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bundles / scipy 1.17.1 / scipy / optimize / _optimize / rosen_der

function

scipy.optimize._optimize:rosen_der

source: /scipy/optimize/_optimize.py :391

Signature

def   rosen_der ( x )

Summary

The derivative (i.e. gradient) of the Rosenbrock function.

Parameters

x : array_like

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

Returns

rosen_der : (N,) ndarray

The gradient of the Rosenbrock function at x.

Notes

Array API Standard Support

rosen_der 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 dev-arrayapi for more information.

Examples

import numpy as np
from scipy.optimize import rosen_der
X = 0.1 * np.arange(9)
rosen_der(X)
✓

See also

rosen
rosen_hess
rosen_hess_prod

Aliases

  • scipy.optimize.rosen_der

Referenced by

This package