Function _maamp_multi_distance_profile

stumpy/maamp.py:303–394

Multi-dimensional wrapper to compute the multi-dimensional non-normalized (i.e., without z-normalization) distance profile for a given query window within the times series or sequence that is denoted by the `query_idx` index. Essentially, this is a convenience wrapper around `_multi

(
    query_idx,
    T_A,
    T_B,
    m,
    T_B_subseq_isfinite,
    p=2.0,
    include=None,
    discords=False,
    excl_zone=None,
)

def _maamp_multi_distance_profile(
    query_idx,
    T_A,
    T_B,
    m,
    T_B_subseq_isfinite,
    p=2.0,
    include=None,
    discords=False,
    excl_zone=None,
):
    """
    Multi-dimensional wrapper to compute the multi-dimensional non-normalized (i.e.,
    without z-normalization) distance profile for a given query window within the
    times series or sequence that is denoted by the `query_idx` index. Essentially,
    this is a convenience wrapper around `_multi_mass_absolute`.

    Parameters
    ----------
    query_idx : int
        The window index to calculate the multi-dimensional distance profile

    T_A : numpy.ndarray
        The time series or sequence for which the multi-dimensional distance profile
        will be returned

    T_B : numpy.ndarray
        The time series or sequence that contains your query subsequences

    m : int
        Window size

    T_B_subseq_isfinite : numpy.ndarray
        A boolean array that indicates whether a subsequence in `T_B` contains a
        `np.nan`/`np.inf` value (False)

    p : float
        The p-norm to apply for computing the Minkowski distance. Minkowski distance is
        typically used with `p` being 1 or 2, which correspond to the Manhattan distance
        and the Euclidean distance, respectively.

    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.

    excl_zone : int
        The half width for the exclusion zone relative to the `query_idx`.

    Returns
    -------