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:

fname : string

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

condition : int 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.

baseline : None (default) or tuple of length 2

The time interval to apply baseline correction. If None do not apply it. If baseline is (a, b) the interval is between “a (s)” and “b (s)”. If a is None the beginning of the data is used and if b is None then b is set to the end of the interval. If baseline is equal to (None, None) all the time interval is used. Correction is applied by computing mean of the baseline period and subtracting it from the data. The baseline (a, b) includes both endpoints, i.e. all timepoints t such that a <= t <= b.

kind : str

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

proj : bool

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

allow_maxshield : bool | 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.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

Returns:

evoked : Evoked (if condition is int or str) or list of Evoked (if

condition is None or list) The evoked dataset(s).

See also

write_evokeds