chaospy.Sens_t

chaospy.Sens_t(poly, dist, **kws)

Variance-based decomposition AKA Sobol’ indices

Total effect sensitivity index

Args:

poly (numpoly.ndpoly):

Polynomial to find first order Sobol indices on.

dist (Distribution):

The distributions of the input used in poly.

Returns:

(numpy.ndarray) :

First order sensitivity indices for each parameters in poly, with shape (len(dist),) + poly.shape.

Examples:

>>> q0, q1 = chaospy.variable(2)
>>> poly = chaospy.polynomial([1, q0, q1, 10*q0*q1-1])
>>> dist = chaospy.Iid(chaospy.Uniform(0, 1), 2)
>>> chaospy.Sens_t(poly, dist)
array([[0.        , 1.        , 0.        , 0.57142857],
       [0.        , 0.        , 1.        , 0.57142857]])