Function _prepare_for_forward

mne/forward/_make_forward.py:441–613

Prepare for forward computation. The sensors dict contains keys for each sensor type, e.g. 'meg', 'eeg'. The vale for each of these is a dict that comes from _prep_meg_channels or _prep_eeg_channels. Each dict contains: - defs : a list of dicts (one per channel) with 'rmag', 'cosma

(
    src,
    mri_head_t,
    info,
    bem,
    mindist,
    n_jobs,
    *,
    bem_extra="",
    trans="",
    info_extra="",
    meg=True,
    eeg=True,
    ignore_ref=False,
    allow_bem_none=False,
    on_inside="raise",
    verbose=None,
)

@verbose
def _prepare_for_forward(
    src,
    mri_head_t,
    info,
    bem,
    mindist,
    n_jobs,
    *,
    bem_extra="",
    trans="",
    info_extra="",
    meg=True,
    eeg=True,
    ignore_ref=False,
    allow_bem_none=False,
    on_inside="raise",
    verbose=None,
):
    """Prepare for forward computation.

    The sensors dict contains keys for each sensor type, e.g. 'meg', 'eeg'.
    The vale for each of these is a dict that comes from _prep_meg_channels or
    _prep_eeg_channels. Each dict contains:

    - defs : a list of dicts (one per channel) with 'rmag', 'cosmag', etc.
    - ch_names: a list of str channel names corresponding to the defs
    - compensator (optional): the ndarray compensation matrix to apply
    - post_picks (optional): the ndarray of indices to pick after applying the
      compensator
    """
    # Read the source locations
    logger.info("")
    # let's make a copy in case we modify something
    src = _ensure_src(src).copy()
    nsource = sum(s["nuse"] for s in src)
    if len(src) and nsource == 0:
        raise RuntimeError(
            "No sources are active in these source spaces. "
            '"do_all" option should be used.'
        )
    logger.info(
        "Read %d source spaces a total of %d active source locations", len(src), nsource
    )
    # Delete some keys to clean up the source space:
    for key in ["working_dir", "command_line"]:
        if key in src.info:
            del src.info[key]

    # Read the MRI -> head coordinate transformation
    logger.info("")
    _print_coord_trans(mri_head_t)

    # make a new dict with the relevant information
    arg_list = [info_extra, trans, src, bem_extra, meg, eeg, mindist, n_jobs, verbose]
    cmd = f"make_forward_solution({', '.join(str(a) for a in arg_list)})"
    mri_id = dict(machid=np.zeros(2, np.int32), version=0, secs=0, usecs=0)

    info_trans = str(trans) if isinstance(trans, Path) else trans