Module « scipy.cluster.vq »

Fonction py_vq2 - module scipy.cluster.vq

Signature de la fonction py_vq2

def py_vq2(*args, **kwds) 

Description

py_vq2.__doc__

    `py_vq2` is deprecated, use `py_vq` instead!

     Python version of vq algorithm.

    The algorithm computes the Euclidean distance between each
    observation and every frame in the code_book.

    Parameters
    ----------
    obs : ndarray
        Expects a rank 2 array. Each row is one observation.
    code_book : ndarray
        Code book to use. Same format than obs. Should have same number of
        features (e.g., columns) than obs.
    check_finite : bool, optional
        Whether to check that the input matrices contain only finite numbers.
        Disabling may give a performance gain, but may result in problems
        (crashes, non-termination) if the inputs do contain infinities or NaNs.
        Default: True

    Returns
    -------
    code : ndarray
        code[i] gives the label of the ith obversation; its code is
        code_book[code[i]].
    mind_dist : ndarray
        min_dist[i] gives the distance between the ith observation and its
        corresponding code.

    Notes
    -----
    This function is slower than the C version but works for
    all input types. If the inputs have the wrong types for the
    C versions of the function, this one is called as a last resort.

    It is about 20 times slower than the C version.