Module « scipy.spatial.distance »

Fonction mahalanobis - module scipy.spatial.distance

Signature de la fonction mahalanobis

def mahalanobis(u, v, VI) 

Description

mahalanobis.__doc__

    Compute the Mahalanobis distance between two 1-D arrays.

    The Mahalanobis distance between 1-D arrays `u` and `v`, is defined as

    .. math::

       \sqrt{ (u-v) V^{-1} (u-v)^T }

    where ``V`` is the covariance matrix.  Note that the argument `VI`
    is the inverse of ``V``.

    Parameters
    ----------
    u : (N,) array_like
        Input array.
    v : (N,) array_like
        Input array.
    VI : array_like
        The inverse of the covariance matrix.

    Returns
    -------
    mahalanobis : double
        The Mahalanobis distance between vectors `u` and `v`.

    Examples
    --------
    >>> from scipy.spatial import distance
    >>> iv = [[1, 0.5, 0.5], [0.5, 1, 0.5], [0.5, 0.5, 1]]
    >>> distance.mahalanobis([1, 0, 0], [0, 1, 0], iv)
    1.0
    >>> distance.mahalanobis([0, 2, 0], [0, 1, 0], iv)
    1.0
    >>> distance.mahalanobis([2, 0, 0], [0, 1, 0], iv)
    1.7320508075688772