iter

glemaitre · glemaitre · commit bc61175f2f50 · 2024-12-16T22:25:48.000+01:00
diff --git a/imblearn/base.py b/imblearn/base.py
@@ -183,7 +183,7 @@ def _more_tags(self):
 
     def __sklearn_tags__(self):
         from .utils._sklearn_compat import TargetTags
-        from .utils._tags import Tags, SamplerTags, InputTags
+        from .utils._tags import InputTags, SamplerTags, Tags
 
         tags = Tags(
             estimator_type="sampler",
diff --git a/imblearn/ensemble/_bagging.py b/imblearn/ensemble/_bagging.py
@@ -14,11 +14,11 @@
 from sklearn.ensemble._bagging import _parallel_decision_function
 from sklearn.ensemble._base import _partition_estimators
 from sklearn.tree import DecisionTreeClassifier
+from sklearn.utils._param_validation import HasMethods, Interval, StrOptions
 from sklearn.utils.fixes import parse_version
 from sklearn.utils.metaestimators import available_if
 from sklearn.utils.parallel import Parallel, delayed
 from sklearn.utils.validation import check_is_fitted
-from sklearn.utils._param_validation import HasMethods, Interval, StrOptions
 
 from ..pipeline import Pipeline
 from ..under_sampling import RandomUnderSampler
diff --git a/imblearn/ensemble/_common.py b/imblearn/ensemble/_common.py
@@ -1,7 +1,6 @@
 from numbers import Integral, Real
 
 from sklearn.tree._criterion import Criterion
-
 from sklearn.utils._param_validation import (
     HasMethods,
     Hidden,
diff --git a/imblearn/ensemble/_easy_ensemble.py b/imblearn/ensemble/_easy_ensemble.py
@@ -14,12 +14,12 @@
 from sklearn.ensemble import AdaBoostClassifier, BaggingClassifier
 from sklearn.ensemble._bagging import _parallel_decision_function
 from sklearn.ensemble._base import _partition_estimators
+from sklearn.utils._param_validation import Interval, StrOptions
 from sklearn.utils._tags import _safe_tags
 from sklearn.utils.fixes import parse_version
 from sklearn.utils.metaestimators import available_if
 from sklearn.utils.parallel import Parallel, delayed
 from sklearn.utils.validation import check_is_fitted
-from sklearn.utils._param_validation import Interval, StrOptions
 
 from ..pipeline import Pipeline
 from ..under_sampling import RandomUnderSampler
diff --git a/imblearn/ensemble/_forest.py b/imblearn/ensemble/_forest.py
@@ -23,11 +23,11 @@
 from sklearn.exceptions import DataConversionWarning
 from sklearn.tree import DecisionTreeClassifier
 from sklearn.utils import _safe_indexing, check_random_state
+from sklearn.utils._param_validation import Hidden, Interval, StrOptions
 from sklearn.utils.fixes import parse_version
 from sklearn.utils.multiclass import type_of_target
 from sklearn.utils.parallel import Parallel, delayed
 from sklearn.utils.validation import _check_sample_weight
-from sklearn.utils._param_validation import Hidden, Interval, StrOptions
 
 from ..pipeline import make_pipeline
 from ..under_sampling import RandomUnderSampler
@@ -888,4 +888,4 @@ def __sklearn_tags__(self):
         tags.target_tags.multi_output = False
         tags.classifier_tags.multi_label = False
         tags.input_tags.allow_nan = sklearn_version >= parse_version("1.4")
-        return tags
+        return tags
diff --git a/imblearn/ensemble/_weight_boosting.py b/imblearn/ensemble/_weight_boosting.py
@@ -10,9 +10,9 @@
 from sklearn.ensemble._base import _set_random_states
 from sklearn.tree import DecisionTreeClassifier
 from sklearn.utils import _safe_indexing
+from sklearn.utils._param_validation import Hidden, Interval, StrOptions
 from sklearn.utils.fixes import parse_version
 from sklearn.utils.validation import has_fit_parameter
-from sklearn.utils._param_validation import Hidden, Interval, StrOptions
 
