mne.channels.read_ch_adjacency#
- mne.channels.read_ch_adjacency(fname, picks=None)[source]#
Read a channel adjacency (“neighbors”) file that ships with MNE.
More information on these neighbor definitions can be found on the related FieldTrip documentation pages.
- Parameters:
- fname
str
The path to the file to load, or the name of a channel adjacency matrix that ships with MNE-Python.
Note
You can retrieve the names of all built-in channel adjacencies via
mne.channels.get_builtin_ch_adjacencies()
.- picks
str
| array_like |slice
|None
Channels to include. Slices and lists of integers will be interpreted as channel indices. In lists, channel type strings (e.g.,
['meg', 'eeg']
) will pick channels of those types, channel name strings (e.g.,['MEG0111', 'MEG2623']
will pick the given channels. Can also be the string values “all” to pick all channels, or “data” to pick data channels. None (default) will pick all channels. Note that channels ininfo['bads']
will be included if their names or indices are explicitly provided. Picks must match the template.
- fname
- Returns:
- ch_adjacency
scipy.sparse.csr_matrix
, shape (n_channels, n_channels) The adjacency matrix.
- ch_names
list
The list of channel names present in adjacency matrix.
- ch_adjacency
See also
Notes
If the neighbor definition you need is not shipped by MNE-Python, you may use
find_ch_adjacency()
to compute the adjacency matrix based on your 2D sensor locations.Note that depending on your use case, you may need to additionally use
mne.stats.combine_adjacency()
to prepare a final “adjacency” to pass to the eventual function.