chaospy.Cov

chaospy.Cov(poly, dist=None, **kws)

Variance/Covariance matrix of a distribution or polynomial array.

Args:

poly (numpoly.ndpoly, Distribution) :

Input to take covariance on. Must have len(poly)>=2.

dist (Distribution) :

Defines the space the covariance is taken on. It is ignored if poly is a distribution.

Returns:

(numpy.ndarray):

Covariance matrix with shape poly.shape+poly.shape.

Examples:

>>> dist = chaospy.MvNormal([0, 0], [[2, .5], [.5, 1]])
>>> chaospy.Cov(dist)
array([[2. , 0.5],
       [0.5, 1. ]])
>>> q0, q1 = chaospy.variable(2)
>>> poly = chaospy.polynomial([1, q0, q1, 10*q0*q1-1])
>>> chaospy.Cov(poly, dist)
array([[  0. ,   0. ,   0. ,   0. ],
       [  0. ,   2. ,   0.5,   0. ],
       [  0. ,   0.5,   1. ,   0. ],
       [  0. ,   0. ,   0. , 225. ]])
>>> chaospy.Cov([1, 2, 3], dist)
array([[0., 0., 0.],
       [0., 0., 0.],
       [0., 0., 0.]])