new file mode 100644

@@ -0,0 +1,2 @@

+[settings]

+known_third_party = PIL,atomicwrites,holoviews,ipykernel,matplotlib,nbconvert,numpy,pytest,scipy,setuptools,skopt,sortedcollections,sortedcontainers,zmq

@@ -1,16 +1,43 @@

 repos:

--   repo: https://github.com/ambv/black

-    rev: 19.3b0

-    hooks:

-    - id: black

-      language_version: python3.7

 -   repo: https://github.com/pre-commit/pre-commit-hooks

-    rev: v2.1.0

+    rev: v2.4.0

     hooks:

-    -   id: end-of-file-fixer

     -   id: trailing-whitespace

+    -   id: end-of-file-fixer

+    -   id: check-docstring-first

+    -   id: check-yaml

+    -   id: debug-statements

+    -   id: check-ast

 -   repo: https://gitlab.com/pycqa/flake8

-    rev: 3.7.8

+    rev: 3.7.9

     hooks:

     -   id: flake8

-        args: ['--max-line-length=500', '--ignore=E203,E266,E501,W503', '--max-complexity=18', '--select=B,C,E,F,W,T4,B9']

+        args:

+          - --max-line-length=500

+          - --ignore=E203,E266,E501,W503

+          - --max-complexity=18

+          - --select=B,C,E,F,W,T4,B9

+-   repo: https://github.com/ambv/black

+    rev: 19.10b0

+    hooks:

+    - id: black

+      language_version: python3.7

+-   repo: https://github.com/asottile/pyupgrade

+    rev: v1.25.2

+    hooks:

+    -   id: pyupgrade

+        args: ['--py36-plus']

+-   repo: https://github.com/pre-commit/mirrors-isort

+    rev: v4.3.21

+    hooks:

+    -   id: isort

+        args:

+          - --multi-line=3

+          - --trailing-comma

+          - --force-grid-wrap=0

+          - --use-parentheses

+          - --line-width=88

+-   repo: https://github.com/asottile/seed-isort-config

+    rev: v1.9.3

+    hooks:

+    -   id: seed-isort-config

@@ -1,5 +1,3 @@

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

-

 from contextlib import suppress

 from adaptive import learner, runner, utils

@@ -1,4 +1,3 @@

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

 # This file is part of 'miniver': https://github.com/jbweston/miniver

 #

 import os

@@ -1,5 +1,3 @@

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

-

 from contextlib import suppress

 from adaptive.learner.average_learner import AverageLearner

@@ -1,5 +1,3 @@

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

-

 from math import sqrt

 import numpy as np

@@ -1,5 +1,3 @@

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

-

 import itertools

 from collections import defaultdict

 from collections.abc import Iterable

@@ -1,10 +1,8 @@

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

-

 import abc

 from contextlib import suppress

 from copy import deepcopy

-from adaptive.utils import load, save, _RequireAttrsABCMeta

+from adaptive.utils import _RequireAttrsABCMeta, load, save

 def uses_nth_neighbors(n):

@@ -1,5 +1,3 @@

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

-

 import functools

 from collections import OrderedDict

@@ -1,4 +1,3 @@

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

 # Based on an adaptive quadrature algorithm by Pedro Gonnet

 from collections import defaultdict

@@ -1,4 +1,3 @@

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

 # Based on an adaptive quadrature algorithm by Pedro Gonnet

 import sys

@@ -572,9 +571,15 @@ class IntegratorLearner(BaseLearner):

         )

     def _set_data(self, data):

-        self.priority_split, self.data, self.pending_points, self._stack, x_mapping, self.ivals, self.first_ival = (

-            data

-        )

+        (

+            self.priority_split,

+            self.data,

+            self.pending_points,

+            self._stack,

+            x_mapping,

+            self.ivals,

+            self.first_ival,

+        ) = data

         # Add the pending_points to the _stack such that they are evaluated again

         for x in self.pending_points:

@@ -1,5 +1,3 @@

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

-

 import itertools

 import math

 from collections.abc import Iterable

@@ -1,5 +1,3 @@

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

-

 import itertools

 import warnings

 from collections import OrderedDict

@@ -1,5 +1,3 @@

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

-

 import functools

 import itertools

 import random

@@ -340,8 +338,8 @@ class LearnerND(BaseLearner):

         self._min_value = None

         self._max_value = None

         self._output_multiplier = (

-            1

-        )  # If we do not know anything, do not scale the values

+            1  # If we do not know anything, do not scale the values

+        )

         self._recompute_losses_factor = 1.1

         # create a private random number generator with fixed seed

@@ -1,5 +1,3 @@

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

-

 import collections

 import numpy as np

@@ -228,7 +228,7 @@ def simplex_volume_in_embedding(vertices) -> float:

     # Make matrix and find volume

     sq_dists_mat = scipy.spatial.distance.squareform(bordered)

-    coeff = -(-2) ** (num_verts - 1) * factorial(num_verts - 1) ** 2

+    coeff = -((-2) ** (num_verts - 1)) * factorial(num_verts - 1) ** 2

     vol_square = fast_det(sq_dists_mat) / coeff

     if vol_square < 0:

