grad Subroutine

    subroutine grad(me,x,g)
        !! compute the gradient of the function (Jacobian):
        implicit none
        class(nlesolver_type),intent(inout) :: me
        real(wp),dimension(:),intent(in)    :: x
        real(wp),dimension(:,:),intent(out) :: g

        f_evals = f_evals + 2   ! to approximate forward diff derivatives

        g(1,1) = 2.0_wp * x(1)  !df(1)/dx
        g(2,1) = 0.0_wp         !df(2)/dx

        g(1,2) = 1.0_wp         !df(1)/dy
        g(2,2) = 1.0_wp         !df(2)/dy

    end subroutine grad