timeflux.helpers.mne

---

MNE helpers

mne

timeflux.helpers.mne.logger

timeflux.helpers.mne.xarray_to_mne(data, meta, context_key, event_id, reporting='warn', ch_types='eeg', **kwargs)

Convert DataArray and meta into mne Epochs object

Parameters:

• data (DataArray) – Array of dimensions (‘epoch’, ‘time’, ‘space’)

• meta (dict) – Dictionary with keys ‘epochs_context’, ‘rate’, ‘epochs_onset’

• context_key (str|None) – key to select the context label.

• string (If the context is a) –

• None. (context_key should be set to) –

• event_id (dict) – Associates context label to an event_id that should be an int. (eg. dict(auditory=1, visual=3))

• reporting ('warn'|'error'| None) – How this function handles epochs with invalid context: - ‘error’ will raise a TimefluxException - ‘warn’ will print a warning with warnings.warn() and skip the corrupted epochs - None will skip the corrupted epochs

• ch_types (list|str) – Channel type to

Returns:

mne object with the converted data.

Return type:

epochs (mne.Epochs)

timeflux.helpers.mne.mne_to_xarray(epochs, context_key, event_id, output='dataarray')

Convert mne Epochs object into DataArray along with meta.

Parameters:

• epochs (mne.Epochs) – mne object with the converted data.

• context_key (str|None) – key to select the context label.

• string (If the context is a) –

• None. (context_key should be set to) –

• event_id (dict) – Associates context label to an event_id that should be an int. (eg. dict(auditory=1, visual=3))

• output (str) – type of the expected output (DataArray or Dataset)

Returns:

Array of dimensions (‘epoch’, ‘time’, ‘space’) meta (dict): Dictionary with keys ‘epochs_context’, ‘rate’, ‘epochs_onset’

Return type:

data (DataArray|Dataset)