mne.source_space.compute_distance_to_sensors

mne.source_space.compute_distance_to_sensors(src, info, picks=None, trans=None, verbose=None)

Compute distances between vertices and sensors.

Parameters

srcinstance of SourceSpaces

The object with vertex positions for which to compute distances to sensors.

infoinstance of Info

Measurement information with sensor positions to which distances shall be computed.

picksstr | list | 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 good data channels. Note that channels in info['bads'] will be included if their names or indices are explicitly provided.

transstr | dict | instance of Transform

If str, the path to the head<->MRI transform *-trans.fif file produced during coregistration. Can also be 'fsaverage' to use the built-in fsaverage transformation.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only.

Returns

deptharray of shape (n_vertices, n_channels)

The Euclidean distances of source space vertices with respect to sensors.

Examples using mne.source_space.compute_distance_to_sensors

Display sensitivity maps for EEG and MEG sensors