Updating SquaredGaussianHellinger for catch when negative, and checki…

…ng attribute to use state.mean

stonesoup/measures.py

@@ -253,18 +253,28 @@ def __call__(self, state1, state2):
 
 
         """
+        if hasattr(state1, 'mean'):
+            state_vector1 = state1.mean
+        else:
+            state_vector1 = state1.state_vector
+
+        if hasattr(state2, 'mean'):
+            state_vector2 = state2.mean
+        else:
+            state_vector2 = state2.state_vector
+
         if self.mapping is not None:
-            mu1 = state1.state_vector[self.mapping, :]
-            mu2 = state2.state_vector[self.mapping2, :]
+            mu1 = state_vector1[self.mapping, :]
+            mu2 = state_vector2[self.mapping2, :]
 
             # extract the mapped covariance data
             rows = np.array(self.mapping, dtype=np.intp)
             columns = np.array(self.mapping, dtype=np.intp)
             sigma1 = state1.covar[rows[:, np.newaxis], columns]
             sigma2 = state2.covar[rows[:, np.newaxis], columns]
         else:
-            mu1 = state1.state_vector
-            mu2 = state2.state_vector
+            mu1 = state_vector1
+            mu2 = state_vector2
             sigma1 = state1.covar
             sigma2 = state2.covar
 
@@ -276,6 +286,12 @@ def __call__(self, state1, state2):
         denominator = np.linalg.det(sigma1_plus_sigma2/2)
         squared_hellinger = 1 - np.sqrt(numerator/denominator)*np.exp(epsilon)
         squared_hellinger = squared_hellinger.item()
+
+        if -1e-10 < squared_hellinger < 0.0:
+            squared_hellinger = 0.0
+        elif squared_hellinger < 0.0:  # pragma: no cover
+            raise ValueError("Measure shouldn't be less than 0")  # this should be impossible
+
         return squared_hellinger