Fix flake8 issues in tests and docs

- Also applies Black for future inclusion

.gitlab-ci.yml

@@ -157,3 +157,18 @@ deploy_release:
     - twine upload dist/*
   only:
   - tags
+
+
+precommits-py3.7:
+  stage: test
+  image: bilbydev/v2-dockerfile-test-suite-python37
+  script:
+    - source activate python37
+    - mkdir -p .pip37
+    - pip install --upgrade pip
+    - pip --cache-dir=.pip37 install --upgrade bilby
+    - pip --cache-dir=.pip37 install .
+    - pip --cache-dir=.pip37 install pre-commit
+
+    # Run precommits (flake8, spellcheck, isort, no merge conflicts, etc)
+    - pre-commit run --all-files --verbose --show-diff-on-failure

.pre-commit-config.yaml

+repos:
+-   repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v2.3.0
+    hooks:
+    -   id: check-merge-conflict # prevent committing files with merge conflicts
+    -   id: flake8 # checks for flake8 errors
+#-   repo: https://github.com/codespell-project/codespell
+#    rev: v1.16.0
+#    hooks:
+#    -   id: codespell # Spellchecker
+#        args: [-L, nd, --skip, "*.ipynb,*.html", --ignore-words=.dictionary.txt]
+#        exclude: ^examples/tutorials/
+#-   repo: https://github.com/asottile/seed-isort-config
+#    rev: v1.3.0
+#    hooks:
+#    -   id: seed-isort-config
+#        args: [--application-directories, 'bilby/']
+#-   repo: https://github.com/pre-commit/mirrors-isort
+#    rev: v4.3.21
+#    hooks:
+#    -   id: isort # sort imports alphabetically and separates import into sections
+#        args: [-w=88, -m=3, -tc, -sp=setup.cfg ]

CONTRIBUTING.md

@@ -49,6 +49,33 @@ def my_new_function(x, y, print=False):
 5. Don't repeat yourself. If code is repeated in multiple places, wrap it up into a function.
 6. Add tests. The C.I. is there to do the work of "checking" the code, both now and into the future. Use it.
 
+## Automated code checking
+
+In order to automate checking of the code quality, we use
+[pre-commit](https://pre-commit.com/). For more details, see the documentation,
+here we will give a quick-start guide:
+1. Install and configure:
+```console
+$ pip install pre-commit  # install the pre-commit package
+$ cd bilby
+$ pre-commit install
+```
+2. Now, when you run `$ git commit`, there will be a pre-commit check.
+   This is going to search for issues in your code: spelling, formatting, etc.
+   In some cases, it will automatically fix the code, in other cases, it will
+   print a warning. If it automatically fixed the code, you'll need to add the
+   changes to the index (`$ git add FILE.py`) and run `$ git commit` again. If
+   it didn't automatically fix the code, but still failed, it will have printed
+   a message as to why the commit failed. Read the message, fix the issues,
+   then recommit.
+3. The pre-commit checks are done to avoid pushing and then failing. But, you
+   can skip them by running `$ git commit --no-verify`, but note that the C.I.
+   still does the check so you won't be able to merge until the issues are
+   resolved.
+If you experience any issues with pre-commit, please ask for support on the
+usual help channels.
+
+
 ## Code relevance
 
 The bilby code base is intended to be highly modular and flexible. We encourage

docs/conf.py

@@ -173,5 +173,3 @@ texinfo_documents = [
 ]
 
 numpydoc_show_class_members = False
-
-

setup.cfg

 [flake8]
 exclude = .git,docs,build,dist,test,*__init__.py
 max-line-length = 120
-ignore = E129 W503 W504 W605 E203
+ignore = E129 W503 W504 W605 E203 E402
 
 [tool:pytest]
 addopts =

test/calibration_test.py

@@ -4,7 +4,6 @@ import numpy as np
 
 
 class TestBaseClass(unittest.TestCase):
-
     def setUp(self):
         self.model = calibration.Recalibrate()
 
