from __future__ import print_function

import mne
import os.path as op

"""
Explanation: The :class:Info &lt;mne.Info&gt; data structure
End of explanation
"""


# Read the info object from an example recording
info = mne.io.read_info(
    op.join(mne.datasets.sample.data_path(), 'MEG', 'sample',
            'sample_audvis_raw.fif'), verbose=False)

"""
Explanation: The :class:Info &lt;mne.Info&gt; data object is typically created
when data is imported into MNE-Python and contains details such as:

date, subject information, and other recording details
the sampling rate
information about the data channels (name, type, position, etc.)
digitized points
sensor–head coordinate transformation matrices

and so forth. See the :class:the API reference &lt;mne.Info&gt;
for a complete list of all data fields. Once created, this object is passed
around throughout the data analysis pipeline.
It behaves as a nested Python dictionary:
End of explanation
"""


print('Keys in info dictionary:\n', info.keys())

"""
Explanation: List all the fields in the info object
End of explanation
"""


print(info['sfreq'], 'Hz')

"""
Explanation: Obtain the sampling rate of the data
End of explanation
"""


print(info['chs'][0])

"""
Explanation: List all information about the first data channel
End of explanation
"""


channel_indices = mne.pick_channels(info['ch_names'], ['MEG 0312', 'EEG 005'])

"""
Explanation: Obtaining subsets of channels
There are a number of convenience functions to obtain channel indices, given
an :class:mne.Info object.
Get channel indices by name
End of explanation
"""


channel_indices = mne.pick_channels_regexp(info['ch_names'], 'MEG *')

"""
Explanation: Get channel indices by regular expression
End of explanation
"""


channel_indices = mne.pick_types(info, meg=True)  # MEG only
channel_indices = mne.pick_types(info, eeg=True)  # EEG only

"""
Explanation: Get channel indices by type
End of explanation
"""


channel_indices = mne.pick_types(info, meg='grad', eeg=True)

"""
Explanation: MEG gradiometers and EEG channels
End of explanation
"""


channel_indices_by_type = mne.io.pick.channel_indices_by_type(info)
print('The first three magnetometers:', channel_indices_by_type['mag'][:3])

"""
Explanation: Get a dictionary of channel indices, grouped by channel type
End of explanation
"""


# Channel type of a specific channel
channel_type = mne.io.pick.channel_type(info, 75)
print('Channel #75 is of type:', channel_type)

"""
Explanation: Obtaining information about channels
End of explanation
"""


meg_channels = mne.pick_types(info, meg=True)[:10]
channel_types = [mne.io.pick.channel_type(info, ch) for ch in meg_channels]
print('First 10 MEG channels are of type:\n', channel_types)

"""
Explanation: Channel types of a collection of channels
End of explanation
"""


# Only keep EEG channels
eeg_indices = mne.pick_types(info, meg=False, eeg=True)
reduced_info = mne.pick_info(info, eeg_indices)

print(reduced_info)

"""
Explanation: Dropping channels from an info structure
It is possible to limit the info structure to only include a subset of
channels with the :func:mne.pick_info function:
End of explanation
"""


