bundles / scipy 1.17.1 / scipy / optimize / _slsqp_py / approx_jacobian

function

`scipy.optimize._slsqp_py:approx_jacobian`

source: /scipy/optimize/_slsqp_py.py :36

Signature

def approx_jacobian ( x , func , epsilon , * args )

Summary

Approximate the Jacobian matrix of a callable function.

Parameters

x : array_like: The state vector at which to compute the Jacobian matrix.
func : callable f(x,*args): The vector-valued function.
epsilon : float: The perturbation used to determine the partial derivatives.
args : sequence: Additional arguments passed to func.

Returns

: An array of dimensions ``(lenf, lenx)`` where ``lenf`` is the length
: of the outputs of `func`, and ``lenx`` is the number of elements in
: `x`.

Notes

The approximation is done using forward differences.

Aliases

scipy.optimize._slsqp_py.approx_jacobian