wonambi.ioeeg.bci2000 module

class wonambi.ioeeg.bci2000.BCI2000(filename)[source]

Bases: object

Basic class to read the data.

Parameters:

filename (path to file) – the name of the filename or directory

return_dat(chan, begsam, endsam)[source]

Return the data as 2D numpy.ndarray.

Parameters:
  • chan (int or list) – index (indices) of the channels to read

  • begsam (int) – index of the first sample

  • endsam (int) – index of the last sample

Returns:

numpy.ndarray – A 2d matrix, with dimension chan X samples

return_hdr()[source]

Return the header for further use.

Returns:

  • subj_id (str) – subject identification code

  • start_time (datetime) – start time of the dataset

  • s_freq (float) – sampling frequency

  • chan_name (list of str) – list of all the channels

  • n_samples (int) – number of samples in the dataset

  • orig (dict) – additional information taken directly from the header

Notes

As far as I can, BCI2000 doesn’t have channel labels, so we use dummies starting at chan001 (more consistent with Matlab 1-base indexing…)

return_markers(state='MicromedCode')[source]

Return all the markers (also called triggers or events).

Returns:

list of dict – where each dict contains ‘name’ as str, ‘start’ and ‘end’ as float in seconds from the start of the recordings, and ‘chan’ as list of str with the channels involved (if not of relevance, it’s None).

Raises:

FileNotFoundError – when it cannot read the events for some reason (don’t use other exceptions).