scipy.optimize.

rosen_hess#

scipy.optimize.rosen_hess(x)[source]#

The Hessian matrix of the Rosenbrock function.

Parameters:

xarray_like: 1-D array of points at which the Hessian matrix is to be computed.

Returns:

rosen_hessndarray: The Hessian matrix of the Rosenbrock function at x.

See also

rosen, rosen_der, rosen_hess_prod

Notes

rosen_hess 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
>>> X = 0.1 * np.arange(4)
>>> rosen_hess(X)
array([[-38.,   0.,   0.,   0.],
       [  0., 134., -40.,   0.],
       [  0., -40., 130., -80.],
       [  0.,   0., -80., 200.]])