default is to copy the channelcombinations from the first dataset
% and these have been concatenated by forcedimord -> tear them apart
cfg.channelcmb = label2cmb(remember{1}.label);
end
% instead of matching channelcombinations, we will match channels that
% consist of the concatenated labels of the channelcombinations
cfg.channel = cmb2label(cfg.channelcmb);
cfg.channelcmb = []; % this will be reconstructed at the end
else
% by default this should be empty
cfg.channelcmb = [];
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% adjust the selection of channels, latency and frequency so that it
% matches with all datasets
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for c=1:Nvarargin
% match the channel selection with this dataset
cfg.channel = ft_channelselection(cfg.channel, remember{c}.label);
% match the selected latency with this dataset
if isempty(findstr(remember{c}.dimord, 'time')) || all(isnan(remember{c}.time))
cfg.latency = [];
elseif ischar(cfg.latency) && strcmp(cfg.latency, 'all')
cfg.latency = [];
cfg.latency(1) = min(remember{c}.time);
cfg.latency(2) = max(remember{c}.time);
else
cfg.latency(1) = max(cfg.latency(1), min(remember{c}.time));
cfg.latency(2) = min(cfg.latency(2), max(remember{c}.time));
end
% match the selected frequency with this dataset
if isempty(findstr(remember{c}.dimord, 'freq')) || all(isnan(remember{c}.freq))
cfg.frequency = [];
elseif ischar(cfg.frequency) && strcmp(cfg.frequency, 'all')
cfg.frequency = [];
cfg.frequency(1) = min(remember{c}.freq);
cfg.frequency(2) = max(remember{c}.freq);
else
cfg.frequency(1) = max(cfg.frequency(1), min(remember{c}.freq));
cfg.frequency(2) = min(cfg.frequency(2), max(remember{c}.freq));
end
% keep track of the number of replications
Nrepl(c) = length(remember{c}.repl);
end
% count the number of channels, time bins and frequency bins
dimord = remember{c}.dimord;
if ~isempty(cfg.latency) && ~all(isnan(cfg.latency))
timesel = nearest(remember{1}.time, cfg.latency(1)):nearest(remember{1}.time, cfg.latency(2));
else
timesel = 1;
end
if ~isempty(cfg.frequency) && ~all(isnan(cfg.frequency))
freqsel = nearest(remember{1}.freq, cfg.frequency(1)):nearest(remember{1}.freq, cfg.frequency(2));
else
freqsel = 1;
end
Nchan = length(cfg.channel);
Ntime = length(timesel);
Nfreq = length(freqsel);
if ~hascrsspctrm
% print the information for channels
if Nchan<1
error('channel selection is empty')
elseif strcmp(cfg.avgoverchan, 'yes')
fprintf('averaging over %d channels\n', Nchan);
Nchan = 1; % after averaging
else
fprintf('selected %d channels\n', Nchan);
end
else
% print the (same) information for channelcombinations
if Nchan<1
error('channelcombination selection is empty')
elseif strcmp(cfg.avgoverchan, 'yes')
fprintf('averaging over %d channelcombinations\n', Nchan);
Nchan = 1; % after averaging
else
fprintf('selected %d channelcombinations\n', Nchan);
end
end
if Ntime<1
error('latency selection is empty')
elseif strcmp(cfg.avgovertime, 'yes')
fprintf('averaging over %d time bins\n', Ntime);
Ntime = 1; % after averaging
else
fprintf('selected %d time bins\n', Ntime);
end
if Nfreq<1
error('latency selection is empty')
elseif strcmp(cfg.avgoverfreq, 'yes')
fprintf('averaging over %d frequency bins\n', Nfreq);
Nfreq = 1; % after averaging
else
fprintf('selected %d frequency bins\n', Nfreq);
end
% determine whether, and over which dimensions the data should be averaged
tok = tokenize(dimord, '_');
chandim = find(strcmp(tok, 'chan'));
timedim = find(strcmp(tok, 'time'));
freqdim = find(strcmp(tok, 'freq'));
avgdim = [];
if strcmp(cfg.avgoverchan, 'yes') && ~isempty(chandim)
avgdim = [avgdim chandim];
end
if strcmp(cfg.avgovertime, 'yes') && ~isempty(timedim)
avgdim = [avgdim timedim];
end
if strcmp(cfg.avgoverfreq, 'yes') && ~isempty(freqdim)
avgdim = [avgdim freqdim];
end
% this will hold the output data
if strcmp(cfg.datarepresentation, 'cell-array')
dat = {};
dof = {};
elseif strcmp(cfg.datarepresentation, 'concatenated')
% preallocate memory to hold all the data
if hascrsspctrm
if str2num(version('-release'))>=14
dat = complex(zeros(sum(Nrepl), Nchan, Nfreq, Ntime, cfg.precision));
else
% use double precision for default and Matlab versions prior to release 14
if ~strcmp(cfg.precision, 'double')
warning('Matlab versions prior to release 14 only support double precision');
end
dat = complex(zeros(sum(Nrepl), Nchan, Nfreq, Ntime));
end
else
if str2num(version('-release'))>=14
dat = zeros(sum(Nrepl), Nchan, Nfreq, Ntime, cfg.precision);
else
% use double precision for default and Matlab versions prior to release 14
if ~strcmp(cfg.precision, 'double')
warning('Matlab versions prior to release 14 only support double precision');
end
dat = zeros(sum(Nrepl), Nchan, Nfreq, Ntime);
end
end
if isempty(avgdim)
dof = zeros(sum(Nrepl), Nfreq, Ntime);
end;
else
error('unsupported output data representation');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% select the desired channels, latency and frequency bins from each dataset
% this is the second time that the data will be swapped from file into memory
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for c=1:Nvarargin
% swap the data into memory
varargin{c} = swapmemfile(varargin{c});
% reformat the data, and combine cross and power spectra
[varargin{c}, hascrsspctrm] = forcedimord(varargin{c});
% select the channels, sorted according to the order in the configuration
[dum, chansel] = match_str(cfg.channel, varargin{c}.label);
if ~isempty(cfg.latency)
timesel = nearest(varargin{c}.time, cfg.latency(1)):nearest(varargin{c}.time, cfg.latency(2));
end
if ~isempty(cfg.frequency)
freqsel = nearest(varargin{c}.freq, cfg.frequency(1)):nearest(varargin{c}.freq, cfg.frequency(2));
end
if hascrsspctrm
Nfreq = size(varargin{c}.crs, 3);
Ntime = size(varargin{c}.crs, 4);
% separate selection for the auto-spectra and cross-spectra
Ndat = size(varargin{c}.dat, 2); % count the total number of auto-spectra
Ncrs = size(varargin{c}.crs, 2); % count the total number of cross-spectra
[dum, chansel_dat] = ismember(chansel, 1:Ndat); % selection of auto-spectra
chansel_dat=chansel_dat(chansel_dat~=0)';
[dum, chansel_crs] = ismember(chansel, (1:Ncrs)+Ndat); % selection of cross-spectra
chansel_crs=chansel_crs(chansel_crs~=0)';
Ndatsel = length(chansel_dat); % count the number of selected auto-spectra
Ncrssel = length(chansel_crs); % count the number of selected cross-spectra
else
Nfreq = size(varargin{c}.dat, 3);
Ntime = size(varargin{c}.dat, 4);
end
% collect the data, average if required
if strcmp(cfg.datarepresentation, 'cell-array')
if hascrsspctrm
dat{c} = cat(2, avgoverdim(varargin{c}.dat(:, chansel_dat, freqsel, timesel), avgdim), avgoverdim(varargin{c}.crs(:, chansel_crs, freqsel, timesel), avgdim));
else
dat{c} = avgoverdim(varargin{c}.dat(:, chansel, freqsel, timesel), avgdim);
end
if isfield(varargin{c},'dof')
containsdof = isempty(avgdim);
if containsdof
dof{c} = varargin{c}.dof(:,freqsel,timesel);
else
warning('Degrees of freedom cannot be calculated if averaging over channels, frequencies, or time bins is requested.');
end;
end;
elseif strcmp(cfg.datarepresentation, 'concatenated')
if c==1
trialsel = 1:Nrepl(1);
else
trialsel = (1+sum(Nrepl(1:(c-1)))):sum(Nrepl(1:c));
end
% THIS IS IMPLEMENTED WITH STRICT MEMORY CONSIDERATIONS
% handle cross-spectrum and auto-spectrum separately
% first copy complex part (crs) then real part (pow), otherwise dat first will be made real and then complex again
% copy selection of "all" as complete matrix and not as selection
% copy selection with for loops (not yet implemented below)
if isempty(avgdim) && hascrsspctrm
if length(chansel_crs)==Ncrs && length(freqsel)==Nfreq && length(timesel)==Ntime && all(chansel_crs==(1:Ncrs)) && all(freqsel==(1:Nfreq)) && all(timesel==(1:Ntime))
% copy everything into the output data array
% this is more memory efficient than selecting everything
dat(trialsel,(1:Ncrssel)+Ndatsel,:,:) = varargin{c}.crs;
else
% copy only a selection into the output data array
% this could be made more memory efficient using for-loops
dat(trialsel,(1:Ncrssel)+Ndatsel,:,:) = varargin{c}.crs(:, chansel_crs, freqsel, timesel);
end
dat(trialsel,1:Ndatsel,:,:) = varargin{c}.dat(:, chansel_dat, freqsel, timesel);
elseif ~isempty(avgdim) && hascrsspctrm
if length(chansel_crs)==Ncrs && length(freqsel)==Nfreq && length(timesel)==Ntime && all(chansel_crs==(1:Ncrs)) && all(freqsel==(1:Nfreq)) && all(timesel==(1:Ntime))
% copy everything into the output data array
% this is more memory efficient than selecting everything
dat(trialsel,(1:Ncrssel)+Ndatsel,:,:) = avgoverdim(varargin{c}.crs, avgdim);
else
% copy only a selection into the output data array
% this could be made more memory efficient using for-loops
dat(trialsel,(1:Ncrssel)+Ndatsel,:,:) = avgoverdim(varargin{c}.crs(:, chansel_crs, freqsel, timesel), avgdim);
end
dat(trialsel,1:Ndatsel,:,:) = avgoverdim(varargin{c}.dat(:, chansel_dat, freqsel, timesel), avgdim);
elseif isempty(avgdim) && ~hascrsspctrm
dat(trialsel,:,:,:) = varargin{c}.dat(:, chansel, freqsel, timesel);
elseif ~isempty(avgdim) && ~hascrsspctrm
dat(trialsel,:,:,:) = avgoverdim(varargin{c}.dat(:, chansel, freqsel, timesel), avgdim);
end
if isfield(varargin{c},'dof')
containsdof = isempty(avgdim);
if containsdof
dof(trialsel,:,:) = varargin{c}.dof(:,freqsel,timesel);
else
warning('Degrees of freedom cannot be calculated if averaging over channels, frequencies, or time bins is requested.');
end;
end;
end
% swap the data out of memory
varargin{c} = swapmemfile(varargin{c});
end
% collect the output data
data.biol = dat;
data.dimord = dimord;
if containsdof
data.dof = dof;
end;
if strcmp(cfg.datarepresentation, 'concatenated')
% all trials are combined together, construct a design matrix to ensure
% that they can be identified afterwards
data.design(:,1) = 1:sum(Nrepl);
for c=1:Nvarargin
if c==1
trialsel = 1:Nrepl(1);
else
trialsel = (1+sum(Nrepl(1:(c-1)))):sum(Nrepl(1:c));
end
data.design(trialsel,2) = 1:length(trialsel);
data.design(trialsel,3) = c;
end
end
if ~hascrsspctrm
if strcmp(cfg.avgoverchan, 'yes')
concatlabel = sprintf('%s+', remember{end}.label{chansel}); % concatenate the labels with a '+' in between
concatlabel(end) = []; % remove the last '+'
data.label = {concatlabel}; % this should be a cell-array
else
data.label = remember{end}.label(chansel);
end
else
% specify the correct dimord and channelcombinations
labelcmb = label2cmb(remember{end}.label(chansel));
if strcmp(cfg.avgoverchan, 'yes')
% the cross-spectra have been averaged, therefore there is only one combination left
str1 = sprintf('%s+', labelcmb{:,1}); str1(end) = [];
str2 = sprintf('%s+', labelcmb{:,2}); str2(end) = [];
data.labelcmb = {str1, str2};
else
data.labelcmb = labelcmb;
end
% the dimord should specify chancmb instead of chan
s = strfind(dimord, 'chan');
data.dimord = [data.dimord(1:(s-1)) 'chancmb' data.dimord((s+4):end)];
end
if ~all(isnan(cfg.latency))
if strcmp(cfg.avgovertime, 'yes')
data.time = mean(remember{end}.time(timesel));
else
data.time = remember{end}.time(timesel);
end
else
% the output data contains a time dimension, but the input data did not contain a time axis
data.time = nan;
cfg.latency = [];
end
if ~all(isnan(cfg.frequency))
if strcmp(cfg.avgoverfreq, 'yes')
data.freq = mean(remember{end}.freq(freqsel));
else
data.freq = remember{end}.freq(freqsel);
end
else
% the output data contains a freq dimension, but the input data did not contain a freq axis
data.freq = nan;
cfg.frequency = [];
end
% add version information to the configuration
cfg.version.name = mfilename('fullpath');
cfg.version.id = '$Id: prepare_timefreq_data.m 7123 2012-12-06 21:21:38Z roboos $';
cfg.previous = [];
% remember the configuration details from the input data
for c=1:Nvarargin
try, cfg.previous{c} = remember{c}.cfg; end
end
% remember the full configuration details
data.cfg = cfg;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION to help with the averaging over multiple dimensions at the
% same time. Furthermore, the output data will have the same NUMBER of
% dimensions as the input data (i.e. no squeezing)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [dat] = avgoverdim(dat, dim);
siz = size(dat);
siz((end+1):4) = 1; % this should work at least up to 4 dimensions, also if not present in the data
for i=dim
siz(i) = 1;
dat = mean(dat, i); % compute the mean over this dimension
dat = reshape(dat, siz); % ensure that the number of dimenstions remains the same
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that reformats the data into a consistent struct with a fixed
% dimord and that combines power and cross-spectra
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [output, hascrsspctrm] = forcedimord(input);
% for backward compatibility with old timelockanalysis data that does not contain a dimord
if ~isfield(input, 'dimord') && isfield(input, 'avg') && isfield(input, 'var') && isfield(input, 'trial')
input.dimord = 'repl_chan_time';
elseif ~isfield(input, 'dimord') && isfield(input, 'avg') && isfield(input, 'var') && ~isfield(input, 'trial')
input.dimord = 'chan_time';
end
outputdim = tokenize('repl_chan_freq_time', '_');
inputdim = tokenize(input.dimord, '_');
% ensure consistent names of the dimensions
try, inputdim{strcmp(inputdim, 'rpt')} = 'repl'; end;
try, inputdim{strcmp(inputdim, 'rpttap')} = 'repl'; end;
try, inputdim{strcmp(inputdim, 'trial')} = 'repl'; end;
try, inputdim{strcmp(inputdim, 'subj')} = 'repl'; end;
try, inputdim{strcmp(inputdim, 'sgncmb')} = 'chan'; end;
try, inputdim{strcmp(inputdim, 'sgn')} = 'chan'; end;
try, inputdim{strcmp(inputdim, 'frq')} = 'freq'; end;
try, inputdim{strcmp(inputdim, 'tim')} = 'time'; end;
try, output.cfg = input.cfg; end; % general
try, output.time = input.time; end; % for ERPs and TFRs
try, output.freq = input.freq; end; % for frequency data
if isfield(input, 'powspctrm') && isfield(input, 'crsspctrm')
hascrsspctrm = 1;
chandim = find(strcmp(inputdim, 'chan'));
% concatenate powspctrm and crsspctrm
% output.dat = cat(chandim, input.powspctrm, input.crsspctrm);
% seperate output for auto and cross-spectra
output.dat = input.powspctrm;
output.crs = input.crsspctrm;
% concatenate the labels of the channelcombinations into one Nx1 cell-array
output.label = cmb2label([[input.label(:) input.label(:)]; input.labelcmb]);
elseif isfield(input, 'powspctrm')
hascrsspctrm = 0;
% output only power spectrum
output.dat = input.powspctrm;
output.label = input.label;
elseif isfield(input, 'fourierspctrm')
hascrsspctrm = 0;
% output only fourier spectrum
output.dat = input.fourierspctrm;
output.label = input.label;
else
hascrsspctrm = 0;
try, output.dat = input.avg; end; % for average ERP
try, output.dat = input.trial; end; % for average ERP with keeptrial
try, output.dat = input.individual; end; % for grandaverage ERP with keepsubject
output.label = input.label;
end
% determine the size of each dimension
repldim = find(strcmp(inputdim, 'repl'));
chandim = find(strcmp(inputdim, 'chan'));
freqdim = find(strcmp(inputdim, 'freq'));
timedim = find(strcmp(inputdim, 'time'));
if isempty(repldim)
Nrepl = 1;
else
Nrepl = size(output.dat, repldim);
end
if isempty(chandim)
error('data must contain channels');
else
if hascrsspctrm
Nchan = size(output.dat, chandim) + size(output.crs, chandim);
Ncrs = size(output.crs, chandim);
else
Nchan = size(output.dat, chandim);
end
end
if isempty(freqdim)
Nfreq = 1;
else
Nfreq = size(output.dat, freqdim);
end
if isempty(timedim)
Ntime = 1;
else
Ntime = size(output.dat, timedim);
end
% find the overlapping dimensions in the input and output
[dum, inputorder, outputorder] = intersect(inputdim, outputdim);
% sort them according to the specified output dimensions
[outputorder, indx] = sort(outputorder);
inputorder = inputorder(indx);
% rearrange the input dimensions in the same order as the desired output
if ~all(inputorder==sort(inputorder))
if hascrsspctrm
output.dat = permute(output.dat, inputorder);
output.crs = permute(output.crs, inputorder);
else
output.dat = permute(output.dat, inputorder);
end
end
% reshape the data so that it contains the (optional) singleton dimensions
if ~(size(output.dat,1)==Nrepl && size(output.dat,2)==Nchan && size(output.dat,3)==Nfreq && size(output.dat,4)==Ntime)
if hascrsspctrm
output.dat = reshape(output.dat, Nrepl, Nchan-Ncrs, Nfreq, Ntime);
output.crs = reshape(output.crs, Nrepl, Ncrs , Nfreq, Ntime);
else
output.dat = reshape(output.dat, Nrepl, Nchan, Nfreq, Ntime);
end
end
if isfield(input,'dof') && numel(input.dof)==Nrepl*Nfreq*Ntime
output.dof=reshape(input.dof, Nrepl, Nfreq, Ntime);
end;
% add the fields that describe the axes of the data
if ~isfield(output, 'time')
output.time = nan;
end
if ~isfield(output, 'freq')
output.freq = nan;
end
% create replication axis, analogous to time and frequency axis
output.repl = 1:Nrepl;
output.dimord = 'repl_chan_freq_time';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION convert Nx2 cell array with channel combinations into Nx1 cell array with labels
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function label = cmb2label(labelcmb);
label = {};
for i=1:size(labelcmb)
label{i,1} = [labelcmb{i,1} '&' labelcmb{i,2}];
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION convert Nx1 cell array with labels into N2x cell array with channel combinations
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function labelcmb = label2cmb(label);
labelcmb = {};
for i=1:length(label)
labelcmb(i,1:2) = tokenize(label{i}, '&');
end
|
github
|
philippboehmsturm/antx-master
|
bsscca.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/bsscca.m
| 7,428 |
utf_8
|
d64d6dd63efc92dff2aabe9e03c7dbb1
|
function [w,rho] = bsscca(X, delay)
% BSSCCA computes the unmixing matrix based on the canonical correlation between a signal and its lagged-one copy. It implements the algorithm described in [1]
%
% DeClercq et al 2006, IEEE Biomed Eng 2583.
if nargin<2,
delay = 1;
end
% hmmmm we need to observe the epochs' boundaries to not create rubbish
% support cell array input
if isa(X, 'cell')
delay = setdiff(delay(:)', 0);
n = size(X{1},1);
mX = cellmean(X,2);
X = cellvecadd(X, -mX);
C = cellcovshift(X,[0 delay],2,0);
m = size(C,1)-n;
XY = C(1:n, (n+1):end); % cross terms XY
XX = C(1:n, 1:n); % auto terms X;
YY = C((n+1):end, (n+1):end); % auto terms Y
YX = C((n+1):end, 1:n);
%A(1:n,1:n) = 0;
%A((n+1):end,(n+1):end) = 0;
%B(1:n,(n+1):end) = 0;
%B((n+1):end,1:n) = 0;
else
% input is a single data matrix assumed to be a continuous stretch
[n,m] = size(X);
% get the means
%m = ones(1,m-1);
%mX = mean(X(:,2:end),2); % lag zero
%mX2 = mean(X(:,1:end-1),2); % lag one
% use Borga's (2001) formulation from 'a unified approach to PCA, PLS, MLR
% and CCA'
A = zeros(2*n);
B = zeros(2*n);
if numel(delay)==1
Xlag = X(:,1:(m-delay));
else
end
XY = X(:,delay+(1:(m-delay)))*Xlag';
XX = X(:,delay+(1:(m-delay)))*X(:,delay+(1:(m-delay)))';
YY = Xlag*Xlag';
%XY = (X(:,2:end)-mX*m)*(X(:,1:end-1)-mX2*m)';
A(1:n,(n+1):end) = XY;
A((n+1):end,1:n) = XY';
B(1:n,1:n) = XX;
B((n+1):end,(n+1):end) = YY;
%B(1:n,1:n) = (X(:,2:end)-mX*m)*(X(:,2:end)-mX*m)';
%B((n+1):end,(n+1):end) = (X(:,1:end-1)-mX2*m)*(X(:,1:end-1)-mX2*m)';
end
%if cond(B)>1e8
% s = svd(B);
% [w,rho] = eig((B+eye(size(B,1))*s(1)*0.00000001)\A);
%else
% [w,rho] = eig(B\A);
%end
if cond(XX)>1e8
s = svd(XX);
XX = XX+eye(size(XX,1))*s(1)*0.00000001;
end
if cond(YY)>1e8
s = svd(YY);
YY = YY+eye(size(YY,1))*s(1)*0.00000001;
end
[wx,rho] = eig((XX\XY)*(YY\YX));
rho = sqrt(real(diag(rho)));
[dummy,ix] = sort(rho, 'descend');
rho = rho(ix);
wx = wx(:,ix);
w = wx';
%[dummy,ix] = sort(diag(abs(rho).^2),'descend');
%w = w(1:n,ix(2:2:end))';
%w = w(1:n,1:n);
%rho = abs(rho(ix(2:2:2*n),ix(2:2:2*n))).^2;
% normalise to unit norm
%for k= 1:size(w,1)
% w(k,:) = w(k,:)./norm(w(k,:));
%end
function [m] = cellmean(x, dim)
% [M] = CELLMEAN(X, DIM) computes the mean, across all cells in x along
% the dimension dim.
%
% X should be an linear cell-array of matrices for which the size in at
% least one of the dimensions should be the same for all cells
nx = size(x);
if ~iscell(x) || length(nx)>2 || all(nx>1),
error('incorrect input for cellmean');
end
if nargin==1,
scx1 = cellfun('size', x, 1);
scx2 = cellfun('size', x, 2);
if all(scx2==scx2(1)), dim = 2; %let second dimension prevail
elseif all(scx1==scx1(1)), dim = 1;
else error('no dimension to compute mean for');
end
end
nx = max(nx);
nsmp = cellfun('size', x, dim);
ssmp = cellfun(@sum, x, repmat({dim},1,nx), 'UniformOutput', 0);
m = sum(cell2mat(ssmp), dim)./sum(nsmp);
function [y] = cellvecadd(x, v)
% [Y]= CELLVECADD(X, V) - add vector to all rows or columns of each matrix
% in cell-array X
% check once and for all to save time
persistent bsxfun_exists;
if isempty(bsxfun_exists);
bsxfun_exists=(exist('bsxfun')==5);
if ~bsxfun_exists;
error('bsxfun not found.');
end
end
nx = size(x);
if ~iscell(x) || length(nx)>2 || all(nx>1),
error('incorrect input for cellmean');
end
if ~iscell(v),
v = repmat({v}, nx);
end
sx1 = cellfun('size', x, 1);
sx2 = cellfun('size', x, 2);
sv1 = cellfun('size', v, 1);
sv2 = cellfun('size', v, 2);
if all(sx1==sv1) && all(sv2==1),
dim = mat2cell([ones(length(sx2),1) sx2(:)]', repmat(2,nx(1),1), repmat(1,nx(2),1));
elseif all(sx2==sv2) && all(sv1==1),
dim = mat2cell([sx1(:) ones(length(sx1),1)]', repmat(2,nx(1),1), repmat(1,nx(2),1));
elseif all(sv1==1) && all(sv2==1),
dim = mat2cell([sx1(:) sx2(:)]'', nx(1), nx(2));
else error('inconsistent input');
end
y = cellfun(@bsxfun, repmat({@plus}, nx), x, v, 'UniformOutput', 0);
%y = cellfun(@vplus, x, v, dim, 'UniformOutput', 0);
function [c] = cellcov(x, y, dim, flag)
% [C] = CELLCOV(X, DIM) computes the covariance, across all cells in x along
% the dimension dim. When there are three inputs, covariance is computed between
% all cells in x and y
%
% X (and Y) should be linear cell-array(s) of matrices for which the size in at
% least one of the dimensions should be the same for all cells
if nargin<4 && iscell(y)
flag = 1;
elseif nargin<4 && isnumeric(y)
flag = dim;
end
if nargin<3 && iscell(y)
scx1 = cellfun('size', x, 1);
scx2 = cellfun('size', x, 2);
if all(scx2==scx2(1)), dim = 2; %let second dimension prevail
elseif all(scx1==scx1(1)), dim = 1;
else error('no dimension to compute covariance for');
end
elseif nargin<=3 && isnumeric(y)
dim = y;
end
if isnumeric(y), y = []; end
nx = size(x);
if ~iscell(x) || length(nx)>2 || all(nx>1),
error('incorrect input for cellmean');
end
if flag,
mx = cellmean(x, 2);
x = cellvecadd(x, -mx);
if ~isempty(y),
my = cellmean(y, 2);
y = cellvecadd(y, -my);
end
end
nx = max(nx);
nsmp = cellfun('size', x, dim);
if isempty(y),
csmp = cellfun(@covc, x, repmat({dim},1,nx), 'UniformOutput', 0);
else
csmp = cellfun(@covc, x, y, repmat({dim},1,nx), 'UniformOutput', 0);
end
nc = size(csmp{1});
c = sum(reshape(cell2mat(csmp), [nc(1) nc(2) nx]), 3)./sum(nsmp);
function [c] = covc(x, y, dim)
if nargin==2,
dim = y;
y = x;
end
if dim==1,
c = x'*y;
elseif dim==2,
c = x*y';
end
function [c] = cellcovshift(x, shift, dim, flag)
% [C] = CELLCOVSHIFT(X, SHIFT, DIM) computes the covariance, across all cells
% in x along the dimension dim.
%
% X should be linear cell-array(s) of matrices for which the size in at
% least one of the dimensions is be the same for all cells
if nargin<4,
flag = 1;
end
if nargin<3,
dim = find(size(x{1})>1, 1, 'first');
end
nx = size(x);
if ~iscell(x) || length(nx)>2 || all(nx>1) || ndims(x{1})>2,
error('incorrect input for cellcovshift');
end
% shift the time axis
y = cellshift(x, shift, dim);
% compute covariance
c = cellcov(y, dim, flag);
function [x] = cellshift(x, shift, dim, maxshift)
% CELLSHIFT(X, SHIFT, DIM)
if numel(shift)>1
x = x(:)';
y = cell(numel(shift),numel(x));
for k = 1:numel(shift)
y(k,:) = cellshift(x, shift(k), dim, max(abs(shift)));
end
for k = 1:size(y,2)
y{1,k} = cell2mat(y(:,k));
for m = 2:size(y,1)
y{m,k} = nan;
end
end
x = y(1,:);
return;
end
if nargin<4
maxshift = max(abs(shift));
end
if any(abs(shift))>abs(maxshift)
error('the value for maxshift should be >= shift');
end
if nargin<3
dim = find(size(x{1})>1, 1, 'first');
end
maxshift = abs(maxshift);
if numel(maxshift)==1, maxshift = maxshift([1 1]); end
nx = size(x);
if ~iscell(x) || length(nx)>2 || all(nx>1),
error('incorrect input for cellshift');
end
n = numel(x);
nsmp = cellfun('size', x, dim);
beg1 = ones(1,n) + shift + maxshift(1);
end1 = nsmp + shift - maxshift(2);
switch dim
case 1
for k = 1:n
x{k} = x{k}(beg1(k):end1(k),:);
end
case 2
for k = 1:n
x{k} = x{k}(:,beg1(k):end1(k));
end
otherwise
error('dimensionality of >2 is not supported');
end
|
github
|
philippboehmsturm/antx-master
|
inside_contour.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/inside_contour.m
| 1,106 |
utf_8
|
37d10e5d9a05c79551aac24c328e34aa
|
function bool = inside_contour(pos, contour);
npos = size(pos,1);
ncnt = size(contour,1);
x = pos(:,1);
y = pos(:,2);
minx = min(x);
miny = min(y);
maxx = max(x);
maxy = max(y);
bool = true(npos,1);
bool(x<minx) = false;
bool(y<miny) = false;
bool(x>maxx) = false;
bool(y>maxy) = false;
% the summed angle over the contour is zero if the point is outside, and 2*pi if the point is inside the contour
% leave some room for inaccurate f
critval = 0.1;
% the remaining points have to be investigated with more attention
sel = find(bool);
for i=1:length(sel)
contourx = contour(:,1) - pos(sel(i),1);
contoury = contour(:,2) - pos(sel(i),2);
angle = atan2(contoury, contourx);
% angle = unwrap(angle);
angle = my_unwrap(angle);
total = sum(diff(angle));
bool(sel(i)) = (abs(total)>critval);
end
function x = my_unwrap(x)
% this is a faster implementation of the MATLAB unwrap function
% with hopefully the same functionality
d = diff(x);
indx = find(abs(d)>pi);
for i=indx(:)'
if d(i)>0
x((i+1):end) = x((i+1):end) - 2*pi;
else
x((i+1):end) = x((i+1):end) + 2*pi;
end
end
|
github
|
philippboehmsturm/antx-master
|
smudge.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/smudge.m
| 1,949 |
utf_8
|
a793adc32ad1bfa0f193bd20c3ca7764
|
function [datout, S] = smudge(datin, tri, niter, threshold)
% SMUDGE(DATIN, TRI) computes a smudged version of the input data datain,
% given a triangulation tri. The algorithm is according to what is in
% MNE-Suite, documented in chapter 8.3
if nargin<3 || isempty(niter),
niter = 1;
end
if nargin<4
threshold = 0;
end
for k = 1:niter
[tmp, Stmp] = do_smudge(datin, tri, threshold);
if k==1,
S = Stmp;
else
S = Stmp*S;
end
datout = tmp;
datin = tmp;
end
function [datout, S] = do_smudge(datin, tri, threshold)
% number of points
npnt = numel(datin);
% non-zero points
nz = find(datin>threshold);
% triangles containing 1 or 2 non-zero points
nzt = ismember(tri, nz);
tnz = sum(nzt, 2)>0 & sum(nzt,2)<3;
% points with non-zero neighbours
nzn = tri(tnz, :);
nzt = nzt(tnz, :);
vec1 = zeros(size(nzn,1)*2,1);
vec2 = zeros(size(nzn,1)*2,1);
for k = 1:size(nzn,1)
indx0 = (k-1)*2+(1:2);
indx1 = nzn(k, nzt(k,:));
indx2 = nzn(k,~nzt(k,:));
vec1(indx0) = indx1;
vec2(indx0) = indx2;
end
% matrices that define edges which has one of the members 0
% sorted according to the left or the right column respectively
vecx = sortrows([vec1 vec2]); % having the non-zero vertex upfront, sorted accordingly
vecy = sortrows([vec2 vec1]); % having the zero vertex upfront, sorted accordingly
clear vec1 vec2;
% in a closed surface the edges occur in doubles
vecx = vecx(1:2:end,:);
vecy = vecy(1:2:end,:);
% vecx now has in the first column the column indices for matrix S
% vecx now has in the second column the row indices for matrix S
% reconstruct the value that has to be put into the matrix
[uval,i1,i2] = unique(vecy(:,1));
tmp = diff([0;vecy(:,1)])>0;
nix = diff(find([tmp;1]==1));
nix(end+1:numel(uval)) = 1;
[dummy,i1,i2] = unique(vecx(:,2));
val = 1./nix(i2);
S = sparse(vecx(:,2),vecx(:,1),val,npnt,npnt);
S = S + spdiags(datin(:)>threshold, 0, npnt, npnt);
datout = S*datin(:);
|
github
|
philippboehmsturm/antx-master
|
butter.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/butter.m
| 3,559 |
utf_8
|
ad82b4c04911a5ea11fd6bd2cc5fd590
|
% Copyright (C) 1999 Paul Kienzle
%
% This program 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 2 of the License, or
% (at your option) any later version.
%
% This program 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 this program; If not, see <http://www.gnu.org/licenses/>.
% Generate a butterworth filter.
% Default is a discrete space (Z) filter.
%
% [b,a] = butter(n, Wc)
% low pass filter with cutoff pi*Wc radians
%
% [b,a] = butter(n, Wc, 'high')
% high pass filter with cutoff pi*Wc radians
%
% [b,a] = butter(n, [Wl, Wh])
% band pass filter with edges pi*Wl and pi*Wh radians
%
% [b,a] = butter(n, [Wl, Wh], 'stop')
% band reject filter with edges pi*Wl and pi*Wh radians
%
% [z,p,g] = butter(...)
% return filter as zero-pole-gain rather than coefficients of the
% numerator and denominator polynomials.
%
% [...] = butter(...,'s')
% return a Laplace space filter, W can be larger than 1.
%
% [a,b,c,d] = butter(...)
% return state-space matrices
%
% References:
%
% Proakis & Manolakis (1992). Digital Signal Processing. New York:
% Macmillan Publishing Company.
% Author: Paul Kienzle <[email protected]>
% Modified by: Doug Stewart <[email protected]> Feb, 2003
function [a, b, c, d] = butter (n, W, varargin)
if (nargin>4 || nargin<2) || (nargout>4 || nargout<2)
usage ('[b, a] or [z, p, g] or [a,b,c,d] = butter (n, W [, "ftype"][,"s"])');
end
% interpret the input parameters
if (~(length(n)==1 && n == round(n) && n > 0))
error ('butter: filter order n must be a positive integer');
end
stop = 0;
digital = 1;
for i=1:length(varargin)
switch varargin{i}
case 's', digital = 0;
case 'z', digital = 1;
case { 'high', 'stop' }, stop = 1;
case { 'low', 'pass' }, stop = 0;
otherwise, error ('butter: expected [high|stop] or [s|z]');
end
end
[r, c]=size(W);
if (~(length(W)<=2 && (r==1 || c==1)))
error ('butter: frequency must be given as w0 or [w0, w1]');
elseif (~(length(W)==1 || length(W) == 2))
error ('butter: only one filter band allowed');
elseif (length(W)==2 && ~(W(1) < W(2)))
error ('butter: first band edge must be smaller than second');
end
if ( digital && ~all(W >= 0 & W <= 1))
error ('butter: critical frequencies must be in (0 1)');
elseif ( ~digital && ~all(W >= 0 ))
error ('butter: critical frequencies must be in (0 inf)');
end
% Prewarp to the band edges to s plane
if digital
T = 2; % sampling frequency of 2 Hz
W = 2/T*tan(pi*W/T);
end
% Generate splane poles for the prototype butterworth filter
% source: Kuc
C = 1; % default cutoff frequency
pole = C*exp(1i*pi*(2*[1:n] + n - 1)/(2*n));
if mod(n,2) == 1, pole((n+1)/2) = -1; end % pure real value at exp(i*pi)
zero = [];
gain = C^n;
% splane frequency transform
[zero, pole, gain] = sftrans(zero, pole, gain, W, stop);
% Use bilinear transform to convert poles to the z plane
if digital
[zero, pole, gain] = bilinear(zero, pole, gain, T);
end
% convert to the correct output form
if nargout==2,
a = real(gain*poly(zero));
b = real(poly(pole));
elseif nargout==3,
a = zero;
b = pole;
c = gain;
else
% output ss results
[a, b, c, d] = zp2ss (zero, pole, gain);
end
|
github
|
philippboehmsturm/antx-master
|
convert_event.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/convert_event.m
| 7,841 |
utf_8
|
e54a2ce9399657ba01d486a361f9d234
|
function [obj] = convert_event(obj, target, varargin)
% CONVERT_EVENT converts between the different representations of events,
% which can be
% 1) event structure, see FT_READ_EVENT
% 2) matrix representation as in trl (Nx3), see FT_DEFINETRIAL
% 3) matrix representation as in artifact (Nx2), see FT_ARTIFACT_xxx
% 4) boolean vector representation with 1 for samples containing trial/artifact
%
% Use as
% [object] = convert_event(object, target, ....)
%
% Possible input objects types are
% event structure
% Nx3 trl matrix, or cell array of multiple trl definitions
% Nx2 artifact matrix, or cell array of multiple artifact definitions
% boolean vector, or matrix with multiple vectors as rows
%
% Possible targets are 'event', 'trl', 'artifact', 'boolvec'
%
% Additional options should be specified in key-value pairs and can be
% 'endsample' =
% 'typenames' =
%
% See READ_EVENT, DEFINETRIAL, REJECTARTIFACT, ARTIFACT_xxx
% Copyright (C) 2009, Ingrid Nieuwenhuis
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: convert_event.m 7123 2012-12-06 21:21:38Z roboos $
% Check if target is specified correctly
if sum(strcmp(target, {'event', 'trl', 'artifact', 'boolvec'})) < 1
error('target has to be ''event'', ''trl'', ''artifact'', or ''boolvec''.')
end
% Get the options
endsample = ft_getopt(varargin, 'endsample');
typenames = ft_getopt(varargin, 'typenames');
% Determine what the input object is
if isempty(obj)
input_obj = 'empty';
elseif isstruct(obj)
input_obj = 'event';
elseif iscell(obj)
if isempty(obj{1})
input_obj = 'empty';
elseif size(obj{1},2) == 3
input_obj = 'trl';
elseif size(obj{1},2) == 2
input_obj = 'artifact';
elseif size(obj{1},2) > 3
% could be a strange trl-matrix with multiple columns
input_obj = 'trl';
for i = 1:length(obj)
if ~isempty(obj{i})
obj{i} = obj{i}(:,1:3);
end
end
else
error('incorrect input object, see help for what is allowed.')
end
elseif islogical(obj)
input_obj = 'boolvec';
elseif size(obj,2) == 3
input_obj = 'trl';
elseif size(obj,2) == 2
input_obj = 'artifact';
elseif size(obj,2) > 3
tmp = unique(obj);
if isempty(find(tmp>2, 1))
input_obj = 'boolvec';
obj = logical(obj);
else
%it is at least not boolean but could be a strange
%trl-matrix with multiple columns
input_obj = 'trl';
obj = obj(:,1:3);
end
else
error('incorrect input object, see help for what is allowed.')
end
% do conversion
if (strcmp(input_obj, 'trl') || strcmp(input_obj, 'artifact') || strcmp(input_obj, 'empty')) && strcmp(target, 'boolvec')
if ~isempty(endsample)
obj = artifact2artvec(obj,endsample);
else
obj = artifact2artvec(obj);
end
elseif strcmp(input_obj, 'boolvec') && strcmp(target,'artifact' )
obj = artvec2artifact(obj);
elseif strcmp(input_obj, 'boolvec') && strcmp(target,'trl' )
obj = artvec2artifact(obj);
if iscell(obj)
for i=1:length(obj)
obj{i}(:,3) = 0;
end
else
obj(:,3) = 0;
end
elseif (strcmp(input_obj, 'trl') || strcmp(input_obj, 'artifact')) && strcmp(target, 'event')
obj = artifact2event(obj, typenames);
elseif strcmp(input_obj, 'artifact') && strcmp(target,'trl')
if iscell(obj)
for i=1:length(obj)
obj{i}(:,3) = 0;
end
else
obj(:,3) = 0;
end
elseif strcmp(input_obj, 'trl') && strcmp(target,'artifact')
if iscell(obj)
for i=1:length(obj)
obj{i}(:,3:end) = [];
end
else
obj(:,3:end) = [];
end
elseif strcmp(input_obj, 'empty')
obj = [];
else
warning('conversion not supported yet') %FIXME
end
%%%%%%%%%%%%%%% SUBFUNCTION %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function artvec = artifact2artvec(varargin)
% ARTIFACT2ARTVEC makes boolian vector (or matrix when artifact is
% cell array of multiple artifact definitions) with 0 for artifact free
% sample and 1 for sample containing an artifact according to artifact
% specification. Length of vector is (from sample 1) last sample as
% defined in the artifact definition, or when datendsample is speciefied
% vector is length datendsample.
artifact = varargin{1};
if length(varargin) == 1
if ~iscell(artifact) % assume only one artifact is given
if isempty(artifact)
error('When input object is empty ''endsample'' must be specified to convert into boolvec')
else
endsample = max(artifact(:,2));
end
elseif length(artifact) == 1
if isempty(artifact{1})
error('When input object is empty ''endsample'' must be specified to convert into boolvec')
else
endsample = max(artifact{1}(:,2));
end
else
error('when giving multiple artifact definitions, endsample should be specified to assure all output vectors are of the same length')
end
elseif length(varargin) == 2
endsample = varargin{2};
elseif length(varargin) > 2
error('too many input arguments')
end
if ~iscell(artifact)
artifact = {artifact};
end
% make artvec
artvec = zeros(length(artifact), endsample);
breakflag = 0;
for i=1:length(artifact)
for j=1:size(artifact{i},1)
artbegsample = artifact{i}(j,1);
artendsample = artifact{i}(j,2);
if artbegsample > endsample
warning('artifact definition contains later samples than endsample, these samples are ignored')
break
elseif artendsample > endsample
warning('artifact definition contains later samples than endsample, these samples are ignored')
artendsample = endsample;
breakflag = 1;
end
artvec(i, artbegsample:artendsample) = 1;
if breakflag
break
end
end
end
%%%%%%%%%%%%%%% SUBFUNCTION %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function artifact = artvec2artifact(artvec)
% ARTVEC2ARTIFACT makes artifact definition (or cell array of artifact
% definitions) from boolian vector (or matrix) with [artbegsample
% artendsample]. Assumed is that the artvec starts with sample 1.
for i=1:size(artvec,1)
tmp = diff([0 artvec(i,:) 0]);
artbeg = find(tmp==+1);
artend = find(tmp==-1) - 1;
artifact{i} = [artbeg' artend'];
end
if length(artifact) == 1
artifact = artifact{1};
end
%%%%%%%%%%%%%%% SUBFUNCTION %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function event = artifact2event(artifact, typenames)
% ARTIFACT2EVENT makes event structure from artifact definition (or cell
% array of artifact definitions). event.type is always 'artifact', but
% incase of cellarays of artifacts is is also possible to hand 'typenames'
% with length(artifact)
if ~iscell(artifact)
artifact = {artifact};
end
if ~isempty(typenames)
if length(artifact) ~= length(typenames)
error('length typenames should be the same as length artifact')
end
end
event = [];
for i=1:length(artifact)
for j=1:size(artifact{i},1)
event(end+1).sample = artifact{i}(j,1);
event(end ).duration = artifact{i}(j,2)-artifact{i}(j,1)+1;
if ~isempty(typenames)
event(end).type = typenames{i};
elseif size(artifact{i},2) == 2
event(end).type = 'artifact';
elseif size(artifact{i},2) == 3
event(end).type = 'trial';
end
event(end ).value = [];
event(end ).offset = [];
end
end
|
github
|
philippboehmsturm/antx-master
|
fdr.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/fdr.m
| 1,987 |
utf_8
|
6d3291c124f575d01ad10bf51ec8854a
|
function [h] = fdr(p, q);
% FDR false discovery rate
%
% Use as
% h = fdr(p, q)
%
% This implements
% Genovese CR, Lazar NA, Nichols T.
% Thresholding of statistical maps in functional neuroimaging using the false discovery rate.
% Neuroimage. 2002 Apr;15(4):870-8.
% Copyright (C) 2005, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: fdr.m 7123 2012-12-06 21:21:38Z roboos $
% convert the input into a row vector
dim = size(p);
p = reshape(p, 1, numel(p));
% sort the observed uncorrected probabilities
[ps, indx] = sort(p);
% count the number of voxels
V = length(p);
% compute the threshold probability for each voxel
pi = ((1:V)/V) * q / c(V);
h = (ps<=pi);
% undo the sorting
[dum, unsort] = sort(indx);
h = h(unsort);
% convert the output back into the original format
h = reshape(h, dim);
function s = c(V)
% See Genovese, Lazar and Holmes (2002) page 872, second column, first paragraph
if V<1000
% compute it exactly
s = sum(1./(1:V));
else
% approximate it
s = log(V) + 0.57721566490153286060651209008240243104215933593992359880576723488486772677766467093694706329174674951463144724980708248096050401448654283622417399764492353625350033374293733773767394279259525824709491600873520394816567;
end
|
github
|
philippboehmsturm/antx-master
|
read_labview_dtlg.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/read_labview_dtlg.m
| 5,153 |
utf_8
|
9fc442c5cf83bbfd05e00c4acea65bed
|
function [dat] = read_labview_dtlg(filename, datatype);
% READ_LABVIEW_DTLG
%
% Use as
% dat = read_labview_dtlg(filename, datatype)
% where datatype can be 'int32' or 'int16'
%
% The output of this function is a structure.
% Copyright (C) 2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_labview_dtlg.m 7123 2012-12-06 21:21:38Z roboos $
fid = fopen(filename, 'r', 'ieee-be');
header = fread(fid, 4, 'uint8=>char')';
if ~strcmp(header, 'DTLG')
error('unsupported file, header should start with DTLG');
end
version = fread(fid, 4, 'char')'; % clear version
nd = fread(fid, 1, 'int32');
p = fread(fid, 1, 'int32');
% the following seems to work for files with version [7 0 128 0]
% but in files files with version [8 0 128 0] the length of the descriptor is not correct
ld = fread(fid, 1, 'int16');
descriptor = fread(fid, ld, 'uint8=>char')';
% ROBOOS: the descriptor should ideally be decoded, since it contains the variable
% name, type and size
% The first offset block always starts immediately after the data descriptor (at offset p, which should ideally be equal to 16+ld)
if nd<=128
% The first offset block contains the offsets for all data sets.
% In this case P points to the start of the offset block.
fseek(fid, p, 'bof');
offset = fread(fid, 128, 'uint32')';
else
% The first offset block contains the offsets for the first 128 data sets.
% The entries for the remaining data sets are stored in additional offset blocks.
% The locations of those blocks are contained in a block table starting at P.
offset = [];
fseek(fid, p, 'bof');
additional = fread(fid, 128, 'uint32');
for i=1:sum(additional>0)
fseek(fid, additional(i), 'bof');
tmp = fread(fid, 128, 'uint32')';
offset = cat(2, offset, tmp);
end
clear additional i tmp
end
% ROBOOS: remove the zeros in the offset array for non-existing datasets
offset = offset(1:nd);
% ROBOOS: how to determine the data datatype?
switch datatype
case 'uint32'
datasize = 4;
case 'int32'
datasize = 4;
case 'uint16'
datasize = 2;
case 'int16'
datasize = 2;
otherwise
error('unsupported datatype');
end
% If the data sets are n-dimensional arrays, the first n u32 longwords in each data
% set contain the array dimensions, imediately followed by the data values.
% ROBOOS: how to determine whether they are n-dimensional arrays?
% determine the number of dimensions by looking at the first array
% assume that all subsequent arrays have the same number of dimensions
if nd>1
estimate = (offset(2)-offset(1)); % initial estimate for the number of datasize in the array
fseek(fid, offset(1), 'bof');
n = fread(fid, 1, 'int32');
while mod(estimate-4*length(n), (datasize*prod(n)))~=0
% determine the number and size of additional array dimensions
n = cat(1, n, fread(fid, 1, 'int32'));
if datasize*prod(n)>estimate
error('could not determine array size');
end
end
ndim = length(n);
clear estimate n
else
estimate = filesize(fid)-offset;
fseek(fid, offset(1), 'bof');
n = fread(fid, 1, 'int32');
while mod(estimate-4*length(n), (datasize*prod(n)))~=0
% determine the number and size of additional array dimensions
n = cat(1, n, fread(fid, 1, 'int32'));
if datasize*prod(n)>estimate
error('could not determine array size');
end
end
ndim = length(n);
clear estimate n
end
% read the dimensions and the data from each array
for i=1:nd
fseek(fid, offset(i), 'bof');
n = fread(fid, ndim, 'int32')';
% Labview uses the C-convention for storing data, and Matlab uses the Fortran convention
n = fliplr(n);
data{i} = fread(fid, n, datatype);
end
clear i n ndim
fclose(fid);
% put all local variables into a structure, this is a bit unusual programming style
% the output structure is messy, but contains all relevant information
tmp = whos;
dat = [];
for i=1:length(tmp)
if isempty(strmatch(tmp(i).name, {'tmp', 'fid', 'ans', 'handles'}))
dat = setfield(dat, tmp(i).name, eval(tmp(i).name));
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% local helper function to determine the size of the file
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function siz = filesize(fid)
fp = ftell(fid);
fseek(fid, 0, 'eof');
siz = ftell(fid);
fseek(fid, fp, 'bof');
|
github
|
philippboehmsturm/antx-master
|
sphericalSplineInterpolate.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/sphericalSplineInterpolate.m
| 5,226 |
utf_8
|
27ce6fd83adee8c3957c477f73dad771
|
function [W,Gss,Gds,Hds]=sphericalSplineInterpolate(src,dest,lambda,order,type,tol)
%interpolate matrix for spherical interpolation
%
% W = sphericalSplineInterpolate(src,dest,lambda,order,type,tol)
%
% Inputs:
% src - [3 x N] old electrode positions
% dest - [3 x M] new electrode positions
% lambda - [float] regularisation parameter for smoothing the estimates (1e-5)
% order - [float] order of the polynomial interplotation to use (4)
% type - [str] one of; ('spline')
% 'spline' - spherical Spline
% 'slap' - surface Laplician (aka. CSD)
% tol - [float] tolerance for the legendre poly approx (1e-7)
% Outputs:
% W - [M x N] linear mapping matrix between old and new co-ords
%
% Based upon the paper: Perrin89
% Copyright 2009- by Jason D.R. Farquhar ([email protected])
% Permission is granted for anyone to copy, use, or modify this
% software and accompanying documents, provided this copyright
% notice is retained, and note is made of any changes that have been
% made. This software and documents are distributed without any
% warranty, express or implied.
if ( nargin < 3 || isempty(lambda) ) lambda=1e-5; end;
if ( nargin < 4 || isempty(order) ) order=4; end;
if ( nargin < 5 || isempty(type)) type='spline'; end;
if ( nargin < 6 || isempty(tol) ) tol=eps; end;
% map the positions onto the sphere (not using repop, by JMH)
src = src ./repmat(sqrt(sum(src.^2)), size(src, 1), 1); % src = repop(src,'./',sqrt(sum(src.^2)));
dest = dest./repmat(sqrt(sum(dest.^2)), size(dest, 1), 1); % dest = repop(dest,'./',sqrt(sum(dest.^2)));
%calculate the cosine of the angle between the new and old electrodes. If
%the vectors are on top of each other, the result is 1, if they are
%pointing the other way, the result is -1
cosSS = src'*src; % angles between source positions
cosDS = dest'*src; % angles between destination positions
% Compute the interpolation matrix to tolerance tol
[Gss] = interpMx(cosSS,order,tol); % [nSrc x nSrc]
[Gds Hds] = interpMx(cosDS,order,tol); % [nDest x nSrc]
% Include the regularisation
if ( lambda>0 ) Gss = Gss+lambda*eye(size(Gss)); end;
% Compute the mapping to the polynomial coefficients space % [nSrc+1 x nSrc+1]
% N.B. this can be numerically unstable so use the PINV to solve..
muGss=1;%median(diag(Gss)); % used to improve condition number when inverting. Probably uncessary
%C = [ Gss muGss*ones(size(Gss,1),1)];
C = [ Gss muGss*ones(size(Gss,1),1);...
