test the usage of a ConvexHull

adaptive/tests/test_learnernd.py

 # -*- coding: utf-8 -*-
 
 from ..learner import LearnerND
-from ..runner import replay_log
-
+from ..runner import replay_log, simple
+from .test_learners import ring_of_fire, generate_random_parametrization
+import scipy.spatial
 
 def test_faiure_case_LearnerND():
     log = [
@@ -21,3 +22,15 @@ def test_faiure_case_LearnerND():
     ]
     learner = LearnerND(lambda *x: x, bounds=[(-1, 1), (-1, 1), (-1, 1)])
     replay_log(learner, log)
+
+def test_interior_vs_bbox_gives_same_result():
+    f = generate_random_parametrization(ring_of_fire)
+    
+    control = LearnerND(f, bounds=[(-1, 1), (-1, 1)])
+    hull = scipy.spatial.ConvexHull(control._bounds_points)
+    learner = LearnerND(f, bounds=hull)
+
+    simple(control, goal=lambda l: l.loss() < 0.1)
+    simple(learner, goal=lambda l: l.loss() < 0.1)
+
+    assert learner.data == control.data