args and kwargs now work fully for minimize_ipopt

[moorepants]

args & kwargs work with all user funcs in minimize_ipopt

- Passed in args and kwargs to all IpoptProblemWrapper.
- Added a unit test with args and kwargs for all funcs.

[moorepants]

Actually this does fail for passing args/kwargs into the hessian:

==================================================================================================== FAILURES =====================================================================================================
______________________________________________________________________ test_minimize_ipopt_jac_and_hessians_constraints_if_scipy_args_kwargs ______________________________________________________________________

    @pytest.mark.skipif("scipy" not in sys.modules,
                        reason="Test only valid if Scipy available.")
    def test_minimize_ipopt_jac_and_hessians_constraints_if_scipy_args_kwargs(
    ):
        """`minimize_ipopt` works with objective gradient and Hessian
           and constraint jacobians and Hessians."""
        from scipy.optimize import rosen, rosen_der, rosen_hess
    
        rosen2 = lambda x, a, b=1.0: rosen(x)*a*b
        rosen_der2 = lambda x, a, b=1.0: rosen_der(x)*a*b
        rosen_hess2 = lambda x, a, b=1.0: rosen_hess(x)*a*b
    
        x0 = [0.0, 0.0]
        constr = {
            "type": "ineq",
            "fun": lambda x, a, b=1.0: -x[0]**2 - x[1]**2 + 2*a*b,
            "jac": lambda x, a, b=1.0: np.array([-2 * x[0], -2 * x[1]])*a*b,
            "hess": lambda x, v, a, b=1.0: -2 * np.eye(2) * v[0]*a*b,
            "args": (1.0, ),
            "kwargs": {'b': 1.0},
        }
>       res = cyipopt.minimize_ipopt(rosen2, x0,
                                     jac=rosen_der2, hess=rosen_hess2,
                                     args=constr['args'],
                                     kwargs=constr['kwargs'],
                                     constraints=constr)

cyipopt/tests/unit/test_scipy_optional.py:121: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
cyipopt/scipy_interface.py:391: in minimize_ipopt
    x, info = nlp.solve(_x0)
cyipopt/cython/ipopt_wrapper.pyx:642: in ipopt_wrapper.Problem.solve
    raise self.__exception[0], self.__exception[1], self.__exception[2]
cyipopt/cython/ipopt_wrapper.pyx:895: in ipopt_wrapper.hessian_cb
    ret_val = self.__hessian(_x, _lambda, obj_factor)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <cyipopt.scipy_interface.IpoptProblemWrapper object at 0x7f66ba6ef220>, x = array([0., 0.]), lagrange = array([-1.]), obj_factor = 1.0

    def hessian(self, x, lagrange, obj_factor):
>       H = obj_factor * self.obj_hess(x)  # type: ignore
E       TypeError: <lambda>() missing 1 required positional argument: 'a'

cyipopt/scipy_interface.py:202: TypeError
============================================================================================= short test summary info =============================================================================================
FAILED cyipopt/tests/unit/test_scipy_optional.py::test_minimize_ipopt_jac_and_hessians_constraints_if_scipy_args_kwargs - TypeError: <lambda>() missing 1 required positional argument: 'a'
===================================================================================== 1 failed, 13 passed, 1 skipped in 0.92s =====================================================================================

[moorepants]

I'm sorry, I did this forgetting #176. This PR fixes what 176 had and more. There are more comprehensive tests there. We could merge this and then include the tests from #176.

[moorepants]

This doesn't break anything, so I'm going to merge.