muGss*ones(1,size(Gss,2)) 0];
iC = pinv(C);
% Compute the mapping from source measurements and positions to destination positions
if ( strcmp(lower(type),'spline') )
W = [Gds ones(size(Gds,1),1).*muGss]*iC(:,1:end-1); % [nDest x nSrc]
elseif (strcmp(lower(type),'slap'))
W = Hds*iC(1:end-1,1:end-1);%(:,1:end-1); % [nDest x nSrc]
end
return;
%--------------------------------------------------------------------------
function [G,H]=interpMx(cosEE,order,tol)
% compute the interpolation matrix for this set of point pairs
if ( nargin < 3 || isempty(tol) ) tol=1e-10; end;
G=zeros(size(cosEE)); H=zeros(size(cosEE));
for i=1:numel(cosEE);
x = cosEE(i);
n=1; Pns1=1; Pn=x; % seeds for the legendre ploy recurence
tmp = ( (2*n+1) * Pn ) / ((n*n+n).^order);
G(i) = tmp ; % 1st element in the sum
H(i) = (n*n+n)*tmp; % 1st element in the sum
oGi=inf; dG=abs(G(i)); oHi=inf; dH=abs(H(i));
for n=2:500; % do the sum
Pns2=Pns1; Pns1=Pn; Pn=((2*n-1)*x*Pns1 - (n-1)*Pns2)./n; % legendre poly recurance
oGi=G(i); oHi=H(i);
tmp = ((2*n+1) * Pn) / ((n*n+n).^order) ;
G(i) = G(i) + tmp; % update function estimate, spline interp
H(i) = H(i) + (n*n+n)*tmp; % update function estimate, SLAP
dG = (abs(oGi-G(i))+dG)/2; dH=(abs(oHi-H(i))+dH)/2; % moving ave gradient est for convergence
%fprintf('%d) dG =%g \t dH = %g\n',n,dG,dH);%abs(oGi-G(i)),abs(oHi-H(i)));
if ( dG<tol && dH<tol ) break; end; % stop when tol reached
end
end
G= G./(4*pi);
H= H./(4*pi);
return;
%--------------------------------------------------------------------------
function testCase()
src=randn(3,100); src(3,:)=abs(src(3,:)); src=repop(src,'./',sqrt(sum(src.^2))); % source points on sphere
dest=rand(3,30); dest(3,:)=abs(dest(3,:)); dest=repop(dest,'./',sqrt(sum(dest.^2))); % dest points on sphere
clf;scatPlot(src,'b.');
W=sphericalSplineInterpolate(src,dest);
W=sphericalSplineInterpolate(src(:,1:70),src);
clf;imagesc(W);
clf;jplot(src(1:2,1:70),W(70:75,:)');
z=jf_load('eeg/vgrid/nips2007/1-rect230ms','jh','flip_rc_sep');
z=jf_retain(z,'dim','ch','idx',[z.di(1).extra.iseeg]);
lambda=0; order=4;
chPos=[z.di(1).extra.pos3d];
incIdx=1:size(dest,2)-3; exIdx=setdiff(1:size(dest,2),incIdx); % included + excluded channels
W=sphericalSplineInterpolate(chPos(:,incIdx),chPos,lambda,order); % estimate the removed channels
clf;imagesc(W);
clf;jplot(chPos(:,incIdx),W(exIdx,:)');
% compare estimated with true
X=z.X(:,:,2);
Xest=W*z.X(incIdx,:,2);
clf;mcplot([X(exIdx(1),:);Xest(exIdx(1),:)]')
clf;subplot(211);mcplot(X');subplot(212);mcplot(Xest');
|
github
|
philippboehmsturm/antx-master
|
clusterstat.m
|
.m
|
antx-master/xspm8/external/fieldtrip/private/clusterstat.m
| 33,336 |
utf_8
|
40434805aa0d746d547a5ffad1b5f987
|
function [stat, cfg] = clusterstat(cfg, statrnd, statobs, varargin)
% SUBFUNCTION for computing cluster statistic for N-D volumetric source data
% or for channel-freq-time data
%
% This function uses
% cfg.dim
% cfg.inside (only for source data)
% cfg.tail = -1, 0, 1
% cfg.multivariate = no, yes
% cfg.orderedstats = no, yes
% cfg.clusterstatistic = max, maxsize, maxsum, wcm
% cfg.clusterthreshold = parametric, nonparametric_individual, nonparametric_common
% cfg.clusteralpha
% cfg.clustercritval
% cfg.wcm_weight
% cfg.feedback
% Copyright (C) 2005-2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: clusterstat.m 7123 2012-12-06 21:21:38Z roboos $
% set the defaults
if ~isfield(cfg,'orderedstats'), cfg.orderedstats = 'no'; end
if ~isfield(cfg,'multivariate'), cfg.multivariate = 'no'; end
if ~isfield(cfg,'minnbchan'), cfg.minnbchan=0; end
% if ~isfield(cfg,'channeighbstructmat'), cfg.channeighbstructmat=[]; end
% if ~isfield(cfg,'chancmbneighbstructmat'), cfg.chancmbneighbstructmat=[]; end
% if ~isfield(cfg,'chancmbneighbselmat'), cfg.chancmbneighbselmat=[]; end
% get issource from varargin, to determine source-data-specific options and allow the proper usage of cfg.neighbours
% (cfg.neighbours was previously used in determining wheter source-data was source data or not) set to zero by default
% note, this may cause problems when functions call clusterstat without giving issource, as issource was previously
% set in clusterstat.m but has now been transfered to the function that calls clusterstat.m (but only implemented in ft_statistics_montecarlo)
issource = ft_getopt(varargin, 'issource', false);
if cfg.tail~=cfg.clustertail
error('cfg.tail and cfg.clustertail should be identical')
end
% create neighbour structure (but only when not using source data)
if isfield(cfg, 'neighbours') && ~issource
channeighbstructmat = makechanneighbstructmat(cfg);
else
channeighbstructmat = 0;
end
% perform fixinside fix if input data is source data
if issource
% cfg contains dim and inside that are needed for reshaping the data to a volume, and inside should behave as a index vector
cfg = fixinside(cfg, 'index');
end
needpos = cfg.tail==0 || cfg.tail== 1;
needneg = cfg.tail==0 || cfg.tail==-1;
Nsample = size(statrnd,1);
Nrand = size(statrnd,2);
prb_pos = ones(Nsample, 1);
prb_neg = ones(Nsample, 1);
postailobs = false(Nsample, 1); % this holds the thresholded values
negtailobs = false(Nsample, 1); % this holds the thresholded values
postailrnd = false(Nsample,Nrand); % this holds the thresholded values
negtailrnd = false(Nsample,Nrand); % this holds the thresholded values
Nobspos = 0; % number of positive clusters in observed data
Nobsneg = 0; % number of negative clusters in observed data
if strcmp(cfg.clusterthreshold, 'parametric')
% threshold based on the critical value from parametric distribution
siz = size(cfg.clustercritval);
if all(siz==1) && cfg.clustertail==0
% it only specifies one critical value, assume that the left and right tail are symmetric around zero
negtailcritval = -cfg.clustercritval;
postailcritval = cfg.clustercritval;
elseif all(siz==1) && cfg.clustertail==-1
% it only specifies one critical value corresponding to the left tail
negtailcritval = cfg.clustercritval;
postailcritval = +inf * ones(size(negtailcritval));
elseif all(siz==1) && cfg.clustertail==1
% it only specifies one critical value corresponding to the right tail
postailcritval = cfg.clustercritval;
negtailcritval = -inf * ones(size(postailcritval));
elseif siz(1)==Nsample && siz(2)==1 && cfg.clustertail==0
% it specifies a single critical value for each sample, assume that the left and right tail are symmetric around zero
negtailcritval = -cfg.clustercritval;
postailcritval = cfg.clustercritval;
elseif siz(1)==Nsample && siz(2)==1 && cfg.clustertail==-1
% it specifies a critical value for the left tail
% which is different for each sample (samples have a different df)
negtailcritval = cfg.clustercritval;
postailcritval = +inf * ones(size(negtailcritval));
elseif siz(1)==Nsample && siz(2)==1 && cfg.clustertail==1
% it specifies a critical value for the right tail
% which is different for each sample (samples have a different df)
postailcritval = cfg.clustercritval;
negtailcritval = +inf * ones(size(postailcritval));
elseif siz(1)==Nsample && siz(2)==2 && cfg.clustertail==0
% it specifies a critical value for the left and for the right tail of the distribution
% which is different for each sample (samples have a different df)
negtailcritval = cfg.clustercritval(:,1);
postailcritval = cfg.clustercritval(:,2);
elseif prod(siz)==2 && cfg.clustertail==0
% it specifies a critical value for the left and for the right tail of the distribution
% which is the same for each sample (samples have the same df)
negtailcritval = cfg.clustercritval(1);
postailcritval = cfg.clustercritval(2);
else
error('cannot make sense out of the specified parametric critical values');
end
elseif strcmp(cfg.clusterthreshold, 'nonparametric_individual')
% threshold based on bootstrap using all other randomizations
% each voxel will get an individual threshold
[srt, ind] = sort(statrnd,2);
if cfg.clustertail==0
% both tails are needed
negtailcritval = srt(:,round(( cfg.clusteralpha/2)*size(statrnd,2)));
postailcritval = srt(:,round((1-cfg.clusteralpha/2)*size(statrnd,2)));
elseif cfg.clustertail==1
% only positive tail is needed
postailcritval = srt(:,round((1-cfg.clusteralpha)*size(statrnd,2)));
negtailcritval = -inf * ones(size(postailcritval));
elseif cfg.clustertail==1
% only negative tail is needed
negtailcritval = srt(:,round(( cfg.clusteralpha)*size(statrnd,2)));
postailcritval = +inf * ones(size(negtailcritval));
end
elseif strcmp(cfg.clusterthreshold, 'nonparametric_common')
% threshold based on bootstrap using all other randomizations
% all voxels will get a common threshold
[srt, ind] = sort(statrnd(:));
if cfg.clustertail==0
% both tails are needed
negtailcritval = srt(round(( cfg.clusteralpha/2)*prod(size(statrnd))));
postailcritval = srt(round((1-cfg.clusteralpha/2)*prod(size(statrnd))));
elseif cfg.clustertail==1
% only positive tail is needed
postailcritval = srt(round((1-cfg.clusteralpha)*prod(size(statrnd))));
negtailcritval = -inf * ones(size(postailcritval));
elseif cfg.clustertail==1
% only negative tail is needed
negtailcritval = srt(round(( cfg.clusteralpha)*prod(size(statrnd))));
postailcritval = +inf * ones(size(negtailcritval));
end
else
error('no valid threshold for clustering was given')
end % determine clusterthreshold
% these should be scalars or column vectors
negtailcritval = negtailcritval(:);
postailcritval = postailcritval(:);
% remember the critical values
cfg.clustercritval = [negtailcritval postailcritval];
% test whether the observed and the random statistics exceed the threshold
postailobs = (statobs >= postailcritval);
negtailobs = (statobs <= negtailcritval);
for i=1:Nrand
postailrnd(:,i) = (statrnd(:,i) >= postailcritval);
negtailrnd(:,i) = (statrnd(:,i) <= negtailcritval);
end
% first do the clustering on the observed data
if needpos,
if issource
if isfield(cfg, 'origdim'), cfg.dim = cfg.origdim; end %this snippet is to support correct clustering of N-dimensional data, not fully tested yet
tmp = zeros(cfg.dim);
tmp(cfg.inside) = postailobs;
numdims = length(cfg.dim);
if numdims == 2 || numdims == 3 % if 2D or 3D data
ft_hastoolbox('spm8',1);
[posclusobs, posnum] = spm_bwlabel(tmp, 2*numdims); % use spm_bwlabel for 2D/3D data to avoid usage of image toolbox
else
posclusobs = bwlabeln(tmp, conndef(length(cfg.dim),'min')); % spm_bwlabel yet (feb 2011) supports only 2D/3D data
end
posclusobs = posclusobs(cfg.inside);
else
if 0
posclusobs = findcluster(reshape(postailobs, [cfg.dim,1]),cfg.chancmbneighbstructmat,cfg.chancmbneighbselmat,cfg.minnbchan);
else
posclusobs = findcluster(reshape(postailobs, [cfg.dim,1]),channeighbstructmat,cfg.minnbchan);
end
posclusobs = posclusobs(:);
end
Nobspos = max(posclusobs); % number of clusters exceeding the threshold
fprintf('found %d positive clusters in observed data\n', Nobspos);
end
if needneg,
if issource
tmp = zeros(cfg.dim);
tmp(cfg.inside) = negtailobs;
numdims = length(cfg.dim);
if numdims == 2 || numdims == 3 % if 2D or 3D data
ft_hastoolbox('spm8',1);
[negclusobs, negnum] = spm_bwlabel(tmp, 2*numdims); % use spm_bwlabel for 2D/3D data to avoid usage of image toolbox
else
negclusobs = bwlabeln(tmp, conndef(length(cfg.dim),'min')); % spm_bwlabel yet (feb 2011) supports only 2D/3D data
end
negclusobs = negclusobs(cfg.inside);
else
if 0
negclusobs = findcluster(reshape(negtailobs, [cfg.dim,1]),cfg.chancmbneighbstructmat,cfg.chancmbneighbselmat,cfg.minnbchan);
else
negclusobs = findcluster(reshape(negtailobs, [cfg.dim,1]),channeighbstructmat,cfg.minnbchan);
end
negclusobs = negclusobs(:);
end
Nobsneg = max(negclusobs);
fprintf('found %d negative clusters in observed data\n', Nobsneg);
end
stat = [];
stat.stat = statobs;
% catch situation where no clustering of the random data is needed
if (Nobspos+Nobsneg)==0
warning('no clusters were found in the observed data');
stat.prob = ones(Nsample, 1);
return
end
% allocate space to hold the randomization distributions of the cluster statistic
if strcmp(cfg.multivariate, 'yes') || strcmp(cfg.orderedstats, 'yes')
fprintf('allocating space for a %d-multivariate distribution of the positive clusters\n', Nobspos);
fprintf('allocating space for a %d-multivariate distribution of the negative clusters\n', Nobsneg);
posdistribution = zeros(Nobspos,Nrand); % this holds the multivariate randomization distribution of the positive cluster statistics
negdistribution = zeros(Nobsneg,Nrand); % this holds the multivariate randomization distribution of the negative cluster statistics
else
posdistribution = zeros(1,Nrand); % this holds the statistic of the largest positive cluster in each randomization
negdistribution = zeros(1,Nrand); % this holds the statistic of the largest negative cluster in each randomization
end
% do the clustering on the randomized data
ft_progress('init', cfg.feedback, 'computing clusters in randomization');
for i=1:Nrand
ft_progress(i/Nrand, 'computing clusters in randomization %d from %d\n', i, Nrand);
if needpos,
if issource
tmp = zeros(cfg.dim);
tmp(cfg.inside) = postailrnd(:,i);
numdims = length(cfg.dim);
if numdims == 2 || numdims == 3 % if 2D or 3D data
[posclusrnd, posrndnum] = spm_bwlabel(tmp, 2*numdims); % use spm_bwlabel for 2D/3D data to avoid usage of image toolbox
else
posclusrnd = bwlabeln(tmp, conndef(length(cfg.dim),'min')); % spm_bwlabel yet (feb 2011) supports only 2D/3D data
end
posclusrnd = posclusrnd(cfg.inside);
else
if 0
posclusrnd = findcluster(reshape(postailrnd(:,i), [cfg.dim,1]),cfg.chancmbneighbstructmat,cfg.chancmbneighbselmat,cfg.minnbchan);
else
posclusrnd = findcluster(reshape(postailrnd(:,i), [cfg.dim,1]),channeighbstructmat,cfg.minnbchan);
end
posclusrnd = posclusrnd(:);
end
Nrndpos = max(posclusrnd); % number of clusters exceeding the threshold
stat = zeros(1,Nrndpos); % this will hold the statistic for each cluster
% fprintf('found %d positive clusters in this randomization\n', Nrndpos);
for j = 1:Nrndpos
if strcmp(cfg.clusterstatistic, 'max'),
stat(j) = max(statrnd(find(posclusrnd==j),i));
elseif strcmp(cfg.clusterstatistic, 'maxsize'),
stat(j) = length(find(posclusrnd==j));
elseif strcmp(cfg.clusterstatistic, 'maxsum'),
stat(j) = sum(statrnd(find(posclusrnd==j),i));
elseif strcmp(cfg.clusterstatistic, 'wcm'),
stat(j) = sum((statrnd(find(posclusrnd==j),i)-postailcritval).^cfg.wcm_weight);
else
error('unknown clusterstatistic');
end
end % for 1:Nrdnpos
if strcmp(cfg.multivariate, 'yes') || strcmp(cfg.orderedstats, 'yes')
stat = sort(stat, 'descend'); % sort them from most positive to most negative
if Nrndpos>Nobspos
posdistribution(:,i) = stat(1:Nobspos); % remember the largest N clusters
else
posdistribution(1:Nrndpos,i) = stat; % remember the largest N clusters
end
else
% univariate -> remember the most extreme cluster
if ~isempty(stat), posdistribution(i) = max(stat); end
end
end % needpos
if needneg,
if issource
tmp = zeros(cfg.dim);
tmp(cfg.inside) = negtailrnd(:,i);
numdims = length(cfg.dim);
if numdims == 2 || numdims == 3 % if 2D or 3D data
ft_hastoolbox('spm8',1);
[negclusrnd, negrndnum] = spm_bwlabel(tmp, 2*numdims); % use spm_bwlabel for 2D/3D to avoid usage of image toolbox
else
negclusrnd = bwlabeln(tmp, conndef(length(cfg.dim),'min')); % spm_bwlabel yet (feb 2011) supports only 2D/3D data
end
negclusrnd = negclusrnd(cfg.inside);
else
if 0
negclusrnd = findcluster(reshape(negtailrnd(:,i), [cfg.dim,1]),cfg.chancmbneighbstructmat,cfg.chancmbneighbselmat,cfg.minnbchan);
else
negclusrnd = findcluster(reshape(negtailrnd(:,i), [cfg.dim,1]),channeighbstructmat,cfg.minnbchan);
end
negclusrnd = negclusrnd(:);
end
Nrndneg = max(negclusrnd); % number of clusters exceeding the threshold
stat = zeros(1,Nrndneg); % this will hold the statistic for each cluster
% fprintf('found %d negative clusters in this randomization\n', Nrndneg);
for j = 1:Nrndneg
if strcmp(cfg.clusterstatistic, 'max'),
stat(j) = min(statrnd(find(negclusrnd==j),i));
elseif strcmp(cfg.clusterstatistic, 'maxsize'),
stat(j) = -length(find(negclusrnd==j)); % encode the size of a negative cluster as a negative value
elseif strcmp(cfg.clusterstatistic, 'maxsum'),
stat(j) = sum(statrnd(find(negclusrnd==j),i));
elseif strcmp(cfg.clusterstatistic, 'wcm'),
stat(j) = -sum((abs(statrnd(find(negclusrnd==j),i)-negtailcritval)).^cfg.wcm_weight); % encoded as a negative value
else
error('unknown clusterstatistic');
end
end % for 1:Nrndneg
if strcmp(cfg.multivariate, 'yes') || strcmp(cfg.orderedstats, 'yes')
stat = sort(stat, 'ascend'); % sort them from most negative to most positive
if Nrndneg>Nobsneg
negdistribution(:,i) = stat(1:Nobsneg); % remember the most extreme clusters, i.e. the most negative
else
negdistribution(1:Nrndneg,i) = stat; % remember the most extreme clusters, i.e. the most negative
end
else
% univariate -> remember the most extreme cluster, which is the most negative
if ~isempty(stat), negdistribution(i) = min(stat); end
end
end % needneg
end % for 1:Nrand
ft_progress('close');
% compare the values for the observed clusters with the randomization distribution
if needpos,
posclusters = [];
stat = zeros(1,Nobspos);
for j = 1:Nobspos
if strcmp(cfg.clusterstatistic, 'max'),
stat(j) = max(statobs(find(posclusobs==j)));
elseif strcmp(cfg.clusterstatistic, 'maxsize'),
stat(j) = length(find(posclusobs==j));
elseif strcmp(cfg.clusterstatistic, 'maxsum'),
stat(j) = sum(statobs(find(posclusobs==j)));
elseif strcmp(cfg.clusterstatistic, 'wcm'),
stat(j) = sum((statobs(find(posclusobs==j))-postailcritval).^cfg.wcm_weight);
else
error('unknown clusterstatistic');
end
end
% sort the clusters based on their statistical value
[stat, indx] = sort(stat,'descend');
% reorder the cluster indices in the data
tmp = zeros(size(posclusobs));
for j=1:Nobspos
tmp(find(posclusobs==indx(j))) = j;
end
posclusobs = tmp;
if strcmp(cfg.multivariate, 'yes')
% estimate the probability of the mutivariate tail, i.e. one p-value for all clusters
prob = 0;
for i=1:Nrand
% compare all clusters simultaneosuly
prob = prob + any(posdistribution(:,i)>stat(:));
end
if isequal(cfg.numrandomization, 'all')
prob = prob/Nrand;
else % the minimum possible p-value should not be 0, but 1/N
prob = (prob + 1)/(Nrand + 1);
end
for j = 1:Nobspos
% collect a summary of the cluster properties
posclusters(j).prob = prob;
posclusters(j).clusterstat = stat(j);
end
% collect the probabilities in one large array
prb_pos(find(posclusobs~=0)) = prob;
elseif strcmp(cfg.orderedstats, 'yes')
% compare the Nth ovbserved cluster against the randomization distribution of the Nth cluster
prob = zeros(1,Nobspos);
for j = 1:Nobspos
if isequal(cfg.numrandomization, 'all')
prob(j) = sum(posdistribution(j,:)>stat(j))/Nrand;
else % the minimum possible p-value should not be 0, but 1/N
prob(j) = (sum(posdistribution(j,:)>stat(j)) + 1)/(Nrand + 1);
end
% collect a summary of the cluster properties
posclusters(j).prob = prob(j);
posclusters(j).clusterstat = stat(j);
% collect the probabilities in one large array
prb_pos(find(posclusobs==j)) = prob(j);
end
else
% univariate -> each cluster has it's own probability
prob = zeros(1,Nobspos);
for j = 1:Nobspos
if isequal(cfg.numrandomization, 'all')
prob(j) = sum(posdistribution>stat(j))/Nrand;
else % the minimum possible p-value should not be 0, but 1/N
prob(j) = (sum(posdistribution>stat(j)) + 1)/(Nrand + 1);
end
% collect a summary of the cluster properties
posclusters(j).prob = prob(j);
posclusters(j).clusterstat = stat(j);
% collect the probabilities in one large array
prb_pos(find(posclusobs==j)) = prob(j);
end
end
end
if needneg,
negclusters = [];
stat = zeros(1,Nobsneg);
for j = 1:Nobsneg
if strcmp(cfg.clusterstatistic, 'max'),
stat(j) = min(statobs(find(negclusobs==j)));
elseif strcmp(cfg.clusterstatistic, 'maxsize'),
stat(j) = -length(find(negclusobs==j)); % encode the size of a negative cluster as a negative value
elseif strcmp(cfg.clusterstatistic, 'maxsum'),
stat(j) = sum(statobs(find(negclusobs==j)));
elseif strcmp(cfg.clusterstatistic, 'wcm'),
stat(j) = -sum((abs(statobs(find(negclusobs==j))-negtailcritval)).^cfg.wcm_weight); % encoded as a negative value
else
error('unknown clusterstatistic');
end
end
% sort the clusters based on their statistical value
[stat, indx] = sort(stat,'ascend');
% reorder the cluster indices in the observed data
tmp = zeros(size(negclusobs));
for j=1:Nobsneg
tmp(find(negclusobs==indx(j))) = j;
end
negclusobs = tmp;
if strcmp(cfg.multivariate, 'yes')
% estimate the probability of the mutivariate tail, i.e. one p-value for all clusters
prob = 0;
for i=1:Nrand
% compare all clusters simultaneosuly
prob = prob + any(negdistribution(:,i)<stat(:));
end
if isequal(cfg.numrandomization, 'all')
prob = prob/Nrand;
else % the minimum possible p-value should not be 0, but 1/N
prob = (prob + 1)/(Nrand + 1);
end
for j = 1:Nobsneg
% collect a summary of the cluster properties
negclusters(j).prob = prob;
negclusters(j).clusterstat = stat(j);
end
% collect the probabilities in one large array
prb_neg(find(negclusobs~=0)) = prob;
elseif strcmp(cfg.orderedstats, 'yes')
% compare the Nth ovbserved cluster against the randomization distribution of the Nth cluster
prob = zeros(1,Nobsneg);
for j = 1:Nobsneg
if isequal(cfg.numrandomization, 'all')
prob(j) = sum(negdistribution(j,:)<stat(j))/Nrand;
else % the minimum possible p-value should not be 0, but 1/N
prob(j) = (sum(negdistribution(j,:)<stat(j)) + 1)/(Nrand + 1);
end
% collect a summary of the cluster properties
negclusters(j).prob = prob(j);
negclusters(j).clusterstat = stat(j);
% collect the probabilities in one large array
prb_neg(find(negclusobs==j)) = prob(j);
end
else
% univariate -> each cluster has it's own probability
prob = zeros(1,Nobsneg);
for j = 1:Nobsneg
if isequal(cfg.numrandomization, 'all')
prob(j) = sum(negdistribution<stat(j))/Nrand;
else % the minimum possible p-value should not be 0, but 1/N
prob(j) = (sum(negdistribution<stat(j)) + 1)/(Nrand + 1);
end
% collect a summary of the cluster properties
negclusters(j).prob = prob(j);
negclusters(j).clusterstat = stat(j);
% collect the probabilities in one large array
prb_neg(find(negclusobs==j)) = prob(j);
end
end
end
if cfg.tail==0
% consider both tails
prob = min(prb_neg, prb_pos); % this is the probability for the most unlikely tail
elseif cfg.tail==1
% only consider the positive tail
prob = prb_pos;
elseif cfg.tail==-1
% only consider the negative tail
prob = prb_neg;
end
% collect the remaining details in the output structure
stat.prob = prob;
if needpos,
stat.posclusters = posclusters;
stat.posclusterslabelmat = posclusobs;
stat.posdistribution = posdistribution;
end
if needneg,
stat.negclusters = negclusters;
stat.negclusterslabelmat = negclusobs;
stat.negdistribution = negdistribution;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% BEGIN SUBFUNCTION MAKECHANNEIGHBSTRUCTMAT
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function channeighbstructmat = makechanneighbstructmat(cfg);
% MAKECHANNEIGHBSTRUCTMAT makes the makes the matrix containing the channel
% neighbourhood structure.
% because clusterstat has no access to the actual data (containing data.label), this workaround is required
% cfg.neighbours is cleared here because it is not done where avgoverchan is effectuated (it should actually be changed there)
if strcmp(cfg.avgoverchan, 'no')
nchan=length(cfg.channel);
elseif strcmp(cfg.avgoverchan, 'yes')
nchan = 1;
cfg.neighbours = [];
end
channeighbstructmat = false(nchan,nchan);
for chan=1:length(cfg.neighbours)
[seld] = match_str(cfg.channel, cfg.neighbours(chan).label);
[seln] = match_str(cfg.channel, cfg.neighbours(chan).neighblabel);
if isempty(seld)
% this channel was not present in the data
continue;
else
% add the neighbours of this channel to the matrix
channeighbstructmat(seld, seln) = true;
end
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% BEGIN SUBFUNCTION MAKECHANCMBNEIGHBMATS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [chancmbneighbstructmat, chancmbneighbselmat] = makechancmbneighbmats(channeighbstructmat,labelcmb,label,orderedchancmbs,original);
% compute CHANCMBNEIGHBSTRUCTMAT and CHANCMBNEIGHBSELMAT, which will be
% used for clustering channel combinations.
nchan=length(label);
nchansqr=nchan^2;
% Construct an array labelcmbnrs from labelcmb by replacing the label pairs
% in labelcmb by numbers that correspond to the order of the labels in label.
nchancmb = size(labelcmb,1);
labelcmbnrs=zeros(nchancmb,2);
for chanindx=1:nchan
[chansel1] = match_str(labelcmb(:,1),label(chanindx));
labelcmbnrs(chansel1,1)=chanindx;
[chansel2] = match_str(labelcmb(:,2),label(chanindx));
labelcmbnrs(chansel2,2)=chanindx;
end;
% Calculate the row and column indices (which are identical) of the
% channel combinations that are present in the data.
chancmbindcs=zeros(nchancmb,1);
for indx=1:nchancmb
chancmbindcs(indx)=(labelcmbnrs(indx,1)-1)*nchan + labelcmbnrs(indx,2);
end;
% put all elements on the diagonal of CHANNEIGHBSTRUCTMAT equal to one
channeighbstructmat=channeighbstructmat | logical(eye(nchan));
% Compute CHANCMBNEIGHBSTRUCTMAT
% First compute the complete CHANCMBNEIGHBSTRUCTMAT (containing all
% ORDERED channel combinations that can be formed with all channels present in
% the data) and later select and reorder the channel combinations actually
% present in data). In the complete CHANCMBNEIGHBSTRUCTMAT, the row and the
% column pairs are ordered lexicographically.
chancmbneighbstructmat = false(nchansqr);
if original
% two channel pairs are neighbours if their first elements are
% neighbours
chancmbneighbstructmat = logical(kron(channeighbstructmat,ones(nchan)));
% or if their second elements are neighbours
chancmbneighbstructmat = chancmbneighbstructmat | logical(kron(ones(nchan),channeighbstructmat));
else % version that consumes less memory
for chanindx=1:nchan
% two channel pairs are neighbours if their first elements are neighbours
% or if their second elements are neighbours
chancmbneighbstructmat(:,((chanindx-1)*nchan + 1):(chanindx*nchan)) = ...
logical(kron(channeighbstructmat(:,chanindx),ones(nchan))) | ...
logical(kron(ones(nchan,1),channeighbstructmat));
end;
end;
if ~orderedchancmbs
if original
% or if the first element of the row channel pair is a neighbour of the
% second element of the column channel pair
chancmbneighbstructmat = chancmbneighbstructmat | logical(repmat(kron(channeighbstructmat,ones(nchan,1)), [1 nchan]));
% or if the first element of the column channel pair is a neighbour of the
% second element of the row channel pair
chancmbneighbstructmat = chancmbneighbstructmat | logical(repmat(kron(channeighbstructmat,ones(1,nchan)),[nchan 1]));
else
for chanindx=1:nchan
% two channel pairs are neighbours if
% the first element of the row channel pair is a neighbour of the
% second element of the column channel pair
% or if the first element of the column channel pair is a neighbour of the
% second element of the row channel pair
chancmbneighbstructmat(:,((chanindx-1)*nchan + 1):(chanindx*nchan)) = ...
chancmbneighbstructmat(:,((chanindx-1)*nchan + 1):(chanindx*nchan)) | ...
logical(kron(channeighbstructmat,ones(nchan,1))) | ...
logical(repmat(kron(channeighbstructmat(:,chanindx),ones(1,nchan)),[nchan 1]));
end;
end;
end;
% reorder and select the entries in chancmbneighbstructmat such that they correspond to labelcmb.
chancmbneighbstructmat = sparse(chancmbneighbstructmat);
chancmbneighbstructmat = chancmbneighbstructmat(chancmbindcs,chancmbindcs);
% compute CHANCMBNEIGHBSELMAT
% CHANCMBNEIGHBSELMAT identifies so-called parallel pairs. A channel pair
% is parallel if (a) all four sensors are different and (b) all elements (of the first
% and the second pair) are neighbours of an element of the other pair.
% if orderedpairs is true, then condition (b) is as follows: the first
% elements of the two pairs are neighbours, and the second elements of the
% two pairs are neighbours.
% put all elements on the diagonal of CHANNEIGHBSTRUCTMAT equal to zero
channeighbstructmat = logical(channeighbstructmat.*(ones(nchan)-diag(ones(nchan,1))));
chancmbneighbselmat = false(nchansqr);
if orderedchancmbs
if original
% if the first element of the row pair is a neighbour of the
% first element of the column pair
chancmbneighbselmat = logical(kron(channeighbstructmat,ones(nchan)));
% and the second element of the row pair is a neighbour of the
% second element of the column pair
chancmbneighbselmat = chancmbneighbselmat & logical(kron(ones(nchan),channeighbstructmat));
else % version that consumes less memory
for chanindx=1:nchan
% if the first element of the row pair is a neighbour of the
% first element of the column pair
% and the second element of the row pair is a neighbour of the
% second element of the column pair
chancmbneighbselmat(:,((chanindx-1)*nchan + 1):(chanindx*nchan)) = ...
logical(kron(channeighbstructmat(:,chanindx),ones(nchan))) & logical(kron(ones(nchan,1),channeighbstructmat));
end;
end;
else % unordered channel combinations
if original
% if the first element of the row pair is a neighbour of one of the
% two elements of the column pair
chancmbneighbselmat = logical(kron(channeighbstructmat,ones(nchan))) | logical(repmat(kron(channeighbstructmat,ones(nchan,1)), [1 nchan]));
% and the second element of the row pair is a neighbour of one of the
% two elements of the column pair
chancmbneighbselmat = chancmbneighbselmat & (logical(kron(ones(nchan),channeighbstructmat)) | ...
logical(repmat(kron(channeighbstructmat,ones(1,nchan)), [nchan 1])));
else % version that consumes less memory
for chanindx=1:nchan
% if the first element of the row pair is a neighbour of one of the
% two elements of the column pair
% and the second element of the row pair is a neighbour of one of the
% two elements of the column pair
chancmbneighbselmat(:,((chanindx-1)*nchan + 1):(chanindx*nchan)) = ...
(logical(kron(channeighbstructmat(:,chanindx),ones(nchan))) | logical(kron(channeighbstructmat,ones(nchan,1)))) ...
& (logical(kron(ones(nchan,1),channeighbstructmat)) | ...
logical(repmat(kron(channeighbstructmat(:,chanindx),ones(1,nchan)), [nchan 1])));
end;
end;
end;
if original
% remove all pairs of channel combinations that have one channel in common.
% common channel in the first elements of the two pairs.
chancmbneighbselmat = chancmbneighbselmat & kron(~eye(nchan),ones(nchan));
% common channel in the second elements of the two pairs.
chancmbneighbselmat = chancmbneighbselmat & kron(ones(nchan),~eye(nchan));
% common channel in the first element of the row pair and the second
% element of the column pair.
tempselmat=logical(zeros(nchansqr));
tempselmat(:)= ~repmat([repmat([ones(nchan,1); zeros(nchansqr,1)],[(nchan-1) 1]); ones(nchan,1)],[nchan 1]);
chancmbneighbselmat = chancmbneighbselmat & tempselmat;
% common channel in the second element of the row pair and the first
% element of the column pair.
chancmbneighbselmat = chancmbneighbselmat & tempselmat';
else
noteye=~eye(nchan);
tempselmat=logical(zeros(nchansqr,nchan));
tempselmat(:)= ~[repmat([ones(nchan,1); zeros(nchansqr,1)],[(nchan-1) 1]); ones(nchan,1)];
for chanindx=1:nchan
% remove all pairs of channel combinations that have one channel in common.
% common channel in the first elements of the two pairs.
% common channel in the second elements of the two pairs.
% common channel in the first element of the row pair and the second
% element of the column pair.
chancmbneighbselmat(:,((chanindx-1)*nchan + 1):(chanindx*nchan)) = ...
chancmbneighbselmat(:,((chanindx-1)*nchan + 1):(chanindx*nchan)) ...
& logical(kron(noteye(:,chanindx),ones(nchan))) ...
& logical(kron(ones(nchan,1),noteye)) ...
& tempselmat;
end;
for chanindx=1:nchan
% remove all pairs of channel combinations that have one
% common channel in the second element of the row pair and the first
% element of the column pair.
chancmbneighbselmat(((chanindx-1)*nchan + 1):(chanindx*nchan),:) = ...
chancmbneighbselmat(((chanindx-1)*nchan + 1):(chanindx*nchan),:) & tempselmat';
end;
end;
% reorder and select the entries in chancmbneighbselmat such that they correspond to labelcmb.
chancmbneighbselmat = sparse(chancmbneighbselmat);
chancmbneighbselmat = chancmbneighbselmat(chancmbindcs,chancmbindcs);
% put all elements below and on the diagonal equal to zero
nchancmbindcs = length(chancmbindcs);
for chancmbindx=1:nchancmbindcs
selvec=[true(chancmbindx-1,1);false(nchancmbindcs-chancmbindx+1,1)];
chancmbneighbstructmat(:,chancmbindx) = chancmbneighbstructmat(:,chancmbindx) & selvec;
chancmbneighbselmat(:,chancmbindx) = chancmbneighbselmat(:,chancmbindx) & selvec;
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION convert Nx2 cell array with channel combinations into Nx1 cell array with labels
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function label = cmb2label(labelcmb);
label = {};
for i=1:size(labelcmb)
label{i,1} = [labelcmb{i,1} '&' labelcmb{i,2}];
end
|
github
|
philippboehmsturm/antx-master
|
ft_chantype.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/ft_chantype.m
| 22,382 |
utf_8
|
c6505953f3663b6a747e7cc7089a5629
|
function type = ft_chantype(input, desired)
% FT_CHANTYPE determines for each individual channel what type of data it
% represents, e.g. a planar gradiometer, axial gradiometer, magnetometer,
% trigger channel, etc. If you want to know what the acquisition system is
% (e.g. ctf151 or neuromag306), you should not use this function but
% FT_SENSTYPE instead.
%
% Use as
% type = ft_chantype(hdr)
% type = ft_chantype(sens)
% type = ft_chantype(label)
% or as
% type = ft_chantype(hdr, desired)
% type = ft_chantype(sens, desired)
% type = ft_chantype(label, desired)
%
% If the desired unit is not specified as second input argument, this
% function returns a Nchan*1 cell-array with a string describing the type
% of each channel.
%
% If the desired unit is specified as second input argument, this function
% returns a Nchan*1 boolean vector with "true" for the channels of the
% desired type and "false" for the ones that do not match.
%
% The specification of the channel types depends on the acquisition system,
% for example the ctf275 system includes the following type of channels:
% meggrad, refmag, refgrad, adc, trigger, eeg, headloc, headloc_gof.
%
% See also FT_READ_HEADER, FT_SENSTYPE, FT_CHANUNIT
% Copyright (C) 2008-2011, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_chantype.m 7215 2012-12-17 19:33:22Z roboos $
% this is to avoid a recursion loop
persistent recursion
if isempty(recursion)
recursion = false;
end
% determine the type of input, this is handled similarly as in FT_CHANUNIT
isheader = isa(input, 'struct') && isfield(input, 'label') && isfield(input, 'Fs');
isgrad = isa(input, 'struct') && isfield(input, 'pnt') && isfield(input, 'ori');
isgrad = (isa(input, 'struct') && isfield(input, 'coilpos')) || isgrad;
isgrad = (isa(input, 'struct') && isfield(input, 'chanpos')) || isgrad;
islabel = isa(input, 'cell') && isa(input{1}, 'char');
hdr = input;
grad = input;
label = input;
if isheader
label = hdr.label;
numchan = length(hdr.label);
if isfield(hdr, 'grad')
grad = hdr.grad;
[i1, i2] = match_str(label, grad.label); % ensure that the grad.label order matches the hdr.label order
grad.label = grad.label(i2); % reorder the channel labels
if isfield(hdr.grad, 'tra')
grad.tra = grad.tra(i2,:); % reorder the rows from the tra matrix
end
end
elseif isgrad
label = grad.label;
numchan = length(label);
elseif islabel
numchan = length(label);
else
error('the input that was provided to this function cannot be deciphered');
end
% start with unknown type for all channels
type = repmat({'unknown'}, numchan, 1);
if ft_senstype(input, 'unknown')
% don't bother doing all subsequent checks to determine the type of sensor array
elseif ft_senstype(input, 'neuromag') && isheader
% channames-KI is the channel kind, 1=meg, 202=eog, 2=eeg, 3=trigger (I am not sure, but have inferred this from a single test file)
% chaninfo-TY is the Coil type (0=magnetometer, 1=planar gradiometer)
if isfield(hdr, 'orig') && isfield(hdr.orig, 'channames')
for sel=find(hdr.orig.channames.KI(:)==202)'
type{sel} = 'eog';
end
for sel=find(hdr.orig.channames.KI(:)==2)'
type{sel} = 'eeg';
end
for sel=find(hdr.orig.channames.KI(:)==3)'
type{sel} = 'digital trigger';
end
% determine the MEG channel subtype
selmeg=find(hdr.orig.channames.KI(:)==1)';
for i=1:length(selmeg)
if hdr.orig.chaninfo.TY(i)==0
type{selmeg(i)} = 'megmag';
elseif hdr.orig.chaninfo.TY(i)==1
type{selmeg(i)} = 'megplanar';
end
end
elseif isfield(hdr, 'orig') && isfield(hdr.orig, 'chs') && isfield(hdr.orig.chs, 'coil_type')
% all the chs.kinds and chs.coil_types are obtained from the MNE manual, p.210-211
for sel=find([hdr.orig.chs.kind]==1 & [hdr.orig.chs.coil_type]==2)' %planar gradiometers
type(sel) = {'megplanar'}; %Neuromag-122 planar gradiometer
end
for sel=find([hdr.orig.chs.kind]==1 & [hdr.orig.chs.coil_type]==3012)' %planar gradiometers
type(sel) = {'megplanar'}; %Type T1 planar grad
end
for sel=find([hdr.orig.chs.kind]==1 & [hdr.orig.chs.coil_type]==3013)' %planar gradiometers
type(sel) = {'megplanar'}; %Type T2 planar grad
end
for sel=find([hdr.orig.chs.kind]==1 & [hdr.orig.chs.coil_type]==3014)' %planar gradiometers
type(sel) = {'megplanar'}; %Type T3 planar grad
end
for sel=find([hdr.orig.chs.kind]==1 & [hdr.orig.chs.coil_type]==3022)' %magnetometers
type(sel) = {'megmag'}; %Type T1 magenetometer
end
for sel=find([hdr.orig.chs.kind]==1 & [hdr.orig.chs.coil_type]==3023)' %magnetometers
type(sel) = {'megmag'}; %Type T2 magenetometer
end
for sel=find([hdr.orig.chs.kind]==1 & [hdr.orig.chs.coil_type]==3024)' %magnetometers
type(sel) = {'megmag'}; %Type T3 magenetometer
end
for sel=find([hdr.orig.chs.kind]==301)' %MEG reference channel, located far from head
type(sel) = {'ref'};
end
for sel=find([hdr.orig.chs.kind]==2)' %EEG channels
type(sel) = {'eeg'};
end
for sel=find([hdr.orig.chs.kind]==201)' %MCG channels
type(sel) = {'mcg'};
end
for sel=find([hdr.orig.chs.kind]==3)' %Stim channels
if any([hdr.orig.chs(sel).logno] == 101) %new systems: 101 (and 102, if enabled) are digital;
%low numbers are 'pseudo-analog' (if enabled)
type(sel([hdr.orig.chs(sel).logno] == 101)) = {'digital trigger'};
type(sel([hdr.orig.chs(sel).logno] == 102)) = {'digital trigger'};
type(sel([hdr.orig.chs(sel).logno] <= 32)) = {'analog trigger'};
others = [hdr.orig.chs(sel).logno] > 32 & [hdr.orig.chs(sel).logno] ~= 101 & ...
[hdr.orig.chs(sel).logno] ~= 102;
type(sel(others)) = {'other trigger'};
elseif any([hdr.orig.chs(sel).logno] == 14) %older systems: STI 014/015/016 are digital;
%lower numbers 'pseudo-analog'(if enabled)
type(sel([hdr.orig.chs(sel).logno] == 14)) = {'digital trigger'};
type(sel([hdr.orig.chs(sel).logno] == 15)) = {'digital trigger'};
type(sel([hdr.orig.chs(sel).logno] == 16)) = {'digital trigger'};
type(sel([hdr.orig.chs(sel).logno] <= 13)) = {'analog trigger'};
others = [hdr.orig.chs(sel).logno] > 16;
type(sel(others)) = {'other trigger'};
else
warning('There does not seem to be a suitable trigger channel.');
type(sel) = {'other trigger'};
end
end
for sel=find([hdr.orig.chs.kind]==202)' %EOG
type(sel) = {'eog'};
end
for sel=find([hdr.orig.chs.kind]==302)' %EMG
type(sel) = {'emg'};
end
for sel=find([hdr.orig.chs.kind]==402)' %ECG
type(sel) = {'ecg'};
end
for sel=find([hdr.orig.chs.kind]==502)' %MISC
type(sel) = {'misc'};
end
for sel=find([hdr.orig.chs.kind]==602)' %Resp
type(sel) = {'respiration'};
end
end
elseif ft_senstype(input, 'neuromag122')
% the name can be something like "MEG 001" or "MEG001" or "MEG 0113" or "MEG0113"
% i.e. with two or three digits and with or without a space
sel = myregexp('^MEG', label);
type(sel) = {'megplanar'};
elseif ft_senstype(input, 'neuromag306') && isgrad
% there should be 204 planar gradiometers and 102 axial magnetometers
if isfield(grad, 'tra')
tmp = sum(abs(grad.tra),2);
sel = (tmp==median(tmp));
type(sel) = {'megplanar'};
sel = (tmp~=median(tmp));
type(sel) = {'megmag'};
end
elseif ft_senstype(input, 'ctf') && isheader
% According to one source of information meg channels are 5, refmag 0,
% refgrad 1, adcs 18, trigger 11, eeg 9.
%
% According to another source of information it is as follows
% refMagnetometers: 0
% refGradiometers: 1
% meg_sens: 5
% eeg_sens: 9
% adc: 10
% stim_ref: 11
% video_time: 12
% sam: 15
% virtual_channels: 16
% sclk_ref: 17
% start with an empty one
origSensType = [];
if isfield(hdr, 'orig')
if isfield(hdr.orig, 'sensType') && isfield(hdr.orig, 'Chan')
% the header was read using the open-source matlab code that originates from CTF and that was modified by the FCDC
origSensType = hdr.orig.sensType;
elseif isfield(hdr.orig, 'res4') && isfield(hdr.orig.res4, 'senres')
% the header was read using the CTF p-files, i.e. readCTFds
origSensType = [hdr.orig.res4.senres.sensorTypeIndex];
elseif isfield(hdr.orig, 'sensor') && isfield(hdr.orig.sensor, 'info')
% the header was read using the CTF importer from the NIH and Daren Weber
origSensType = [hdr.orig.sensor.info.index];
end
end
if isempty(origSensType)
warning('could not determine channel type from the CTF header');
end
for sel=find(origSensType(:)==5)'
type{sel} = 'meggrad';
end
for sel=find(origSensType(:)==0)'
type{sel} = 'refmag';
end
for sel=find(origSensType(:)==1)'
type{sel} = 'refgrad';
end
for sel=find(origSensType(:)==18)'
type{sel} = 'adc';
end
for sel=find(origSensType(:)==11)'
type{sel} = 'trigger';
end
for sel=find(origSensType(:)==9)'
type{sel} = 'eeg';
end
for sel=find(origSensType(:)==29)'
type{sel} = 'reserved'; % these are "reserved for future use", but relate to head localization
end
for sel=find(origSensType(:)==13)'
type{sel} = 'headloc'; % these represent the x, y, z position of the head coils
end
for sel=find(origSensType(:)==28)'
type{sel} = 'headloc_gof'; % these represent the goodness of fit for the head coils
end
% for sel=find(origSensType(:)==23)'
% type{sel} = 'SPLxxxx'; % I have no idea what these are
% end
elseif ft_senstype(input, 'ctf') && isgrad
% in principle it is possible to look at the number of coils, but here the channels are identified based on their name
sel = myregexp('^M[ZLR][A-Z][0-9][0-9]$', grad.label);
type(sel) = {'meggrad'}; % normal gradiometer channels
sel = myregexp('^S[LR][0-9][0-9]$', grad.label);
type(sel) = {'meggrad'}; % normal gradiometer channels in the 64 channel CTF system
sel = myregexp('^B[GPQR][0-9]$', grad.label);
type(sel) = {'refmag'}; % reference magnetometers
sel = myregexp('^[GPQR][0-9][0-9]$', grad.label);
type(sel) = {'refgrad'}; % reference gradiometers
elseif ft_senstype(input, 'ctf') && islabel
% the channels have to be identified based on their name alone
sel = myregexp('^M[ZLR][A-Z][0-9][0-9]$', label);
type(sel) = {'meggrad'}; % normal gradiometer channels
sel = myregexp('^S[LR][0-9][0-9]$', label);
type(sel) = {'meggrad'}; % normal gradiometer channels in the 64 channel CTF system
sel = myregexp('^B[GPR][0-9]$', label);
type(sel) = {'refmag'}; % reference magnetometers
sel = myregexp('^[GPQR][0-9][0-9]$', label);
type(sel) = {'refgrad'}; % reference gradiometers
elseif ft_senstype(input, 'bti')
% all 4D-BTi MEG channels start with "A"
% all 4D-BTi reference channels start with M or G
% all 4D-BTi EEG channels start with E
type(strncmp('A', label, 1)) = {'meg'};
type(strncmp('M', label, 1)) = {'refmag'};
type(strncmp('G', label, 1)) = {'refgrad'};
if isgrad && isfield(grad, 'tra')
gradtype = repmat({'unknown'}, size(grad.label));
gradtype(strncmp('A', grad.label, 1)) = {'meg'};
gradtype(strncmp('M', grad.label, 1)) = {'refmag'};
gradtype(strncmp('G', grad.label, 1)) = {'refgrad'};
% look at the number of coils of the meg channels
selchan = find(strcmp('meg', gradtype));
for k = 1:length(selchan)
ncoils = length(find(grad.tra(selchan(k),:)==1));
if ncoils==1,
gradtype{selchan(k)} = 'megmag';
elseif ncoils==2,
gradtype{selchan(k)} = 'meggrad';
end
end
[selchan, selgrad] = match_str(label, grad.label);
type(selchan) = gradtype(selgrad);
end
% This is to allow setting additional channel types based on the names
if isheader && issubfield(hdr, 'orig.channel_data.chan_label')
tmplabel = {hdr.orig.channel_data.chan_label};
tmplabel = tmplabel(:);
else
tmplabel = label; % might work
end
sel = strmatch('unknown', type, 'exact');
if ~isempty(sel)
type(sel)= ft_chantype(tmplabel(sel));
sel = strmatch('unknown', type, 'exact');
if ~isempty(sel)
type(sel(strncmp('E', label(sel), 1))) = {'eeg'};
end
end
elseif ft_senstype(input, 'itab') && isheader
origtype = [input.orig.ch.type];
type(origtype==0) = {'unknown'};
type(origtype==1) = {'ele'};
type(origtype==2) = {'mag'}; % might be magnetometer or gradiometer, look at the number of coils
type(origtype==4) = {'ele ref'};
type(origtype==8) = {'mag ref'};
type(origtype==16) = {'aux'};
type(origtype==32) = {'param'};
type(origtype==64) = {'digit'};
type(origtype==128) = {'flag'};
% these are the channels that are visible to fieldtrip
chansel = 1:input.orig.nchan;
type = type(chansel);
elseif ft_senstype(input, 'yokogawa') && isheader
% This is to recognize Yokogawa channel types from the original header
% This is from the original documentation
NullChannel = 0;
MagnetoMeter = 1;
AxialGradioMeter = 2;
PlannerGradioMeter = 3;
RefferenceChannelMark = hex2dec('0100');
RefferenceMagnetoMeter = bitor( RefferenceChannelMark, MagnetoMeter );
RefferenceAxialGradioMeter = bitor( RefferenceChannelMark, AxialGradioMeter );
RefferencePlannerGradioMeter = bitor( RefferenceChannelMark, PlannerGradioMeter);
TriggerChannel = -1;
EegChannel = -2;
EcgChannel = -3;
EtcChannel = -4;
if ft_hastoolbox('yokogawa_meg_reader')
% shorten names
ch_info = hdr.orig.channel_info.channel;
type_orig = [ch_info.type];
sel = (type_orig == NullChannel);
type(sel) = {'null'};
sel = (type_orig == MagnetoMeter);
type(sel) = {'megmag'};
sel = (type_orig == AxialGradioMeter);
type(sel) = {'meggrad'};
sel = (type_orig == PlannerGradioMeter);
type(sel) = {'megplanar'};
sel = (type_orig == RefferenceMagnetoMeter);
type(sel) = {'refmag'};
sel = (type_orig == RefferenceAxialGradioMeter);
type(sel) = {'refgrad'};
sel = (type_orig == RefferencePlannerGradioMeter);
type(sel) = {'refplanar'};
sel = (type_orig == TriggerChannel);
type(sel) = {'trigger'};
sel = (type_orig == EegChannel);
type(sel) = {'eeg'};
sel = (type_orig == EcgChannel);
type(sel) = {'ecg'};
sel = (type_orig == EtcChannel);
type(sel) = {'etc'};
elseif ft_hastoolbox('yokogawa')
sel = (hdr.orig.channel_info(:, 2) == NullChannel);
type(sel) = {'null'};
sel = (hdr.orig.channel_info(:, 2) == MagnetoMeter);
type(sel) = {'megmag'};
sel = (hdr.orig.channel_info(:, 2) == AxialGradioMeter);
type(sel) = {'meggrad'};
sel = (hdr.orig.channel_info(:, 2) == PlannerGradioMeter);
type(sel) = {'megplanar'};
sel = (hdr.orig.channel_info(:, 2) == RefferenceMagnetoMeter);
type(sel) = {'refmag'};
sel = (hdr.orig.channel_info(:, 2) == RefferenceAxialGradioMeter);
type(sel) = {'refgrad'};
sel = (hdr.orig.channel_info(:, 2) == RefferencePlannerGradioMeter);
type(sel) = {'refplanar'};
sel = (hdr.orig.channel_info(:, 2) == TriggerChannel);
type(sel) = {'trigger'};
sel = (hdr.orig.channel_info(:, 2) == EegChannel);
type(sel) = {'eeg'};
sel = (hdr.orig.channel_info(:, 2) == EcgChannel);
type(sel) = {'ecg'};
sel = (hdr.orig.channel_info(:, 2) == EtcChannel);
type(sel) = {'etc'};
end
elseif ft_senstype(input, 'yokogawa') && isgrad
% all channels in the gradiometer definition are meg
% type(1:end) = {'meg'};
% channels are identified based on their name: only magnetic as isgrad==1
sel = myregexp('^M[0-9][0-9][0-9]$', grad.label);
type(sel) = {'megmag'};
sel = myregexp('^AG[0-9][0-9][0-9]$', grad.label);
type(sel) = {'meggrad'};
sel = myregexp('^PG[0-9][0-9][0-9]$', grad.label);
type(sel) = {'megplanar'};
sel = myregexp('^RM[0-9][0-9][0-9]$', grad.label);
type(sel) = {'refmag'};
sel = myregexp('^RAG[0-9][0-9][0-9]$', grad.label);
type(sel) = {'refgrad'};
sel = myregexp('^RPG[0-9][0-9][0-9]$', grad.label);
type(sel) = {'refplanar'};
elseif ft_senstype(input, 'yokogawa') && islabel
% the yokogawa channel labels are a mess, so autodetection is not possible
% type(1:end) = {'meg'};
sel = myregexp('[0-9][0-9][0-9]$', label);
type(sel) = {'null'};
sel = myregexp('^M[0-9][0-9][0-9]$', label);
type(sel) = {'megmag'};
sel = myregexp('^AG[0-9][0-9][0-9]$', label);
type(sel) = {'meggrad'};
sel = myregexp('^PG[0-9][0-9][0-9]$', label);
type(sel) = {'megplanar'};
sel = myregexp('^RM[0-9][0-9][0-9]$', label);
type(sel) = {'refmag'};
sel = myregexp('^RAG[0-9][0-9][0-9]$', label);
type(sel) = {'refgrad'};
sel = myregexp('^RPG[0-9][0-9][0-9]$', label);
type(sel) = {'refplanar'};
sel = myregexp('^TRIG[0-9][0-9][0-9]$', label);
type(sel) = {'trigger'};
sel = myregexp('^EEG[0-9][0-9][0-9]$', label);
type(sel) = {'eeg'};
sel = myregexp('^ECG[0-9][0-9][0-9]$', label);
type(sel) = {'ecg'};
sel = myregexp('^ETC[0-9][0-9][0-9]$', label);
type(sel) = {'etc'};
elseif ft_senstype(input, 'itab') && isheader
sel = ([hdr.orig.ch.type]==0);
type(sel) = {'unknown'};
sel = ([hdr.orig.ch.type]==1);
type(sel) = {'unknown'};
sel = ([hdr.orig.ch.type]==2);
type(sel) = {'megmag'};
sel = ([hdr.orig.ch.type]==8);
type(sel) = {'megref'};
sel = ([hdr.orig.ch.type]==16);
type(sel) = {'aux'};
sel = ([hdr.orig.ch.type]==64);
type(sel) = {'digital'};
% not all channels are actually processed by fieldtrip, so only return
% the types fopr the ones that read_header and read_data return
type = type(hdr.orig.chansel);
elseif ft_senstype(input, 'itab') && isgrad
% the channels have to be identified based on their name alone
sel = myregexp('^MAG_[0-9][0-9][0-9]$', label);
type(sel) = {'megmag'};
sel = myregexp('^MAG_[0-9][0-9]$', label); % for the itab28 system
type(sel) = {'megmag'};
sel = myregexp('^MAG_[0-9]$', label); % for the itab28 system
type(sel) = {'megmag'};
sel = myregexp('^REF_[0-9][0-9][0-9]$', label);
type(sel) = {'megref'};
sel = myregexp('^AUX.*$', label);
type(sel) = {'aux'};
elseif ft_senstype(input, 'itab') && islabel
% the channels have to be identified based on their name alone
sel = myregexp('^MAG_[0-9][0-9][0-9]$', label);
type(sel) = {'megmag'};
sel = myregexp('^REF_[0-9][0-9][0-9]$', label);
type(sel) = {'megref'};
sel = myregexp('^AUX.*$', label);
type(sel) = {'aux'};
elseif ft_senstype(input, 'eeg') && islabel
% use an external helper function to define the list with EEG channel names
type(match_str(label, ft_senslabel(ft_senstype(label)))) = {'eeg'};
elseif ft_senstype(input, 'eeg') && isheader
% use an external helper function to define the list with EEG channel names
type(match_str(hdr.label, ft_senslabel(ft_senstype(hdr)))) = {'eeg'};
elseif ft_senstype(input, 'plexon') && isheader
% this is a complete header that was read from a Plexon *.nex file using read_plexon_nex
for i=1:numchan
switch hdr.orig.VarHeader(i).Type
case 0
type{i} = 'spike';
case 1
type{i} = 'event';
case 2
type{i} = 'interval'; % Interval variables?
case 3
type{i} = 'waveform';
case 4
type{i} = 'population'; % Population variables ?
case 5
type{i} = 'analog';
otherwise
% keep the default 'unknown' type
end
end
end % ft_senstype
% if possible, set additional types based on channel labels
label2type = {
{'ecg', 'ekg'};
{'emg'};
{'eog', 'heog', 'veog'};
{'lfp'};
{'eeg'};
};
for i = 1:numel(label2type)
for j = 1:numel(label2type{i})
type(intersect(strmatch(label2type{i}{j}, lower(label)), strmatch('unknown', type, 'exact'))) = label2type{i}(1);
end
end
if all(strcmp(type, 'unknown')) && ~recursion
% try whether only lowercase channel labels makes a difference
if islabel
recursion = true;
type = ft_chantype(lower(input));
recursion = false;
elseif isfield(input, 'label')
input.label = lower(input.label);
recursion = true;
type = ft_chantype(input);
recursion = false;
end
end
if all(strcmp(type, 'unknown')) && ~recursion
% try whether only uppercase channel labels makes a difference
if islabel
recursion = true;
type = ft_chantype(upper(input));
recursion = false;
elseif isfield(input, 'label')
input.label = upper(input.label);
recursion = true;
type = ft_chantype(input);
recursion = false;
end
end
if nargin>1
% return a boolean vector
if isequal(desired, 'meg') || isequal(desired, 'ref')
% only compare the first three characters, i.e. meggrad or megmag should match
type = strncmp(desired, type, 3);
else
type = strcmp(desired, type);
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% helper function
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function match = myregexp(pat, list)
match = false(size(list));
for i=1:numel(list)
match(i) = ~isempty(regexp(list{i}, pat, 'once'));
end
|
github
|
philippboehmsturm/antx-master
|
ft_read_event.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/ft_read_event.m
| 66,708 |
utf_8
|
4935be6afe902a8f429fc10ecc1b06ac
|
function [event] = ft_read_event(filename, varargin)
% FT_READ_EVENT reads all events from an EEG/MEG dataset and returns
% them in a well defined structure. It is a wrapper around different
% EEG/MEG file importers, directly supported formats are CTF, Neuromag,
% EEP, BrainVision, Neuroscan and Neuralynx.
%
% Use as
% [event] = ft_read_event(filename, ...)
%
% Additional options should be specified in key-value pairs and can be
% 'dataformat' string
% 'headerformat' string
% 'eventformat' string
% 'header' structure, see FT_READ_HEADER
% 'detectflank' string, can be 'up', 'down', 'both' or 'auto' (default is system specific)
% 'trigshift' integer, number of samples to shift from flank to detect trigger value (default = 0)
% 'trigindx' list with channel numbers for the trigger detection, only for Yokogawa (default is automatic)
% 'threshold' threshold for analog trigger channels (default is system specific)
% 'blocking' wait for the selected number of events (default = 'no')
% 'timeout' amount of time in seconds to wait when blocking (default = 5)
%
% Furthermore, you can specify optional arguments as key-value pairs
% for filtering the events, e.g. to select only events of a specific
% type, of a specific value, or events between a specific begin and
% end sample. This event filtering is especially usefull for real-time
% processing. See FT_FILTER_EVENT for more details.
%
% Some data formats have trigger channels that are sampled continuously with
% the same rate as the electrophysiological data. The default is to detect
% only the up-going TTL flanks. The trigger events will correspond with the
% first sample where the TTL value is up. This behaviour can be changed
% using the 'detectflank' option, which also allows for detecting the
% down-going flank or both. In case of detecting the down-going flank, the
% sample number of the event will correspond with the first sample at which
% the TTF went down, and the value will correspond to the TTL value just
% prior to going down.
%
% This function returns an event structure with the following fields
% event.type = string
% event.sample = expressed in samples, the first sample of a recording is 1
% event.value = number or string
% event.offset = expressed in samples
% event.duration = expressed in samples
% event.timestamp = expressed in timestamp units, which vary over systems (optional)
%
% The event type and sample fields are always defined, other fields can be empty,
% depending on the type of event file. Events are sorted by the sample on
% which they occur. After reading the event structure, you can use the
% following tricks to extract information about those events in which you
% are interested.
%
% Determine the different event types
% unique({event.type})
%
% Get the index of all trial events
% find(strcmp('trial', {event.type}))
%
% Make a vector with all triggers that occurred on the backpanel
% [event(find(strcmp('backpanel trigger', {event.type}))).value]
%
% Find the events that occurred in trial 26
% t=26; samples_trials = [event(find(strcmp('trial', {event.type}))).sample];
% find([event.sample]>samples_trials(t) & [event.sample]<samples_trials(t+1))
%
% The list of supported file formats can be found in FT_READ_HEADER.
%
% See also FT_READ_HEADER, FT_READ_DATA, FT_WRITE_EVENT, FT_FILTER_EVENT
% Copyright (C) 2004-2012 Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_read_event.m 7350 2013-01-18 05:03:58Z josdie $
global event_queue % for fcdc_global
persistent sock % for fcdc_tcp
persistent db_blob % for fcdc_mysql
if isempty(db_blob)
db_blob = 0;
end
if iscell(filename)
% use recursion to read from multiple event sources
event = [];
for i=1:numel(filename)
tmp = ft_read_event(filename{i}, varargin{:});
event = appendevent(event(:), tmp(:));
end
return
end
% optionally get the data from the URL and make a temporary local copy
filename = fetch_url(filename);
% get the options
eventformat = ft_getopt(varargin, 'eventformat');
if isempty(eventformat)
% only do the autodetection if the format was not specified
eventformat = ft_filetype(filename);
end
hdr = ft_getopt(varargin, 'header');
detectflank = ft_getopt(varargin, 'detectflank', 'up'); % up, down or both
trigshift = ft_getopt(varargin, 'trigshift'); % default is assigned in subfunction
trigindx = ft_getopt(varargin, 'trigindx'); % this allows to override the automatic trigger channel detection and is useful for Yokogawa
headerformat = ft_getopt(varargin, 'headerformat');
dataformat = ft_getopt(varargin, 'dataformat');
threshold = ft_getopt(varargin, 'threshold'); % this is used for analog channels
% this allows to read only events in a certain range, supported for selected data formats only
flt_type = ft_getopt(varargin, 'type');
flt_value = ft_getopt(varargin, 'value');
flt_minsample = ft_getopt(varargin, 'minsample');
flt_maxsample = ft_getopt(varargin, 'maxsample');
flt_mintimestamp = ft_getopt(varargin, 'mintimestamp');
flt_maxtimestamp = ft_getopt(varargin, 'maxtimestamp');
flt_minnumber = ft_getopt(varargin, 'minnumber');
flt_maxnumber = ft_getopt(varargin, 'maxnumber');
% thie allows blocking reads to avoid having to poll many times for online processing
blocking = ft_getopt(varargin, 'blocking', false); % true or false
timeout = ft_getopt(varargin, 'timeout', 5); % seconds
% convert from 'yes'/'no' into boolean
blocking = istrue(blocking);
if any(strcmp(eventformat, {'brainvision_eeg', 'brainvision_dat'}))
[p, f] = fileparts(filename);
filename = fullfile(p, [f '.vhdr']);
eventformat = 'brainvision_vhdr';
end
if strcmp(eventformat, 'brainvision_vhdr')
% read the headerfile belonging to the dataset and try to determine the corresponding markerfile
eventformat = 'brainvision_vmrk';
hdr = read_brainvision_vhdr(filename);
% replace the filename with the filename of the markerfile
if ~isfield(hdr, 'MarkerFile') || isempty(hdr.MarkerFile)
filename = [];
else
[p, f] = fileparts(filename);
filename = fullfile(p, hdr.MarkerFile);
end
end
% start with an empty event structure
event = [];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% read the events with the low-level reading function
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
switch eventformat
case 'fcdc_global'
event = event_queue;
case {'4d' '4d_pdf', '4d_m4d', '4d_xyz'}
if isempty(hdr)
hdr = ft_read_header(filename, 'headerformat', eventformat);
end
% read the trigger channel and do flank detection
trgindx = match_str(hdr.label, 'TRIGGER');
if isfield(hdr, 'orig') && isfield(hdr.orig, 'config_data') && strcmp(hdr.orig.config_data.site_name, 'Glasgow'),
trigger = read_trigger(filename, 'header', hdr, 'begsample', flt_minsample, 'endsample', flt_maxsample, 'chanindx', trgindx, 'detectflank', detectflank, 'trigshift', trigshift,'fix4dglasgow',1, 'dataformat', '4d');
else
trigger = read_trigger(filename, 'header', hdr, 'begsample', flt_minsample, 'endsample', flt_maxsample, 'chanindx', trgindx, 'detectflank', detectflank, 'trigshift', trigshift,'fix4dglasgow',0, 'dataformat', '4d');
end
event = appendevent(event, trigger);
respindx = match_str(hdr.label, 'RESPONSE');
if ~isempty(respindx)
response = read_trigger(filename, 'header', hdr, 'begsample', flt_minsample, 'endsample', flt_maxsample, 'chanindx', respindx, 'detectflank', detectflank, 'trigshift', trigshift, 'dataformat', '4d');
event = appendevent(event, response);
end
case 'bci2000_dat'
% this requires the load_bcidat mex file to be present on the path
ft_hastoolbox('BCI2000', 1);
if isempty(hdr)
hdr = ft_read_header(filename);
end
if isfield(hdr.orig, 'signal') && isfield(hdr.orig, 'states')
% assume that the complete data is stored in the header, this speeds up subsequent read operations
signal = hdr.orig.signal;
states = hdr.orig.states;
parameters = hdr.orig.parameters;
total_samples = hdr.orig.total_samples;
else
[signal, states, parameters, total_samples] = load_bcidat(filename);
end
list = fieldnames(states);
% loop over all states and detect the flanks, the following code was taken from read_trigger
for i=1:length(list)
channel = list{i};
trig = double(getfield(states, channel));
pad = trig(1);
trigshift = 0;
begsample = 1;
switch detectflank
case 'up'
% convert the trigger into an event with a value at a specific sample
for j=find(diff([pad trig(:)'])>0)
event(end+1).type = channel;
event(end ).sample = j + begsample - 1; % assign the sample at which the trigger has gone down
event(end ).value = trig(j+trigshift); % assign the trigger value just _after_ going up
end
case 'down'
% convert the trigger into an event with a value at a specific sample
for j=find(diff([pad trig(:)'])<0)
event(end+1).type = channel;
event(end ).sample = j + begsample - 1; % assign the sample at which the trigger has gone down
event(end ).value = trig(j-1-trigshift); % assign the trigger value just _before_ going down
end
case 'both'
% convert the trigger into an event with a value at a specific sample
for j=find(diff([pad trig(:)'])>0)
event(end+1).type = [channel '_up']; % distinguish between up and down flank
event(end ).sample = j + begsample - 1; % assign the sample at which the trigger has gone down
event(end ).value = trig(j+trigshift); % assign the trigger value just _after_ going up
end
% convert the trigger into an event with a value at a specific sample
for j=find(diff([pad trig(:)'])<0)
event(end+1).type = [channel '_down']; % distinguish between up and down flank
event(end ).sample = j + begsample - 1; % assign the sample at which the trigger has gone down
event(end ).value = trig(j-1-trigshift); % assign the trigger value just _before_ going down
end
otherwise
error('incorrect specification of ''detectflank''');
end
end
case {'besa_avr', 'besa_swf'}
if isempty(hdr)
hdr = ft_read_header(filename);
end
event(end+1).type = 'average';
event(end ).sample = 1;
event(end ).duration = hdr.nSamples;
event(end ).offset = -hdr.nSamplesPre;
event(end ).value = [];
case {'biosemi_bdf', 'bham_bdf'}
% read the header, required to determine the stimulus channels and trial specification
if isempty(hdr)
hdr = ft_read_header(filename);
end
% specify the range to search for triggers, default is the complete file
if ~isempty(flt_minsample)
begsample = flt_minsample;
else
begsample = 1;
end
if ~isempty(flt_maxsample)
endsample = flt_maxsample;
else
endsample = hdr.nSamples*hdr.nTrials;
end
if ~strcmp(detectflank, 'up')
if strcmp(detectflank, 'both')
warning('only up-going flanks are supported for Biosemi');
detectflank = 'up';
else
error('only up-going flanks are supported for Biosemi');
% FIXME the next section on trigger detection should be merged with the
% READ_CTF_TRIGGER (which also does masking with bit-patterns) into the
% READ_TRIGGER function
end
end
% find the STATUS channel and read the values from it
schan = find(strcmpi(hdr.label,'STATUS'));
sdata = ft_read_data(filename, 'header', hdr, 'dataformat', dataformat, 'begsample', begsample, 'endsample', endsample, 'chanindx', schan);
try
% find indices of negative numbers
bit24i = find(sdata < 0);
% make number positive and preserve bits 0-22
sdata(bit24i) = bitcmp(abs(sdata(bit24i))-1,24);
% re-insert the sign bit on its original location, i.e. bit24
sdata(bit24i) = sdata(bit24i)+(2^(24-1));
% typecast the data to ensure that the status channel is represented in 32 bits
sdata = uint32(sdata);
catch
% convert to 32-bit integer representation and only preserve the lowest 24 bits
sdata = bitand(int32(sdata), 2^24-1);
end
byte1 = 2^8 - 1;
byte2 = 2^16 - 1 - byte1;
byte3 = 2^24 - 1 - byte1 - byte2;
% get the respective status and trigger bits
trigger = bitand(sdata, bitor(byte1, byte2)); % contained in the lower two bytes
epoch = int8(bitget(sdata, 16+1));
cmrange = int8(bitget(sdata, 20+1));
battery = int8(bitget(sdata, 22+1));
% determine when the respective status bits go up or down
flank_trigger = diff([0 trigger]);
flank_epoch = diff([0 epoch ]);
flank_cmrange = diff([0 cmrange]);
flank_battery = diff([0 battery]);
for i=find(flank_trigger>0)
event(end+1).type = 'STATUS';
event(end ).sample = i + begsample - 1;
event(end ).value = double(trigger(i));
end
for i=find(flank_epoch==1)
event(end+1).type = 'Epoch';
event(end ).sample = i;
end
for i=find(flank_cmrange==1)
event(end+1).type = 'CM_in_range';
event(end ).sample = i;
end
for i=find(flank_cmrange==-1)
event(end+1).type = 'CM_out_of_range';
event(end ).sample = i;
end
for i=find(flank_battery==1)
event(end+1).type = 'Battery_low';
event(end ).sample = i;
end
for i=find(flank_battery==-1)
event(end+1).type = 'Battery_ok';
event(end ).sample = i;
end
case {'biosig', 'gdf'}
% FIXME it would be nice to figure out how sopen/sread return events
% for all possible fileformats that can be processed with biosig
%
% This section of code is opaque with respect to the gdf file being a
% single file or the first out of a sequence with postfix _1, _2, ...
