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scipy.optimize.

# rosen_hess

scipy.optimize.rosen_hess(x)

  The Hessian matrix of the Rosenbrock function.

  Parameters:
    x array_like

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

  Returns:
    rosen_hess ndarray

      The Hessian matrix of the Rosenbrock function at x.

  See also

  `rosen`, `rosen_der`, `rosen_hess_prod`

  Notes

  Array API Standard Support

  `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 | ✅ | n/a

  > 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.]])