ICAPipe

Tip

💡 Usage Examples - See the notebook for usage examples and code snippets: ICA

class sleepeegpy.pipeline.ICAPipe(prec_pipe=None, path_to_eeg='', output_dir='', method='fastica', n_components=None, fit_params=None, path_to_ica=None, **ica_kwargs)

Bases: BasePipe

The ICA pipeline element.

Contains ica fitting, plotting multiple ica plots, selecting ica exclusion components and its application to the raw data. More at mne.preprocessing.ICA.

Methods:

apply	A wrapper for mne.preprocessing.ICA.apply().
fit	High-pass filters (1 Hz) a copy of the mne_raw object and then runs mne.preprocessing.ICA.fit() on it.
interpolate_bads	A wrapper for mne.io.Raw.interpolate_bads()
plot	A wrapper for mne.io.Raw.plot().
plot_components	A wrapper for mne.preprocessing.ICA.plot_components().
plot_properties	A wrapper for mne.preprocessing.ICA.plot_properties().
plot_sensors	A wrapper for mne.viz.plot_sensors() with a legend.
plot_sources	A wrapper for mne.preprocessing.ICA.plot_sources().
save_ica	A wrapper for mne.preprocessing.ICA.save().
save_raw	A wrapper for mne.io.Raw.save().
set_eeg_reference	A wrapper for mne.io.Raw.set_eeg_reference().

Attributes:

mne_ica	Instance of mne.preprocessing.ICA.
bad_data_percent	Calculates percent of data segments annotated as BAD.
sf	A wrapper for raw.info["sfreq"].
prec_pipe	Preceding pipe that hands over mne_raw object and output_dir.
path_to_eeg	Can be any eeg file type supported by mne.io.read_raw().
output_dir	Path to the directory where the output will be saved.
mne_raw	An instanse of mne.io.Raw.

mne_ica: ICA

Instance of mne.preprocessing.ICA.

fit(filter_kwargs=None, **fit_kwargs)

High-pass filters (1 Hz) a copy of the mne_raw object and then runs mne.preprocessing.ICA.fit() on it.

Parameters:

• filter_args – Arguments passed to mne.io.Raw.filter(). Defaults to None.

• **fit_kwargs – Arguments passed to mne.preprocessing.ICA.fit().

plot_sources(**kwargs)

A wrapper for mne.preprocessing.ICA.plot_sources().

plot_components(save=False, **kwargs)

A wrapper for mne.preprocessing.ICA.plot_components().

plot_properties(picks=None, save=False, **kwargs)

A wrapper for mne.preprocessing.ICA.plot_properties().

apply(exclude=None, **kwargs)

A wrapper for mne.preprocessing.ICA.apply().

save_ica(fname='data-ica.fif', overwrite=False)

A wrapper for mne.preprocessing.ICA.save().

Parameters:

• fname (str) – filename for the ica file being saved. Defaults to “data-ica.fif”.

• overwrite (bool) – Whether to overwrite the file. Defaults to False.

property bad_data_percent

Calculates percent of data segments annotated as BAD.

Returns:

percent of bad data spans in raw data

Return type:

float

interpolate_bads(**interp_kwargs)

A wrapper for mne.io.Raw.interpolate_bads()

Parameters:

**interp_kwargs – Arguments passed to mne.io.Raw.interpolate_bads().

plot(save_annotations=False, save_bad_channels=False, overwrite=False, **kwargs)

A wrapper for mne.io.Raw.plot().

Parameters:

• save_annotations (bool) – Whether to save annotations as txt. Defaults to False.

• save_bad_channels (bool) – Whether to save bad channels as txt. Defaults to False.

• overwrite (bool) – Whether to overwrite annotations and bad_channels files if exist. Defaults to False.

• **kwargs – Arguments passed to mne.io.Raw.plot().

plot_sensors(legend=None, legend_args=None, **kwargs)

A wrapper for mne.viz.plot_sensors() with a legend.

Parameters:

• legend (Iterable[str]) – ch_groups names to connect to colors. Defaults to None.

• legend_args (dict) – Arguments passed to matplotlib.axes.Axes.legend(). Defaults to None.

• **kwargs – Arguments passed to mne.viz.plot_sensors().

save_raw(fname, **kwargs)

A wrapper for mne.io.Raw.save().

Parameters:

• fname (str) – Filename for the fif file being saved.

• **kwargs – Arguments passed to mne.io.Raw.save().

set_eeg_reference(ref_channels='average', projection=False, **kwargs)

A wrapper for mne.io.Raw.set_eeg_reference().

Parameters:

• ref_channels – ref_channels. Defaults to ‘average’.

• projection – projection. Defaults to False.

• **kwargs – Additional arguments passed to mne.io.Raw.set_eeg_reference().

property sf

A wrapper for raw.info["sfreq"].

Returns:

sampling frequency

Return type:

float

prec_pipe: Type[BasePipeType]

Preceding pipe that hands over mne_raw object and output_dir.

path_to_eeg: Path

Can be any eeg file type supported by mne.io.read_raw().

output_dir: Path

Path to the directory where the output will be saved.

mne_raw: mne.io.Raw

An instanse of mne.io.Raw.