lint doc strings

copulas/multivariate/gaussian.py

@@ -155,9 +155,7 @@ def probability_density(self, X):
         self.check_fit()
         transformed = self._transform_to_normal(X)
 
-        return stats.multivariate_normal.pdf(
-            transformed, cov=self.correlation, allow_singular=True
-        )
+        return stats.multivariate_normal.pdf(transformed, cov=self.correlation, allow_singular=True)
 
     def cumulative_distribution(self, X):
         """Compute the cumulative distribution value for each point in X.

pyproject.toml

@@ -171,11 +171,11 @@ filename = 'copulas/__init__.py'
 search = "__version__ = '{current_version}'"
 replace = "__version__ = '{new_version}'"
 
-
 [tool.ruff]
 preview = true
-line-length = 99
-src = ["copulas"]
+line-length = 100
+indent-width = 4
+src = ["rdt"]
 target-version = "py312"
 exclude = [
     "docs",
@@ -201,19 +201,21 @@ ignore = [
     "D417",   # Missing argument descriptions in the docstring, this is a bug from pydocstyle: https://github.com/PyCQA/pydocstyle/issues/449
 ]
 
+[tool.ruff.format]
+quote-style = "single"
+indent-style = "space"
+preview = true
+docstring-code-format = true
+docstring-code-line-length = "dynamic"
+
 [tool.ruff.lint.pep8-naming]
 extend-ignore-names = ["X", "C", "X_padded", "Y", "Y_padded"]
 
 [tool.ruff.lint.isort]
-known-first-party = ["copulas"]
+known-first-party = ["rdt"]
 
 [tool.ruff.lint.per-file-ignores]
 "__init__.py" = ["F401", "E402", "F403", "F405", "E501", "I001"]
 
-[tool.ruff.format]
-quote-style = "single"
-indent-style = "space"
-preview = true
-
 [tool.ruff.lint.pydocstyle]
 convention = "google"

tests/end-to-end/bivariate/test_base.py

@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from copulas.bivariate import Bivariate
 
 

tests/end-to-end/multivariate/test_base.py

@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from copulas.datasets import sample_trivariate_xyz
 from copulas.multivariate import GaussianMultivariate, VineCopula
 

tests/end-to-end/multivariate/test_gaussian.py

@@ -5,7 +5,6 @@
 
 import numpy as np
 import pandas as pd
-
 from copulas.datasets import sample_trivariate_xyz
 from copulas.multivariate import GaussianMultivariate
 from copulas.univariate import BetaUnivariate, GaussianKDE, ParametricType, Univariate

tests/end-to-end/test___init__.py

@@ -1,5 +1,4 @@
 import numpy as np
-
 from copulas import random_state
 
 

tests/end-to-end/univariate/test_beta.py

@@ -3,9 +3,8 @@
 from unittest import TestCase
 
 import numpy as np
-from scipy.stats import beta
-
 from copulas.univariate import BetaUnivariate
+from scipy.stats import beta
 
 
 class TestGaussian(TestCase):

tests/end-to-end/univariate/test_gamma.py

@@ -3,9 +3,8 @@
 from unittest import TestCase
 
 import numpy as np
-from scipy.stats import gamma
-
 from copulas.univariate import GammaUnivariate
+from scipy.stats import gamma
 
 
 class TestGaussian(TestCase):

tests/end-to-end/univariate/test_gaussian.py

@@ -3,9 +3,8 @@
 from unittest import TestCase
 
 import numpy as np
-from scipy.stats import norm
-
 from copulas.univariate import GaussianUnivariate
+from scipy.stats import norm
 
 
 class TestGaussian(TestCase):

tests/end-to-end/univariate/test_gaussian_kde.py

@@ -3,11 +3,10 @@
 from unittest import TestCase
 
 import numpy as np
-from scipy.stats import ks_2samp, norm, randint
-
 from copulas.datasets import sample_univariate_bimodal
 from copulas.multivariate import GaussianMultivariate
 from copulas.univariate.gaussian_kde import GaussianKDE
+from scipy.stats import ks_2samp, norm, randint
 
 
 class TestGaussian(TestCase):