 from ..pipeline import make_pipeline
 from ..under_sampling import RandomUnderSampler
@@ -402,8 +402,10 @@ def _boost_discrete(self, iboost, X, y, sample_weight, random_state):
     def _boost(self, iboost, X, y, sample_weight, random_state):
         if self.algorithm != "deprecated":
             warnings.warn(
-                "`algorithm` parameter is deprecated in 0.12 and will be removed in "
-                "0.14. In the future, the SAMME algorithm will always be used.",
+                (
+                    "`algorithm` parameter is deprecated in 0.12 and will be removed in"
+                    " 0.14. In the future, the SAMME algorithm will always be used."
+                ),
                 FutureWarning,
             )
         if self.algorithm == "SAMME.R":
diff --git a/imblearn/ensemble/tests/test_weight_boosting.py b/imblearn/ensemble/tests/test_weight_boosting.py
@@ -59,7 +59,7 @@ def test_rusboost(imbalanced_dataset):
     assert rusboost.decision_function(X_test).shape[1] == len(classes)
 
     score = rusboost.score(X_test, y_test)
-    assert score > 0.6, f"Failed with algorithm {algorithm} and score {score}"
+    assert score > 0.6, f"Failed with score {score}"
 
     y_pred = rusboost.predict(X_test)
     assert y_pred.shape == y_test.shape
diff --git a/imblearn/metrics/_classification.py b/imblearn/metrics/_classification.py
@@ -24,9 +24,9 @@
 from sklearn.metrics import mean_absolute_error, precision_recall_fscore_support
 from sklearn.metrics._classification import _check_targets, _prf_divide
 from sklearn.preprocessing import LabelEncoder
+from sklearn.utils._param_validation import Interval, StrOptions, validate_params
 from sklearn.utils.multiclass import unique_labels
 from sklearn.utils.validation import check_consistent_length, column_or_1d
-from sklearn.utils._param_validation import Interval, StrOptions, validate_params
 
 
 @validate_params(
diff --git a/imblearn/metrics/pairwise.py b/imblearn/metrics/pairwise.py
@@ -9,9 +9,9 @@
 from scipy.spatial import distance_matrix
 from sklearn.base import BaseEstimator
 from sklearn.utils import check_consistent_length
+from sklearn.utils._param_validation import StrOptions
 from sklearn.utils.multiclass import unique_labels
 from sklearn.utils.validation import check_is_fitted
-from sklearn.utils._param_validation import StrOptions
 
 from ..utils._sklearn_compat import _fit_context, check_array, validate_data
 
@@ -234,7 +234,6 @@ def _more_tags(self):
             "requires_positive_X": True,  # X should be encoded with OrdinalEncoder
         }
 
-
     def __sklearn_tags__(self):
         tags = super().__sklearn_tags__()
         tags.input_tags.positive_only = True
diff --git a/imblearn/over_sampling/_random_over_sampler.py b/imblearn/over_sampling/_random_over_sampler.py
@@ -10,8 +10,8 @@
 import numpy as np
 from scipy import sparse
 from sklearn.utils import _safe_indexing, check_array, check_random_state
-from sklearn.utils.sparsefuncs import mean_variance_axis
 from sklearn.utils._param_validation import Interval
+from sklearn.utils.sparsefuncs import mean_variance_axis
 
 from ..utils import Substitution, check_target_type
 from ..utils._docstring import _random_state_docstring
@@ -264,4 +264,4 @@ def __sklearn_tags__(self):
         tags.input_tags.allow_nan = True
         tags.input_tags.string = True
         tags.sampler_tags.sample_indices = True
-        return tags
+        return tags
diff --git a/imblearn/over_sampling/_smote/base.py b/imblearn/over_sampling/_smote/base.py
@@ -21,12 +21,12 @@
     check_array,
     check_random_state,
 )
+from sklearn.utils._param_validation import HasMethods, Interval, StrOptions
 from sklearn.utils.fixes import parse_version
 from sklearn.utils.sparsefuncs_fast import (
     csr_mean_variance_axis0,
 )
 from sklearn.utils.validation import _num_features
-from sklearn.utils._param_validation import HasMethods, Interval, StrOptions
 
 from ...metrics.pairwise import ValueDifferenceMetric
 from ...utils import Substitution, check_neighbors_object, check_target_type
diff --git a/imblearn/over_sampling/_smote/tests/test_smote_nc.py b/imblearn/over_sampling/_smote/tests/test_smote_nc.py
@@ -14,6 +14,7 @@
 from sklearn.utils._testing import assert_allclose, assert_array_equal
 