@@ -1,5 +1,3 @@

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

-

 import asyncio

 import datetime

 import importlib

@@ -1,5 +1,3 @@

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

-

 import abc

 import asyncio

 import concurrent.futures as concurrent

@@ -1,5 +1,3 @@

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

-

 import random

 import numpy as np

@@ -1,5 +1,3 @@

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

-

 import pytest

 from adaptive.learner import BalancingLearner, Learner1D

@@ -1,5 +1,3 @@

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

-

 from functools import partial

 from operator import attrgetter

@@ -1,5 +1,3 @@

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

-

 import random

 import numpy as np

@@ -1,5 +1,3 @@

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

-

 import numpy as np

 import scipy.spatial

@@ -1,5 +1,3 @@

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

-

 import collections

 import functools as ft

 import inspect

@@ -129,7 +127,7 @@ def linear_with_peak(x, d: uniform(-1, 1)):

 def ring_of_fire(xy, d: uniform(0.2, 1)):

     a = 0.2

     x, y = xy

-    return x + math.exp(-(x ** 2 + y ** 2 - d ** 2) ** 2 / a ** 4)

+    return x + math.exp(-((x ** 2 + y ** 2 - d ** 2) ** 2) / a ** 4)

 @learn_with(LearnerND, bounds=((-1, 1), (-1, 1), (-1, 1)))

@@ -137,7 +135,7 @@ def ring_of_fire(xy, d: uniform(0.2, 1)):

 def sphere_of_fire(xyz, d: uniform(0.2, 1)):

     a = 0.2

     x, y, z = xyz

-    return x + math.exp(-(x ** 2 + y ** 2 + z ** 2 - d ** 2) ** 2 / a ** 4) + z ** 2

+    return x + math.exp(-((x ** 2 + y ** 2 + z ** 2 - d ** 2) ** 2) / a ** 4) + z ** 2

 @learn_with(SequenceLearner, sequence=range(1000))

@@ -1,5 +1,3 @@

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

-

 import ipykernel.iostream

 import zmq

@@ -1,5 +1,3 @@

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

-

 import asyncio

 import time

@@ -1,5 +1,3 @@

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

-

 import numpy as np

 import pytest

@@ -1,5 +1,3 @@

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

-

 import itertools

 from collections import Counter

 from math import factorial

@@ -12,7 +12,7 @@ def ring_of_fire(xy):

     a = 0.2

     d = 0.7

     x, y = xy

-    return x + math.exp(-(x ** 2 + y ** 2 - d ** 2) ** 2 / a ** 4)

+    return x + math.exp(-((x ** 2 + y ** 2 - d ** 2) ** 2) / a ** 4)

 def test_learnerND_inits_loss_depends_on_neighbors_correctly():

@@ -11,7 +11,7 @@ from adaptive.runner import simple as SimpleRunner

 def ring_of_fire(xy, d=0.75):

     a = 0.2

     x, y = xy

-    return x + math.exp(-(x ** 2 + y ** 2 - d ** 2) ** 2 / a ** 4)

+    return x + math.exp(-((x ** 2 + y ** 2 - d ** 2) ** 2) / a ** 4)

 def test_learnerND_runs_to_10_points():

@@ -1,5 +1,3 @@

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

-

 import abc

 import functools

 import gzip

@@ -15,7 +15,7 @@ def f_1d(x, offset=offset):

 def f_2d(xy):

     x, y = xy

     a = 0.2

-    return x + np.exp(-(x ** 2 + y ** 2 - 0.75 ** 2) ** 2 / a ** 4)

+    return x + np.exp(-((x ** 2 + y ** 2 - 0.75 ** 2) ** 2) / a ** 4)

 class TimeLearner1D:

@@ -8,7 +8,7 @@ from PIL import Image, ImageDraw

 sys.path.insert(0, os.path.abspath(".."))  # to get adaptive on the path

-import adaptive  # noqa: E402

+import adaptive  # noqa: E402, isort:skip

 holoviews.notebook_extension("matplotlib")

@@ -19,7 +19,7 @@ def create_and_run_learner():

         x, y = xy

         a = 0.2

-        return x + np.exp(-(x ** 2 + y ** 2 - 0.75 ** 2) ** 2 / a ** 4)

+        return x + np.exp(-((x ** 2 + y ** 2 - 0.75 ** 2) ** 2) / a ** 4)

     learner = adaptive.Learner2D(ring, bounds=[(-1, 1), (-1, 1)])

     adaptive.runner.simple(learner, goal=lambda l: l.loss() < 0.01)

@@ -1,4 +1,3 @@

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

 #

 # Configuration file for the Sphinx documentation builder.

 #

@@ -18,12 +17,11 @@ import sys

 package_path = os.path.abspath("../..")

 # Insert into sys.path so that we can import adaptive here

 sys.path.insert(0, package_path)

-

-import adaptive  # noqa: E402

-

 # Insert into PYTHONPATH so that jupyter-sphinx will pick it up

 os.environ["PYTHONPATH"] = ":".join((package_path, os.environ.get("PYTHONPATH", "")))

+import adaptive  # noqa: E402, isort:skip

+

 # -- Project information -----------------------------------------------------

 project = "adaptive"

@@ -1,5 +1,4 @@

 #!/usr/bin/env python3

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

 import sys