Compute inter-source distances along the cortical surface.
This function will also try to add patch info for the source space.
It will only occur if the
dist_limit is sufficiently high that all
points on the surface are within
dist_limit of a point in the
The source spaces to compute distances for.
The upper limit of distances to include (in meters). Note: if limit < np.inf, scipy > 0.13 (bleeding edge as of 10/2013) must be installed. If 0, then only patch (nearest vertex) information is added.
The number of jobs to run in parallel. If
-1, it is set
to the number of CPU cores. Requires the
None (default) is a marker for ‘unset’ that will be interpreted
n_jobs=1 (sequential execution) unless the call is performed under
joblib.parallel_backend() context manager that sets another
The original source spaces, with distance information added. The distances are stored in src[n][‘dist’]. Note: this function operates in-place.
This function can be memory- and CPU-intensive. On a high-end machine
(2012) running 6 jobs in parallel, an ico-5 (10242 per hemi) source space
takes about 10 minutes to compute all distances (
dist_limit = np.inf).
dist_limit = 0.007, computing distances takes about 1 minute.
We recommend computing distances once per source space and then saving the source space to disk, as the computed distances will automatically be stored along with the source space data for future use.