Iteratively apply the operator `T` to `v`. Modify `v` in-place.
        Iteration is performed for at most a number `max_iter` of times.
        If `tol` is specified, it is terminated once the distance of
        `T(v)` from `v` (in the max norm) is less than `tol`.

        Parameters
        ----------
        T : callable
            Operator that acts on `v`.

        v : ndarray
            Object on which `T` acts. Modified in-place.

        max_iter : scalar(int)
            Maximum number of iterations.

        tol : scalar(float), optional(default=None)
            Error tolerance.

        args, kwargs :
            Other arguments and keyword arguments that are passed
            directly to the function T each time it is called.

        Returns
        -------
        num_iter : scalar(int)
            Number of iterations performed.

def operator_iteration(self, T, v, max_iter, tol=None, *args, **kwargs):
        """
        Iteratively apply the operator `T` to `v`. Modify `v` in-place.
        Iteration is performed for at most a number `max_iter` of times.
        If `tol` is specified, it is terminated once the distance of
        `T(v)` from `v` (in the max norm) is less than `tol`.

        Parameters
        ----------
        T : callable
            Operator that acts on `v`.

        v : ndarray
            Object on which `T` acts. Modified in-place.

        max_iter : scalar(int)
            Maximum number of iterations.

        tol : scalar(float), optional(default=None)
            Error tolerance.

        args, kwargs :
            Other arguments and keyword arguments that are passed
            directly to the function T each time it is called.

        Returns
        -------
        num_iter : scalar(int)
            Number of iterations performed.

        """
        # May be replaced with quantecon.compute_fixed_point
        if max_iter <= 0:
            return v, 0

        for i in range(max_iter):
            new_v = T(v, *args, **kwargs)
            if tol is not None and np.abs(new_v - v).max() < tol:
                v[:] = new_v
                break
            v[:] = new_v

        num_iter = i + 1

        return num_iter