kernels are now consistent with pep8 and common reason

GPy/kern/parts/white.py

@@ -0,0 +1,84 @@
+# Copyright (c) 2012, GPy authors (see AUTHORS.txt).
+# Licensed under the BSD 3-clause license (see LICENSE.txt)
+
+from kernpart import Kernpart
+import numpy as np
+
+class White(Kernpart):
+    """
+    White noise kernel.
+
+    :param input_dim: the number of input dimensions
+    :type input_dim: int
+    :param variance:
+    :type variance: float
+    """
+    def __init__(self,input_dim,variance=1.):
+        self.input_dim = input_dim
+        self.num_params = 1
+        self.name = 'white'
+        self._set_params(np.array([variance]).flatten())
+        self._psi1 = 0 # TODO: more elegance here
+        
+    def _get_params(self):
+        return self.variance
+
+    def _set_params(self,x):
+        assert x.shape==(1,)
+        self.variance = x
+
+    def _get_param_names(self):
+        return ['variance']
+
+    def K(self,X,X2,target):
+        if X2 is None:
+            target += np.eye(X.shape[0])*self.variance
+
+    def Kdiag(self,X,target):
+        target += self.variance
+
+    def dK_dtheta(self,dL_dK,X,X2,target):
+        if X2 is None:
+            target += np.trace(dL_dK)
+
+    def dKdiag_dtheta(self,dL_dKdiag,X,target):
+        target += np.sum(dL_dKdiag)
+
+    def dK_dX(self,dL_dK,X,X2,target):
+        pass
+
+    def dKdiag_dX(self,dL_dKdiag,X,target):
+        pass
+
+    def psi0(self,Z,mu,S,target):
+        target += self.variance
+
+    def dpsi0_dtheta(self,dL_dpsi0,Z,mu,S,target):
+        target += dL_dpsi0.sum()
+
+    def dpsi0_dmuS(self,dL_dpsi0,Z,mu,S,target_mu,target_S):
+        pass
+
+    def psi1(self,Z,mu,S,target):
+        pass
+
+    def dpsi1_dtheta(self,dL_dpsi1,Z,mu,S,target):
+        pass
+
+    def dpsi1_dZ(self,dL_dpsi1,Z,mu,S,target):
+        pass
+
+    def dpsi1_dmuS(self,dL_dpsi1,Z,mu,S,target_mu,target_S):
+        pass
+
+    def psi2(self,Z,mu,S,target):
+        pass
+
+    def dpsi2_dZ(self,dL_dpsi2,Z,mu,S,target):
+        pass
+
+    def dpsi2_dtheta(self,dL_dpsi2,Z,mu,S,target):
+        pass
+
+    def dpsi2_dmuS(self,dL_dpsi2,Z,mu,S,target_mu,target_S):
+        pass