From 1731b88096e8ecf40614140b9ba23c298384007e Mon Sep 17 00:00:00 2001 From: chkoar Date: Tue, 18 Oct 2016 16:25:57 +0300 Subject: [PATCH] Reorganize imports --- doc/conf.py | 2 +- examples/combine/plot_smote_enn.py | 8 +++-- examples/combine/plot_smote_tomek.py | 8 +++-- examples/datasets/plot_make_imbalance.py | 6 ++-- examples/ensemble/plot_balance_cascade.py | 10 ++++--- examples/ensemble/plot_easy_ensemble.py | 10 ++++--- examples/over-sampling/plot_adasyn.py | 8 +++-- .../plot_random_over_sampling.py | 8 +++-- examples/over-sampling/plot_smote.py | 8 +++-- .../over-sampling/plot_smote_bordeline_1.py | 8 +++-- .../over-sampling/plot_smote_bordeline_2.py | 8 +++-- examples/over-sampling/plot_smote_svm.py | 8 +++-- .../pipeline/plot_pipeline_classification.py | 7 ++--- examples/under-sampling/plot_allknn.py | 11 +++---- .../under-sampling/plot_cluster_centroids.py | 8 +++-- .../plot_condensed_nearest_neighbour.py | 8 +++-- .../plot_edited_nearest_neighbours.py | 8 +++-- .../plot_instance_hardness_threshold.py | 8 +++-- examples/under-sampling/plot_nearmiss_1.py | 8 +++-- examples/under-sampling/plot_nearmiss_2.py | 8 +++-- examples/under-sampling/plot_nearmiss_3.py | 8 +++-- .../plot_neighbourhood_cleaning_rule.py | 8 +++-- .../plot_one_sided_selection.py | 8 +++-- .../plot_random_under_sampler.py | 8 +++-- ...plot_repeated_edited_nearest_neighbours.py | 10 ++++--- examples/under-sampling/plot_tomek_links.py | 8 +++-- imblearn/base.py | 15 ++++------ imblearn/combine/smote_enn.py | 5 ++-- imblearn/combine/smote_tomek.py | 5 ++-- imblearn/combine/tests/test_smote_enn.py | 8 ++--- imblearn/combine/tests/test_smote_tomek.py | 8 ++--- imblearn/datasets/imbalance.py | 7 ++--- .../datasets/tests/test_make_imbalance.py | 7 ++--- imblearn/ensemble/balance_cascade.py | 2 -- imblearn/ensemble/easy_ensemble.py | 2 -- .../ensemble/tests/test_balance_cascade.py | 7 ++--- imblearn/ensemble/tests/test_easy_ensemble.py | 10 ++----- imblearn/over_sampling/adasyn.py | 6 ++-- imblearn/over_sampling/random_over_sampler.py | 6 ++-- imblearn/over_sampling/smote.py | 8 ++--- imblearn/over_sampling/tests/test_adasyn.py | 8 ++--- .../tests/test_random_over_sampler.py | 11 +++---- imblearn/over_sampling/tests/test_smote.py | 8 ++--- imblearn/pipeline.py | 5 ++-- imblearn/tests/test_pipeline.py | 30 +++++++------------ imblearn/under_sampling/cluster_centroids.py | 6 ++-- .../condensed_nearest_neighbour.py | 8 ++--- .../edited_nearest_neighbours.py | 8 ++--- .../instance_hardness_threshold.py | 7 ++--- imblearn/under_sampling/nearmiss.py | 7 ++--- .../neighbourhood_cleaning_rule.py | 6 ++-- .../under_sampling/one_sided_selection.py | 9 ++---- .../under_sampling/random_under_sampler.py | 6 ++-- imblearn/under_sampling/tests/test_allknn.py | 11 ++----- .../tests/test_cluster_centroids.py | 12 +++----- .../tests/test_condensed_nearest_neighbour.py | 10 ++----- .../tests/test_edited_nearest_neighbours.py | 10 ++----- .../tests/test_instance_hardness_threshold.py | 8 ++--- .../under_sampling/tests/test_nearmiss_1.py | 10 ++----- .../under_sampling/tests/test_nearmiss_2.py | 10 ++----- .../under_sampling/tests/test_nearmiss_3.py | 10 ++----- .../tests/test_neighbourhood_cleaning_rule.py | 10 ++----- .../tests/test_one_sided_selection.py | 10 ++----- .../tests/test_random_under_sampler.py | 11 +++---- ...test_repeated_edited_nearest_neighbours.py | 10 ++----- .../under_sampling/tests/test_tomek_links.py | 7 ++--- imblearn/under_sampling/tomek_links.py | 6 ++-- setup.py | 6 ++-- 68 files changed, 238 insertions(+), 326 deletions(-) diff --git a/doc/conf.py b/doc/conf.py index 6ba4298ff..05daf8d13 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -12,8 +12,8 @@ # All configuration values have a default; values that are commented out # serve to show the default. -import sys import os +import sys import sphinx_rtd_theme diff --git a/examples/combine/plot_smote_enn.py b/examples/combine/plot_smote_enn.py index 14b69649e..ec1f18404 100644 --- a/examples/combine/plot_smote_enn.py +++ b/examples/combine/plot_smote_enn.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.combine import SMOTEENN + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.combine import SMOTEENN # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/combine/plot_smote_tomek.py b/examples/combine/plot_smote_tomek.py index 69438d81c..28fd3fa39 100644 --- a/examples/combine/plot_smote_tomek.py +++ b/examples/combine/plot_smote_tomek.