mne.read_evokeds#

mne.read_evokeds(fname, condition=None, baseline=None, kind='average', proj=True, allow_maxshield=False, verbose=None)[source]#

Read evoked dataset(s).

Parameters:

fnamepath-like

The filename, which should end with -ave.fif or -ave.fif.gz.

conditionint or str | list of int or str | None

The index or list of indices of the evoked dataset to read. FIF files can contain multiple datasets. If None, all datasets are returned as a list.

baselineNone | tuple of length 2

The time interval to consider as “baseline” when applying baseline correction. If None, do not apply baseline correction. If a tuple (a, b), the interval is between a and b (in seconds), including the endpoints. If a is None, the beginning of the data is used; and if b is None, it is set to the end of the interval. If (None, None), the entire time interval is used.

Note

The baseline (a, b) includes both endpoints, i.e. all timepoints t such that a <= t <= b.

Correction is applied to each channel individually in the following way:

Calculate the mean signal of the baseline period.
Subtract this mean from the entire Evoked.

If None (default), do not apply baseline correction.

Note

Note that if the read Evoked objects have already been baseline-corrected, the data retrieved from disk will always be baseline-corrected (in fact, only the baseline-corrected version of the data will be saved, so there is no way to undo this procedure). Only after the data has been loaded, a custom (additional) baseline correction may be optionally applied by passing a tuple here. Passing None will not remove an existing baseline correction, but merely omit the optional, additional baseline correction.

kindstr

Either ‘average’ or ‘standard_error’, the type of data to read.

projbool

If False, available projectors won’t be applied to the data.

allow_maxshieldbool | str (default False)

If True, allow loading of data that has been recorded with internal active compensation (MaxShield). Data recorded with MaxShield should generally not be loaded directly, but should first be processed using SSS/tSSS to remove the compensation signals that may also affect brain activity. Can also be “yes” to load without eliciting a warning.

verbosebool | str | int | None

Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Returns:

evokedEvoked or list of Evoked: The evoked dataset(s); one Evoked if condition is an integer or string; or a list of Evoked if condition is None or a list.