Move import statements for codebase coherence.

imblearn/combine/tests/test_smote_enn.py

@@ -6,9 +6,10 @@
 from __future__ import print_function
 
 import numpy as np
-from sklearn.utils.testing import assert_allclose, assert_array_equal
 from pytest import raises
 
+from sklearn.utils.testing import assert_allclose, assert_array_equal
+
 from imblearn.combine import SMOTEENN
 from imblearn.under_sampling import EditedNearestNeighbours
 from imblearn.over_sampling import SMOTE

imblearn/combine/tests/test_smote_tomek.py

@@ -6,9 +6,10 @@
 from __future__ import print_function
 
 import numpy as np
-from sklearn.utils.testing import assert_allclose, assert_array_equal
 from pytest import raises
 
+from sklearn.utils.testing import assert_allclose, assert_array_equal
+
 from imblearn.combine import SMOTETomek
 from imblearn.over_sampling import SMOTE
 from imblearn.under_sampling import TomekLinks

imblearn/datasets/tests/test_imbalance.py

@@ -10,11 +10,11 @@
 
 import numpy as np
 
-from sklearn.datasets import load_iris
-from imblearn.utils.testing import warns
-
 from pytest import raises
 
+from sklearn.datasets import load_iris
+
+from imblearn.utils.testing import warns
 from imblearn.datasets import make_imbalance
 
 data = load_iris()

imblearn/ensemble/tests/test_balance_cascade.py

@@ -6,13 +6,14 @@
 from __future__ import print_function
 
 import numpy as np
-from sklearn.utils.testing import assert_array_equal
 
+from pytest import raises
+
+from sklearn.utils.testing import assert_array_equal
 from sklearn.ensemble import RandomForestClassifier
 
 from imblearn.ensemble import BalanceCascade
 
-from pytest import raises
 
 RND_SEED = 0
 X = np.array([[0.11622591, -0.0317206], [0.77481731, 0.60935141],

imblearn/metrics/tests/test_classification.py

@@ -10,6 +10,8 @@
 
 import numpy as np
 
+from pytest import approx, raises
+
 from sklearn import datasets
 from sklearn import svm
 
@@ -31,7 +33,6 @@
 from imblearn.metrics import make_index_balanced_accuracy
 from imblearn.metrics import classification_report_imbalanced
 
-from pytest import approx, raises
 from imblearn.utils.testing import warns
 
 

imblearn/over_sampling/tests/test_adasyn.py

@@ -6,12 +6,13 @@
 from __future__ import print_function
 
 import numpy as np
+from pytest import raises
+
 from sklearn.utils.testing import assert_allclose, assert_array_equal
 from sklearn.neighbors import NearestNeighbors
 
 from imblearn.over_sampling import ADASYN
 
-from pytest import raises
 
 RND_SEED = 0
 X = np.array([[0.11622591, -0.0317206], [0.77481731, 0.60935141],

imblearn/over_sampling/tests/test_smote.py

@@ -6,13 +6,14 @@
 from __future__ import print_function
 
 import numpy as np
+from pytest import raises
+
 from sklearn.utils.testing import assert_allclose, assert_array_equal
 from sklearn.neighbors import NearestNeighbors
 from sklearn.svm import SVC
 
 from imblearn.over_sampling import SMOTE
 
-from pytest import raises
 
 RND_SEED = 0
 X = np.array([[0.11622591, -0.0317206], [0.77481731, 0.60935141],

imblearn/tests/test_exceptions.py

@@ -3,11 +3,10 @@
 #          Christos Aridas
 # License: MIT
 
+from pytest import raises
 
 from imblearn.exceptions import raise_isinstance_error
 
-from pytest import raises
-
 
 def test_raise_isinstance_error():
     var = 10.0

imblearn/tests/test_pipeline.py

@@ -11,6 +11,8 @@
 import time
 
 import numpy as np
+from pytest import raises
+
 from sklearn.utils.testing import assert_array_equal
 from sklearn.utils.testing import assert_array_almost_equal
 from sklearn.utils.testing import assert_allclose
@@ -30,7 +32,6 @@
 from imblearn.under_sampling import (RandomUnderSampler,
                                      EditedNearestNeighbours as ENN)
 
-from pytest import raises
 
 JUNK_FOOD_DOCS = (
     "the pizza pizza beer copyright",

imblearn/under_sampling/prototype_generation/tests/test_cluster_centroids.py

@@ -4,9 +4,10 @@
 from collections import Counter
 
 import numpy as np
+from pytest import raises
+
 from sklearn.utils.testing import assert_allclose
 from sklearn.utils.testing import assert_array_equal
-from pytest import raises
 
 from sklearn.cluster import KMeans
 

imblearn/under_sampling/prototype_selection/tests/test_allknn.py

@@ -6,13 +6,14 @@
 from __future__ import print_function
 
 import numpy as np
+from pytest import raises
+
 from sklearn.utils.testing import assert_allclose, assert_array_equal
 from sklearn.neighbors import NearestNeighbors
 from sklearn.datasets import make_classification
 
 from imblearn.under_sampling import AllKNN
 
-from pytest import raises
 
 RND_SEED = 0
 X = np.array([[-0.12840393, 0.66446571], [1.32319756, -0.13181616],

imblearn/under_sampling/prototype_selection/tests/test_edited_nearest_neighbours.py

