pnpl.preprocessing.BandpassFilter

pnpl.preprocessing.BandpassFilter#

class pnpl.preprocessing.BandpassFilter(step_name='bp', l_freq=0.1, h_freq=125.0, picks='meg')[source]#

Apply bandpass filter.

Parameters:

  • l_freq (float) – Low cutoff frequency (default: 0.1 Hz)

  • h_freq (float) – High cutoff frequency (default: 125 Hz)

  • picks (Any) – Channels to filter, as accepted by mne.io.Raw.filter() (default: "meg"; use "eeg" or "data" for EEG recordings)

  • step_name (str)

__init__(step_name='bp', l_freq=0.1, h_freq=125.0, picks='meg')#
Parameters:

  • step_name (str)

  • l_freq (float)

  • h_freq (float)

  • picks (Any)

Return type:

None

Methods

__init__([step_name, l_freq, h_freq, picks])

apply(raw, context)

Apply this preprocessing step to raw data.

Attributes

h_freq

l_freq

picks

step_name