@@ -12,7 +11,7 @@ class TestBaseClass(unittest.TestCase):
         del self.model
 
     def test_repr(self):
-        expected = 'Recalibrate(prefix={})'.format('\'recalib_\'')
+        expected = "Recalibrate(prefix={})".format("'recalib_'")
         actual = repr(self.model)
         self.assertEqual(expected, actual)
 
@@ -23,18 +22,22 @@ class TestBaseClass(unittest.TestCase):
 
 
 class TestCubicSpline(unittest.TestCase):
-
     def setUp(self):
-        self.prefix = 'recalib_'
+        self.prefix = "recalib_"
         self.minimum_frequency = 20
         self.maximum_frequency = 1024
         self.n_points = 5
         self.model = calibration.CubicSpline(
-            prefix=self.prefix, minimum_frequency=self.minimum_frequency,
-            maximum_frequency=self.maximum_frequency, n_points=self.n_points)
-        self.parameters = {'recalib_{}_{}'.format(param, ii): 0.0
-                           for ii in range(5)
-                           for param in ['amplitude', 'phase']}
+            prefix=self.prefix,
+            minimum_frequency=self.minimum_frequency,
+            maximum_frequency=self.maximum_frequency,
+            n_points=self.n_points,
+        )
+        self.parameters = {
+            "recalib_{}_{}".format(param, ii): 0.0
+            for ii in range(5)
+            for param in ["amplitude", "phase"]
+        }
 
     def tearDown(self):
         del self.prefix
@@ -46,27 +49,28 @@ class TestCubicSpline(unittest.TestCase):
 
     def test_calibration_factor(self):
         frequency_array = np.linspace(20, 1024, 1000)
-        cal_factor = self.model.get_calibration_factor(frequency_array,
-                                                       **self.parameters)
+        cal_factor = self.model.get_calibration_factor(
+            frequency_array, **self.parameters
+        )
         assert np.alltrue(cal_factor.real == np.ones_like(frequency_array))
 
     def test_repr(self):
-        expected = 'CubicSpline(prefix=\'{}\', minimum_frequency={}, maximum_frequency={}, n_points={})'\
-            .format(self.prefix, self.minimum_frequency, self.maximum_frequency, self.n_points)
+        expected = "CubicSpline(prefix='{}', minimum_frequency={}, maximum_frequency={}, n_points={})".format(
+            self.prefix, self.minimum_frequency, self.maximum_frequency, self.n_points
+        )
         actual = repr(self.model)
         self.assertEqual(expected, actual)
 
 
 class TestCubicSplineRequiresFourNodes(unittest.TestCase):
-
     def test_cannot_instantiate_with_too_few_nodes(self):
         for ii in range(6):
             if ii < 4:
                 with self.assertRaises(ValueError):
-                    calibration.CubicSpline('test', 1, 10, ii)
+                    calibration.CubicSpline("test", 1, 10, ii)
             else:
-                calibration.CubicSpline('test', 1, 10, ii)
+                calibration.CubicSpline("test", 1, 10, ii)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     unittest.main()

test/context.py

 import os
 import sys
-sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
 
-import bilby
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
+
+import bilby  # noqa

test/cosmology_test.py

@@ -6,18 +6,17 @@ from bilby.gw import cosmology
 
 
 class TestSetCosmology(unittest.TestCase):
-
     def setUp(self):
         pass
 
     def test_setting_cosmology_with_string(self):
-        cosmology.set_cosmology('WMAP9')
-        self.assertEqual(cosmology.COSMOLOGY[1], 'WMAP9')
-        cosmology.set_cosmology('Planck15')
+        cosmology.set_cosmology("WMAP9")
+        self.assertEqual(cosmology.COSMOLOGY[1], "WMAP9")
+        cosmology.set_cosmology("Planck15")
 
     def test_setting_cosmology_with_astropy_object(self):
         cosmology.set_cosmology(WMAP9)
-        self.assertEqual(cosmology.COSMOLOGY[1], 'WMAP9')
+        self.assertEqual(cosmology.COSMOLOGY[1], "WMAP9")
         cosmology.set_cosmology(Planck15)
 
