Skip to main content
`Ctrl`+`K`
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`

  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.])