moabb.paradigms.motor_imagery.SinglePass

class moabb.paradigms.motor_imagery.SinglePass(fmin=8, fmax=32, **kwargs)[source][source]

Single Bandpass filter motot Imagery.

Motor imagery paradigm with only one bandpass filter (default 8 to 32 Hz)

Parameters
  • fmin (float (default 8)) – cutoff frequency (Hz) for the high pass filter

  • fmax (float (default 32)) – cutoff frequency (Hz) for the low pass filter

  • events (List of str | None (default None)) – event to use for epoching. If None, default to all events defined in the dataset.

  • tmin (float (default 0.0)) – Start time (in second) of the epoch, relative to the dataset specific task interval e.g. tmin = 1 would mean the epoch will start 1 second after the begining of the task as defined by the dataset.

  • tmax (float | None, (default None)) – End time (in second) of the epoch, relative to the begining of the dataset specific task interval. tmax = 5 would mean the epoch will end 5 second after the begining of the task as defined in the dataset. If None, use the dataset value.

  • baseline (None | tuple of length 2) – The time interval to consider as “baseline” when applying baseline correction. If None, do not apply baseline correction. If a tuple (a, b), the interval is between a and b (in seconds), including the endpoints. Correction is applied by computing the mean of the baseline period and subtracting it from the data (see mne.Epochs)

  • channels (list of str | None (default None)) – list of channel to select. If None, use all EEG channels available in the dataset.

  • resample (float | None (default None)) – If not None, resample the eeg data with the sampling rate provided.

Attributes
datasets

Property that define the list of compatible datasets

scoring

Property that defines scoring metric (e.g.

Methods

get_data(dataset[, subjects, return_epochs])

Return the data for a list of subject.

is_valid(dataset)

Verify the dataset is compatible with the paradigm.

prepare_process(dataset)

Prepare processing of raw files

process_raw(raw, dataset[, return_epochs])

Process one raw data file.

used_events