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Merge pull request #29 from VisLab/check-issues
Resolved parfor issue and updateNoisyChannels issue
2 parents 3ed337e + d3a050f commit 9ac9ea0

12 files changed

Lines changed: 1319 additions & 1298 deletions

EEGLABPlugin/PrepPipeline0.55.4.zip renamed to EEGLABPlugin/PrepPipeline0.56.0.zip

251 KB
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‎PrepPipeline/eegplugin_prepPipeline.m‎

Lines changed: 47 additions & 47 deletions
Original file line numberDiff line numberDiff line change
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% eegplugin_prepPipeline() - a wrapper to the prepPipeline, which does early stage
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%
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% Usage:
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% >> eegplugin_prepPipeline(fig, try_strings, catch_strings);
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%
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% see also: prepPipeline
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% Author: Kay Robbins, with contributions from Nima Bigdely-Shamlo, Tim Mullen, Christian Kothe, and Cassidy Matousek.
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% This program is free software; you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation; either version 2 of the License, or
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% (at your option) any later version.
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%
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% This program is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with this program; if not, write to the Free Software
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% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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%function eegplugin_clean_rawdata(fig,try_strings,catch_strings)
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% create menu
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% toolsmenu = findobj(fig, 'tag', 'tools');
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% uimenu( toolsmenu, 'label', 'Clean continuous data using ASR', 'separator','on',...
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% 'callback', 'EEG = pop_clean_rawdata(EEG); [ALLEEG EEG CURRENTSET] = eeg_store(ALLEEG, EEG); eeglab redraw');
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% eegplugin_prepPipeline() - the PREP pipeline plugin
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function vers = eegplugin_prepPipeline(fig, trystrs, catchstrs)
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%% Add path to prepPipeline subdirectories if not in the list
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tmp = which('getPrepDefaults');
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if isempty(tmp)
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myPath = fileparts(which('prepPipeline'));
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addpath(genpath(myPath));
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end;
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vers = getPrepVersion();
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% create menu
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comprep = [trystrs.no_check '[EEG LASTCOM] = pop_prepPipeline(EEG);' catchstrs.new_and_hist];
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menu = findobj(fig, 'tag', 'tools');
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uimenu( menu, 'Label', 'Run PREP pipeline', 'callback', comprep, ...
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'separator', 'on');
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% eegplugin_prepPipeline() - a wrapper to the prepPipeline, which does early stage
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%
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% Usage:
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% >> eegplugin_prepPipeline(fig, try_strings, catch_strings);
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%
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% see also: prepPipeline
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8+
% Author: Kay Robbins, with contributions from Nima Bigdely-Shamlo, Tim Mullen, Christian Kothe, and Cassidy Matousek.
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10+
% This program is free software; you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
12+
% the Free Software Foundation; either version 2 of the License, or
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% (at your option) any later version.
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%
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% This program is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with this program; if not, write to the Free Software
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% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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%function eegplugin_clean_rawdata(fig,try_strings,catch_strings)
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% create menu
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% toolsmenu = findobj(fig, 'tag', 'tools');
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% uimenu( toolsmenu, 'label', 'Clean continuous data using ASR', 'separator','on',...
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% 'callback', 'EEG = pop_clean_rawdata(EEG); [ALLEEG EEG CURRENTSET] = eeg_store(ALLEEG, EEG); eeglab redraw');
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% eegplugin_prepPipeline() - the PREP pipeline plugin
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function vers = eegplugin_prepPipeline(fig, trystrs, catchstrs)
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%% Add path to prepPipeline subdirectories if not in the list
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tmp = which('getPrepDefaults');
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if isempty(tmp)
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myPath = fileparts(which('prepPipeline'));
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addpath(genpath(myPath));
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end
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vers = getPrepVersion();
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% create menu
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comprep = [trystrs.no_check '[EEG LASTCOM] = pop_prepPipeline(EEG);' catchstrs.new_and_hist];
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menu = findobj(fig, 'tag', 'tools');
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uimenu( menu, 'Label', 'Run PREP pipeline', 'callback', comprep, ...
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'separator', 'on');
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‎PrepPipeline/examples/runVEPPrepPipeline.m‎

