From 0f6004034e0a9fb17c4f5311a36038cd6249eb37 Mon Sep 17 00:00:00 2001
From: Zhenwen Dai <z.dai@shef.ac.uk>
Date: Mon, 3 Mar 2014 17:56:47 +0000
Subject: [PATCH] [SSGPLVM] support non-ARD rbf

---
 GPy/kern/_src/rbf.py                         | 11 ++++++++---
 GPy/kern/_src/rbf_psi_comp/ssrbf_psi_comp.py | 14 ++++----------
 2 files changed, 12 insertions(+), 13 deletions(-)

diff --git a/GPy/kern/_src/rbf.py b/GPy/kern/_src/rbf.py
index 007bac77..498ab0ac 100644
--- a/GPy/kern/_src/rbf.py
+++ b/GPy/kern/_src/rbf.py
@@ -62,13 +62,18 @@ class RBF(Stationary):
     
             #from psi1
             self.variance.gradient += np.sum(dL_dpsi1 * _dpsi1_dvariance)
-            self.lengthscale.gradient = (dL_dpsi1[:,:,None]*_dpsi1_dlengthscale).reshape(-1,self.input_dim).sum(axis=0) 
+            if self.ARD:
+                self.lengthscale.gradient = (dL_dpsi1[:,:,None]*_dpsi1_dlengthscale).reshape(-1,self.input_dim).sum(axis=0)
+            else:
+                self.lengthscale.gradient = (dL_dpsi1[:,:,None]*_dpsi1_dlengthscale).sum()  
         
     
             #from psi2
             self.variance.gradient += (dL_dpsi2 * _dpsi2_dvariance).sum()
-            self.lengthscale.gradient += (dL_dpsi2[:,:,:,None] * _dpsi2_dlengthscale).reshape(-1,self.input_dim).sum(axis=0)        
-            return
+            if self.ARD:
+                self.lengthscale.gradient += (dL_dpsi2[:,:,:,None] * _dpsi2_dlengthscale).reshape(-1,self.input_dim).sum(axis=0)
+            else:
+                self.lengthscale.gradient += (dL_dpsi2[:,:,:,None] * _dpsi2_dlengthscale).sum()
         
         elif isinstance(variational_posterior, variational.NormalPosterior):
         
diff --git a/GPy/kern/_src/rbf_psi_comp/ssrbf_psi_comp.py b/GPy/kern/_src/rbf_psi_comp/ssrbf_psi_comp.py
index f3d5ee6b..13b3f65f 100644
--- a/GPy/kern/_src/rbf_psi_comp/ssrbf_psi_comp.py
+++ b/GPy/kern/_src/rbf_psi_comp/ssrbf_psi_comp.py
@@ -6,22 +6,15 @@ The package for the psi statistics computation
 """
 
 import numpy as np
+from GPy.util.caching import Cache_this
 
+@Cache_this(limit=1)
 def _Z_distances(Z):
     Zhat = 0.5 * (Z[:, None, :] + Z[None, :, :]) # M,M,Q
     Zdist = 0.5 * (Z[:, None, :] - Z[None, :, :]) # M,M,Q
     return Zhat, Zdist
 
-# def _psi1computations(self, Z, vp):
-#     mu, S = vp.mean, vp.variance
-#     l2 = lengthscale **2
-#     denom = S[:, None, :] / l2 + 1. # N,1,Q
-#     dist = Z[None, :, :] - mu[:, None, :] # N,M,Q
-#     dist_sq = np.square(dist) / l2 / denom # N,M,Q
-#     exponent = -0.5 * np.sum(dist_sq + np.log(denom), -1)#N,M
-#     psi1 = self.variance * np.exp(exponent) # N,M
-#     return denom, dist, dist_sq, psi1
-
+@Cache_this(limit=1)
 def _psi1computations(variance, lengthscale, Z, mu, S, gamma):
     """
     Z - MxQ
@@ -64,6 +57,7 @@ def _psi1computations(variance, lengthscale, Z, mu, S, gamma):
 
     return _psi1, _dpsi1_dvariance, _dpsi1_dgamma, _dpsi1_dmu, _dpsi1_dS, _dpsi1_dZ, _dpsi1_dlengthscale
 
+@Cache_this(limit=1)
 def _psi2computations(variance, lengthscale, Z, mu, S, gamma):
     """
     Z - MxQ