def samples(self, gp, Y_metadata=None):
orig_shape = gp.shape<EOL>gp = gp.flatten()<EOL>dfs = np.ones_like(gp)*self.v<EOL>scales = np.ones_like(gp)*np.sqrt(self.sigma2)<EOL>student_t_samples = stats.t.rvs(dfs, loc=self.gp_link.transf(gp),<EOL>scale=scales)<EOL>return student_t_samples.reshape(orig_shape)<EOL>
Returns a set of samples of observations based on a given value of the latent variable.

:param gp: latent variable