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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
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Reading/Writing a noise covariance matrix
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Plot a noise covariance matrix.
Step1:  Show covariance
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Python Code:
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
#
# License: BSD (3-clause)
from os import path as op
import mne
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
fname_cov = op.join(data_path, 'MEG', 'sample', 'sample_audvis-cov.fif')
fname_evo = op.join(data_path, 'MEG', 'sample', 'sample_audvis-ave.fif')
cov = mne.read_cov(fname_cov)
print(cov)
evoked = mne.read_evokeds(fname_evo)[0]
Explanation: =========================================
Reading/Writing a noise covariance matrix
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Plot a noise covariance matrix.
End of explanation
cov.plot(evoked.info, exclude='bads', show_svd=False)
Explanation: Show covariance
End of explanation
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