abstract_process.py 文件源码

def grad_input(self, x):
        """Compute the gradient of the mean function and the standard deviation
        function at the provided input.
        """
        # Compute the gradient of the mean function.
        d_kernel = self.kernel.grad_input(x, self.X)
        d_mean = d_kernel.T.dot(self.alpha)
        # Compute the gradient of the standard deviation function. It is
        # absolutely crucial to note that the predict method returns the
        # variance, not the standard deviation, of the prediction.
        sd = self.predict(x)[1]
        K_cross = self.kernel.cov(x, self.X)
        M = spla.cho_solve((self.L, True), K_cross.T).ravel()
        d_sd = -d_kernel.T.dot(M) / sd

        return d_mean, d_sd