scipy.optimize.fsolve Jacobian argument incomplete in the documentation

[gautamdivgi]

This seems to be a minor documentation bug & an easy fix

The scipy.optimize.fsolve accepts a jacobian in the fprime argument

scipy.optimize.fsolve(func, x0, args=(), fprime=None, full_output=0, col_deriv=0, xtol=1.49012e-08, maxfev=0, band=None, epsfcn=None, factor=100, diag=None)

fprime is defined as

fprime : callable(x), optional A function to compute the Jacobian offuncwith derivatives across the rows. By default, the Jacobian will be estimated.

I believe it should really be

fprime : callable(x, *args), optional A function to compute the Jacobian offuncwith derivatives across the rows. By default, the Jacobian will be estimated.

The args from fsolve are passed down to the jacobian. This can be confirmed from the code in scipy/optimize/minpack.py, _root_hybr (code snippet below - the last line is where there is check to see if the jacobian accepts x0 & args)

` Dfun = jac

if Dfun is None:

    if band is None:

        ml, mu = -10, -10

    else:

        ml, mu = band[:2]

    if maxfev == 0:

        maxfev = 200 * (n + 1)

    retval = _minpack._hybrd(func, x0, args, 1, xtol, maxfev,
                             ml, mu, epsfcn, factor, diag)

else:

    _check_func('fsolve', 'fprime', Dfun, x0, args, n, (n, n))

`