Function _compute_morph_matrix

mne/morph.py:1175–1224

Compute morph matrix.

(
    subject_from,
    subject_to,
    vertices_from,
    vertices_to,
    smooth=None,
    subjects_dir=None,
    warn=True,
    xhemi=False,
)

def _compute_morph_matrix(
    subject_from,
    subject_to,
    vertices_from,
    vertices_to,
    smooth=None,
    subjects_dir=None,
    warn=True,
    xhemi=False,
):
    """Compute morph matrix."""
    logger.info("Computing morph matrix...")
    subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)

    tris = _get_subject_sphere_tris(subject_from, subjects_dir)
    maps = read_morph_map(subject_from, subject_to, subjects_dir, xhemi)

    # morph the data

    morpher = []
    for hemi_to in range(2):  # iterate over to / block-rows of CSR matrix
        hemi_from = (1 - hemi_to) if xhemi else hemi_to
        morpher.append(
            _hemi_morph(
                tris[hemi_from],
                vertices_to[hemi_to],
                vertices_from[hemi_from],
                smooth,
                maps[hemi_from],
                warn,
            )
        )

    shape = (sum(len(v) for v in vertices_to), sum(len(v) for v in vertices_from))
    data = [m.data for m in morpher]
    indices = [m.indices.copy() for m in morpher]
    indptr = [m.indptr.copy() for m in morpher]
    # column indices need to be adjusted
    indices[0 if xhemi else 1] += len(vertices_from[0])
    indices = np.concatenate(indices)
    # row index pointers need to be adjusted
    indptr[1] = indptr[1][1:] + len(data[0])
    indptr = np.concatenate(indptr)
    # data does not need to be adjusted
    data = np.concatenate(data)
    # this is equivalent to morpher = sparse_block_diag(morpher).tocsr(),
    # but works for xhemi mode
    morpher = sparse.csr_array((data, indices, indptr), shape=shape)
    logger.info("[done]")
    return morpher


def _hemi_morph(tris, vertices_to, vertices_from, smooth, maps, warn):