 from imblearn.over_sampling import SMOTENC
+
 # from imblearn.utils.estimator_checks import (
 #     _set_checking_parameters,
 #     check_param_validation,
diff --git a/imblearn/pipeline.py b/imblearn/pipeline.py
@@ -15,30 +15,29 @@
 # License: BSD
 import warnings
 from contextlib import contextmanager
-from copy import deepcopy
 
 import sklearn
 from sklearn import pipeline
 from sklearn.base import clone
 from sklearn.exceptions import NotFittedError
 from sklearn.utils import Bunch
-from sklearn.utils.fixes import parse_version
-from sklearn.utils.metaestimators import available_if
-from sklearn.utils.validation import check_memory, check_is_fitted
-
 from sklearn.utils._metadata_requests import (
     METHODS,
     MetadataRouter,
     MethodMapping,
     _raise_for_params,
     _routing_enabled,
+    get_routing_for_object,
     process_routing,
 )
 from sklearn.utils._param_validation import HasMethods
+from sklearn.utils.fixes import parse_version
+from sklearn.utils.metaestimators import available_if
+from sklearn.utils.validation import check_is_fitted, check_memory
+
 from .utils._sklearn_compat import (
     _fit_context,
     _print_elapsed_time,
-    get_tags,
     validate_params,
 )
 
@@ -66,10 +65,12 @@ def _raise_or_warn_if_not_fitted(estimator):
         check_is_fitted(estimator)
     except NotFittedError:
         warnings.warn(
-            "This Pipeline instance is not fitted yet. Call 'fit' with "
-            "appropriate arguments before using other methods such as transform, "
-            "predict, etc. This will raise an error in 1.8 instead of the current "
-            "warning.",
+            (
+                "This Pipeline instance is not fitted yet. Call 'fit' with "
+                "appropriate arguments before using other methods such as transform, "
+                "predict, etc. This will raise an error in 1.8 instead of the current "
+                "warning."
+            ),
             FutureWarning,
         )
 
diff --git a/imblearn/tests/test_common.py b/imblearn/tests/test_common.py
@@ -10,28 +10,27 @@
 import numpy as np
 import pytest
 import sklearn
-from sklearn.base import clone
 from sklearn.exceptions import ConvergenceWarning
-from sklearn.utils.fixes import parse_version
 from sklearn.utils._testing import ignore_warnings
 from sklearn.utils.estimator_checks import (
     parametrize_with_checks as parametrize_with_checks_sklearn,
 )
+from sklearn.utils.fixes import parse_version
 
 from imblearn.over_sampling import RandomOverSampler
-from imblearn.under_sampling import NearMiss, RandomUnderSampler
+from imblearn.under_sampling import RandomUnderSampler
+from imblearn.utils._test_common.instance_generator import (
+    _get_check_estimator_ids,
+    _get_expected_failed_checks,
+    _tested_estimators,
+)
 from imblearn.utils.estimator_checks import (
     _set_checking_parameters,
     check_dataframe_column_names_consistency,
     check_param_validation,
     parametrize_with_checks,
 )
 from imblearn.utils.testing import all_estimators
-from imblearn.utils._test_common.instance_generator import (
-    _get_check_estimator_ids,
-    _get_expected_failed_checks,
-    _tested_estimators,
-)
 
 sklearn_version = parse_version(parse_version(sklearn.__version__).base_version)
 if sklearn_version >= parse_version("1.6"):
diff --git a/imblearn/tests/test_docstring_parameters.py b/imblearn/tests/test_docstring_parameters.py
@@ -24,9 +24,9 @@
 
 import imblearn
 from imblearn.base import is_sampler
+from imblearn.utils._sklearn_compat import _construct_instances
 from imblearn.utils.estimator_checks import _set_checking_parameters
 from imblearn.utils.testing import all_estimators
-from imblearn.utils._sklearn_compat import _construct_instances
 
 # walk_packages() ignores DeprecationWarnings, now we need to ignore
 # FutureWarnings
diff --git a/imblearn/tests/test_public_functions.py b/imblearn/tests/test_public_functions.py
@@ -5,7 +5,6 @@
 from inspect import signature
 
 import pytest
-
 from sklearn.utils._param_validation import (
     generate_invalid_param_val,
     generate_valid_param,
diff --git a/imblearn/utils/_sklearn_compat.py b/imblearn/utils/_sklearn_compat.py
@@ -19,7 +19,6 @@
 from typing import Callable, Literal
 
 import sklearn
-from sklearn.utils._param_validation import validate_parameter_constraints
 from sklearn.utils.fixes import parse_version
 
 sklearn_version = parse_version(parse_version(sklearn.__version__).base_version)
diff --git a/imblearn/utils/_tags.py b/imblearn/utils/_tags.py
@@ -1,6 +1,6 @@
 from dataclasses import dataclass
 