tests/end-to-end/univariate/test_student_t.py

@@ -3,9 +3,8 @@
 from unittest import TestCase
 
 import numpy as np
-from scipy.stats import t
-
 from copulas.univariate import StudentTUnivariate
+from scipy.stats import t
 
 
 class TestStudentT(TestCase):

tests/end-to-end/univariate/test_truncated_gaussian.py

@@ -3,9 +3,8 @@
 from unittest import TestCase
 
 import numpy as np
-from scipy.stats import truncnorm
-
 from copulas.univariate import TruncatedGaussian
+from scipy.stats import truncnorm
 
 
 class TestGaussian(TestCase):

tests/large_scale_evaluation.py

@@ -43,11 +43,10 @@
 import tabulate
 from botocore import UNSIGNED
 from botocore.client import Config
-from scipy.stats import ks_2samp
-
 from copulas import get_instance
 from copulas.multivariate import GaussianMultivariate, VineCopula
 from copulas.univariate import GaussianUnivariate
+from scipy.stats import ks_2samp
 
 LOGGER = logging.getLogger(__name__)
 

tests/numerical/cdf/test_cdf.py

@@ -5,7 +5,6 @@
 import numpy as np
 import pandas as pd
 import pytest
-
 from copulas import get_instance
 
 BASE = os.path.dirname(__file__)

tests/numerical/fit/test_fit.py

@@ -5,7 +5,6 @@
 import numpy as np
 import pandas as pd
 import pytest
-
 from copulas import get_instance
 
 BASE = os.path.dirname(__file__)

tests/numerical/pdf/test_pdf.py

@@ -5,7 +5,6 @@
 import numpy as np
 import pandas as pd
 import pytest
-
 from copulas import get_instance
 
 BASE = os.path.dirname(__file__)

tests/unit/bivariate/test___init__.py

@@ -1,8 +1,7 @@
 import numpy as np
-from scipy import stats
-
 from copulas.bivariate import select_copula
 from copulas.bivariate.frank import Frank
+from scipy import stats
 
 
 def test_select_copula_negative_tau():

tests/unit/bivariate/test_base.py

@@ -1,8 +1,8 @@
 from unittest import TestCase, mock
 
 import numpy as np
-
 from copulas.bivariate.base import Bivariate, CopulaTypes
+
 from tests import compare_nested_dicts
 
 

tests/unit/bivariate/test_clayton.py

@@ -1,8 +1,8 @@
 from unittest import TestCase
 
 import numpy as np
-
 from copulas.bivariate.clayton import Clayton
+
 from tests import copula_single_arg_not_one, copula_zero_if_arg_zero
 
 

tests/unit/bivariate/test_frank.py

@@ -2,8 +2,8 @@
 from unittest.mock import patch
 
 import numpy as np
-
 from copulas.bivariate.frank import Frank
+
 from tests import compare_nested_iterables, copula_single_arg_not_one, copula_zero_if_arg_zero
 
 

tests/unit/bivariate/test_gumbel.py

@@ -2,8 +2,8 @@
 from unittest.mock import patch
 
 import numpy as np
-
 from copulas.bivariate.gumbel import Gumbel
+
 from tests import compare_nested_iterables, copula_single_arg_not_one, copula_zero_if_arg_zero
 
 

tests/unit/bivariate/test_independence.py

@@ -1,7 +1,6 @@
 from unittest import TestCase
 
 import numpy as np
-
 from copulas.bivariate.independence import Independence
 
 

tests/unit/multivariate/test_base.py

@@ -1,5 +1,4 @@
 import numpy as np
-
 from copulas.multivariate.base import Multivariate
 
 

tests/unit/multivariate/test_gaussian.py

@@ -3,7 +3,6 @@
 
 import numpy as np
 import pandas as pd
-
 from copulas import get_qualified_name
 from copulas.multivariate.gaussian import GaussianMultivariate
 from copulas.univariate import GaussianUnivariate
@@ -309,9 +308,7 @@ def test_fit_distribution_selector(self):
     def test_fit_numpy_array(self):
         """Fit should work indistinctly with numpy arrays and pandas dataframes"""
         # Setup
-        copula = GaussianMultivariate(
-            distribution='copulas.univariate.gaussian.GaussianUnivariate'
-        )
+        copula = GaussianMultivariate(distribution='copulas.univariate.gaussian.GaussianUnivariate')
 
