test all the different loss functions in each test

Improve the tests

• test all the different loss functions in each test
• add Learner1D._recompute_losses_factor to remove xfail from two tests
• speed up the tests

adaptive/learner/learner1D.py

@@ -228,6 +228,11 @@ class Learner1D(BaseLearner):
         self.losses = {}
         self.losses_combined = {}
 
+        # When the scale changes by a factor 2, the losses are
+        # recomputed. This is tunable such that we can test
+        # the learners behavior in the tests.
+        self._recompute_losses_factor = 2
+
         self.data = {}
         self.pending_points = set()
 
@@ -447,7 +452,7 @@ class Learner1D(BaseLearner):
         self._update_losses(x, real=True)
 
         # If the scale has increased enough, recompute all losses.
-        if self._scale[1] > 2 * self._oldscale[1]:
+        if self._scale[1] > self._recompute_losses_factor * self._oldscale[1]:
 
             for interval in self.losses:
                 self._update_interpolated_loss_in_interval(*interval)