% because it uses private/read_trigger which again uses ft_read_data
if isempty(hdr)
hdr = ft_read_header(filename);
end
% the following applies to Biosemi data that is stored in the gdf format
statusindx = find(strcmp(hdr.label, 'STATUS'));
if length(statusindx)==1
% represent the rising flanks in the STATUS channel as events
event = read_trigger(filename, 'header', hdr, 'chanindx', statusindx, ...
'detectflank', 'up', 'fixbiosemi', true, 'begsample', flt_minsample, 'endsample', flt_maxsample);
else
warning('BIOSIG does not have a consistent event representation, skipping events')
event = [];
end
case 'brainvision_vmrk'
fid=fopen(filename,'rt');
if fid==-1,
error('cannot open BrainVision marker file')
end
line = [];
while ischar(line) || isempty(line)
line = fgetl(fid);
if ~isempty(line) && ~(isnumeric(line) && line==-1)
if strncmpi(line, 'Mk', 2)
% this line contains a marker
tok = tokenize(line, '=', 0); % do not squeeze repetitions of the seperator
if length(tok)~=2
warning('skipping unexpected formatted line in BrainVision marker file');
else
% the line looks like "MkXXX=YYY", which is ok
% the interesting part now is in the YYY, i.e. the second token
tok = tokenize(tok{2}, ',', 0); % do not squeeze repetitions of the seperator
if isempty(tok{1})
tok{1} = [];
end
if isempty(tok{2})
tok{2} = [];
end
event(end+1).type = tok{1};
event(end ).value = tok{2};
event(end ).sample = str2num(tok{3});
event(end ).duration = str2num(tok{4});
end
end
end
end
fclose(fid);
case 'ced_son'
% check that the required low-level toolbox is available
ft_hastoolbox('neuroshare', 1);
orig = read_ced_son(filename,'readevents','yes');
event = struct('type', {orig.events.type},...
'sample', {orig.events.sample},...
'value', {orig.events.value},...
'offset', {orig.events.offset},...
'duration', {orig.events.duration});
case 'ced_spike6mat'
if isempty(hdr)
hdr = ft_read_header(filename);
end
chanindx = [];
for i = 1:numel(hdr.orig)
if ~any(isfield(hdr.orig{i}, {'units', 'scale'}))
chanindx = [chanindx i];
end
end
if ~isempty(chanindx)
trigger = read_trigger(filename, 'header', hdr, 'dataformat', dataformat, 'begsample', flt_minsample, 'endsample', flt_maxsample, 'chanindx', chanindx, 'detectflank', detectflank);
event = appendevent(event, trigger);
end
case {'ctf_ds', 'ctf_meg4', 'ctf_res4', 'ctf_old'}
% obtain the dataset name
if ft_filetype(filename, 'ctf_meg4') || ft_filetype(filename, 'ctf_res4')
filename = fileparts(filename);
end
[path, name, ext] = fileparts(filename);
headerfile = fullfile(path, [name ext], [name '.res4']);
datafile = fullfile(path, [name ext], [name '.meg4']);
classfile = fullfile(path, [name ext], 'ClassFile.cls');
markerfile = fullfile(path, [name ext], 'MarkerFile.mrk');
% in case ctf_old was specified as eventformat, the other reading functions should also know about that
if strcmp(eventformat, 'ctf_old')
dataformat = 'ctf_old';
headerformat = 'ctf_old';
end
% read the header, required to determine the stimulus channels and trial specification
if isempty(hdr)
hdr = ft_read_header(headerfile, 'headerformat', headerformat);
end
try
% read the trigger codes from the STIM channel, usefull for (pseudo) continuous data
% this splits the trigger channel into the lowers and highest 16 bits,
% corresponding with the front and back panel of the electronics cabinet at the Donders Centre
[backpanel, frontpanel] = read_ctf_trigger(filename);
for i=find(backpanel(:)')
event(end+1).type = 'backpanel trigger';
event(end ).sample = i;
event(end ).value = backpanel(i);
end
for i=find(frontpanel(:)')
event(end+1).type = 'frontpanel trigger';
event(end ).sample = i;
event(end ).value = frontpanel(i);
end
end
% determine the trigger channels from the header
if isfield(hdr, 'orig') && isfield(hdr.orig, 'sensType')
origSensType = hdr.orig.sensType;
elseif isfield(hdr, 'orig') && isfield(hdr.orig, 'res4')
origSensType = [hdr.orig.res4.senres.sensorTypeIndex];
else
origSensType = [];
end
% meg channels are 5, refmag 0, refgrad 1, adcs 18, trigger 11, eeg 9
trigchanindx = find(origSensType==11);
if ~isempty(trigchanindx)
% read the trigger channel and do flank detection
trigger = read_trigger(filename, 'header', hdr, 'begsample', flt_minsample, 'endsample', flt_maxsample, 'chanindx', trigchanindx, 'dataformat', dataformat, 'detectflank', detectflank, 'trigshift', trigshift, 'fixctf', 1);
event = appendevent(event, trigger);
end
% read the classification file and make an event for each classified trial
[condNumbers,condLabels] = read_ctf_cls(classfile);
if ~isempty(condNumbers)
Ncond = length(condLabels);
for i=1:Ncond
for j=1:length(condNumbers{i})
event(end+1).type = 'classification';
event(end ).value = condLabels{i};
event(end ).sample = (condNumbers{i}(j)-1)*hdr.nSamples + 1;
event(end ).offset = -hdr.nSamplesPre;
event(end ).duration = hdr.nSamples;
end
end
end
if exist(markerfile,'file')
% read the marker file and make an event for each marker
% this depends on the readmarkerfile function that I got from Tom Holroyd
% I have not tested this myself extensively, since at the FCDC we
% don't use the marker files
mrk = readmarkerfile(filename);
for i=1:mrk.number_markers
for j=1:mrk.number_samples(i)
% determine the location of the marker, expressed in samples
trialnum = mrk.trial_times{i}(j,1);
synctime = mrk.trial_times{i}(j,2);
begsample = (trialnum-1)*hdr.nSamples + 1; % of the trial, relative to the start of the datafile
endsample = (trialnum )*hdr.nSamples; % of the trial, relative to the start of the datafile
offset = round(synctime*hdr.Fs); % this is the offset (in samples) relative to time t=0 for this trial
offset = offset + hdr.nSamplesPre; % and time t=0 corrsponds with the nSamplesPre'th sample
% store this marker as an event
event(end+1).type = mrk.marker_names{i};
event(end ).value = [];
event(end ).sample = begsample + offset;
event(end ).duration = 0;
event(end ).offset = offset;
end
end
end
case 'ctf_shm'
% contact Robert Oostenveld if you are interested in real-time acquisition on the CTF system
% read the events from shared memory
event = read_shm_event(filename, varargin{:});
case 'edf'
% EDF itself does not contain events, but EDF+ does define an annotation channel
if isempty(hdr)
hdr = ft_read_header(filename);
end
if issubfield(hdr, 'orig.annotation') && ~isempty(hdr.orig.annotation)
% read the data of the annotation channel as 16 bit
evt = read_edf(filename, hdr);
% undo the faulty calibration
evt = (evt - hdr.orig.Off(hdr.orig.annotation)) ./ hdr.orig.Cal(hdr.orig.annotation);
% convert the 16 bit format into the seperate bytes
evt = typecast(int16(evt), 'uint8');
% construct the Time-stamped Annotations Lists (TAL)
tal = tokenize(evt, char(0), true);
event = [];
for i=1:length(tal)
tok = tokenize(tal{i}, char(20));
time = str2double(char(tok{1}));
% there can be multiple annotations per time, the last cell is always empty
for j=2:length(tok)-1
anot = char(tok{j});
% represent the annotation as event
event(end+1).type = 'annotation';
event(end ).value = anot;
event(end ).sample = round(time*hdr.Fs) + 1;
event(end ).duration = 0;
event(end ).offset = 0;
end
end
else
event = [];
end
case 'eeglab_set'
if isempty(hdr)
hdr = ft_read_header(filename);
end
event = read_eeglabevent(filename, 'header', hdr);
case 'eeglab_erp'
if isempty(hdr)
hdr = ft_read_header(filename);
end
event = read_erplabevent(filename, 'header', hdr);
case 'spmeeg_mat'
if isempty(hdr)
hdr = ft_read_header(filename);
end
event = read_spmeeg_event(filename, 'header', hdr);
case 'eep_avr'
% check that the required low-level toolbox is available
ft_hastoolbox('eeprobe', 1);
% the headerfile and datafile are the same
if isempty(hdr)
hdr = ft_read_header(filename);
end
event(end+1).type = 'average';
event(end ).sample = 1;
event(end ).duration = hdr.nSamples;
event(end ).offset = -hdr.nSamplesPre;
event(end ).value = [];
case 'eep_cnt'
% check that the required low-level toolbox is available
ft_hastoolbox('eeprobe', 1);
% try to read external trigger file in EEP format
trgfile = [filename(1:(end-3)), 'trg'];
if exist(trgfile, 'file')
if isempty(hdr)
hdr = ft_read_header(filename);
end
tmp = read_eep_trg(trgfile);
% translate the EEProbe trigger codes to events
for i=1:length(tmp)
event(i).type = 'trigger';
event(i).sample = round((tmp(i).time/1000) * hdr.Fs) + 1; % convert from ms to samples
event(i).value = tmp(i).code;
event(i).offset = 0;
event(i).duration = 0;
end
else
warning('no triggerfile was found');
end
case 'egi_egis'
if isempty(hdr)
hdr = ft_read_header(filename);
end
fhdr = hdr.orig.fhdr;
chdr = hdr.orig.chdr;
ename = hdr.orig.ename;
cnames = hdr.orig.cnames;
fcom = hdr.orig.fcom;
ftext = hdr.orig.ftext;
eventCount=0;
for cel=1:fhdr(18)
for trial=1:chdr(cel,2)
eventCount=eventCount+1;
event(eventCount).type = 'trial';
event(eventCount).sample = (eventCount-1)*hdr.nSamples + 1;
event(eventCount).offset = -hdr.nSamplesPre;
event(eventCount).duration = hdr.nSamples;
event(eventCount).value = cnames{cel};
end
end
case 'egi_egia'
if isempty(hdr)
hdr = ft_read_header(filename);
end
fhdr = hdr.orig.fhdr;
chdr = hdr.orig.chdr;
ename = hdr.orig.ename;
cnames = hdr.orig.cnames;
fcom = hdr.orig.fcom;
ftext = hdr.orig.ftext;
eventCount=0;
for cel=1:fhdr(18)
for subject=1:chdr(cel,2)
eventCount=eventCount+1;
event(eventCount).type = 'trial';
event(eventCount).sample = (eventCount-1)*hdr.nSamples + 1;
event(eventCount).offset = -hdr.nSamplesPre;
event(eventCount).duration = hdr.nSamples;
event(eventCount).value = ['Sub' sprintf('%03d',subject) cnames{cel}];
end
end
case 'egi_sbin'
if ~exist('segHdr','var')
[EventCodes, segHdr, eventData] = read_sbin_events(filename);
end
if ~exist('header_array','var')
[header_array, CateNames, CatLengths, preBaseline] = read_sbin_header(filename);
end
if isempty(hdr)
hdr = ft_read_header(filename,'headerformat','egi_sbin');
end
version = header_array(1);
unsegmented = ~mod(version, 2);
eventCount=0;
if unsegmented
[evType,sampNum] = find(eventData);
for k = 1:length(evType)
event(k).sample = sampNum(k);
event(k).offset = [];
event(k).duration = 0;
event(k).type = 'trigger';
event(k).value = char(EventCodes(evType(k),:));
end
else
for theEvent=1:size(eventData,1)
for segment=1:hdr.nTrials
if any(eventData(theEvent,((segment-1)*hdr.nSamples +1):segment*hdr.nSamples))
eventCount=eventCount+1;
event(eventCount).sample = min(find(eventData(theEvent,((segment-1)*hdr.nSamples +1):segment*hdr.nSamples))) +(segment-1)*hdr.nSamples;
event(eventCount).offset = -hdr.nSamplesPre;
event(eventCount).duration = length(find(eventData(theEvent,((segment-1)*hdr.nSamples +1):segment*hdr.nSamples )>0))-1;
event(eventCount).type = 'trigger';
event(eventCount).value = char(EventCodes(theEvent,:));
end
end
end
end
if ~unsegmented
for segment=1:hdr.nTrials % cell information
eventCount=eventCount+1;
event(eventCount).type = 'trial';
event(eventCount).sample = (segment-1)*hdr.nSamples + 1;
event(eventCount).offset = -hdr.nSamplesPre;
event(eventCount).duration = hdr.nSamples;
event(eventCount).value = char([CateNames{segHdr(segment,1)}(1:CatLengths(segHdr(segment,1)))]);
end
end;
case {'egi_mff_v1' 'egi_mff'} % this is currently the default
% The following represents the code that was written by Ingrid, Robert
% and Giovanni to get started with the EGI mff dataset format. It might
% not support all details of the file formats.
% An alternative implementation has been provided by EGI, this is
% released as fieldtrip/external/egi_mff and referred further down in
% this function as 'egi_mff_v2'.
if isempty(hdr)
% use the corresponding code to read the header
hdr = ft_read_header(filename, 'headerformat', eventformat);
end
if ~usejava('jvm')
error('the xml2struct requires MATLAB to be running with the Java virtual machine (JVM)');
% an alternative implementation which does not require the JVM but runs much slower is
% available from http://www.mathworks.com/matlabcentral/fileexchange/6268-xml4mat-v2-0
end
% get event info from xml files
warning('off', 'MATLAB:REGEXP:deprecated') % due to some small code xml2struct
xmlfiles = dir( fullfile(filename, '*.xml'));
disp('reading xml files to obtain event info... This might take a while if many events/triggers are present')
if isempty(xmlfiles)
xml=struct([]);
else
xml=[];
end;
for i = 1:numel(xmlfiles)
if strcmpi(xmlfiles(i).name(1:6), 'Events')
fieldname = xmlfiles(i).name(1:end-4);
filename_xml = fullfile(filename, xmlfiles(i).name);
xml.(fieldname) = xml2struct(filename_xml);
end
end
warning('on', 'MATLAB:REGEXP:deprecated')
% construct info needed for FieldTrip Event
eventNames = fieldnames(xml);
begTime = hdr.orig.xml.info.recordTime;
begTime(11) = ' '; begTime(end-5:end) = [];
begSDV = datenum(begTime);
% find out if there are epochs in this dataset
if isfield(hdr.orig.xml,'epoch') && length(hdr.orig.xml.epoch) > 1
Msamp2offset = zeros(2,size(hdr.orig.epochdef,1),1+max(hdr.orig.epochdef(:,2)-hdr.orig.epochdef(:,1)));
Msamp2offset(:) = NaN;
for iEpoch = 1:size(hdr.orig.epochdef,1)
nSampEpoch = hdr.orig.epochdef(iEpoch,2)-hdr.orig.epochdef(iEpoch,1)+1;
Msamp2offset(1,iEpoch,1:nSampEpoch) = hdr.orig.epochdef(iEpoch,1):hdr.orig.epochdef(iEpoch,2); %sample number in samples
Msamp2offset(2,iEpoch,1:nSampEpoch) = hdr.orig.epochdef(iEpoch,3):hdr.orig.epochdef(iEpoch,3)+nSampEpoch-1; %offset in samples
end
end
% construct event according to FieldTrip rules
eventCount = 0;
for iXml = 1:length(eventNames)
for iEvent = 1:length(xml.(eventNames{iXml}))
eventTime = xml.(eventNames{iXml})(iEvent).event.beginTime;
eventTime(11) = ' '; eventTime(end-5:end) = [];
if strcmp('-',eventTime(21))
% event out of range (before recording started): do nothing.
else
eventSDV = datenum(eventTime);
eventOffset = round((eventSDV - begSDV)*24*60*60*hdr.Fs); %in samples, relative to start of recording
if eventOffset < 0
% event out of range (before recording started): do nothing
else
eventCount = eventCount+1;
% calculate eventSample, relative to start of epoch
if isfield(hdr.orig.xml,'epoch') && length(hdr.orig.xml.epoch) > 1
for iEpoch = 1:size(hdr.orig.epochdef,1)
[dum,dum2] = intersect(squeeze(Msamp2offset(2,iEpoch,:)), eventOffset);
if ~isempty(dum2)
EpochNum = iEpoch;
SampIndex = dum2;
end
end
eventSample = Msamp2offset(1,EpochNum,SampIndex);
else
eventSample = eventOffset+1;
end
event(eventCount).type = eventNames{iXml}(8:end);
event(eventCount).sample = eventSample;
event(eventCount).offset = 0;
event(eventCount).duration = str2double(xml.(eventNames{iXml})(iEvent).event.duration)./1000000000*hdr.Fs;
event(eventCount).value = xml.(eventNames{iXml})(iEvent).event.code;
end %if that takes care of non "-" events that are still out of range
end %if that takes care of "-" events, which are out of range
end %iEvent
end
case 'egi_mff_v2'
% ensure that the EGI toolbox is on the path
ft_hastoolbox('egi_mff', 1);
if isunix && filename(1)~=filesep
% add the full path to the dataset directory
filename = fullfile(pwd, filename);
else
% FIXME I don't know how this is supposed to work on Windows computers
% with the drive letter in front of the path
end
% pass the header along to speed it up, it will be read on the fly in case it is empty
event = read_mff_event(filename, hdr);
% clean up the fields in the event structure
fn = fieldnames(event);
fn = setdiff(fn, {'type', 'sample', 'value', 'offset', 'duration', 'timestamp'});
for i=1:length(fn)
event = rmfield(event, fn{i});
end
case 'eyelink_asc'
if isempty(hdr)
hdr = ft_read_header(filename);
end
if isfield(hdr.orig, 'input')
% this is inefficient, since it keeps the complete data in memory
% but it does speed up subsequent read operations without the user
% having to care about it
asc = hdr.orig;
else
asc = read_eyelink_asc(filename);
end
timestamp = [asc.input(:).timestamp];
value = [asc.input(:).value];
% note that in this dataformat the first input trigger can be before
% the start of the data acquisition
for i=1:length(timestamp)
event(end+1).type = 'INPUT';
event(end ).sample = (timestamp(i)-hdr.FirstTimeStamp)/hdr.TimeStampPerSample + 1;
event(end ).timestamp = timestamp(i);
event(end ).value = value(i);
event(end ).duration = 1;
event(end ).offset = 0;
end
case 'fcdc_buffer'
% read from a networked buffer for realtime analysis
[host, port] = filetype_check_uri(filename);
% SK: the following was intended to speed up, but does not work
% the buffer server will try to return exact indices, even
% if the intend here is to filter based on a maximum range.
% We could change the definition of GET_EVT to comply
% with filtering, but that might break other existing code.
%if isempty(flt_minnumber) && isempty(flt_maxnumber)
% evtsel = [];
%else
% evtsel = [0 2^32-1];
% if ~isempty(flt_minnumber)
% evtsel(1) = flt_minnumber-1;
% end
% if ~isempty(flt_maxnumber)
% evtsel(2) = flt_maxnumber-1;
% end
%end
if blocking && isempty(flt_minnumber) && isempty(flt_maxnumber)
warning('disabling blocking because no selection was specified');
blocking = false;
end
if blocking
nsamples = -1; % disable waiting for samples
if isempty(flt_minnumber)
nevents = flt_maxnumber;
elseif isempty(flt_maxnumber)
nevents = flt_minnumber;
else
nevents = max(flt_minnumber, flt_maxnumber);
end
available = buffer_wait_dat([nsamples nevents timeout*1000], host, port);
if available.nevents<nevents
error('buffer timed out while waiting for %d events', nevents);
end
end
try
event = buffer('get_evt', [], host, port);
catch
if strfind(lasterr, 'the buffer returned an error')
% this happens if the buffer contains no events
% which in itself is not a problem and should not result in an error
event = [];
else
rethrow(lasterr);
end
end
case 'fcdc_buffer_offline'
[path, file, ext] = fileparts(filename);
if isempty(hdr)
headerfile = fullfile(path, 'header');
hdr = read_buffer_offline_header(headerfile);
end
eventfile = fullfile(path, 'events');
event = read_buffer_offline_events(eventfile, hdr);
case 'fcdc_matbin'
% this is multiplexed data in a *.bin file, accompanied by a matlab file containing the header and event
[path, file, ext] = fileparts(filename);
filename = fullfile(path, [file '.mat']);
% read the events from the Matlab file
tmp = load(filename, 'event');
event = tmp.event;
case 'fcdc_fifo'
fifo = filetype_check_uri(filename);
if ~exist(fifo,'file')
warning('the FIFO %s does not exist; attempting to create it', fifo);
fid = fopen(fifo, 'r');
system(sprintf('mkfifo -m 0666 %s',fifo));
end
msg = fread(fid, inf, 'uint8');
fclose(fid);
try
event = mxDeserialize(uint8(msg));
catch
warning(lasterr);
end
case 'fcdc_tcp'
% requires tcp/udp/ip-toolbox
ft_hastoolbox('TCP_UDP_IP', 1);
[host, port] = filetype_check_uri(filename);
if isempty(sock)
sock=pnet('tcpsocket',port);
end
con = pnet(sock, 'tcplisten');
if con~=-1
try
pnet(con,'setreadtimeout',10);
% read packet
msg=pnet(con,'readline'); %,1000,'uint8','network');
if ~isempty(msg)
event = mxDeserialize(uint8(str2num(msg)));
end
% catch
% warning(lasterr);
end
pnet(con,'close');
end
con = [];
case 'fcdc_udp'
% requires tcp/udp/ip-toolbox
ft_hastoolbox('TCP_UDP_IP', 1);
[host, port] = filetype_check_uri(filename);
try
% read from localhost
udp=pnet('udpsocket',port);
% Wait/Read udp packet to read buffer
len=pnet(udp,'readpacket');
if len>0,
% if packet larger then 1 byte then read maximum of 1000 doubles in network byte order
msg=pnet(udp,'read',1000,'uint8');
if ~isempty(msg)
event = mxDeserialize(uint8(msg));
end
end
catch
warning(lasterr);
end
% On break or error close connection
pnet(udp,'close');
case 'fcdc_serial'
% this code is moved to a seperate file
event = read_serial_event(filename);
case 'fcdc_mysql'
% check that the required low-level toolbox is available
ft_hastoolbox('mysql', 1);
% read from a MySQL server listening somewhere else on the network
db_open(filename);
if db_blob
event = db_select_blob('fieldtrip.event', 'msg');
else
event = db_select('fieldtrip.event', {'type', 'value', 'sample', 'offset', 'duration'});
end
case 'gtec_mat'
if isempty(hdr)
hdr = ft_read_header(filename);
end
if isempty(trigindx)
% these are probably trigger channels
trigindx = match_str(hdr.label, {'Display', 'Target'});
end
% use a helper function to read the trigger channels and detect the flanks
% pass all the other users options to the read_trigger function
event = read_trigger(filename, 'header', hdr, 'begsample', flt_minsample, 'endsample', flt_maxsample, 'chanindx', trigindx, 'dataformat', dataformat, 'detectflank', detectflank, 'trigshift', trigshift);
case {'itab_raw' 'itab_mhd'}
if isempty(hdr)
hdr = ft_read_header(filename);
end
for i=1:hdr.orig.nsmpl
event(end+1).type = 'trigger';
event(end ).value = hdr.orig.smpl(i).type;
event(end ).sample = hdr.orig.smpl(i).start + 1;
event(end ).duration = hdr.orig.smpl(i).ntptot;
event(end ).offset = -hdr.orig.smpl(i).ntppre; % number of samples prior to the trigger
end
if isempty(event)
warning('no events found in the event table, reading the trigger channel(s)');
trigsel = find(ft_chantype(hdr, 'flag'));
trigger = read_trigger(filename, 'header', hdr, 'dataformat', dataformat, 'begsample', flt_minsample, 'endsample', flt_maxsample, 'chanindx', trigsel, 'detectflank', detectflank, 'trigshift', trigshift);
event = appendevent(event, trigger);
end
case 'matlab'
% read the events from a normal Matlab file
tmp = load(filename, 'event');
event = tmp.event;
case 'micromed_trc'
if isempty(hdr)
hdr = ft_read_header(filename);
end
if isfield(hdr, 'orig') && isfield(hdr.orig, 'Trigger_Area') && isfield(hdr.orig, 'Tigger_Area_Length')
if ~isempty(trigindx)
trigger = read_trigger(filename, 'header', hdr, 'begsample', flt_minsample, 'endsample', flt_maxsample, 'chanindx', trigindx, 'detectflank', detectflank, 'trigshift', trigshift,'dataformat', 'micromed_trc');
event = appendevent(event, trigger);
else
% routine that reads analog triggers in case no index is specified
event = read_micromed_event(filename);
end
else
error('Not a correct event format')
end
case {'mpi_ds', 'mpi_dap'}
if isempty(hdr)
hdr = ft_read_header(filename);
end
% determine the DAP files that compromise this dataset
if isdir(filename)
ls = dir(filename);
dapfile = {};
for i=1:length(ls)
if ~isempty(regexp(ls(i).name, '.dap$', 'once' ))
dapfile{end+1} = fullfile(filename, ls(i).name);
end
end
dapfile = sort(dapfile);
elseif iscell(filename)
dapfile = filename;
else
dapfile = {filename};
end
% assume that each DAP file is accompanied by a dat file
% read the trigger values from the separate dat files
trg = [];
for i=1:length(dapfile)
datfile = [dapfile{i}(1:(end-4)) '.dat'];
trg = cat(1, trg, textread(datfile, '', 'headerlines', 1));
end
% construct a event structure, one 'trialcode' event per trial
for i=1:length(trg)
event(i).type = 'trialcode'; % string
event(i).sample = (i-1)*hdr.nSamples + 1; % expressed in samples, first sample of file is 1
event(i).value = trg(i); % number or string
event(i).offset = 0; % expressed in samples
event(i).duration = hdr.nSamples; % expressed in samples
end
case {'babysquid_fif' 'babysquid_eve'}
if strcmp(eventformat, 'babysquid_fif')
% ensure that we are reading the *.eve file
[p, f, x] = fileparts(filename);
filename = fullfile(p, [f '.eve']);
end
% see http://bugzilla.fcdonders.nl/show_bug.cgi?id=1914 for details
[smp, tim, val, typ] = read_babysquid_eve(filename);
if ~isempty(smp)
smp = num2cell(smp);
val = num2cell(val);
typ = cellfun(@num2str, num2cell(typ), 'UniformOutput', false);
offset = num2cell(zeros(size(smp)));
% convert to a structure array
event = struct('type', typ, 'value', val, 'sample', smp, 'offset', offset);
else
event = [];
end
case {'neuromag_fif' 'neuromag_mne' 'neuromag_mex'}
if strcmp(eventformat, 'neuromag_fif')
% the default is to use the MNE reader for fif files
eventformat = 'neuromag_mne';
end
if strcmp(eventformat, 'neuromag_mex')
% check that the required low-level toolbox is available
ft_hastoolbox('meg-pd', 1);
if isempty(headerformat), headerformat = eventformat; end
if isempty(dataformat), dataformat = eventformat; end
elseif strcmp(eventformat, 'neuromag_mne')
% check that the required low-level toolbox is available
ft_hastoolbox('mne', 1);
if isempty(headerformat), headerformat = eventformat; end
if isempty(dataformat), dataformat = eventformat; end
end
if isempty(hdr)
hdr = ft_read_header(filename, 'headerformat', headerformat);
end
% note below we've had to include some chunks of code that are only
% called if the file is an averaged file, or if the file is continuous.
% These are defined in hdr by read_header for neuromag_mne, but do not
% exist for neuromag_fif, hence we run the code anyway if the fields do
% not exist (this is what happened previously anyway).
if strcmp(eventformat, 'neuromag_mex')
iscontinuous = 1;
isaverage = 0;
isepoched = 0;
elseif strcmp(eventformat, 'neuromag_mne')
iscontinuous = hdr.orig.iscontinuous;
isaverage = hdr.orig.isaverage;
isepoched = hdr.orig.isepoched;
end
if iscontinuous
analogindx = find(strcmp(ft_chantype(hdr), 'analog trigger'));
binaryindx = find(strcmp(ft_chantype(hdr), 'digital trigger'));
if isempty(binaryindx)&&isempty(analogindx)
% included in case of problems with older systems and MNE reader:
% use a predefined set of channel names
binary = {'STI 014', 'STI 015', 'STI 016'};
binaryindx = match_str(hdr.label, binary);
end
if ~isempty(binaryindx)
trigger = read_trigger(filename, 'header', hdr, 'dataformat', dataformat, 'begsample', flt_minsample, 'endsample', flt_maxsample, 'chanindx', binaryindx, 'detectflank', detectflank, 'trigshift', trigshift, 'fixneuromag', 0);
event = appendevent(event, trigger);
end
if ~isempty(analogindx)
% add the triggers to the event structure based on trigger channels with the name "STI xxx"
% there are some issues with noise on these analog trigger
% channels, on older systems only
% read the trigger channel and do flank detection
trigger = read_trigger(filename, 'header', hdr, 'dataformat', dataformat, 'begsample', flt_minsample, 'endsample', flt_maxsample, 'chanindx', analogindx, 'detectflank', detectflank, 'trigshift', trigshift, 'fixneuromag', 1);
event = appendevent(event, trigger);
end
elseif isaverage
% the length of each average can be variable
nsamples = zeros(1, length(hdr.orig.evoked));
for i=1:length(hdr.orig.evoked)
nsamples(i) = size(hdr.orig.evoked(i).epochs, 2);
end
begsample = cumsum([1 nsamples]);
for i=1:length(hdr.orig.evoked)
event(end+1).type = 'average';
event(end ).sample = begsample(i);
event(end ).value = hdr.orig.evoked(i).comment; % this is a descriptive string
event(end ).offset = hdr.orig.evoked(i).first;
event(end ).duration = hdr.orig.evoked(i).last - hdr.orig.evoked(i).first + 1;
end
elseif isepoched
error('Support for epoched *.fif data is not yet implemented.')
end
case {'neuralynx_ttl' 'neuralynx_bin' 'neuralynx_dma' 'neuralynx_sdma'}
if isempty(hdr)
hdr = ft_read_header(filename);
end
% specify the range to search for triggers, default is the complete file
if ~isempty(flt_minsample)
begsample = flt_minsample;
else
begsample = 1;
end
if ~isempty(flt_maxsample)
endsample = flt_maxsample;
else
endsample = hdr.nSamples*hdr.nTrials;
end
if strcmp(eventformat, 'neuralynx_dma')
% read the Parallel_in channel from the DMA log file
ttl = read_neuralynx_dma(filename, begsample, endsample, 'ttl');
elseif strcmp(eventformat, 'neuralynx_sdma')
% determine the seperate files with the trigger and timestamp information
[p, f, x] = fileparts(filename);
ttlfile = fullfile(filename, [f '.ttl.bin']);
tslfile = fullfile(filename, [f '.tsl.bin']);
tshfile = fullfile(filename, [f '.tsh.bin']);
if ~exist(ttlfile) && ~exist(tslfile) && ~exist(tshfile)
% perhaps it is an old splitted dma dataset?
ttlfile = fullfile(filename, [f '.ttl']);
tslfile = fullfile(filename, [f '.tsl']);
tshfile = fullfile(filename, [f '.tsh']);
end
if ~exist(ttlfile) && ~exist(tslfile) && ~exist(tshfile)
% these files must be present in a splitted dma dataset
error('could not locate the individual ttl, tsl and tsh files');
end
% read the trigger values from the seperate file
ttl = read_neuralynx_bin(ttlfile, begsample, endsample);
elseif strcmp(eventformat, 'neuralynx_ttl')
% determine the optional files with timestamp information
tslfile = [filename(1:(end-4)) '.tsl'];
tshfile = [filename(1:(end-4)) '.tsh'];
% read the triggers from a seperate *.ttl file
ttl = read_neuralynx_ttl(filename, begsample, endsample);
elseif strcmp(eventformat, 'neuralynx_bin')
% determine the optional files with timestamp information
tslfile = [filename(1:(end-8)) '.tsl.bin'];
tshfile = [filename(1:(end-8)) '.tsh.bin'];
% read the triggers from a seperate *.ttl.bin file
ttl = read_neuralynx_bin(filename, begsample, endsample);
end
ttl = int32(ttl / (2^16)); % parallel port provides int32, but word resolution is int16. Shift the bits and typecast to signed integer.
d1 = (diff(ttl)~=0); % determine the flanks, which can be multiple samples long (this looses one sample)
d2 = (diff(d1)==1); % determine the onset of the flanks (this looses one sample)
smp = find(d2)+2; % find the onset of the flanks, add the two samples again
val = ttl(smp+5); % look some samples further for the trigger value, to avoid the flank
clear d1 d2 ttl
ind = find(val~=0); % look for triggers tith a non-zero value, this avoids downgoing flanks going to zero
smp = smp(ind); % discard triggers with a value of zero
val = val(ind); % discard triggers with a value of zero
if ~isempty(smp)
% try reading the timestamps
if strcmp(eventformat, 'neuralynx_dma')
tsl = read_neuralynx_dma(filename, 1, max(smp), 'tsl');
tsl = typecast(tsl(smp), 'uint32');
tsh = read_neuralynx_dma(filename, 1, max(smp), 'tsh');
tsh = typecast(tsh(smp), 'uint32');
ts = timestamp_neuralynx(tsl, tsh);
elseif exist(tslfile) && exist(tshfile)
tsl = read_neuralynx_bin(tslfile, 1, max(smp));
tsl = tsl(smp);
tsh = read_neuralynx_bin(tshfile, 1, max(smp));
tsh = tsh(smp);
ts = timestamp_neuralynx(tsl, tsh);
else
ts = [];
end
% reformat the values as cell array, since the struct function can work with those
type = repmat({'trigger'},size(smp));
value = num2cell(val);
sample = num2cell(smp + begsample - 1);
duration = repmat({[]},size(smp));
offset = repmat({[]},size(smp));
if ~isempty(ts)
timestamp = reshape(num2cell(ts),size(smp));
else
timestamp = repmat({[]},size(smp));
end
% convert it into a structure array, this can be done in one go
event = struct('type', type, 'value', value, 'sample', sample, 'timestamp', timestamp, 'offset', offset, 'duration', duration);
clear type value sample timestamp offset duration
end
if (strcmp(eventformat, 'neuralynx_bin') || strcmp(eventformat, 'neuralynx_ttl')) && isfield(hdr, 'FirstTimeStamp')
% the header was obtained from an external dataset which could be at a different sampling rate
% use the timestamps to redetermine the sample numbers
fprintf('using sample number of the downsampled file to reposition the TTL events\n');
% convert the timestamps into samples, keeping in mind the FirstTimeStamp and TimeStampPerSample
smp = round(double(ts - uint64(hdr.FirstTimeStamp))./hdr.TimeStampPerSample + 1);
for i=1:length(event)
% update the sample number
event(i).sample = smp(i);
end
end
case 'neuralynx_ds'
% read the header of the dataset
if isempty(hdr)
hdr = ft_read_header(filename);
end
% the event file is contained in the dataset directory
if exist(fullfile(filename, 'Events.Nev'))
filename = fullfile(filename, 'Events.Nev');
elseif exist(fullfile(filename, 'Events.nev'))
filename = fullfile(filename, 'Events.nev');
elseif exist(fullfile(filename, 'events.Nev'))
filename = fullfile(filename, 'events.Nev');
elseif exist(fullfile(filename, 'events.nev'))
filename = fullfile(filename, 'events.nev');
end
% read the events, apply filter is applicable
nev = read_neuralynx_nev(filename, 'type', flt_type, 'value', flt_value, 'mintimestamp', flt_mintimestamp, 'maxtimestamp', flt_maxtimestamp, 'minnumber', flt_minnumber, 'maxnumber', flt_maxnumber);
% the following code should only be executed if there are events,
% otherwise there will be an error subtracting an uint64 from an []
if ~isempty(nev)
% now get the values as cell array, since the struct function can work with those
value = {nev.TTLValue};
timestamp = {nev.TimeStamp};
number = {nev.EventNumber};
type = repmat({'trigger'},size(value));
duration = repmat({[]},size(value));
offset = repmat({[]},size(value));
sample = num2cell(round(double(cell2mat(timestamp) - hdr.FirstTimeStamp)/hdr.TimeStampPerSample + 1));
% convert it into a structure array
event = struct('type', type, 'value', value, 'sample', sample, 'timestamp', timestamp, 'duration', duration, 'offset', offset, 'number', number);
end
case 'neuralynx_cds'
% this is a combined Neuralynx dataset with seperate subdirectories for the LFP, MUA and spike channels
dirlist = dir(filename);
%haslfp = any(filetype_check_extension({dirlist.name}, 'lfp'));
%hasmua = any(filetype_check_extension({dirlist.name}, 'mua'));
%hasspike = any(filetype_check_extension({dirlist.name}, 'spike'));
%hastsl = any(filetype_check_extension({dirlist.name}, 'tsl')); % seperate file with original TimeStampLow
%hastsh = any(filetype_check_extension({dirlist.name}, 'tsh')); % seperate file with original TimeStampHi
hasttl = any(filetype_check_extension({dirlist.name}, 'ttl')); % seperate file with original Parallel_in
hasnev = any(filetype_check_extension({dirlist.name}, 'nev')); % original Events.Nev file
hasmat = 0;
if hasttl
eventfile = fullfile(filename, dirlist(find(filetype_check_extension({dirlist.name}, 'ttl'))).name);
% read the header from the combined dataset
if isempty(hdr)
hdr = ft_read_header(filename);
end
% read the events from the *.ttl file
event = ft_read_event(eventfile);
% convert the sample numbers from the dma or ttl file to the downsampled dataset
% assume that the *.ttl file is sampled at 32556Hz and is aligned with the rest of the data
for i=1:length(event)
event(i).sample = round((event(i).sample-1) * hdr.Fs/32556 + 1);
end
% elseif hasnev
% FIXME, do something here
% elseif hasmat
% FIXME, do something here
else
error('no event file found');
end
% The sample number is missingin the code below, since it is not available
% without looking in the continuously sampled data files. Therefore
% sorting the events (later in this function) based on the sample number
% fails and no events can be returned.
%
% case 'neuralynx_nev'
% [nev] = read_neuralynx_nev(filename);
% % select only the events with a TTL value
% ttl = [nev.TTLValue];
% sel = find(ttl~=0);
% % now get the values as cell array, since teh struct function can work with those
% value = {nev(sel).TTLValue};
% timestamp = {nev(sel).TimeStamp};
% event = struct('value', value, 'timestamp', timestamp);
% for i=1:length(event)
% % assign the other fixed elements
% event(i).type = 'trigger';
% event(i).offset = [];
% event(i).duration = [];
% event(i).sample = [];
% end
case {'neuroprax_eeg', 'neuroprax_mrk'}
tmp = np_readmarker (filename, 0, inf, 'samples');
event = [];
for i = 1:numel(tmp.marker)
if isempty(tmp.marker{i})
break;
end
event = [event struct('type', tmp.markernames(i),...
'sample', num2cell(tmp.marker{i}),...
'value', {tmp.markertyp(i)})];
end
case 'nexstim_nxe'
event = read_nexstim_event(filename);
case 'nimh_cortex'
if isempty(hdr)
hdr = ft_read_header(filename);
end
cortex = hdr.orig.trial;
for i=1:length(cortex)
% add one 'trial' event for every trial and add the trigger events
event(end+1).type = 'trial';
event(end ).sample = nan;
event(end ).duration = nan;
event(end ).offset = nan;
event(end ).value = i; % use the trial number as value
for j=1:length(cortex(i).event)
event(end+1).type = 'trigger';
event(end ).sample = nan;
event(end ).duration = nan;
event(end ).offset = nan;
event(end ).value = cortex(i).event(j);
end
end
case 'ns_avg'
if isempty(hdr)
hdr = ft_read_header(filename);
end
event(end+1).type = 'average';
event(end ).sample = 1;
event(end ).duration = hdr.nSamples;
event(end ).offset = -hdr.nSamplesPre;
event(end ).value = [];
case {'ns_cnt', 'ns_cnt16', 'ns_cnt32'}
% read the header, the original header includes the event table
if isempty(hdr)
hdr = ft_read_header(filename, 'headerformat', eventformat);
end
% translate the event table into known FieldTrip event types
for i=1:numel(hdr.orig.event)
event(end+1).type = 'trigger';
event(end ).sample = hdr.orig.event(i).offset + 1; % +1 was in EEGLAB pop_loadcnt
event(end ).value = hdr.orig.event(i).stimtype;
event(end ).offset = 0;
event(end ).duration = 0;
% the code above assumes that all events are stimulus triggers
% howevere, there are also interesting events possible, such as responses
if hdr.orig.event(i).stimtype~=0
event(end+1).type = 'stimtype';
event(end ).sample = hdr.orig.event(i).offset + 1; % +1 was in EEGLAB pop_loadcnt
event(end ).value = hdr.orig.event(i).stimtype;
event(end ).offset = 0;
event(end ).duration = 0;
elseif hdr.orig.event(i).keypad_accept~=0
event(end+1).type = 'keypad_accept';
event(end ).sample = hdr.orig.event(i).offset + 1; % +1 was in EEGLAB pop_loadcnt
event(end ).value = hdr.orig.event(i).keypad_accept;
event(end ).offset = 0;
event(end ).duration = 0;
end
end
case 'ns_eeg'
if isempty(hdr)
hdr = ft_read_header(filename);
end
for i=1:hdr.nTrials
% the *.eeg file has a fixed trigger value for each trial
% furthermore each trial has additional fields like accept, correct, response and rt
tmp = read_ns_eeg(filename, i);
% create an event with the trigger value
event(end+1).type = 'trial';
event(end ).sample = (i-1)*hdr.nSamples + 1;
event(end ).value = tmp.sweep.type; % trigger value
event(end ).offset = -hdr.nSamplesPre;
event(end ).duration = hdr.nSamples;
% create an event with the boolean accept/reject code
event(end+1).type = 'accept';
event(end ).sample = (i-1)*hdr.nSamples + 1;
event(end ).value = tmp.sweep.accept; % boolean value indicating accept/reject
event(end ).offset = -hdr.nSamplesPre;
event(end ).duration = hdr.nSamples;
% create an event with the boolean accept/reject code
event(end+1).type = 'correct';
event(end ).sample = (i-1)*hdr.nSamples + 1;
event(end ).value = tmp.sweep.correct; % boolean value
event(end ).offset = -hdr.nSamplesPre;
event(end ).duration = hdr.nSamples;
% create an event with the boolean accept/reject code
event(end+1).type = 'response';
event(end ).sample = (i-1)*hdr.nSamples + 1;
event(end ).value = tmp.sweep.response; % probably a boolean value
event(end ).offset = -hdr.nSamplesPre;
event(end ).duration = hdr.nSamples;
% create an event with the boolean accept/reject code
event(end+1).type = 'rt';
event(end ).sample = (i-1)*hdr.nSamples + 1;
event(end ).value = tmp.sweep.rt; % time in seconds
event(end ).offset = -hdr.nSamplesPre;
event(end ).duration = hdr.nSamples;
end
case 'plexon_nex'
event = read_nex_event(filename);
case {'yokogawa_ave', 'yokogawa_con', 'yokogawa_raw'}
% check that the required low-level toolbox is available
if ~ft_hastoolbox('yokogawa', 0);
ft_hastoolbox('yokogawa_meg_reader', 1);
end
% the user should be able to specify the analog threshold
% the user should be able to specify the trigger channels
% the user should be able to specify the flank, but the code falls back to 'auto' as default
if isempty(detectflank)
detectflank = 'auto';
end
event = read_yokogawa_event(filename, 'detectflank', detectflank, 'trigindx', trigindx, 'threshold', threshold);
case 'nmc_archive_k'
event = read_nmc_archive_k_event(filename);
case 'netmeg'
warning('reading of events for the netmeg format is not yet supported');
event = [];
case 'neuroshare' % NOTE: still under development
% check that the required neuroshare toolbox is available
ft_hastoolbox('neuroshare', 1);
tmp = read_neuroshare(filename, 'readevent', 'yes');
for i=1:length(tmp.event.timestamp)
event(i).type = tmp.hdr.eventinfo(i).EventType;
event(i).value = tmp.event.data(i);
event(i).timestamp = tmp.event.timestamp(i);
event(i).sample = tmp.event.sample(i);
end
case 'dataq_wdq'
if isempty(hdr)
hdr = ft_read_header(filename, 'headerformat', 'dataq_wdq');
end
trigger = read_wdq_data(filename, hdr.orig, 'lowbits');
[ix, iy] = find(trigger>1); %it seems as if the value of 1 is meaningless
for i=1:numel(ix)
event(i).type = num2str(ix(i));
event(i).value = trigger(ix(i),iy(i));
event(i).sample = iy(i);
end
case 'bucn_nirs'
event = read_bucn_nirsevent(filename);
otherwise
warning('FieldTrip:ft_read_event:unsupported_event_format','unsupported event format (%s)', eventformat);
event = [];
end
if ~isempty(hdr) && hdr.nTrials>1 && (isempty(event) || ~any(strcmp({event.type}, 'trial')))
% the data suggests multiple trials and trial events have not yet been defined
% make an event for each trial according to the file header
for i=1:hdr.nTrials
event(end+1).type = 'trial';
event(end ).sample = (i-1)*hdr.nSamples + 1;
event(end ).offset = -hdr.nSamplesPre;
event(end ).duration = hdr.nSamples;
event(end ).value = [];
end
end
if ~isempty(event)
% make sure that all required elements are present
if ~isfield(event, 'type'), error('type field not defined for each event'); end
if ~isfield(event, 'sample'), error('sample field not defined for each event'); end
if ~isfield(event, 'value'), for i=1:length(event), event(i).value = []; end; end
if ~isfield(event, 'offset'), for i=1:length(event), event(i).offset = []; end; end
if ~isfield(event, 'duration'), for i=1:length(event), event(i).duration = []; end; end
end
% make sure that all numeric values are double
if ~isempty(event)
for i=1:length(event)
if isnumeric(event(i).value)
event(i).value = double(event(i).value);
end
event(i).sample = double(event(i).sample);
event(i).offset = double(event(i).offset);
event(i).duration = double(event(i).duration);
end
end
if ~isempty(event)
% sort the events on the sample on which they occur
% this has the side effect that events without a sample number are discarded
[dum, indx] = sort([event.sample]);
event = event(indx);
% else
% warning('no events found in %s', filename);
end
% apply the optional filters
event = ft_filter_event(event, varargin{:});
if isempty(event)
% ensure that it has the correct fields, even if it is empty
event = struct('type', {}, 'value', {}, 'sample', {}, 'offset', {}, 'duration', {});
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% poll implementation for backwards compatibility with ft buffer version 1
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function available = buffer_wait_dat(selection, host, port)
% selection(1) nsamples
% selection(2) nevents
% selection(3) timeout in msec
% check if backwards compatibilty mode is required
try
% the WAIT_DAT request waits until it has more samples or events
selection(1) = selection(1)-1;
selection(2) = selection(2)-1;
% the following should work for buffer version 2
available = buffer('WAIT_DAT', selection, host, port);
catch
% the error means that the buffer is version 1, which does not support the WAIT_DAT request
% the wait_dat can be implemented by polling the buffer
nsamples = selection(1);
nevents = selection(2);
timeout = selection(3)/1000; % in seconds
stopwatch = tic;
% results are retrieved in the order written to the buffer
orig = buffer('GET_HDR', [], host, port);
if timeout > 0
% wait maximal timeout seconds until more than nsamples samples or nevents events have been received
while toc(stopwatch)<timeout
if nsamples == -1 && nevents == -1, break, end
if nsamples ~= -1 && orig.nsamples >= nsamples, break, end
if nevents ~= -1 && orig.nevents >= nevents, break, end
orig = buffer('GET_HDR', [], host, port);
pause(0.001);
end
else
% no reason to wait
end
available.nsamples = orig.nsamples;
available.nevents = orig.nevents;
end % try buffer v1 or v2
|
github
|
philippboehmsturm/antx-master
|
ft_read_header.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/ft_read_header.m
| 72,943 |
utf_8
|
21175eb77cfb3d7992b08521a46b5a36
|
function [hdr] = ft_read_header(filename, varargin)
% FT_READ_HEADER reads header information from a variety of EEG, MEG and LFP
% files and represents the header information in a common data-independent
% format. The supported formats are listed below.
%
% Use as
% hdr = ft_read_header(filename, ...)
%
% Additional options should be specified in key-value pairs and can be
% 'headerformat' string
% 'fallback' can be empty or 'biosig' (default = [])
% 'coordsys' string, 'head' or 'dewar' (default = 'head')
%
% This returns a header structure with the following elements
% hdr.Fs sampling frequency
% hdr.nChans number of channels
% hdr.nSamples number of samples per trial
% hdr.nSamplesPre number of pre-trigger samples in each trial
% hdr.nTrials number of trials
% hdr.label Nx1 cell-array with the label of each channel
% hdr.chantype Nx1 cell-array with the channel type, see FT_CHANTYPE
% hdr.chanunit Nx1 cell-array with the physical units, see FT_CHANUNIT
%
% For continuously recorded data, nSamplesPre=0 and nTrials=1.
%
% For some data formats that are recorded on animal electrophysiology
% systems (e.g. Neuralynx, Plexon), the following optional fields are
% returned, which allows for relating the timing of spike and LFP data
% hdr.FirstTimeStamp number, 32 bit or 64 bit unsigned integer
% hdr.TimeStampPerSample double
%
% Depending on the file format, additional header information can be
% returned in the hdr.orig subfield.
%
% The following MEG dataformats are supported
% CTF - VSM MedTech (*.ds, *.res4, *.meg4)
% Neuromag - Elekta (*.fif)
% BTi - 4D Neuroimaging (*.m4d, *.pdf, *.xyz)
% Yokogawa (*.ave, *.con, *.raw)
% NetMEG (*.nc)
% ITAB - Chieti (*.mhd)
%
% The following EEG dataformats are supported
% ANT - Advanced Neuro Technology, EEProbe (*.avr, *.eeg, *.cnt)
% BCI2000 (*.dat)
% Biosemi (*.bdf)
% BrainVision (*.eeg, *.seg, *.dat, *.vhdr, *.vmrk)
% CED - Cambridge Electronic Design (*.smr)
% EGI - Electrical Geodesics, Inc. (*.egis, *.ave, *.gave, *.ses, *.raw, *.sbin, *.mff)
% GTec (*.mat)
% Generic data formats (*.edf, *.gdf)
% Megis/BESA (*.avr, *.swf)
% NeuroScan (*.eeg, *.cnt, *.avg)
% Nexstim (*.nxe)
%
% The following spike and LFP dataformats are supported (with some limitations)
% Neuralynx (*.ncs, *.nse, *.nts, *.nev, DMA log files)
% Plextor (*.nex, *.plx, *.ddt)
% CED - Cambridge Electronic Design (*.smr)
% MPI - Max Planck Institute (*.dap)
% neurosim_spikes
% neurosim_signals, Neurosim_ds
%
% The following NIRS dataformats are supported
% BUCN (*.txt)
%
% See also FT_READ_DATA, FT_READ_EVENT, FT_WRITE_DATA, FT_WRITE_EVENT,
% FT_CHANTYPE, FT_CHANUNIT
% Copyright (C) 2003-2012 Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_read_header.m 7353 2013-01-18 05:14:26Z josdie $
% TODO channel renaming should be made a general option (see bham_bdf)
persistent cacheheader % for caching the full header
persistent cachechunk % for caching the res4 chunk when doing realtime analysis on the CTF scanner
persistent db_blob % for fcdc_mysql
if isempty(db_blob)
db_blob = false;
end
% optionally get the data from the URL and make a temporary local copy
filename = fetch_url(filename);
% test whether the file or directory exists
if ~strcmp(ft_filetype(filename), 'fcdc_buffer') && ~strcmp(ft_filetype(filename), 'ctf_shm') && ~strcmp(ft_filetype(filename), 'fcdc_mysql') && ~exist(filename, 'file')
error('FILEIO:InvalidFileName', 'file or directory ''%s'' does not exist', filename);
end
% get the options
retry = ft_getopt(varargin, 'retry', false); % the default is not to retry reading the header
headerformat = ft_getopt(varargin, 'headerformat');
coordsys = ft_getopt(varargin, 'coordsys', 'head'); % this is used for CTF, it can be head or dewar
if isempty(headerformat)
% only do the autodetection if the format was not specified
headerformat = ft_filetype(filename);
end
% The checkUniqueLabels flag is used for the realtime buffer in case
% it contains fMRI data. It prevents 1000000 voxel names to be checked
% for uniqueness. fMRI users will probably never use channel names
% for anything.
% The skipInitialCheck flag is used to speed up the read operation from
% the realtime buffer in general.
if strcmp(headerformat, 'fcdc_buffer')
% skip the rest of the initial checks to increase the speed for realtime operation
checkUniqueLabels = false;
% the cache and fallback option should always be false for realtime processing
cache = false;
fallback = false;
else
checkUniqueLabels = true;
% the cache and fallback option are according to the user's specification
cache = ft_getopt(varargin, 'cache');
fallback = ft_getopt(varargin, 'fallback');
if isempty(cache),
if strcmp(headerformat, 'bci2000_dat') || strcmp(headerformat, 'eyelink_asc') || strcmp(headerformat, 'gtec_mat') || strcmp(headerformat, 'biosig')
cache = true;
else
cache = false;
end
end
% ensure that the headerfile and datafile are defined, which are sometimes different than the name of the dataset
[filename, headerfile, datafile] = dataset2files(filename, headerformat);
if ~strcmp(filename, headerfile) && ~ft_filetype(filename, 'ctf_ds') && ~ft_filetype(filename, 'fcdc_buffer_offline') && ~ft_filetype(filename, 'fcdc_matbin')
filename = headerfile; % this function should read the headerfile, not the dataset
headerformat = ft_filetype(filename); % update the filetype
end
end % if skip initial check
% start with an empty header
hdr = [];
% implement the caching in a data-format independent way
if cache && exist(headerfile, 'file') && ~isempty(cacheheader)
% try to get the header from cache
details = dir(headerfile);
if isequal(details, cacheheader.details)
% the header file has not been updated, fetch it from the cache
% fprintf('got header from cache\n');
hdr = rmfield(cacheheader, 'details');
switch ft_filetype(datafile)
case {'ctf_ds' 'ctf_meg4' 'ctf_old' 'read_ctf_res4'}
% for realtime analysis EOF chasing the res4 does not correctly
% estimate the number of samples, so we compute it on the fly
sz = 0;
files = dir([filename '/*.*meg4']);
for j=1:numel(files)
sz = sz + files(j).bytes;
end
hdr.nTrials = floor((sz - 8) / (hdr.nChans*4) / hdr.nSamples);
end
return;
end % if the details correspond
end % if cache
% the support for head/dewar coordinates is still limited
if strcmp(coordsys, 'dewar') && ~any(strcmp(headerformat, {'fcdc_buffer', 'ctf_ds', 'ctf_meg4', 'ctf_res4'}))
error('dewar coordinates are sofar only supported for CTF data');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% read the data with the low-level reading function
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
switch headerformat
case '4d'
orig = read_4d_hdr(datafile);
hdr.Fs = orig.header_data.SampleFrequency;
hdr.nChans = orig.header_data.TotalChannels;
hdr.nSamples = orig.header_data.SlicesPerEpoch;
hdr.nSamplesPre = round(orig.header_data.FirstLatency*orig.header_data.SampleFrequency);
hdr.nTrials = orig.header_data.TotalEpochs;
%hdr.label = {orig.channel_data(:).chan_label}';
hdr.label = orig.Channel;
[hdr.grad, elec] = bti2grad(orig);
if ~isempty(elec),
hdr.elec = elec;
end
% remember original header details
hdr.orig = orig;
case {'4d_pdf', '4d_m4d', '4d_xyz'}
orig = read_bti_m4d(filename);
hdr.Fs = orig.SampleFrequency;
hdr.nChans = orig.TotalChannels;
hdr.nSamples = orig.SlicesPerEpoch;
hdr.nSamplesPre = round(orig.FirstLatency*orig.SampleFrequency);
hdr.nTrials = orig.TotalEpochs;
hdr.label = orig.ChannelOrder(:);
[hdr.grad, elec] = bti2grad(orig);
if ~isempty(elec),
hdr.elec = elec;
end
% remember original header details
hdr.orig = orig;
case 'bci2000_dat'
% this requires the load_bcidat mex file to be present on the path
ft_hastoolbox('BCI2000', 1);
% this is inefficient, since it reads the complete data
[signal, states, parameters, total_samples] = load_bcidat(filename);
% convert into a FieldTrip-like header
hdr = [];
hdr.nChans = size(signal,2);
hdr.nSamples = total_samples;
hdr.nSamplesPre = 0; % it is continuous
hdr.nTrials = 1; % it is continuous
hdr.Fs = parameters.SamplingRate.NumericValue;
% there are some differences in the fields that are present in the
% *.dat files, probably due to different BCI2000 versions
if isfield(parameters, 'ChannelNames') && isfield(parameters.ChannelNames, 'Value') && ~isempty(parameters.ChannelNames.Value)
hdr.label = parameters.ChannelNames.Value;
elseif isfield(parameters, 'ChannelNames') && isfield(parameters.ChannelNames, 'Values') && ~isempty(parameters.ChannelNames.Values)
hdr.label = parameters.ChannelNames.Values;
else
% give this warning only once
warning_once('creating fake channel names');
for i=1:hdr.nChans
hdr.label{i} = sprintf('%d', i);
end
end
% remember the original header details
hdr.orig.parameters = parameters;
% also remember the complete data upon request
if cache
hdr.orig.signal = signal;
hdr.orig.states = states;
hdr.orig.total_samples = total_samples;
end
case 'besa_avr'
orig = read_besa_avr(filename);
hdr.Fs = 1000/orig.di;
hdr.nChans = size(orig.data,1);
hdr.nSamples = size(orig.data,2);
hdr.nSamplesPre = -(hdr.Fs * orig.tsb/1000); % convert from ms to samples
hdr.nTrials = 1;
if isfield(orig, 'label') && iscell(orig.label)
hdr.label = orig.label;
elseif isfield(orig, 'label') && ischar(orig.label)
hdr.label = tokenize(orig.label, ' ');
else
% give this warning only once
warning_once('creating fake channel names');
for i=1:hdr.nChans
hdr.label{i} = sprintf('%d', i);
end
end
case 'besa_swf'
orig = read_besa_swf(filename);
hdr.Fs = 1000/orig.di;
hdr.nChans = size(orig.data,1);
hdr.nSamples = size(orig.data,2);
hdr.nSamplesPre = -(hdr.Fs * orig.tsb/1000); % convert from ms to samples
hdr.nTrials = 1;
hdr.label = orig.label;
case {'biosig'}
% this requires the biosig toolbox
ft_hastoolbox('BIOSIG', 1);
hdr = read_biosig_header(filename);
case {'gdf'}
% this requires the biosig toolbox
ft_hastoolbox('BIOSIG', 1);
% In the case that the gdf files are written by one of the FieldTrip
% realtime applications, such as biosig2ft, the gdf recording can be
% split over multiple 1GB files. The sequence of files is then
% filename.gdf <- this is the one that should be specified as the filename/dataset
% filename_1.gdf
% filename_2.gdf
% ...
