restricted_gaussian_sampler.py 文件源码

def covariance_matrix(self):
        if self._debug:
            # return None
            ka = self.k_active
            if ka > 0:
                C = np.eye(self.N) + np.dot(self.V[:ka].T * self.S[:ka],
                                            self.V[:ka])
                C = (C * self.D).T * self.D
            else:
                C = np.diag(self.D**2)
            C *= self.sigma**2
        else:
            # Fake Covariance Matrix for Speed
            C = np.ones(1)
            self.B = np.ones(1)
        return C