def cartesian_to_index(ranges, maxima=None):
    """
        Inverts tuples from a cartesian product to a numeric index ie. the index this 
        tuple would have in a cartesian product.

        Each column gets multiplied with a place value according to the preceding columns maxmimum
        and all columns are summed up.

        This function in the same direction as utils.cartesian, ie. the first column has the largest value.
    """
    if maxima is None:
        return reduce(lambda y,x: (x*y[1] + y[0],(np.max(x)+1)*y[1]), ranges[:,::-1].transpose(), (np.array([0]*ranges.shape[0]),1))[0]
    else:
        maxima_prod = np.concatenate([np.cumprod(np.array(maxima)[::-1])[1::-1],[1]])
        return np.sum(ranges * maxima_prod, 1)
Inverts tuples from a cartesian product to a numeric index ie. the index this 
        tuple would have in a cartesian product.

        Each column gets multiplied with a place value according to the preceding columns maxmimum
        and all columns are summed up.

        This function in the same direction as utils.cartesian, ie. the first column has the largest value.