# # .. warning:: # Both :func:`~mne.pick_channels` and :func:`~mne.pick_channels_regexp` # operate on lists of channel names, so they are unaware of which channels # (if any) have been marked as "bad" in ``info['bads']``. Use caution to # avoid accidentally selecting bad channels. # # # Obtaining channel type information # ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ # # Sometimes it can be useful to know channel type based on its index in the # data array. For this case, use :func:`mne.channel_type`, which takes # an :class:`~mne.Info` object and a single integer channel index: print(mne.channel_type(info, 25)) # %% # To obtain several channel types at once, you could embed # :func:`~mne.channel_type` in a :term:`list comprehension`, or use the # :meth:`~mne.io.Raw.get_channel_types` method of a :class:`~mne.io.Raw`, # :class:`~mne.Epochs`, or :class:`~mne.Evoked` instance: picks = (25, 76, 77, 319) print([mne.channel_type(info, x) for x in picks]) print(raw.get_channel_types(picks=picks)) # %% # Alternatively, you can get the indices of all channels of *all* channel types # present in the data, using :func:`~mne.channel_indices_by_type`, # which returns a :class:`dict` with channel types as keys, and lists of
# # .. warning:: # Both :func:`~mne.pick_channels` and :func:`~mne.pick_channels_regexp` # operate on lists of channel names, so they are unaware of which channels # (if any) have been marked as "bad" in ``info['bads']``. Use caution to # avoid accidentally selecting bad channels. # # # Obtaining channel type information # ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ # # Sometimes it can be useful to know channel type based on its index in the # data array. For this case, use :func:`mne.channel_type`, which takes # an :class:`~mne.Info` object and a single integer channel index: print(mne.channel_type(info, 25)) ############################################################################### # To obtain several channel types at once, you could embed # :func:`~mne.channel_type` in a :term:`list comprehension`: print([mne.channel_type(info, x) for x in (25, 76, 77, 319)]) ############################################################################### # Alternatively, you can get the indices of all channels of *all* channel types # present in the data, using :func:`~mne.channel_indices_by_type`, # which returns a :class:`dict` with channel types as keys, and lists of # channel indices as values: ch_idx_by_type = mne.channel_indices_by_type(info) print(ch_idx_by_type.keys())
def pick_types(
info,
eeg=False,
seeg=False,
ecog=False,
include=(),
exclude="bads",
selection=None,
):
"""Pick channels by type and names.
Parameters
----------
info : dict
The measurement info.
eeg : bool
If True include EEG channels.
seeg : bool
Stereotactic EEG channels.
ecog : bool
Electrocorticography channels.
include : list of str
List of additional channels to include. If empty do not include any.
exclude : list of str | str
List of channels to exclude. If 'bads' (default), exclude channels
in ``info['bads']``.
selection : list of str
Restrict sensor channels (MEG, EEG) to this list of channel names.
Returns
-------
sel : array of int
Indices of good channels.
"""
# only issue deprecation warning if there are MEG channels in the data and
# if the function was called with the default arg for meg
deprecation_warn = False
exclude = []
nchan = info["nchan"]
pick = np.zeros(nchan, dtype=bool)
for param in (
eeg,
seeg,
ecog,
):
if not isinstance(param, bool):
w = ("Parameters for all channel types (with the exception of "
'"meg", "ref_meg" and "fnirs") must be of type bool, not {}.')
raise ValueError(w.format(type(param)))
param_dict = dict(
eeg=eeg,
seeg=seeg,
ecog=ecog,
)
# avoid triage if possible
for k in range(nchan):
ch_type = channel_type(info, k)
pick[k] = param_dict[ch_type]
# restrict channels to selection if provided
if selection is not None:
# the selection only restricts these types of channels
sel_kind = [FIFF.FIFFV_EEG_CH]
for k in np.where(pick)[0]:
if (info["chs"][k]["kind"] in sel_kind
and info["ch_names"][k] not in selection):
pick[k] = False
myinclude = [info["ch_names"][k] for k in range(nchan) if pick[k]]
myinclude += include
if len(myinclude) == 0:
sel = np.array([], int)
else:
sel = pick_channels(info["ch_names"], myinclude, exclude)
if deprecation_warn:
warn(
"The default of meg=True will change to meg=False in version 0.22"
", set meg explicitly to avoid this warning.",
DeprecationWarning,
)
return sel