resolve 105

adaptive/learner/learnerND.py

@@ -222,6 +222,7 @@ class LearnerND(BaseLearner):
 
         try:
             self._tri = Triangulation(self.points)
+            self.update_losses(set(), self._tri.simplices)
             return self._tri
         except ValueError:
             # A ValueError is raised if we do not have enough points or
@@ -229,8 +230,6 @@ class LearnerND(BaseLearner):
             # a valid triangulation
             return None
 
-        # XXX: also compute losses of initial simplex
-
     @property
     def values(self):
         return np.array(list(self.data.values()), dtype=float)
@@ -359,8 +358,8 @@ class LearnerND(BaseLearner):
         # Could not find a simplex, this code should never be reached
         assert self.tri is not None
         raise AssertionError(
-            "Could not find a simplex to. Yet there should always be a simplex "
-            "available if LearnerND.tri() is not None"
+            "Could not find a simplex to subdivide. Yet there should always be" 
+            "a simplex available if LearnerND.tri() is not None."
         )
 
     def _ask_best_point(self):