perlin.py 文件源码

def _generate_gradient(self):
        # Generate a random unit vector at each grid point -- this is the
        # "gradient" vector, in that the grid tile slopes towards it

        # 1 dimension is special, since the only unit vector is trivial;
        # instead, use a slope between -1 and 1
        if self.dimension == 1:
            return (random.uniform(-1, 1),)

        # Generate a random point on the surface of the unit n-hypersphere;
        # this is the same as a random unit vector in n dimensions.  Thanks
        # to: http://mathworld.wolfram.com/SpherePointPicking.html
        # Pick n normal random variables with stddev 1
        random_point = [random.gauss(0, 1) for _ in range(self.dimension)]
        # Then scale the result to a unit vector
        scale = sum(n * n for n in random_point) ** -0.5
        return tuple(coord * scale for coord in random_point)