BaseHypnoPipe#

class sleepeegpy.base.BaseHypnoPipe(*, prec_pipe=None, path_to_eeg=_Nothing.NOTHING, output_dir=_Nothing.NOTHING, path_to_hypno=None, hypno_freq=_Nothing.NOTHING, hypno=_Nothing.NOTHING)[source]#

Bases: BasePipe, ABC

A base class for the sleep-stage-analysis pipeline segments.

Methods:

`interpolate_bads`	A wrapper for `mne.io.Raw.interpolate_bads()`
`plot`	A wrapper for `mne.io.Raw.plot()`.
`plot_sensors`	A wrapper for `mne.viz.plot_sensors()` with a legend.
`predict_hypno`	Runs YASA's automatic sleep staging.
`save_raw`	A wrapper for `mne.io.Raw.save()`.
`set_eeg_reference`	A wrapper for `mne.io.Raw.set_eeg_reference()`.
`sleep_stats`	A wrapper for `yasa.sleep_statistics()`.

Attributes:

`bad_data_percent`	Calculates percent of data segments annotated as BAD.
`sf`	A wrapper for `raw.info["sfreq"]`.
`path_to_hypno`	Path to hypnogram.
`hypno_freq`	Sampling rate of the hypnogram in Hz.
`hypno`	Hypnogram with sampling frequency hypno_freq with int representing sleep stage.
`hypno_up`	Hypnogram upsampled to the sampling frequency of the raw data.
`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`.

path_to_hypno: Path#: Path to hypnogram. Must be text file with every row being int representing sleep stage for the epoch.

hypno_freq: float#

Sampling rate of the hypnogram in Hz.

E.g., 1/30 means 1 sample per 30 secs epoch, 250 means 1 sample per 1/250 sec epoch.

hypno: ndarray#: Hypnogram with sampling frequency hypno_freq with int representing sleep stage.

hypno_up: array#: Hypnogram upsampled to the sampling frequency of the raw data.

predict_hypno(eeg_name='E183', eog_name='E252', emg_name='E247', ref_name='E26', save=True)[source]#

Runs YASA’s automatic sleep staging.

Parameters:

eeg_name (str) – Preferentially a central electrode. Defaults to “E183”.
eog_name (str) – Preferentially, the left LOC channel. Defaults to “E252”.
emg_name (str) – Preferentially a chin electrode. Defaults to “E247”.
ref_name (str) – Reference channel, preferentially a mastoid. Defaults to “E26”.
save (bool) – Whether to save the hypnogram to file. Defaults to True.

sleep_stats(save=False)[source]#

A wrapper for yasa.sleep_statistics().

Parameters:: save (bool) – Whether to save the stats to csv. 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[TypeVar(BasePipeType, bound= BasePipe)]#: 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: Raw#: An instanse of mne.io.Raw.