Function subspace

stumpy/mstump.py:96–242

Compute the ``k``-dimensional matrix profile subspace for a given subsequence index and its nearest neighbor index Parameters ---------- T : numpy.ndarray The time series or sequence for which the multi-dimensional matrix profile, multi-dimensional matrix profil

(
    T,
    m,
    subseq_idx,
    nn_idx,
    k,
    include=None,
    discords=False,
    discretize_func=None,
    n_bit=8,
    normalize=True,
    p=2.0,
    T_subseq_isconstant=None,
)

@core.non_normalized(maamp_subspace, exclude=["normalize", "T_subseq_isconstant"])
def subspace(
    T,
    m,
    subseq_idx,
    nn_idx,
    k,
    include=None,
    discords=False,
    discretize_func=None,
    n_bit=8,
    normalize=True,
    p=2.0,
    T_subseq_isconstant=None,
):
    """
    Compute the ``k``-dimensional matrix profile subspace for a given subsequence index
    and its nearest neighbor index

    Parameters
    ----------
    T : numpy.ndarray
        The time series or sequence for which the multi-dimensional matrix profile,
        multi-dimensional matrix profile indices were computed.

    m : int
        Window size.

    subseq_idx : int
        The subsequence index in ``T``.

    nn_idx : int
        The nearest neighbor index in ``T``.

    k : int
        The subset number of dimensions out of ``D = T.shape[0]``-dimensions to return
        the subspace for. Note that zero-based indexing is used.

    include : numpy.ndarray, default None
        A list of (zero-based) indices corresponding to the dimensions in ``T`` that
        must be included in the constrained multidimensional motif search.
        For more information, see Section IV D in:

        `DOI: 10.1109/ICDM.2017.66 \
        <https://www.cs.ucr.edu/~eamonn/Motif_Discovery_ICDM.pdf>`__

    discords : bool, default False
        When set to ``True``, this reverses the distance profile to favor discords
        rather than motifs. Note that indices in ``include`` are still maintained and
        respected.

    discretize_func : func, default None
        A function for discretizing each input array. When this is ``None``, an
        appropriate discretization function (based on the ``normalize`` parameter) will
        be applied.

    n_bit : int, default 8
        The number of bits used for discretization. For more information on an
        appropriate value, see Figure 4 in: