- mne.filter.resample(x, up=1.0, down=1.0, npad=100, axis=-1, window='boxcar', n_jobs=None, pad='reflect_limited', *, verbose=None)[source]#
Resample an array.
Operates along the last dimension of the array.
Signal to resample.
Factor to upsample by.
Factor to downsample by.
Amount to pad the start and end of the data. Can also be “auto” to use a padding that will result in a power-of-two size (can be much faster).
Axis along which to resample (default is the last axis).
Frequency-domain window to use in resampling. See
Number of jobs to run in parallel. Can be ‘cuda’ if
cupyis installed properly.
The type of padding to use. Supports all
modeoptions. Can also be
"reflect_limited", which pads with a reflected version of each vector mirrored on the first and last values of the vector, followed by zeros. The default is
New in version 0.15.
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.
The x array resampled.
This uses (hopefully) intelligent edge padding and frequency-domain windowing improve scipy.signal.resample’s resampling method, which we have adapted for our use here. Choices of npad and window have important consequences, and the default choices should work well for most natural signals.
Resampling arguments are broken into “up” and “down” components for future compatibility in case we decide to use an upfirdn implementation. The current implementation is functionally equivalent to passing up=up/down and down=1.
Spectro-temporal receptive field (STRF) estimation on continuous data
Receptive Field Estimation and Prediction