(self, noise)
return k
Fold noise into k.
        Args:
            noise: A T x Du noise vector with mean 0 and variance 1.
        Returns:
            k: A T x dU bias vector.
Fold noise into k.
        Args:
            noise: A T x Du noise vector with mean 0 and variance 1.
        Returns:
            k: A T x dU bias vector.
Fold noise into k . Args : noise : A T x Du noise vector with mean 0 and variance 1 . Returns : k : A T x dU bias vector .
def fold_k(self, noise):
        """
        Fold noise into k.
        Args:
            noise: A T x Du noise vector with mean 0 and variance 1.
        Returns:
            k: A T x dU bias vector.
        """
        k = np.zeros_like(self.k)
        for i in range(self.T):
            scaled_noise = self.chol_pol_covar[i].T.dot(noise[i])
            k[i] = scaled_noise + self.k[i]
        return k
def fold_k ( self , noise ) : k = np . zeros_like ( self . k ) for i in range ( self . T ) : scaled_noise = self . chol_pol_covar [ i ] . T . dot ( noise [ i ] ) k [ i ] = scaled_noise + self . k [ i ] return k