     def test_setting_cosmology_with_default(self):
@@ -27,30 +26,29 @@ class TestSetCosmology(unittest.TestCase):
     def test_setting_cosmology_with_flat_lambda_cdm_dict(self):
         cosmo_dict = dict(H0=67.7, Om0=0.3)
         cosmology.set_cosmology(cosmo_dict)
-        self.assertEqual(cosmology.COSMOLOGY[1][:13], 'FlatLambdaCDM')
+        self.assertEqual(cosmology.COSMOLOGY[1][:13], "FlatLambdaCDM")
 
     def test_setting_cosmology_with_lambda_cdm_dict(self):
         cosmo_dict = dict(H0=67.7, Om0=0.3, Ode0=0.7)
         cosmology.set_cosmology(cosmo_dict)
-        self.assertEqual(cosmology.COSMOLOGY[1][:9], 'LambdaCDM')
+        self.assertEqual(cosmology.COSMOLOGY[1][:9], "LambdaCDM")
 
     def test_setting_cosmology_with_w_cdm_dict(self):
         cosmo_dict = dict(H0=67.7, Om0=0.3, Ode0=0.7, w0=-1.0)
         cosmology.set_cosmology(cosmo_dict)
-        self.assertEqual(cosmology.COSMOLOGY[1][:4], 'wCDM')
+        self.assertEqual(cosmology.COSMOLOGY[1][:4], "wCDM")
 
 
 class TestGetCosmology(unittest.TestCase):
-
     def setUp(self):
         pass
 
     def test_getting_cosmology_with_string(self):
-        self.assertEqual(cosmology.get_cosmology('WMAP9').name, 'WMAP9')
+        self.assertEqual(cosmology.get_cosmology("WMAP9").name, "WMAP9")
 
     def test_getting_cosmology_with_default(self):
         self.assertEqual(cosmology.get_cosmology(), cosmology.COSMOLOGY[0])
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     unittest.main()

test/example_test.py

 from __future__ import absolute_import
 import matplotlib
-matplotlib.use('Agg')
+
+matplotlib.use("Agg")
 
 import unittest
 import os
@@ -12,14 +13,14 @@ from past.builtins import execfile
 import bilby.core.utils
 
 # Imported to ensure the examples run
-import numpy as np
-import inspect
+import numpy as np  # noqa: F401
+import inspect  # noqa: F401
 
 bilby.core.utils.command_line_args.bilby_test_mode = True
 
 
 class Test(unittest.TestCase):
-    outdir = 'outdir'
+    outdir = "outdir"
     dir_path = os.path.dirname(os.path.realpath(__file__))
     dir_path = os.path.abspath(os.path.join(dir_path, os.path.pardir))
 
@@ -29,8 +30,7 @@ class Test(unittest.TestCase):
             try:
                 shutil.rmtree(self.outdir)
             except OSError:
-                logging.warning(
-                    "{} not removed prior to tests".format(self.outdir))
+                logging.warning("{} not removed prior to tests".format(self.outdir))
 
     @classmethod
     def tearDownClass(self):
@@ -38,20 +38,18 @@ class Test(unittest.TestCase):
             try:
                 shutil.rmtree(self.outdir)
             except OSError:
-                logging.warning(
-                    "{} not removed prior to tests".format(self.outdir))
+                logging.warning("{} not removed prior to tests".format(self.outdir))
 
     def test_examples(self):
         """ Loop over examples to check they run """
-        examples = ['examples/core_examples/linear_regression.py',
-                    'examples/core_examples/linear_regression_unknown_noise.py',
-                    ]
+        examples = [
+            "examples/core_examples/linear_regression.py",
+            "examples/core_examples/linear_regression_unknown_noise.py",
+        ]
         for filename in examples:
             print("Testing {}".format(filename))
             execfile(filename)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     unittest.main()
-
-

