@@ -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.

@@ -13,14 +13,6 @@ from .algorithm_4 import DivergentIntegralError as A4DivergentIntegralError

 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():

@@ -4,7 +4,7 @@ import random

 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

@@ -11,8 +11,8 @@ import scipy.spatial

 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):

@@ -1,6 +1,5 @@

 # -*- coding: utf-8 -*-

-import concurrent.futures as concurrent

 import asyncio

 from ..learner import Learner2D

@@ -1,6 +1,5 @@

 # -*- coding: utf-8 -*-

-import random

 import numpy as np

 import pytest

@@ -1,4 +1,4 @@

-from collections import defaultdict, Counter

+from collections import Counter

 from math import factorial

 import itertools

 import pytest

@@ -297,7 +297,7 @@ 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)

@@ -305,12 +305,12 @@ def test_initialisation_raises_when_not_enough_points(dim):

 @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}