move 'SKOptLearner' test to 'test_skopt_learner.py'

adaptive/tests/test_learners.py

@@ -14,12 +14,6 @@ import pytest
 from ..learner import *
 from ..runner import simple, replay_log
 
-try:
-    import skopt
-    with_scikit_optimize = True
-except ModuleNotFoundError:
-    with_scikit_optimize = False
-
 
 def generate_random_parametrization(f):
     """Return a realization of 'f' with parameters bound to random values.
@@ -129,24 +123,6 @@ def ask_randomly(learner, rounds, points):
     return xs, ls
 
 
-@pytest.mark.skipif(not with_scikit_optimize,
-                    reason='scikit-optimize is not installed')
-def test_skopt_learner_runs():
-    """The SKOptLearner provides very few guarantees about its
-       behaviour, so we only test the most basic usage
-    """
-
-    def g(x, noise_level=0.1):
-        return (np.sin(5 * x) * (1 - np.tanh(x ** 2))
-                + np.random.randn() * noise_level)
-
-    learner = SKOptLearner(g, dimensions=[(-2., 2.)])
-
-    for _ in range(11):
-        (x,), _ = learner.ask(1)
-        learner.tell(x, learner.function(x))
-
-
 @run_with(Learner1D)
 def test_uniform_sampling1D(learner_type, f, learner_kwargs):
     """Points are sampled uniformly if no data is provided.

adaptive/tests/test_skopt_learner.py

+# -*- coding: utf-8 -*-
+
+import random
+import numpy as np
+
+import pytest
+
+
+try:
+    import skopt
+    with_scikit_optimize = True
+    from ..learner import SKOptLearner
+except ModuleNotFoundError:
+    with_scikit_optimize = False
+
+
+@pytest.mark.skipif(not with_scikit_optimize,
+                    reason='scikit-optimize is not installed')
+def test_skopt_learner_runs():
+    """The SKOptLearner provides very few guarantees about its
+       behaviour, so we only test the most basic usage
+    """
+
+    def g(x, noise_level=0.1):
+        return (np.sin(5 * x) * (1 - np.tanh(x ** 2))
+                + np.random.randn() * noise_level)
+
+    learner = SKOptLearner(g, dimensions=[(-2., 2.)])
+
+    for _ in range(11):
+        (x,), _ = learner.ask(1)
+        learner.tell(x, learner.function(x))