[p, f, x] = fileparts(filename);
if exist(sprintf('%s_%d%s', fullfile(p, f), 1, x), 'file')
% there are multiple files, count the number of additional files (excluding the first one)
count = 0;
while exist(sprintf('%s_%d%s', fullfile(p, f), count+1, x), 'file')
count = count+1;
end
hdr = read_biosig_header(filename);
for i=1:count
hdr(i+1) = read_biosig_header(sprintf('%s_%d%s', fullfile(p, f), i, x));
% do some sanity checks
if hdr(i+1).nChans~=hdr(1).nChans
error('multiple GDF files detected that should be appended, but the channel count is inconsistent');
elseif hdr(i+1).Fs~=hdr(1).Fs
error('multiple GDF files detected that should be appended, but the sampling frequency is inconsistent');
elseif ~isequal(hdr(i+1).label, hdr(1).label)
error('multiple GDF files detected that should be appended, but the channel names are inconsistent');
end
end % for count
% combine all headers into one
combinedhdr = [];
combinedhdr.Fs = hdr(1).Fs;
combinedhdr.nChans = hdr(1).nChans;
combinedhdr.nSamples = sum([hdr.nSamples].*[hdr.nTrials]);
combinedhdr.nSamplesPre = 0;
combinedhdr.nTrials = 1;
combinedhdr.label = hdr(1).label;
combinedhdr.orig = hdr; % include all individual file details
hdr = combinedhdr;
else
% there is only a single file
hdr = read_biosig_header(filename);
% the GDF format is always continuous
hdr.nSamples = hdr.nSamples * hdr.nTrials;
hdr.nTrials = 1;
hdr.nSamplesPre = 0;
end % if single or multiple gdf files
case {'biosemi_bdf', 'bham_bdf'}
hdr = read_biosemi_bdf(filename);
if any(diff(hdr.orig.SampleRate))
error('channels with different sampling rate not supported');
end
if ft_filetype(filename, 'bham_bdf')
% TODO channel renaming should be made a general option
% this is for the Biosemi system used at the University of Birmingham
labelold = { 'A1' 'A2' 'A3' 'A4' 'A5' 'A6' 'A7' 'A8' 'A9' 'A10' 'A11' 'A12' 'A13' 'A14' 'A15' 'A16' 'A17' 'A18' 'A19' 'A20' 'A21' 'A22' 'A23' 'A24' 'A25' 'A26' 'A27' 'A28' 'A29' 'A30' 'A31' 'A32' 'B1' 'B2' 'B3' 'B4' 'B5' 'B6' 'B7' 'B8' 'B9' 'B10' 'B11' 'B12' 'B13' 'B14' 'B15' 'B16' 'B17' 'B18' 'B19' 'B20' 'B21' 'B22' 'B23' 'B24' 'B25' 'B26' 'B27' 'B28' 'B29' 'B30' 'B31' 'B32' 'C1' 'C2' 'C3' 'C4' 'C5' 'C6' 'C7' 'C8' 'C9' 'C10' 'C11' 'C12' 'C13' 'C14' 'C15' 'C16' 'C17' 'C18' 'C19' 'C20' 'C21' 'C22' 'C23' 'C24' 'C25' 'C26' 'C27' 'C28' 'C29' 'C30' 'C31' 'C32' 'D1' 'D2' 'D3' 'D4' 'D5' 'D6' 'D7' 'D8' 'D9' 'D10' 'D11' 'D12' 'D13' 'D14' 'D15' 'D16' 'D17' 'D18' 'D19' 'D20' 'D21' 'D22' 'D23' 'D24' 'D25' 'D26' 'D27' 'D28' 'D29' 'D30' 'D31' 'D32' 'EXG1' 'EXG2' 'EXG3' 'EXG4' 'EXG5' 'EXG6' 'EXG7' 'EXG8' 'Status'};
labelnew = { 'P9' 'PPO9h' 'PO7' 'PPO5h' 'PPO3h' 'PO5h' 'POO9h' 'PO9' 'I1' 'OI1h' 'O1' 'POO1' 'PO3h' 'PPO1h' 'PPO2h' 'POz' 'Oz' 'Iz' 'I2' 'OI2h' 'O2' 'POO2' 'PO4h' 'PPO4h' 'PO6h' 'POO10h' 'PO10' 'PO8' 'PPO6h' 'PPO10h' 'P10' 'P8' 'TPP9h' 'TP7' 'TTP7h' 'CP5' 'TPP7h' 'P7' 'P5' 'CPP5h' 'CCP5h' 'CP3' 'P3' 'CPP3h' 'CCP3h' 'CP1' 'P1' 'Pz' 'CPP1h' 'CPz' 'CPP2h' 'P2' 'CPP4h' 'CP2' 'CCP4h' 'CP4' 'P4' 'P6' 'CPP6h' 'CCP6h' 'CP6' 'TPP8h' 'TP8' 'TPP10h' 'T7' 'FTT7h' 'FT7' 'FC5' 'FCC5h' 'C5' 'C3' 'FCC3h' 'FC3' 'FC1' 'C1' 'CCP1h' 'Cz' 'FCC1h' 'FCz' 'FFC1h' 'Fz' 'FFC2h' 'FC2' 'FCC2h' 'CCP2h' 'C2' 'C4' 'FCC4h' 'FC4' 'FC6' 'FCC6h' 'C6' 'TTP8h' 'T8' 'FTT8h' 'FT8' 'FT9' 'FFT9h' 'F7' 'FFT7h' 'FFC5h' 'F5' 'AFF7h' 'AF7' 'AF5h' 'AFF5h' 'F3' 'FFC3h' 'F1' 'AF3h' 'Fp1' 'Fpz' 'Fp2' 'AFz' 'AF4h' 'F2' 'FFC4h' 'F4' 'AFF6h' 'AF6h' 'AF8' 'AFF8h' 'F6' 'FFC6h' 'FFT8h' 'F8' 'FFT10h' 'FT10'};
% rename the channel labels
for i=1:length(labelnew)
chan = strcmp(labelold(i), hdr.label);
hdr.label(chan) = labelnew(chan);
end
end
case {'biosemi_old'}
% this uses the openbdf and readbdf functions that were copied from EEGLAB
orig = openbdf(filename);
if any(orig.Head.SampleRate~=orig.Head.SampleRate(1))
error('channels with different sampling rate not supported');
end
hdr.Fs = orig.Head.SampleRate(1);
hdr.nChans = orig.Head.NS;
hdr.label = cellstr(orig.Head.Label);
% it is continuous data, therefore append all records in one trial
hdr.nSamples = orig.Head.NRec * orig.Head.Dur * orig.Head.SampleRate(1);
hdr.nSamplesPre = 0;
hdr.nTrials = 1;
hdr.orig = orig;
% close the file between seperate read operations
fclose(orig.Head.FILE.FID);
case {'brainvision_vhdr', 'brainvision_seg', 'brainvision_eeg', 'brainvision_dat'}
orig = read_brainvision_vhdr(filename);
hdr.Fs = orig.Fs;
hdr.nChans = orig.NumberOfChannels;
hdr.label = orig.label;
hdr.nSamples = orig.nSamples;
hdr.nSamplesPre = orig.nSamplesPre;
hdr.nTrials = orig.nTrials;
hdr.orig = orig;
case 'ced_son'
% check that the required low-level toolbox is available
ft_hastoolbox('neuroshare', 1);
% use the reading function supplied by Gijs van Elswijk
orig = read_ced_son(filename,'readevents','no','readdata','no');
orig = orig.header;
% In Spike2, channels can have different sampling rates, units, length
% etc. etc. Here, channels need to have to same properties.
if length(unique([orig.samplerate]))>1,
error('channels with different sampling rates are not supported');
else
hdr.Fs = orig(1).samplerate;
end;
hdr.nChans = length(orig);
% nsamples of the channel with least samples
hdr.nSamples = min([orig.nsamples]);
hdr.nSamplesPre = 0;
% only continuous data supported
if sum(strcmpi({orig.mode},'continuous')) < hdr.nChans,
error('not all channels contain continuous data');
else
hdr.nTrials = 1;
end;
hdr.label = {orig.label};
case 'combined_ds'
hdr = read_combined_ds(filename);
case {'ctf_ds', 'ctf_meg4', 'ctf_res4'}
% check the presence of the required low-level toolbox
ft_hastoolbox('ctf', 1);
orig = readCTFds(filename);
if isempty(orig)
% this is to deal with data from the 64 channel system and the error
% readCTFds: .meg4 file header=MEG4CPT Valid header options: MEG41CP MEG42CP
error('could not read CTF with this implementation, please try again with the ''ctf_old'' file format');
end
hdr.Fs = orig.res4.sample_rate;
hdr.nChans = orig.res4.no_channels;
hdr.nSamples = orig.res4.no_samples;
hdr.nSamplesPre = orig.res4.preTrigPts;
hdr.nTrials = orig.res4.no_trials;
hdr.label = cellstr(orig.res4.chanNames);
for i=1:numel(hdr.label)
% remove the site-specific numbers from each channel name, e.g. 'MZC01-1706' becomes 'MZC01'
hdr.label{i} = strtok(hdr.label{i}, '-');
end
% read the balance coefficients, these are used to compute the synthetic gradients
coeftype = cellstr(char(orig.res4.scrr(:).coefType));
try
[alphaMEG,MEGlist,Refindex] = getCTFBalanceCoefs(orig,'NONE', 'T');
orig.BalanceCoefs.none.alphaMEG = alphaMEG;
orig.BalanceCoefs.none.MEGlist = MEGlist;
orig.BalanceCoefs.none.Refindex = Refindex;
catch
warning('cannot read balancing coefficients for NONE');
end
if any(~cellfun(@isempty,strfind(coeftype, 'G1BR')))
try
[alphaMEG,MEGlist,Refindex] = getCTFBalanceCoefs(orig,'G1BR', 'T');
orig.BalanceCoefs.G1BR.alphaMEG = alphaMEG;
orig.BalanceCoefs.G1BR.MEGlist = MEGlist;
orig.BalanceCoefs.G1BR.Refindex = Refindex;
catch
warning('cannot read balancing coefficients for G1BR');
end
end
if any(~cellfun(@isempty,strfind(coeftype, 'G2BR')))
try
[alphaMEG,MEGlist,Refindex] = getCTFBalanceCoefs(orig, 'G2BR', 'T');
orig.BalanceCoefs.G2BR.alphaMEG = alphaMEG;
orig.BalanceCoefs.G2BR.MEGlist = MEGlist;
orig.BalanceCoefs.G2BR.Refindex = Refindex;
catch
warning('cannot read balancing coefficients for G2BR');
end
end
if any(~cellfun(@isempty,strfind(coeftype, 'G3BR')))
try
[alphaMEG,MEGlist,Refindex] = getCTFBalanceCoefs(orig, 'G3BR', 'T');
orig.BalanceCoefs.G3BR.alphaMEG = alphaMEG;
orig.BalanceCoefs.G3BR.MEGlist = MEGlist;
orig.BalanceCoefs.G3BR.Refindex = Refindex;
catch
warning('cannot read balancing coefficients for G3BR');
end
end
if any(~cellfun(@isempty,strfind(coeftype, 'G3AR')))
try
[alphaMEG,MEGlist,Refindex] = getCTFBalanceCoefs(orig, 'G3AR', 'T');
orig.BalanceCoefs.G3AR.alphaMEG = alphaMEG;
orig.BalanceCoefs.G3AR.MEGlist = MEGlist;
orig.BalanceCoefs.G3AR.Refindex = Refindex;
catch
% May not want a warning here if these are not commonly used.
% Already get a (fprintf) warning from getCTFBalanceCoefs.m
% warning('cannot read balancing coefficients for G3AR');
end
end
% add a gradiometer structure for forward and inverse modelling
try
hdr.grad = ctf2grad(orig, strcmp(coordsys, 'dewar'));
catch
% this fails if the res4 file is not correctly closed, e.g. during realtime processing
tmp = lasterror;
disp(tmp.message);
warning('could not construct gradiometer definition from the header');
end
% for realtime analysis EOF chasing the res4 does not correctly
% estimate the number of samples, so we compute it on the fly from the
% meg4 file sizes.
sz = 0;
files = dir([filename '/*.*meg4']);
for j=1:numel(files)
sz = sz + files(j).bytes;
end
hdr.nTrials = floor((sz - 8) / (hdr.nChans*4) / hdr.nSamples);
% add the original header details
hdr.orig = orig;
case {'ctf_old', 'read_ctf_res4'}
% read it using the open-source matlab code that originates from CTF and that was modified by the FCDC
orig = read_ctf_res4(headerfile);
hdr.Fs = orig.Fs;
hdr.nChans = orig.nChans;
hdr.nSamples = orig.nSamples;
hdr.nSamplesPre = orig.nSamplesPre;
hdr.nTrials = orig.nTrials;
hdr.label = orig.label;
% add a gradiometer structure for forward and inverse modelling
try
hdr.grad = ctf2grad(orig);
catch
% this fails if the res4 file is not correctly closed, e.g. during realtime processing
tmp = lasterror;
disp(tmp.message);
warning('could not construct gradiometer definition from the header');
end
% add the original header details
hdr.orig = orig;
case 'ctf_read_res4'
% check that the required low-level toolbos ix available
ft_hastoolbox('eegsf', 1);
% read it using the CTF importer from the NIH and Daren Weber
orig = ctf_read_res4(fileparts(headerfile), 0);
% convert the header into a structure that FieldTrip understands
hdr = [];
hdr.Fs = orig.setup.sample_rate;
hdr.nChans = length(orig.sensor.info);
hdr.nSamples = orig.setup.number_samples;
hdr.nSamplesPre = orig.setup.pretrigger_samples;
hdr.nTrials = orig.setup.number_trials;
for i=1:length(orig.sensor.info)
hdr.label{i} = orig.sensor.info(i).label;
end
hdr.label = hdr.label(:);
% add a gradiometer structure for forward and inverse modelling
try
hdr.grad = ctf2grad(orig);
catch
% this fails if the res4 file is not correctly closed, e.g. during realtime processing
tmp = lasterror;
disp(tmp.message);
warning('could not construct gradiometer definition from the header');
end
% add the original header details
hdr.orig = orig;
case 'ctf_shm'
% read the header information from shared memory
hdr = read_shm_header(filename);
case 'dataq_wdq'
orig = read_wdq_header(filename);
hdr = [];
hdr.Fs = orig.fsample;
hdr.nChans = orig.nchan;
hdr.nSamples = orig.nbytesdat/(2*hdr.nChans);
hdr.nSamplesPre = 0;
hdr.nTrials = 1;
for k = 1:hdr.nChans
if isfield(orig.chanhdr(k), 'annot') && ~isempty(orig.chanhdr(k).annot)
hdr.label{k,1} = orig.chanhdr(k).annot;
else
hdr.label{k,1} = orig.chanhdr(k).label;
end
end
% add the original header details
hdr.orig = orig;
case {'deymed_ini' 'deymed_dat'}
% the header is stored in a *.ini file
orig = read_deymed_ini(headerfile);
hdr = [];
hdr.Fs = orig.Fs;
hdr.nChans = orig.nChans;
hdr.nSamples = orig.nSamples;
hdr.nSamplesPre = 0;
hdr.nTrials = 1;
hdr.label = orig.label(:);
hdr.orig = orig; % remember the original details
case 'edf'
% this reader is largely similar to the bdf reader
hdr = read_edf(filename);
case 'eep_avr'
% check that the required low-level toolbox is available
ft_hastoolbox('eeprobe', 1);
% read the whole average and keep only header info (it is a bit silly, but the easiest to do here)
hdr = read_eep_avr(filename);
hdr.Fs = hdr.rate;
hdr.nChans = size(hdr.data,1);
hdr.nSamples = size(hdr.data,2);
hdr.nSamplesPre = hdr.xmin*hdr.rate/1000;
hdr.nTrials = 1; % it can always be interpreted as continuous data
% remove the data and variance if present
hdr = rmfield(hdr, 'data');
try, hdr = rmfield(hdr, 'variance'); end
case 'eeglab_set'
hdr = read_eeglabheader(filename);
case 'eeglab_erp'
hdr = read_erplabheader(filename);
case 'eyelink_asc'
asc = read_eyelink_asc(filename);
hdr.nChans = size(asc.dat,1);
hdr.nSamples = size(asc.dat,2);
hdr.nSamplesPre = 0;
hdr.nTrials = 1;
hdr.FirstTimeStamp = asc.dat(1,1);
hdr.TimeStampPerSample = mean(diff(asc.dat(1,:)));
hdr.Fs = 1000/hdr.TimeStampPerSample; % these timestamps are in miliseconds
% give this warning only once
warning_once('creating fake channel names');
for i=1:hdr.nChans
hdr.label{i} = sprintf('%d', i);
end
% remember the original header details
hdr.orig.header = asc.header;
% remember all header and data details upon request
if cache
hdr.orig = asc;
end
case 'spmeeg_mat'
hdr = read_spmeeg_header(filename);
case 'ced_spike6mat'
hdr = read_spike6mat_header(filename);
case 'eep_cnt'
% check that the required low-level toolbox is available
ft_hastoolbox('eeprobe', 1);
% read the first sample from the continous data, which will also return the header
hdr = read_eep_cnt(filename, 1, 1);
hdr.Fs = hdr.rate;
hdr.nSamples = hdr.nsample;
hdr.nSamplesPre = 0;
hdr.nChans = hdr.nchan;
hdr.nTrials = 1; % it can always be interpreted as continuous data
case 'egi_egia'
[fhdr,chdr,ename,cnames,fcom,ftext] = read_egis_header(filename);
[p, f, x] = fileparts(filename);
if any(chdr(:,4)-chdr(1,4))
error('Sample rate not the same for all cells.');
end;
hdr.Fs = chdr(1,4); %making assumption that sample rate is same for all cells
hdr.nChans = fhdr(19);
for i = 1:hdr.nChans
% this should be consistent with ft_senslabel
hdr.label{i,1} = ['E' num2str(i)];
end;
%since NetStation does not properly set the fhdr(11) field, use the number of subjects from the chdr instead
hdr.nTrials = chdr(1,2)*fhdr(18); %number of trials is numSubjects * numCells
hdr.nSamplesPre = ceil(fhdr(14)/(1000/hdr.Fs));
if any(chdr(:,3)-chdr(1,3))
error('Number of samples not the same for all cells.');
end;
hdr.nSamples = chdr(1,3); %making assumption that number of samples is same for all cells
% remember the original header details
hdr.orig.fhdr = fhdr;
hdr.orig.chdr = chdr;
hdr.orig.ename = ename;
hdr.orig.cnames = cnames;
hdr.orig.fcom = fcom;
hdr.orig.ftext = ftext;
case 'egi_egis'
[fhdr,chdr,ename,cnames,fcom,ftext] = read_egis_header(filename);
[p, f, x] = fileparts(filename);
if any(chdr(:,4)-chdr(1,4))
error('Sample rate not the same for all cells.');
end;
hdr.Fs = chdr(1,4); %making assumption that sample rate is same for all cells
hdr.nChans = fhdr(19);
for i = 1:hdr.nChans
% this should be consistent with ft_senslabel
hdr.label{i,1} = ['E' num2str(i)];
end;
hdr.nTrials = sum(chdr(:,2));
hdr.nSamplesPre = ceil(fhdr(14)/(1000/hdr.Fs));
% assuming that a utility was used to insert the correct baseline
% duration into the header since it is normally absent. This slot is
% actually allocated to the age of the subject, although NetStation
% does not use it when generating an EGIS session file.
if any(chdr(:,3)-chdr(1,3))
error('Number of samples not the same for all cells.');
end;
hdr.nSamples = chdr(1,3); %making assumption that number of samples is same for all cells
% remember the original header details
hdr.orig.fhdr = fhdr;
hdr.orig.chdr = chdr;
hdr.orig.ename = ename;
hdr.orig.cnames = cnames;
hdr.orig.fcom = fcom;
hdr.orig.ftext = ftext;
case 'egi_sbin'
% segmented type only
[header_array, CateNames, CatLengths, preBaseline] = read_sbin_header(filename);
[p, f, x] = fileparts(filename);
hdr.Fs = header_array(9);
hdr.nChans = header_array(10);
for i = 1:hdr.nChans
% this should be consistent with ft_senslabel
hdr.label{i,1} = ['E' num2str(i)];
end;
hdr.nTrials = header_array(15);
hdr.nSamplesPre = preBaseline;
hdr.nSamples = header_array(16); % making assumption that number of samples is same for all cells
% remember the original header details
hdr.orig.header_array = header_array;
hdr.orig.CateNames = CateNames;
hdr.orig.CatLengths = CatLengths;
case {'egi_mff_v1' 'egi_mff'} % this is currently the default
% The following represents the code that was written by Ingrid, Robert
% and Giovanni to get started with the EGI mff dataset format. It might
% not support all details of the file formats.
% An alternative implementation has been provided by EGI, this is
% released as fieldtrip/external/egi_mff and referred further down in
% this function as 'egi_mff_v2'.
if ~usejava('jvm')
error('the xml2struct requires MATLAB to be running with the Java virtual machine (JVM)');
% an alternative implementation which does not require the JVM but runs much slower is
% available from http://www.mathworks.com/matlabcentral/fileexchange/6268-xml4mat-v2-0
end
% get header info from .bin files
binfiles = dir(fullfile(filename, 'signal*.bin'));
if isempty(binfiles)
error('could not find any signal.bin in mff directory')
end
orig = [];
for iSig = 1:length(binfiles)
signalname = binfiles(iSig).name;
fullsignalname = fullfile(filename, signalname);
orig.signal(iSig).blockhdr = read_mff_bin(fullsignalname);
end
% get hdr info from xml files
warning('off', 'MATLAB:REGEXP:deprecated') % due to some small code xml2struct
xmlfiles = dir( fullfile(filename, '*.xml'));
disp('reading xml files to obtain header info...')
for i = 1:numel(xmlfiles)
if strcmpi(xmlfiles(i).name(1:2), '._') % Mac sometimes creates this useless files, don't use them
elseif strcmpi(xmlfiles(i).name(1:6), 'Events') % don't read in events here, can take a lot of time, and we can do that in ft_read_event
else
fieldname = xmlfiles(i).name(1:end-4);
filename_xml = fullfile(filename, xmlfiles(i).name);
orig.xml.(fieldname) = xml2struct(filename_xml);
end
end
warning('on', 'MATLAB:REGEXP:deprecated')
%make hdr according to FieldTrip rules
hdr = [];
Fs = zeros(length(orig.signal),1);
nChans = zeros(length(orig.signal),1);
nSamples = zeros(length(orig.signal),1);
for iSig = 1:length(orig.signal)
Fs(iSig) = orig.signal(iSig).blockhdr(1).fsample(1);
nChans(iSig) = orig.signal(iSig).blockhdr(1).nsignals;
% the number of samples per block can be different
nSamples_Block = zeros(length(orig.signal(iSig).blockhdr),1);
for iBlock = 1:length(orig.signal(iSig).blockhdr)
nSamples_Block(iBlock) = orig.signal(iSig).blockhdr(iBlock).nsamples(1);
end
nSamples(iSig) = sum(nSamples_Block);
end
if length(unique(Fs)) > 1 || length(unique(nSamples)) > 1
error('Fs and nSamples should be the same in all signals')
end
hdr.Fs = Fs(1);
hdr.nChans = sum(nChans);
hdr.nSamplesPre = 0;
hdr.nSamples = nSamples(1);
hdr.nTrials = 1;
%-get channel labels for signal 1 (main net), otherwise create them
if isfield(orig.xml, 'sensorLayout') % asuming that signal1 is hdEEG sensornet, and channels are in xml file sensorLayout
for iSens = 1:numel(orig.xml.sensorLayout.sensors)
if ~isempty(orig.xml.sensorLayout.sensors(iSens).sensor.name) && ~(isstruct(orig.xml.sensorLayout.sensors(iSens).sensor.name) && numel(fieldnames(orig.xml.sensorLayout.sensors(iSens).sensor.name))==0)
%only get name when channel is EEG (type 0), or REF (type 1),
%rest are non interesting channels like place holders and COM and should not be added.
if strcmp(orig.xml.sensorLayout.sensors(iSens).sensor.type, '0') || strcmp(orig.xml.sensorLayout.sensors(iSens).sensor.type, '1')
% get the sensor name from the datafile
hdr.label{iSens} = orig.xml.sensorLayout.sensors(iSens).sensor.name;
end
elseif strcmp(orig.xml.sensorLayout.sensors(iSens).sensor.type, '0') % EEG chan
% this should be consistent with ft_senslabel
hdr.label{iSens} = ['E' num2str(orig.xml.sensorLayout.sensors(iSens).sensor.number)];
elseif strcmp(orig.xml.sensorLayout.sensors(iSens).sensor.type, '1') % REF chan
% ingnie: I now choose REF as name for REF channel since our discussion see bug 1407. Arbitrary choice...
hdr.label{iSens} = ['REF' num2str(iSens)];
else
% non interesting channels like place holders and COM
end
end
%check if the amount of lables corresponds with nChannels in signal 1
if length(hdr.label) == nChans(1)
%good
elseif length(hdr.label) > orig.signal(1).blockhdr(1).nsignals
warning('found more lables in xml.sensorLayout than channels in signal 1, thus can not use info in sensorLayout, creating labels on the fly')
for iSens = 1:orig.signal(1).blockhdr(1).nsignals
% this should be consistent with ft_senslabel
hdr.label{iSens} = ['E' num2str(iSens)];
end
else warning('found less lables in xml.sensorLayout than channels in signal 1, thus can not use info in sensorLayout, creating labels on the fly')
for iSens = 1:orig.signal(1).blockhdr(1).nsignals
% this should be consistent with ft_senslabel
hdr.label{iSens} = ['E' num2str(iSens)];
end
end
% get lables for other signals
if length(orig.signal) == 2
if isfield(orig.xml, 'pnsSet') % signal2 is PIB box, and lables are in xml file pnsSet
nbEEGchan = length(hdr.label);
for iSens = 1:numel(orig.xml.pnsSet.sensors)
hdr.label{nbEEGchan+iSens} = num2str(orig.xml.pnsSet.sensors(iSens).sensor.name);
end
if length(hdr.label) == orig.signal(2).blockhdr(1).nsignals + orig.signal(2).blockhdr(1).nsignals
% good
elseif length(hdr.label) < orig.signal(1).blockhdr(1).nsignals + orig.signal(2).blockhdr(1).nsignals
warning('found less lables in xml.pnsSet than channels in signal 2, labeling with s2_unknownN instead')
for iSens = length(hdr.label)+1 : orig.signal(1).blockhdr(1).nsignals + orig.signal(2).blockhdr(1).nsignals
hdr.label{iSens} = ['s2_unknown', num2str(iSens)];
end
else warning('found more lables in xml.pnsSet than channels in signal 2, thus can not use info in pnsSet, and labeling with s2_eN instead')
for iSens = orig.signal(1).blockhdr(1).nsignals+1 : orig.signal(1).blockhdr(1).nsignals + orig.signal(2).blockhdr(1).nsignals
hdr.label{iSens} = ['s2_E', num2str(iSens)];
end
end
else % signal2 is not PIBbox
warning('creating channel labels for signal 2 on the fly')
for iSens = 1:orig.signal(2).blockhdr(1).nsignals
hdr.label{end+1} = ['s2_E', num2str(iSens)];
end
end
elseif length(orig.signal) > 2
% loop over signals and label channels accordingly
warning('creating channel labels for signal 2 to signal N on the fly')
for iSig = 2:length(orig.signal)
for iSens = 1:orig.signal(iSig).blockhdr(1).nsignals
if iSig == 1 && iSens == 1
hdr.label{1} = ['s',num2str(iSig),'_E', num2str(iSens)];
else
hdr.label{end+1} = ['s',num2str(iSig),'_E', num2str(iSens)];
end
end
end
end
else % no xml.sensorLayout present
warning('no sensorLayout found in xml files, creating channel labels on the fly')
for iSig = 1:length(orig.signal)
for iSens = 1:orig.signal(iSig).blockhdr(1).nsignals
if iSig == 1 && iSens == 1
hdr.label{1} = ['s',num2str(iSig),'_E', num2str(iSens)];
else
hdr.label{end+1} = ['s',num2str(iSig),'_E', num2str(iSens)];
end
end
end
end
% check if multiple epochs are present
if isfield(orig.xml,'epoch') && length(orig.xml.epoch) > 1
% add info to header about which sample correspond to which epochs, becasue this is quite hard for user to get...
epochdef = zeros(length(orig.xml.epoch),3);
for iEpoch = 1:length(orig.xml.epoch)
if iEpoch == 1
epochdef(iEpoch,1) = round(str2double(orig.xml.epoch(iEpoch).epoch.beginTime)./1000./hdr.Fs)+1;
epochdef(iEpoch,2) = round(str2double(orig.xml.epoch(iEpoch).epoch.endTime)./1000./hdr.Fs);
epochdef(iEpoch,3) = round(str2double(orig.xml.epoch(iEpoch).epoch.beginTime)./1000./hdr.Fs); %offset corresponds to timing
else
NbSampEpoch = round(str2double(orig.xml.epoch(iEpoch).epoch.endTime)./1000./hdr.Fs - str2double(orig.xml.epoch(iEpoch).epoch.beginTime)./1000./hdr.Fs);
epochdef(iEpoch,1) = epochdef(iEpoch-1,2) + 1;
epochdef(iEpoch,2) = epochdef(iEpoch-1,2) + NbSampEpoch;
epochdef(iEpoch,3) = round(str2double(orig.xml.epoch(iEpoch).epoch.beginTime)./1000./hdr.Fs); %offset corresponds to timing
end
end
warning('the data contains multiple epochs with possibly discontinuous boundaries. Added ''epochdef'' to hdr.orig defining begin and end sample of each epoch. See hdr.orig.xml.epoch for epoch details, use ft_read_header to obtain header or look in data.dhr.')
% sanity check
if epochdef(end,2) ~= hdr.nSamples
error('number of samples in all epochs do not add up to total number of samples')
end
orig.epochdef = epochdef;
end
hdr.orig = orig;
case 'egi_mff_v2'
% ensure that the EGI_MFF toolbox is on the path
ft_hastoolbox('egi_mff', 1);
% ensure that the JVM is running and the jar file is on the path
mff_setup;
if isunix && filename(1)~=filesep
% add the full path to the dataset directory
filename = fullfile(pwd, filename);
else
% FIXME I don't know how this is supposed to work on Windows computers
% with the drive letter in front of the path
end
hdr = read_mff_header(filename);
case 'fcdc_buffer'
% read from a networked buffer for realtime analysis
[host, port] = filetype_check_uri(filename);
if retry
orig = [];
while isempty(orig)
try
% try reading the header, catch the error and retry
orig = buffer('get_hdr', [], host, port);
catch
warning('could not read header from %s, retrying in 1 second', filename);
pause(1);
end
end % while
else
% try reading the header only once, give error if it fails
orig = buffer('get_hdr', [], host, port);
end % if retry
hdr.Fs = orig.fsample;
hdr.nChans = orig.nchans;
hdr.nSamples = orig.nsamples;
hdr.nSamplesPre = 0; % since continuous
hdr.nTrials = 1; % since continuous
hdr.orig = []; % this will contain the chunks (if present)
% add the contents of attached RES4 chunk after decoding to Matlab structure
if isfield(orig, 'ctf_res4')
if isempty(cachechunk)
% this only needs to be decoded once
cachechunk = decode_res4(orig.ctf_res4);
end
% copy the gradiometer details
hdr.grad = cachechunk.grad;
hdr.orig = cachechunk.orig;
if isfield(orig, 'channel_names')
% get the same selection of channels from the two chunks
[selbuf, selres4] = match_str(orig.channel_names, cachechunk.label);
if length(selres4)<length(orig.channel_names)
error('the res4 chunk did not contain all channels')
end
% copy some of the channel details
hdr.label = cachechunk.label(selres4);
hdr.chantype = cachechunk.chantype(selres4);
hdr.chanunit = cachechunk.chanunit(selres4);
% add the channel names chunk as well
hdr.orig.channel_names = orig.channel_names;
end
% add the raw chunk as well
hdr.orig.ctf_res4 = orig.ctf_res4;
end
% add the contents of attached NIFTI-1 chunk after decoding to Matlab structure
if isfield(orig, 'nifti_1')
hdr.nifti_1 = decode_nifti1(orig.nifti_1);
% add the raw chunk as well
hdr.orig.nifti_1 = orig.nifti_1;
end
% add the contents of attached SiemensAP chunk after decoding to Matlab structure
if isfield(orig, 'siemensap') && exist('sap2matlab')==3 % only run this if MEX file is present
hdr.siemensap = sap2matlab(orig.siemensap);
% add the raw chunk as well
hdr.orig.siemensap = orig.siemensap;
end
if ~isfield(hdr, 'label')
% prevent overwriting the labels that we might have gotten from a RES4 chunk
if isfield(orig, 'channel_names')
hdr.label = orig.channel_names;
else
hdr.label = cell(hdr.nChans,1);
if hdr.nChans < 2000 % don't do this for fMRI etc.
warning_once('creating fake channel names'); % give this warning only once
for i=1:hdr.nChans
hdr.label{i} = sprintf('%d', i);
end
else
warning_once('skipping fake channel names'); % give this warning only once
checkUniqueLabels = false;
end
end
end
hdr.orig.bufsize = orig.bufsize;
case 'fcdc_buffer_offline'
[hdr, nameFlag] = read_buffer_offline_header(headerfile);
switch nameFlag
case 0
% no labels generated (fMRI etc)
checkUniqueLabels = false; % no need to check these
case 1
% has generated fake channels
% give this warning only once
warning_once('creating fake channel names');
checkUniqueLabels = false; % no need to check these
case 2
% got labels from chunk, check those
checkUniqueLabels = true;
end
case 'fcdc_matbin'
% this is multiplexed data in a *.bin file, accompanied by a matlab file containing the header
load(headerfile, 'hdr');
case 'fcdc_mysql'
% check that the required low-level toolbox is available
ft_hastoolbox('mysql', 1);
% read from a MySQL server listening somewhere else on the network
db_open(filename);
if db_blob
hdr = db_select_blob('fieldtrip.header', 'msg', 1);
else
hdr = db_select('fieldtrip.header', {'nChans', 'nSamples', 'nSamplesPre', 'Fs', 'label'}, 1);
hdr.label = mxDeserialize(hdr.label);
end
case 'gtec_mat'
% this is a simple MATLAB format, it contains a log and a names variable
tmp = load(headerfile);
log = tmp.log;
names = tmp.names;
hdr.label = cellstr(names);
hdr.nChans = size(log,1);
hdr.nSamples = size(log,2);
hdr.nSamplesPre = 0;
hdr.nTrials = 1; % assume continuous data, not epoched
% compute the sampling frequency from the time channel
sel = strcmp(hdr.label, 'Time');
time = log(sel,:);
hdr.Fs = 1./(time(2)-time(1));
% also remember the complete data upon request
if cache
hdr.orig.log = log;
hdr.orig.names = names;
end
case {'itab_raw' 'itab_mhd'}
% read the full header information frtom the binary header structure
header_info = read_itab_mhd(headerfile);
% these are the channels that are visible to fieldtrip
chansel = 1:header_info.nchan;
% convert the header information into a fieldtrip compatible format
hdr.nChans = length(chansel);
hdr.label = {header_info.ch(chansel).label};
hdr.label = hdr.label(:); % should be column vector
hdr.Fs = header_info.smpfq;
% it will always be continuous data
hdr.nSamples = header_info.ntpdata;
hdr.nSamplesPre = 0; % it is a single continuous trial
hdr.nTrials = 1; % it is a single continuous trial
% keep the original details AND the list of channels as used by fieldtrip
hdr.orig = header_info;
hdr.orig.chansel = chansel;
% add the gradiometer definition
hdr.grad = itab2grad(header_info);
case 'micromed_trc'
orig = read_micromed_trc(filename);
hdr = [];
hdr.Fs = orig.Rate_Min; % FIXME is this correct?
hdr.nChans = orig.Num_Chan;
hdr.nSamples = orig.Num_Samples;
hdr.nSamplesPre = 0; % continuous
hdr.nTrials = 1; % continuous
hdr.label = cell(1,hdr.nChans);
% give this warning only once
warning('creating fake channel names');
for i=1:hdr.nChans
hdr.label{i} = sprintf('%d', i);
end
% this should be a column vector
hdr.label = hdr.label(:);
% remember the original header details
hdr.orig = orig;
case {'mpi_ds', 'mpi_dap'}
hdr = read_mpi_ds(filename);
case 'netmeg'
ft_hastoolbox('netcdf', 1);
% this will read all NetCDF data from the file and subsequently convert
% each of the three elements into a more easy to parse MATLAB structure
s = netcdf(filename);
for i=1:numel(s.AttArray)
fname = fixname(s.AttArray(i).Str);
fval = s.AttArray(i).Val;
if ischar(fval)
fval = fval(fval~=0); % remove the \0 characters
fval = strtrim(fval); % remove insignificant whitespace
end
Att.(fname) = fval;
end
for i=1:numel(s.VarArray)
fname = fixname(s.VarArray(i).Str);
fval = s.VarArray(i).Data;
if ischar(fval)
fval = fval(fval~=0); % remove the \0 characters
fval = strtrim(fval); % remove insignificant whitespace
end
Var.(fname) = fval;
end
for i=1:numel(s.DimArray)
fname = fixname(s.DimArray(i).Str);
fval = s.DimArray(i).Dim;
if ischar(fval)
fval = fval(fval~=0); % remove the \0 characters
fval = strtrim(fval); % remove insignificant whitespace
end
Dim.(fname) = fval;
end
% convert the relevant fields into teh default header structure
hdr.Fs = 1000/Var.samplinginterval;
hdr.nChans = length(Var.channelstatus);
hdr.nSamples = Var.numsamples;
hdr.nSamplesPre = 0;
hdr.nTrials = size(Var.waveforms, 1);
hdr.chanunit = cellstr(reshape(Var.channelunits, hdr.nChans, 2));
hdr.chantype = cellstr(reshape(lower(Var.channeltypes), hdr.nChans, 3));
warning_once('creating fake channel names');
hdr.label = cell(hdr.nChans, 1);
for i=1:hdr.nChans
hdr.label{i} = sprintf('%d', i);
end
% remember the original details of the file
% note that this also includes the data
% this is large, but can be reused elsewhere
hdr.orig.Att = Att;
hdr.orig.Var = Var;
hdr.orig.Dim = Dim;
% construct the gradiometer structure from the complete header information
hdr.grad = netmeg2grad(hdr);
case 'neuralynx_dma'
hdr = read_neuralynx_dma(filename);
case 'neuralynx_sdma'
hdr = read_neuralynx_sdma(filename);
case 'neuralynx_ncs'
ncs = read_neuralynx_ncs(filename, 1, 0);
[p, f, x] = fileparts(filename);
hdr.Fs = ncs.hdr.SamplingFrequency;
hdr.label = {f};
hdr.nChans = 1;
hdr.nTrials = 1;
hdr.nSamplesPre = 0;
hdr.nSamples = ncs.NRecords * 512;
hdr.orig = ncs.hdr;
FirstTimeStamp = ncs.hdr.FirstTimeStamp; % this is the first timestamp of the first block
LastTimeStamp = ncs.hdr.LastTimeStamp; % this is the first timestamp of the last block, i.e. not the timestamp of the last sample
hdr.TimeStampPerSample = double(LastTimeStamp - FirstTimeStamp) ./ ((ncs.NRecords-1)*512);
hdr.FirstTimeStamp = FirstTimeStamp;
case 'neuralynx_nse'
nse = read_neuralynx_nse(filename, 1, 0);
[p, f, x] = fileparts(filename);
hdr.Fs = nse.hdr.SamplingFrequency;
hdr.label = {f};
hdr.nChans = 1;
hdr.nTrials = nse.NRecords; % each record contains one waveform
hdr.nSamples = 32; % there are 32 samples in each waveform
hdr.nSamplesPre = 0;
hdr.orig = nse.hdr;
% FIXME add hdr.FirstTimeStamp and hdr.TimeStampPerSample
case {'neuralynx_ttl', 'neuralynx_tsl', 'neuralynx_tsh'}
% these are hardcoded, they contain an 8-byte header and int32 values for a single channel
% FIXME this should be done similar as neuralynx_bin, i.e. move the hdr into the function
hdr = [];
hdr.Fs = 32556;
hdr.nChans = 1;
hdr.nSamples = (filesize(filename)-8)/4;
hdr.nSamplesPre = 1;
hdr.nTrials = 1;
hdr.label = {headerformat((end-3):end)};
case 'neuralynx_bin'
hdr = read_neuralynx_bin(filename);
case 'neuralynx_ds'
hdr = read_neuralynx_ds(filename);
case 'neuralynx_cds'
hdr = read_neuralynx_cds(filename);
case 'nexstim_nxe'
hdr = read_nexstim_nxe(filename);
case {'neuromag_fif' 'neuromag_mne' 'babysquid_fif'}
% check that the required low-level toolbox is available
ft_hastoolbox('mne', 1);
orig = fiff_read_meas_info(filename);
% convert to fieldtrip format header
hdr.label = orig.ch_names(:);
hdr.nChans = orig.nchan;
hdr.Fs = orig.sfreq;
% add a gradiometer structure for forward and inverse modelling
try
[hdr.grad, elec] = mne2grad(orig);
if ~isempty(elec)
hdr.elec = elec;
end
catch
disp(lasterr);
end
iscontinuous = 0;
isaverage = 0;
isepoched = 0; % FIXME don't know how to determine this, or whether epoched .fif data exists!
if isempty(fiff_find_evoked(filename)) % true if file contains no evoked responses
iscontinuous = 1;
else
isaverage = 1;
end
if iscontinuous
try
% we only use 1 input argument here to allow backward
% compatibility up to MNE 2.6.x:
raw = fiff_setup_read_raw(filename);
catch
% the "catch me" syntax is broken on MATLAB74, this fixes it
me = lasterror;
% there is an error - we try to use MNE 2.7.x (if present) to
% determine if the cause is maxshielding:
try
allow_maxshield = true;
raw = fiff_setup_read_raw(filename,allow_maxshield);
catch
%unknown problem, or MNE version 2.6.x or less:
rethrow(me);
end
% no error message from fiff_setup_read_raw? Then maxshield
% was applied, but maxfilter wasn't, so return this error:
error(['Maxshield data has not had maxfilter applied to it - cannot be read by fieldtrip. ' ...
'Apply Neuromag maxfilter before converting to fieldtrip format.']);
end
hdr.nSamples = raw.last_samp - raw.first_samp + 1; % number of samples per trial
hdr.nSamplesPre = 0;
% otherwise conflicts will occur in read_data
hdr.nTrials = 1;
orig.raw = raw; % keep all the details
elseif isaverage
evoked_data = fiff_read_evoked_all(filename);
vartriallength = any(diff([evoked_data.evoked.first])) || any(diff([evoked_data.evoked.last]));
if vartriallength
% there are trials averages with variable durations in the file
warning('EVOKED FILE with VARIABLE TRIAL LENGTH! - check data have been processed accurately');
hdr.nSamples = 0;
for i=1:length(evoked_data.evoked)
hdr.nSamples = hdr.nSamples + size(evoked_data.evoked(i).epochs, 2);
end
% represent it as a continuous file with a single trial
% all trial average details will be available through read_event
hdr.nSamplesPre = 0;
hdr.nTrials = 1;
orig.evoked = evoked_data.evoked; % this is used by read_data to get the actual data, i.e. to prevent re-reading
orig.info = evoked_data.info; % keep all the details
orig.vartriallength = 1;
else
% represent it as a file with multiple trials, each trial has the same length
% all trial average details will be available through read_event
hdr.nSamples = evoked_data.evoked(1).last - evoked_data.evoked(1).first + 1;
hdr.nSamplesPre = -evoked_data.evoked(1).first; % represented as negative number in fif file
hdr.nTrials = length(evoked_data.evoked);
orig.evoked = evoked_data.evoked; % this is used by read_data to get the actual data, i.e. to prevent re-reading
orig.info = evoked_data.info; % keep all the details
orig.vartriallength = 0;
end
elseif isepoched
error('Support for epoched *.fif data is not yet implemented.')
end
% remember the original header details
hdr.orig = orig;
% these are useful to know in read_event
hdr.orig.isaverage = isaverage;
hdr.orig.iscontinuous = iscontinuous;
hdr.orig.isepoched = isepoched;
case 'neuromag_mex'
% check that the required low-level toolbox is available
ft_hastoolbox('meg-pd', 1);
rawdata('any',filename);
rawdata('goto', 0);
megmodel('head',[0 0 0],filename);
% get the available information from the fif file
[orig.rawdata.range,orig.rawdata.calib] = rawdata('range');
[orig.rawdata.sf] = rawdata('sf');
[orig.rawdata.samples] = rawdata('samples');
[orig.chaninfo.N,orig.chaninfo.S,orig.chaninfo.T] = chaninfo; % Numbers, names & places
[orig.chaninfo.TY,orig.chaninfo.NA] = chaninfo('type'); % Coil type
[orig.chaninfo.NO] = chaninfo('noise'); % Default noise level
[orig.channames.NA,orig.channames.KI,orig.channames.NU] = channames(filename); % names, kind, logical numbers
% read a single trial to determine the data size
[buf, status] = rawdata('next');
rawdata('close');
% This is to solve a problem reported by Doug Davidson: The problem
% is that rawdata('samples') is not returning the number of samples
% correctly. It appears that the example script rawchannels in meg-pd
% might work, however, so I want to use rawchannels to read in one
% channel of data in order to get the number of samples in the file:
if orig.rawdata.samples<0
tmpchannel = 1;
tmpvar = rawchannels(filename,tmpchannel);
[orig.rawdata.samples] = size(tmpvar,2);
clear tmpvar tmpchannel;
end
% convert to fieldtrip format header
hdr.label = orig.channames.NA;
hdr.Fs = orig.rawdata.sf;
hdr.nSamplesPre = 0; % I don't know how to get this out of the file
hdr.nChans = size(buf,1);
hdr.nSamples = size(buf,2); % number of samples per trial
hdr.nTrials = orig.rawdata.samples ./ hdr.nSamples;
% add a gradiometer structure for forward and inverse modelling
hdr.grad = fif2grad(filename);
% remember the original header details
hdr.orig = orig;
case 'neuroprax_eeg'
orig = np_readfileinfo(filename);
hdr.Fs = orig.fa;
hdr.nChans = orig.K;
hdr.nSamples = orig.N;
hdr.nSamplesPre = 0; % continuous
hdr.nTrials = 1; % continuous
hdr.label = orig.channels(:);
hdr.unit = orig.units(:);
% remember the original header details
hdr.orig = orig;
case 'neurosim_evolution'
hdr = read_neurosim_evolution(filename);
case {'neurosim_ds' 'neurosim_signals'}
hdr = read_neurosim_signals(filename);
case 'neurosim_spikes'
headerOnly=true;
hdr= read_neurosim_spikes(filename,headerOnly);
case 'nimh_cortex'
cortex = read_nimh_cortex(filename, 'epp', 'no', 'eog', 'no');
% look at the first trial to determine whether it contains data in the EPP and EOG channels
trial1 = read_nimh_cortex(filename, 'epp', 'yes', 'eog', 'yes', 'begtrial', 1, 'endtrial', 1);
hasepp = ~isempty(trial1.epp);
haseog = ~isempty(trial1.eog);
if hasepp
warning('EPP channels are not yet supported');
end
% at the moment only the EOG channels are supported here
if haseog
hdr.label = {'EOGx' 'EOGy'};
hdr.nChans = 2;
else
hdr.label = {};
hdr.nChans = 0;
end
hdr.nTrials = length(cortex);
hdr.nSamples = inf;
hdr.nSamplesPre = 0;
hdr.orig.trial = cortex;
hdr.orig.hasepp = hasepp;
hdr.orig.haseog = haseog;
case 'ns_avg'
orig = read_ns_hdr(filename);
% do some reformatting/renaming of the header items
hdr.Fs = orig.rate;
hdr.nSamples = orig.npnt;
hdr.nSamplesPre = round(-orig.rate*orig.xmin/1000);
hdr.nChans = orig.nchan;
hdr.label = orig.label(:);
hdr.nTrials = 1; % the number of trials in this datafile is only one, i.e. the average
% remember the original header details
hdr.orig = orig;
case {'ns_cnt' 'ns_cnt16', 'ns_cnt32'}
if strcmp(headerformat, 'ns_cnt')
orig = loadcnt(filename);
elseif strcmp(headerformat, 'ns_cnt16')
orig = loadcnt(filename, 'dataformat', 'int16');
elseif strcmp(headerformat, 'ns_cnt32')
orig = loadcnt(filename, 'dataformat', 'int32');
end
orig = rmfield(orig, {'data', 'ldnsamples'});
% do some reformatting/renaming of the header items
hdr.Fs = orig.header.rate;
hdr.nChans = orig.header.nchannels;
hdr.nSamples = orig.header.nums;
hdr.nSamplesPre = 0;
hdr.nTrials = 1;
for i=1:hdr.nChans
hdr.label{i} = deblank(orig.electloc(i).lab);
end
% remember the original header details
hdr.orig = orig;
case 'ns_eeg'
orig = read_ns_hdr(filename);
% do some reformatting/renaming of the header items
hdr.label = orig.label;
hdr.Fs = orig.rate;
hdr.nSamples = orig.npnt;
hdr.nSamplesPre = round(-orig.rate*orig.xmin/1000);
hdr.nChans = orig.nchan;
hdr.nTrials = orig.nsweeps;
% remember the original header details
hdr.orig = orig;
case 'plexon_ds'
hdr = read_plexon_ds(filename);
case 'plexon_ddt'
orig = read_plexon_ddt(filename);
hdr.nChans = orig.NChannels;
hdr.Fs = orig.Freq;
hdr.nSamples = orig.NSamples;
hdr.nSamplesPre = 0; % continuous
hdr.nTrials = 1; % continuous
hdr.label = cell(1,hdr.nChans);
% give this warning only once
warning('creating fake channel names');
for i=1:hdr.nChans
hdr.label{i} = sprintf('%d', i);
end
% also remember the original header
hdr.orig = orig;
case {'read_nex_data'} % this is an alternative reader for nex files
orig = read_nex_header(filename);
% assign the obligatory items to the output FCDC header
numsmp = cell2mat({orig.varheader.numsmp});
adindx = find(cell2mat({orig.varheader.typ})==5);
if isempty(adindx)
error('file does not contain continuous channels');
end
hdr.nChans = length(orig.varheader);
hdr.Fs = orig.varheader(adindx(1)).wfrequency; % take the sampling frequency from the first A/D channel
hdr.nSamples = max(numsmp(adindx)); % take the number of samples from the longest A/D channel
hdr.nTrials = 1; % it can always be interpreted as continuous data
hdr.nSamplesPre = 0; % and therefore it is not trial based
for i=1:hdr.nChans
hdr.label{i} = deblank(char(orig.varheader(i).nam));
end
hdr.label = hdr.label(:);
% also remember the original header details
hdr.orig = orig;
case {'read_plexon_nex' 'plexon_nex'} % this is the default reader for nex files
orig = read_plexon_nex(filename);
numsmp = cell2mat({orig.VarHeader.NPointsWave});
adindx = find(cell2mat({orig.VarHeader.Type})==5);
if isempty(adindx)
error('file does not contain continuous channels');
end
hdr.nChans = length(orig.VarHeader);
hdr.Fs = orig.VarHeader(adindx(1)).WFrequency; % take the sampling frequency from the first A/D channel
hdr.nSamples = max(numsmp(adindx)); % take the number of samples from the longest A/D channel
hdr.nTrials = 1; % it can always be interpreted as continuous data
hdr.nSamplesPre = 0; % and therefore it is not trial based
for i=1:hdr.nChans
hdr.label{i} = deblank(char(orig.VarHeader(i).Name));
end
hdr.label = hdr.label(:);
hdr.FirstTimeStamp = orig.FileHeader.Beg;
hdr.TimeStampPerSample = orig.FileHeader.Frequency ./ hdr.Fs;
% also remember the original header details
hdr.orig = orig;
case 'plexon_plx'
orig = read_plexon_plx(filename);
if orig.NumSlowChannels==0
error('file does not contain continuous channels');
end
fsample = [orig.SlowChannelHeader.ADFreq];
if any(fsample~=fsample(1))
error('different sampling rates in continuous data not supported');
end
for i=1:length(orig.SlowChannelHeader)
label{i} = deblank(orig.SlowChannelHeader(i).Name);
end
% continuous channels don't always contain data, remove the empty ones
sel = [orig.DataBlockHeader.Type]==5; % continuous
chan = [orig.DataBlockHeader.Channel];
for i=1:length(label)
chansel(i) = any(chan(sel)==orig.SlowChannelHeader(i).Channel);
end
chansel = find(chansel); % this is required for timestamp selection
label = label(chansel);
% only the continuous channels are returned as visible
hdr.nChans = length(label);
hdr.Fs = fsample(1);
hdr.label = label;
% also remember the original header
hdr.orig = orig;
% select the first continuous channel that has data
sel = ([orig.DataBlockHeader.Type]==5 & [orig.DataBlockHeader.Channel]==orig.SlowChannelHeader(chansel(1)).Channel);
% get the timestamps that correspond with the continuous data
tsl = [orig.DataBlockHeader(sel).TimeStamp]';
tsh = [orig.DataBlockHeader(sel).UpperByteOf5ByteTimestamp]';
ts = timestamp_plexon(tsl, tsh); % use helper function, this returns an uint64 array
% determine the number of samples in the continuous channels
num = [orig.DataBlockHeader(sel).NumberOfWordsInWaveform];
hdr.nSamples = sum(num);
hdr.nSamplesPre = 0; % continuous
hdr.nTrials = 1; % continuous
% the timestamps indicate the beginning of each block, hence the timestamp of the last block corresponds with the end of the previous block
hdr.TimeStampPerSample = double(ts(end)-ts(1))/sum(num(1:(end-1)));
hdr.FirstTimeStamp = ts(1); % the timestamp of the first continuous sample
% also make the spike channels visible
for i=1:length(orig.ChannelHeader)
hdr.label{end+1} = deblank(orig.ChannelHeader(i).Name);
end
hdr.label = hdr.label(:);
hdr.nChans = length(hdr.label);
case {'tdt_tsq', 'tdt_tev'}
% FIXME the code below is not yet functional, it requires more input from the ESI in Frankfurt
% tsq = read_tdt_tsq(headerfile);
% k = 0;
% chan = unique([tsq.channel]);
% % loop over the physical channels
% for i=1:length(chan)
% chansel = [tsq.channel]==chan(i);
% code = unique({tsq(chansel).code});
% % loop over the logical channels
% for j=1:length(code)
% codesel = false(size(tsq));
% for k=1:numel(codesel)
% codesel(k) = identical(tsq(k).code, code{j});
% end
% % find the first instance of this logical channel
% this = find(chansel(:) & codesel(:), 1);
% % add it to the list of channels
% k = k + 1;
% frequency(k) = tsq(this).frequency;
% label{k} = [char(typecast(tsq(this).code, 'uint8')) num2str(tsq(this).channel)];
% tsqorig(k) = tsq(this);
% end
% end
error('not yet implemented');
case {'yokogawa_ave', 'yokogawa_con', 'yokogawa_raw', 'yokogawa_mrk'}
% header can be read with two toolboxes: Yokogawa MEG Reader and Yokogawa MEG160 (old inofficial toolbox)
% newest toolbox takes precedence.
if ft_hastoolbox('yokogawa_meg_reader', 3); % stay silent if it cannot be added
hdr = read_yokogawa_header_new(filename);
% add a gradiometer structure for forward and inverse modelling
hdr.grad = yokogawa2grad_new(hdr);
else
ft_hastoolbox('yokogawa', 1); % try it with the old version of the toolbox
hdr = read_yokogawa_header(filename);
% add a gradiometer structure for forward and inverse modelling
hdr.grad = yokogawa2grad(hdr);
end
case 'nmc_archive_k'
hdr = read_nmc_archive_k_hdr(filename);
case 'neuroshare' % NOTE: still under development
% check that the required neuroshare toolbox is available
ft_hastoolbox('neuroshare', 1);
tmp = read_neuroshare(filename);
hdr.Fs = tmp.hdr.analoginfo(end).SampleRate; % take the sampling freq from the last analog channel (assuming this is the same for all chans)
hdr.nChans = length(tmp.list.analog(tmp.analog.contcount~=0)); % get the analog channels, only the ones that are not empty
hdr.nSamples = max([tmp.hdr.entityinfo(tmp.list.analog).ItemCount]); % take the number of samples from the longest channel
hdr.nSamplesPre = 0; % continuous data
hdr.nTrials = 1; % continuous data
hdr.label = {tmp.hdr.entityinfo(tmp.list.analog(tmp.analog.contcount~=0)).EntityLabel}; %%% contains non-unique chans?
hdr.orig = tmp; % remember the original header
case 'bucn_nirs'
orig = read_bucn_nirshdr(filename);
hdr = rmfield(orig, 'time');
hdr.orig = orig;
otherwise
if strcmp(fallback, 'biosig') && ft_hastoolbox('BIOSIG', 1)
hdr = read_biosig_header(filename);
else
error('unsupported header format (%s)', headerformat);
end
end % switch headerformat
% Sometimes, the not all labels are correctly filled in by low-level reading
% functions. See for example bug #1572.
% First, make sure that there are enough (potentially empty) labels:
if numel(hdr.label) < hdr.nChans
warning('low-level reading function did not supply enough channel labels');
hdr.label{hdr.nChans} = [];
end
% Now, replace all empty labels with new name:
if any(cellfun(@isempty, hdr.label))
warning('channel labels should not be empty, creating unique labels');
hdr.label = fix_empty(hdr.label);
end
if checkUniqueLabels
if length(hdr.label)~=length(unique(hdr.label))
% all channels must have unique names
warning('all channels must have unique labels, creating unique labels');
for i=1:hdr.nChans
sel = find(strcmp(hdr.label{i}, hdr.label));
if length(sel)>1
for j=1:length(sel)
hdr.label{sel(j)} = sprintf('%s-%d', hdr.label{sel(j)}, j);
end
end
end
end
end
% ensure that it is a column array
hdr.label = hdr.label(:);
% as of November 2011, the header is supposed to include the channel type
% (see FT_CHANTYPE) and the units of each channel (e.g. uV, fT, ...).
if ~isfield(hdr, 'chantype')
% use a helper function which has some built in intelligence
hdr.chantype = ft_chantype(hdr);
end % for
if ~isfield(hdr, 'chanunit')
% use a helper function which has some built in intelligence
hdr.chanunit = ft_chanunit(hdr);
end % for
% ensure that the output grad/elec is according to the latest definition
% allow both elec and sens to be present
if isfield(hdr, 'grad')
hdr.grad = ft_datatype_sens(hdr.grad);
end
if isfield(hdr, 'elec')
hdr.elec = ft_datatype_sens(hdr.elec);
end
% ensure that these are double precision and not integers, otherwise
% subsequent computations that depend on these might be messed up
hdr.Fs = double(hdr.Fs);
hdr.nSamples = double(hdr.nSamples);
hdr.nSamplesPre = double(hdr.nSamplesPre);
hdr.nTrials = double(hdr.nTrials);
hdr.nChans = double(hdr.nChans);
if cache && exist(headerfile, 'file')
% put the header in the cache
cacheheader = hdr;
% update the header details (including time stampp, size and name)
cacheheader.details = dir(headerfile);
% fprintf('added header to cache\n');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION to determine the file size in bytes
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [siz] = filesize(filename)
l = dir(filename);
if l.isdir
error('"%s" is not a file', filename);
end
siz = l.bytes;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION to determine the file size in bytes
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [hdr] = recursive_read_header(filename)
[p, f, x] = fileparts(filename);
ls = dir(filename);
ls = ls(~strcmp({ls.name}, '.')); % exclude this directory
ls = ls(~strcmp({ls.name}, '..')); % exclude parent directory
for i=1:length(ls)
% make sure that the directory listing includes the complete path
ls(i).name = fullfile(filename, ls(i).name);
end
lst = {ls.name};
hdr = cell(size(lst));
sel = zeros(size(lst));
for i=1:length(lst)
% read the header of each individual file
try
thishdr = ft_read_header(lst{i});
if isstruct(thishdr)
thishdr.filename = lst{i};
end
catch
thishdr = [];
warning(lasterr);
fprintf('while reading %s\n\n', lst{i});
end
if ~isempty(thishdr)
hdr{i} = thishdr;
sel(i) = true;
else
sel(i) = false;
end
end
sel = logical(sel(:));
hdr = hdr(sel);
tmp = {};
for i=1:length(hdr)
if isstruct(hdr{i})
tmp = cat(1, tmp, hdr(i));
elseif iscell(hdr{i})
tmp = cat(1, tmp, hdr{i}{:});
end
end
hdr = tmp;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION to fill in empty labels
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function labels = fix_empty(labels)
for i = find(cellfun(@isempty, {labels{:}}));
labels{i} = sprintf('%d', i);
end
|
github
|
philippboehmsturm/antx-master
|
ft_filetype.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/ft_filetype.m
| 59,071 |
utf_8
|
63c215c5b603d0b75250113171f7298d
|
function [type] = ft_filetype(filename, desired, varargin)
% FT_FILETYPE determines the filetype of many EEG/MEG/MRI data files by
% looking at the name, extension and optionally (part of) its contents.
% It tries to determine the global type of file (which usually
% corresponds to the manufacturer, the recording system or to the
% software used to create the file) and the particular subtype (e.g.
% continuous, average).
%
% Use as
% type = ft_filetype(filename)
% type = ft_filetype(dirname)
%
% This gives you a descriptive string with the data type, and can be
% used in a switch-statement. The descriptive string that is returned
% usually is something like 'XXX_YYY'/ where XXX refers to the
% manufacturer and YYY to the type of the data.
%
% Alternatively, use as
% flag = ft_filetype(filename, type)
% flag = ft_filetype(dirname, type)
% This gives you a boolean flag (0 or 1) indicating whether the file
% is of the desired type, and can be used to check whether the
% user-supplied file is what your subsequent code expects.
%
% Alternatively, use as
% flag = ft_filetype(dirlist, type)
% where the dirlist contains a list of files contained within one
% directory. This gives you a boolean vector indicating for each file
% whether it is of the desired type.
%
% Most filetypes of the following manufacturers and/or software programs are recognized
% - 4D/BTi
% - AFNI
% - ASA
% - Analyse
% - Analyze/SPM
% - BESA
% - BrainVision
% - Curry
% - Dataq
% - EDF
% - EEProbe
% - Elektra/Neuromag
% - LORETA
% - FreeSurfer
% - MINC
% - Neuralynx
% - Neuroscan
% - Plexon
% - SR Research Eyelink
% - Tucker Davis Technology
% - VSM-Medtech/CTF
% - Yokogawa
% - nifti, gifti
% Copyright (C) 2003-2011 Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_filetype.m 7351 2013-01-18 05:09:26Z josdie $
% these are for remembering the type on subsequent calls with the same input arguments
persistent previous_argin previous_argout previous_pwd
if nargin<2
% ensure that all input arguments are defined
desired = [];
end
current_argin = {filename, desired, varargin{:}};
current_pwd = pwd;
if isequal(current_argin, previous_argin) && isequal(current_pwd, previous_pwd)
% don't do the detection again, but return the previous value from cache
type = previous_argout{1};
return
end
if isa(filename, 'memmapfile')
filename = filename.Filename;
end
% % get the optional arguments
% checkheader = ft_getopt(varargin, 'checkheader', true);
%
% if ~checkheader
% % assume that the header is always ok, e.g when the file does not yet exist
% % this replaces the normal function with a function that always returns true
% filetype_check_header = @filetype_true;
% end
if iscell(filename)
if ~isempty(desired)
% perform the test for each filename, return a boolean vector
type = false(size(filename));
else
% return a string with the type for each filename
type = cell(size(filename));
end
for i=1:length(filename)
if strcmp(filename{i}(end), '.')
