Rescale (baseline correct) data.
array
It can be of any shape. The only constraint is that the last dimension should be time.
array
Time instants is seconds.
None
| tuple
of length 2The 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
.
Perform baseline correction by
subtracting the mean of baseline values (‘mean’)
dividing by the mean of baseline values (‘ratio’)
dividing by the mean of baseline values and taking the log (‘logratio’)
subtracting the mean of baseline values followed by dividing by the mean of baseline values (‘percent’)
subtracting the mean of baseline values and dividing by the standard deviation of baseline values (‘zscore’)
dividing by the mean of baseline values, taking the log, and dividing by the standard deviation of log baseline values (‘zlogratio’)
Whether to return a new instance or modify in place.
list
of int
| None
Data to process along the axis=-2 (None, default, processes all).
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.
array
Array of same shape as data after rescaling.
mne.baseline.rescale
#Explore event-related dynamics for specific frequency bands
Time-frequency on simulated data (Multitaper vs. Morlet vs. Stockwell)