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

Notes

rosen_hess_prod has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

Library	CPU	GPU
NumPy	✓	n/a
CuPy	n/a	✓
PyTorch	✓	✓
JAX	✗	✗
Dask	✓	✓

See Support for the array API standard for more information.

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.])