-from ._sklearn_compat import _dataclass_args, InputTags, Tags
+from ._sklearn_compat import InputTags, Tags, _dataclass_args
 
 
 @dataclass(**_dataclass_args())
diff --git a/imblearn/utils/_test_common/instance_generator.py b/imblearn/utils/_test_common/instance_generator.py
@@ -9,9 +9,9 @@
 from inspect import isfunction
 
 from sklearn import clone, config_context
+from sklearn.exceptions import SkipTestWarning
 from sklearn.linear_model import LogisticRegression
 from sklearn.tree import DecisionTreeClassifier
-from sklearn.exceptions import SkipTestWarning
 from sklearn.utils._testing import SkipTest
 
 from imblearn.combine import SMOTEENN, SMOTETomek
@@ -23,13 +23,13 @@
 )
 from imblearn.over_sampling import (
     ADASYN,
-    BorderlineSMOTE,
-    KMeansSMOTE,
-    RandomOverSampler,
     SMOTE,
     SMOTEN,
     SMOTENC,
     SVMSMOTE,
+    BorderlineSMOTE,
+    KMeansSMOTE,
+    RandomOverSampler,
 )
 from imblearn.pipeline import Pipeline
 from imblearn.under_sampling import (
@@ -218,7 +218,8 @@ def _yield_instances_for_check(check, estimator_orig):
     },
 }
 
+
 def _get_expected_failed_checks(estimator):
     """Get the expected failed checks for all estimators in scikit-learn."""
     failed_checks = PER_ESTIMATOR_XFAIL_CHECKS.get(type(estimator), {})
-    return failed_checks
+    return failed_checks
diff --git a/imblearn/utils/_validation.py b/imblearn/utils/_validation.py
@@ -17,8 +17,8 @@
 from sklearn.utils.multiclass import type_of_target
 from sklearn.utils.validation import _num_samples
 
-from .fixes import _is_pandas_df
 from ..utils._sklearn_compat import check_array
+from .fixes import _is_pandas_df
 
 SAMPLING_KIND = (
     "over-sampling",
diff --git a/imblearn/utils/estimator_checks.py b/imblearn/utils/estimator_checks.py
@@ -25,6 +25,7 @@
 )
 from sklearn.exceptions import SkipTestWarning
 from sklearn.preprocessing import StandardScaler, label_binarize
+from sklearn.utils._param_validation import generate_invalid_param_val, make_constraint
 from sklearn.utils._testing import (
     SkipTest,
     assert_allclose,
@@ -33,20 +34,20 @@
     set_random_state,
 )
 from sklearn.utils.estimator_checks import (
-    _enforce_estimator_tags_X, _enforce_estimator_tags_y
+    _enforce_estimator_tags_X,
+    _enforce_estimator_tags_y,
 )
 from sklearn.utils.fixes import parse_version
 from sklearn.utils.multiclass import type_of_target
-from sklearn.utils._param_validation import generate_invalid_param_val, make_constraint
-
 
 from imblearn.datasets import make_imbalance
 from imblearn.over_sampling.base import BaseOverSampler
 from imblearn.under_sampling.base import BaseCleaningSampler, BaseUnderSampler
+from imblearn.utils._sklearn_compat import get_tags
 from imblearn.utils._test_common.instance_generator import (
-    _get_check_estimator_ids, _yield_instances_for_check
+    _get_check_estimator_ids,
+    _yield_instances_for_check,
 )
-from imblearn.utils._sklearn_compat import get_tags
 
 sklearn_version = parse_version(sklearn.__version__)
 
diff --git a/pyproject.toml b/pyproject.toml
@@ -216,7 +216,7 @@ ci-py313-latest-optional-dependencies = ["py313", "optional", "tests"]
 
 [tool.black]
 line-length = 88
-target_version = ['py310', 'py311', 'py312', 'py313']
+target_version = ['py310', 'py311']
 preview = true
 # Exclude irrelevant directories for formatting
 exclude = '''
