Function _gpu_aamp

stumpy/gpu_aamp.py:201–440

A Numba CUDA version of AAMP for parallel computation of the non-normalized (i.e., without z-normalization) matrix profile, matrix profile indices, left matrix profile indices, and right matrix profile indices. Parameters ---------- T_A_fname : str The file name for

(
    T_A_fname,
    T_B_fname,
    m,
    range_stop,
    excl_zone,
    T_A_subseq_isfinite_fname,
    T_B_subseq_isfinite_fname,
    p,
    p_norm_fname,
    p_norm_first_fname,
    w,
    ignore_trivial=True,
    range_start=1,
    device_id=0,
    k=1,
)

def _gpu_aamp(
    T_A_fname,
    T_B_fname,
    m,
    range_stop,
    excl_zone,
    T_A_subseq_isfinite_fname,
    T_B_subseq_isfinite_fname,
    p,
    p_norm_fname,
    p_norm_first_fname,
    w,
    ignore_trivial=True,
    range_start=1,
    device_id=0,
    k=1,
):
    """
    A Numba CUDA version of AAMP for parallel computation of the non-normalized (i.e.,
    without z-normalization) matrix profile, matrix profile indices, left matrix profile
    indices, and right matrix profile indices.

    Parameters
    ----------
    T_A_fname : str
        The file name for the time series or sequence for which to compute
        the matrix profile

    T_B_fname : str
        The file name for the time series or sequence that will be used to annotate T_A.
        For every subsequence in T_A, its nearest neighbor in T_B will be recorded.

    m : int
        Window size

    range_stop : int
        The index value along T_B for which to stop the matrix profile
        calculation. This parameter is here for consistency with the
        distributed `stumped` algorithm.

    excl_zone : int
        The half width for the exclusion zone relative to the current
        sliding window

    T_A_subseq_isfinite_fname : str
        The file name for the boolean array that indicates whether a subsequence in
        `T_A` contains a `np.nan`/`np.inf` value (False)

    T_B_subseq_isfinite_fname : str
        The file name for the 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.

    p_norm_fname : str