charestlab / eegprep Goto Github PK

/home/adf/vandejjf/Projects/eegprep/env/src/mne/mne/epochs.py:2881: RuntimeWarning: overflow encountered in long_scalars
  int((10 + tmax) * epochs.info['sfreq']))
/home/adf/vandejjf/Projects/eegprep/eegprep/preproc.py:84: RuntimeWarning: The events passed to the Epochs constructor are not chronologically ordered.
  task_epochs = mne.epochs.concatenate_epochs(task_epochs_list)
The events passed to the Epochs constructor are not chronologically ordered.
3554 matching events found
Applying baseline correction (mode: mean)
Not setting metadata
3554 bad epochs dropped
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
~/Projects/eegprep/eegprep/preproc.py in <module>()
     84         task_epochs = mne.epochs.concatenate_epochs(task_epochs_list)
     85         task_epochs = task_epochs.pick_types(eeg=True, exclude=refChannels)
---> 86         task_epochs.save(join(derivdir, 'sub-{}_task-{}_epo.fif'.format(sub, task)))

~/Projects/eegprep/env/src/mne/mne/epochs.py in save(self, fname, split_size, verbose)

~/Projects/eegprep/env/src/mne/mne/utils.py in verbose(function, *args, **kwargs)
    736         # set it back if we get an exception
    737         with use_log_level(verbose_level):
--> 738             return function(*args, **kwargs)
    739     return function(*args, **kwargs)
    740 

~/Projects/eegprep/env/src/mne/mne/epochs.py in save(self, fname, split_size, verbose)
   1652         self.drop_bad()
   1653         self._check_consistency()
-> 1654         total_size = self[0].get_data().nbytes * len(self)
   1655         total_size /= 2  # 64bit data converted to 32bit before writing.
   1656         n_parts = int(np.ceil(total_size / float(split_size)))

~/Projects/eegprep/env/src/mne/mne/epochs.py in __getitem__(self, item)
   1486                .. versionadded:: 0.16
   1487         """
-> 1488         return self._getitem(item)
   1489 
   1490     def _getitem(self, item, reason='IGNORED', copy=True, drop_event_id=True,

~/Projects/eegprep/env/src/mne/mne/epochs.py in _getitem(***failed resolving arguments***)
   1537                 select = np.array([], int)
   1538 
-> 1539         key_selection = epochs.selection[select]
   1540         if reason is not None:
   1541             for k in np.setdiff1d(epochs.selection, key_selection):

IndexError: index 0 is out of bounds for axis 1 with size 0