rosen_der(x)

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.

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

See Also

rosen

rosen_hess

rosen_hess_prod

Examples

>>> from scipy.optimize import rosen_der
... X = 0.1 * np.arange(9)
... rosen_der(X)
array([ -2. ,  10.6,  15.6,  13.4,   6.4,  -3. , -12.4, -19.4,  62. ])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.optimize._optimize.rosen scipy.optimize._optimize.rosen_hess scipy.optimize._optimize.rosen_der scipy.optimize._minimize.minimize scipy.optimize._optimize.rosen_hess_prod

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