Class stumpi

stumpy/stumpi.py:19–553

A class to compute an incremental z-normalized matrix profile for streaming data This is based on the on-line STOMPI and STAMPI algorithms. Parameters ---------- T : numpy.ndarray The time series or sequence for which the matrix profile and matrix profile indic

    ],
)
class stumpi:
    """
    A class to compute an incremental z-normalized matrix profile for streaming data

    This is based on the on-line STOMPI and STAMPI algorithms.

    Parameters
    ----------
    T : numpy.ndarray
        The time series or sequence for which the matrix profile and matrix profile
        indices will be returned.

    m : int
        Window size.

    egress : bool, default True
        If set to ``True``, the oldest data point in the time series is removed and
        the time series length remains constant rather than forever increasing

    normalize : bool, default True
        When set to ``True``, this z-normalizes subsequences prior to computing
        distances. Otherwise, this class gets re-routed to its complementary
        non-normalized equivalent set in the ``@core.non_normalized`` class decorator.

    p : float, default 2.0
        The p-norm to apply for computing the Minkowski distance. This parameter is
        ignored when ``normalize == True``.

    k : int, default 1
        The number of top ``k`` smallest distances used to construct the matrix profile.
        Note that this will increase the total computational time and memory usage
        when ``k > 1``.

    mp : numpy.ndarray, default None
        A pre-computed matrix profile (and corresponding matrix profile indices).
        This is a 2D array of shape ``(len(T) - m + 1, 2 * k + 2)``, where the first
        ``k`` columns are top-k matrix profile, and the next ``k`` columns are their
        corresponding indices. The last two columns correspond to the top-1 left and
        top-1 right matrix profile indices. When ``None`` (default), this array is
        computed internally using ``stumpy.stump``.

    T_subseq_isconstant_func : function, default None
        A custom, user-defined function that returns a boolean array that indicates
        whether a subsequence in ``T`` is constant (``True``). The function must only
        take two arguments, ``a``, a 1-D array, and ``w``, the window size, while
        additional arguments may be specified by currying the user-defined function
        using ``functools.partial``. Any subsequence with at least one
        ``np.nan``/``np.inf`` will automatically have its corresponding value set to
        ``False`` in this boolean array.

    Attributes
    ----------
    P_ : numpy.ndarray
        The updated (top-k) matrix profile for ``T``. When ``k = 1`` (default), the
        first (and only) column in this 2D array consists of the matrix profile. When
        ``k > 1``, the output has exactly ``k`` columns consisting of the top-k matrix
        profile.