% do not recurse into this directory or the parent directory
continue
else
if iscell(type)
type{i} = ft_filetype(filename{i}, desired);
else
type(i) = ft_filetype(filename{i}, desired);
end
end
end
return
end
% start with unknown values
type = 'unknown';
manufacturer = 'unknown';
content = 'unknown';
if isempty(filename)
if isempty(desired)
% return the "unknown" outputs
return
else
% return that it is a non-match
type = false;
return
end
end
% the parts of the filename are used further down
[p, f, x] = fileparts(filename);
% prevent this test if the filename resembles an URI, i.e. like "scheme://"
if isempty(strfind(filename , '://')) && isdir(filename)
% the directory listing is needed below
ls = dir(filename);
% remove the parent directory and the directory itself from the list
ls = ls(~strcmp({ls.name}, '.'));
ls = ls(~strcmp({ls.name}, '..'));
for i=1:length(ls)
% make sure that the directory listing includes the complete path
ls(i).name = fullfile(filename, ls(i).name);
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% start determining the filetype
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% this checks for a compressed file (of arbitrary type)
if filetype_check_extension(filename, 'zip')...
|| (filetype_check_extension(filename, '.gz') && ~filetype_check_extension(filename, '.nii.gz'))...
|| filetype_check_extension(filename, 'tgz')...
|| filetype_check_extension(filename, 'tar')
type = 'compressed';
manufacturer = 'undefined';
content = 'unknown, extract first';
% these are some streams for asynchronous BCI
elseif filetype_check_uri(filename, 'fifo')
type = 'fcdc_fifo';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'stream';
elseif filetype_check_uri(filename, 'buffer')
type = 'fcdc_buffer';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'stream';
elseif filetype_check_uri(filename, 'mysql')
type = 'fcdc_mysql';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'stream';
elseif filetype_check_uri(filename, 'tcp')
type = 'fcdc_tcp';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'stream';
elseif filetype_check_uri(filename, 'udp')
type = 'fcdc_udp';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'stream';
elseif filetype_check_uri(filename, 'rfb')
type = 'fcdc_rfb';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'stream';
elseif filetype_check_uri(filename, 'serial')
type = 'fcdc_serial';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'stream';
elseif filetype_check_uri(filename, 'global')
type = 'fcdc_global';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'global variable';
elseif filetype_check_uri(filename, 'shm')
type = 'ctf_shm';
manufacturer = 'CTF';
content = 'real-time shared memory buffer';
elseif filetype_check_uri(filename, 'empty')
type = 'empty';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = '/dev/null';
% known CTF file types
elseif isdir(filename) && filetype_check_extension(filename, '.ds') && exist(fullfile(filename, [f '.res4']))
type = 'ctf_ds';
manufacturer = 'CTF';
content = 'MEG dataset';
elseif isdir(filename) && ~isempty(dir(fullfile(filename, '*.res4'))) && ~isempty(dir(fullfile(filename, '*.meg4')))
type = 'ctf_ds';
manufacturer = 'CTF';
content = 'MEG dataset';
elseif filetype_check_extension(filename, '.res4') && (filetype_check_header(filename, 'MEG41RS') || filetype_check_header(filename, 'MEG42RS') || filetype_check_header(filename, 'MEG4RES') || filetype_check_header(filename, 'MEG3RES')) %'MEG3RES' pertains to ctf64.ds
type = 'ctf_res4';
manufacturer = 'CTF';
content = 'MEG/EEG header information';
elseif filetype_check_extension(filename, '.meg4') && (filetype_check_header(filename, 'MEG41CP') || filetype_check_header(filename, 'MEG4CPT')) %'MEG4CPT' pertains to ctf64.ds
type = 'ctf_meg4';
manufacturer = 'CTF';
content = 'MEG/EEG';
elseif strcmp(f, 'MarkerFile') && filetype_check_extension(filename, '.mrk') && filetype_check_header(filename, 'PATH OF DATASET:')
type = 'ctf_mrk';
manufacturer = 'CTF';
content = 'marker file';
elseif filetype_check_extension(filename, '.mri') && filetype_check_header(filename, 'CTF_MRI_FORMAT VER 2.2')
type = 'ctf_mri';
manufacturer = 'CTF';
content = 'MRI';
elseif filetype_check_extension(filename, '.mri') && filetype_check_header(filename, 'CTF_MRI_FORMAT VER 4', 31)
type = 'ctf_mri4';
manufacturer = 'CTF';
content = 'MRI';
elseif filetype_check_extension(filename, '.hdm')
type = 'ctf_hdm';
manufacturer = 'CTF';
content = 'volume conduction model';
elseif filetype_check_extension(filename, '.hc')
type = 'ctf_hc';
manufacturer = 'CTF';
content = 'headcoil locations';
elseif filetype_check_extension(filename, '.shape')
type = 'ctf_shape';
manufacturer = 'CTF';
content = 'headshape points';
elseif filetype_check_extension(filename, '.shape_info')
type = 'ctf_shapeinfo';
manufacturer = 'CTF';
content = 'headshape information';
elseif filetype_check_extension(filename, '.wts')
type = 'ctf_wts';
manufacturer = 'CTF';
content = 'SAM coefficients, i.e. spatial filter weights';
elseif filetype_check_extension(filename, '.svl')
type = 'ctf_svl';
manufacturer = 'CTF';
content = 'SAM (pseudo-)statistic volumes';
% known Micromed file types
elseif filetype_check_extension(filename, '.trc') && filetype_check_header(filename, '* MICROMED')
type = 'micromed_trc';
manufacturer = 'Micromed';
content = 'Electrophysiological data';
% known BabySQUID file types, these should go before Neuromag
elseif filetype_check_extension(filename, '.fif') && exist(fullfile(p, [f '.eve']), 'file')
type = 'babysquid_fif';
manufacturer = 'Tristan Technologies';
content = 'MEG data';
elseif filetype_check_extension(filename, '.eve') && exist(fullfile(p, [f '.fif']), 'file')
type = 'babysquid_eve';
manufacturer = 'Tristan Technologies';
content = 'MEG data';
% known Neuromag file types
elseif filetype_check_extension(filename, '.fif')
type = 'neuromag_fif';
manufacturer = 'Neuromag';
content = 'MEG header and data';
elseif filetype_check_extension(filename, '.bdip')
type = 'neuromag_bdip';
manufacturer = 'Neuromag';
content = 'dipole model';
% known Yokogawa file types
elseif filetype_check_extension(filename, '.ave') || filetype_check_extension(filename, '.sqd')
type = 'yokogawa_ave';
manufacturer = 'Yokogawa';
content = 'averaged MEG data';
elseif filetype_check_extension(filename, '.con')
type = 'yokogawa_con';
manufacturer = 'Yokogawa';
content = 'continuous MEG data';
elseif filetype_check_extension(filename, '.raw') && filetype_check_header(filename, char([0 0 0 0])) % FIXME, this detection should possibly be improved
type = 'yokogawa_raw';
manufacturer = 'Yokogawa';
content = 'evoked/trialbased MEG data';
elseif filetype_check_extension(filename, '.mrk') && filetype_check_header(filename, char([0 0 0 0])) % FIXME, this detection should possibly be improved
type = 'yokogawa_mrk';
manufacturer = 'Yokogawa';
content = 'headcoil locations';
elseif filetype_check_extension(filename, '.txt') && numel(strfind(filename,'-coregis')) == 1
type = 'yokogawa_coregis';
manufacturer = 'Yokogawa';
content = 'exported fiducials';
elseif filetype_check_extension(filename, '.txt') && numel(strfind(filename,'-calib')) == 1
type = 'yokogawa_calib';
manufacturer = 'Yokogawa';
elseif filetype_check_extension(filename, '.txt') && numel(strfind(filename,'-channel')) == 1
type = 'yokogawa_channel';
manufacturer = 'Yokogawa';
elseif filetype_check_extension(filename, '.txt') && numel(strfind(filename,'-property')) == 1
type = 'yokogawa_property';
manufacturer = 'Yokogawa';
elseif filetype_check_extension(filename, '.txt') && numel(strfind(filename,'-TextData')) == 1
type = 'yokogawa_textdata';
manufacturer = 'Yokogawa';
elseif filetype_check_extension(filename, '.txt') && numel(strfind(filename,'-FLL')) == 1
type = 'yokogawa_fll';
manufacturer = 'Yokogawa';
elseif filetype_check_extension(filename, '.hsp')
type = 'yokogawa_hsp';
manufacturer = 'Yokogawa';
% Neurosim files; this has to go before the 4D detection
elseif ~isdir(filename) && (strcmp(f,'spikes') || filetype_check_header(filename,'# Spike information'))
type = 'neurosim_spikes';
manufacturer = 'Jan van der Eerden (DCCN)';
content = 'simulated spikes';
elseif ~isdir(filename) && (strcmp(f,'evolution') || filetype_check_header(filename,'# Voltages'))
type = 'neurosim_evolution';
manufacturer = 'Jan van der Eerden (DCCN)';
content = 'simulated membrane voltages and currents';
elseif ~isdir(filename) && (strcmp(f,'signals') || filetype_check_header(filename,'# Internal',2))
type = 'neurosim_signals';
manufacturer = 'Jan van der Eerden (DCCN)';
content = 'simulated network signals';
elseif isdir(filename) && exist(fullfile(filename, 'signals'), 'file') && exist(fullfile(filename, 'spikes'), 'file')
type = 'neurosim_ds';
manufacturer = 'Jan van der Eerden (DCCN)';
content = 'simulated spikes and continuous signals';
% known 4D/BTI file types
elseif filetype_check_extension(filename, '.pdf') && filetype_check_header(filename, 'E|lk') % I am not sure whether this header always applies
type = '4d_pdf';
manufacturer = '4D/BTI';
content = 'raw MEG data (processed data file)';
elseif exist([filename '.m4d'], 'file') && exist([filename '.xyz'], 'file') % these two ascii header files accompany the raw data
type = '4d_pdf';
manufacturer = '4D/BTI';
content = 'raw MEG data (processed data file)';
elseif filetype_check_extension(filename, '.m4d') && exist([filename(1:(end-3)) 'xyz'], 'file') % these come in pairs
type = '4d_m4d';
manufacturer = '4D/BTI';
content = 'MEG header information';
elseif filetype_check_extension(filename, '.xyz') && exist([filename(1:(end-3)) 'm4d'], 'file') % these come in pairs
type = '4d_xyz';
manufacturer = '4D/BTI';
content = 'MEG sensor positions';
elseif isequal(f, 'hs_file') % the filename is "hs_file"
type = '4d_hs';
manufacturer = '4D/BTI';
content = 'head shape';
elseif length(filename)>=4 && ~isempty(strfind(filename,',rf'))
type = '4d';
manufacturer = '4D/BTi';
content = '';
elseif filetype_check_extension(filename, '.el.ascii') && filetype_check_ascii(filename, 20) % assume that there are at least 20 bytes in the file, the example one has 4277 bytes
type = '4d_el_ascii';
manufacturer = '4D/BTi';
content = 'electrode positions';
elseif length(f)<=4 && filetype_check_dir(p, 'config')%&& ~isempty(p) && exist(fullfile(p,'config'), 'file') %&& exist(fullfile(p,'hs_file'), 'file')
% this could be a 4D file with non-standard/processed name
% it will be detected as a 4D file when there is a config file in the
% same directory as the specified file
type = '4d';
manufacturer = '4D/BTi';
content = '';
% known EEProbe file types
elseif filetype_check_extension(filename, '.cnt') && filetype_check_header(filename, 'RIFF')
type = 'eep_cnt';
manufacturer = 'EEProbe';
content = 'EEG';
elseif filetype_check_extension(filename, '.avr') && filetype_check_header(filename, char([38 0 16 0]))
type = 'eep_avr';
manufacturer = 'EEProbe';
content = 'ERP';
elseif filetype_check_extension(filename, '.trg')
type = 'eep_trg';
manufacturer = 'EEProbe';
content = 'trigger information';
elseif filetype_check_extension(filename, '.rej')
type = 'eep_rej';
manufacturer = 'EEProbe';
content = 'rejection marks';
% the yokogawa_mri has to be checked prior to asa_mri, because this one is more strict
elseif filetype_check_extension(filename, '.mri') && filetype_check_header(filename, char(0)) % FIXME, this detection should possibly be improved
type = 'yokogawa_mri';
manufacturer = 'Yokogawa';
content = 'anatomical MRI';
% known ASA file types
elseif filetype_check_extension(filename, '.elc')
type = 'asa_elc';
manufacturer = 'ASA';
content = 'electrode positions';
elseif filetype_check_extension(filename, '.vol')
type = 'asa_vol';
manufacturer = 'ASA';
content = 'volume conduction model';
elseif filetype_check_extension(filename, '.bnd')
type = 'asa_bnd';
manufacturer = 'ASA';
content = 'boundary element model details';
elseif filetype_check_extension(filename, '.msm')
type = 'asa_msm';
manufacturer = 'ASA';
content = 'ERP';
elseif filetype_check_extension(filename, '.msr')
type = 'asa_msr';
manufacturer = 'ASA';
content = 'ERP';
elseif filetype_check_extension(filename, '.dip')
% FIXME, can also be CTF dipole file
type = 'asa_dip';
manufacturer = 'ASA';
elseif filetype_check_extension(filename, '.mri')
% FIXME, can also be CTF mri file
type = 'asa_mri';
manufacturer = 'ASA';
content = 'MRI image header';
elseif filetype_check_extension(filename, '.iso')
type = 'asa_iso';
manufacturer = 'ASA';
content = 'MRI image data';
% known BCI2000 file types
elseif filetype_check_extension(filename, '.dat') && (filetype_check_header(filename, 'BCI2000') || filetype_check_header(filename, 'HeaderLen='))
type = 'bci2000_dat';
manufacturer = 'BCI2000';
content = 'continuous EEG';
% known Neuroscan file types
elseif filetype_check_extension(filename, '.avg') && filetype_check_header(filename, 'Version 3.0')
type = 'ns_avg';
manufacturer = 'Neuroscan';
content = 'averaged EEG';
elseif filetype_check_extension(filename, '.cnt') && filetype_check_header(filename, 'Version 3.0')
type = 'ns_cnt';
manufacturer = 'Neuroscan';
content = 'continuous EEG';
elseif filetype_check_extension(filename, '.eeg') && filetype_check_header(filename, 'Version 3.0')
type = 'ns_eeg';
manufacturer = 'Neuroscan';
content = 'epoched EEG';
elseif filetype_check_extension(filename, '.eeg') && filetype_check_header(filename, 'V3.0')
type = 'neuroprax_eeg';
manufacturer = 'eldith GmbH';
content = 'continuous EEG';
elseif filetype_check_extension(filename, '.ee_')
type = 'neuroprax_mrk';
manufacturer = 'eldith GmbH';
content = 'EEG markers';
% known Analyze & SPM file types
elseif filetype_check_extension(filename, '.hdr')
type = 'analyze_hdr';
manufacturer = 'Mayo Analyze';
content = 'PET/MRI image header';
elseif filetype_check_extension(filename, '.img')
type = 'analyze_img';
manufacturer = 'Mayo Analyze';
content = 'PET/MRI image data';
elseif filetype_check_extension(filename, '.mnc')
type = 'minc';
content = 'MRI image data';
elseif filetype_check_extension(filename, '.nii')
type = 'nifti';
content = 'MRI image data';
% known FSL file types
elseif filetype_check_extension(filename, '.nii.gz')
type = 'nifti_fsl';
content = 'MRI image data';
% known LORETA file types
elseif filetype_check_extension(filename, '.lorb')
type = 'loreta_lorb';
manufacturer = 'old LORETA';
content = 'source reconstruction';
elseif filetype_check_extension(filename, '.slor')
type = 'loreta_slor';
manufacturer = 'sLORETA';
content = 'source reconstruction';
% known AFNI file types
elseif filetype_check_extension(filename, '.brik') || filetype_check_extension(filename, '.BRIK')
type = 'afni_brik';
content = 'MRI image data';
elseif filetype_check_extension(filename, '.head') || filetype_check_extension(filename, '.HEAD')
type = 'afni_head';
content = 'MRI header data';
% known BrainVison file types
elseif filetype_check_extension(filename, '.vhdr')
type = 'brainvision_vhdr';
manufacturer = 'BrainProducts';
content = 'EEG header';
elseif filetype_check_extension(filename, '.vmrk')
type = 'brainvision_vmrk';
manufacturer = 'BrainProducts';
content = 'EEG markers';
elseif filetype_check_extension(filename, '.vabs')
type = 'brainvision_vabs';
manufacturer = 'BrainProducts';
content = 'Brain Vison Analyzer macro';
elseif filetype_check_extension(filename, '.eeg') && exist(fullfile(p, [f '.vhdr']), 'file')
type = 'brainvision_eeg';
manufacturer = 'BrainProducts';
content = 'continuous EEG data';
elseif filetype_check_extension(filename, '.seg')
type = 'brainvision_seg';
manufacturer = 'BrainProducts';
content = 'segmented EEG data';
elseif filetype_check_extension(filename, '.dat') && exist(fullfile(p, [f '.vhdr']), 'file') &&...
~filetype_check_header(filename, 'HeaderLen=') && ~filetype_check_header(filename, 'BESA_SA_IMAGE') &&...
~(exist(fullfile(p, [f '.gen']), 'file') || exist(fullfile(p, [f '.generic']), 'file'))
% WARNING this is a very general name, it could be exported BrainVision
% data but also a BESA beamformer source reconstruction or BCI2000
type = 'brainvision_dat';
manufacturer = 'BrainProducts';
content = 'exported EEG data';
elseif filetype_check_extension(filename, '.marker')
type = 'brainvision_marker';
manufacturer = 'BrainProducts';
content = 'rejection markers';
% known Polhemus file types
elseif filetype_check_extension(filename, '.pos')
type = 'polhemus_pos';
manufacturer = 'BrainProducts/CTF/Polhemus?'; % actually I don't know whose software it is
content = 'electrode positions';
% known Neuralynx file types
elseif filetype_check_extension(filename, '.nev') || filetype_check_extension(filename, '.Nev')
type = 'neuralynx_nev';
manufacturer = 'Neuralynx';
content = 'event information';
elseif filetype_check_extension(filename, '.ncs') && filetype_check_header(filename, '####')
type = 'neuralynx_ncs';
manufacturer = 'Neuralynx';
content = 'continuous single channel recordings';
elseif filetype_check_extension(filename, '.nse') && filetype_check_header(filename, '####')
type = 'neuralynx_nse';
manufacturer = 'Neuralynx';
content = 'spike waveforms';
elseif filetype_check_extension(filename, '.nts') && filetype_check_header(filename, '####')
type = 'neuralynx_nts';
manufacturer = 'Neuralynx';
content = 'timestamps only';
elseif filetype_check_extension(filename, '.nvt')
type = 'neuralynx_nvt';
manufacturer = 'Neuralynx';
content = 'video tracker';
elseif filetype_check_extension(filename, '.nst')
type = 'neuralynx_nst';
manufacturer = 'Neuralynx';
content = 'continuous stereotrode recordings';
elseif filetype_check_extension(filename, '.ntt')
type = 'neuralynx_ntt';
manufacturer = 'Neuralynx';
content = 'continuous tetrode recordings';
elseif strcmpi(f, 'logfile') && strcmpi(x, '.txt') % case insensitive
type = 'neuralynx_log';
manufacturer = 'Neuralynx';
content = 'log information in ASCII format';
elseif ~isempty(strfind(lower(f), 'dma')) && strcmpi(x, '.log') % this is not a very strong detection
type = 'neuralynx_dma';
manufacturer = 'Neuralynx';
content = 'raw aplifier data directly from DMA';
elseif filetype_check_extension(filename, '.nrd') % see also above, since Cheetah 5.x the file extension has changed
type = 'neuralynx_dma';
manufacturer = 'Neuralynx';
content = 'raw aplifier data directly from DMA';
elseif isdir(filename) && (any(filetype_check_extension({ls.name}, '.nev')) || any(filetype_check_extension({ls.name}, '.Nev')))
% a regular Neuralynx dataset directory that contains an event file
type = 'neuralynx_ds';
manufacturer = 'Neuralynx';
content = 'dataset';
elseif isdir(filename) && most(filetype_check_extension({ls.name}, '.ncs'))
% a directory containing continuously sampled channels in Neuralynx format
type = 'neuralynx_ds';
manufacturer = 'Neuralynx';
content = 'continuously sampled channels';
elseif isdir(filename) && most(filetype_check_extension({ls.name}, '.nse'))
% a directory containing spike waveforms in Neuralynx format
type = 'neuralynx_ds';
manufacturer = 'Neuralynx';
content = 'spike waveforms';
elseif isdir(filename) && most(filetype_check_extension({ls.name}, '.nte'))
% a directory containing spike timestamps in Neuralynx format
type = 'neuralynx_ds';
manufacturer = 'Neuralynx';
content = 'spike timestamps';
elseif isdir(filename) && most(filetype_check_extension({ls.name}, '.ntt'))
% a directory containing tetrode recordings in Neuralynx format
type = 'neuralynx_ds';
manufacturer = 'Neuralynx';
content = 'tetrode recordings ';
elseif isdir(p) && exist(fullfile(p, 'header'), 'file') && exist(fullfile(p, 'events'), 'file')
type = 'fcdc_buffer_offline';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'FieldTrip buffer offline dataset';
elseif isdir(filename) && exist(fullfile(filename, 'info.xml'), 'file') && exist(fullfile(filename, 'signal1.bin'), 'file')
% this is an OS X package directory representing a complete EEG dataset
% it contains a Content file, multiple xml files and one or more signalN.bin files
type = 'egi_mff';
manufacturer = 'Electrical Geodesics Incorporated';
content = 'raw EEG data';
elseif ~isdir(filename) && isdir(p) && exist(fullfile(p, 'info.xml'), 'file') && exist(fullfile(p, 'signal1.bin'), 'file')
% the file that the user specified is one of the files in an mff package directory
type = 'egi_mff';
manufacturer = 'Electrical Geodesics Incorporated';
content = 'raw EEG data';
% these are formally not Neuralynx file formats, but at the FCDC we use them together with Neuralynx
elseif isdir(filename) && filetype_check_neuralynx_cds(filename)
% a downsampled Neuralynx DMA file can be split into three seperate lfp/mua/spike directories
% treat them as one combined dataset
type = 'neuralynx_cds';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'dataset containing seperate lfp/mua/spike directories';
elseif filetype_check_extension(filename, '.tsl') && filetype_check_header(filename, 'tsl')
type = 'neuralynx_tsl';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'timestamps from DMA log file';
elseif filetype_check_extension(filename, '.tsh') && filetype_check_header(filename, 'tsh')
type = 'neuralynx_tsh';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'timestamps from DMA log file';
elseif filetype_check_extension(filename, '.ttl') && filetype_check_header(filename, 'ttl')
type = 'neuralynx_ttl';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'Parallel_in from DMA log file';
elseif filetype_check_extension(filename, '.bin') && filetype_check_header(filename, {'uint8', 'uint16', 'uint32', 'int8', 'int16', 'int32', 'int64', 'float32', 'float64'})
type = 'neuralynx_bin';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'single channel continuous data';
elseif isdir(filename) && any(filetype_check_extension({ls.name}, '.ttl')) && any(filetype_check_extension({ls.name}, '.tsl')) && any(filetype_check_extension({ls.name}, '.tsh'))
% a directory containing the split channels from a DMA logfile
type = 'neuralynx_sdma';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'split DMA log file';
elseif isdir(filename) && filetype_check_extension(filename, '.sdma')
% a directory containing the split channels from a DMA logfile
type = 'neuralynx_sdma';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'split DMA log file';
% known Plexon file types
elseif filetype_check_extension(filename, '.nex') && filetype_check_header(filename, 'NEX1')
type = 'plexon_nex';
manufacturer = 'Plexon';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.plx') && filetype_check_header(filename, 'PLEX')
type = 'plexon_plx';
manufacturer = 'Plexon';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.ddt')
type = 'plexon_ddt';
manufacturer = 'Plexon';
elseif isdir(filename) && most(filetype_check_extension({ls.name}, '.nex')) && most(filetype_check_header({ls.name}, 'NEX1'))
% a directory containing multiple plexon NEX files
type = 'plexon_ds';
manufacturer = 'Plexon';
content = 'electrophysiological data';
% known Cambridge Electronic Design file types
elseif filetype_check_extension(filename, '.smr')
type = 'ced_son';
manufacturer = 'Cambridge Electronic Design';
content = 'Spike2 SON filing system';
% known BESA file types
elseif filetype_check_extension(filename, '.avr') && strcmp(type, 'unknown')
type = 'besa_avr'; % FIXME, can also be EEProbe average EEG
manufacturer = 'BESA';
content = 'average EEG';
elseif filetype_check_extension(filename, '.elp')
type = 'besa_elp';
manufacturer = 'BESA';
content = 'electrode positions';
elseif filetype_check_extension(filename, '.eps')
type = 'besa_eps';
manufacturer = 'BESA';
content = 'digitizer information';
elseif filetype_check_extension(filename, '.sfp')
type = 'besa_sfp';
manufacturer = 'BESA';
content = 'sensor positions';
elseif filetype_check_extension(filename, '.ela')
type = 'besa_ela';
manufacturer = 'BESA';
content = 'sensor information';
elseif filetype_check_extension(filename, '.pdg')
type = 'besa_pdg';
manufacturer = 'BESA';
content = 'paradigm file';
elseif filetype_check_extension(filename, '.tfc')
type = 'besa_tfc';
manufacturer = 'BESA';
content = 'time frequency coherence';
elseif filetype_check_extension(filename, '.mul')
type = 'besa_mul';
manufacturer = 'BESA';
content = 'multiplexed ascii format';
elseif filetype_check_extension(filename, '.dat') && filetype_check_header(filename, 'BESA_SA') % header can start with BESA_SA_IMAGE or BESA_SA_MN_IMAGE
type = 'besa_src';
manufacturer = 'BESA';
content = 'beamformer source reconstruction';
elseif filetype_check_extension(filename, '.swf') && filetype_check_header(filename, 'Npts=')
type = 'besa_swf';
manufacturer = 'BESA';
content = 'beamformer source waveform';
elseif filetype_check_extension(filename, '.bsa')
type = 'besa_bsa';
manufacturer = 'BESA';
content = 'beamformer source locations and orientations';
elseif exist(fullfile(p, [f '.dat']), 'file') && (exist(fullfile(p, [f '.gen']), 'file') || exist(fullfile(p, [f '.generic']), 'file'))
type = 'besa_sb';
manufacturer = 'BESA';
content = 'simple binary channel data with a seperate generic ascii header';
% known Dataq file formats
elseif filetype_check_extension(upper(filename), '.WDQ')
type = 'dataq_wdq';
manufacturer = 'dataq instruments';
content = 'electrophysiological data';
% old files from Pascal Fries' PhD research at the MPI
elseif filetype_check_extension(filename, '.dap') && filetype_check_header(filename, char(1))
type = 'mpi_dap';
manufacturer = 'MPI Frankfurt';
content = 'electrophysiological data';
elseif isdir(filename) && ~isempty(cell2mat(regexp({ls.name}, '.dap$')))
type = 'mpi_ds';
manufacturer = 'MPI Frankfurt';
content = 'electrophysiological data';
% Frankfurt SPASS format, which uses the Labview Datalog (DTLG) format
elseif filetype_check_extension(filename, '.ana') && filetype_check_header(filename, 'DTLG')
type = 'spass_ana';
manufacturer = 'MPI Frankfurt';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.swa') && filetype_check_header(filename, 'DTLG')
type = 'spass_swa';
manufacturer = 'MPI Frankfurt';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.spi') && filetype_check_header(filename, 'DTLG')
type = 'spass_spi';
manufacturer = 'MPI Frankfurt';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.stm') && filetype_check_header(filename, 'DTLG')
type = 'spass_stm';
manufacturer = 'MPI Frankfurt';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.bhv') && filetype_check_header(filename, 'DTLG')
type = 'spass_bhv';
manufacturer = 'MPI Frankfurt';
content = 'electrophysiological data';
% known Chieti ITAB file types
elseif filetype_check_extension(filename, '.raw') && (filetype_check_header(filename, 'FORMAT: ATB-BIOMAGDATA') || filetype_check_header(filename, '[HeaderType]'))
type = 'itab_raw';
manufacturer = 'Chieti ITAB';
content = 'MEG data, including sensor positions';
elseif filetype_check_extension(filename, '.raw.mhd')
type = 'itab_mhd';
manufacturer = 'Chieti ITAB';
content = 'MEG header data, including sensor positions';
elseif filetype_check_extension(filename, '.asc') && ~filetype_check_header(filename, '**')
type = 'itab_asc';
manufacturer = 'Chieti ITAB';
content = 'headshape digitization file';
% known Nexstim file types
elseif filetype_check_extension(filename, '.nxe')
type = 'nexstim_nxe';
manufacturer = 'Nexstim';
content = 'electrophysiological data';
% known Tucker-Davis-Technology file types
elseif filetype_check_extension(filename, '.tbk')
type = 'tdt_tbk';
manufacturer = 'Tucker-Davis-Technology';
content = 'database/tank meta-information';
elseif filetype_check_extension(filename, '.tdx')
type = 'tdt_tdx';
manufacturer = 'Tucker-Davis-Technology';
content = 'database/tank meta-information';
elseif filetype_check_extension(filename, '.tsq')
type = 'tdt_tsq';
manufacturer = 'Tucker-Davis-Technology';
content = 'block header information';
elseif filetype_check_extension(filename, '.tev')
type = 'tdt_tev';
manufacturer = 'Tucker-Davis-Technology';
content = 'electrophysiological data';
elseif (filetype_check_extension(filename, '.dat') || filetype_check_extension(filename, '.Dat')) && (exist(fullfile(p, [f '.ini']), 'file') || exist(fullfile(p, [f '.Ini']), 'file'))
% this should go before curry_dat
type = 'deymed_dat';
manufacturer = 'Deymed';
content = 'raw eeg data';
elseif (filetype_check_extension(filename, '.ini') || filetype_check_extension(filename, '.Ini')) && (exist(fullfile(p, [f '.dat']), 'file') || exist(fullfile(p, [f '.Dat']), 'file'))
type = 'deymed_ini';
manufacturer = 'Deymed';
content = 'eeg header information';
% known Curry V4 file types
elseif filetype_check_extension(filename, '.dap')
type = 'curry_dap'; % FIXME, can also be MPI Frankfurt electrophysiological data
manufacturer = 'Curry';
content = 'data parameter file';
elseif filetype_check_extension(filename, '.dat')
type = 'curry_dat';
manufacturer = 'Curry';
content = 'raw data file';
elseif filetype_check_extension(filename, '.rs4')
type = 'curry_rs4';
manufacturer = 'Curry';
content = 'sensor geometry file';
elseif filetype_check_extension(filename, '.par')
type = 'curry_par';
manufacturer = 'Curry';
content = 'data or image parameter file';
elseif filetype_check_extension(filename, '.bd0') || filetype_check_extension(filename, '.bd1') || filetype_check_extension(filename, '.bd2') || filetype_check_extension(filename, '.bd3') || filetype_check_extension(filename, '.bd4') || filetype_check_extension(filename, '.bd5') || filetype_check_extension(filename, '.bd6') || filetype_check_extension(filename, '.bd7') || filetype_check_extension(filename, '.bd8') || filetype_check_extension(filename, '.bd9')
type = 'curry_bd';
manufacturer = 'Curry';
content = 'BEM description file';
elseif filetype_check_extension(filename, '.bt0') || filetype_check_extension(filename, '.bt1') || filetype_check_extension(filename, '.bt2') || filetype_check_extension(filename, '.bt3') || filetype_check_extension(filename, '.bt4') || filetype_check_extension(filename, '.bt5') || filetype_check_extension(filename, '.bt6') || filetype_check_extension(filename, '.bt7') || filetype_check_extension(filename, '.bt8') || filetype_check_extension(filename, '.bt9')
type = 'curry_bt';
manufacturer = 'Curry';
content = 'BEM transfer matrix file';
elseif filetype_check_extension(filename, '.bm0') || filetype_check_extension(filename, '.bm1') || filetype_check_extension(filename, '.bm2') || filetype_check_extension(filename, '.bm3') || filetype_check_extension(filename, '.bm4') || filetype_check_extension(filename, '.bm5') || filetype_check_extension(filename, '.bm6') || filetype_check_extension(filename, '.bm7') || filetype_check_extension(filename, '.bm8') || filetype_check_extension(filename, '.bm9')
type = 'curry_bm';
manufacturer = 'Curry';
content = 'BEM full matrix file';
elseif filetype_check_extension(filename, '.dig')
type = 'curry_dig';
manufacturer = 'Curry';
content = 'digitizer file';
% known SR Research eyelink file formats
elseif filetype_check_extension(filename, '.asc') && filetype_check_header(filename, '**')
type = 'eyelink_asc';
manufacturer = 'SR Research (ascii)';
content = 'eyetracker data';
elseif filetype_check_extension(filename, '.edf') && filetype_check_header(filename, 'SR_RESEARCH')
type = 'eyelink_edf';
manufacturer = 'SR Research';
content = 'eyetracker data (binary)';
% known Curry V2 file types
elseif filetype_check_extension(filename, '.sp0') || filetype_check_extension(filename, '.sp1') || filetype_check_extension(filename, '.sp2') || filetype_check_extension(filename, '.sp3') || filetype_check_extension(filename, '.sp4') || filetype_check_extension(filename, '.sp5') || filetype_check_extension(filename, '.sp6') || filetype_check_extension(filename, '.sp7') || filetype_check_extension(filename, '.sp8') || filetype_check_extension(filename, '.sp9')
type = 'curry_sp';
manufacturer = 'Curry';
content = 'point list';
elseif filetype_check_extension(filename, '.s10') || filetype_check_extension(filename, '.s11') || filetype_check_extension(filename, '.s12') || filetype_check_extension(filename, '.s13') || filetype_check_extension(filename, '.s14') || filetype_check_extension(filename, '.s15') || filetype_check_extension(filename, '.s16') || filetype_check_extension(filename, '.s17') || filetype_check_extension(filename, '.s18') || filetype_check_extension(filename, '.s19') || filetype_check_extension(filename, '.s20') || filetype_check_extension(filename, '.s21') || filetype_check_extension(filename, '.s22') || filetype_check_extension(filename, '.s23') || filetype_check_extension(filename, '.s24') || filetype_check_extension(filename, '.s25') || filetype_check_extension(filename, '.s26') || filetype_check_extension(filename, '.s27') || filetype_check_extension(filename, '.s28') || filetype_check_extension(filename, '.s29') || filetype_check_extension(filename, '.s30') || filetype_check_extension(filename, '.s31') || filetype_check_extension(filename, '.s32') || filetype_check_extension(filename, '.s33') || filetype_check_extension(filename, '.s34') || filetype_check_extension(filename, '.s35') || filetype_check_extension(filename, '.s36') || filetype_check_extension(filename, '.s37') || filetype_check_extension(filename, '.s38') || filetype_check_extension(filename, '.s39')
type = 'curry_s';
manufacturer = 'Curry';
content = 'triangle or tetraedra list';
elseif filetype_check_extension(filename, '.pom')
type = 'curry_pom';
manufacturer = 'Curry';
content = 'anatomical localization file';
elseif filetype_check_extension(filename, '.res')
type = 'curry_res';
manufacturer = 'Curry';
content = 'functional localization file';
% known MBFYS file types
elseif filetype_check_extension(filename, '.tri')
type = 'mbfys_tri';
manufacturer = 'MBFYS';
content = 'triangulated surface';
elseif filetype_check_extension(filename, '.ama') && filetype_check_header(filename, [10 0 0 0])
type = 'mbfys_ama';
manufacturer = 'MBFYS';
content = 'BEM volume conduction model';
% Electrical Geodesics Incorporated formats
% the egi_mff format is checked earlier
elseif (filetype_check_extension(filename, '.egis') || filetype_check_extension(filename, '.ave') || filetype_check_extension(filename, '.gave') || filetype_check_extension(filename, '.raw')) && (filetype_check_header(filename, [char(1) char(2) char(3) char(4) char(255) char(255)]) || filetype_check_header(filename, [char(3) char(4) char(1) char(2) char(255) char(255)]))
type = 'egi_egia';
manufacturer = 'Electrical Geodesics Incorporated';
content = 'averaged EEG data';
elseif (filetype_check_extension(filename, '.egis') || filetype_check_extension(filename, '.ses') || filetype_check_extension(filename, '.raw')) && (filetype_check_header(filename, [char(1) char(2) char(3) char(4) char(0) char(3)]) || filetype_check_header(filename, [char(3) char(4) char(1) char(2) char(0) char(3)]))
type = 'egi_egis';
manufacturer = 'Electrical Geodesics Incorporated';
content = 'raw EEG data';
elseif (filetype_check_extension(filename, '.sbin') || filetype_check_extension(filename, '.raw'))
% note that the Chieti MEG data format also has the extension *.raw
% but that can be detected by looking at the file header
type = 'egi_sbin';
manufacturer = 'Electrical Geodesics Incorporated';
content = 'averaged EEG data';
% FreeSurfer file formats, see also http://www.grahamwideman.com/gw/brain/fs/surfacefileformats.htm
elseif filetype_check_extension(filename, '.mgz')
type = 'freesurfer_mgz';
manufacturer = 'FreeSurfer';
content = 'anatomical MRI';
elseif filetype_check_extension(filename, '.mgh')
type = 'freesurfer_mgh';
manufacturer = 'FreeSurfer';
content = 'anatomical MRI';
elseif filetype_check_header(filename, [255 255 254])
% FreeSurfer Triangle Surface Binary Format
type = 'freesurfer_triangle_binary'; % there is also an ascii triangle format
manufacturer = 'FreeSurfer';
content = 'surface description';
elseif filetype_check_header(filename, [255 255 255])
% Quadrangle File
type = 'freesurfer_quadrangle'; % there is no ascii quadrangle format
manufacturer = 'FreeSurfer';
content = 'surface description';
elseif filetype_check_header(filename, [255 255 253]) && ~exist([filename(1:(end-4)) '.mat'], 'file')
% "New" Quadrangle File
type = 'freesurfer_quadrangle_new';
manufacturer = 'FreeSurfer';
content = 'surface description';
elseif filetype_check_extension(filename, '.curv') && filetype_check_header(filename, [255 255 255])
% "New" Curv File
type = 'freesurfer_curv_new';
manufacturer = 'FreeSurfer';
content = 'surface description';
elseif filetype_check_extension(filename, '.annot')
% Freesurfer annotation file
type = 'freesurfer_annot';
manufacturer = 'FreeSurfer';
content = 'parcellation annotation';
elseif filetype_check_extension(filename, '.txt') && numel(strfind(filename,'_nrs_')) == 1
% This may be improved by looking into the file, rather than assuming the
% filename has "_nrs_" somewhere. Also, distinction by the different file
% types could be made
type = 'bucn_nirs';
manufacturer = 'BUCN';
content = 'ascii formatted nirs data';
% known TETGEN file types, see http://tetgen.berlios.de/fformats.html
elseif any(filetype_check_extension(filename, {'.node' '.poly' '.smesh' '.ele' '.face' '.edge' '.vol' '.var' '.neigh'})) && exist(fullfile(p, [f '.node']), 'file') && filetype_check_ascii(fullfile(p, [f '.node']), 100) && exist(fullfile(p, [f '.poly']), 'file')
type = 'tetgen_poly';
manufacturer = 'TetGen, see http://tetgen.berlios.de';
content = 'geometrical data desribed with piecewise linear complex';
elseif any(filetype_check_extension(filename, {'.node' '.poly' '.smesh' '.ele' '.face' '.edge' '.vol' '.var' '.neigh'})) && exist(fullfile(p, [f '.node']), 'file') && filetype_check_ascii(fullfile(p, [f '.node']), 100) && exist(fullfile(p, [f '.smesh']), 'file')
type = 'tetgensmesh';
manufacturer = 'TetGen, see http://tetgen.berlios.de';
content = 'geometrical data desribed with simple piecewise linear complex';
elseif any(filetype_check_extension(filename, {'.node' '.poly' '.smesh' '.ele' '.face' '.edge' '.vol' '.var' '.neigh'})) && exist(fullfile(p, [f '.node']), 'file') && filetype_check_ascii(fullfile(p, [f '.node']), 100) && exist(fullfile(p, [f '.ele']), 'file')
type = 'tetgen_ele';
manufacturer = 'TetGen, see http://tetgen.berlios.de';
content = 'geometrical data desribed with tetrahedra';
elseif any(filetype_check_extension(filename, {'.node' '.poly' '.smesh' '.ele' '.face' '.edge' '.vol' '.var' '.neigh'})) && exist(fullfile(p, [f '.node']), 'file') && filetype_check_ascii(fullfile(p, [f '.node']), 100) && exist(fullfile(p, [f '.face']), 'file')
type = 'tetgen_face';
manufacturer = 'TetGen, see http://tetgen.berlios.de';
content = 'geometrical data desribed with triangular faces';
elseif any(filetype_check_extension(filename, {'.node' '.poly' '.smesh' '.ele' '.face' '.edge' '.vol' '.var' '.neigh'})) && exist(fullfile(p, [f '.node']), 'file') && filetype_check_ascii(fullfile(p, [f '.node']), 100) && exist(fullfile(p, [f '.edge']), 'file')
type = 'tetgen_edge';
manufacturer = 'TetGen, see http://tetgen.berlios.de';
content = 'geometrical data desribed with boundary edges';
elseif any(filetype_check_extension(filename, {'.node' '.poly' '.smesh' '.ele' '.face' '.edge' '.vol' '.var' '.neigh'})) && exist(fullfile(p, [f '.node']), 'file') && filetype_check_ascii(fullfile(p, [f '.node']), 100) && exist(fullfile(p, [f '.vol']), 'file')
type = 'tetgen_vol';
manufacturer = 'TetGen, see http://tetgen.berlios.de';
content = 'geometrical data desribed with maximum volumes';
elseif any(filetype_check_extension(filename, {'.node' '.poly' '.smesh' '.ele' '.face' '.edge' '.vol' '.var' '.neigh'})) && exist(fullfile(p, [f '.node']), 'file') && filetype_check_ascii(fullfile(p, [f '.node']), 100) && exist(fullfile(p, [f '.var']), 'file')
type = 'tetgen_var';
manufacturer = 'TetGen, see http://tetgen.berlios.de';
content = 'geometrical data desribed with variant constraints for facets/segments';
elseif any(filetype_check_extension(filename, {'.node' '.poly' '.smesh' '.ele' '.face' '.edge' '.vol' '.var' '.neigh'})) && exist(fullfile(p, [f '.node']), 'file') && filetype_check_ascii(fullfile(p, [f '.node']), 100) && exist(fullfile(p, [f '.neigh']), 'file')
type = 'tetgen_neigh';
manufacturer = 'TetGen, see http://tetgen.berlios.de';
content = 'geometrical data desribed with neighbors';
elseif any(filetype_check_extension(filename, {'.node' '.poly' '.smesh' '.ele' '.face' '.edge' '.vol' '.var' '.neigh'})) && exist(fullfile(p, [f '.node']), 'file') && filetype_check_ascii(fullfile(p, [f '.node']), 100)
type = 'tetgen_node';
manufacturer = 'TetGen, see http://tetgen.berlios.de';
content = 'geometrical data desribed with only nodes';
% some other known file types
elseif length(filename)>4 && exist([filename(1:(end-4)) '.mat'], 'file') && exist([filename(1:(end-4)) '.bin'], 'file')
% this is a self-defined FCDC data format, consisting of two files
% there is a matlab V6 file with the header and a binary file with the data (multiplexed, ieee-le, double)
type = 'fcdc_matbin';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'multiplexed electrophysiology data';
elseif filetype_check_extension(filename, '.lay')
type = 'layout';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'layout of channels for plotting';
elseif filetype_check_extension(filename, '.stl')
type = 'stl';
manufacturer = 'various';
content = 'stereo litography file';
elseif filetype_check_extension(filename, '.dcm') || filetype_check_extension(filename, '.ima') || filetype_check_header(filename, 'DICM', 128)
type = 'dicom';
manufacturer = 'Dicom';
content = 'image data';
elseif filetype_check_extension(filename, '.trl')
type = 'fcdc_trl';
manufacturer = 'Donders Centre for Cognitive Neuroimaging';
content = 'trial definitions';
elseif filetype_check_extension(filename, '.bdf') && filetype_check_header(filename, [255 'BIOSEMI'])
type = 'biosemi_bdf';
manufacturer = 'Biosemi Data Format';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.edf')
type = 'edf';
manufacturer = 'European Data Format';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.gdf') && filetype_check_header(filename, 'GDF')
type = 'gdf';
manufacturer = 'BIOSIG - Alois Schloegl';
content = 'biosignals';
elseif filetype_check_extension(filename, '.mat') && filetype_check_header(filename, 'MATLAB') && filetype_check_spmeeg_mat(filename)
type = 'spmeeg_mat';
manufacturer = 'Wellcome Trust Centre for Neuroimaging, UCL, UK';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.mat') && filetype_check_header(filename, 'MATLAB') && filetype_check_gtec_mat(filename)
type = 'gtec_mat';
manufacturer = 'Guger Technologies, http://www.gtec.at';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.mat') && filetype_check_header(filename, 'MATLAB') && filetype_check_ced_spike6mat(filename)
type = 'ced_spike6mat';
manufacturer = 'Cambridge Electronic Design Limited';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.mat') && filetype_check_header(filename, 'MATLAB')
type = 'matlab';
manufacturer = 'Matlab';
content = 'Matlab binary data';
elseif filetype_check_header(filename, 'RIFF', 0) && filetype_check_header(filename, 'WAVE', 8)
type = 'riff_wave';
manufacturer = 'Microsoft';
content = 'audio';
elseif filetype_check_extension(filename, '.txt')
type = 'ascii_txt';
manufacturer = '';
content = '';
elseif filetype_check_extension(filename, '.pol')
type = 'polhemus_fil';
manufacturer = 'Functional Imaging Lab, London, UK';
content = 'headshape points';
elseif filetype_check_extension(filename, '.set')
type = 'eeglab_set';
manufacturer = 'Swartz Center for Computational Neuroscience, San Diego, USA';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.erp')
type = 'eeglab_erp';
manufacturer = 'Swartz Center for Computational Neuroscience, San Diego, USA';
content = 'electrophysiological data';
elseif filetype_check_extension(filename, '.t') && filetype_check_header(filename, '%%BEGINHEADER')
type = 'mclust_t';
manufacturer = 'MClust';
content = 'sorted spikes';
elseif filetype_check_header(filename, 26)
type = 'nimh_cortex';
manufacturer = 'NIMH Laboratory of Neuropsychology, http://www.cortex.salk.edu';
content = 'events and eye channels';
elseif filetype_check_extension(filename, '.foci') && filetype_check_header(filename, '<?xml')
type = 'caret_foci';
manufacturer = 'Caret and ConnectomeWB';
elseif filetype_check_extension(filename, '.border') && filetype_check_header(filename, '<?xml')
type = 'caret_border';
manufacturer = 'Caret and ConnectomeWB';
elseif filetype_check_extension(filename, '.spec') && filetype_check_header(filename, '<?xml')
type = 'caret_spec';
manufacturer = 'Caret and ConnectomeWB';
elseif filetype_check_extension(filename, '.gii') && ~isempty(strfind(filename, '.coord.')) && filetype_check_header(filename, '<?xml')
type = 'caret_coord';
manufacturer = 'Caret and ConnectomeWB';
elseif filetype_check_extension(filename, '.gii') && ~isempty(strfind(filename, '.topo.')) && filetype_check_header(filename, '<?xml')
type = 'caret_topo';
manufacturer = 'Caret and ConnectomeWB';
elseif filetype_check_extension(filename, '.gii') && ~isempty(strfind(filename, '.surf.')) && filetype_check_header(filename, '<?xml')
type = 'caret_surf';
manufacturer = 'Caret and ConnectomeWB';
elseif filetype_check_extension(filename, '.gii') && ~isempty(strfind(filename, '.label.')) && filetype_check_header(filename, '<?xml')
type = 'caret_label';
manufacturer = 'Caret and ConnectomeWB';
elseif filetype_check_extension(filename, '.gii') && ~isempty(strfind(filename, '.func.')) && filetype_check_header(filename, '<?xml')
type = 'caret_func';
manufacturer = 'Caret and ConnectomeWB';
elseif filetype_check_extension(filename, '.gii') && ~isempty(strfind(filename, '.shape.')) && filetype_check_header(filename, '<?xml')
type = 'caret_shape';
manufacturer = 'Caret and ConnectomeWB';
elseif filetype_check_extension(filename, '.gii') && filetype_check_header(filename, '<?xml')
type = 'gifti';
manufacturer = 'Neuroimaging Informatics Technology Initiative';
content = 'tesselated surface description';
elseif filetype_check_extension(filename, '.v')
type = 'vista';
manufacturer = 'University of British Columbia, Canada, http://www.cs.ubc.ca/nest/lci/vista/vista.html';
content = 'A format for computer vision research, contains meshes or volumes';
elseif filetype_check_extension(filename, '.tet')
type = 'tet';
manufacturer = 'a.o. INRIA, see http://shapes.aimatshape.net/';
content = 'tetraedral mesh';
elseif filetype_check_extension(filename, '.nc')
type = 'netmeg';
manufacturer = 'Center for Biomedical Research Excellence (COBRE), see http://cobre.mrn.org/megsim/tools/netMEG/netMEG.html';
content = 'MEG data';
elseif filetype_check_extension(filename, 'trk')
type = 'trackvis_trk';
manufacturer = 'Martinos Center for Biomedical Imaging, see http://www.trackvis.org';
content = 'fiber tracking data from diffusion MR imaging';
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% finished determining the filetype
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if strcmp(type, 'unknown')
warning_once(sprintf('could not determine filetype of %s', filename));
end
if ~isempty(desired)
% return a boolean value instead of a descriptive string
type = strcmp(type, desired);
end
% remember the current input and output arguments, so that they can be
% reused on a subsequent call in case the same input argument is given
current_argout = {type};
if isempty(previous_argin) && ~strcmp(type, 'unknown')
previous_argin = current_argin;
previous_argout = current_argout;
previous_pwd = current_pwd;
elseif isempty(previous_argin) && (exist(filename,'file') || exist(filename,'dir')) && strcmp(type, 'unknown') % if the type is unknown, but the file or dir exists, save the current output
previous_argin = current_argin;
previous_argout = current_argout;
previous_pwd = current_pwd;
else
% don't remember in case unknown
previous_argin = [];
previous_argout = [];
previous_pwd = [];
end
return % filetype main()
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that helps in deciding whether a directory with files should
% be treated as a "dataset". This function returns a logical 1 (TRUE) if more
% than half of the element of a vector are nonzero number or are 1 or TRUE.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function y = most(x)
x = x(~isnan(x(:)));
y = sum(x==0)<ceil(length(x)/2);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that always returns a true value
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function y = filetype_true(varargin)
y = 1;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that checks for CED spike6 mat file
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function res = filetype_check_ced_spike6mat(filename)
res = 1;
var = whos('-file', filename);
% Check whether all the variables in the file are structs (representing channels)
if ~all(strcmp('struct', unique({var(:).class})) == 1)
res = 0;
return;
end
var = load(filename, var(1).name);
var = struct2cell(var);
% Check whether the fields of the first struct have some particular names
fnames = {
'title'
'comment'
'interval'
'scale'
'offset'
'units'
'start'
'length'
'values'
'times'
};
res = (numel(intersect(fieldnames(var{1}), fnames)) >= 5);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that checks for a SPM eeg/meg mat file
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function res = filetype_check_spmeeg_mat(filename)
% check for the accompanying *.dat file
res = exist([filename(1:(end-4)) '.dat'], 'file');
if ~res, return; end
% check the content of the *.mat file
var = whos('-file', filename);
res = res && numel(var)==1;
res = res && strcmp('D', getfield(var, {1}, 'name'));
res = res && strcmp('struct', getfield(var, {1}, 'class'));
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that checks for a GTEC mat file
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function res = filetype_check_gtec_mat(filename)
% check the content of the *.mat file
var = whos('-file', filename);
res = length(intersect({'log', 'names'}, {var.name}))==2;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that checks the presence of a specified file in a directory
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function res = filetype_check_dir(p, filename)
if ~isempty(p)
d = dir(p);
else
d = dir;
end
res = ~isempty(strmatch(filename,{d.name},'exact'));
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that checks whether the directory is neuralynx_cds
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function res = filetype_check_neuralynx_cds(filename)
res=false;
files=dir(filename);
dirlist=files([files.isdir]);
% 1) check for a subdirectory with extension .lfp, .mua or .spike
haslfp = any(filetype_check_extension({dirlist.name}, 'lfp'));
hasmua = any(filetype_check_extension({dirlist.name}, 'mua'));
hasspike = any(filetype_check_extension({dirlist.name}, 'spike'));
% 2) check for each of the subdirs being a neuralynx_ds
if haslfp || hasmua || hasspike
sel=find(filetype_check_extension({dirlist.name}, 'lfp')+...
filetype_check_extension({dirlist.name}, 'mua')+...
filetype_check_extension({dirlist.name}, 'spike'));
neuralynxdirs=cell(1,length(sel));
for n=1:length(sel)
neuralynxdirs{n}=fullfile(filename, dirlist(sel(n)).name);
end
res=any(ft_filetype(neuralynxdirs, 'neuralynx_ds'));
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION that checks whether the file contains only ascii characters
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function res = filetype_check_ascii(filename, len)
% See http://en.wikipedia.org/wiki/ASCII
if exist(filename, 'file')
fid = fopen(filename, 'rt');
bin = fread(fid, len, 'uint8=>uint8');
fclose(fid);
printable = bin>31 & bin<127; % the printable characters, represent letters, digits, punctuation marks, and a few miscellaneous symbols
special = bin==10 | bin==13 | bin==11; % line feed, form feed, tab
res = all(printable | special);
else
% always return true if the file does not (yet) exist, this is important
% for determining the format to which data should be written
res = 1;
end
|
github
|
philippboehmsturm/antx-master
|
read_mff_bin.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_mff_bin.m
| 4,095 |
utf_8
|
14e1df31f92faf2b6f02cfe4a32060c9
|
function [output] = read_mff_bin(filename, begblock, endblock, chanindx)
% READ_MFF_BIN
%
% Use as
% [hdr] = read_mff_bin(filename)
% or
% [dat] = read_mff_bin(filename, begblock, endblock);
fid = fopen(filename,'r');
if fid == -1
error('wrong filename') % could not find signal(n)
end
needhdr = (nargin==1);
needdat = (nargin==4);
if needhdr
hdr = read_mff_block(fid, [], [], 'skip');
prevhdr = hdr(end);
for i=2:hdr.opthdr.nblocks
hdr(i) = read_mff_block(fid, prevhdr, [], 'skip');
prevhdr = hdr(end);
end
% assign the output variable
output = hdr;
elseif needdat
prevhdr = [];
dat = {};
block = 0;
while true
block = block+1;
if block<begblock
[hdr] = read_mff_block(fid, prevhdr, chanindx, 'skip');
prevhdr = hdr;
continue % with the next block
end
if block==begblock
[hdr, dat] = read_mff_block(fid, prevhdr, chanindx, 'read');
prevhdr = hdr;
continue % with the next block
end
if block<=endblock
[hdr, dat(:,end+1)] = read_mff_block(fid, prevhdr, chanindx, 'read');
prevhdr = hdr;
continue % with the next block
end
break % out of the while loop
end % while
% assign the output variable
output = dat;
end % need header or data
fclose(fid);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [hdr, dat] = read_mff_block(fid, prevhdr, chanindx, action)
if nargin<3
prevhdr = [];
end
if nargin<4
action = 'none';
end
%-Endianness
endian = 'ieee-le';
% General information
hdr.version = fread(fid, 1, 'int32', endian);
if hdr.version==0
% the header did not change compared to the previous one
% no additional information is present in the file
% the file continues with the actual data
hdr = prevhdr;
hdr.version = 0;
else
hdr.headersize = fread(fid, 1, 'int32', endian);
hdr.datasize = fread(fid, 1, 'int32', endian); % the documentation specified that this includes the data, but that seems not to be the case
hdr.nsignals = fread(fid, 1, 'int32', endian);
% channel-specific information
hdr.offset = fread(fid, hdr.nsignals, 'int32', endian);
% signal depth and frequency for each channel
for i = 1:hdr.nsignals
hdr.depth(i) = fread(fid, 1, 'int8', endian);
hdr.fsample(i) = fread(fid, 1, 'bit24', endian); %ingnie: is bit24 the same as int24?
end
%-Optional header length
hdr.optlength = fread(fid, 1, 'int32', endian);
if hdr.optlength
hdr.opthdr.EGItype = fread(fid, 1, 'int32', endian);
hdr.opthdr.nblocks = fread(fid, 1, 'int64', endian);
hdr.opthdr.nsamples = fread(fid, 1, 'int64', endian);
hdr.opthdr.nsignals = fread(fid, 1, 'int32', endian);
else
hdr.opthdr = [];
end
% determine the number of samples for each channel
hdr.nsamples = diff(hdr.offset);
% the last one has to be determined by looking at the total data block length
hdr.nsamples(end+1) = hdr.datasize - hdr.offset(end);
% divide by the number of bytes in each channel
hdr.nsamples = hdr.nsamples(:) ./ (hdr.depth(:)./8);
end % reading the rest of the header
switch action
case 'read'
dat = cell(length(chanindx), 1);
currchan = 1;
for i = 1:hdr.nsignals
switch hdr.depth(i) % length in bit
case 16
slen = 2; % sample length, for fseek
datatype = 'int16';
case 32
slen = 4; % sample length, for fseek
datatype = 'single';
case 64
slen = 8; % sample length, for fseek
datatype = 'double';
end % case
tmp = fread(fid, [1 hdr.nsamples(i)], datatype);
if ~isempty(intersect(chanindx,i)) %only keep channels that are requested
dat{currchan} = tmp;
currchan = currchan + 1;
end
end % for
case 'skip'
dat = {};
fseek(fid, hdr.datasize, 'cof');
case 'none'
dat = {};
return;
end % switch action
|
github
|
philippboehmsturm/antx-master
|
ft_datatype_sens.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/ft_datatype_sens.m
| 8,876 |
utf_8
|
9cca02c1384fde3f0c40f1a5a3a0253a
|
function [sens] = ft_datatype_sens(sens, varargin)
% FT_DATATYPE_SENS describes the FieldTrip structure that represents
% an EEG, ECoG, or MEG sensor array. This structure is commonly called
% "elec" for EEG and "grad" for MEG, or more general "sens" for either
% one.
%
% The structure for MEG gradiometers and/or magnetometers contains
% sens.label = Mx1 cell-array with channel labels
% sens.chanpos = Mx3 matrix with channel positions
% sens.chanori = Mx3 matrix with channel orientations, used for synthetic planar gradient computation
% sens.tra = MxN matrix to combine coils into channels
% sens.coilpos = Nx3 matrix with coil positions
% sens.coilori = Nx3 matrix with coil orientations
% sens.balance = structure containing info about the balancing, See FT_APPLY_MONTAGE
%
% The structure for EEG or ECoG channels contains
% sens.label = Mx1 cell-array with channel labels
% sens.chanpos = Mx3 matrix with channel positions
% sens.tra = MxN matrix to combine electrodes into channels
% sens.elecpos = Nx3 matrix with electrode positions
% In case sens.tra is not present in the EEG sensor array, the channels
% are assumed to be average referenced.
%
% The following fields are optional
% sens.type = string with the MEG or EEG acquisition system, see FT_SENSTYPE
% sens.chantype = Mx1 cell-array with the type of the channel, see FT_CHANTYPE
% sens.chanunit = Mx1 cell-array with the units of the channel signal, e.g. 'T', 'fT' or 'fT/cm'
% sens.fid = structure with fiducial information
%
% Revision history:
%
% (2011v2/latest) The chantype and chanunit have been added for MEG.
%
% (2011v1) To facilitate determining the position of channels (e.g. for plotting)
% in case of balanced MEG or bipolar EEG, an explicit distinction has been made
% between chanpos+chanori and coilpos+coilori (for MEG) and chanpos and elecpos
% (for EEG). The pnt and ori fields are removed
%
% (2010) Added support for bipolar or otherwise more complex linear combinations
% of EEG electrodes using sens.tra, similar to MEG.
%
% (2009) Noice reduction has been added for MEG systems in the balance field.
%
% (2006) The optional fields sens.type and sens.unit were added.
%
% (2003) The initial version was defined, which looked like this for EEG
% sens.pnt = Mx3 matrix with electrode positions
% sens.label = Mx1 cell-array with channel labels
% and like this for MEG
% sens.pnt = Nx3 matrix with coil positions
% sens.ori = Nx3 matrix with coil orientations
% sens.tra = MxN matrix to combine coils into channels
% sens.label = Mx1 cell-array with channel labels
%
% See also FT_READ_SENS, FT_SENSTYPE, FT_CHANTYPE, FT_APPLY_MONTAGE, CTF2GRAD, FIF2GRAD,
% BTI2GRAD, YOKOGAWA2GRAD, ITAB2GRAD
% Copyright (C) 2011, Robert Oostenveld & Jan-Mathijs Schoffelen
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_datatype_sens.m 7248 2012-12-21 11:37:13Z roboos $
% these are for remembering the type on subsequent calls with the same input arguments
persistent previous_argin previous_argout
current_argin = [{sens} varargin];
if isequal(current_argin, previous_argin)
% don't do the whole cheking again, but return the previous output from cache
sens = previous_argout{1};
end
% get the optional input arguments, which should be specified as key-value pairs
version = ft_getopt(varargin, 'version', 'latest');
if strcmp(version, 'latest')
version = '2011v2';
end
if isempty(sens)
return;
end
switch version
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case '2011v2'
% This speeds up subsequent calls to ft_senstype and channelposition.
