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scipy.optimize.

# rosen_hess_prod

scipy.optimize.rosen_hess_prod(x, p)

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

  Parameters:
    x array_like

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

    p array_like

      1-D array, the vector to be multiplied by the Hessian matrix.

  Returns:
    rosen_hess_prod ndarray

      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 | ✅ | n/a

  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.])