diff --git a/GPy/kern/parts/hierarchical.py b/GPy/kern/parts/hierarchical.py
new file mode 100644
index 00000000..98f4a183
--- /dev/null
+++ b/GPy/kern/parts/hierarchical.py
@@ -0,0 +1,75 @@
+# Copyright (c) 2012, James Hesnsman
+# Licensed under the BSD 3-clause license (see LICENSE.txt)
+
+from kernpart import Kernpart
+import numpy as np
+from independent_outputs import index_to_slices
+
+class hierarchical(Kernpart):
+    """
+    A kernel part which can reopresent a hierarchy of indepencnce: a gerenalisation of independent_outputs
+
+    """
+    def __init__(self,parts):
+        self.levels = len(parts)
+        self.input_dim = parts[0].input_dim + 1
+        self.num_params = np.sum([k.num_params for k in parts])
+        self.name = 'hierarchy'
+        self.parts = parts
+
+        self.param_starts = np.hstack((0,np.cumsum([k.num_params for k in self.parts[:-1]])))
+        self.param_stops = np.cumsum([k.num_params for k in self.parts])
+
+    def _get_params(self):
+        return np.hstack([k._get_params() for k in self.parts])
+
+    def _set_params(self,x):
+        [k._set_params(x[start:stop]) for start, stop in zip(self.param_starts, self.param_stops)]
+
+    def _get_param_names(self):
+        return self.k._get_param_names()
+
+    def _sort_slices(self,X,X2):
+        slices = [index_to_slices(x) for x in X[-self.levels:].T]
+        X = X[:-self.levels]
+        if X2 is None:
+            slices2 = slices
+            X2 = X
+        else:
+            slices2 = [index_to_slices(x) for x in X2[-self.levels:].T]
+            X2 = X2[:-self.levels]
+        return X, X2, slices, slices2
+
+    def K(self,X,X2,target):
+        X, X2, slices, slices2 = self._sort_slices(X,X2)
+
+        [[[k.K(X[s],X2[s2],target[s,s2]) for s in slices_i] for s2 in slices_j] for k,slices_i,slices_j in zip(self.parts,slices,slices2)]
+
+    def Kdiag(self,X,target):
+        raise NotImplementedError
+        #X,slices = X[:,:-1],index_to_slices(X[:,-1])
+        #[[self.k.Kdiag(X[s],target[s]) for s in slices_i] for slices_i in slices]
+
+    def dK_dtheta(self,dL_dK,X,X2,target):
+        [[[k.dK_dtheta(dL_dK[s,s2],X[s],X2[s2],target[p_start:p_stop]) for s in slices_i] for s2 in slices_j] for k,slices_i,slices_j, p_start, p_stop in zip(self.parts, slices, slices2, self.param_starts, self.param_stops)]
+
+
+    def dK_dX(self,dL_dK,X,X2,target):
+        raise NotImplementedError
+        #X,slices = X[:,:-1],index_to_slices(X[:,-1])
+        #if X2 is None:
+            #X2,slices2 = X,slices
+        #else:
+            #X2,slices2 = X2[:,:-1],index_to_slices(X2[:,-1])
+        #[[[self.k.dK_dX(dL_dK[s,s2],X[s],X2[s2],target[s,:-1]) for s in slices_i] for s2 in slices_j] for slices_i,slices_j in zip(slices,slices2)]
+#
+    def dKdiag_dX(self,dL_dKdiag,X,target):
+        raise NotImplementedError
+        #X,slices = X[:,:-1],index_to_slices(X[:,-1])
+        #[[self.k.dKdiag_dX(dL_dKdiag[s],X[s],target[s,:-1]) for s in slices_i] for slices_i in slices]
+
+
+    def dKdiag_dtheta(self,dL_dKdiag,X,target):
+        raise NotImplementedError
+        #X,slices = X[:,:-1],index_to_slices(X[:,-1])
+        #[[self.k.dKdiag_dX(dL_dKdiag[s],X[s],target) for s in slices_i] for slices_i in slices]