From d5a8e5dd3aa0983c71cbd0cba31b5e4053a1e4e5 Mon Sep 17 00:00:00 2001
From: Max Zwiessele <ibinbei@gmail.com>
Date: Thu, 27 Mar 2014 13:08:54 +0000
Subject: [PATCH] right active dims when adding kernels

---
 GPy/kern/_src/add.py  |  4 +++-
 GPy/kern/_src/kern.py | 10 +++++++---
 2 files changed, 10 insertions(+), 4 deletions(-)

diff --git a/GPy/kern/_src/add.py b/GPy/kern/_src/add.py
index 57e611ed..ddc480de 100644
--- a/GPy/kern/_src/add.py
+++ b/GPy/kern/_src/add.py
@@ -176,5 +176,7 @@ class Add(CombinationKernel):
             for p in other_params:
                 other.remove_parameter(p)
             self.add_parameters(*other_params)
-        else: self.add_parameter(other)
+        else:
+            self.add_parameter(other)
+        self.input_dim, self.active_dims = self.get_input_dim_active_dims(self.parts)
         return self
\ No newline at end of file
diff --git a/GPy/kern/_src/kern.py b/GPy/kern/_src/kern.py
index 9d8d3f7b..5cd71215 100644
--- a/GPy/kern/_src/kern.py
+++ b/GPy/kern/_src/kern.py
@@ -208,9 +208,7 @@ class CombinationKernel(Kern):
         :param array-like|slice extra_dims: if needed extra dimensions for the combination kernel to work on
         """
         assert all([isinstance(k, Kern) for k in kernels])
-        active_dims = reduce(np.union1d, (np.r_[x.active_dims] for x in kernels), np.array([], dtype=int))
-        input_dim = active_dims.max()+1 + len(extra_dims)
-        active_dims = slice(active_dims.max()+1+len(extra_dims))
+        input_dim, active_dims = self.get_input_dim_active_dims(kernels, extra_dims)
         # initialize the kernel with the full input_dim
         super(CombinationKernel, self).__init__(input_dim, active_dims, name)
         self.extra_dims = extra_dims
@@ -220,6 +218,12 @@ class CombinationKernel(Kern):
     def parts(self):
         return self._parameters_
 
+    def get_input_dim_active_dims(self, kernels, extra_dims = None):
+        active_dims = reduce(np.union1d, (np.r_[x.active_dims] for x in kernels), np.array([], dtype=int))
+        input_dim = active_dims.max()+1 + (len(extra_dims) if extra_dims is not None else 0)
+        active_dims = slice(input_dim)
+        return input_dim, active_dims
+
     def input_sensitivity(self):
         in_sen = np.zeros((self.num_params, self.input_dim))
         for i, p in enumerate(self.parts):