remove dead code

Author: glemaitre

imblearn/base.py

@@ -7,18 +7,14 @@
 from abc import ABCMeta, abstractmethod
 
 import numpy as np
-import sklearn
 from sklearn.base import BaseEstimator, OneToOneFeatureMixin
 from sklearn.preprocessing import label_binarize
-from sklearn.utils.fixes import parse_version
 from sklearn.utils.multiclass import check_classification_targets
 
 from .utils import check_sampling_strategy, check_target_type
 from .utils._param_validation import validate_parameter_constraints
 from .utils._validation import ArraysTransformer
 
-sklearn_version = parse_version(sklearn.__version__)
-
 
 class _ParamsValidationMixin:
     """Mixin class to validate parameters."""

imblearn/ensemble/tests/test_bagging.py

@@ -7,7 +7,6 @@
 
 import numpy as np
 import pytest
-import sklearn
 from sklearn.cluster import KMeans
 from sklearn.datasets import load_iris, make_classification, make_hastie_10_2
 from sklearn.dummy import DummyClassifier
@@ -22,7 +21,6 @@
     assert_array_almost_equal,
     assert_array_equal,
 )
-from sklearn.utils.fixes import parse_version
 
 from imblearn import FunctionSampler
 from imblearn.datasets import make_imbalance
@@ -31,7 +29,6 @@
 from imblearn.pipeline import make_pipeline
 from imblearn.under_sampling import ClusterCentroids, RandomUnderSampler
 
-sklearn_version = parse_version(sklearn.__version__)
 iris = load_iris()
 
 

imblearn/ensemble/tests/test_easy_ensemble.py

@@ -5,20 +5,17 @@
 
 import numpy as np
 import pytest
-import sklearn
 from sklearn.datasets import load_iris, make_hastie_10_2
 from sklearn.ensemble import AdaBoostClassifier
 from sklearn.feature_selection import SelectKBest
 from sklearn.model_selection import GridSearchCV, train_test_split
 from sklearn.utils._testing import assert_allclose, assert_array_equal
-from sklearn.utils.fixes import parse_version
 
 from imblearn.datasets import make_imbalance
 from imblearn.ensemble import EasyEnsembleClassifier
 from imblearn.pipeline import make_pipeline
 from imblearn.under_sampling import RandomUnderSampler
 
-sklearn_version = parse_version(sklearn.__version__)
 iris = load_iris()
 
 # Generate a global dataset to use

imblearn/ensemble/tests/test_weight_boosting.py

@@ -1,15 +1,11 @@
 import numpy as np
 import pytest
-import sklearn
 from sklearn.datasets import make_classification
 from sklearn.model_selection import train_test_split
 from sklearn.utils._testing import assert_array_equal
-from sklearn.utils.fixes import parse_version
 
 from imblearn.ensemble import RUSBoostClassifier
 
-sklearn_version = parse_version(sklearn.__version__)
-
 
 @pytest.fixture
 def imbalanced_dataset():

imblearn/over_sampling/_smote/tests/test_smote_nc.py

@@ -8,21 +8,17 @@
 
 import numpy as np
 import pytest
-import sklearn
 from scipy import sparse
 from sklearn.datasets import make_classification
 from sklearn.preprocessing import OneHotEncoder
 from sklearn.utils._testing import assert_allclose, assert_array_equal
-from sklearn.utils.fixes import parse_version
 
 from imblearn.over_sampling import SMOTENC
 from imblearn.utils.estimator_checks import (
     _set_checking_parameters,
     check_param_validation,
 )
 
-sklearn_version = parse_version(sklearn.__version__)
-
 
 def data_heterogneous_ordered():
     rng = np.random.RandomState(42)

imblearn/tests/test_pipeline.py

@@ -13,7 +13,6 @@
 
 import numpy as np
 import pytest
-import sklearn
 from joblib import Memory
 from pytest import raises
 from sklearn.base import BaseEstimator, clone
@@ -31,16 +30,13 @@
     assert_array_almost_equal,
     assert_array_equal,
 )
-from sklearn.utils.fixes import parse_version
 
 from imblearn.datasets import make_imbalance
 from imblearn.pipeline import Pipeline, make_pipeline
 from imblearn.under_sampling import EditedNearestNeighbours as ENN
 from imblearn.under_sampling import RandomUnderSampler
 from imblearn.utils.estimator_checks import check_param_validation
 
-sklearn_version = parse_version(sklearn.__version__)
-
 JUNK_FOOD_DOCS = (
     "the pizza pizza beer copyright",
     "the pizza burger beer copyright",

imblearn/utils/_param_validation.py

@@ -13,9 +13,9 @@
 import sklearn
 from scipy.sparse import csr_matrix, issparse
 from sklearn.utils.fixes import parse_version
+from sklearn.utils.validation import _is_arraylike_not_scalar
 
 from .._config import config_context, get_config
-from ..utils.fixes import _is_arraylike_not_scalar
 
 sklearn_version = parse_version(sklearn.__version__)
 

imblearn/utils/fixes.py

@@ -7,7 +7,6 @@
 import functools
 import sys
 
-import numpy as np
 import scipy
 import scipy.stats
 import sklearn
@@ -26,17 +25,6 @@ def _mode(a, axis=0):
     return scipy.stats.mode(a, axis=axis)
 
 
-# TODO: Remove when scikit-learn 1.1 is the minimum supported version
-if sklearn_version >= parse_version("1.1"):
-    from sklearn.utils.validation import _is_arraylike_not_scalar
-else:
-    from sklearn.utils.validation import _is_arraylike
-
-    def _is_arraylike_not_scalar(array):
-        """Return True if array is array-like and not a scalar"""
-        return _is_arraylike(array) and not np.isscalar(array)
-
-
 # TODO: remove when scikit-learn minimum version is 1.3
 if sklearn_version < parse_version("1.3"):