From 127340d17d8711f53858d8a900475196d91e9fd2 Mon Sep 17 00:00:00 2001
From: Ricardo <acq11ra@sheffield.ac.uk>
Date: Mon, 16 Sep 2013 15:45:23 +0100
Subject: [PATCH] likelihoods are now Parameterized objects

---
 GPy/core/parameterized.py               |  5 ++++-
 GPy/likelihoods/ep.py                   |  2 ++
 GPy/likelihoods/gaussian.py             |  2 ++
 GPy/likelihoods/gaussian_mixed_noise.py |  2 ++
 GPy/likelihoods/likelihood.py           | 13 +++++--------
 5 files changed, 15 insertions(+), 9 deletions(-)

diff --git a/GPy/core/parameterized.py b/GPy/core/parameterized.py
index 015f35f5..15e11134 100644
--- a/GPy/core/parameterized.py
+++ b/GPy/core/parameterized.py
@@ -372,7 +372,10 @@ class Parameterized(object):
             for j in tie:
                 ties[j] = '(' + str(i) + ')'
 
-        values = ['%.4f' % float(v) for v in values]
+        if values.size == 1:
+            values = ['%.4f' %float(values)]
+        else:
+            values = ['%.4f' % float(v) for v in values]
         max_names = max([len(names[i]) for i in range(len(names))] + [len(header[0])])
         max_values = max([len(values[i]) for i in range(len(values))] + [len(header[1])])
         max_constraint = max([len(constraints[i]) for i in range(len(constraints))] + [len(header[2])])
diff --git a/GPy/likelihoods/ep.py b/GPy/likelihoods/ep.py
index c9f23839..9a816e65 100644
--- a/GPy/likelihoods/ep.py
+++ b/GPy/likelihoods/ep.py
@@ -37,6 +37,8 @@ class EP(likelihood):
         self.VVT_factor = self.V
         self.trYYT = 0.
 
+        super(EP, self).__init__()
+
     def restart(self):
         self.tau_tilde = np.zeros(self.N)
         self.v_tilde = np.zeros(self.N)
diff --git a/GPy/likelihoods/gaussian.py b/GPy/likelihoods/gaussian.py
index cdf54dd6..8f66d074 100644
--- a/GPy/likelihoods/gaussian.py
+++ b/GPy/likelihoods/gaussian.py
@@ -34,6 +34,8 @@ class Gaussian(likelihood):
         self._variance = np.asarray(variance) + 1.
         self._set_params(np.asarray(variance))
 
+        super(Gaussian, self).__init__()
+
     def set_data(self, data):
         self.data = data
         self.N, D = data.shape
diff --git a/GPy/likelihoods/gaussian_mixed_noise.py b/GPy/likelihoods/gaussian_mixed_noise.py
index e7df2584..4df01ec2 100644
--- a/GPy/likelihoods/gaussian_mixed_noise.py
+++ b/GPy/likelihoods/gaussian_mixed_noise.py
@@ -45,6 +45,8 @@ class Gaussian_Mixed_Noise(likelihood):
         self.set_data(data_list)
         self._set_params(np.asarray(noise_params))
 
+        super(Gaussian_Mixed_Noise, self).__init__()
+
     def set_data(self, data_list):
         self.data = np.vstack(data_list)
         self.N, D = self.data.shape
diff --git a/GPy/likelihoods/likelihood.py b/GPy/likelihoods/likelihood.py
index d073ba6e..cda62bfc 100644
--- a/GPy/likelihoods/likelihood.py
+++ b/GPy/likelihoods/likelihood.py
@@ -1,7 +1,8 @@
 import numpy as np
 import copy
+from ..core.parameterized import Parameterized
 
-class likelihood:
+class likelihood(Parameterized):
     """
     The atom for a likelihood class
 
@@ -16,10 +17,10 @@ class likelihood:
     self.is_heteroscedastic : enables significant computational savings in GP
     self.precision : a scalar or vector representation of the effective target precision
     self.YYT : (optional) = np.dot(self.Y, self.Y.T) enables computational savings for D>N
-    self.V : self.precision * self.Y 
+    self.V : self.precision * self.Y
     """
-    def __init__(self,data):
-        raise ValueError, "this class is not to be instantiated"
+    def __init__(self):
+        Parameterized.__init__(self)
 
     def _get_params(self):
         raise NotImplementedError
@@ -38,7 +39,3 @@ class likelihood:
 
     def predictive_values(self, mu, var):
         raise NotImplementedError
-
-    def copy(self):
-        """ Returns a (deep) copy of the current likelihood """
-        return copy.deepcopy(self)