scipy.optimize.rosen_hess_prod#

scipy.optimize.rosen_hess_prod(x, p)[source]#

Product of the Hessian matrix of the Rosenbrock function with a vector.

Parameters:

xarray_like: 1-D array of points at which the Hessian matrix is to be computed.
parray_like: 1-D array, the vector to be multiplied by the Hessian matrix.

Returns:

rosen_hess_prodndarray: The Hessian matrix of the Rosenbrock function at x multiplied by the vector p.

See also

rosen, rosen_der, rosen_hess

Examples

>>> import numpy as np
>>> from scipy.optimize import rosen_hess_prod
>>> X = 0.1 * np.arange(9)
>>> p = 0.5 * np.arange(9)
>>> rosen_hess_prod(X, p)
array([  -0.,   27.,  -10.,  -95., -192., -265., -278., -195., -180.])