fix flake8 issues for the learner tests

adaptive/tests/test_average_learner.py

@@ -30,7 +30,7 @@ def test_avg_std_and_npoints():
         # This will add 5000 points at random values of n.
         # It could try to readd already evaluated points.
 
-        n = random.randint(0, 2*300)
+        n = random.randint(0, 2 * 300)
         value = random.random()
 
         # With 10% chance None is added to simulate asking that point.

adaptive/tests/test_cquad.py

@@ -13,14 +13,6 @@
 eps = np.spacing(1)
 
 
-def rolling_shuffle(nums, size):
-    for i in range(len(nums) - size):
-        x = nums[i:i+size+1]
-        random.shuffle(x)
-        nums[i:i+size+1] = x
-    return nums
-
-
 def run_integrator_learner(f, a, b, tol, n):
     learner = IntegratorLearner(f, bounds=(a, b), tol=tol)
     for _ in range(n):
@@ -73,6 +65,7 @@ def same_ivals(f, a, b, tol):
 
         return equal_ivals(learner.ivals, ivals, verbose=True)
 
+
 # XXX: This *should* pass (https://gitlab.kwant-project.org/qt/adaptive/issues/84)
 @pytest.mark.xfail
 def test_that_gives_same_intervals_as_reference_implementation():
@@ -162,7 +155,6 @@ def test_adding_points_and_skip_one_point():
     np.testing.assert_almost_equal(learner.igral, learner2.igral)
 
 
-
 # XXX: This *should* pass (https://gitlab.kwant-project.org/qt/adaptive/issues/84)
 @pytest.mark.xfail
 def test_tell_in_random_order(first_add_33=False):
@@ -224,7 +216,6 @@ def test_tell_in_random_order(first_add_33=False):
             assert np.isfinite(l.err)
 
 
-
 # XXX: This *should* pass (https://gitlab.kwant-project.org/qt/adaptive/issues/84)
 @pytest.mark.xfail
 def test_tell_in_random_order_first_add_33():

adaptive/tests/test_learner1d.py

@@ -4,7 +4,7 @@
 import numpy as np
 
 from ..learner import Learner1D
-from ..runner import simple, replay_log
+from ..runner import simple
 
 
 def test_pending_loss_intervals():
@@ -200,7 +200,8 @@ def test_small_deviations():
 
 def test_uniform_sampling1D_v2():
     def check(known, expect):
-        def f(x): return x
+        def f(x):
+            return x
         learner = Learner1D(f, bounds=(-1, 1))
         for x in known:
             learner.tell(x, f(x))
@@ -241,8 +242,8 @@ def test_tell_many():
     def f(x, offset=0.123214):
         a = 0.01
         return (np.sin(x**2) + np.sin(x**5)
-            + a**2 / (a**2 + (x - offset)**2)
-            + x**2 + 1e-5 * x**3)
+                + a**2 / (a**2 + (x - offset)**2)
+                + x**2 + 1e-5 * x**3)
 
     def f_vec(x, offset=0.123214):
         a = 0.01

adaptive/tests/test_learners.py

@@ -11,8 +11,8 @@
 
 import pytest
 
-from ..learner import *
-from ..runner import simple, replay_log
+from ..learner import AverageLearner, BalancingLearner, Learner1D, Learner2D, LearnerND
+from ..runner import simple
 
 
 def generate_random_parametrization(f):

adaptive/tests/test_runner.py

@@ -1,6 +1,5 @@
 # -*- coding: utf-8 -*-
 
-import concurrent.futures as concurrent
 import asyncio
 
 from ..learner import Learner2D

adaptive/tests/test_skopt_learner.py

@@ -1,6 +1,5 @@
 # -*- coding: utf-8 -*-
 
-import random
 import numpy as np
 
 import pytest

adaptive/tests/test_triangulation.py

@@ -1,4 +1,4 @@
-from collections import defaultdict, Counter
+from collections import Counter
 from math import factorial
 import itertools
 import pytest
@@ -297,20 +297,20 @@ def test_triangulation_is_deterministic(dim):
 @with_dimension
 def test_initialisation_raises_when_not_enough_points(dim):
     deficient_simplex = _make_standard_simplex(dim)[:-1]
-    
+
     with pytest.raises(ValueError):
         Triangulation(deficient_simplex)
 
 
 @with_dimension
 def test_initialisation_raises_when_points_coplanar(dim):
     zero_volume_simplex = _make_standard_simplex(dim)[:-1]
-    
+
     new_point1 = np.average(zero_volume_simplex, axis=0)
     new_point2 = np.sum(zero_volume_simplex, axis=0)
-    zero_volume_simplex = np.vstack((zero_volume_simplex, 
+    zero_volume_simplex = np.vstack((zero_volume_simplex,
                                      new_point1, new_point2))
-    
+
     with pytest.raises(ValueError):
         Triangulation(zero_volume_simplex)
 
@@ -326,6 +326,6 @@ def test_initialisation_accepts_more_than_one_simplex(dim):
     simplex1 = tuple(range(dim+1))
     simplex2 = tuple(range(1, dim+2))
 
-    _check_triangulation_is_valid(tri)    
-    
+    _check_triangulation_is_valid(tri)
+
     assert tri.simplices == {simplex1, simplex2}