test/grid_test.py

@@ -2,10 +2,8 @@ from __future__ import absolute_import, division
 
 import unittest
 import numpy as np
-import pandas as pd
 import shutil
 import os
-import json
 from scipy.stats import multivariate_normal
 
 import bilby
@@ -30,32 +28,41 @@ class MultiGaussian(bilby.Likelihood):
 
 
 class TestGrid(unittest.TestCase):
-
     def setUp(self):
         np.random.seed(7)
-        
+
         # set 2D multivariate Gaussian (zero mean, unit variance)
-        self.mus = [0., 0.]
-        self.cov = [[1., 0.], [0., 1.]]
+        self.mus = [0.0, 0.0]
+        self.cov = [[1.0, 0.0], [0.0, 1.0]]
         dim = len(self.mus)
         self.likelihood = MultiGaussian(self.mus, self.cov)
-        
+
         # set priors out to +/- 5 sigma
         self.priors = bilby.core.prior.PriorDict()
         self.priors.update(
-            {"x{0}".format(i): bilby.core.prior.Uniform(-5, 5, "x{0}".format(i)) for i in range(dim)}
+            {
+                "x{0}".format(i): bilby.core.prior.Uniform(-5, 5, "x{0}".format(i))
+                for i in range(dim)
+            }
         )
 
         # expected evidence integral should be (1/V) where V is the prior volume
-        log_prior_vol = np.sum(np.log([prior.maximum - prior.minimum for key, prior in self.priors.items()]))
+        log_prior_vol = np.sum(
+            np.log(
+                [prior.maximum - prior.minimum for key, prior in self.priors.items()]
+            )
+        )
         self.expected_ln_evidence = -log_prior_vol
 
         self.grid_size = 100
 
         grid = bilby.core.grid.Grid(
-            label='label', outdir='outdir', priors=self.priors,
-            grid_size=self.grid_size, likelihood=self.likelihood,
-            save=True
+            label="label",
+            outdir="outdir",
+            priors=self.priors,
+            grid_size=self.grid_size,
+            likelihood=self.likelihood,
+            save=True,
         )
 
         self.grid = grid
@@ -71,29 +78,33 @@ class TestGrid(unittest.TestCase):
         pass
 
     def test_grid_file_name_default(self):
-        outdir = 'outdir'
-        label = 'label'
-        self.assertEqual(bilby.core.grid.grid_file_name(outdir, label),
-                         '{}/{}_grid.json'.format(outdir, label))
-        self.assertEqual(bilby.core.grid.grid_file_name(outdir, label, True),
-                         '{}/{}_grid.json.gz'.format(outdir, label))
+        outdir = "outdir"
+        label = "label"
+        self.assertEqual(
+            bilby.core.grid.grid_file_name(outdir, label),
+            "{}/{}_grid.json".format(outdir, label),
+        )
+        self.assertEqual(
+            bilby.core.grid.grid_file_name(outdir, label, True),
+            "{}/{}_grid.json.gz".format(outdir, label),
+        )
 
     def test_fail_save_and_load(self):
         with self.assertRaises(ValueError):
             bilby.core.grid.Grid.read()
 
         with self.assertRaises(IOError):
-            bilby.core.grid.Grid.read(filename='not/a/file.json')
+            bilby.core.grid.Grid.read(filename="not/a/file.json")
 
     def test_fail_marginalize(self):
         with self.assertRaises(TypeError):
             self.grid.marginalize_posterior(parameters=2.4)
-        
+
         with self.assertRaises(TypeError):
             self.grid.marginalize_posterior(not_parameters=4.7)
-        
+
         with self.assertRaises(ValueError):
-            self.grid.marginalize_posterior(parameters='jkgsd')
+            self.grid.marginalize_posterior(parameters="jkgsd")
 
