@@ -476,7 +476,7 @@ class Learner2D(BaseLearner):

             points, values = self._data_in_bounds()

             return interpolate.LinearNDInterpolator(points, values)

-    def _interpolate_combined(self):

+    def _interpolator_combined(self):

         """A `scipy.interpolate.LinearNDInterpolator` instance

         containing the learner's data *and* interpolated data of

         the `pending_points`."""

@@ -513,7 +513,7 @@ class Learner2D(BaseLearner):

             raise ValueError("too few points...")

         # Interpolate

-        ip = self._interpolate_combined()

+        ip = self._interpolator_combined()

         losses = self.loss_per_triangle(ip)

@@ -581,7 +581,7 @@ class Learner2D(BaseLearner):

     def loss(self, real=True):

         if not self.bounds_are_done:

             return np.inf

-        ip = self.interpolator(scaled=True) if real else self._interpolate_combined()

+        ip = self.interpolator(scaled=True) if real else self._interpolator_combined()

         losses = self.loss_per_triangle(ip)

         return losses.max()