% However, if it is not more precise than MEG or EEG, don't keep it in
% the output (see further down).
if ~isfield(sens, 'type')
sens.type = ft_senstype(sens);
end
% there are many cases which deal with either eeg or meg
ismeg = ft_senstype(sens, 'meg');
if isfield(sens, 'pnt')
if ismeg
% sensor description is a MEG sensor-array, containing oriented coils
sens.coilpos = sens.pnt; sens = rmfield(sens, 'pnt');
sens.coilori = sens.ori; sens = rmfield(sens, 'ori');
else
% sensor description is something else, EEG/ECoG etc
sens.elecpos = sens.pnt; sens = rmfield(sens, 'pnt');
end
end
if ~isfield(sens, 'chanpos')
if ismeg
% sensor description is a MEG sensor-array, containing oriented coils
[chanpos, chanori, lab] = channelposition(sens, 'channel', 'all');
% the channel order can be different in the two representations
[selsens, selpos] = match_str(sens.label, lab);
sens.chanpos = nan(length(sens.label), 3);
sens.chanori = nan(length(sens.label), 3);
% insert the determined position/orientation on the appropriate rows
sens.chanpos(selsens,:) = chanpos(selpos,:);
sens.chanori(selsens,:) = chanori(selpos,:);
if length(selsens)~=length(sens.label)
warning('cannot determine the position and orientation for all channels');
end
else
% sensor description is something else, EEG/ECoG etc
% note that chanori will be all NaNs
[chanpos, chanori, lab] = channelposition(sens, 'channel', 'all');
% the channel order can be different in the two representations
[selsens, selpos] = match_str(sens.label, lab);
sens.chanpos = nan(length(sens.label), 3);
% insert the determined position/orientation on the appropriate rows
sens.chanpos(selsens,:) = chanpos(selpos,:);
if length(selsens)~=length(sens.label)
warning('cannot determine the position and orientation for all channels');
end
end
end
if ~isfield(sens, 'chantype') || all(strcmp(sens.chantype, 'unknown'))
if ismeg
sens.chantype = ft_chantype(sens);
else
% FIXME for EEG we have not yet figured out how to deal with this
end
end
if ~isfield(sens, 'chanunit') || all(strcmp(sens.chanunit, 'unknown'))
if ismeg
sens.chanunit = ft_chanunit(sens);
else
% FIXME for EEG we have not yet figured out how to deal with this
end
end
if ~isfield(sens, 'unit')
sens = ft_convert_units(sens);
end
if any(strcmp(sens.type, {'meg', 'eeg', 'magnetometer', 'electrode', 'unknown'}))
% this is not sufficiently informative, so better remove it
% see also http://bugzilla.fcdonders.nl/show_bug.cgi?id=1806
sens = rmfield(sens, 'type');
end
if size(sens.chanpos,1)~=length(sens.label) || ...
isfield(sens, 'tra') && size(sens.tra,1)~=length(sens.label) || ...
isfield(sens, 'tra') && isfield(sens, 'elecpos') && size(sens.tra,2)~=size(sens.elecpos,1) || ...
isfield(sens, 'tra') && isfield(sens, 'coilpos') && size(sens.tra,2)~=size(sens.coilpos,1) || ...
isfield(sens, 'tra') && isfield(sens, 'coilori') && size(sens.tra,2)~=size(sens.coilori,1) || ...
isfield(sens, 'chanpos') && size(sens.chanpos,1)~=length(sens.label) || ...
isfield(sens, 'chanori') && size(sens.chanori,1)~=length(sens.label)
error('inconsistent number of channels in sensor description');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
otherwise
error('converting to version %s is not supported', version);
end % switch
% this makes the display with the "disp" command look better
sens = sortfieldnames(sens);
% remember the current input and output arguments, so that they can be
% reused on a subsequent call in case the same input argument is given
current_argout = {sens};
previous_argin = current_argin;
previous_argout = current_argout;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function b = sortfieldnames(a)
fn = sort(fieldnames(a));
for i=1:numel(fn)
b.(fn{i}) = a.(fn{i});
end
|
github
|
philippboehmsturm/antx-master
|
avw_img_read.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/avw_img_read.m
| 29,199 |
utf_8
|
be1e5b74cfdcf9acc49582896e9fadec
|
function [ avw, machine ] = avw_img_read(fileprefix,IMGorient,machine,verbose)
% avw_img_read - read Analyze format data image (*.img)
%
% [ avw, machine ] = avw_img_read(fileprefix,[orient],[machine],[verbose])
%
% fileprefix - a string, the filename without the .img extension
%
% orient - read a specified orientation, integer values:
%
% '', use header history orient field
% 0, transverse unflipped (LAS*)
% 1, coronal unflipped (LA*S)
% 2, sagittal unflipped (L*AS)
% 3, transverse flipped (LPS*)
% 4, coronal flipped (LA*I)
% 5, sagittal flipped (L*AI)
%
% where * follows the slice dimension and letters indicate +XYZ
% orientations (L left, R right, A anterior, P posterior,
% I inferior, & S superior).
%
% Some files may contain data in the 3-5 orientations, but this
% is unlikely. For more information about orientation, see the
% documentation at the end of this .m file. See also the
% AVW_FLIP function for orthogonal reorientation.
%
% machine - a string, see machineformat in fread for details.
% The default here is 'ieee-le' but the routine
% will automatically switch between little and big
% endian to read any such Analyze header. It
% reports the appropriate machine format and can
% return the machine value.
%
% verbose - the default is to output processing information to the command
% window. If verbose = 0, this will not happen.
%
% Returned values:
%
% avw.hdr - a struct with image data parameters.
% avw.img - a 3D matrix of image data (double precision).
%
% A returned 3D matrix will correspond with the
% default ANALYZE coordinate system, which
% is Left-handed:
%
% X-Y plane is Transverse
% X-Z plane is Coronal
% Y-Z plane is Sagittal
%
% X axis runs from patient right (low X) to patient Left (high X)
% Y axis runs from posterior (low Y) to Anterior (high Y)
% Z axis runs from inferior (low Z) to Superior (high Z)
%
% The function can read a 4D Analyze volume, but only if it is in the
% axial unflipped orientation.
%
% See also: avw_hdr_read (called by this function),
% avw_view, avw_write, avw_img_write, avw_flip
%
% $Revision: 7123 $ $Date: 2009/01/14 09:24:45 $
% Licence: GNU GPL, no express or implied warranties
% History: 05/2002, [email protected]
% The Analyze format is copyright
% (c) Copyright, 1986-1995
% Biomedical Imaging Resource, Mayo Foundation
% 01/2003, [email protected]
% - adapted for matlab v5
% - revised all orientation information and handling
% after seeking further advice from AnalyzeDirect.com
% 03/2003, [email protected]
% - adapted for -ve pixdim values (non standard Analyze)
% 07/2004, [email protected], added ability to
% read volumes with dimensionality greather than 3.
% a >3D volume cannot be flipped. and error is thrown if a volume of
% greater than 3D (ie, avw.hdr.dime.dim(1) > 3) requests a data flip
% (ie, avw.hdr.hist.orient ~= 0 ). i pulled the transfer of read-in
% data (tmp) to avw.img out of any looping mechanism. looping is not
% necessary as the data is already in its correct orientation. using
% 'reshape' rather than looping should be faster but, more importantly,
% it allows the reading in of N-D volumes. See lines 270-280.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if ~exist('IMGorient','var'), IMGorient = ''; end
if ~exist('machine','var'), machine = 'ieee-le'; end
if ~exist('verbose','var'), verbose = 1; end
if isempty(IMGorient), IMGorient = ''; end
if isempty(machine), machine = 'ieee-le'; end
if isempty(verbose), verbose = 1; end
if ~exist('fileprefix','var'),
msg = sprintf('...no input fileprefix - see help avw_img_read\n\n');
error(msg);
end
if findstr('.hdr',fileprefix),
fileprefix = strrep(fileprefix,'.hdr','');
end
if findstr('.img',fileprefix),
fileprefix = strrep(fileprefix,'.img','');
end
% MAIN
% Read the file header
[ avw, machine ] = avw_hdr_read(fileprefix,machine,verbose);
avw = read_image(avw,IMGorient,machine,verbose);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ avw ] = read_image(avw,IMGorient,machine,verbose)
fid = fopen(sprintf('%s.img',avw.fileprefix),'r',machine);
if fid < 0,
msg = sprintf('...cannot open file %s.img\n\n',avw.fileprefix);
error(msg);
end
if verbose,
ver = '[$Revision: 7123 $]';
fprintf('\nAVW_IMG_READ [v%s]\n',ver(12:16)); tic;
end
% short int bitpix; /* Number of bits per pixel; 1, 8, 16, 32, or 64. */
% short int datatype /* Datatype for this image set */
% /*Acceptable values for datatype are*/
% #define DT_NONE 0
% #define DT_UNKNOWN 0 /*Unknown data type*/
% #define DT_BINARY 1 /*Binary ( 1 bit per voxel)*/
% #define DT_UNSIGNED_CHAR 2 /*Unsigned character ( 8 bits per voxel)*/
% #define DT_SIGNED_SHORT 4 /*Signed short (16 bits per voxel)*/
% #define DT_SIGNED_INT 8 /*Signed integer (32 bits per voxel)*/
% #define DT_FLOAT 16 /*Floating point (32 bits per voxel)*/
% #define DT_COMPLEX 32 /*Complex (64 bits per voxel; 2 floating point numbers)/*
% #define DT_DOUBLE 64 /*Double precision (64 bits per voxel)*/
% #define DT_RGB 128 /*A Red-Green-Blue datatype*/
% #define DT_ALL 255 /*Undocumented*/
switch double(avw.hdr.dime.bitpix),
case 1, precision = 'bit1';
case 8, precision = 'uchar';
case 16, precision = 'int16';
case 32,
if isequal(avw.hdr.dime.datatype, 8), precision = 'int32';
else precision = 'single';
end
case 64, precision = 'double';
otherwise,
precision = 'uchar';
if verbose, fprintf('...precision undefined in header, using ''uchar''\n'); end
end
% read the whole .img file into matlab (faster)
if verbose,
fprintf('...reading %s Analyze %s image format.\n',machine,precision);
end
fseek(fid,0,'bof');
% adjust for matlab version
ver = version;
ver = str2num(ver(1));
if ver < 6,
tmp = fread(fid,inf,sprintf('%s',precision));
else,
tmp = fread(fid,inf,sprintf('%s=>double',precision));
end
fclose(fid);
% Update the global min and max values
avw.hdr.dime.glmax = max(double(tmp));
avw.hdr.dime.glmin = min(double(tmp));
%---------------------------------------------------------------
% Now partition the img data into xyz
% --- first figure out the size of the image
% short int dim[ ]; /* Array of the image dimensions */
%
% dim[0] Number of dimensions in database; usually 4.
% dim[1] Image X dimension; number of pixels in an image row.
% dim[2] Image Y dimension; number of pixel rows in slice.
% dim[3] Volume Z dimension; number of slices in a volume.
% dim[4] Time points; number of volumes in database.
PixelDim = double(avw.hdr.dime.dim(2));
RowDim = double(avw.hdr.dime.dim(3));
SliceDim = double(avw.hdr.dime.dim(4));
TimeDim = double(avw.hdr.dime.dim(5));
PixelSz = double(avw.hdr.dime.pixdim(2));
RowSz = double(avw.hdr.dime.pixdim(3));
SliceSz = double(avw.hdr.dime.pixdim(4));
TimeSz = double(avw.hdr.dime.pixdim(5));
% ---- NON STANDARD ANALYZE...
% Some Analyze files have been found to set -ve pixdim values, eg
% the MNI template avg152T1_brain in the FSL etc/standard folder,
% perhaps to indicate flipped orientation? If so, this code below
% will NOT handle the flip correctly!
if PixelSz < 0,
warning('X pixdim < 0 !!! resetting to abs(avw.hdr.dime.pixdim(2))');
PixelSz = abs(PixelSz);
avw.hdr.dime.pixdim(2) = single(PixelSz);
end
if RowSz < 0,
warning('Y pixdim < 0 !!! resetting to abs(avw.hdr.dime.pixdim(3))');
RowSz = abs(RowSz);
avw.hdr.dime.pixdim(3) = single(RowSz);
end
if SliceSz < 0,
warning('Z pixdim < 0 !!! resetting to abs(avw.hdr.dime.pixdim(4))');
SliceSz = abs(SliceSz);
avw.hdr.dime.pixdim(4) = single(SliceSz);
end
% ---- END OF NON STANDARD ANALYZE
% --- check the orientation specification and arrange img accordingly
if ~isempty(IMGorient),
if ischar(IMGorient),
avw.hdr.hist.orient = uint8(str2num(IMGorient));
else
avw.hdr.hist.orient = uint8(IMGorient);
end
end,
if isempty(avw.hdr.hist.orient),
msg = [ '...unspecified avw.hdr.hist.orient, using default 0\n',...
' (check image and try explicit IMGorient option).\n'];
fprintf(msg);
avw.hdr.hist.orient = uint8(0);
end
% --- check if the orientation is to be flipped for a volume with more
% --- than 3 dimensions. this logic is currently unsupported so throw
% --- an error. volumes of any dimensionality may be read in *only* as
% --- unflipped, ie, avw.hdr.hist.orient == 0
if ( TimeDim > 1 ) && (avw.hdr.hist.orient ~= 0 ),
msg = [ 'ERROR: This volume has more than 3 dimensions *and* ', ...
'requires flipping the data. Flipping is not supported ', ...
'for volumes with dimensionality greater than 3. Set ', ...
'avw.hdr.hist.orient = 0 and flip your volume after ', ...
'calling this function' ];
msg = sprintf( '%s (%s).', msg, mfilename );
error( msg );
end
switch double(avw.hdr.hist.orient),
case 0, % transverse unflipped
% orient = 0: The primary orientation of the data on disk is in the
% transverse plane relative to the object scanned. Most commonly, the fastest
% moving index through the voxels that are part of this transverse image would
% span the right-left extent of the structure imaged, with the next fastest
% moving index spanning the posterior-anterior extent of the structure. This
% 'orient' flag would indicate to Analyze that this data should be placed in
% the X-Y plane of the 3D Analyze Coordinate System, with the Z dimension
% being the slice direction.
% For the 'transverse unflipped' type, the voxels are stored with
% Pixels in 'x' axis (varies fastest) - from patient right to left
% Rows in 'y' axis - from patient posterior to anterior
% Slices in 'z' axis - from patient inferior to superior
if verbose, fprintf('...reading axial unflipped orientation\n'); end
% -- This code will handle nD files
dims = double( avw.hdr.dime.dim(2:end) );
% replace dimensions of 0 with 1 to be used in reshape
idx = find( dims == 0 );
dims( idx ) = 1;
avw.img = reshape( tmp, dims );
% -- The code above replaces this
% avw.img = zeros(PixelDim,RowDim,SliceDim);
%
% n = 1;
% x = 1:PixelDim;
% for z = 1:SliceDim,
% for y = 1:RowDim,
% % load Y row of X values into Z slice avw.img
% avw.img(x,y,z) = tmp(n:n+(PixelDim-1));
% n = n + PixelDim;
% end
% end
% no need to rearrange avw.hdr.dime.dim or avw.hdr.dime.pixdim
case 1, % coronal unflipped
% orient = 1: The primary orientation of the data on disk is in the coronal
% plane relative to the object scanned. Most commonly, the fastest moving
% index through the voxels that are part of this coronal image would span the
% right-left extent of the structure imaged, with the next fastest moving
% index spanning the inferior-superior extent of the structure. This 'orient'
% flag would indicate to Analyze that this data should be placed in the X-Z
% plane of the 3D Analyze Coordinate System, with the Y dimension being the
% slice direction.
% For the 'coronal unflipped' type, the voxels are stored with
% Pixels in 'x' axis (varies fastest) - from patient right to left
% Rows in 'z' axis - from patient inferior to superior
% Slices in 'y' axis - from patient posterior to anterior
if verbose, fprintf('...reading coronal unflipped orientation\n'); end
avw.img = zeros(PixelDim,SliceDim,RowDim);
n = 1;
x = 1:PixelDim;
for y = 1:SliceDim,
for z = 1:RowDim,
% load Z row of X values into Y slice avw.img
avw.img(x,y,z) = tmp(n:n+(PixelDim-1));
n = n + PixelDim;
end
end
% rearrange avw.hdr.dime.dim or avw.hdr.dime.pixdim
avw.hdr.dime.dim(2:4) = int16([PixelDim,SliceDim,RowDim]);
avw.hdr.dime.pixdim(2:4) = single([PixelSz,SliceSz,RowSz]);
case 2, % sagittal unflipped
% orient = 2: The primary orientation of the data on disk is in the sagittal
% plane relative to the object scanned. Most commonly, the fastest moving
% index through the voxels that are part of this sagittal image would span the
% posterior-anterior extent of the structure imaged, with the next fastest
% moving index spanning the inferior-superior extent of the structure. This
% 'orient' flag would indicate to Analyze that this data should be placed in
% the Y-Z plane of the 3D Analyze Coordinate System, with the X dimension
% being the slice direction.
% For the 'sagittal unflipped' type, the voxels are stored with
% Pixels in 'y' axis (varies fastest) - from patient posterior to anterior
% Rows in 'z' axis - from patient inferior to superior
% Slices in 'x' axis - from patient right to left
if verbose, fprintf('...reading sagittal unflipped orientation\n'); end
avw.img = zeros(SliceDim,PixelDim,RowDim);
n = 1;
y = 1:PixelDim; % posterior to anterior (fastest)
for x = 1:SliceDim, % right to left (slowest)
for z = 1:RowDim, % inferior to superior
% load Z row of Y values into X slice avw.img
avw.img(x,y,z) = tmp(n:n+(PixelDim-1));
n = n + PixelDim;
end
end
% rearrange avw.hdr.dime.dim or avw.hdr.dime.pixdim
avw.hdr.dime.dim(2:4) = int16([SliceDim,PixelDim,RowDim]);
avw.hdr.dime.pixdim(2:4) = single([SliceSz,PixelSz,RowSz]);
%--------------------------------------------------------------------------------
% Orient values 3-5 have the second index reversed in order, essentially
% 'flipping' the images relative to what would most likely become the vertical
% axis of the displayed image.
%--------------------------------------------------------------------------------
case 3, % transverse/axial flipped
% orient = 3: The primary orientation of the data on disk is in the
% transverse plane relative to the object scanned. Most commonly, the fastest
% moving index through the voxels that are part of this transverse image would
% span the right-left extent of the structure imaged, with the next fastest
% moving index spanning the *anterior-posterior* extent of the structure. This
% 'orient' flag would indicate to Analyze that this data should be placed in
% the X-Y plane of the 3D Analyze Coordinate System, with the Z dimension
% being the slice direction.
% For the 'transverse flipped' type, the voxels are stored with
% Pixels in 'x' axis (varies fastest) - from patient right to Left
% Rows in 'y' axis - from patient anterior to Posterior *
% Slices in 'z' axis - from patient inferior to Superior
if verbose, fprintf('...reading axial flipped (+Y from Anterior to Posterior)\n'); end
avw.img = zeros(PixelDim,RowDim,SliceDim);
n = 1;
x = 1:PixelDim;
for z = 1:SliceDim,
for y = RowDim:-1:1, % flip in Y, read A2P file into P2A 3D matrix
% load a flipped Y row of X values into Z slice avw.img
avw.img(x,y,z) = tmp(n:n+(PixelDim-1));
n = n + PixelDim;
end
end
% no need to rearrange avw.hdr.dime.dim or avw.hdr.dime.pixdim
case 4, % coronal flipped
% orient = 4: The primary orientation of the data on disk is in the coronal
% plane relative to the object scanned. Most commonly, the fastest moving
% index through the voxels that are part of this coronal image would span the
% right-left extent of the structure imaged, with the next fastest moving
% index spanning the *superior-inferior* extent of the structure. This 'orient'
% flag would indicate to Analyze that this data should be placed in the X-Z
% plane of the 3D Analyze Coordinate System, with the Y dimension being the
% slice direction.
% For the 'coronal flipped' type, the voxels are stored with
% Pixels in 'x' axis (varies fastest) - from patient right to Left
% Rows in 'z' axis - from patient superior to Inferior*
% Slices in 'y' axis - from patient posterior to Anterior
if verbose, fprintf('...reading coronal flipped (+Z from Superior to Inferior)\n'); end
avw.img = zeros(PixelDim,SliceDim,RowDim);
n = 1;
x = 1:PixelDim;
for y = 1:SliceDim,
for z = RowDim:-1:1, % flip in Z, read S2I file into I2S 3D matrix
% load a flipped Z row of X values into Y slice avw.img
avw.img(x,y,z) = tmp(n:n+(PixelDim-1));
n = n + PixelDim;
end
end
% rearrange avw.hdr.dime.dim or avw.hdr.dime.pixdim
avw.hdr.dime.dim(2:4) = int16([PixelDim,SliceDim,RowDim]);
avw.hdr.dime.pixdim(2:4) = single([PixelSz,SliceSz,RowSz]);
case 5, % sagittal flipped
% orient = 5: The primary orientation of the data on disk is in the sagittal
% plane relative to the object scanned. Most commonly, the fastest moving
% index through the voxels that are part of this sagittal image would span the
% posterior-anterior extent of the structure imaged, with the next fastest
% moving index spanning the *superior-inferior* extent of the structure. This
% 'orient' flag would indicate to Analyze that this data should be placed in
% the Y-Z plane of the 3D Analyze Coordinate System, with the X dimension
% being the slice direction.
% For the 'sagittal flipped' type, the voxels are stored with
% Pixels in 'y' axis (varies fastest) - from patient posterior to Anterior
% Rows in 'z' axis - from patient superior to Inferior*
% Slices in 'x' axis - from patient right to Left
if verbose, fprintf('...reading sagittal flipped (+Z from Superior to Inferior)\n'); end
avw.img = zeros(SliceDim,PixelDim,RowDim);
n = 1;
y = 1:PixelDim;
for x = 1:SliceDim,
for z = RowDim:-1:1, % flip in Z, read S2I file into I2S 3D matrix
% load a flipped Z row of Y values into X slice avw.img
avw.img(x,y,z) = tmp(n:n+(PixelDim-1));
n = n + PixelDim;
end
end
% rearrange avw.hdr.dime.dim or avw.hdr.dime.pixdim
avw.hdr.dime.dim(2:4) = int16([SliceDim,PixelDim,RowDim]);
avw.hdr.dime.pixdim(2:4) = single([SliceSz,PixelSz,RowSz]);
otherwise
error('unknown value in avw.hdr.hist.orient, try explicit IMGorient option.');
end
if verbose, t=toc; fprintf('...done (%5.2f sec).\n\n',t); end
return
% This function attempts to read the orientation of the
% Analyze file according to the hdr.hist.orient field of the
% header. Unfortunately, this field is optional and not
% all programs will set it correctly, so there is no guarantee,
% that the data loaded will be correctly oriented. If necessary,
% experiment with the 'orient' option to read the .img
% data into the 3D matrix of avw.img as preferred.
%
% (Conventions gathered from e-mail with [email protected])
%
% 0 transverse unflipped
% X direction first, progressing from patient right to left,
% Y direction second, progressing from patient posterior to anterior,
% Z direction third, progressing from patient inferior to superior.
% 1 coronal unflipped
% X direction first, progressing from patient right to left,
% Z direction second, progressing from patient inferior to superior,
% Y direction third, progressing from patient posterior to anterior.
% 2 sagittal unflipped
% Y direction first, progressing from patient posterior to anterior,
% Z direction second, progressing from patient inferior to superior,
% X direction third, progressing from patient right to left.
% 3 transverse flipped
% X direction first, progressing from patient right to left,
% Y direction second, progressing from patient anterior to posterior,
% Z direction third, progressing from patient inferior to superior.
% 4 coronal flipped
% X direction first, progressing from patient right to left,
% Z direction second, progressing from patient superior to inferior,
% Y direction third, progressing from patient posterior to anterior.
% 5 sagittal flipped
% Y direction first, progressing from patient posterior to anterior,
% Z direction second, progressing from patient superior to inferior,
% X direction third, progressing from patient right to left.
%----------------------------------------------------------------------------
% From ANALYZE documentation...
%
% The ANALYZE coordinate system has an origin in the lower left
% corner. That is, with the subject lying supine, the coordinate
% origin is on the right side of the body (x), at the back (y),
% and at the feet (z). This means that:
%
% +X increases from right (R) to left (L)
% +Y increases from the back (posterior,P) to the front (anterior, A)
% +Z increases from the feet (inferior,I) to the head (superior, S)
%
% The LAS orientation is the radiological convention, where patient
% left is on the image right. The alternative neurological
% convention is RAS (also Talairach convention).
%
% A major advantage of the Analzye origin convention is that the
% coordinate origin of each orthogonal orientation (transverse,
% coronal, and sagittal) lies in the lower left corner of the
% slice as it is displayed.
%
% Orthogonal slices are numbered from one to the number of slices
% in that orientation. For example, a volume (x, y, z) dimensioned
% 128, 256, 48 has:
%
% 128 sagittal slices numbered 1 through 128 (X)
% 256 coronal slices numbered 1 through 256 (Y)
% 48 transverse slices numbered 1 through 48 (Z)
%
% Pixel coordinates are made with reference to the slice numbers from
% which the pixels come. Thus, the first pixel in the volume is
% referenced p(1,1,1) and not at p(0,0,0).
%
% Transverse slices are in the XY plane (also known as axial slices).
% Sagittal slices are in the ZY plane.
% Coronal slices are in the ZX plane.
%
%----------------------------------------------------------------------------
%----------------------------------------------------------------------------
% E-mail from [email protected]
%
% The 'orient' field in the data_history structure specifies the primary
% orientation of the data as it is stored in the file on disk. This usually
% corresponds to the orientation in the plane of acquisition, given that this
% would correspond to the order in which the data is written to disk by the
% scanner or other software application. As you know, this field will contain
% the values:
%
% orient = 0 transverse unflipped
% 1 coronal unflipped
% 2 sagittal unflipped
% 3 transverse flipped
% 4 coronal flipped
% 5 sagittal flipped
%
% It would be vary rare that you would ever encounter any old Analyze 7.5
% files that contain values of 'orient' which indicate that the data has been
% 'flipped'. The 'flipped flag' values were really only used internal to
% Analyze to precondition data for fast display in the Movie module, where the
% images were actually flipped vertically in order to accommodate the raster
% paint order on older graphics devices. The only cases you will encounter
% will have values of 0, 1, or 2.
%
% As mentioned, the 'orient' flag only specifies the primary orientation of
% data as stored in the disk file itself. It has nothing to do with the
% representation of the data in the 3D Analyze coordinate system, which always
% has a fixed representation to the data. The meaning of the 'orient' values
% should be interpreted as follows:
%
% orient = 0: The primary orientation of the data on disk is in the
% transverse plane relative to the object scanned. Most commonly, the fastest
% moving index through the voxels that are part of this transverse image would
% span the right-left extent of the structure imaged, with the next fastest
% moving index spanning the posterior-anterior extent of the structure. This
% 'orient' flag would indicate to Analyze that this data should be placed in
% the X-Y plane of the 3D Analyze Coordinate System, with the Z dimension
% being the slice direction.
%
% orient = 1: The primary orientation of the data on disk is in the coronal
% plane relative to the object scanned. Most commonly, the fastest moving
% index through the voxels that are part of this coronal image would span the
% right-left extent of the structure imaged, with the next fastest moving
% index spanning the inferior-superior extent of the structure. This 'orient'
% flag would indicate to Analyze that this data should be placed in the X-Z
% plane of the 3D Analyze Coordinate System, with the Y dimension being the
% slice direction.
%
% orient = 2: The primary orientation of the data on disk is in the sagittal
% plane relative to the object scanned. Most commonly, the fastest moving
% index through the voxels that are part of this sagittal image would span the
% posterior-anterior extent of the structure imaged, with the next fastest
% moving index spanning the inferior-superior extent of the structure. This
% 'orient' flag would indicate to Analyze that this data should be placed in
% the Y-Z plane of the 3D Analyze Coordinate System, with the X dimension
% being the slice direction.
%
% Orient values 3-5 have the second index reversed in order, essentially
% 'flipping' the images relative to what would most likely become the vertical
% axis of the displayed image.
%
% Hopefully you understand the difference between the indication this 'orient'
% flag has relative to data stored on disk and the full 3D Analyze Coordinate
% System for data that is managed as a volume image. As mentioned previously,
% the orientation of patient anatomy in the 3D Analyze Coordinate System has a
% fixed orientation relative to each of the orthogonal axes. This orientation
% is completely described in the information that is attached, but the basics
% are:
%
% Left-handed coordinate system
%
% X-Y plane is Transverse
% X-Z plane is Coronal
% Y-Z plane is Sagittal
%
% X axis runs from patient right (low X) to patient left (high X)
% Y axis runs from posterior (low Y) to anterior (high Y)
% Z axis runs from inferior (low Z) to superior (high Z)
%
%----------------------------------------------------------------------------
%----------------------------------------------------------------------------
% SPM2 NOTES from spm2 webpage: One thing to watch out for is the image
% orientation. The proper Analyze format uses a left-handed co-ordinate
% system, whereas Talairach uses a right-handed one. In SPM99, images were
% flipped at the spatial normalisation stage (from one co-ordinate system
% to the other). In SPM2b, a different approach is used, so that either a
% left- or right-handed co-ordinate system is used throughout. The SPM2b
% program is told about the handedness that the images are stored with by
% the spm_flip_analyze_images.m function and the defaults.analyze.flip
% parameter that is specified in the spm_defaults.m file. These files are
% intended to be customised for each site. If you previously used SPM99
% and your images were flipped during spatial normalisation, then set
% defaults.analyze.flip=1. If no flipping took place, then set
% defaults.analyze.flip=0. Check that when using the Display facility
% (possibly after specifying some rigid-body rotations) that:
%
% The top-left image is coronal with the top (superior) of the head displayed
% at the top and the left shown on the left. This is as if the subject is viewed
% from behind.
%
% The bottom-left image is axial with the front (anterior) of the head at the
% top and the left shown on the left. This is as if the subject is viewed from above.
%
% The top-right image is sagittal with the front (anterior) of the head at the
% left and the top of the head shown at the top. This is as if the subject is
% viewed from the left.
%----------------------------------------------------------------------------
|
github
|
philippboehmsturm/antx-master
|
read_yokogawa_event.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_yokogawa_event.m
| 7,112 |
utf_8
|
a70ad744018275d54a5de06fbcc9d1ff
|
function [event] = read_yokogawa_event(filename, varargin)
% READ_YOKOGAWA_EVENT reads event information from continuous,
% epoched or averaged MEG data that has been generated by the Yokogawa
% MEG system and software and allows those events to be used in
% combination with FieldTrip.
%
% Use as
% [event] = read_yokogawa_event(filename)
%
% See also READ_YOKOGAWA_HEADER, READ_YOKOGAWA_DATA
% Copyright (C) 2005, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_yokogawa_event.m 7123 2012-12-06 21:21:38Z roboos $
event = [];
handles = definehandles;
% get the options, the default is set below
trigindx = ft_getopt(varargin, 'trigindx');
threshold = ft_getopt(varargin, 'threshold');
detectflank = ft_getopt(varargin, 'detectflank');
% ensure that the required toolbox is on the path
if ft_hastoolbox('yokogawa_meg_reader');
% read the dataset header
hdr = read_yokogawa_header_new(filename);
ch_info = hdr.orig.channel_info.channel;
type = [ch_info.type];
% determine the trigger channels (if not specified by the user)
if isempty(trigindx)
trigindx = find(type==handles.TriggerChannel);
end
% Use the MEG Reader documentation if more detailed support is
% required.
if hdr.orig.acq_type==handles.AcqTypeEvokedRaw
% read the trigger id from all trials
event = getYkgwHdrEvent(filename);
% use the standard FieldTrip header for trial events
% make an event for each trial as defined in the header
for i=1:hdr.nTrials
event(end+1).type = 'trial';
event(end ).sample = (i-1)*hdr.nSamples + 1;
event(end ).offset = -hdr.nSamplesPre;
event(end ).duration = hdr.nSamples;
if ~isempty(value)
event(end ).value = event(i).code;
end
end
% Use the MEG Reader documentation if more detailed support is required.
elseif hdr.orig.acq_type==handles.AcqTypeEvokedAve
% make an event for the average
event(1).type = 'average';
event(1).sample = 1;
event(1).offset = -hdr.nSamplesPre;
event(1).duration = hdr.nSamples;
elseif hdr.orig.acq_type==handles.AcqTypeContinuousRaw
% the data structure does not contain events, but flank detection on the trigger channel might reveal them
% this is done below for all formats
end
elseif ft_hastoolbox('yokogawa');
% read the dataset header
hdr = read_yokogawa_header(filename);
% determine the trigger channels (if not specified by the user)
if isempty(trigindx)
trigindx = find(hdr.orig.channel_info(:,2)==handles.TriggerChannel);
end
if hdr.orig.acq_type==handles.AcqTypeEvokedRaw
% read the trigger id from all trials
fid = fopen(filename, 'r');
value = GetMeg160TriggerEventM(fid);
fclose(fid);
% use the standard FieldTrip header for trial events
% make an event for each trial as defined in the header
for i=1:hdr.nTrials
event(end+1).type = 'trial';
event(end ).sample = (i-1)*hdr.nSamples + 1;
event(end ).offset = -hdr.nSamplesPre;
event(end ).duration = hdr.nSamples;
if ~isempty(value)
event(end ).value = value(i);
end
end
elseif hdr.orig.acq_type==handles.AcqTypeEvokedAve
% make an event for the average
event(1).type = 'average';
event(1).sample = 1;
event(1).offset = -hdr.nSamplesPre;
event(1).duration = hdr.nSamples;
elseif hdr.orig.acq_type==handles.AcqTypeContinuousRaw
% the data structure does not contain events, but flank detection on the trigger channel might reveal them
% this is done below for all formats
end
else
error('cannot determine, whether Yokogawa toolbox is present');
end
% read the trigger channels and detect the flanks
if ~isempty(trigindx)
trigger = read_trigger(filename, 'header', hdr, 'denoise', false, 'chanindx', trigindx, 'detectflank', detectflank, 'threshold', threshold);
% combine the triggers and the other events
event = appendevent(event, trigger);
end
if isempty(event)
warning('no triggers were detected, please specify the "trigindx" option');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% this defines some usefull constants
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function handles = definehandles;
handles.output = [];
handles.sqd_load_flag = false;
handles.mri_load_flag = false;
handles.NullChannel = 0;
handles.MagnetoMeter = 1;
handles.AxialGradioMeter = 2;
handles.PlannerGradioMeter = 3;
handles.RefferenceChannelMark = hex2dec('0100');
handles.RefferenceMagnetoMeter = bitor( handles.RefferenceChannelMark, handles.MagnetoMeter );
handles.RefferenceAxialGradioMeter = bitor( handles.RefferenceChannelMark, handles.AxialGradioMeter );
handles.RefferencePlannerGradioMeter = bitor( handles.RefferenceChannelMark, handles.PlannerGradioMeter );
handles.TriggerChannel = -1;
handles.EegChannel = -2;
handles.EcgChannel = -3;
handles.EtcChannel = -4;
handles.NonMegChannelNameLength = 32;
handles.DefaultMagnetometerSize = (4.0/1000.0); % Square of 4.0mm in length
handles.DefaultAxialGradioMeterSize = (15.5/1000.0); % Circle of 15.5mm in diameter
handles.DefaultPlannerGradioMeterSize = (12.0/1000.0); % Square of 12.0mm in length
handles.AcqTypeContinuousRaw = 1;
handles.AcqTypeEvokedAve = 2;
handles.AcqTypeEvokedRaw = 3;
handles.sqd = [];
handles.sqd.selected_start = [];
handles.sqd.selected_end = [];
handles.sqd.axialgradiometer_ch_no = [];
handles.sqd.axialgradiometer_ch_info = [];
handles.sqd.axialgradiometer_data = [];
handles.sqd.plannergradiometer_ch_no = [];
handles.sqd.plannergradiometer_ch_info = [];
handles.sqd.plannergradiometer_data = [];
handles.sqd.eegchannel_ch_no = [];
handles.sqd.eegchannel_data = [];
handles.sqd.nullchannel_ch_no = [];
handles.sqd.nullchannel_data = [];
handles.sqd.selected_time = [];
handles.sqd.sample_rate = [];
handles.sqd.sample_count = [];
handles.sqd.pretrigger_length = [];
handles.sqd.matching_info = [];
handles.sqd.source_info = [];
handles.sqd.mri_info = [];
handles.mri = [];
|
github
|
philippboehmsturm/antx-master
|
read_4d_hdr.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_4d_hdr.m
| 25,611 |
utf_8
|
77cce2d47b4c91e12a33138b871a54d0
|
function [header] = read_4d_hdr(datafile, configfile)
% hdr=READ_4D_HDR(datafile, configfile)
% Collects the required Fieldtrip header data from the data file 'filename'
% and the associated 'config' file for that data.
%
% Adapted from the MSI>>Matlab code written by Eugene Kronberg
% Copyright (C) 2008-2009, Centre for Cognitive Neuroimaging, Glasgow, Gavin Paterson & J.M.Schoffelen
% Copyright (C) 2010-2011, Donders Institute for Brain, Cognition and Behavior, J.M.Schoffelen
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_4d_hdr.m 7238 2012-12-20 19:53:52Z jansch $
%read header
if nargin ~= 2
[path, file, ext] = fileparts(datafile);
configfile = fullfile(path, 'config');
end
if ~isempty(datafile),
%always big endian
fid = fopen(datafile, 'r', 'b');
if fid == -1
error('Cannot open file %s', datafile);
end
fseek(fid, 0, 'eof');
header_end = ftell(fid);
%last 8 bytes of the pdf is header offset
fseek(fid, -8, 'eof');
header_offset = fread(fid,1,'uint64');
%first byte of the header
fseek(fid, header_offset, 'bof');
% read header data
align_file_pointer(fid)
header.header_data.FileType = fread(fid, 1, 'uint16=>uint16');
file_type = char(fread(fid, 5, 'uchar'))';
header.header_data.file_type = file_type(file_type>0);
fseek(fid, 1, 'cof');
format = fread(fid, 1, 'int16=>int16');
switch format
case 1
header.header_data.Format = 'SHORT';
case 2
header.header_data.Format = 'LONG';
case 3
header.header_data.Format = 'FLOAT';
case 4
header.header_data.Format ='DOUBLE';
end
header.header_data.acq_mode = fread(fid, 1, 'uint16=>uint16');
header.header_data.TotalEpochs = fread(fid, 1, 'uint32=>double');
header.header_data.input_epochs = fread(fid, 1, 'uint32=>uint32');
header.header_data.TotalEvents = fread(fid, 1, 'uint32=>uint32');
header.header_data.total_fixed_events = fread(fid, 1, 'uint32=>uint32');
header.header_data.SamplePeriod = fread(fid, 1, 'float32=>float64');
header.header_data.SampleFrequency = 1/header.header_data.SamplePeriod;
xaxis_label = char(fread(fid, 16, 'uchar'))';
header.header_data.xaxis_label = xaxis_label(xaxis_label>0);
header.header_data.total_processes = fread(fid, 1, 'uint32=>uint32');
header.header_data.TotalChannels = fread(fid, 1, 'uint16=>double');
fseek(fid, 2, 'cof');
header.header_data.checksum = fread(fid, 1, 'int32=>int32');
header.header_data.total_ed_classes = fread(fid, 1, 'uint32=>uint32');
header.header_data.total_associated_files = fread(fid, 1, 'uint16=>uint16');
header.header_data.last_file_index = fread(fid, 1, 'uint16=>uint16');
header.header_data.timestamp = fread(fid, 1, 'uint32=>uint32');
header.header_data.reserved = fread(fid, 20, 'uchar')';
fseek(fid, 4, 'cof');
%read epoch_data
for epoch = 1:header.header_data.TotalEpochs;
align_file_pointer(fid)
header.epoch_data(epoch).pts_in_epoch = fread(fid, 1, 'uint32=>uint32');
header.epoch_data(epoch).epoch_duration = fread(fid, 1, 'float32=>float32');
header.epoch_data(epoch).expected_iti = fread(fid, 1, 'float32=>float32');
header.epoch_data(epoch).actual_iti = fread(fid, 1, 'float32=>float32');
header.epoch_data(epoch).total_var_events = fread(fid, 1, 'uint32=>uint32');
header.epoch_data(epoch).checksum = fread(fid, 1, 'int32=>int32');
header.epoch_data(epoch).epoch_timestamp = fread(fid, 1, 'int32=>int32');
header.epoch_data(epoch).reserved = fread(fid, 28, 'uchar')';
header.header_data.SlicesPerEpoch = double(header.epoch_data(1).pts_in_epoch);
%read event data (var_events)
for event = 1:header.epoch_data(epoch).total_var_events
align_file_pointer(fid)
event_name = char(fread(fid, 16, 'uchar'))';
header.epoch_data(epoch).var_event{event}.event_name = event_name(event_name>0);
header.epoch_data(epoch).var_event{event}.start_lat = fread(fid, 1, 'float32=>float32');
header.epoch_data(epoch).var_event{event}.end_lat = fread(fid, 1, 'float32=>float32');
header.epoch_data(epoch).var_event{event}.step_size = fread(fid, 1, 'float32=>float32');
header.epoch_data(epoch).var_event{event}.fixed_event = fread(fid, 1, 'uint16=>uint16');
fseek(fid, 2, 'cof');
header.epoch_data(epoch).var_event{event}.checksum = fread(fid, 1, 'int32=>int32');
header.epoch_data(epoch).var_event{event}.reserved = fread(fid, 32, 'uchar')';
fseek(fid, 4, 'cof');
end
end
%read channel ref data
for channel = 1:header.header_data.TotalChannels
align_file_pointer(fid)
chan_label = (fread(fid, 16, 'uint8=>char'))';
header.channel_data(channel).chan_label = chan_label(chan_label>0);
header.channel_data(channel).chan_no = fread(fid, 1, 'uint16=>uint16');
header.channel_data(channel).attributes = fread(fid, 1, 'uint16=>uint16');
header.channel_data(channel).scale = fread(fid, 1, 'float32=>float32');
yaxis_label = char(fread(fid, 16, 'uint8=>char'))';
header.channel_data(channel).yaxis_label = yaxis_label(yaxis_label>0);
header.channel_data(channel).valid_min_max = fread(fid, 1, 'uint16=>uint16');
fseek(fid, 6, 'cof');
header.channel_data(channel).ymin = fread(fid, 1, 'float64');
header.channel_data(channel).ymax = fread(fid, 1, 'float64');
header.channel_data(channel).index = fread(fid, 1, 'uint32=>uint32');
header.channel_data(channel).checksum = fread(fid, 1, 'int32=>int32');
header.channel_data(channel).whatisit = char(fread(fid, 4, 'uint8=>char'))';
header.channel_data(channel).reserved = fread(fid, 28, 'uint8')';
end
%read event data
for event = 1:header.header_data.total_fixed_events
align_file_pointer(fid)
event_name = char(fread(fid, 16, 'uchar'))';
header.event_data(event).event_name = event_name(event_name>0);
header.event_data(event).start_lat = fread(fid, 1, 'float32=>float32');
header.event_data(event).end_lat = fread(fid, 1, 'float32=>float32');
header.event_data(event).step_size = fread(fid, 1, 'float32=>float32');
header.event_data(event).fixed_event = fread(fid, 1, 'uint16=>uint16');
fseek(fid, 2, 'cof');
header.event_data(event).checksum = fread(fid, 1, 'int32=>int32');
header.event_data(event).reserved = fread(fid, 32, 'uchar')';
fseek(fid, 4, 'cof');
end
header.header_data.FirstLatency = double(header.event_data(1).start_lat);
%experimental: read process information
for np = 1:header.header_data.total_processes
align_file_pointer(fid)
nbytes = fread(fid, 1, 'uint32=>uint32');
fp = ftell(fid);
header.process(np).hdr.nbytes = nbytes;
type = char(fread(fid, 20, 'uchar'))';
header.process(np).hdr.type = type(type>0);
header.process(np).hdr.checksum = fread(fid, 1, 'int32=>int32');
user = char(fread(fid, 32, 'uchar'))';
header.process(np).user = user(user>0);
header.process(np).timestamp = fread(fid, 1, 'uint32=>uint32');
fname = char(fread(fid, 32, 'uchar'))';
header.process(np).filename = fname(fname>0);
fseek(fid, 28*8, 'cof'); %dont know
header.process(np).totalsteps = fread(fid, 1, 'uint32=>uint32');
header.process(np).checksum = fread(fid, 1, 'int32=>int32');
header.process(np).reserved = fread(fid, 32, 'uchar')';
for ns = 1:header.process(np).totalsteps
align_file_pointer(fid)
nbytes2 = fread(fid, 1, 'uint32=>uint32');
header.process(np).step(ns).hdr.nbytes = nbytes2;
type = char(fread(fid, 20, 'uchar'))';
header.process(np).step(ns).hdr.type = type(type>0); %dont know how to interpret the first two
header.process(np).step(ns).hdr.checksum = fread(fid, 1, 'int32=>int32');
userblocksize = fread(fid, 1, 'int32=>int32'); %we are at 32 bytes here
header.process(np).step(ns).userblocksize = userblocksize;
fseek(fid, nbytes2 - 32, 'cof');
if strcmp(header.process(np).step(ns).hdr.type, 'PDF_Weight_Table'),
warning('reading in weight table: no warranty that this is correct. it seems to work for the Glasgow 248-magnetometer system. if you have some code yourself, and/or would like to test it on your own data, please contact Jan-Mathijs');
tmpfp = ftell(fid);
tmp = fread(fid, 1, 'uint8');
Nchan = fread(fid, 1, 'uint32');
Nref = fread(fid, 1, 'uint32');
for k = 1:Nref
name = fread(fid, 17, 'uchar'); %strange number, but seems to be true
header.process(np).step(ns).RefChan{k,1} = char(name(name>0))';
end
fseek(fid, 152, 'cof');
for k = 1:Nchan
name = fread(fid, 17, 'uchar');
header.process(np).step(ns).Chan{k,1} = char(name(name>0))';
end
%fseek(fid, 20, 'cof');
%fseek(fid, 4216, 'cof');
header.process(np).step(ns).stuff1 = fread(fid, 4236, 'uint8');
name = fread(fid, 16, 'uchar');
header.process(np).step(ns).Creator = char(name(name>0))';
%some stuff I don't understand yet
%fseek(fid, 136, 'cof');
header.process(np).step(ns).stuff2 = fread(fid, 136, 'uint8');
%now something strange is going to happen: the weights are probably little-endian encoded.
%here we go: check whether this applies to the whole PDF weight table
fp = ftell(fid);
fclose(fid);
fid = fopen(datafile, 'r', 'l');
fseek(fid, fp, 'bof');
for k = 1:Nchan
header.process(np).step(ns).Weights(k,:) = fread(fid, 23, 'float32=>float32')';
fseek(fid, 36, 'cof');
end
else
if userblocksize < 1e6,
%for one reason or another userblocksize can assume strangely high values
fseek(fid, userblocksize, 'cof');
end
end
end
end
fclose(fid);
end
%end read header
%read config file
fid = fopen(configfile, 'r', 'b');
if fid == -1
error('Cannot open config file');
end
header.config_data.version = fread(fid, 1, 'uint16=>uint16');
site_name = char(fread(fid, 32, 'uchar'))';
header.config_data.site_name = site_name(site_name>0);
dap_hostname = char(fread(fid, 16, 'uchar'))';
header.config_data.dap_hostname = dap_hostname(dap_hostname>0);
header.config_data.sys_type = fread(fid, 1, 'uint16=>uint16');
header.config_data.sys_options = fread(fid, 1, 'uint32=>uint32');
header.config_data.supply_freq = fread(fid, 1, 'uint16=>uint16');
header.config_data.total_chans = fread(fid, 1, 'uint16=>uint16');
header.config_data.system_fixed_gain = fread(fid, 1, 'float32=>float32');
header.config_data.volts_per_bit = fread(fid, 1, 'float32=>float32');
header.config_data.total_sensors = fread(fid, 1, 'uint16=>uint16');
header.config_data.total_user_blocks = fread(fid, 1, 'uint16=>uint16');
header.config_data.next_derived_channel_number = fread(fid, 1, 'uint16=>uint16');
fseek(fid, 2, 'cof');
header.config_data.checksum = fread(fid, 1, 'int32=>int32');
header.config_data.reserved = fread(fid, 32, 'uchar=>uchar')';
header.config.Xfm = fread(fid, [4 4], 'double');
%user blocks
for ub = 1:header.config_data.total_user_blocks
align_file_pointer(fid)
header.user_block_data{ub}.hdr.nbytes = fread(fid, 1, 'uint32=>uint32');
type = char(fread(fid, 20, 'uchar'))';
header.user_block_data{ub}.hdr.type = type(type>0);
header.user_block_data{ub}.hdr.checksum = fread(fid, 1, 'int32=>int32');
user = char(fread(fid, 32, 'uchar'))';
header.user_block_data{ub}.user = user(user>0);
header.user_block_data{ub}.timestamp = fread(fid, 1, 'uint32=>uint32');
header.user_block_data{ub}.user_space_size = fread(fid, 1, 'uint32=>uint32');
header.user_block_data{ub}.reserved = fread(fid, 32, 'uchar=>uchar')';
fseek(fid, 4, 'cof');
user_space_size = double(header.user_block_data{ub}.user_space_size);
if strcmp(type(type>0), 'B_weights_used'),
%warning('reading in weight table: no warranty that this is correct. it seems to work for the Glasgow 248-magnetometer system. if you have some code yourself, and/or would like to test it on your own data, please contact Jan-Mathijs');
tmpfp = ftell(fid);
%read user_block_data weights
%there is information in the 4th and 8th byte, these might be related to the settings?
version = fread(fid, 1, 'uint32');
header.user_block_data{ub}.version = version;
if version==1,
Nbytes = fread(fid,1,'uint32');
Nchan = fread(fid,1,'uint32');
Position = fread(fid, 32, 'uchar');
header.user_block_data{ub}.position = char(Position(Position>0))';
fseek(fid,tmpfp+user_space_size - Nbytes*Nchan, 'bof');
Ndigital = floor((Nbytes - 4*2) / 4);
Nanalog = 3; %lucky guess?
% how to know number of analog weights vs digital weights???
for ch = 1:Nchan
% for Konstanz -- comment for others?
header.user_block_data{ub}.aweights(ch,:) = fread(fid, [1 Nanalog], 'int16')';
fseek(fid,2,'cof'); % alignment
header.user_block_data{ub}.dweights(ch,:) = fread(fid, [1 Ndigital], 'single=>double')';
end
fseek(fid, tmpfp, 'bof');
%there is no information with respect to the channels here.
%the best guess would be to assume the order identical to the order in header.config.channel_data
%for the digital weights it would be the order of the references in that list
%for the analog weights I would not know
elseif version==2,
unknown2 = fread(fid, 1, 'uint32');
Nchan = fread(fid, 1, 'uint32');
Position = fread(fid, 32, 'uchar');
header.user_block_data{ub}.position = char(Position(Position>0))';
fseek(fid, tmpfp+124, 'bof');
Nanalog = fread(fid, 1, 'uint32');
Ndigital = fread(fid, 1, 'uint32');
fseek(fid, tmpfp+204, 'bof');
for k = 1:Nchan
Name = fread(fid, 16, 'uchar');
header.user_block_data{ub}.channames{k,1} = char(Name(Name>0))';
end
for k = 1:Nanalog
Name = fread(fid, 16, 'uchar');
header.user_block_data{ub}.arefnames{k,1} = char(Name(Name>0))';
end
for k = 1:Ndigital
Name = fread(fid, 16, 'uchar');
header.user_block_data{ub}.drefnames{k,1} = char(Name(Name>0))';
end
header.user_block_data{ub}.dweights = fread(fid, [Ndigital Nchan], 'single=>double')';
header.user_block_data{ub}.aweights = fread(fid, [Nanalog Nchan], 'int16')';
fseek(fid, tmpfp, 'bof');
end
elseif strcmp(type(type>0), 'B_E_table_used'),
%warning('reading in weight table: no warranty that this is correct');
%tmpfp = ftell(fid);
%fseek(fid, 4, 'cof'); %there's info here dont know how to interpret
%Nx = fread(fid, 1, 'uint32');
%Nchan = fread(fid, 1, 'uint32');
%type = fread(fid, 32, 'uchar'); %don't know whether correct
%header.user_block_data{ub}.type = char(type(type>0))';
%fseek(fid, 16, 'cof');
%for k = 1:Nchan
% name = fread(fid, 16, 'uchar');
% header.user_block_data{ub}.name{k,1} = char(name(name>0))';
%end
elseif strcmp(type(type>0), 'B_COH_Points'),
tmpfp = ftell(fid);
Ncoil = fread(fid, 1, 'uint32');
N = fread(fid, 1, 'uint32');
coils = fread(fid, [7 Ncoil], 'double');
header.user_block_data{ub}.pnt = coils(1:3,:)';
header.user_block_data{ub}.ori = coils(4:6,:)';
header.user_block_data{ub}.Ncoil = Ncoil;
header.user_block_data{ub}.N = N;
tmp = fread(fid, (904-288)/8, 'double');
header.user_block_data{ub}.tmp = tmp; %FIXME try to find out what these bytes mean
fseek(fid, tmpfp, 'bof');
elseif strcmp(type(type>0), 'b_ccp_xfm_block'),
tmpfp = ftell(fid);
tmp1 = fread(fid, 1, 'uint32');
%tmp = fread(fid, [4 4], 'double');
%tmp = fread(fid, [4 4], 'double');
%the next part seems to be in little endian format (at least when I tried)
tmp = fread(fid, 128, 'uint8');
tmp = uint8(reshape(tmp, [8 16])');
xfm = zeros(4,4);
for k = 1:size(tmp,1)
xfm(k) = typecast(tmp(k,:), 'double');
if abs(xfm(k))<1e-10 || abs(xfm(k))>1e10, xfm(k) = typecast(fliplr(tmp(k,:)), 'double');end
end
fseek(fid, tmpfp, 'bof'); %FIXME try to find out why this looks so strange
elseif strcmp(type(type>0), 'b_eeg_elec_locs'),
%this block contains the digitized coil and electrode positions
tmpfp = ftell(fid);
Npoints = user_space_size./40;
for k = 1:Npoints
tmp = fread(fid, 16, 'uchar');
%tmplabel = char(tmp(tmp>47 & tmp<128)'); %stick to plain ASCII
% store up until the first space
tmplabel = char(tmp(1:max(1,(find(tmp==0,1,'first')-1)))'); %stick to plain ASCII
%if strmatch('Coil', tmplabel),
% label{k} = tmplabel(1:5);
%elseif ismember(tmplabel(1), {'L' 'R' 'C' 'N' 'I'}),
% label{k} = tmplabel(1);
%else
% label{k} = '';
%end
label{k} = tmplabel;
tmp = fread(fid, 3, 'double');
pnt(k,:) = tmp(:)';
end
% post-processing of the labels
% it seems the following can happen
% - a sequence of L R N C I, i.e. the coordinate system defining landmarks
for k = 1:numel(label)
firstletter(k) = label{k}(1);
end
sel = strfind(firstletter, 'LRNCI');
if ~isempty(sel)
label{sel} = label{sel}(1);
label{sel+1} = label{sel+1}(1);
label{sel+2} = label{sel+2}(1);
label{sel+3} = label{sel+3}(1);
label{sel+4} = label{sel+4}(1);
end
% - a sequence of coil1...coil5 i.e. the localization coils
for k = 1:numel(label)
if strncmpi(label{k},'coil',4)
label{k} = label{k}(1:5);
end
end
% - something else: EEG electrodes?
header.user_block_data{ub}.label = label(:);
header.user_block_data{ub}.pnt = pnt;
fseek(fid, tmpfp, 'bof');
end
fseek(fid, user_space_size, 'cof');
end
%channels
for ch = 1:header.config_data.total_chans
align_file_pointer(fid)
name = char(fread(fid, 16, 'uchar'))';
header.config.channel_data(ch).name = name(name>0);
%FIXME this is a very dirty fix to get the reading in of continuous headlocalization
%correct. At the moment, the numbering of the hmt related channels seems to start with 1000
%which I don't understand, but seems rather nonsensical.
chan_no = fread(fid, 1, 'uint16=>uint16');
if chan_no > header.config_data.total_chans,
%FIXME fix the number in header.channel_data as well
sel = find([header.channel_data.chan_no]== chan_no);
if ~isempty(sel),
chan_no = ch;
header.channel_data(sel).chan_no = chan_no;
header.channel_data(sel).chan_label = header.config.channel_data(ch).name;
else
%does not matter
end
end
header.config.channel_data(ch).chan_no = chan_no;
header.config.channel_data(ch).type = fread(fid, 1, 'uint16=>uint16');
header.config.channel_data(ch).sensor_no = fread(fid, 1, 'int16=>int16');
fseek(fid, 2, 'cof');
header.config.channel_data(ch).gain = fread(fid, 1, 'float32=>float32');
header.config.channel_data(ch).units_per_bit = fread(fid, 1, 'float32=>float32');
yaxis_label = char(fread(fid, 16, 'uchar'))';
header.config.channel_data(ch).yaxis_label = yaxis_label(yaxis_label>0);
header.config.channel_data(ch).aar_val = fread(fid, 1, 'double');
header.config.channel_data(ch).checksum = fread(fid, 1, 'int32=>int32');
header.config.channel_data(ch).reserved = fread(fid, 32, 'uchar=>uchar')';
fseek(fid, 4, 'cof');
align_file_pointer(fid)
header.config.channel_data(ch).device_data.hdr.size = fread(fid, 1, 'uint32=>uint32');
header.config.channel_data(ch).device_data.hdr.checksum = fread(fid, 1, 'int32=>int32');
header.config.channel_data(ch).device_data.hdr.reserved = fread(fid, 32, 'uchar=>uchar')';
switch header.config.channel_data(ch).type
case {1, 3}%meg/ref
header.config.channel_data(ch).device_data.inductance = fread(fid, 1, 'float32=>float32');
fseek(fid, 4, 'cof');
header.config.channel_data(ch).device_data.Xfm = fread(fid, [4 4], 'double');
header.config.channel_data(ch).device_data.xform_flag = fread(fid, 1, 'uint16=>uint16');
header.config.channel_data(ch).device_data.total_loops = fread(fid, 1, 'uint16=>uint16');
header.config.channel_data(ch).device_data.reserved = fread(fid, 32, 'uchar=>uchar')';
fseek(fid, 4, 'cof');
for loop = 1:header.config.channel_data(ch).device_data.total_loops
align_file_pointer(fid)
header.config.channel_data(ch).device_data.loop_data(loop).position = fread(fid, 3, 'double');
header.config.channel_data(ch).device_data.loop_data(loop).direction = fread(fid, 3, 'double');
header.config.channel_data(ch).device_data.loop_data(loop).radius = fread(fid, 1, 'double');
header.config.channel_data(ch).device_data.loop_data(loop).wire_radius = fread(fid, 1, 'double');
header.config.channel_data(ch).device_data.loop_data(loop).turns = fread(fid, 1, 'uint16=>uint16');
fseek(fid, 2, 'cof');
header.config.channel_data(ch).device_data.loop_data(loop).checksum = fread(fid, 1, 'int32=>int32');
header.config.channel_data(ch).device_data.loop_data(loop).reserved = fread(fid, 32, 'uchar=>uchar')';
end
case 2%eeg
header.config.channel_data(ch).device_data.impedance = fread(fid, 1, 'float32=>float32');
fseek(fid, 4, 'cof');
header.config.channel_data(ch).device_data.Xfm = fread(fid, [4 4], 'double');
header.config.channel_data(ch).device_data.reserved = fread(fid, 32, 'uchar=>uchar')';
case 4%external
header.config.channel_data(ch).device_data.user_space_size = fread(fid, 1, 'uint32=>uint32');
header.config.channel_data(ch).device_data.reserved = fread(fid, 32, 'uchar=>uchar')';
fseek(fid, 4, 'cof');
case 5%TRIGGER
header.config.channel_data(ch).device_data.user_space_size = fread(fid, 1, 'uint32=>uint32');
header.config.channel_data(ch).device_data.reserved = fread(fid, 32, 'uchar=>uchar')';
fseek(fid, 4, 'cof');
case 6%utility
header.config.channel_data(ch).device_data.user_space_size = fread(fid, 1, 'uint32=>uint32');
header.config.channel_data(ch).device_data.reserved = fread(fid, 32, 'uchar=>uchar')';
fseek(fid, 4, 'cof');
case 7%derived
header.config.channel_data(ch).device_data.user_space_size = fread(fid, 1, 'uint32=>uint32');
header.config.channel_data(ch).device_data.reserved = fread(fid, 32, 'uchar=>uchar')';
fseek(fid, 4, 'cof');
case 8%shorted
header.config.channel_data(ch).device_data.reserved = fread(fid, 32, 'uchar=>uchar')';
otherwise
error('Unknown device type: %d\n', header.config.channel_data(ch).type);
end
end
fclose(fid);
%end read config file
header.header_data.FileDescriptor = 0; %no obvious field to take this from
header.header_data.Events = 1;%no obvious field to take this from
header.header_data.EventCodes = 0;%no obvious field to take this from
if isfield(header, 'channel_data'),
header.ChannelGain = double([header.config.channel_data([header.channel_data.chan_no]).gain]');
header.ChannelUnitsPerBit = double([header.config.channel_data([header.channel_data.chan_no]).units_per_bit]');
%header.Channel = {header.config.channel_data([header.channel_data.chan_no]).name}';
header.Channel = {header.channel_data.chan_label}';
header.Format = header.header_data.Format;
end
function align_file_pointer(fid)
current_position = ftell(fid);
if mod(current_position, 8) ~= 0
offset = 8 - mod(current_position,8);
fseek(fid, offset, 'cof');
end
|
github
|
philippboehmsturm/antx-master
|
decode_nifti1.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/decode_nifti1.m
| 2,915 |
utf_8
|
32b6ac0b0549062ef13624ad21eb55e2
|
function H = decode_nifti1(blob)
% function H = decode_nifti1(blob)
%
% Decodes a NIFTI-1 header given as raw 348 bytes (uint8) into a Matlab structure
% that matches the C struct defined in nifti1.h, with the only difference that the
% variable length arrays "dim" and "pixdim" are cut off to the right size, e.g., the
% "dim" entry will only contain the relevant elements:
% dim[0..7]={3,64,64,18,x,x,x,x} in C would become dim=[64,64,18] in Matlab.
