ICAPipe#

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)[source]#

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[source]#: Instance of mne.preprocessing.ICA.

fit(filter_kwargs=None, **fit_kwargs)[source]#

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)[source]#: A wrapper for mne.preprocessing.ICA.plot_sources().

plot_components(save=False, **kwargs)[source]#: A wrapper for mne.preprocessing.ICA.plot_components().

plot_properties(picks=None, save=False, **kwargs)[source]#: A wrapper for mne.preprocessing.ICA.plot_properties().

apply(exclude=None, **kwargs)[source]#: A wrapper for mne.preprocessing.ICA.apply().

save_ica(fname='data-ica.fif', overwrite=False)[source]#

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[source]#

Calculates percent of data segments annotated as BAD.

Returns:: percent of bad data spans in raw data
Return type:: float

interpolate_bads(**interp_kwargs)[source]#

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)[source]#

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)[source]#

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)[source]#

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)[source]#

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[source]#

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.