simplifications

adaptive/learner/learner1D.py

@@ -121,11 +121,13 @@ def _get_neighbors_from_list(xs):
     return sortedcontainers.SortedDict(neighbors)
 
 
-def _get_interval(x, neighbors, nn_neighbors):
+def _get_intervals(x, neighbors, nn_neighbors):
     n = nn_neighbors
     index = neighbors.bisect_left(x)
-    return [neighbors.iloc[i] for i in range(index - n - 1, index + 2 + n)
-            if 0 <= i < len(neighbors)]
+    points = [neighbors.iloc[i] for i in range(index - n - 1, index + 2 + n)
+              if 0 <= i < len(neighbors)]
+    intervals = zip(points, points[1:])
+    return list(intervals)
 
 
 class Learner1D(BaseLearner):
@@ -243,9 +245,8 @@ class Learner1D(BaseLearner):
             return 0
 
         # we need to compute the loss for this interval
-        interval = (x_left, x_right)
         return self.loss_per_interval(
-            interval, self._scale, self.data, self.neighbors)
+            (x_left, x_right), self._scale, self.data, self.neighbors)
 
 
     def _update_interpolated_loss_in_interval(self, x_left, x_right):
@@ -281,8 +282,7 @@ class Learner1D(BaseLearner):
             # (x_left, x), (x, x_right) and the nn_neighbors nearest
             # neighboring intervals. Since the addition of the
             # point 'x' could change their loss.
-            points = _get_interval(x, self.neighbors, self.nn_neighbors)
-            for ival in zip(points, points[1:]):
+            for ival in _get_intervals(x, self.neighbors, self.nn_neighbors):
                 self._update_interpolated_loss_in_interval(*ival)
 
             # Since 'x' is in between (x_left, x_right),
@@ -429,10 +429,8 @@ class Learner1D(BaseLearner):
 
         # The the losses for the "real" intervals.
         self.losses = {}
-        for x_left, x_right in intervals:
-            self.losses[x_left, x_right] = (
-                self._get_loss_in_interval(x_left, x_right)
-                if x_right - x_left >= self._dx_eps else 0)
+        for ival in intervals:
+            self.losses[ival] = self._get_loss_in_interval(*ival)
 
         # List with "real" intervals that have interpolated intervals inside
         to_interpolate = []