%
% WARNING: This function currently ignores endianness !!!
% (C) 2010 S.Klanke
if class(blob)~='uint8'
error 'Bad type for blob'
end
if length(blob)~=348
error 'Blob must be exactly 348 bytes long'
end
% see nift1.h for information on structure
H = [];
magic = char(blob(345:347));
if blob(348)~=0 | magic~='ni1' & magic~='n+1'
error 'Not a NIFTI-1 header!';
end
H.sizeof_hdr = typecast(blob(1:4),'int32');
H.data_type = cstr2matlab(blob(5:14));
H.db_name = cstr2matlab(blob(15:32));
H.extents = typecast(blob(33:36),'int32');
H.session_error = typecast(blob(37:38),'int16');
H.regular = blob(39);
H.dim_info = blob(40);
dim = typecast(blob(41:56),'int16');
H.dim = dim(2:dim(1)+1);
H.intent_p1 = typecast(blob(57:60),'single');
H.intent_p2 = typecast(blob(61:64),'single');
H.intent_p3 = typecast(blob(65:68),'single');
H.intent_code = typecast(blob(69:70),'int16');
H.datatype = typecast(blob(71:72),'int16');
H.bitpix = typecast(blob(73:74),'int16');
H.slice_start = typecast(blob(75:76),'int16');
pixdim = typecast(blob(77:108),'single');
H.qfac = pixdim(1);
H.pixdim = pixdim(2:dim(1)+1);
H.vox_offset = typecast(blob(109:112),'single');
H.scl_scope = typecast(blob(113:116),'single');
H.scl_inter = typecast(blob(117:120),'single');
H.slice_end = typecast(blob(121:122),'int16');
H.slice_code = blob(123);
H.xyzt_units = blob(124);
H.cal_max = typecast(blob(125:128),'single');
H.cal_min = typecast(blob(129:132),'single');
H.slice_duration = typecast(blob(133:136),'single');
H.toffset = typecast(blob(137:140),'single');
H.glmax = typecast(blob(141:144),'int32');
H.glmin = typecast(blob(145:148),'int32');
H.descrip = cstr2matlab(blob(149:228));
H.aux_file = cstr2matlab(blob(229:252));
H.qform_code = typecast(blob(253:254),'int16');
H.sform_code = typecast(blob(255:256),'int16');
quats = typecast(blob(257:280),'single');
H.quatern_b = quats(1);
H.quatern_c = quats(2);
H.quatern_d = quats(3);
H.quatern_x = quats(4);
H.quatern_y = quats(5);
H.quatern_z = quats(6);
trafo = typecast(blob(281:328),'single');
H.srow_x = trafo(1:4);
H.srow_y = trafo(5:8);
H.srow_z = trafo(9:12);
%H.S = [H.srow_x; H.srow_y; H.srow_z; 0 0 0 1];
H.intent_name = cstr2matlab(blob(329:344));
H.magic = magic;
function ms = cstr2matlab(cs)
if cs(1)==0
ms = '';
else
ind = find(cs==0);
if isempty(ind)
ms = char(cs)';
else
ms = char(cs(1:ind(1)-1))';
end
end
|
github
|
philippboehmsturm/antx-master
|
read_edf.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_edf.m
| 14,871 |
utf_8
|
f65668521c40899923c7b7feca756f23
|
function [dat] = read_edf(filename, hdr, begsample, endsample, chanindx)
% READ_EDF reads specified samples from an EDF continous datafile
% It neglects all trial boundaries as if the data was acquired in
% non-continous mode.
%
% Use as
% [hdr] = read_edf(filename);
% where
% filename name of the datafile, including the .bdf extension
% This returns a header structure with the following elements
% hdr.Fs sampling frequency
% hdr.nChans number of channels
% hdr.nSamples number of samples per trial
% hdr.nSamplesPre number of pre-trigger samples in each trial
% hdr.nTrials number of trials
% hdr.label cell-array with labels of each channel
% hdr.orig detailled EDF header information
%
% Or use as
% [dat] = read_edf(filename, hdr, begsample, endsample, chanindx);
% where
% filename name of the datafile, including the .bdf extension
% hdr header structure, see above
% begsample index of the first sample to read
% endsample index of the last sample to read
% chanindx index of channels to read (optional, default is all)
% This returns a Nchans X Nsamples data matrix
% Copyright (C) 2006, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_edf.m 7123 2012-12-06 21:21:38Z roboos $
needhdr = (nargin==1);
needevt = (nargin==2);
needdat = (nargin>3);
if needhdr
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% read the header, this code is from EEGLAB's openbdf
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
FILENAME = filename;
% defines Seperator for Subdirectories
SLASH='/';
BSLASH=char(92);
cname=computer;
if cname(1:2)=='PC' SLASH=BSLASH; end;
fid=fopen(FILENAME,'r','ieee-le');
if fid<0
fprintf(2,['Error LOADEDF: File ' FILENAME ' not found\n']);
return;
end;
EDF.FILE.FID=fid;
EDF.FILE.OPEN = 1;
EDF.FileName = FILENAME;
PPos=min([max(find(FILENAME=='.')) length(FILENAME)+1]);
SPos=max([0 find((FILENAME=='/') | (FILENAME==BSLASH))]);
EDF.FILE.Ext = FILENAME(PPos+1:length(FILENAME));
EDF.FILE.Name = FILENAME(SPos+1:PPos-1);
if SPos==0
EDF.FILE.Path = pwd;
else
EDF.FILE.Path = FILENAME(1:SPos-1);
end;
EDF.FileName = [EDF.FILE.Path SLASH EDF.FILE.Name '.' EDF.FILE.Ext];
H1=char(fread(EDF.FILE.FID,256,'char')'); %
EDF.VERSION=H1(1:8); % 8 Byte Versionsnummer
%if 0 fprintf(2,'LOADEDF: WARNING Version EDF Format %i',ver); end;
EDF.PID = deblank(H1(9:88)); % 80 Byte local patient identification
EDF.RID = deblank(H1(89:168)); % 80 Byte local recording identification
%EDF.H.StartDate = H1(169:176); % 8 Byte
%EDF.H.StartTime = H1(177:184); % 8 Byte
EDF.T0=[str2num(H1(168+[7 8])) str2num(H1(168+[4 5])) str2num(H1(168+[1 2])) str2num(H1(168+[9 10])) str2num(H1(168+[12 13])) str2num(H1(168+[15 16])) ];
% Y2K compatibility until year 2090
if EDF.VERSION(1)=='0'
if EDF.T0(1) < 91
EDF.T0(1)=2000+EDF.T0(1);
else
EDF.T0(1)=1900+EDF.T0(1);
end;
else ;
% in a future version, this is hopefully not needed
end;
EDF.HeadLen = str2num(H1(185:192)); % 8 Byte Length of Header
% reserved = H1(193:236); % 44 Byte
EDF.NRec = str2num(H1(237:244)); % 8 Byte # of data records
EDF.Dur = str2num(H1(245:252)); % 8 Byte # duration of data record in sec
EDF.NS = str2num(H1(253:256)); % 8 Byte # of signals
EDF.Label = char(fread(EDF.FILE.FID,[16,EDF.NS],'char')');
EDF.Transducer = char(fread(EDF.FILE.FID,[80,EDF.NS],'char')');
EDF.PhysDim = char(fread(EDF.FILE.FID,[8,EDF.NS],'char')');
EDF.PhysMin= str2num(char(fread(EDF.FILE.FID,[8,EDF.NS],'char')'));
EDF.PhysMax= str2num(char(fread(EDF.FILE.FID,[8,EDF.NS],'char')'));
EDF.DigMin = str2num(char(fread(EDF.FILE.FID,[8,EDF.NS],'char')'));
EDF.DigMax = str2num(char(fread(EDF.FILE.FID,[8,EDF.NS],'char')'));
% check validity of DigMin and DigMax
if (length(EDF.DigMin) ~= EDF.NS)
fprintf(2,'Warning OPENEDF: Failing Digital Minimum\n');
EDF.DigMin = -(2^15)*ones(EDF.NS,1);
end
if (length(EDF.DigMax) ~= EDF.NS)
fprintf(2,'Warning OPENEDF: Failing Digital Maximum\n');
EDF.DigMax = (2^15-1)*ones(EDF.NS,1);
end
if (any(EDF.DigMin >= EDF.DigMax))
fprintf(2,'Warning OPENEDF: Digital Minimum larger than Maximum\n');
end
% check validity of PhysMin and PhysMax
if (length(EDF.PhysMin) ~= EDF.NS)
fprintf(2,'Warning OPENEDF: Failing Physical Minimum\n');
EDF.PhysMin = EDF.DigMin;
end
if (length(EDF.PhysMax) ~= EDF.NS)
fprintf(2,'Warning OPENEDF: Failing Physical Maximum\n');
EDF.PhysMax = EDF.DigMax;
end
if (any(EDF.PhysMin >= EDF.PhysMax))
fprintf(2,'Warning OPENEDF: Physical Minimum larger than Maximum\n');
EDF.PhysMin = EDF.DigMin;
EDF.PhysMax = EDF.DigMax;
end
EDF.PreFilt= char(fread(EDF.FILE.FID,[80,EDF.NS],'char')'); %
tmp = fread(EDF.FILE.FID,[8,EDF.NS],'char')'; % samples per data record
EDF.SPR = str2num(char(tmp)); % samples per data record
fseek(EDF.FILE.FID,32*EDF.NS,0);
EDF.Cal = (EDF.PhysMax-EDF.PhysMin)./(EDF.DigMax-EDF.DigMin);
EDF.Off = EDF.PhysMin - EDF.Cal .* EDF.DigMin;
tmp = find(EDF.Cal < 0);
EDF.Cal(tmp) = ones(size(tmp));
EDF.Off(tmp) = zeros(size(tmp));
EDF.Calib=[EDF.Off';(diag(EDF.Cal))];
%EDF.Calib=sparse(diag([1; EDF.Cal]));
%EDF.Calib(1,2:EDF.NS+1)=EDF.Off';
EDF.SampleRate = EDF.SPR / EDF.Dur;
EDF.FILE.POS = ftell(EDF.FILE.FID);
if EDF.NRec == -1 % unknown record size, determine correct NRec
fseek(EDF.FILE.FID, 0, 'eof');
endpos = ftell(EDF.FILE.FID);
EDF.NRec = floor((endpos - EDF.FILE.POS) / (sum(EDF.SPR) * 2));
fseek(EDF.FILE.FID, EDF.FILE.POS, 'bof');
H1(237:244)=sprintf('%-8i',EDF.NRec); % write number of records
end;
EDF.Chan_Select=(EDF.SPR==max(EDF.SPR));
for k=1:EDF.NS
if EDF.Chan_Select(k)
EDF.ChanTyp(k)='N';
else
EDF.ChanTyp(k)=' ';
end;
if findstr(upper(EDF.Label(k,:)),'ECG')
EDF.ChanTyp(k)='C';
elseif findstr(upper(EDF.Label(k,:)),'EKG')
EDF.ChanTyp(k)='C';
elseif findstr(upper(EDF.Label(k,:)),'EEG')
EDF.ChanTyp(k)='E';
elseif findstr(upper(EDF.Label(k,:)),'EOG')
EDF.ChanTyp(k)='O';
elseif findstr(upper(EDF.Label(k,:)),'EMG')
EDF.ChanTyp(k)='M';
end;
end;
EDF.AS.spb = sum(EDF.SPR); % Samples per Block
bi=[0;cumsum(EDF.SPR)];
idx=[];idx2=[];
for k=1:EDF.NS,
idx2=[idx2, (k-1)*max(EDF.SPR)+(1:EDF.SPR(k))];
end;
maxspr=max(EDF.SPR);
idx3=zeros(EDF.NS*maxspr,1);
for k=1:EDF.NS, idx3(maxspr*(k-1)+(1:maxspr))=bi(k)+ceil((1:maxspr)'/maxspr*EDF.SPR(k));end;
%EDF.AS.bi=bi;
EDF.AS.IDX2=idx2;
%EDF.AS.IDX3=idx3;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% convert the header to Fieldtrip-style
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if all(EDF.SampleRate==EDF.SampleRate(1))
hdr.Fs = EDF.SampleRate(1);
hdr.nChans = EDF.NS;
hdr.label = cellstr(EDF.Label);
% it is continuous data, therefore append all records in one trial
hdr.nSamples = EDF.Dur * EDF.SampleRate(1);
hdr.nSamplesPre = 0;
hdr.nTrials = EDF.NRec;
hdr.orig = EDF;
elseif all(EDF.SampleRate(1:end-1)==EDF.SampleRate(1))
% only the last channel has a deviant sampling frequency
% this is the case for EGI recorded datasets that have been converted
% to EDF+, in which case the annotation channel is the last
chansel = find(EDF.SampleRate==EDF.SampleRate(1));
% continue with the subset of channels that has a consistent sampling frequency
hdr.Fs = EDF.SampleRate(chansel(1));
hdr.nChans = length(chansel);
warning('Skipping "%s" as continuous data channel because of inconsistent sampling frequency (%g Hz)', deblank(EDF.Label(end,:)), EDF.SampleRate(end));
hdr.label = cellstr(EDF.Label);
hdr.label = hdr.label(chansel);
% it is continuous data, therefore append all records in one trial
hdr.nSamples = EDF.Dur * EDF.SampleRate(chansel(1));
hdr.nSamplesPre = 0;
hdr.nTrials = EDF.NRec;
hdr.orig = EDF;
% this will be used on subsequent reading of data
hdr.orig.chansel = chansel;
hdr.orig.annotation = find(strcmp(cellstr(hdr.orig.Label), 'EDF Annotations'));
else
% select the sampling rate that results in the most channels
[a, b, c] = unique(EDF.SampleRate);
for i=1:length(a)
chancount(i) = sum(c==i);
end
[dum, indx] = max(chancount);
chansel = find(EDF.SampleRate == a(indx));
% continue with the subset of channels that has a consistent sampling frequency
hdr.Fs = EDF.SampleRate(chansel(1));
hdr.nChans = length(chansel);
hdr.label = cellstr(EDF.Label);
hdr.label = hdr.label(chansel);
% it is continuous data, therefore append all records in one trial
hdr.nSamples = EDF.Dur * EDF.SampleRate(chansel(1));
hdr.nSamplesPre = 0;
hdr.nTrials = EDF.NRec;
hdr.orig = EDF;
% this will be used on subsequent reading of data
hdr.orig.chansel = chansel;
hdr.orig.annotation = find(strcmp(cellstr(hdr.orig.Label), 'EDF Annotations'));
warning('channels with different sampling rate not supported, using a subselection of %d channels at %f Hz', length(hdr.label), hdr.Fs);
end
% return the header
dat = hdr;
elseif needdat || needevt
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% read the data
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% retrieve the original header
EDF = hdr.orig;
% determine whether a subset of channels should be used
% which is the case if channels have a variable sampling frequency
variableFs = isfield(EDF, 'chansel');
if variableFs && needevt
% read the annotation channel, not the data channels
EDF.chansel = EDF.annotation;
begsample = 1;
endsample = EDF.SampleRate(end)*EDF.NRec*EDF.Dur;
end
if variableFs
epochlength = EDF.Dur * EDF.SampleRate(EDF.chansel(1)); % in samples for the selected channel
blocksize = sum(EDF.Dur * EDF.SampleRate); % in samples for all channels
chanoffset = EDF.Dur * EDF.SampleRate;
chanoffset = cumsum([0; chanoffset(1:end-1)]);
% use a subset of channels
nchans = length(EDF.chansel);
else
epochlength = EDF.Dur * EDF.SampleRate(1); % in samples for a single channel
blocksize = sum(EDF.Dur * EDF.SampleRate); % in samples for all channels
% use all channels
nchans = EDF.NS;
end
% determine the trial containing the begin and end sample
begepoch = floor((begsample-1)/epochlength) + 1;
endepoch = floor((endsample-1)/epochlength) + 1;
nepochs = endepoch - begepoch + 1;
if nargin<5
chanindx = 1:nchans;
end
% allocate memory to hold the data
dat = zeros(length(chanindx),nepochs*epochlength);
% read and concatenate all required data epochs
for i=begepoch:endepoch
if variableFs
% only a subset of channels with consistent sampling frequency is read
offset = EDF.HeadLen + (i-1)*blocksize*2; % in bytes
% read the complete data block
buf = readLowLevel(filename, offset, blocksize); % see below in subfunction
for j=1:length(chanindx)
% cut out the part that corresponds with a single channel
dat(j,((i-begepoch)*epochlength+1):((i-begepoch+1)*epochlength)) = buf((1:epochlength) + chanoffset(EDF.chansel(chanindx(j))));
end
elseif length(chanindx)==1
% this is more efficient if only one channel has to be read, e.g. the status channel
offset = EDF.HeadLen + (i-1)*blocksize*2; % in bytes
offset = offset + (chanindx-1)*epochlength*2;
% read the data for a single channel
buf = readLowLevel(filename, offset, epochlength); % see below in subfunction
dat(:,((i-begepoch)*epochlength+1):((i-begepoch+1)*epochlength)) = buf;
else
% read the data from all channels, subsequently select the desired channels
offset = EDF.HeadLen + (i-1)*blocksize*2; % in bytes
% read the complete data block
buf = readLowLevel(filename, offset, blocksize); % see below in subfunction
buf = reshape(buf, epochlength, nchans);
dat(:,((i-begepoch)*epochlength+1):((i-begepoch+1)*epochlength)) = buf(:,chanindx)';
end
end
% select the desired samples
begsample = begsample - (begepoch-1)*epochlength; % correct for the number of bytes that were skipped
endsample = endsample - (begepoch-1)*epochlength; % correct for the number of bytes that were skipped
dat = dat(:, begsample:endsample);
% Calibrate the data
if variableFs
calib = diag(EDF.Cal(EDF.chansel(chanindx)));
else
calib = diag(EDF.Cal(chanindx));
end
if length(chanindx)>1
% using a sparse matrix speeds up the multiplication
dat = sparse(calib) * dat;
else
% in case of one channel the sparse multiplication would result in a sparse array
dat = calib * dat;
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION for reading the 16 bit values
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function buf = readLowLevel(filename, offset, numwords)
if offset < 2*1024^2
% use the external mex file, only works for <2GB
buf = read_16bit(filename, offset, numwords);
else
% use plain matlab, thanks to Philip van der Broek
fp = fopen(filename,'r','ieee-le');
status = fseek(fp, offset, 'bof');
if status
error(['failed seeking ' filename]);
end
[buf,num] = fread(fp,numwords,'bit16=>double');
fclose(fp);
if (num<numwords)
error(['failed reading ' filename]);
return
end
end
|
github
|
philippboehmsturm/antx-master
|
yokogawa2grad.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/yokogawa2grad.m
| 7,205 |
utf_8
|
c61a324e8fd20060380618a1f0760a72
|
function grad = yokogawa2grad(hdr)
% YOKOGAWA2GRAD converts the position and weights of all coils that
% compromise a gradiometer system into a structure that can be used
% by FieldTrip. This implementation uses the old "yokogawa" toolbox.
%
% See also CTF2GRAD, BTI2GRAD, FIF2GRAD, MNE2GRAD, ITAB2GRAD,
% FT_READ_SENS, FT_READ_HEADER
% Copyright (C) 2005-2008, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: yokogawa2grad.m 7123 2012-12-06 21:21:38Z roboos $
if ~ft_hastoolbox('yokogawa')
error('cannot determine whether Yokogawa toolbox is present');
end
if isfield(hdr, 'label')
label = hdr.label; % keep for later use
end
if isfield(hdr, 'orig')
hdr = hdr.orig; % use the original header, not the FieldTrip header
end
% The "channel_info" contains
% 1 channel number, zero offset
% 2 channel type, type of gradiometer
% 3 position x (in m)
% 4 position y (in m)
% 5 position z (in m)
% 6 orientation of first coil (theta in deg)
% 7 orientation of first coil (phi in deg)
% 8 orientation from the 1st to 2nd coil for gradiometer (theta in deg)
% 9 orientation from the 1st to 2nd coil for gradiometer (phi in deg)
% 10 coil size (in m)
% 11 baseline (in m)
handles = definehandles;
isgrad = (hdr.channel_info(:,2)==handles.AxialGradioMeter | ...
hdr.channel_info(:,2)==handles.PlannerGradioMeter | ...
hdr.channel_info(:,2)==handles.MagnetoMeter | ...
hdr.channel_info(:,2)==handles.RefferenceAxialGradioMeter);
% reference channels are excluded because the positions are not specified
% hdr.channel_info(:,2)==handles.RefferencePlannerGradioMeter
% hdr.channel_info(:,2)==handles.RefferenceMagnetoMeter
isgrad_handles = hdr.channel_info(isgrad,2);
ismag = (isgrad_handles(:)==handles.MagnetoMeter | isgrad_handles(:)==handles.RefferenceMagnetoMeter);
grad.coilpos = hdr.channel_info(isgrad,3:5)*100; % cm
grad.unit = 'cm';
% Get orientation of the 1st coil
ori_1st = hdr.channel_info(find(isgrad),[6 7]);
% polar to x,y,z coordinates
ori_1st = ...
[sin(ori_1st(:,1)/180*pi).*cos(ori_1st(:,2)/180*pi) ...
sin(ori_1st(:,1)/180*pi).*sin(ori_1st(:,2)/180*pi) ...
cos(ori_1st(:,1)/180*pi)];
grad.coilori = ori_1st;
% Get orientation from the 1st to 2nd coil for gradiometer
ori_1st_to_2nd = hdr.channel_info(find(isgrad),[8 9]);
% polar to x,y,z coordinates
ori_1st_to_2nd = ...
[sin(ori_1st_to_2nd(:,1)/180*pi).*cos(ori_1st_to_2nd(:,2)/180*pi) ...
sin(ori_1st_to_2nd(:,1)/180*pi).*sin(ori_1st_to_2nd(:,2)/180*pi) ...
cos(ori_1st_to_2nd(:,1)/180*pi)];
% Get baseline
baseline = hdr.channel_info(isgrad,size(hdr.channel_info,2));
% Define the location and orientation of 2nd coil
info = hdr.channel_info(isgrad,2);
for i=1:sum(isgrad)
if (info(i) == handles.AxialGradioMeter || info(i) == handles.RefferenceAxialGradioMeter )
grad.coilpos(i+sum(isgrad),:) = [grad.coilpos(i,:)+ori_1st(i,:)*baseline(i)*100];
grad.coilori(i+sum(isgrad),:) = -ori_1st(i,:);
elseif (info(i) == handles.PlannerGradioMeter || info(i) == handles.RefferencePlannerGradioMeter)
grad.coilpos(i+sum(isgrad),:) = [grad.coilpos(i,:)+ori_1st_to_2nd(i,:)*baseline(i)*100];
grad.coilori(i+sum(isgrad),:) = -ori_1st(i,:);
else
grad.coilpos(i+sum(isgrad),:) = [0 0 0];
grad.coilori(i+sum(isgrad),:) = [0 0 0];
end
end
% Define the pair of 1st and 2nd coils for each gradiometer
grad.tra = repmat(diag(ones(1,size(grad.coilpos,1)/2),0),1,2);
% for mangetometers change tra as there is no second coil
if any(ismag)
sz_pnt = size(grad.coilpos,1)/2;
% create logical variable
not_2nd_coil = ([diag(zeros(sz_pnt),0)' ismag']~=0);
grad.tra(ismag,not_2nd_coil) = 0;
end
% the gradiometer labels should be consistent with the channel labels in
% read_yokogawa_header, the predefined list of channel names in ft_senslabel
% and with ft_channelselection
% ONLY consistent with read_yokogawa_header as NO FIXED relation between
% channel index and type of channel exists for Yokogawa systems. Therefore
% all have individual label sequences: No useful support in ft_senslabel possible
if ~isempty(label)
grad.label = label(isgrad);
else
% this is only backup, if something goes wrong above.
label = cell(size(isgrad));
for i=1:length(label)
label{i} = sprintf('AG%03d', i);
end
grad.label = label(isgrad);
end
grad.unit = 'cm';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% this defines some usefull constants
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function handles = definehandles
handles.output = [];
handles.sqd_load_flag = false;
handles.mri_load_flag = false;
handles.NullChannel = 0;
handles.MagnetoMeter = 1;
handles.AxialGradioMeter = 2;
handles.PlannerGradioMeter = 3;
handles.RefferenceChannelMark = hex2dec('0100');
handles.RefferenceMagnetoMeter = bitor( handles.RefferenceChannelMark, handles.MagnetoMeter );
handles.RefferenceAxialGradioMeter = bitor( handles.RefferenceChannelMark, handles.AxialGradioMeter );
handles.RefferencePlannerGradioMeter = bitor( handles.RefferenceChannelMark, handles.PlannerGradioMeter );
handles.TriggerChannel = -1;
handles.EegChannel = -2;
handles.EcgChannel = -3;
handles.EtcChannel = -4;
handles.NonMegChannelNameLength = 32;
handles.DefaultMagnetometerSize = (4.0/1000.0); % ????4.0mm???????`
handles.DefaultAxialGradioMeterSize = (15.5/1000.0); % ???a15.5mm???~??
handles.DefaultPlannerGradioMeterSize = (12.0/1000.0); % ????12.0mm???????`
handles.AcqTypeContinuousRaw = 1;
handles.AcqTypeEvokedAve = 2;
handles.AcqTypeEvokedRaw = 3;
handles.sqd = [];
handles.sqd.selected_start = [];
handles.sqd.selected_end = [];
handles.sqd.axialgradiometer_ch_no = [];
handles.sqd.axialgradiometer_ch_info = [];
handles.sqd.axialgradiometer_data = [];
handles.sqd.plannergradiometer_ch_no = [];
handles.sqd.plannergradiometer_ch_info = [];
handles.sqd.plannergradiometer_data = [];
handles.sqd.nullchannel_ch_no = [];
handles.sqd.nullchannel_data = [];
handles.sqd.selected_time = [];
handles.sqd.sample_rate = [];
handles.sqd.sample_count = [];
handles.sqd.pretrigger_length = [];
handles.sqd.matching_info = [];
handles.sqd.source_info = [];
handles.sqd.mri_info = [];
handles.mri = [];
|
github
|
philippboehmsturm/antx-master
|
read_erplabheader.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_erplabheader.m
| 2,048 |
utf_8
|
c72fab70eaf79706e1f1f452bc50692a
|
% read_erplabheader() - import ERPLAB dataset files
%
% Usage:
% >> header = read_erplabheader(filename);
%
% Inputs:
% filename - [string] file name
%
% Outputs:
% header - FILEIO toolbox type structure
%
% Modified from read_eeglabheader
%123456789012345678901234567890123456789012345678901234567890123456789012
% Copyright (C) 2008 Arnaud Delorme, SCCN, INC, UCSD, [email protected]
%
% This program 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 2 of the License, or
% (at your option) any later version.
%
% This program 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 this program; if not, write to the Free Software
% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
function header = read_erplabheader(filename)
if nargin < 1
help read_erplabheader;
return;
end;
if ~isstruct(filename)
load('-mat', filename);
else
ERP = filename;
end;
header.Fs = ERP.srate;
header.nChans = ERP.nchan;
header.nSamples = ERP.pnts;
header.nSamplesPre = -ERP.xmin*ERP.srate;
header.nTrials = ERP.nbin;
try
header.label = { ERP.chanlocs.labels }';
catch
warning('creating default channel names');
for i=1:header.nChans
header.label{i} = sprintf('chan%03d', i);
end
end
ind = 1;
for i = 1:length( ERP.chanlocs )
if isfield(ERP.chanlocs(i), 'X') && ~isempty(ERP.chanlocs(i).X)
header.elec.label{ind, 1} = ERP.chanlocs(i).labels;
% this channel has a position
header.elec.pnt(ind,1) = ERP.chanlocs(i).X;
header.elec.pnt(ind,2) = ERP.chanlocs(i).Y;
header.elec.pnt(ind,3) = ERP.chanlocs(i).Z;
ind = ind+1;
end;
end;
header.orig = ERP;
|
github
|
philippboehmsturm/antx-master
|
write_plexon_nex.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/write_plexon_nex.m
| 9,546 |
utf_8
|
c3e00b18b8d0d194f3b0231301f3945f
|
function write_plexon_nex(filename, nex)
% WRITE_PLEXON_NEX writes a Plexon *.nex file, which is a file
% containing action-potential (spike) timestamps and waveforms (spike
% channels), event timestamps (event channels), and continuous variable
% data (continuous A/D channels).
%
% Use as
% write_plexon_nex(filename, nex);
%
% The data structure should contain
% nex.hdr.FileHeader.Frequency = TimeStampFreq
% nex.hdr.VarHeader.Type = type, 5 for continuous
% nex.hdr.VarHeader.Name = label, padded to length 64
% nex.hdr.VarHeader.WFrequency = sampling rate of continuous channel
% nex.var.dat = data
% nex.var.ts = timestamps
%
% See also READ_PLEXON_NEX, READ_PLEXON_PLX, READ_PLEXON_DDT
% Copyright (C) 2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: write_plexon_nex.m 7123 2012-12-06 21:21:38Z roboos $
% get the optional arguments, these are all required
% FirstTimeStamp = ft_getopt(varargin, 'FirstTimeStamp');
% TimeStampFreq = ft_getopt(varargin, 'TimeStampFreq');
hdr = nex.hdr;
UVtoMV = 1/1000;
switch hdr.VarHeader.Type
case 5
dat = nex.var.dat; % this is in microVolt
buf = zeros(size(dat), 'int16');
nchans = size(dat,1);
nsamples = size(dat,2);
nwaves = 1; % only one continuous datasegment is supported
if length(hdr.VarHeader)~=nchans
error('incorrect number of channels');
end
% convert the data from floating point into int16 values
% each channel gets its own optimal calibration factor
for varlop=1:nchans
ADMaxValue = double(intmax('int16'));
ADMaxUV = max(abs(dat(varlop,:))); % this is in microVolt
ADMaxMV = ADMaxUV/1000; % this is in miliVolt
if isa(dat, 'int16')
% do not rescale data that is already 16 bit
MVtoAD = 1;
elseif ADMaxMV==0
% do not rescale the data if the data is zero
MVtoAD = 1;
elseif ADMaxMV>0
% rescale the data so that it fits into the 16 bits with as little loss as possible
MVtoAD = ADMaxValue / ADMaxMV;
end
buf(varlop,:) = int16(double(dat) * UVtoMV * MVtoAD);
% remember the calibration value, it should be stored in the variable header
ADtoMV(varlop) = 1/MVtoAD;
end
dat = buf;
clear buf;
case 3
dat = nex.var.dat; % this is in microVolt
nchans = 1; % only one channel is supported
nsamples = size(dat,1);
nwaves = size(dat,2);
if length(hdr.VarHeader)~=nchans
error('incorrect number of channels');
end
% convert the data from floating point into int16 values
ADMaxValue = double(intmax('int16'));
ADMaxUV = max(abs(dat(:))); % this is in microVolt
ADMaxMV = ADMaxUV/1000; % this is in miliVolt
if isa(dat, 'int16')
% do not rescale data that is already 16 bit
MVtoAD = 1;
elseif ADMaxMV==0
% do not rescale the data if the data is zero
MVtoAD = 1;
elseif ADMaxMV>0
% rescale the data so that it fits into the 16 bits with as little loss as possible
MVtoAD = ADMaxValue / ADMaxMV;
end
dat = int16(double(dat) * UVtoMV * MVtoAD);
% remember the calibration value, it should be stored in the variable header
ADtoMV = 1/MVtoAD;
otherwise
error('unsupported data type')
end % switch type
% determine the first and last timestamp
ts = nex.var.ts;
ts_beg = min(ts);
ts_end = 0; % FIXME
fid = fopen(filename, 'wb', 'ieee-le');
% write the file header
write_NexFileHeader;
% write the variable headers
for varlop=1:nchans
write_NexVarHeader;
end
% write the variable data
for varlop=1:nchans
write_NexVarData;
end
fclose(fid);
return
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% nested function for writing the details
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function write_NexFileHeader
% prepare the two char buffers
buf1 = padstr('$Id: write_plexon_nex.m 7123 2012-12-06 21:21:38Z roboos $', 256);
buf2 = char(zeros(1, 256));
% write the stuff to the file
fwrite(fid, 'NEX1' , 'char'); % NexFileHeader = string NEX1
fwrite(fid, 100 , 'int32'); % Version = version
fwrite(fid, buf1 , 'char'); % Comment = comment, 256 bytes
fwrite(fid, hdr.FileHeader.Frequency, 'double'); % Frequency = timestamped freq. - tics per second
fwrite(fid, ts_beg, 'int32'); % Beg = usually 0, minimum of all the timestamps in the file
fwrite(fid, ts_end, 'int32'); % End = maximum timestamp + 1
fwrite(fid, nchans, 'int32'); % NumVars = number of variables in the first batch
fwrite(fid, 0 , 'int32'); % NextFileHeader = position of the next file header in the file, not implemented yet
fwrite(fid, buf2 , 'char'); % Padding = future expansion
end % of the nested function
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% nested function for writing the details
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function write_NexVarHeader
filheadersize = 544;
varheadersize = 208;
offset = filheadersize + nchans*varheadersize + (varlop-1)*nsamples;
calib = ADtoMV(varlop);
% prepare the two char buffers
buf1 = padstr(hdr.VarHeader(varlop).Name, 64);
buf2 = char(zeros(1, 68));
% write the continuous variable to the file
fwrite(fid, hdr.VarHeader.Type, 'int32'); % Type = 0 - neuron, 1 event, 2- interval, 3 - waveform, 4 - pop. vector, 5 - continuously recorded
fwrite(fid, 100, 'int32'); % Version = 100
fwrite(fid, buf1, 'char'); % Name = variable name, 1x64 char
fwrite(fid, offset, 'int32'); % DataOffset = where the data array for this variable is located in the file
fwrite(fid, nwaves, 'int32'); % Count = number of events, intervals, waveforms or weights
fwrite(fid, 0, 'int32'); % WireNumber = neuron only, not used now
fwrite(fid, 0, 'int32'); % UnitNumber = neuron only, not used now
fwrite(fid, 0, 'int32'); % Gain = neuron only, not used now
fwrite(fid, 0, 'int32'); % Filter = neuron only, not used now
fwrite(fid, 0, 'double'); % XPos = neuron only, electrode position in (0,100) range, used in 3D
fwrite(fid, 0, 'double'); % YPos = neuron only, electrode position in (0,100) range, used in 3D
fwrite(fid, hdr.VarHeader.WFrequency, 'double'); % WFrequency = waveform and continuous vars only, w/f sampling frequency
fwrite(fid, calib, 'double'); % ADtoMV = waveform continuous vars only, coeff. to convert from A/D values to Millivolts
fwrite(fid, nsamples, 'int32'); % NPointsWave = waveform only, number of points in each wave
fwrite(fid, 0, 'int32'); % NMarkers = how many values are associated with each marker
fwrite(fid, 0, 'int32'); % MarkerLength = how many characters are in each marker value
fwrite(fid, buf2, 'char'); % Padding, 1x68 char
end % of the nested function
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% nested function for writing the details
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function write_NexVarData
switch hdr.VarHeader.Type
case 5
% this code only supports one continuous segment
index = 0;
fwrite(fid, ts , 'int32'); % timestamps, one for each continuous segment
fwrite(fid, index , 'int32'); % where to cut the segments, zero offset
fwrite(fid, dat(varlop,:) , 'int16'); % data
case 3
fwrite(fid, ts , 'int32'); % timestamps, one for each spike
fwrite(fid, dat , 'int16'); % waveforms, one for each spike
otherwise
error('unsupported data type');
end % switch
end % of the nested function
end % of the primary function
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% subfunction for zero padding a char array to fixed length
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function str = padstr(str, num);
if length(str)>num
str = str(1:num);
else
str((end+1):num) = 0;
end
end % of the padstr subfunction
|
github
|
philippboehmsturm/antx-master
|
ft_convert_units.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/ft_convert_units.m
| 7,014 |
utf_8
|
b6713ad4580d1dac67d2d43489f0dc55
|
function [obj] = ft_convert_units(obj, target)
% FT_CONVERT_UNITS changes the geometrical dimension to the specified SI unit.
% The units of the input object is determined from the structure field
% object.unit, or is estimated based on the spatial extend of the structure,
% e.g. a volume conduction model of the head should be approximately 20 cm large.
%
% Use as
% [object] = ft_convert_units(object, target)
%
% The following input objects are supported
% simple dipole position
% electrode definition
% gradiometer array definition
% volume conductor definition
% dipole grid definition
% anatomical mri
% segmented mri
%
% Possible target units are 'm', 'dm', 'cm ' or 'mm'. If no target units
% are specified, this function will only determine the native geometrical
% units of the object.
%
% See FT_ESTIMATE_UNITS, FT_READ_VOL, FT_READ_SENS
% Copyright (C) 2005-2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_convert_units.m 7337 2013-01-16 15:52:00Z johzum $
% This function consists of three parts:
% 1) determine the input units
% 2) determine the requested scaling factor to obtain the output units
% 3) try to apply the scaling to the known geometrical elements in the input object
if isstruct(obj) && numel(obj)>1
% deal with a structure array
for i=1:numel(obj)
if nargin>1
tmp(i) = ft_convert_units(obj(i), target);
else
tmp(i) = ft_convert_units(obj(i));
end
end
obj = tmp;
return
end
% determine the unit-of-dimension of the input object
if isfield(obj, 'unit') && ~isempty(obj.unit)
% use the units specified in the object
unit = obj.unit;
else
% try to determine the units by looking at the size of the object
if isfield(obj, 'chanpos') && ~isempty(obj.chanpos)
siz = norm(idrange(obj.chanpos));
unit = ft_estimate_units(siz);
elseif isfield(obj, 'pnt') && ~isempty(obj.pnt)
siz = norm(idrange(obj.pnt));
unit = ft_estimate_units(siz);
elseif isfield(obj, 'pos') && ~isempty(obj.pos)
siz = norm(idrange(obj.pos));
unit = ft_estimate_units(siz);
elseif isfield(obj, 'transform') && ~isempty(obj.transform)
% construct the corner points of the volume in voxel and in head coordinates
[pos_voxel, pos_head] = cornerpoints(obj.dim, obj.transform);
siz = norm(idrange(pos_head));
unit = ft_estimate_units(siz);
elseif isfield(obj, 'fid') && isfield(obj.fid, 'pnt') && ~isempty(obj.fid.pnt)
siz = norm(idrange(obj.fid.pnt));
unit = ft_estimate_units(siz);
elseif ft_voltype(obj, 'infinite')
% this is an infinite medium volume conductor, which does not care about units
unit = 'm';
elseif ft_voltype(obj,'singlesphere')
siz = obj.r;
unit = ft_estimate_units(siz);
elseif ft_voltype(obj,'localspheres')
siz = median(obj.r);
unit = ft_estimate_units(siz);
elseif ft_voltype(obj,'concentricspheres')
siz = max(obj.r);
unit = ft_estimate_units(siz);
elseif isfield(obj, 'bnd') && isstruct(obj.bnd) && isfield(obj.bnd(1), 'pnt') && ~isempty(obj.bnd(1).pnt)
siz = norm(idrange(obj.bnd(1).pnt));
unit = ft_estimate_units(siz);
elseif isfield(obj, 'nas') && isfield(obj, 'lpa') && isfield(obj, 'rpa')
pnt = [obj.nas; obj.lpa; obj.rpa];
siz = norm(idrange(pnt));
unit = ft_estimate_units(siz);
else
error('cannot determine geometrical units');
end % recognized type of volume conduction model or sensor array
end % determine input units
if nargin<2 || isempty(target)
% just remember the units in the output and return
obj.unit = unit;
return
elseif strcmp(unit, target)
% no conversion is needed
obj.unit = unit;
return
end
% compue the scaling factor from the input units to the desired ones
scale = scalingfactor(unit, target);
% give some information about the conversion
fprintf('converting units from ''%s'' to ''%s''\n', unit, target)
% volume conductor model
if isfield(obj, 'r'), obj.r = scale * obj.r; end
if isfield(obj, 'o'), obj.o = scale * obj.o; end
if isfield(obj, 'bnd'), for i=1:length(obj.bnd), obj.bnd(i).pnt = scale * obj.bnd(i).pnt; end, end
% gradiometer array
if isfield(obj, 'pnt1'), obj.pnt1 = scale * obj.pnt1; end
if isfield(obj, 'pnt2'), obj.pnt2 = scale * obj.pnt2; end
if isfield(obj, 'prj'), obj.prj = scale * obj.prj; end
% gradiometer array, electrode array, head shape or dipole grid
if isfield(obj, 'pnt'), obj.pnt = scale * obj.pnt; end
if isfield(obj, 'chanpos'), obj.chanpos = scale * obj.chanpos; end
if isfield(obj, 'coilpos'), obj.coilpos = scale * obj.coilpos; end
if isfield(obj, 'elecpos'), obj.elecpos = scale * obj.elecpos; end
% gradiometer array that combines multiple coils in one channel
if isfield(obj, 'tra') && isfield(obj, 'chanunit')
% find the gradiometer channels that are expressed as unit of field strength divided by unit of distance, e.g. T/cm
for i=1:length(obj.chanunit)
tok = tokenize(obj.chanunit{i}, '/');
if length(tok)==1
% assume that it is T or so
elseif length(tok)==2
% assume that it is T/cm or so
obj.tra(i,:) = obj.tra(i,:) / scale;
obj.chanunit{i} = [tok{1} '/' target];
else
error('unexpected units %s', obj.chanunit{i});
end
end % for
end % if
% fiducials
if isfield(obj, 'fid') && isfield(obj.fid, 'pnt'), obj.fid.pnt = scale * obj.fid.pnt; end
% dipole grid
if isfield(obj, 'pos'), obj.pos = scale * obj.pos; end
% anatomical MRI or functional volume
if isfield(obj, 'transform'),
H = diag([scale scale scale 1]);
obj.transform = H * obj.transform;
end
if isfield(obj, 'transformorig'),
H = diag([scale scale scale 1]);
obj.transformorig = H * obj.transformorig;
end
% remember the unit
obj.unit = target;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% IDRANGE interdecile range for more robust range estimation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function r = idrange(x)
keeprow=true(size(x,1),1);
for l=1:size(x,2)
keeprow = keeprow & isfinite(x(:,l));
end
sx = sort(x(keeprow,:), 1);
ii = round(interp1([0, 1], [1, size(x(keeprow,:), 1)], [.1, .9])); % indices for 10 & 90 percentile
r = diff(sx(ii, :));
|
github
|
philippboehmsturm/antx-master
|
nansum.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/nansum.m
| 185 |
utf_8
|
4859ec062780c478011dd7a8d94684a0
|
% NANSUM provides a replacement for MATLAB's nanmean.
%
% For usage see SUM.
function y = nansum(x, dim)
if nargin == 1
dim = 1;
end
idx = isnan(x);
x(idx) = 0;
y = sum(x, dim);
end
|
github
|
philippboehmsturm/antx-master
|
ft_datatype.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/ft_datatype.m
| 7,749 |
utf_8
|
975852e96f4caa3ccb50bbbd5f8c5248
|
function [type, dimord] = ft_datatype(data, desired)
% FT_DATATYPE determines the type of data represented in a FieldTrip data
% structure and returns a string with raw, freq, timelock source, comp,
% spike, source, volume, dip.
%
% Use as
% [type, dimord] = ft_datatype(data)
% [status] = ft_datatype(data, desired)
%
% See also FT_DATATYPE_COMP FT_DATATYPE_FREQ FT_DATATYPE_MVAR
% FT_DATATYPE_SEGMENTATION FT_DATATYPE_PARCELLATION FT_DATATYPE_SOURCE
% FT_DATATYPE_TIMELOCK FT_DATATYPE_DIP FT_DATATYPE_HEADMODEL
% FT_DATATYPE_RAW FT_DATATYPE_SENS FT_DATATYPE_SPIKE FT_DATATYPE_VOLUME
% Copyright (C) 2008-2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_datatype.m 7123 2012-12-06 21:21:38Z roboos $
% determine the type of input data, this can be raw, freq, timelock, comp, spike, source, volume, dip, segmentation, parcellation
israw = isfield(data, 'label') && isfield(data, 'time') && isa(data.time, 'cell') && isfield(data, 'trial') && isa(data.trial, 'cell') && ~isfield(data,'trialtime');
isfreq = (isfield(data, 'label') || isfield(data, 'labelcmb')) && isfield(data, 'freq') && ~isfield(data,'trialtime') && ~isfield(data,'origtrial'); %&& (isfield(data, 'powspctrm') || isfield(data, 'crsspctrm') || isfield(data, 'cohspctrm') || isfield(data, 'fourierspctrm') || isfield(data, 'powcovspctrm'));
istimelock = isfield(data, 'label') && isfield(data, 'time') && ~isfield(data, 'freq') && ~isfield(data,'trialtime'); %&& ((isfield(data, 'avg') && isnumeric(data.avg)) || (isfield(data, 'trial') && isnumeric(data.trial) || (isfield(data, 'cov') && isnumeric(data.cov))));
iscomp = isfield(data, 'label') && isfield(data, 'topo') || isfield(data, 'topolabel');
isvolume = isfield(data, 'transform') && isfield(data, 'dim');
issource = isfield(data, 'pos');
isdip = isfield(data, 'dip');
ismvar = isfield(data, 'dimord') && ~isempty(strfind(data.dimord, 'lag'));
isfreqmvar = isfield(data, 'freq') && isfield(data, 'transfer');
ischan = isfield(data, 'dimord') && strcmp(data.dimord, 'chan') && ~isfield(data, 'time') && ~isfield(data, 'freq');
issegmentation = check_segmentation(data);
isparcellation = check_parcellation(data);
if ~isfreq
% this applies to a ferq structure from 2003 up to early 2006
isfreq = all(isfield(data, {'foi', 'label', 'dimord'})) && ~isempty(strfind(data.dimord, 'frq'));
end
% check if it is a spike structure
spk_hastimestamp = isfield(data,'label') && isfield(data, 'timestamp') && isa(data.timestamp, 'cell');
spk_hastrials = isfield(data,'label') && isfield(data, 'time') && isa(data.time, 'cell') && isfield(data, 'trial') && isa(data.trial, 'cell') && isfield(data, 'trialtime') && isa(data.trialtime, 'numeric');
spk_hasorig = isfield(data,'origtrial') && isfield(data,'origtime'); % for compatibility
isspike = isfield(data, 'label') && (spk_hastimestamp || spk_hastrials || spk_hasorig);
% check if it is a sensor array
isgrad = isfield(data, 'label') && isfield(data, 'coilpos') && isfield(data, 'chanpos') && isfield(data, 'coilori');
iselec = isfield(data, 'label') && isfield(data, 'elecpos') && isfield(data, 'chanpos');
if iscomp
% comp should conditionally go before raw, otherwise the returned ft_datatype will be raw
type = 'comp';
elseif israw
type = 'raw';
elseif isfreqmvar
% freqmvar should conditionally go before freq, otherwise the returned ft_datatype will be freq in the case of frequency mvar data
type = 'freqmvar';
elseif isfreq
type = 'freq';
elseif ismvar
type = 'mvar';
elseif isdip
% dip should conditionally go before timelock, otherwise the ft_datatype will be timelock
type = 'dip';
elseif istimelock
type = 'timelock';
elseif isspike
type = 'spike';
elseif issegmentation
% a segmentation data structure is a volume data structure, but in general not vice versa
% segmentation should conditionally go before volume, otherwise the returned ft_datatype will be volume
type = 'segmentation';
elseif isvolume
type = 'volume';
elseif isparcellation
% a parcellation data structure is a source data structure, but in general not vice versa
% parcellation should conditionally go before source, otherwise the returned ft_datatype will be source
type = 'parcellation';
elseif issource
type = 'source';
elseif ischan
% this results from avgovertime/avgoverfreq after timelockstatistics or freqstatistics
type = 'chan';
elseif iselec
type = 'elec';
elseif isgrad
type = 'grad';
else
type = 'unknown';
end
if nargin>1
% return a boolean value
switch desired
case 'raw'
type = any(strcmp(type, {'raw', 'comp'}));
case 'volume'
type = any(strcmp(type, {'volume', 'segmentation'}));
case 'source'
type = any(strcmp(type, {'source', 'parcellation'}));
case 'sens'
type = any(strcmp(type, {'elec', 'grad'}));
otherwise
type = strcmp(type, desired);
end % switch
end
if nargout>1
% also return the dimord of the input data
if isfield(data, 'dimord')
dimord = data.dimord;
else
dimord = 'unknown';
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [res] = check_segmentation(volume)
res = false;
if ~isfield(volume, 'dim')
return
end
if isfield(volume, 'pos')
return
end
if any(isfield(volume, {'seg', 'csf', 'white', 'gray', 'skull', 'scalp', 'brain'}))
res = true;
return
end
fn = fieldnames(volume);
for i=1:length(fn)
if isfield(volume, [fn{i} 'label'])
res = true;
return
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [res] = check_parcellation(source)
res = false;
if ~isfield(source, 'pos')
return
end
fn = fieldnames(source);
fb = false(size(fn));
npos = size(source.pos,1);
for i=1:numel(fn)
% for each of the fields check whether it might be a logical array with the size of the number of sources
tmp = source.(fn{i});
fb(i) = numel(tmp)==npos && islogical(tmp);
end
if sum(fb)>1
% the presence of multiple logical arrays suggests it is a parcellation
res = true;
end
if res == false % check if source has more D elements
check = 0;
for i = 1: length(fn)
fname = fn{i};
switch fname
case 'tri'
npos = size(source.tri,1);
check = 1;
case 'hex'
npos = size(source.hex,1);
check = 1;
case 'tet'
npos = size(source.tet,1);
check = 1;
end
end
if check == 1 % check if elements are labelled
for i=1:numel(fn)
tmp = source.(fn{i});
fb(i) = numel(tmp)==npos && islogical(tmp);
end
if sum(fb)>1
res = true;
end
end
end
fn = fieldnames(source);
for i=1:length(fn)
if isfield(source, [fn{i} 'label'])
res = true;
return
end
end
|
github
|
philippboehmsturm/antx-master
|
ft_apply_montage.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/ft_apply_montage.m
| 13,440 |
utf_8
|
ba256ae86f2bc28cc2d9f26098e25236
|
function [input] = ft_apply_montage(input, montage, varargin)
% FT_APPLY_MONTAGE changes the montage of an electrode or gradiometer array. A
% montage can be used for EEG rereferencing, MEG synthetic gradients, MEG
% planar gradients or unmixing using ICA. This function applies the montage
% to the inputor array. The inputor array can subsequently be used for
% forward computation and source reconstruction of the data.
%
% Use as
% [sens] = ft_apply_montage(sens, montage, ...)
% [data] = ft_apply_montage(data, montage, ...)
% [freq] = ft_apply_montage(freq, montage, ...)
% [montage] = ft_apply_montage(montage1, montage2, ...)
%
% A montage is specified as a structure with the fields
% montage.tra = MxN matrix
% montage.labelnew = Mx1 cell-array
% montage.labelorg = Nx1 cell-array
%
% As an example, a bipolar montage could look like this
% bipolar.labelorg = {'1', '2', '3', '4'}
% bipolar.labelnew = {'1-2', '2-3', '3-4'}
% bipolar.tra = [
% +1 -1 0 0
% 0 +1 -1 0
% 0 0 +1 -1
% ];
%
% Additional options should be specified in key-value pairs and can be
% 'keepunused' string, 'yes' or 'no' (default = 'no')
% 'inverse' string, 'yes' or 'no' (default = 'no')
%
% If the first input is a montage, then the second input montage will be
% applied to the first. In effect, the output montage will first do
% montage1, then montage2.
%
% See also FT_READ_SENS, FT_TRANSFORM_SENS
% Copyright (C) 2008-2012, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: ft_apply_montage.m 7394 2013-01-23 14:33:30Z jorhor $
% get optional input arguments
keepunused = ft_getopt(varargin, 'keepunused', 'no');
inverse = ft_getopt(varargin, 'inverse', 'no');
feedback = ft_getopt(varargin, 'feedback', 'text');
bname = ft_getopt(varargin, 'balancename', '');
if ~isfield(input, 'label') && isfield(input, 'labelnew')
% the input data structure is also a montage
inputlabel = input.labelnew;
else
% the input should describe the channel labels
inputlabel = input.label;
end
% check the consistency of the input inputor array or data
if ~all(isfield(montage, {'tra', 'labelorg', 'labelnew'}))
error('the second input argument does not correspond to a montage');
end
% check the consistency of the montage
if size(montage.tra,1)~=length(montage.labelnew)
error('the number of channels in the montage is inconsistent');
elseif size(montage.tra,2)~=length(montage.labelorg)
error('the number of channels in the montage is inconsistent');
end
if strcmp(inverse, 'yes')
% apply the inverse montage, i.e. undo a previously applied montage
tmp.labelnew = montage.labelorg; % swap around
tmp.labelorg = montage.labelnew; % swap around
tmp.tra = full(montage.tra);
if rank(tmp.tra) < length(tmp.tra)
warning('the linear projection for the montage is not full-rank, the resulting data will have reduced dimensionality');
tmp.tra = pinv(tmp.tra);
else
tmp.tra = inv(tmp.tra);
end
montage = tmp;
end
% use default transfer from sensors to channels if not specified
if isfield(input, 'pnt') && ~isfield(input, 'tra')
nchan = size(input.pnt,1);
input.tra = eye(nchan);
elseif isfield(input, 'chanpos') && ~isfield(input, 'tra')
nchan = size(input.chanpos,1);
input.tra = eye(nchan);
end
% select and keep the columns that are non-empty, i.e. remove the empty columns
selcol = find(~all(montage.tra==0, 1));
montage.tra = montage.tra(:,selcol);
montage.labelorg = montage.labelorg(selcol);
clear selcol
% select and remove the columns corresponding to channels that are not present in the original data
remove = setdiff(montage.labelorg, intersect(montage.labelorg, inputlabel));
selcol = match_str(montage.labelorg, remove);
% we cannot just remove the colums, all rows that depend on it should also be removed
selrow = false(length(montage.labelnew),1);
for i=1:length(selcol)
selrow = selrow & (montage.tra(:,selcol(i))~=0);
end
% convert from indices to logical vector
selcol = indx2logical(selcol, length(montage.labelorg));
% remove rows and columns
montage.labelorg = montage.labelorg(~selcol);
montage.labelnew = montage.labelnew(~selrow);
montage.tra = montage.tra(~selrow, ~selcol);
clear remove selcol selrow i
% add columns for the channels that are present in the data but not involved in the montage, and stick to the original order in the data
[add, ix] = setdiff(inputlabel, montage.labelorg);
add = inputlabel(sort(ix));
m = size(montage.tra,1);
n = size(montage.tra,2);
k = length(add);
if strcmp(keepunused, 'yes')
% add the channels that are not rereferenced to the input and output
montage.tra((m+(1:k)),(n+(1:k))) = eye(k);
montage.labelorg = cat(1, montage.labelorg(:), add(:));
montage.labelnew = cat(1, montage.labelnew(:), add(:));
else
% add the channels that are not rereferenced to the input montage only
montage.tra(:,(n+(1:k))) = zeros(m,k);
montage.labelorg = cat(1, montage.labelorg(:), add(:));
end
clear add m n k
% determine whether all channels are unique
m = size(montage.tra,1);
n = size(montage.tra,2);
if length(unique(montage.labelnew))~=m
error('not all output channels of the montage are unique');
end
if length(unique(montage.labelorg))~=n
error('not all input channels of the montage are unique');
end
% determine whether all channels that have to be rereferenced are available
if length(intersect(inputlabel, montage.labelorg))~=length(montage.labelorg)
error('not all channels that are required in the montage are available in the data');
end
% reorder the columns of the montage matrix
[selinput, selmontage] = match_str(inputlabel, montage.labelorg);
montage.tra = double(montage.tra(:,selmontage));
montage.labelorg = montage.labelorg(selmontage);
% making the tra matrix sparse will speed up subsequent multiplications
% but should not result in a sparse matrix
if size(montage.tra,1)>1
montage.tra = sparse(montage.tra);
end
inputtype = 'unknown';
if isfield(input, 'labelorg') && isfield(input, 'labelnew')
inputtype = 'montage';
elseif isfield(input, 'tra')
inputtype = 'sens';
elseif isfield(input, 'trial')
inputtype = 'raw';
elseif isfield(input, 'fourierspctrm')
inputtype = 'freq';
end
switch inputtype
case 'montage'
% apply the montage on top of the other montage
if isa(input.tra, 'single')
% sparse matrices and single precision do not match
input.tra = full(montage.tra) * input.tra;
else
input.tra = montage.tra * input.tra;
end
input.labelnew = montage.labelnew;
case 'sens'
% apply the montage to an electrode or gradiometer description
sens = input;
clear input
% apply the montage to the inputor array
if isa(sens.tra, 'single')
% sparse matrices and single precision do not match
sens.tra = full(montage.tra) * sens.tra;
else
sens.tra = montage.tra * sens.tra;
end
% The montage operates on the coil weights in sens.tra, but the output
% channels can be different. If possible, we want to keep the original
% channel positions and orientations.
[sel1, sel2] = match_str(montage.labelnew, inputlabel);
keepchans = length(sel1)==length(montage.labelnew);
if isfield(sens, 'chanpos')
if keepchans
sens.chanpos = sens.chanpos(sel2,:);
else
sens.chanpos = nan(numel(montage.labelnew),3);
%input = rmfield(input, 'chanpos');
end
end
if isfield(sens, 'chanori')
if keepchans
sens.chanori = sens.chanori(sel2,:);
else
sens.chanori = nan(numel(montage.labelnew),3);
%input = rmfield(input, 'chanori');
end
end
sens.label = montage.labelnew;
% keep track of the order of the balancing and which one is the current one
if strcmp(inverse, 'yes')
if isfield(sens, 'balance')% && isfield(sens.balance, 'previous')
if isfield(sens.balance, 'previous') && numel(sens.balance.previous)>=1
sens.balance.current = sens.balance.previous{1};
sens.balance.previous = sens.balance.previous(2:end);
elseif isfield(sens.balance, 'previous')
sens.balance.current = 'none';
sens.balance = rmfield(sens.balance, 'previous');
else
sens.balance.current = 'none';
end
end
elseif ~strcmp(inverse, 'yes') && ~isempty(bname)
if isfield(sens, 'balance'),
% check whether a balancing montage with name bname already exist,
% and if so, how many
mnt = fieldnames(sens.balance);
sel = strmatch(bname, mnt);
if numel(sel)==0,
% bname can stay the same
elseif numel(sel)==1
% the original should be renamed to 'bname1' and the new one should
% be 'bname2'
sens.balance.([bname, '1']) = sens.balance.(bname);
sens.balance = rmfield(sens.balance, bname);
if isfield(sens.balance, 'current') && strcmp(sens.balance.current, bname)
sens.balance.current = [bname, '1'];
end
if isfield(sens.balance, 'previous')
sel2 = strmatch(bname, sens.balance.previous);
if ~isempty(sel2)
sens.balance.previous{sel2} = [bname, '1'];
end
end
bname = [bname, '2'];
else
bname = [bname, num2str(length(sel)+1)];
end
end
if isfield(sens, 'balance') && isfield(sens.balance, 'current')
if ~isfield(sens.balance, 'previous')
sens.balance.previous = {};
end
sens.balance.previous = [{sens.balance.current} sens.balance.previous];
sens.balance.current = bname;
sens.balance.(bname) = montage;
end
end
% rename the output variable
input = sens;
clear sens
case 'raw';
% apply the montage to the raw data that was preprocessed using fieldtrip
data = input;
clear input
Ntrials = numel(data.trial);
ft_progress('init', feedback, 'processing trials');
for i=1:Ntrials
ft_progress(i/Ntrials, 'processing trial %d from %d\n', i, Ntrials);
if isa(data.trial{i}, 'single')
% sparse matrices and single precision do not match
data.trial{i} = full(montage.tra) * data.trial{i};
else
data.trial{i} = montage.tra * data.trial{i};
end
end
ft_progress('close');
data.label = montage.labelnew;
% rename the output variable
input = data;
clear data
case 'freq'
% apply the montage to the spectrally decomposed data
freq = input;
clear input
if strcmp(freq.dimord, 'rpttap_chan_freq')
siz = size(freq.fourierspctrm);
nrpt = siz(1);
nchan = siz(2);
nfreq = siz(3);
output = zeros(nrpt, size(montage.tra,1), nfreq);
for foilop=1:nfreq
output(:,:,foilop) = freq.fourierspctrm(:,:,foilop) * montage.tra';
end
elseif strcmp(freq.dimord, 'rpttap_chan_freq_time')
siz = size(freq.fourierspctrm);
nrpt = siz(1);
nchan = siz(2);
nfreq = siz(3);
ntime = siz(4);
output = zeros(nrpt, size(montage.tra,1), nfreq, ntime);
for foilop=1:nfreq
for toilop = 1:ntime
output(:,:,foilop,toilop) = freq.fourierspctrm(:,:,foilop,toilop) * montage.tra';
end
end
else
error('unsupported dimord in frequency data (%s)', freq.dimord);
end
% replace the Fourier spectrum
freq.fourierspctrm = output;
freq.label = montage.labelnew;
% rename the output variable
input = freq;
clear freq
otherwise
error('unrecognized input');
end % switch inputtype
% check whether the input contains chantype and/or chanunit and remove these
% as they may have been invalidated by the transform (e.g. with megplanar)
[sel1, sel2] = match_str(montage.labelnew, inputlabel);
keepchans = (length(sel1)==length(montage.labelnew));
if isfield(input, 'chantype')
if keepchans
% reorder them according to the montage
sens.chantype = input.chantype(sel2,:);
else
input = rmfield(input, 'chantype');
end
end
if isfield(input, 'chanunit')
if keepchans
% reorder them according to the montage
sens.chanunit = input.chanunit(sel2,:);
else
input = rmfield(input, 'chanunit');
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% HELPER FUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function y = indx2logical(x, n)
y = false(1,n);
y(x) = true;
|
github
|
philippboehmsturm/antx-master
|
read_erplabdata.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_erplabdata.m
| 2,110 |
utf_8
|
60380c3ce12bbfd85b4dd554bdc0ae20
|
% read_erplabdata() - import ERPLAB dataset files
%
% Usage:
% >> dat = read_erplabdata(filename);
%
% Inputs:
% filename - [string] file name
%
% Optional inputs:
% 'begtrial' - [integer] first trial to read
% 'endtrial' - [integer] last trial to read
% 'chanindx' - [integer] list with channel indices to read
% 'header' - FILEIO structure header
%
% Outputs:
% dat - data over the specified range
%
% Modified from read_eeglabheader
%123456789012345678901234567890123456789012345678901234567890123456789012
% Copyright (C) 2008 Arnaud Delorme, SCCN, INC, UCSD, [email protected]
%
% This program 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 2 of the License, or
% (at your option) any later version.
