@@ -127,7 +127,7 @@ class AverageLearner(BaseLearner):

         self.sum_f = 0

         self.sum_f_sq = 0

-    def choose_points(self, n=10, add_data=True):

+    def choose_points(self, n, add_data=True):

         points = list(range(self.n_requested, self.n_requested + n))

         loss_improvements = [None] * n

         if add_data:

@@ -313,7 +313,7 @@ class Learner1D(BaseLearner):

                                     for x in self.losses_combined}

             self._oldscale = self._scale

-    def choose_points(self, n=10, add_data=True):

+    def choose_points(self, n, add_data=True):

         """Return n points that are expected to maximally reduce the loss."""

         # Find out how to divide the n points over the intervals

         # by finding  positive integer n_i that minimize max(L_i / n_i) subject