eelbrain.load.fiff.mne_epochs¶
-
eelbrain.load.fiff.
mne_epochs
(ds, tmin=-0.1, tmax=None, baseline=None, i_start='i_start', raw=None, drop_bad_chs=True, picks=None, reject=None, tstop=None, name=None, decim=1, **kwargs)¶ Load epochs as
mne.Epochs
.Parameters: - ds : Dataset
Dataset containing a variable which defines epoch cues (i_start).
- tmin : scalar
First sample to include in the epochs in seconds (Default is -0.1).
- tmax : scalar
Last sample to include in the epochs in seconds (Default 0.6; use
tstop
instead to specify index exclusive of last sample).- baseline : tuple(tmin, tmax) |
None
Time interval for baseline correction. Tmin/tmax in seconds, or None to use all the data (e.g.,
(None, 0)
uses all the data from the beginning of the epoch up to t=0).baseline=None
for no baseline correction (default).- i_start : str
name of the variable containing the index of the events.
- raw : None | mne Raw
If None, ds.info[‘raw’] is used.
- drop_bad_chs : bool
Drop all channels in raw.info[‘bads’] form the Epochs. This argument is ignored if the picks argument is specified.
- picks, reject
mne.Epochs
parameters.- tstop : scalar
Alternative to
tmax
: Whiletmax
specifies the last samples to include,tstop
can be used to specify the epoch time excluding the last time point (i.e., standard Python/Eelbrain indexing convention). For example, at 100 Hz the epoch withtmin=-0.1, tmax=0.4
will have 51 samples, while the epoch specified withtmin=-0.1, tstop=0.4
will have 50 samples.- …
mne.Epochs
parameters.