'Plot whitened evoked response.
Plots the whitened evoked response and the whitened GFP as described in
[1]_. If one single covariance object is passed, the GFP panel (bottom)
will depict different sensor types. If multiple covariance objects are
passed as a list, the left column will display the whitened evoked
responses for each channel based on the whitener from the noise
covariance that has the highest log-likelihood. The left column will
depict the whitened GFPs based on each estimator separately for each
sensor type. Instead of numbers of channels the GFP display shows the
estimated rank. The rank estimation will be printed by the logger for
each noise covariance estimator that is passed.
Parameters
noise_cov : list | instance of Covariance | str
The noise covariance as computed by ``mne.cov.compute_covariance``.
show : bool
Whether to show the figure or not. Defaults to True.
Returns
fig : instance of matplotlib.figure.Figure
The figure object containing the plot.
References
.. [1] Engemann D. and Gramfort A. (2015) Automated model selection in
covariance estimation and spatial whitening of MEG and EEG
signals, vol. 108, 328-342, NeuroImage.
Notes
.. versionadded:: 0.9.0'

def plot_white(self, noise_cov, show=True):

    return _plot_evoked_white(self, noise_cov=noise_cov, scalings=None, rank=None, show=show)