         # Run
         copula.fit(self.data.to_numpy())

tests/unit/multivariate/test_tree.py

@@ -5,11 +5,11 @@
 import numpy as np
 import pandas as pd
 import pytest
-
 from copulas import EPSILON
 from copulas.bivariate import CopulaTypes
 from copulas.multivariate.tree import Edge, Tree, TreeTypes, get_tree
 from copulas.univariate.gaussian_kde import GaussianKDE
+
 from tests import compare_nested_dicts, compare_nested_iterables, compare_values_epsilon
 
 

tests/unit/multivariate/test_vine.py

@@ -5,9 +5,9 @@
 import numpy as np
 import pandas as pd
 import pytest
-
 from copulas.multivariate.tree import TreeTypes
 from copulas.multivariate.vine import VineCopula
+
 from tests import compare_nested_dicts, compare_nested_iterables
 
 
@@ -203,9 +203,7 @@ def test_sample_random_state(self):
         X = pd.DataFrame([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]])
         vine.fit(X)
 
-        expected_result = pd.DataFrame(
-            [[0.101933, 0.527734, 0.080266, 0.078328]], columns=range(4)
-        )
+        expected_result = pd.DataFrame([[0.101933, 0.527734, 0.080266, 0.078328]], columns=range(4))
 
         # Run
         result = vine.sample(1)

tests/unit/optimize/test___init__.py

@@ -1,7 +1,6 @@
 from unittest import TestCase
 
 import numpy as np
-
 from copulas.optimize import bisect, chandrupatla
 
 

tests/unit/test___init__.py

@@ -2,12 +2,10 @@
 from unittest import TestCase
 from unittest.mock import MagicMock, call, patch
 
+import copulas
 import numpy as np
 import pandas as pd
 import pytest
-from numpy.testing import assert_array_equal
-
-import copulas
 from copulas import (
     _find_addons,
     check_valid_values,
@@ -18,6 +16,7 @@
     vectorize,
 )
 from copulas.multivariate import GaussianMultivariate
+from numpy.testing import assert_array_equal
 
 
 class TestVectorize(TestCase):

tests/unit/univariate/test_base.py

@@ -1,7 +1,6 @@
 from unittest.mock import patch
 
 import numpy as np
-
 from copulas.univariate.base import BoundedType, ParametricType, Univariate
 from copulas.univariate.beta import BetaUnivariate
 from copulas.univariate.gamma import GammaUnivariate
@@ -11,6 +10,7 @@
 from copulas.univariate.student_t import StudentTUnivariate
 from copulas.univariate.truncated_gaussian import TruncatedGaussian
 from copulas.univariate.uniform import UniformUnivariate
+
 from tests import compare_nested_iterables
 
 

tests/unit/univariate/test_beta.py

@@ -2,9 +2,8 @@
 from unittest.mock import patch
 
 import numpy as np
-from scipy.stats import beta
-
 from copulas.univariate import BetaUnivariate
+from scipy.stats import beta
 
 
 class TestBetaUnivariate(TestCase):

tests/unit/univariate/test_gamma.py

@@ -1,9 +1,8 @@
 from unittest import TestCase
 
 import numpy as np
-from scipy.stats import gamma
-
 from copulas.univariate import GammaUnivariate
+from scipy.stats import gamma
 
 
 class TestGammaUnivariate(TestCase):

tests/unit/univariate/test_gaussian.py

@@ -1,9 +1,8 @@
 from unittest import TestCase
 
 import numpy as np
-from scipy.stats import norm
-
 from copulas.univariate.gaussian import GaussianUnivariate
+from scipy.stats import norm
 
 
 class TestGaussianUnivariate(TestCase):

tests/unit/univariate/test_gaussian_kde.py

@@ -8,10 +8,9 @@
 
 import numpy as np
 import pytest
-from scipy.stats import gaussian_kde
-
 from copulas.datasets import sample_univariate_bimodal
 from copulas.univariate.gaussian_kde import GaussianKDE
+from scipy.stats import gaussian_kde
 
 
 class TestGaussianKDE(TestCase):