Merge branch 'learner1D_bounds_bug' into 'master'

1D: fix the rare case where the right boundary point exists before the left bound

Closes #94

See merge request !95

adaptive/learner/learner1D.py

@@ -261,17 +261,15 @@ class Learner1D(BaseLearner):
             return [], []
 
         # If the bounds have not been chosen yet, we choose them first.
-        points = [b for b in self.bounds if b not in self.data
-                  and b not in self.pending_points]
+        missing_bounds = [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
+        if missing_bounds:
             loss_improvements = [np.inf] * n
-            points = np.linspace(*self.bounds, n).tolist()
-        elif len(points) == 1:
-            # Second time, if we previously returned just self.bounds[0]
-            loss_improvements = [np.inf] * n
-            points = np.linspace(*self.bounds, n + 1)[1:].tolist()
+            # XXX: should check if points are present in self.data or self.pending_points
+            points = np.linspace(*self.bounds, n + 2 - len(missing_bounds)).tolist()
+            if len(missing_bounds) == 1:
+                points = points[1:] if missing_bounds[0] == self.bounds[1] else points[:-1]
         else:
             def xs(x_left, x_right, n):
                 if n == 1:

adaptive/tests/test_learner.py

@@ -363,7 +363,7 @@ def test_learner1d_first_iteration():
     """Edge cases where we ask for a few points at the start."""
     learner = Learner1D(lambda x: None, (-1, 1))
     points, loss_improvements = learner.ask(2)
-    assert set(points) == set([-1, 1])
+    assert set(points) == set(learner.bounds)
 
     learner = Learner1D(lambda x: None, (-1, 1))
     points, loss_improvements = learner.ask(3)
@@ -371,17 +371,27 @@ def test_learner1d_first_iteration():
 
     learner = Learner1D(lambda x: None, (-1, 1))
     points, loss_improvements = learner.ask(1)
-    assert len(points) == 1 and points[0] in [-1, 1]
+    assert len(points) == 1 and points[0] in learner.bounds
     rest = set([-1, 0, 1]) - set(points)
     points, loss_improvements = learner.ask(2)
     assert set(points) == set(rest)
 
     learner = Learner1D(lambda x: None, (-1, 1))
     points, loss_improvements = learner.ask(1)
-    to_see = set([-1, 1]) - set(points)
+    to_see = set(learner.bounds) - set(points)
     points, loss_improvements = learner.ask(1)
     assert set(points) == set(to_see)
 
+    learner = Learner1D(lambda x: None, (-1, 1))
+    learner.tell(1, 0)
+    points, loss_improvements = learner.ask(1)
+    assert points == [-1]
+
+    learner = Learner1D(lambda x: None, (-1, 1))
+    learner.tell(-1, 0)
+    points, loss_improvements = learner.ask(1)
+    assert points == [1]
+
 
 def _run_on_discontinuity(x_0, bounds):