Merge pull request #110 from fahrenfort/bugfixes

Bugfixes

eeg_mvpa/classify_RAW_eeglab_data.m

@@ -179,7 +179,6 @@ function classify_RAW_eeglab_data(filepath,filenames,outpath,nFolds,channelset,m
 basis_sigma = 1; % default width of basis set if not a delta, if this is empty, do a simple basis set (delta function)
 unbalance_events = false;
 unbalance_classes = false;
-detrend_eeg = false;
 whiten = false;
 whiten_test_using_train = false;
 for c=1:numel(methods)
@@ -264,9 +263,6 @@ function classify_RAW_eeglab_data(filepath,filenames,outpath,nFolds,channelset,m
     if any(strcmpi(methods{c},{'oversample'}))
         unbalance_classes = false;
     end
-    if any(strcmpi(methods{c},{'detrend','detrend_eeg'}))
-        detrend_eeg = true;
-    end
     if any(strcmpi(methods{c},{'whiten'}))
         whiten = true;
     end
@@ -362,7 +358,6 @@ function classify_RAW_eeglab_data(filepath,filenames,outpath,nFolds,channelset,m
     msettings.clean_data = clean_muscle;
     msettings.clean_window = clean_window;
     msettings.shuffle_trials = true;
-    msettings.detrend_eeg= detrend_eeg;
     [FT_EEG(cFile), filenames{cFile}, chanlocs{cFile}] = read_raw_data(filepath,filenames{cFile},outpath,msettings);
     % randomize labels for first level random permutation testing. NOTE: permuting all observations/labels regardless of the conditions in the experiment
     if randomize_labels
@@ -622,7 +617,6 @@ function classify_RAW_eeglab_data(filepath,filenames,outpath,nFolds,channelset,m
 settings.crossclass = crossclass;
 settings.erp_baseline = erp_baseline;
 settings.clean_window = clean_window;
-settings.detrend_eeg = detrend_eeg;
 settings.BDM = do_BDM;
 settings.FEM = do_FEM;
 settings.basis_set_sigma = basis_sigma;

eeg_mvpa/classify_TFR_from_eeglab_data.m

@@ -173,7 +173,6 @@ function classify_TFR_from_eeglab_data(filepath,filenames,outpath,nFolds,channel
 basis_sigma = 1; % default width of basis set if not a delta, if this is empty, do a simple basis set (delta function)
 unbalance_events = false;
 unbalance_classes = false;
-detrend_eeg = false;
 whiten = false;
 whiten_test_using_train = false;
 for c=1:numel(methods)
@@ -261,9 +260,6 @@ function classify_TFR_from_eeglab_data(filepath,filenames,outpath,nFolds,channel
     if any(strcmpi(methods{c},{'oversample'}))
         unbalance_classes = false;
     end
-    if any(strcmpi(methods{c},{'detrend','detrend_eeg'}))
-        detrend_eeg = true;
-    end
     if any(strcmpi(methods{c},{'whiten'}))
         whiten = true;
     end
@@ -350,7 +346,6 @@ function classify_TFR_from_eeglab_data(filepath,filenames,outpath,nFolds,channel
     msettings.clean_data = clean_muscle;
     msettings.clean_window = clean_window;
     msettings.shuffle_trials = true;
-    msettings.detrend_eeg= detrend_eeg;
     [FT_EEG(cFile), filenames{cFile}, chanlocs{cFile}] = read_raw_data(filepath,filenames{cFile},outpath,msettings);
     % randomize labels for first level random permutation testing. NOTE: permuting all observations/labels regardless of the conditions in the experiment
     if randomize_labels
@@ -660,7 +655,6 @@ function classify_TFR_from_eeglab_data(filepath,filenames,outpath,nFolds,channel
     settings.erp_baseline = erp_baseline;
     settings.tf_baseline = tf_baseline;
     settings.clean_window = clean_window;
-    settings.detrend_eeg = detrend_eeg;
     settings.BDM = do_BDM;
     settings.FEM = do_FEM;
     settings.basis_set_sigma = basis_sigma;

eeg_mvpa/read_raw_data.m

@@ -6,7 +6,6 @@
 % Johannes Fahrenfort, VU 2016, 2017, 2018
 
 % set some defaults
-detrend_eeg = false;
 shuffle_trials = false;
 clean_window = [];
 clean_data = false;
@@ -74,11 +73,6 @@
     error(['The following required fields are missing from your data: ' cell2csv(absentfields,true)]);
 end
 
-% detrend eeg
-if detrend_eeg
-    FT_EEG = detrend_FT_EEG(FT_EEG);
-end
-
 % keep track of index numbers
 origindex = 1:numel(FT_EEG.trialinfo);
 % muscle artifact detection

eeg_preprocessing/adam_detrend_and_epoch.m

@@ -4,9 +4,7 @@ function adam_detrend_and_epoch(cfg)
 % and writes out as EPOCHED (!) EEGLAB file. Note that the data are high-pass filtered early on to
 % identify faulty electrodes, but that the highpass filtered data is discarded after identifying
 % these electrodes. Polynomial detrending is applied to remove drifts in raw data. Faulty
-% electrodes are interpolated back in after detrending. filenames: names of files either in a cell
-% array or as comma separated string. Wildcards * and ? can be used, e.g. filenames = '*' will take
-% all the .set files in the input filepath as sources. The output of this function can serve as
+% electrodes are interpolated back in after detrending. The output of this function can serve as
 % input for ADAM_MVPA_FIRSTLEVEL.
 %
 %       cfg.datadir           = string specifiying the directory where the input files are

eeg_preprocessing/detrend_and_epoch.m

@@ -318,6 +318,7 @@ function detrend_and_epoch(datadir,filename,outputdir, start_epoch, end_epoch, p
 end
 
 %% save
-% save([outputdir filesep fname '.mat'],'DETRENDED_FT_EEG');
-% as EEGLAB file
+% can also save as FT_EEG if that is preferred:
+% save([outputdir filesep fname '.mat'],'DETRENDED_FT_EEG'); 
+% OR as EEGLAB file
 pop_saveset(EEG, 'filename',[fname '.set'],'filepath',outputdir);

eeg_preprocessing/pop_exportepoch.m

@@ -33,7 +33,7 @@
         events(cEvents,1) = event;
         pointlatency = EEG.event(cEvents).latency; % expressed in samples (!!!!)
         % eventlatency = round(pointlatency/EEG.srate*1000);
-        eventlatency = round(EEG.times(round(pointlatency))); % expressed in ms. :-)
+        eventlatency = EEG.times(round(pointlatency)); % expressed in ms. :-)
         events(cEvents,2) = eventlatency;
     end
 else % extracting only epoched events that occur at time zero of each epoch, without time stamp