eelbrain.datasets.get_mne_sample¶
-
eelbrain.datasets.
get_mne_sample
(tmin=-0.1, tmax=0.4, baseline=(None, 0), sns=False, src=None, sub="modality=='A'", ori='free', snr=2, method='dSPM', rm=False, stc=False, hpf=0)¶ Load events and epochs from the MNE sample data
Parameters: - tmin : scalar
Relative time of the first sample of the epoch.
- tmax : scalar
Relative time of the last sample of the epoch.
- baseline : {None, tuple of 2 {scalar, None}}
Period for baseline correction.
- sns : bool | str
Add sensor space data as NDVar as
ds['meg']
(defaultFalse
). Set to'grad'
to load gradiometer data.- src : False | ‘ico’ | ‘vol’
Add source space data as NDVar as
ds['src']
(defaultFalse
).- sub : str | list | None
Expression for subset of events to load. For a very small dataset use e.g.
[0,1]
.- ori : ‘free’ | ‘fixed’ | ‘vector’
Orientation of sources.
- snr : scalar
MNE inverse parameter.
- method : str
MNE inverse parameter.
- rm : bool
Pretend to be a repeated measures dataset (adds ‘subject’ variable).
- stc : bool
Add mne SourceEstimate for source space data as
ds['stc']
(defaultFalse
).- hpf : scalar
High pass filter cutoff.
Returns: - ds : Dataset
Dataset with epochs from the MNE sample dataset in
ds['epochs']
.