Lines changed: 50 additions & 51 deletions
Original file line numberDiff line numberDiff line change
@@ -1,51 +1,50 @@
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%% Example: Running the pipeline on a directory of EEG files
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%% Set up the input and the output directories
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basename = 'vep';
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indir = 'F:\DataPool\CTADATA\VEP\BiosemiOriginalSetCorrected';
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outdir = 'D:\TempCTA';
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%% Make the output directory if needed
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if ~exist(outdir, 'dir')
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mkdir(outdir)
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end
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%% Set up the params structure
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params = struct();
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params.lineFrequencies = [60, 120, 180, 212, 240];
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params.referenceChannels = 1:64;
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params.evaluationChannels = 1:64;
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params.rereferencedChannels = 1:70;
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params.detrendChannels = 1:70;
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params.lineNoiseChannels = 1:70;
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params.detrendType = 'high pass';
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params.detrendCutoff = 1;
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params.referenceType = 'robust';
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params.meanEstimateType = 'median';
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params.interpolationOrder = 'post-reference';
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params.removeInterpolatedChannels = true;
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params.keepFiltered = false;
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basenameOut = [basename 'robust_1Hz_post_median_unfiltered'];
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%% Get the filelist
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fileList = getFileList('FILES', indir);
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%% Run the pipeline
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for k = 1:length(fileList)
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[~, thisName, ~] = fileparts(fileList{k});
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EEG = pop_loadset(fileList{k});
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params.name = thisName;
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[EEG, params, computationTimes] = prepPipeline(EEG, params);
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fprintf('Computation times (seconds):\n %s\n', ...
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getStructureString(computationTimes));
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fprintf('Post-process\n')
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EEG = prepPostProcess(EEG, params);
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fname = [outdir filesep thisName '.set'];
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save(fname, 'EEG', '-mat', '-v7.3');
46-
if strcmpi(params.errorMsgs, 'verbose')
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outputPrepParams(params, 'Prep parameters (non-defaults)');
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outputPrepErrors(EEG.etc.noiseDetection, 'Prep error status');
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end
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51-
end
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%% Example: Running the pipeline on a directory of EEG files
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%% Set up the input and the output directories
4+
basename = 'vep';
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indir = 'F:\DataPool\CTADATA\VEP\BiosemiOriginalSetCorrected';
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outdir = 'F:\TempData';
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%% Make the output directory if needed
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if ~exist(outdir, 'dir')
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mkdir(outdir)
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end
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%% Set up the params structure
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params = struct();
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params.lineFrequencies = [60, 120, 180, 212, 240];
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params.referenceChannels = 1:64;
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params.evaluationChannels = 1:64;
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params.rereferencedChannels = 1:70;
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params.detrendChannels = 1:70;
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params.lineNoiseChannels = 1:70;
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params.detrendType = 'high pass';
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params.detrendCutoff = 1;
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params.referenceType = 'robust';
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params.meanEstimateType = 'median';
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params.interpolationOrder = 'post-reference';
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params.removeInterpolatedChannels = true;
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params.keepFiltered = false;
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basenameOut = [basename 'robust_1Hz_post_median_unfiltered'];
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%% Get the filelist
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fileList = getFileList('FILES', indir);
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%% Run the pipeline
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for k = 1:length(fileList)
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[~, thisName, ~] = fileparts(fileList{k});
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EEG = pop_loadset(fileList{k});
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params.name = thisName;
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[EEG, params, computationTimes] = prepPipeline(EEG, params);
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fprintf('Computation times (seconds):\n %s\n', ...
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getStructureString(computationTimes));
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fprintf('Post-process\n')
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EEG = prepPostProcess(EEG, params);
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fname = [outdir filesep thisName '.set'];
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save(fname, 'EEG', '-mat', '-v7.3');
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if strcmpi(params.errorMsgs, 'verbose')
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outputPrepParams(params, 'Prep parameters (non-defaults)');
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outputPrepErrors(EEG.etc.noiseDetection, 'Prep error status');
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end
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end

‎PrepPipeline/examples/runVEPPrepReport.m‎

Lines changed: 35 additions & 36 deletions
Original file line numberDiff line numberDiff line change
@@ -1,37 +1,36 @@
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%% Read in the file and set the necessary parameters
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% dataDir = 'O:\ARL_Data\VEP\VEP_Robust_1Hz';
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% summaryFolder = 'O:\ARL_Data\VEP\VEP_Robust_1Hz_New_Report_B';
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dataDir = 'D:\TempCTA';
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summaryFolder = 'D:\TempCTA';
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publishOn = true;
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%% Get the directory list
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inList = dir(dataDir);
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inNames = {inList(:).name};
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inTypes = [inList(:).isdir];
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inNames = inNames(~inTypes);
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%%
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basename = 'vep';
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summaryReportName = [basename '_summary.html'];
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sessionFolder = '.';
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summaryFileName = [summaryFolder filesep summaryReportName];
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if exist(summaryFileName, 'file')
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delete(summaryFileName);
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end
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%% Run the pipeline
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for k = 1:length(inNames)
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[~, theName, theExt] = fileparts(inNames{k});
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if ~strcmpi(theExt, '.set') && ~strcmpi(theExt, '.mat')
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continue;
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end
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sessionReportName = [theName '.pdf'];
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fname = [dataDir filesep inNames{k}];
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load(fname, '-mat');
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sessionFileName = [summaryFolder filesep sessionReportName];
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consoleFID = 1;
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publishPrepReport(EEG, summaryFileName, sessionFileName, consoleFID, publishOn);
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%% This script takes a directory of files that have been processed by PREP
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% and produces reports.
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%% Read in the file and set the necessary parameters
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dataDir = 'F:\TempData';
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summaryFolder = 'F:\TempDataReports';
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publishOn = true;
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%% Get the directory list
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inList = dir(dataDir);
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inNames = {inList(:).name};
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inTypes = [inList(:).isdir];
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inNames = inNames(~inTypes);
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%% Setup up the names
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basename = 'vep';
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summaryReportName = [basename '_summary.html'];
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sessionFolder = '.';
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summaryFileName = [summaryFolder filesep summaryReportName];
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if exist(summaryFileName, 'file')
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delete(summaryFileName);
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end
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%% Publish the reports
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for k = 1:length(inNames)
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[~, theName, theExt] = fileparts(inNames{k});
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if ~strcmpi(theExt, '.set') && ~strcmpi(theExt, '.mat')
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continue;
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end
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sessionReportName = [theName '.pdf'];
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fname = [dataDir filesep inNames{k}];
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load(fname, '-mat');
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sessionFileName = [summaryFolder filesep sessionReportName];
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consoleFID = 1;
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publishPrepReport(EEG, summaryFileName, sessionFileName, consoleFID, publishOn);
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end

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