     def test_parameter_names(self):
         assert list(self.priors.keys()) == self.grid.parameter_names
@@ -102,94 +113,150 @@ class TestGrid(unittest.TestCase):
     def test_no_marginalization(self):
         # test arrays are the same if no parameters are given to marginalize
         # over
-        assert np.array_equal(self.grid.ln_likelihood,
-                              self.grid.marginalize_ln_likelihood(not_parameters=self.grid.parameter_names))
-    
+        assert np.array_equal(
+            self.grid.ln_likelihood,
+            self.grid.marginalize_ln_likelihood(
+                not_parameters=self.grid.parameter_names
+            ),
+        )
+
     def test_marginalization_shapes(self):
         assert len(self.grid.marginalize_ln_likelihood().shape) == 0
-        
-        marg1 = self.grid.marginalize_ln_likelihood(parameters=self.grid.parameter_names[0])
+
+        marg1 = self.grid.marginalize_ln_likelihood(
+            parameters=self.grid.parameter_names[0]
+        )
         assert marg1.shape == (self.grid_size,)
 
-        marg2 = self.grid.marginalize_ln_likelihood(parameters=self.grid.parameter_names[1])
+        marg2 = self.grid.marginalize_ln_likelihood(
+            parameters=self.grid.parameter_names[1]
+        )
         assert marg2.shape == (self.grid_size,)
 
         assert self.grid.ln_likelihood.shape == (self.grid_size, self.grid_size)
         assert self.grid.ln_posterior.shape == (self.grid_size, self.grid_size)
 
     def test_marginalization_opposite(self):
-        assert np.array_equal(self.grid.marginalize_ln_likelihood(parameters=self.grid.parameter_names[0]),
-                              self.grid.marginalize_ln_likelihood(not_parameters=self.grid.parameter_names[1]))
-        assert np.array_equal(self.grid.marginalize_ln_likelihood(parameters=self.grid.parameter_names[1]),
-                              self.grid.marginalize_ln_likelihood(not_parameters=self.grid.parameter_names[0]))
-    
+        assert np.array_equal(
+            self.grid.marginalize_ln_likelihood(
+                parameters=self.grid.parameter_names[0]
+            ),
+            self.grid.marginalize_ln_likelihood(
+                not_parameters=self.grid.parameter_names[1]
+            ),
+        )
+        assert np.array_equal(
+            self.grid.marginalize_ln_likelihood(
+                parameters=self.grid.parameter_names[1]
+            ),
+            self.grid.marginalize_ln_likelihood(
+                not_parameters=self.grid.parameter_names[0]
+            ),
+        )
+
     def test_max_marginalized_likelihood(self):
         # marginalised likelihoods should have max values of 1 (as they are not
         # properly normalised)
-        assert self.grid.marginalize_likelihood(self.grid.parameter_names[0]).max() == 1.
-        assert self.grid.marginalize_likelihood(self.grid.parameter_names[1]).max() == 1.
+        assert (
+            self.grid.marginalize_likelihood(self.grid.parameter_names[0]).max() == 1.0
+        )
+        assert (
+            self.grid.marginalize_likelihood(self.grid.parameter_names[1]).max() == 1.0
+        )
 
     def test_ln_evidence(self):
         assert np.isclose(self.grid.ln_evidence, self.expected_ln_evidence)
 
     def test_fail_grid_size(self):
         with self.assertRaises(TypeError):
-            grid = bilby.core.grid.Grid(
-                label='label', outdir='outdir', priors=self.priors,
-                grid_size=2.3, likelihood=self.likelihood,
-                save=True
+            bilby.core.grid.Grid(
+                label="label",
+                outdir="outdir",
+                priors=self.priors,
+                grid_size=2.3,
+                likelihood=self.likelihood,
+                save=True,
             )
 
     def test_mesh_grid(self):
         assert self.grid.mesh_grid[0].shape == (self.grid_size, self.grid_size)
-        assert self.grid.mesh_grid[0][0,0] == self.priors[self.grid.parameter_names[0]].minimum
-        assert self.grid.mesh_grid[0][-1,-1] == self.priors[self.grid.parameter_names[1]].maximum
+        assert (
+            self.grid.mesh_grid[0][0, 0]
+            == self.priors[self.grid.parameter_names[0]].minimum
+        )
+        assert (
+            self.grid.mesh_grid[0][-1, -1]
+            == self.priors[self.grid.parameter_names[1]].maximum
+        )
 
