switch input_sensitivity function to model

GPy/core/model.py

@@ -147,6 +147,12 @@ class Model(Parameterized):
         """
         raise DeprecationWarning, 'parameters now have default constraints'
 
+    def input_sensitivity(self):
+        """
+        Returns the sensitivity for each dimension of this kernel.
+        """
+        return self.kern.input_sensitivity()
+
     def objective_function(self, x):
         """
         The objective function passed to the optimizer. It combines

GPy/kern/_src/kern.py

@@ -89,7 +89,7 @@ class Kern(Parameterized):
         """
         Returns the sensitivity for each dimension of this kernel.
         """
-        return np.zeros(self.input_dim)
+        return self.kern.input_sensitivity()
 
     def __add__(self, other):
         """ Overloading of the '+' operator. for more control, see self.add """

GPy/models/ss_gplvm.py

@@ -66,6 +66,12 @@ class SSGPLVM(SparseGP):
         # update for the KL divergence
         self.variational_prior.update_gradients_KL(self.X)
 
+    def input_sensitivity(self):
+        if self.kern.ARD:
+            return self.kern.input_sensitivity()
+        else:
+            return self.variational_prior.pi
+
     def plot_latent(self, plot_inducing=True, *args, **kwargs):
         import sys
         assert "matplotlib" in sys.modules, "matplotlib package has not been imported."

GPy/plotting/matplot_dep/dim_reduction_plots.py

@@ -20,7 +20,7 @@ def most_significant_input_dimensions(model, which_indices):
             input_1, input_2 = 0, 1
         else:
             try:
-                input_1, input_2 = np.argsort(model.kern.input_sensitivity())[::-1][:2]
+                input_1, input_2 = np.argsort(model.input_sensitivity())[::-1][:2]
             except:
                 raise ValueError, "cannot automatically determine which dimensions to plot, please pass 'which_indices'"
     else: