gp.py 文件源码

def log_likelihood(self):
        """
        GP Marginal likelihood

        Notes
        -----
        This is called by the samplers when fitting the hyperparameters.
        """
        cov   = self.kernel.cov(self.observed_inputs)
        chol  = spla.cholesky(cov, lower=True)
        solve = spla.cho_solve((chol, True), self.observed_values - self.mean.value)

        # Uses the identity that log det A = log prod diag chol A = sum log diag chol A
        return -np.sum(np.log(np.diag(chol)))-0.5*np.dot(self.observed_values - self.mean.value, solve)