@@ -125,10 +125,7 @@ class Learner1D(BaseLearner):

     def loss(self, real=True):

         losses = self.losses if real else self.losses_combined

-        if len(losses) == 0:

-            return float('inf')

-        else:

-            return max(losses.values())

+        return max(losses.values()) if len(losses) > 0 else float('inf')

     def update_interpolated_loss_in_interval(self, x_left, x_right):

         if x_left is not None and x_right is not None:

@@ -176,7 +173,7 @@ class Learner1D(BaseLearner):

         if x in neighbors:

             return neighbors[x]

         pos = neighbors.bisect_left(x)

-        x_left = neighbors.iloc[pos-1] if pos != 0 else None

+        x_left = neighbors.iloc[pos - 1] if pos != 0 else None

         x_right = neighbors.iloc[pos] if pos != len(neighbors) else None

         return x_left, x_right

@@ -264,10 +261,8 @@ class Learner1D(BaseLearner):

             return [], []

         # If the bounds have not been chosen yet, we choose them first.

-        points = []

-        for bound in self.bounds:

-            if bound not in self.data and bound not in self.pending_points:

-                points.append(bound)

+        points = [b for b in self.bounds if b not in self.data

+                  and b not in self.pending_points]

         if len(points) == 2:

             # First time

@@ -288,12 +283,10 @@ class Learner1D(BaseLearner):

             # Calculate how many points belong to each interval.

             x_scale = self._scale[0]

-

             quals = []

-            for ((x_left, x_right), loss) in self.losses_combined.items():

-                quality = -loss if not math.isinf(loss) else -(x_right - x_left) / x_scale

-                quals.append((quality, (x_left, x_right), 1))

-

+            for x, loss in self.losses_combined.items():

+                quality = -loss if not math.isinf(loss) else -(x[1] - x[0]) / x_scale

+                quals.append((quality, x, 1))

             heapq.heapify(quals)

             for point_number in range(n):