@@ -6,9 +6,10 @@
 from __future__ import print_function
 
 import numpy as np
-from sklearn.utils.testing import assert_array_equal
 from pytest import raises
 
+from sklearn.utils.testing import assert_array_equal
+
 from sklearn.neighbors import NearestNeighbors
 
 from imblearn.under_sampling import EditedNearestNeighbours

imblearn/under_sampling/prototype_selection/tests/test_instance_hardness_threshold.py

@@ -6,13 +6,13 @@
 from __future__ import print_function
 
 import numpy as np
+from pytest import raises
+
 from sklearn.utils.testing import assert_array_equal
 from sklearn.ensemble import GradientBoostingClassifier
-from pytest import raises
 
 from imblearn.under_sampling import InstanceHardnessThreshold
 
-from pytest import raises
 
 RND_SEED = 0
 X = np.array([[-0.3879569, 0.6894251], [-0.09322739, 1.28177189],

imblearn/under_sampling/prototype_selection/tests/test_nearmiss.py

@@ -6,13 +6,15 @@
 from __future__ import print_function
 
 import numpy as np
+from pytest import raises
+
 from sklearn.utils.testing import assert_array_equal
-from imblearn.utils.testing import warns
 from sklearn.neighbors import NearestNeighbors
-from pytest import raises
 
 from imblearn.under_sampling import NearMiss
 
+from imblearn.utils.testing import warns
+
 RND_SEED = 0
 X = np.array([[1.17737838, -0.2002118],
               [0.4960075, 0.86130762],

imblearn/under_sampling/prototype_selection/tests/test_neighbourhood_cleaning_rule.py

@@ -3,12 +3,11 @@
 #          Christos Aridas
 # License: MIT
 
-from __future__ import print_function
-
 import numpy as np
-from sklearn.utils.testing import assert_array_equal
 from pytest import raises
 
+from sklearn.utils.testing import assert_array_equal
+
 from sklearn.neighbors import NearestNeighbors
 
 from imblearn.under_sampling import NeighbourhoodCleaningRule

imblearn/under_sampling/prototype_selection/tests/test_one_sided_selection.py

@@ -6,9 +6,10 @@
 from __future__ import print_function
 
 import numpy as np
-from sklearn.utils.testing import assert_array_equal
 from pytest import raises
 
+from sklearn.utils.testing import assert_array_equal
+
 from sklearn.neighbors import KNeighborsClassifier
 
 from imblearn.under_sampling import OneSidedSelection

imblearn/utils/estimator_checks.py

@@ -12,14 +12,13 @@
 from collections import Counter
 
 import numpy as np
+from pytest import raises
 
 from sklearn.datasets import make_classification
 from sklearn.utils.estimator_checks import _yield_all_checks \
     as sklearn_yield_all_checks, check_estimator \
     as sklearn_check_estimator, check_parameters_default_constructible
 from sklearn.exceptions import NotFittedError
-from pytest import raises
-from imblearn.utils.testing import warns
 
 from sklearn.utils.testing import set_random_state
 
@@ -28,6 +27,8 @@
 from imblearn.under_sampling.base import BaseCleaningSampler, BaseUnderSampler
 from imblearn.ensemble.base import BaseEnsembleSampler
 
+from imblearn.utils.testing import warns
+
 
 def _yield_sampler_checks(name, Estimator):
     yield check_target_type

imblearn/utils/testing.py

@@ -6,17 +6,16 @@
 
 import inspect
 import pkgutil
+from contextlib import contextmanager
+from re import compile
 
 from operator import itemgetter
-
-import imblearn
-from imblearn.base import SamplerMixin
+from pytest import warns as _warns
 
 from sklearn.base import BaseEstimator
 
-from pytest import warns as _warns
-from contextlib import contextmanager
-from re import compile
+from imblearn.base import SamplerMixin
+import imblearn
 
 
 # meta-estimators need another estimator to be instantiated.

imblearn/utils/tests/test_estimator_checks.py

@@ -1,16 +1,17 @@
 """Estimator tests - adapted from scikit-learn"""
+import sys
+
 import scipy.sparse as sp
 import numpy as np
-import sys
+from pytest import raises
+
 from sklearn.externals.six.moves import cStringIO as StringIO
 
 from sklearn.base import BaseEstimator, ClassifierMixin
 from sklearn.utils.validation import check_X_y, check_array
 
 from imblearn.utils.estimator_checks import check_estimator
 
-from pytest import raises
-
 
 class CorrectNotFittedError(ValueError):
     """Exception class to raise if estimator is used before fitting.

imblearn/utils/tests/test_validation.py

@@ -5,13 +5,13 @@
 
 from collections import Counter
 
+from pytest import raises
 import numpy as np
 
 from sklearn.neighbors.base import KNeighborsMixin
 from sklearn.neighbors import NearestNeighbors
 
 from imblearn.utils.testing import warns
-from pytest import raises
 
 from imblearn.utils import check_neighbors_object
 from imblearn.utils import check_ratio