On Mon, Jun 25, 2018 at 10:30 AM, Mark Alexander Mikofski
<mikofski@berkeley.edu> wrote:
>
> Would anyone disagree or would anyone be interested in a proposal to allow
> the derivative to be returned from the user supplied function as an optional
> second argument in gradient search method like Newton? EG
>
>>>> lambda x,a: (x**3-a, 3*x*"2)
>>>> newton(f, x0, fprime='f2', args=(a,))
>
> Some simple tests show that this may have a 2X speed in cases where the
> derivative expression requires the value of the original function call.

The `minimize` function does something like this for the `jac` keyword: "If jac is a Boolean and is True, fun is assumed to return the gradient along with the objective function.".

If something like this is desirable, then I suggest that the same minimize pattern is used.