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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:
 Interpolate bad channels for MEG/EEG channels
This example shows how to interpolate bad MEG/EEG channels
Using spherical splines from 
Step1:  Compute interpolation (also works with Raw and Epochs objects)
Step2:  You can also use minimum-norm for EEG as well as MEG
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Python Code:
# Authors: Denis A. Engemann <denis.engemann@gmail.com>
#          Mainak Jas <mainak.jas@telecom-paristech.fr>
#
# License: BSD-3-Clause
import mne
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
fname = data_path + '/MEG/sample/sample_audvis-ave.fif'
evoked = mne.read_evokeds(fname, condition='Left Auditory',
                          baseline=(None, 0))
# plot with bads
evoked.plot(exclude=[], picks=('grad', 'eeg'))
Explanation: Interpolate bad channels for MEG/EEG channels
This example shows how to interpolate bad MEG/EEG channels
Using spherical splines from :footcite:PerrinEtAl1989 for EEG data.
Using field interpolation for MEG and EEG data.
In this example, the bad channels will still be marked as bad.
Only the data in those channels is replaced.
End of explanation
evoked_interp = evoked.copy().interpolate_bads(reset_bads=False)
evoked_interp.plot(exclude=[], picks=('grad', 'eeg'))
Explanation: Compute interpolation (also works with Raw and Epochs objects)
End of explanation
evoked_interp_mne = evoked.copy().interpolate_bads(
    reset_bads=False, method=dict(eeg='MNE'), verbose=True)
evoked_interp_mne.plot(exclude=[], picks=('grad', 'eeg'))
Explanation: You can also use minimum-norm for EEG as well as MEG
End of explanation
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