def stratint(f, G, y0, tspan):
    """ Numerically integrate Stratonovich equation dy = f(y,t)dt + G(y,t).dW

    where y is the d-dimensional state vector, f is a vector-valued function,
    G is an d x m matrix-valued function giving the noise coefficients and
    dW(t) = (dW_1, dW_2, ... dW_m) is a vector of independent Wiener increments

    Args:
      f: callable(y,t) returning a numpy array of shape (d,)
         Vector-valued function to define the deterministic part of the system
      G: callable(y,t) returning a numpy array of shape (d,m)
         Matrix-valued function to define the noise coefficients of the system
      y0: array of shape (d,) giving the initial state vector y(t==0)
      tspan (array): The sequence of time points for which to solve for y.
        These must be equally spaced, e.g. np.arange(0,10,0.005)
        tspan[0] is the intial time corresponding to the initial state y0.

    Returns:
      y: array, with shape (len(tspan), len(y0))
         With the initial value y0 in the first row

    Raises:
      SDEValueError
    """
    # In future versions we can automatically choose here the most suitable
    # Stratonovich algorithm based on properties of the system and noise.
    (d, m, f, G, y0, tspan, __, __) = _check_args(f, G, y0, tspan, None, None)
    chosenAlgorithm = stratSRS2
    return chosenAlgorithm(f, G, y0, tspan)