Function compute_whitener

mne/cov.py:2200–2320

Compute whitening matrix. Parameters ---------- noise_cov : Covariance The noise covariance. %(info)s Can be None if ``noise_cov`` has already been prepared with :func:`prepare_noise_cov`. %(picks_good_data_noref)s %(rank_none)s .. versionadded:: 0.1

(
    noise_cov,
    info=None,
    picks=None,
    rank=None,
    scalings=None,
    return_rank=False,
    pca=False,
    return_colorer=False,
    on_rank_mismatch="warn",
    verbose=None,
)

@verbose
def compute_whitener(
    noise_cov,
    info=None,
    picks=None,
    rank=None,
    scalings=None,
    return_rank=False,
    pca=False,
    return_colorer=False,
    on_rank_mismatch="warn",
    verbose=None,
):
    """Compute whitening matrix.

    Parameters
    ----------
    noise_cov : Covariance
        The noise covariance.
    %(info)s Can be None if ``noise_cov`` has already been
        prepared with :func:`prepare_noise_cov`.
    %(picks_good_data_noref)s
    %(rank_none)s

        .. versionadded:: 0.18
           Support for 'info' mode.
    scalings : dict | None
        The rescaling method to be applied. See documentation of
        ``prepare_noise_cov`` for details.
    return_rank : bool
        If True, return the rank used to compute the whitener.

        .. versionadded:: 0.15
    pca : bool | str
        Space to project the data into. Options:

        :data:`python:True`
            Whitener will be shape (n_nonzero, n_channels).
        ``'white'``
            Whitener will be shape (n_channels, n_channels), potentially rank
            deficient, and have the first ``n_channels - n_nonzero`` rows and
            columns set to zero.
        :data:`python:False` (default)
            Whitener will be shape (n_channels, n_channels), potentially rank
            deficient, and rotated back to the space of the original data.

        .. versionadded:: 0.18
    return_colorer : bool
        If True, return the colorer as well.
    %(on_rank_mismatch)s
    %(verbose)s

    Returns
    -------
    W : ndarray, shape (n_channels, n_channels) or (n_nonzero, n_channels)
        The whitening matrix.
    ch_names : list
        The channel names.
    rank : int