Returns a set of samples of observations based on a given value of the latent variable.

        :param gp: latent variable

def samples(self, gp, Y_metadata=None):
        """
        Returns a set of samples of observations based on a given value of the latent variable.

        :param gp: latent variable
        """
        orig_shape = gp.shape
        gp = gp.flatten()
        #FIXME: Very slow as we are computing a new random variable per input!
        #Can't get it to sample all at the same time
        #student_t_samples = np.array([stats.t.rvs(self.v, self.gp_link.transf(gpj),scale=np.sqrt(self.sigma2), size=1) for gpj in gp])
        dfs = np.ones_like(gp)*self.v
        scales = np.ones_like(gp)*np.sqrt(self.sigma2)
        student_t_samples = stats.t.rvs(dfs, loc=self.gp_link.transf(gp),
                                        scale=scales)
        return student_t_samples.reshape(orig_shape)