     def test_different_grids(self):
         npoints = [10, 20]
 
         grid = bilby.core.grid.Grid(
-            label='label', outdir='outdir', priors=self.priors,
-            grid_size=npoints, likelihood=self.likelihood
+            label="label",
+            outdir="outdir",
+            priors=self.priors,
+            grid_size=npoints,
+            likelihood=self.likelihood,
         )
 
         assert grid.mesh_grid[0].shape == tuple(npoints)
-        assert grid.mesh_grid[0][0,0] == self.priors[self.grid.parameter_names[0]].minimum
-        assert grid.mesh_grid[0][-1,-1] == self.priors[self.grid.parameter_names[1]].maximum
+        assert (
+            grid.mesh_grid[0][0, 0] == self.priors[self.grid.parameter_names[0]].minimum
+        )
+        assert (
+            grid.mesh_grid[0][-1, -1]
+            == self.priors[self.grid.parameter_names[1]].maximum
+        )
 
         del grid
 
-        npoints = {'x0': 15, 'x1': 18}
+        npoints = {"x0": 15, "x1": 18}
 
         grid = bilby.core.grid.Grid(
-            label='label', outdir='outdir', priors=self.priors,
-            grid_size=npoints, likelihood=self.likelihood
+            label="label",
+            outdir="outdir",
+            priors=self.priors,
+            grid_size=npoints,
+            likelihood=self.likelihood,
         )
 
-        assert grid.mesh_grid[0].shape == (npoints['x0'], npoints['x1'])
-        assert grid.mesh_grid[0][0,0] == self.priors[self.grid.parameter_names[0]].minimum
-        assert grid.mesh_grid[0][-1,-1] == self.priors[self.grid.parameter_names[1]].maximum
+        assert grid.mesh_grid[0].shape == (npoints["x0"], npoints["x1"])
+        assert (
+            grid.mesh_grid[0][0, 0] == self.priors[self.grid.parameter_names[0]].minimum
+        )
+        assert (
+            grid.mesh_grid[0][-1, -1]
+            == self.priors[self.grid.parameter_names[1]].maximum
+        )
 
         del grid
 
-        x0s = np.linspace(self.priors['x0'].minimum, self.priors['x0'].maximum, 13)
-        x1s = np.linspace(self.priors['x0'].minimum, self.priors['x0'].maximum, 14)
-        npoints = {'x0': x0s,
-                   'x1': x1s}
+        x0s = np.linspace(self.priors["x0"].minimum, self.priors["x0"].maximum, 13)
+        x1s = np.linspace(self.priors["x0"].minimum, self.priors["x0"].maximum, 14)
+        npoints = {"x0": x0s, "x1": x1s}
 
         grid = bilby.core.grid.Grid(
-            label='label', outdir='outdir', priors=self.priors,
-            grid_size=npoints, likelihood=self.likelihood
+            label="label",
+            outdir="outdir",
+            priors=self.priors,
+            grid_size=npoints,
+            likelihood=self.likelihood,
         )
 
         assert grid.mesh_grid[0].shape == (len(x0s), len(x1s))
-        assert grid.mesh_grid[0][0,0] == self.priors[self.grid.parameter_names[0]].minimum
-        assert grid.mesh_grid[0][-1,-1] == self.priors[self.grid.parameter_names[1]].maximum
-        assert np.array_equal(grid.sample_points['x0'], x0s)
-        assert np.array_equal(grid.sample_points['x1'], x1s)
+        assert (
+            grid.mesh_grid[0][0, 0] == self.priors[self.grid.parameter_names[0]].minimum
+        )
+        assert (
+            grid.mesh_grid[0][-1, -1]
+            == self.priors[self.grid.parameter_names[1]].maximum
+        )