From c29c82684780ab64c170530f387feb3d59e7b473 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Mon, 16 Dec 2013 15:11:59 +0000 Subject: [PATCH 1/3] minor --- GPy/core/gp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 83705e89..f7ac0f12 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -3,7 +3,7 @@ import numpy as np from gp_base import GPBase -from ..util.linalg import dtrtrs +from ..util.linalg import dtrtrs, tdot from ..inference.latent_function_inference import exact_gaussian_inference, expectation_propagation from .. import likelihoods From 6996700d091bc54c6c472bf0af5d6ee6af0d6d98 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Mon, 16 Dec 2013 15:13:40 +0000 Subject: [PATCH 2/3] typo --- GPy/core/parameterization/variational.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/core/parameterization/variational.py b/GPy/core/parameterization/variational.py index e7119445..25718fbf 100644 --- a/GPy/core/parameterization/variational.py +++ b/GPy/core/parameterization/variational.py @@ -49,7 +49,7 @@ class Normal(Parameterized): elif isinstance(ax, (tuple, list)): a = ax[i] else: - raise ValueError("Need one ax per latent dimnesion input_dim") + raise ValueError("Need one ax per latent dimension input_dim") a.plot(means, c='k', alpha=.3) plots.extend(a.plot(x, means.T[i], c=colors.next(), label=r"$\mathbf{{X_{{{}}}}}$".format(i))) a.fill_between(x, From c7311b7d536e7a7342e551ae35c9415c64f34974 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Mon, 16 Dec 2013 15:14:15 +0000 Subject: [PATCH 3/3] IMPORTS --- GPy/inference/latent_function_inference/posterior.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/inference/latent_function_inference/posterior.py b/GPy/inference/latent_function_inference/posterior.py index 4dfc334d..56c0f388 100644 --- a/GPy/inference/latent_function_inference/posterior.py +++ b/GPy/inference/latent_function_inference/posterior.py @@ -2,7 +2,7 @@ # Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np -from ...util.linalg import pdinv, dpotrs +from ...util.linalg import pdinv, dpotrs, tdot class Posterior(object): """