Function maamp_subspace

stumpy/maamp.py:66–163

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 in

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

def maamp_subspace(
    T,
    m,
    subseq_idx,
    nn_idx,
    k,
    include=None,
    discords=False,
    discretize_func=None,
    n_bit=8,
    p=2.0,
):
    """
    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

    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:

        `DOI: 10.1109/ICDM.2016.0069 \
        <https://www.cs.ucr.edu/~eamonn/PID4481999_Matrix%20Profile_III.pdf>`__