%
% This program 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 this program; if not, write to the Free Software
% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
function dat = read_erplabdata(filename, varargin);
if nargin < 1
help read_erplabdata;
return;
end;
header = ft_getopt(varargin, 'header');
begsample = ft_getopt(varargin, 'begsample');
endsample = ft_getopt(varargin, 'endsample');
begtrial = ft_getopt(varargin, 'begtrial');
endtrial = ft_getopt(varargin, 'endtrial');
chanindx = ft_getopt(varargin, 'chanindx');
if isempty(header)
header = read_erplabheader(filename);
end
dat = header.orig.bindata;
if isempty(begtrial), begtrial = 1; end;
if isempty(endtrial), endtrial = header.nTrials; end;
if isempty(begsample), begsample = 1; end;
if isempty(endsample), endsample = header.nSamples; end;
dat = dat(:,begsample:endsample,begtrial:endtrial);
if ~isempty(chanindx)
% select the desired channels
dat = dat(chanindx,:,:);
end
|
github
|
philippboehmsturm/antx-master
|
read_biosemi_bdf.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_biosemi_bdf.m
| 10,824 |
utf_8
|
c299fc321e8529aed582e5e6e746d24f
|
function dat = read_biosemi_bdf(filename, hdr, begsample, endsample, chanindx);
% READ_BIOSEMI_BDF reads specified samples from a BDF continous datafile
% It neglects all trial boundaries as if the data was acquired in
% non-continous mode.
%
% Use as
% [hdr] = read_biosemi_bdf(filename);
% where
% filename name of the datafile, including the .bdf extension
% This returns a header structure with the following elements
% hdr.Fs sampling frequency
% hdr.nChans number of channels
% hdr.nSamples number of samples per trial
% hdr.nSamplesPre number of pre-trigger samples in each trial
% hdr.nTrials number of trials
% hdr.label cell-array with labels of each channel
% hdr.orig detailled EDF header information
%
% Or use as
% [dat] = read_biosemi_bdf(filename, hdr, begsample, endsample, chanindx);
% where
% filename name of the datafile, including the .bdf extension
% hdr header structure, see above
% begsample index of the first sample to read
% endsample index of the last sample to read
% chanindx index of channels to read (optional, default is all)
% This returns a Nchans X Nsamples data matrix
% Copyright (C) 2006, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_biosemi_bdf.m 7123 2012-12-06 21:21:38Z roboos $
if nargin==1
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% read the header, this code is from EEGLAB's openbdf
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
FILENAME = filename;
% defines Seperator for Subdirectories
SLASH='/';
BSLASH=char(92);
cname=computer;
if cname(1:2)=='PC' SLASH=BSLASH; end;
fid=fopen(FILENAME,'r','ieee-le');
if fid<0
fprintf(2,['Error LOADEDF: File ' FILENAME ' not found\n']);
return;
end;
EDF.FILE.FID=fid;
EDF.FILE.OPEN = 1;
EDF.FileName = FILENAME;
PPos=min([max(find(FILENAME=='.')) length(FILENAME)+1]);
SPos=max([0 find((FILENAME=='/') | (FILENAME==BSLASH))]);
EDF.FILE.Ext = FILENAME(PPos+1:length(FILENAME));
EDF.FILE.Name = FILENAME(SPos+1:PPos-1);
if SPos==0
EDF.FILE.Path = pwd;
else
EDF.FILE.Path = FILENAME(1:SPos-1);
end;
EDF.FileName = [EDF.FILE.Path SLASH EDF.FILE.Name '.' EDF.FILE.Ext];
H1=char(fread(EDF.FILE.FID,256,'char')'); %
EDF.VERSION=H1(1:8); % 8 Byte Versionsnummer
%if 0 fprintf(2,'LOADEDF: WARNING Version EDF Format %i',ver); end;
EDF.PID = deblank(H1(9:88)); % 80 Byte local patient identification
EDF.RID = deblank(H1(89:168)); % 80 Byte local recording identification
%EDF.H.StartDate = H1(169:176); % 8 Byte
%EDF.H.StartTime = H1(177:184); % 8 Byte
EDF.T0=[str2num(H1(168+[7 8])) str2num(H1(168+[4 5])) str2num(H1(168+[1 2])) str2num(H1(168+[9 10])) str2num(H1(168+[12 13])) str2num(H1(168+[15 16])) ];
% Y2K compatibility until year 2090
if EDF.VERSION(1)=='0'
if EDF.T0(1) < 91
EDF.T0(1)=2000+EDF.T0(1);
else
EDF.T0(1)=1900+EDF.T0(1);
end;
else ;
% in a future version, this is hopefully not needed
end;
EDF.HeadLen = str2num(H1(185:192)); % 8 Byte Length of Header
% reserved = H1(193:236); % 44 Byte
EDF.NRec = str2num(H1(237:244)); % 8 Byte # of data records
EDF.Dur = str2num(H1(245:252)); % 8 Byte # duration of data record in sec
EDF.NS = str2num(H1(253:256)); % 8 Byte # of signals
EDF.Label = char(fread(EDF.FILE.FID,[16,EDF.NS],'char')');
EDF.Transducer = char(fread(EDF.FILE.FID,[80,EDF.NS],'char')');
EDF.PhysDim = char(fread(EDF.FILE.FID,[8,EDF.NS],'char')');
EDF.PhysMin= str2num(char(fread(EDF.FILE.FID,[8,EDF.NS],'char')'));
EDF.PhysMax= str2num(char(fread(EDF.FILE.FID,[8,EDF.NS],'char')'));
EDF.DigMin = str2num(char(fread(EDF.FILE.FID,[8,EDF.NS],'char')'));
EDF.DigMax = str2num(char(fread(EDF.FILE.FID,[8,EDF.NS],'char')'));
% check validity of DigMin and DigMax
if (length(EDF.DigMin) ~= EDF.NS)
fprintf(2,'Warning OPENEDF: Failing Digital Minimum\n');
EDF.DigMin = -(2^15)*ones(EDF.NS,1);
end
if (length(EDF.DigMax) ~= EDF.NS)
fprintf(2,'Warning OPENEDF: Failing Digital Maximum\n');
EDF.DigMax = (2^15-1)*ones(EDF.NS,1);
end
if (any(EDF.DigMin >= EDF.DigMax))
fprintf(2,'Warning OPENEDF: Digital Minimum larger than Maximum\n');
end
% check validity of PhysMin and PhysMax
if (length(EDF.PhysMin) ~= EDF.NS)
fprintf(2,'Warning OPENEDF: Failing Physical Minimum\n');
EDF.PhysMin = EDF.DigMin;
end
if (length(EDF.PhysMax) ~= EDF.NS)
fprintf(2,'Warning OPENEDF: Failing Physical Maximum\n');
EDF.PhysMax = EDF.DigMax;
end
if (any(EDF.PhysMin >= EDF.PhysMax))
fprintf(2,'Warning OPENEDF: Physical Minimum larger than Maximum\n');
EDF.PhysMin = EDF.DigMin;
EDF.PhysMax = EDF.DigMax;
end
EDF.PreFilt= char(fread(EDF.FILE.FID,[80,EDF.NS],'char')'); %
tmp = fread(EDF.FILE.FID,[8,EDF.NS],'char')'; % samples per data record
EDF.SPR = str2num(char(tmp)); % samples per data record
fseek(EDF.FILE.FID,32*EDF.NS,0);
EDF.Cal = (EDF.PhysMax-EDF.PhysMin)./(EDF.DigMax-EDF.DigMin);
EDF.Off = EDF.PhysMin - EDF.Cal .* EDF.DigMin;
tmp = find(EDF.Cal < 0);
EDF.Cal(tmp) = ones(size(tmp));
EDF.Off(tmp) = zeros(size(tmp));
EDF.Calib=[EDF.Off';(diag(EDF.Cal))];
%EDF.Calib=sparse(diag([1; EDF.Cal]));
%EDF.Calib(1,2:EDF.NS+1)=EDF.Off';
EDF.SampleRate = EDF.SPR / EDF.Dur;
EDF.FILE.POS = ftell(EDF.FILE.FID);
if EDF.NRec == -1 % unknown record size, determine correct NRec
fseek(EDF.FILE.FID, 0, 'eof');
endpos = ftell(EDF.FILE.FID);
EDF.NRec = floor((endpos - EDF.FILE.POS) / (sum(EDF.SPR) * 2));
fseek(EDF.FILE.FID, EDF.FILE.POS, 'bof');
H1(237:244)=sprintf('%-8i',EDF.NRec); % write number of records
end;
EDF.Chan_Select=(EDF.SPR==max(EDF.SPR));
for k=1:EDF.NS
if EDF.Chan_Select(k)
EDF.ChanTyp(k)='N';
else
EDF.ChanTyp(k)=' ';
end;
if findstr(upper(EDF.Label(k,:)),'ECG')
EDF.ChanTyp(k)='C';
elseif findstr(upper(EDF.Label(k,:)),'EKG')
EDF.ChanTyp(k)='C';
elseif findstr(upper(EDF.Label(k,:)),'EEG')
EDF.ChanTyp(k)='E';
elseif findstr(upper(EDF.Label(k,:)),'EOG')
EDF.ChanTyp(k)='O';
elseif findstr(upper(EDF.Label(k,:)),'EMG')
EDF.ChanTyp(k)='M';
end;
end;
EDF.AS.spb = sum(EDF.SPR); % Samples per Block
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% convert the header to Fieldtrip-style
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if any(EDF.SampleRate~=EDF.SampleRate(1))
error('channels with different sampling rate not supported');
end
hdr.Fs = EDF.SampleRate(1);
hdr.nChans = EDF.NS;
hdr.label = cellstr(EDF.Label);
% it is continuous data, therefore append all records in one trial
hdr.nTrials = 1;
hdr.nSamples = EDF.NRec * EDF.Dur * EDF.SampleRate(1);
hdr.nSamplesPre = 0;
hdr.orig = EDF;
% return the header
dat = hdr;
else
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% read the data
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% retrieve the original header
EDF = hdr.orig;
% determine the trial containing the begin and end sample
epochlength = EDF.Dur * EDF.SampleRate(1);
begepoch = floor((begsample-1)/epochlength) + 1;
endepoch = floor((endsample-1)/epochlength) + 1;
nepochs = endepoch - begepoch + 1;
nchans = EDF.NS;
if nargin<5
chanindx = 1:nchans;
end
% allocate memory to hold the data
dat = zeros(length(chanindx),nepochs*epochlength);
% read and concatenate all required data epochs
for i=begepoch:endepoch
offset = EDF.HeadLen + (i-1)*epochlength*nchans*3;
if length(chanindx)==1
% this is more efficient if only one channel has to be read, e.g. the status channel
offset = offset + (chanindx-1)*epochlength*3;
buf = readLowLevel(filename, offset, epochlength); % see below in subfunction
dat(:,((i-begepoch)*epochlength+1):((i-begepoch+1)*epochlength)) = buf;
else
% read the data from all channels and then select the desired channels
buf = readLowLevel(filename, offset, epochlength*nchans); % see below in subfunction
buf = reshape(buf, epochlength, nchans);
dat(:,((i-begepoch)*epochlength+1):((i-begepoch+1)*epochlength)) = buf(:,chanindx)';
end
end
% select the desired samples
begsample = begsample - (begepoch-1)*epochlength; % correct for the number of bytes that were skipped
endsample = endsample - (begepoch-1)*epochlength; % correct for the number of bytes that were skipped
dat = dat(:, begsample:endsample);
% Calibrate the data
calib = diag(EDF.Cal(chanindx));
if length(chanindx)>1
% using a sparse matrix speeds up the multiplication
dat = sparse(calib) * dat;
else
% in case of one channel the sparse multiplication would result in a sparse array
dat = calib * dat;
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION for reading the 24 bit values
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function buf = readLowLevel(filename, offset, numwords);
if offset < 2*1024^3
% use the external mex file, only works for <2GB
buf = read_24bit(filename, offset, numwords);
% this would be the only difference between the bdf and edf implementation
% buf = read_16bit(filename, offset, numwords);
else
% use plain matlab, thanks to Philip van der Broek
fp = fopen(filename,'r','ieee-le');
status = fseek(fp, offset, 'bof');
if status
error(['failed seeking ' filename]);
end
[buf,num] = fread(fp,numwords,'bit24=>double');
fclose(fp);
if (num<numwords)
error(['failed opening ' filename]);
return
end
end
|
github
|
philippboehmsturm/antx-master
|
read_ctf_ascii.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_ctf_ascii.m
| 3,218 |
utf_8
|
ed3ebfd532e8ac61a7237dede21d739b
|
function [file] = read_ctf_ascii(filename);
% READ_CTF_ASCII reads general data from an CTF configuration file
%
% The file should be formatted like
% Group
% {
% item1 : value1a value1b value1c
% item2 : value2a value2b value2c
% item3 : value3a value3b value3c
% item4 : value4a value4b value4c
% }
%
% This fileformat structure is used in
% params.avg
% default.hdm
% multiSphere.hdm
% processing.cfg
% and maybe for other files as well.
% Copyright (C) 2003, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_ctf_ascii.m 7123 2012-12-06 21:21:38Z roboos $
fid = fopen(filename, 'r');
if fid==-1
error(sprintf('could not open file %s', filename));
end
line = '';
while ischar(line)
line = cleanline(fgetl(fid));
if isempty(line) || (length(line)==1 && all(line==-1))
continue
end
% the line is not empty, which means that we have encountered a chunck of information
subline = cleanline(fgetl(fid)); % read the {
subline = cleanline(fgetl(fid)); % read the first item
while isempty(findstr(subline, '}'))
if ~isempty(subline)
[item, value] = strtok(subline, ':');
value(1) = ' '; % remove the :
value = strtrim(value);
item = strtrim(item);
% turn warnings off
ws = warning('off');
% the item name should be a real string, otherwise I cannot put it into the structure
if strcmp(sprintf('%d', str2num(deblank(item))), deblank(item))
% add something to the start of the string to distinguish it from a number
item = ['item_' item];
end
% the value can be either a number or a string, and is put into the structure accordingly
if isempty(str2num(value))
% the value appears to be a string
eval(sprintf('file.%s.%s = [ ''%s'' ];', line, item, value));
else
% the value appears to be a number or a list of numbers
eval(sprintf('file.%s.%s = [ %s ];', line, item, value));
end
% revert to previous warning state
warning(ws);
end
subline = cleanline(fgetl(fid)); % read the first item
end
end
fclose(fid);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function line = cleanline(line)
if isempty(line) || (length(line)==1 && all(line==-1))
return
end
comment = findstr(line, '//');
if ~isempty(comment)
line(min(comment):end) = ' ';
end
line = strtrim(line);
|
github
|
philippboehmsturm/antx-master
|
read_mpi_dap.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_mpi_dap.m
| 7,085 |
utf_8
|
a51b5774d3dc46b048015b2b12e95e76
|
function [dap] = read_mpi_dap(filename)
% READ_MPI_DAP read the analog channels from a DAP file
% and returns the values in microvolt (uV)
%
% Use as
% [dap] = read_mpi_dap(filename)
% Copyright (C) 2005-2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_mpi_dap.m 7123 2012-12-06 21:21:38Z roboos $
fid = fopen(filename, 'rb', 'ieee-le');
% read the file header
filehdr = readheader(fid);
analog = {};
analoghdr = {};
analogsweephdr = {};
spike = {};
spikehdr = {};
spikesweephdr = {};
W = filehdr.nexps;
S = filehdr.nsweeps;
for w=1:filehdr.nexps
% read the experiment header
exphdr{w} = readheader(fid);
if filehdr.nanalog
if filehdr.analogmode==-1
% record mode
for s=1:filehdr.nsweeps
% read the analogsweepheader
analogsweephdr{s} = readheader(fid);
for j=1:filehdr.nanalog
% read the analog header
analoghdr{w,s,j} = readheader(fid);
% read the analog data
analog{w,s,j} = fread(fid, analoghdr{w,s,j}.datasize, 'int16');
% calibrate the analog data
analog{w,s,j} = analog{w,s,j} * 2.5/2048;
end
end % for s=1:S
elseif filehdr.analogmode==0
% average mode
s = 1;
for j=1:filehdr.nanalog
% read the analog header
analoghdr{w,s,j} = readheader(fid);
% read the analog data
analog{w,s,j} = fread(fid, analoghdr{w,s,j}.datasize, 'int16');
% calibrate the analog data
analog{w,s,j} = analog{w,s,j} * 2.5/2048;
end
else
error('unknown analog mode');
end
end
if filehdr.nspike
for s=1:filehdr.nsweeps
spikesweephdr{s} = readheader(fid);
for j=1:filehdr.nspike
% read the spike header
spikehdr{w,s,j} = readheader(fid);
% read the spike data
spike{w,s,j} = fread(fid, spikehdr{w,s,j}.datasize, 'int16');
end
end % for s=1:S
end
end % for w=1:W
dap.filehdr = filehdr;
dap.exphdr = exphdr;
dap.analogsweephdr = analogsweephdr;
dap.analoghdr = analoghdr;
dap.analog = analog;
dap.spikesweephdr = spikesweephdr;
dap.spikehdr = spikehdr;
dap.spike = spike;
fclose(fid);
return;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function hdr = readheader(fid);
% determine the header type, header size and data size
hdr.headertype = fread(fid, 1, 'uchar');
dummy = fread(fid, 1, 'uchar');
hdr.headersize = fread(fid, 1, 'int16') + 1; % expressed in words, not bytes
hdr.datasize = fread(fid, 1, 'int16'); % expressed in words, not bytes
% read the header details
switch hdr.headertype
case 1 % fileheader
% fprintf('fileheader at %d\n' ,ftell(fid)-6);
dummy = fread(fid, 1, 'uchar')'; % 6
hdr.nexps = fread(fid, 1, 'uchar')'; % 7
hdr.progname = fread(fid, 7, 'uchar')'; % 8-14
hdr.version = fread(fid, 1, 'uchar')'; % 15
hdr.progversion = fread(fid, 2, 'uchar')'; % 16-17
hdr.fileversion = fread(fid, 2, 'uchar')'; % 18-19
hdr.date = fread(fid, 1, 'int16'); % 20-21
hdr.time = fread(fid, 1, 'int16'); % 22-23
hdr.nanalog = fread(fid, 1, 'uint8'); % 24
hdr.nspike = fread(fid, 1, 'uint8'); % 25
hdr.nbins = fread(fid, 1, 'int16'); % 26-27
hdr.binwidth = fread(fid, 1, 'int16'); % 28-29
dummy = fread(fid, 1, 'int16'); % 30-31
hdr.nsweeps = fread(fid, 1, 'int16'); % 32-33
hdr.analogmode = fread(fid, 1, 'uchar')'; % 34 "0 for average, -1 for record"
dummy = fread(fid, 1, 'uchar')'; % 35
dummy = fread(fid, 1, 'int16'); % 36-37
dummy = fread(fid, 1, 'int16'); % 38-39
dummy = fread(fid, 1, 'int16'); % 40-41
case 65 % expheader
% fprintf('expheader at %d\n' ,ftell(fid)-6);
hdr.time = fread(fid, 1, 'int16'); % 6-7
hdr.parallel = fread(fid, 1, 'int16'); % 8-9
hdr.id = fread(fid, 1, 'int16'); % 10-11
dummy = fread(fid, 1, 'int16'); % 12-13
dummy = fread(fid, 1, 'int16'); % 14-15
dummy = fread(fid, 1, 'int16'); % 16-17
case 129 % analogchannelheader
% fprintf('analogchannelheader at %d\n' ,ftell(fid)-6);
dummy = fread(fid, 1, 'int16'); % 6-7
hdr.channum = fread(fid, 1, 'uchar'); % 8
dummy = fread(fid, 1, 'uchar'); % 9
dummy = fread(fid, 1, 'int16'); % 10-11
dummy = fread(fid, 1, 'int16'); % 12-13
dummy = fread(fid, 1, 'int16'); % 14-15
dummy = fread(fid, 1, 'int16'); % 16-17
case 161 % spikechannelheader
% fprintf('spikechannelheader at %d\n' ,ftell(fid)-6);
dummy = fread(fid, 1, 'int16'); % 6-7
hdr.channum = fread(fid, 1, 'uchar'); % 8
dummy = fread(fid, 1, 'uchar'); % 9
dummy = fread(fid, 1, 'int16'); % 10-11
dummy = fread(fid, 1, 'int16'); % 12-13
dummy = fread(fid, 1, 'int16'); % 14-15
dummy = fread(fid, 1, 'int16'); % 16-17
case 137 % analogsweepheader
% fprintf('analogsweepheader at %d\n' ,ftell(fid)-6);
hdr.sweepnum = fread(fid, 1, 'int16'); % 6-7
hdr.parallel = fread(fid, 1, 'int16'); % 8-9
dummy = fread(fid, 1, 'int16'); % 10-11
dummy = fread(fid, 1, 'int16'); % 12-13
dummy = fread(fid, 1, 'int16'); % 14-15
dummy = fread(fid, 1, 'int16'); % 16-17
case 169 % spikesweepheader
% fprintf('spikesweepheader at %d\n' ,ftell(fid)-6);
hdr.sweepnum = fread(fid, 1, 'int16'); % 6-7
hdr.parallel = fread(fid, 1, 'int16'); % 8-9
dummy = fread(fid, 1, 'int16'); % 10-11
dummy = fread(fid, 1, 'int16'); % 12-13
dummy = fread(fid, 1, 'int16'); % 14-15
dummy = fread(fid, 1, 'int16'); % 16-17
otherwise
error(sprintf('unsupported format for header (%d)', hdr.headertype));
end
|
github
|
philippboehmsturm/antx-master
|
read_neuralynx_bin.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_neuralynx_bin.m
| 6,705 |
utf_8
|
1851b52bfcf664aadb50e417bd3ab74b
|
function [dat] = read_neuralynx_bin(filename, begsample, endsample);
% READ_NEURALYNX_BIN
%
% Use as
% hdr = read_neuralynx_bin(filename)
% or
% dat = read_neuralynx_bin(filename, begsample, endsample)
%
% This is not a formal Neuralynx file format, but at the
% F.C. Donders Centre we use it in conjunction with Neuralynx,
% SPIKESPLITTING and SPIKEDOWNSAMPLE.
%
% The first version of this file format contained in the first 8 bytes the
% channel label as string. Subsequently it contained 32 bit integer values.
%
% The second version of this file format starts with 8 bytes describing (as
% a space-padded string) the data type. The channel label is contained in
% the filename as dataset.chanlabel.bin.
%
% The third version of this file format starts with 7 bytes describing (as
% a zero-padded string) the data type, followed by the 8th byte which
% describes the downscaling for the 8 and 16 bit integer representations.
% The downscaling itself is represented as uint8 and should be interpreted as
% the number of bits to shift. The channel label is contained in the
% filename as dataset.chanlabel.bin.
% Copyright (C) 2007-2008, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_neuralynx_bin.m 7123 2012-12-06 21:21:38Z roboos $
needhdr = (nargin==1);
needdat = (nargin>=2);
% this is used for backward compatibility
oldformat = false;
% the first 8 bytes contain the header
fid = fopen(filename, 'rb', 'ieee-le');
magic = fread(fid, 8, 'uint8=>char')';
% the header describes the format of the subsequent samples
subtype = [];
if strncmp(magic, 'uint8', length('uint8'))
format = 'uint8';
samplesize = 1;
elseif strncmp(magic, 'int8', length('int8'))
format = 'int8';
samplesize = 1;
elseif strncmp(magic, 'uint16', length('uint16'))
format = 'uint16';
samplesize = 2;
elseif strncmp(magic, 'int16', length('int16'))
format = 'int16';
samplesize = 2;
elseif strncmp(magic, 'uint32', length('uint32'))
format = 'uint32';
samplesize = 4;
elseif strncmp(magic, 'int32', length('int32'))
format = 'int32';
samplesize = 4;
elseif strncmp(magic, 'uint64', length('uint64'))
format = 'uint64';
samplesize = 8;
elseif strncmp(magic, 'int64', length('int64'))
format = 'int64';
samplesize = 8;
elseif strncmp(magic, 'float32', length('float32'))
format = 'float32';
samplesize = 4;
elseif strncmp(magic, 'float64', length('float64'))
format = 'float64';
samplesize = 8;
else
warning('could not detect sample format, assuming file format subtype 1 with ''int32''');
subtype = 1; % the file format is version 1
format = 'int32';
samplesize = 4;
end
% determine whether the file format is version 2 or 3
if isempty(subtype)
if all(magic((length(format)+1):end)==' ')
subtype = 2;
else
subtype = 3;
end
end
% determine the channel name
switch subtype
case 1
% the first 8 bytes of the file contain the channel label (padded with spaces)
label = strtrim(magic);
case {2, 3}
% the filename is formatted like "dataset.chanlabel.bin"
[p, f, x1] = fileparts(filename);
[p, f, x2] = fileparts(f);
if isempty(x2)
warning('could not determine channel label');
label = 'unknown';
else
label = x2(2:end);
end
clear p f x1 x2
otherwise
error('unknown file format subtype');
end
% determine the downscale factor, i.e. the number of bits that the integer representation has to be shifted back to the left
switch subtype
case 1
% these never contained a multiplication factor but always corresponded
% to the lowest N bits of the original 32 bit integer
downscale = 0;
case 2
% these might contain a multiplication factor but that factor cannot be retrieved from the file
warning('downscale factor is unknown for ''%s'', assuming that no downscaling was applied', filename);
downscale = 0;
case 3
downscale = double(magic(8));
otherwise
error('unknown file format subtype');
end
[p1, f1, x1] = fileparts(filename);
[p2, f2, x2] = fileparts(f1);
headerfile = fullfile(p1, [f2, '.txt']);
if exist(headerfile, 'file')
orig = neuralynx_getheader(headerfile);
% construct the header from the accompanying text file
hdr = [];
hdr.Fs = orig.SamplingFrequency;
hdr.nChans = 1;
hdr.nSamples = (filesize(filename)-8)/samplesize;
hdr.nSamplesPre = 0;
hdr.nTrials = 1;
hdr.label = {label};
else
% construct the header from the hard-coded defaults
hdr = [];
hdr.Fs = 32556;
hdr.nChans = 1;
hdr.nSamples = (filesize(filename)-8)/samplesize;
hdr.nSamplesPre = 0;
hdr.nTrials = 1;
hdr.label = {label};
end
if ~needdat
% also return the file details
hdr.orig.subtype = subtype;
hdr.orig.magic = magic;
hdr.orig.format = format;
hdr.orig.downscale = downscale;
% return only the header details
dat = hdr;
else
% read and return the data
if begsample<1
begsample = 1;
end
if isinf(endsample)
endsample = hdr.nSamples;
end
fseek(fid, 8+(begsample-1)*samplesize, 'bof'); % skip to the beginning of the interesting data
format = sprintf('%s=>%s', format, format);
dat = fread(fid, [1 endsample-begsample+1], format);
if downscale>1
% the data was downscaled with 2^N, i.e. shifted N bits to the right in case of integer representations
% now it should be upscaled again with the same amount
dat = dat.*(2^downscale);
end
if length(dat)<(endsample-begsample+1)
error('could not read the requested data');
end
end % needdat
fclose(fid);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION to determine the file size in bytes
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [siz] = filesize(filename)
l = dir(filename);
if l.isdir
error(sprintf('"%s" is not a file', filename));
end
siz = l.bytes;
|
github
|
philippboehmsturm/antx-master
|
inifile.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/inifile.m
| 23,578 |
utf_8
|
f647125ffa71c22e44a119c27e73d460
|
function readsett = inifile(fileName,operation,keys,style)
%readsett = INIFILE(fileName,operation,keys,style)
% Creates, reads, or writes data from/to ini (ascii) file.
%
% - fileName: ini file name
% - operation: can be one of the following:
% 'new' (rewrites an existing or creates a new, empty file),
% 'deletekeys'(deletes keys and their values - if they exist),
% 'read' (reads values as strings),
% 'write' (writes values given as strings),
% - keys: cell array of STRINGS; max 5 columns, min
% 3 columns. Each row has the same number of columns. The columns are:
% 'section': section name string (the root is considered if empty or not given)
% 'subsection': subsection name string (the root is considered if empty or not given)
% 'key': name of the field to write/read from (given as a string).
% 'value': (optional) string-value to write to the ini file in case of 'write' operation
% 'defaultValue': (optional) value that is returned when the key is not found when reading ('read' operation)
% - style: 'tabbed' writes sections, subsections and keys in a tabbed style
% to get a more readable file. The 'plain' style is the
% default style. This only affects the keys that will be written/rewritten.
%
% - readsett: read setting in the case of the 'read' operation. If
% the keys are not found, the default values are returned
% as strings (if given in the 5-th column).
%
% EXAMPLE:
% Suppose we want a new ini file, test1.ini with 3 fields.
% We can write them into the file using:
%
% inifile('test1.ini','new');
% writeKeys = {'measurement','person','name','Primoz Cermelj';...
% 'measurement','protocol','id','1';...
% 'application','','description','some...'};
% inifile('test1.ini','write',writeKeys,'plain');
%
% Later, you can read them out. Additionally, if any of them won't
% exist, a default value will be returned (if the 5-th column is given as below).
%
% readKeys = {'measurement','person','name','','John Doe';...
% 'measurement','protocol','id','','0';...
% 'application','','description','','none'};
% readSett = inifile('test1.ini','read',readKeys);
%
%
% NOTES: When the operation is 'new', only the first 2 parameters are
% required. If the operation is 'write' and the file is empty or does not exist,
% a new file is created. When writing and if any of the section or subsection or key does not exist,
% it creates (adds) a new one.
% Everything but value is NOT case sensitive. Given keys and values
% will be trimmed (leading and trailing spaces will be removed).
% Any duplicates (section, subsection, and keys) are ignored. Empty section and/or
% subsection can be given as an empty string, '', but NOT as an empty matrix, [].
%
% This function was tested on the win32 platform only but it should
% also work on Unix/Linux platforms. Since some short-circuit operators
% are used, at least Matlab 6.5 should be used.
%
% FREE SOFTWARE - please refer the source
% Copyright (c) 2003 by Primoz Cermelj
% First release on 29.01.2003
% Primoz Cermelj, Slovenia
% Contact: [email protected]
% Download location: http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=2976&objectType=file
%
% Version: 1.1.0
% Last revision: 04.02.2004
%
% Bug reports, questions, etc. can be sent to the e-mail given above.
%
% This programme 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 2
% of the License, or any later version.
%
% This programme 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.
%--------------------------------------------------------------------------
%----------------
% INIFILE history
%----------------
%
% [v.1.1.0] 04.02.2004
% - FIX: 'writetext' option removed (there was a bug previously)
%
% [v.1.01b] 19.12.2003
% - NEW: A new concept - multiple keys can now be read, written, or deleted
% ALL AT ONCE which makes this function much faster. For example, to
% write 1000 keys, using previous versions it took 157 seconds on a
% 1.5 GHz machine, with this new version it took only 1.83 seconds.
% In general, the speed improvement is greater when larger number of
% read/written keys are considered.
% - NEW: The format of the input parameters has changed. See above.
%
% [v.0.97] 19.11.2003
% - NEW: Additional m-function, strtrim, is no longer needed
%
% [v.0.96] 16.10.2003
% - FIX: Detects empty keys
%
% [v.0.95] 04.07.2003
% - NEW: 'deletekey' option/operation added
% - FIX: A major file refinement to obtain a more compact utility -> additional operations can "easily" be implemented
%
% [v.0.91-0.94]
% - FIX: Some minor refinements
%
% [v.0.90] 29.01.2003
% - NEW: First release of this tool
%
%----------------
global NL_CHAR;
% Checks the input arguments
if nargin < 2
error('Not enough input arguments');
end
if (strcmpi(operation,'read')) | (strcmpi(operation,'deletekeys'))
if nargin < 3
error('Not enough input arguments.');
end
if ~exist(fileName)
error(['File ' fileName ' does not exist.']);
end
[m,n] = size(keys);
if n > 5
error('Keys argument has too many columns');
end
for ii=1:m
if isempty(keys(ii,3)) | ~ischar(keys{ii,3})
error('Empty or non-char keys are not allowed.');
end
end
elseif (strcmpi(operation,'write')) | (strcmpi(operation,'writetext'))
if nargin < 3
error('Not enough input arguments');
end
[m,n] = size(keys);
for ii=1:m
if isempty(keys(ii,3)) | ~ischar(keys{ii,3})
error('Empty or non-char keys are not allowed.');
end
end
elseif (~strcmpi(operation,'new'))
error(['Unknown inifile operation: ''' operation '''']);
end
if nargin >= 3
for ii=1:m
for jj=1:n
if ~ischar(keys{ii,jj})
error('All cells from keys must be given as strings, even the empty ones.');
end
end
end
end
if nargin < 4 || isempty(style)
style = 'plain';
else
if ~(strcmpi(style,'plain') | strcmpi(style,'tabbed')) | ~ischar(style)
error('Unsupported style given or style not given as a string');
end
end
% Sets new-line character (string)
if ispc
NL_CHAR = '\r\n';
else
NL_CHAR = '\n';
end
%----------------------------
% CREATES a new, empty file (rewrites an existing one)
%----------------------------
if strcmpi(operation,'new')
fh = fopen(fileName,'w');
if fh == -1
error(['File: ''' fileName ''' can not be (re)created']);
end
fclose(fh);
return
%----------------------------
% READS key-value pairs out
%----------------------------
elseif (strcmpi(operation,'read'))
if n < 5
defaultValues = cellstrings(m,1);
else
defaultValues = keys(:,5);
end
readsett = defaultValues;
keysIn = keys(:,1:3);
[secsExist,subsecsExist,keysExist,readValues,so,eo] = findkeys(fileName,keysIn);
ind = find(keysExist);
if ~isempty(ind)
readsett(ind) = readValues(ind);
end
return
%----------------------------
% WRITES key-value pairs to an existing or non-existing
% file (file can even be empty)
%----------------------------
elseif (strcmpi(operation,'write'))
if m < 1
error('At least one key is needed when writing keys');
end
if ~exist(fileName)
inifile(fileName,'new');
end
writekeys(fileName,keys,style);
return
%----------------------------
% DELETES key-value pairs out
%----------------------------
elseif (strcmpi(operation,'deletekeys'))
deletekeys(fileName,keys);
else
error('Unknown operation for INIFILE.');
end
%--------------------------------------------------
%%%%%%%%%%%%% SUBFUNCTIONS SECTION %%%%%%%%%%%%%%%%
%--------------------------------------------------
%------------------------------------
function [secsExist,subSecsExist,keysExist,values,startOffsets,endOffsets] = findkeys(fileName,keysIn)
% This function parses ini file for keys as given by keysIn. keysIn is a cell
% array of strings having 3 columns; section, subsection and key in each row.
% section and/or subsection can be empty (root section or root subsection)
% but the key can not be empty. The startOffsets and endOffsets are start and
% end bytes that each key occuppies, respectively. If any of the keys doesn't exist,
% startOffset and endOffset for this key are the same. A special case is
% when the key that doesn't exist also corresponds to a non-existing
% section and non-existing subsection. In such a case, the startOffset and
% endOffset have values of -1.
nKeys = size(keysIn,1); % number of keys
nKeysLocated = 0; % number of keys located
secsExist = zeros(nKeys,1); % if section exists (and is non-empty)
subSecsExist = zeros(nKeys,1); % if subsection...
keysExist = zeros(nKeys,1); % if key that we are looking for exists
keysLocated = keysExist; % if the key's position (existing or non-existing) is LOCATED
values = cellstrings(nKeys,1); % read values of keys (strings)
startOffsets = -ones(nKeys,1); % start byte-position of the keys
endOffsets = -ones(nKeys,1); % end byte-position of the keys
keyInd = find(strcmpi(keysIn(:,1),'')); % key indices having [] section (root section)
line = [];
currSection = '';
currSubSection = '';
fh = fopen(fileName,'r');
if fh == -1
error(['File: ''' fileName ''' does not exist or can not be opened.']);
end
try
%--- Searching for the keys - their values and start and end locations in bytes
while 1
pos1 = ftell(fh);
line = fgetl(fh);
if line == -1 % end of file, exit
line = [];
break
end
[status,readValue,readKey] = processiniline(line);
if (status == 1) % (new) section found
% Keys that were found as belonging to any previous section
% are now assumed as located (because another
% section is found here which could even be a repeated one)
keyInd = find( ~keysLocated & strcmpi(keysIn(:,1),currSection) );
if length(keyInd)
keysLocated(keyInd) = 1;
nKeysLocated = nKeysLocated + length(keyInd);
end
currSection = readValue;
currSubSection = '';
% Indices to non-located keys belonging to current section
keyInd = find( ~keysLocated & strcmpi(keysIn(:,1),currSection) );
if ~isempty(keyInd)
secsExist(keyInd) = 1;
end
pos2 = ftell(fh);
startOffsets(keyInd) = pos2+1;
endOffsets(keyInd) = pos2+1;
elseif (status == 2) % (new) subsection found
% Keys that were found as belonging to any PREVIOUS section
% and/or subsection are now assumed as located (because another
% subsection is found here which could even be a repeated one)
keyInd = find( ~keysLocated & strcmpi(keysIn(:,1),currSection) & ~keysLocated & strcmpi(keysIn(:,2),currSubSection));
if length(keyInd)
keysLocated(keyInd) = 1;
nKeysLocated = nKeysLocated + length(keyInd);
end
currSubSection = readValue;
% Indices to non-located keys belonging to current section and subsection at the same time
keyInd = find( ~keysLocated & strcmpi(keysIn(:,1),currSection) & ~keysLocated & strcmpi(keysIn(:,2),currSubSection));
if ~isempty(keyInd)
subSecsExist(keyInd) = 1;
end
pos2 = ftell(fh);
startOffsets(keyInd) = pos2+1;
endOffsets(keyInd) = pos2+1;
elseif (status == 3) % key found
if isempty(keyInd)
continue % no keys from 'keys' - from section-subsection par currently in
end
currKey = readValue;
pos2 = ftell(fh); % the last-byte position of the read key - the total sum of chars read so far
for ii=1:length(keyInd)
if strcmpi( keysIn(keyInd(ii),3),readKey ) & ~keysLocated(keyInd(ii))
keysExist(keyInd(ii)) = 1;
startOffsets(keyInd(ii)) = pos1+1;
endOffsets(keyInd(ii)) = pos2;
values{keyInd(ii)} = currKey;
keysLocated(keyInd(ii)) = 1;
nKeysLocated = nKeysLocated + 1;
else
if ~keysLocated(keyInd(ii))
startOffsets(keyInd(ii)) = pos2+1;
endOffsets(keyInd(ii)) = pos2+1;
end
end
end
if nKeysLocated >= nKeys % if all the keys are located
break
end
else
% general text found (even empty line(s))
end
%--- End searching
end
fclose(fh);
catch
fclose(fh);
error(['Error parsing the file for keys: ' fileName ': ' lasterr]);
end
%------------------------------------
%------------------------------------
function writekeys(fileName,keys,style)
% Writes keys to the section and subsection pair
% If any of the keys doesn't exist, a new key is added to
% the end of the section-subsection pair otherwise the key is updated (changed).
% Keys is a 4-column cell array of strings.
global NL_CHAR;
RETURN = sprintf('\r');
NEWLINE = sprintf('\n');
[m,n] = size(keys);
if n < 4
error('Keys to be written are given in an invalid format.');
end
% Get keys position first using findkeys
keysIn = keys;
[secsExist,subSecsExist,keysExist,readValues,so,eo] = findkeys(fileName,keys(:,1:3));
% Read the whole file's contents out
fh = fopen(fileName,'r');
if fh == -1
error(['File: ''' fileName ''' does not exist or can not be opened.']);
end
try
dataout = fscanf(fh,'%c');
catch
fclose(fh);
error(lasterr);
end
fclose(fh);
%--- Rewriting the file -> writing the refined contents
fh = fopen(fileName,'w');
if fh == -1
error(['File: ''' fileName ''' does not exist or can not be opened.']);
end
try
tab1 = [];
if strcmpi(style,'tabbed')
tab1 = sprintf('\t');
end
% Proper sorting of keys is cruical at this point in order to avoid
% inproper key-writing.
% Find keys with -1 offsets - keys with non-existing section AND
% subsection - keys that will be added to the end of the file
fs = length(dataout); % file size in bytes
nAddedKeys = 0;
ind = find(so==-1);
if ~isempty(ind)
so(ind) = (fs+10); % make sure these keys will come to the end when sorting
eo(ind) = (fs+10);
nAddedKeys = length(ind);
end
% Sort keys according to start- and end-offsets
[dummy,ind] = sort(so,1);
so = so(ind);
eo = eo(ind);
keysIn = keysIn(ind,:);
keysExist = keysExist(ind);
secsExist = secsExist(ind);
subSecsExist = subSecsExist(ind);
readValues = readValues(ind);
values = keysIn(:,4);
% Find keys with equal start offset (so) and additionally sort them
% (locally). These are non-existing keys, including the ones whose
% section and subsection will also be added.
nKeys = size(so,1);
fullInd = 1:nKeys;
ii = 1;
while ii < nKeys
ind = find(so==so(ii));
if ~isempty(ind) && length(ind) > 1
n = length(ind);
from = ind(1);
to = ind(end);
tmpKeys = keysIn( ind,: );
[tmpKeys,ind2] = sortrows( lower(tmpKeys) );
fullInd(from:to) = ind(ind2);
ii = ii + n;
else
ii = ii + 1;
end
end
% Final (re)sorting
so = so(fullInd);
eo = eo(fullInd);
keysIn = keysIn(fullInd,:);
keysExist = keysExist(fullInd);
secsExist = secsExist(fullInd);
subSecsExist = subSecsExist(fullInd);
readValues = readValues(fullInd);
values = keysIn(:,4);
% Refined data - datain
datain = [];
for ii=1:nKeys % go through all the keys, existing and non-existing ones
if ii==1
from = 1; % from byte-offset of original data (dataout)
else
from = eo(ii-1);
if keysExist(ii-1)
from = from + 1;
end
end
to = min(so(ii)-1,fs); % to byte-offset of original data (dataout)
if ~isempty(dataout)
datain = [datain dataout(from:to)]; % the lines before the key
end
if length(datain) & (~(datain(end)==RETURN | datain(end)==NEWLINE))
datain = [datain, sprintf(NL_CHAR)];
end
tab = [];
if ~keysExist(ii)
if ~secsExist(ii) && ~isempty(keysIn(ii,1))
if ~isempty(keysIn{ii,1})
datain = [datain sprintf(['%s' NL_CHAR],['[' keysIn{ii,1} ']'])];
end
% Key-indices with the same section as this, ii-th key (even empty sections are considered)
ind = find( strcmpi( keysIn(:,1), keysIn(ii,1)) );
% This section exists at all keys corresponding to the same section from know on (even the empty ones)
secsExist(ind) = 1;
end
if ~subSecsExist(ii) && ~isempty(keysIn(ii,2))
if ~isempty( keysIn{ii,2})
if secsExist(ii); tab = tab1; end;
datain = [datain sprintf(['%s' NL_CHAR],[tab '{' keysIn{ii,2} '}'])];
end
% Key-indices with the same section AND subsection as this, ii-th key (even empty sections and subsections are considered)
ind = find( strcmpi( keysIn(:,1), keysIn(ii,1)) & strcmpi( keysIn(:,2), keysIn(ii,2)) );
% This subsection exists at all keys corresponding to the same section and subsection from know on (even the empty ones)
subSecsExist(ind) = 1;
end
end
if secsExist(ii) & (~isempty(keysIn{ii,1})); tab = tab1; end;
if subSecsExist(ii) & (~isempty(keysIn{ii,2})); tab = [tab tab1]; end;
datain = [datain sprintf(['%s' NL_CHAR],[tab keysIn{ii,3} ' = ' values{ii}])];
end
from = eo(ii);
if keysExist(ii)
from = from + 1;
end
to = length(dataout);
if from < to
datain = [datain dataout(from:to)];
end
fprintf(fh,'%c',datain);
catch
fclose(fh);
error(['Error writing keys to file: ''' fileName ''' : ' lasterr]);
end
fclose(fh);
%------------------------------------
%------------------------------------
function deletekeys(fileName,keys)
% Deletes keys and their values out; keys must have at least 3 columns:
% section, subsection, and key
[m,n] = size(keys);
if n < 3
error('Keys to be deleted are given in an invalid format.');
end
% Get keys position first
keysIn = keys;
[secsExist,subSecsExist,keysExist,readValues,so,eo] = findkeys(fileName,keys(:,1:3));
% Read the whole file's contents out
fh = fopen(fileName,'r');
if fh == -1
error(['File: ''' fileName ''' does not exist or can not be opened.']);
end
try
dataout = fscanf(fh,'%c');
catch
fclose(fh);
error(lasterr);
end
fclose(fh);
%--- Rewriting the file -> writing the refined contents
fh = fopen(fileName,'w');
if fh == -1
error(['File: ''' fileName ''' does not exist or can not be opened.']);
end
try
ind = find(keysExist);
nExistingKeys = length(ind);
datain = dataout;
if nExistingKeys
% Filtering - retain only the existing keys...
fs = length(dataout); % file size in bytes
so = so(ind);
eo = eo(ind);
keysIn = keysIn(ind,:);
% ...and sorting
[so,ind] = sort(so);
eo = eo(ind);
keysIn = keysIn(ind,:);
% Refined data - datain
datain = [];
for ii=1:nExistingKeys % go through all the existing keys
if ii==1
from = 1; % from byte-offset of original data (dataout)
else
from = eo(ii-1)+1;
end
to = so(ii)-1; % to byte-offset of original data (dataout)
if ~isempty(dataout)
datain = [datain dataout(from:to)]; % the lines before the key
end
end
from = eo(ii)+1;
to = length(dataout);
if from < to
datain = [datain dataout(from:to)];
end
end
fprintf(fh,'%c',datain);
catch
fclose(fh);
error(['Error deleting keys from file: ''' fileName ''' : ' lasterr]);
end
fclose(fh);
%------------------------------------
%------------------------------------
function [status,value,key] = processiniline(line)
% Processes a line read from the ini file and
% returns the following values:
% - status: 0 => empty line or unknown string
% 1 => section found
% 2 => subsection found
% 3 => key-value pair found
% - value: value-string of a key, section, or subsection
% - key: key-string
status = 0;
value = [];
key = [];
line = strim(line); % removes any leading and trailing spaces
if isempty(line) % empty line
return
end
if (line(1) == '[') & (line(end) == ']')... % section found
& (length(line) >= 3)
value = lower(line(2:end-1));
status = 1;
elseif (line(1) == '{') &... % subsection found
(line(end) == '}') & (length(line) >= 3)
value = lower(line(2:end-1));
status = 2;
else
pos = findstr(line,'=');
if ~isempty(pos) % key-value pair found
status = 3;
key = lower(line(1:pos-1));
value = line(pos+1:end);
key = strim(key); % removes any leading and trailing spaces
value = strim(value); % removes any leading and trailing spaces
if isempty(key) % empty keys are not allowed
status = 0;
key = [];
value = [];
end
end
end
%------------------------------------
%------------------------------------
function outstr = strim(str)
% Removes leading and trailing spaces (spaces, tabs, endlines,...)
% from the str string.
if isnumeric(str);
outstr = str;
return
end
ind = find( ~isspace(str) ); % indices of the non-space characters in the str
if isempty(ind)
outstr = [];
else
outstr = str( ind(1):ind(end) );
end
%------------------------------------
function cs = cellstrings(m,n)
% Creates a m x n cell array of empty strings - ''
cs = cell(m,n);
for ii=1:m
for jj=1:n
cs{ii,jj} = '';
end
end
|
github
|
philippboehmsturm/antx-master
|
yokogawa2grad_new.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/yokogawa2grad_new.m
| 9,123 |
utf_8
|
a05c043b59134bedb201bba241ad57ef
|
function grad = yokogawa2grad_new(hdr)
% YOKOGAWA2GRAD_NEW converts the position and weights of all coils that
% compromise a gradiometer system into a structure that can be used
% by FieldTrip. This implementation uses the new "yokogawa_meg_reader"
% toolbox.
%
% See also FT_READ_HEADER, CTF2GRAD, BTI2GRAD, FIF2GRAD, YOKOGAWA2GRAD
% Copyright (C) 2005-2012, Robert Oostenveld
% Copyright (C) 2010, Tilmann Sander-Thoemmes
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: yokogawa2grad_new.m 7123 2012-12-06 21:21:38Z roboos $
% The following line is only a safety measure: No function of the toolbox
% is actually called in this routine.
if ~ft_hastoolbox('yokogawa_meg_reader')
error('cannot determine whether Yokogawa toolbox is present');
end
if isfield(hdr, 'label')
label = hdr.label; % keep for later use
end
if isfield(hdr, 'orig')
hdr = hdr.orig; % use the original header, not the FieldTrip header
end
% The "channel_info.channel(i)" structure contains, s. sepcifications in
% Yokogawa MEG Reader Toolbox 1.4 specifications.pdf.
% type, type of sensor
% data.x (in m, inner coil)
% data.y (in m, inner coil)
% data.z (in m, inner coil)
% data.size (in m, coil diameter)
% for gradiometers
% data.baseline (in m)
% for axial gradiometers and magnetometers
% data.zdir orientation of inner coil (theta in deg: angle to z-axis)
% data.xdir orientation of inner coil (phi in deg: angle to x-axis)
% for planar gradiometers
% Note, that Yokogawa planar gradiometers contain two coils perpendicular to
% the sphere, i.e. the planar gradiometers normal is the spheres tangential.
% Therefore the definition of an inner coil makes sense here in contrast to
% planar gradiometers from Neuromag, where the gradiometer normal is radial.
% data.zdir1 orientation of inner coil (theta in deg: angle to z-axis)
% data.xdir1 orientation of inner coil (phi in deg: angle to x-axis)
% data.zdir2 baseline orientation from inner coil (theta in deg: angle to z-axis)
% data.xdir2 baseline orientation from inner coil (phi in deg: angle to x-axis)
%
% The code below is not written for speed or elegance, but for readability.
%
% shorten names
ch_info = hdr.channel_info.channel;
type = [ch_info.type];
handles = definehandles;
% get all axial grads, planar grads, and magnetometers.
% reference channels without position information are excluded.
grad_ind = [1:hdr.channel_count];
isgrad = (type==handles.AxialGradioMeter | type==handles.PlannerGradioMeter | ...
type==handles.MagnetoMeter);
isref = (type==handles.RefferenceAxialGradioMeter | type==handles.RefferencePlannerGradioMeter | ...
type==handles.RefferenceMagnetoMeter);
for i = 1: hdr.channel_count
if isref(i) && sum( ch_info( i ).data.x^2 + ch_info( i ).data.y^2 + ch_info( i ).data.z^2 ) > 0.0, isgrad(i) = 1; end;
end
grad_ind = grad_ind(isgrad);
grad_nr = size(grad_ind,2);
grad = [];
grad.coilpos = zeros(2*grad_nr,3);
grad.coilori = zeros(2*grad_nr,3);
% define gradiometer and magnetometer
for i = 1:grad_nr
ch_ind = grad_ind(i);
grad.coilpos(i,1) = ch_info(ch_ind).data.x*100; % cm
grad.coilpos(i,2) = ch_info(ch_ind).data.y*100; % cm
grad.coilpos(i,3) = ch_info(ch_ind).data.z*100; % cm
grad.chanpos = grad.coilpos(1:grad_nr,:);
if ch_info(ch_ind).type==handles.AxialGradioMeter || ch_info(ch_ind).type==handles.RefferenceAxialGradioMeter
baseline = ch_info(ch_ind).data.baseline;
ori_1st = [ch_info(ch_ind).data.zdir ch_info(ch_ind).data.xdir ];
% polar to x,y,z coordinates
ori_1st = ...
[sin(ori_1st(:,1)/180*pi).*cos(ori_1st(:,2)/180*pi) ...
sin(ori_1st(:,1)/180*pi).*sin(ori_1st(:,2)/180*pi) ...
cos(ori_1st(:,1)/180*pi)];
grad.coilori(i,:) = ori_1st;
grad.coilpos(i+grad_nr,:) = [grad.coilpos(i,:)+ori_1st*baseline*100];
grad.coilori(i+grad_nr,:) = -ori_1st;
elseif ch_info(ch_ind).type==handles.PlannerGradioMeter || ch_info(ch_ind).type==handles.RefferencePlannerGradioMeter
baseline = ch_info(ch_ind).data.baseline;
ori_1st = [ch_info(ch_ind).data.zdir1 ch_info(ch_ind).data.xdir1 ];
% polar to x,y,z coordinates
ori_1st = ...
[sin(ori_1st(:,1)/180*pi).*cos(ori_1st(:,2)/180*pi) ...
sin(ori_1st(:,1)/180*pi).*sin(ori_1st(:,2)/180*pi) ...
cos(ori_1st(:,1)/180*pi)];
grad.coilori(i,:) = ori_1st;
ori_1st_to_2nd = [ch_info(ch_ind).data.zdir2 ch_info(ch_ind).data.xdir2 ];
% polar to x,y,z coordinates
ori_1st_to_2nd = ...
[sin(ori_1st_to_2nd(:,1)/180*pi).*cos(ori_1st_to_2nd(:,2)/180*pi) ...
sin(ori_1st_to_2nd(:,1)/180*pi).*sin(ori_1st_to_2nd(:,2)/180*pi) ...
cos(ori_1st_to_2nd(:,1)/180*pi)];
grad.coilpos(i+grad_nr,:) = [grad.coilpos(i,:)+ori_1st_to_2nd*baseline*100];
grad.coilori(i+grad_nr,:) = -ori_1st;
else % magnetometer
ori_1st = [ch_info(ch_ind).data.zdir ch_info(ch_ind).data.xdir ];
% polar to x,y,z coordinates
ori_1st = ...
[sin(ori_1st(:,1)/180*pi).*cos(ori_1st(:,2)/180*pi) ...
sin(ori_1st(:,1)/180*pi).*sin(ori_1st(:,2)/180*pi) ...
cos(ori_1st(:,1)/180*pi)];
grad.coilori(i,:) = ori_1st;
grad.coilpos(i+grad_nr,:) = [0 0 0];
grad.coilori(i+grad_nr,:) = [0 0 0];
end
grad.chanori = grad.coilori(1:grad_nr,:);
end
% Define the pair of 1st and 2nd coils for each gradiometer
grad.tra = repmat(diag(ones(1,grad_nr),0),1,2);
% for mangetometers change tra as there is no second coil
for i = 1:grad_nr
ch_ind = grad_ind(i);
if ch_info(ch_ind).type==handles.MagnetoMeter
grad.tra(i,grad_nr+i) = 0;
end
end
% the gradiometer labels should be consistent with the channel labels in
% read_yokogawa_header, the predefined list of channel names in ft_senslabel
% and with ft_channelselection:
% but it is ONLY consistent with read_yokogawa_header as NO FIXED relation
% between channel index and type of channel exists for Yokogawa systems.
% Therefore all have individual label sequences: Support in ft_senslabel
% is only partial.
if ~isempty(label)
grad.label = label(grad_ind)';
else
% this is only backup, if something goes wrong above.
label = cell(grad_nr,1);
for i=1:length(label)
label{i,1} = sprintf('AG%03d', i);
end
grad.label = label;
end
grad.unit = 'cm';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% this defines some usefull constants
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function handles = definehandles;
handles.output = [];
handles.sqd_load_flag = false;
handles.mri_load_flag = false;
handles.NullChannel = 0;
handles.MagnetoMeter = 1;
handles.AxialGradioMeter = 2;
handles.PlannerGradioMeter = 3;
handles.RefferenceChannelMark = hex2dec('0100');
handles.RefferenceMagnetoMeter = bitor( handles.RefferenceChannelMark, handles.MagnetoMeter );
handles.RefferenceAxialGradioMeter = bitor( handles.RefferenceChannelMark, handles.AxialGradioMeter );
handles.RefferencePlannerGradioMeter = bitor( handles.RefferenceChannelMark, handles.PlannerGradioMeter );
handles.TriggerChannel = -1;
handles.EegChannel = -2;
handles.EcgChannel = -3;
handles.EtcChannel = -4;
handles.NonMegChannelNameLength = 32;
handles.DefaultMagnetometerSize = (4.0/1000.0); % ????4.0mm???????`
handles.DefaultAxialGradioMeterSize = (15.5/1000.0); % ???a15.5mm???~??
handles.DefaultPlannerGradioMeterSize = (12.0/1000.0); % ????12.0mm???????`
handles.AcqTypeContinuousRaw = 1;
handles.AcqTypeEvokedAve = 2;
handles.AcqTypeEvokedRaw = 3;
handles.sqd = [];
handles.sqd.selected_start = [];
handles.sqd.selected_end = [];
handles.sqd.axialgradiometer_ch_no = [];
handles.sqd.axialgradiometer_ch_info = [];
handles.sqd.axialgradiometer_data = [];
handles.sqd.plannergradiometer_ch_no = [];
handles.sqd.plannergradiometer_ch_info = [];
handles.sqd.plannergradiometer_data = [];
handles.sqd.nullchannel_ch_no = [];
handles.sqd.nullchannel_data = [];
handles.sqd.selected_time = [];
handles.sqd.sample_rate = [];
handles.sqd.sample_count = [];
handles.sqd.pretrigger_length = [];
handles.sqd.matching_info = [];
handles.sqd.source_info = [];
handles.sqd.mri_info = [];
handles.mri = [];
|
github
|
philippboehmsturm/antx-master
|
read_besa_avr.m
|
.m
|
antx-master/xspm8/external/fieldtrip/fileio/private/read_besa_avr.m
| 3,929 |
utf_8
|
91f2ee59d1af564811511e0e7f201ba4
|
function [avr] = read_besa_avr(filename)
% READ_BESA_AVR reads average EEG data in BESA format
%
% Use as
% [avr] = read_besa_avr(filename)
%
% This will return a structure with the header information in
% avr.npnt
% avr.tsb
% avr.di
% avr.sb
% avr.sc
% avr.Nchan (optional)
% avr.label (optional)
% and the ERP data is contained in the Nchan X Nsamples matrix
% avr.data
% Copyright (C) 2003-2006, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% 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: read_besa_avr.m 7123 2012-12-06 21:21:38Z roboos $
fid = fopen(filename, 'rt');
% the first line contains header information
headstr = fgetl(fid);
ok = 0;
if ~ok
try
buf = sscanf(headstr, 'Npts= %d TSB= %f DI= %f SB= %f SC= %f Nchan= %f SegmentName= %s\n');
avr.npnt = buf(1);
avr.tsb = buf(2);
avr.di = buf(3);
avr.sb = buf(4);
avr.sc = buf(5);
avr.Nchan = buf(6);
avr.SegmentName = buf(7);
ok = 1;
catch
ok = 0;
end
end
if ~ok
try
buf = fscanf(headstr, 'Npts= %d TSB= %f DI= %f SB= %f SC= %f Nchan= %f\n');
avr.npnt = buf(1);
avr.tsb = buf(2);
avr.di = buf(3);
avr.sb = buf(4);
avr.sc = buf(5);
avr.Nchan = buf(6);
ok = 1;
catch
ok = 0;
end
end
if ~ok
try
buf = sscanf(headstr, 'Npts= %d TSB= %f DI= %f SB= %f SC= %f\n');
avr.npnt = buf(1);
avr.tsb = buf(2);
avr.di = buf(3);
avr.sb = buf(4);
avr.sc = buf(5);
ok = 1;
catch
ok = 0;
end
end
if ~ok
error('Could not interpret the header information.');
end
% rewind to the beginning of the file, skip the header line
fseek(fid, 0, 'bof');
fgetl(fid);
% the second line may contain channel names
chanstr = fgetl(fid);
chanstr = deblank(fliplr(deblank(fliplr(chanstr))));
if (chanstr(1)>='A' && chanstr(1)<='Z') || (chanstr(1)>='a' && chanstr(1)<='z')
haschan = 1;
avr.label = str2cell(strrep(deblank(chanstr), '''', ''))';
else
[root, name] = fileparts(filename);
haschan = 0;
elpfile = fullfile(root, [name '.elp']);
elafile = fullfile(root, [name '.ela']);
if exist(elpfile, 'file')
% read the channel names from the accompanying ELP file
lbl = importdata(elpfile);
avr.label = strrep(lbl.textdata(:,2) ,'''', '');
elseif exist(elafile, 'file')
% read the channel names from the accompanying ELA file
lbl = importdata(elafile);
lbl = strrep(lbl ,'MEG ', ''); % remove the channel type
lbl = strrep(lbl ,'EEG ', ''); % remove the channel type
avr.label = lbl;
else
warning('Could not create channels labels.');
end
end
% seek to the beginning of the data
fseek(fid, 0, 'bof');
fgetl(fid); % skip the header line
if haschan
fgetl(fid); % skip the channel name line
end
buf = fscanf(fid, '%f');
nchan = length(buf)/avr.npnt;
avr.data = reshape(buf, avr.npnt, nchan)';
fclose(fid);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION to cut a string into pieces at the spaces
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function c = str2cell(s)
c = {};
[t, r] = strtok(s, ' ');
while ~isempty(t)
c{end+1} = t;
[t, r] = strtok(r, ' ');
end
|
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