def predict_wishart_embedding(self, Xnew, kern=None, mean=True, covariance=True):
        if kern is None:
            kern = self.kern

        mu_jac, var_jac = self.predict_jacobian(Xnew, kern, full_cov=False)
        mumuT = np.einsum('iqd,ipd->iqp', mu_jac, mu_jac)
        Sigma = np.zeros(mumuT.shape)
        if var_jac.ndim == 3:
            Sigma[(slice(None), )+np.diag_indices(Xnew.shape[1], 2)] = var_jac.sum(-1)
        else:
            Sigma[(slice(None), )+np.diag_indices(Xnew.shape[1], 2)] = self.output_dim*var_jac
        G = 0.
        if mean:
            G += mumuT
        if covariance:
            G += Sigma
        return G
Determines if a file entry for a path specification exists.
dataset/ETHPy150Open SheffieldML/GPy/GPy/core/gp.py/GP.predict_wishart_embedding--crossover with--dataset/ETHPy150Open log2timeline/dfvfs/dfvfs/vfs/file_system.py/FileSystem.FileEntryExistsByPathSpec