student_t.py 文件源码

def _sample_n(self, n, seed=None):
    # We use 2 uniform random floats to generate polar random variates.
    # http://dl.acm.org/citation.cfm?id=179631
    # Theorem 2. Let G, H be iid variates, uniformly distributed on [0,1].
    # Let theta = 2*pi*H, let R = sqrt(df*(G^(-2/df) - 1)) for df > 0.
    # Let X = R*cos(theta), and let Y = R*sin(theta).
    # Then X ~ t_df and Y ~ t_df.
    # The variates X and Y are not independent.
    shape = array_ops.concat(0, ([2, n], self.batch_shape()))
    uniform = random_ops.random_uniform(shape=shape,
                                        dtype=self.dtype,
                                        seed=seed)
    samples_g, samples_h = array_ops.unpack(uniform, num=2)
    theta = (2. * math.pi) * samples_h
    r = math_ops.sqrt(self.df *
                      (math_ops.pow(samples_g, -2 / self.df) - 1))
    samples = r * math_ops.cos(theta)
    return samples * self.sigma + self.mu