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.combine import SMOTETomek + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.combine import SMOTETomek # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/datasets/plot_make_imbalance.py b/examples/datasets/plot_make_imbalance.py index 12271fa27..e646edffb 100644 --- a/examples/datasets/plot_make_imbalance.py +++ b/examples/datasets/plot_make_imbalance.py @@ -11,14 +11,16 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_moons + +from imblearn.datasets import make_imbalance + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_moons -from imblearn.datasets import make_imbalance # Generate the dataset diff --git a/examples/ensemble/plot_balance_cascade.py b/examples/ensemble/plot_balance_cascade.py index 756f4460f..500f52da8 100644 --- a/examples/ensemble/plot_balance_cascade.py +++ b/examples/ensemble/plot_balance_cascade.py @@ -9,19 +9,21 @@ print(__doc__) -import numpy as np import matplotlib.pyplot as plt +import numpy as np import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.ensemble import BalanceCascade + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.ensemble import BalanceCascade # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/ensemble/plot_easy_ensemble.py b/examples/ensemble/plot_easy_ensemble.py index f2d36b507..0aba287d8 100644 --- a/examples/ensemble/plot_easy_ensemble.py +++ b/examples/ensemble/plot_easy_ensemble.py @@ -9,19 +9,21 @@ print(__doc__) -import numpy as np import matplotlib.pyplot as plt +import numpy as np import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.ensemble import EasyEnsemble + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.ensemble import EasyEnsemble # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/over-sampling/plot_adasyn.py b/examples/over-sampling/plot_adasyn.py index 70360222d..fc3fe8751 100644 --- a/examples/over-sampling/plot_adasyn.py +++ b/examples/over-sampling/plot_adasyn.py @@ -12,16 +12,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.over_sampling import ADASYN + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.over_sampling import ADASYN # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/over-sampling/plot_random_over_sampling.py b/examples/over-sampling/plot_random_over_sampling.py index eed901358..cd705461f 100644 --- a/examples/over-sampling/plot_random_over_sampling.py +++ b/examples/over-sampling/plot_random_over_sampling.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.over_sampling import RandomOverSampler + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.over_sampling import RandomOverSampler # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/over-sampling/plot_smote.py b/examples/over-sampling/plot_smote.py index 5737c6df6..755cae0e1 100644 --- a/examples/over-sampling/plot_smote.py +++ b/examples/over-sampling/plot_smote.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.over_sampling import SMOTE + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.over_sampling import SMOTE # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/over-sampling/plot_smote_bordeline_1.py b/examples/over-sampling/plot_smote_bordeline_1.py index cfeae700b..c4e82f705 100644 --- a/examples/over-sampling/plot_smote_bordeline_1.py +++ b/examples/over-sampling/plot_smote_bordeline_1.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.over_sampling import SMOTE + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.over_sampling import SMOTE # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/over-sampling/plot_smote_bordeline_2.py b/examples/over-sampling/plot_smote_bordeline_2.py index c797dc0d3..5c64cf056 100644 --- a/examples/over-sampling/plot_smote_bordeline_2.py +++ b/examples/over-sampling/plot_smote_bordeline_2.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.over_sampling import SMOTE + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.over_sampling import SMOTE # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/over-sampling/plot_smote_svm.py b/examples/over-sampling/plot_smote_svm.py index 2e4ed93a3..430494247 100644 --- a/examples/over-sampling/plot_smote_svm.py +++ b/examples/over-sampling/plot_smote_svm.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.over_sampling import SMOTE + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.over_sampling import SMOTE # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/pipeline/plot_pipeline_classification.py b/examples/pipeline/plot_pipeline_classification.py index eabbea77e..d120bfe8b 100644 --- a/examples/pipeline/plot_pipeline_classification.py +++ b/examples/pipeline/plot_pipeline_classification.py @@ -13,13 +13,12 @@ from sklearn.cross_validation import train_test_split as tts from sklearn.datasets import make_classification from sklearn.decomposition import PCA -from sklearn.neighbors import KNeighborsClassifier as KNN from sklearn.metrics import classification_report - +from sklearn.neighbors import KNeighborsClassifier as KNN from imblearn.pipeline import make_pipeline -from imblearn.under_sampling import EditedNearestNeighbours -from imblearn.under_sampling import RepeatedEditedNearestNeighbours +from imblearn.under_sampling import (EditedNearestNeighbours, + RepeatedEditedNearestNeighbours) # Generate the dataset X, y = make_classification(n_classes=2, class_sep=1.25, weights=[0.3, 0.7], diff --git a/examples/under-sampling/plot_allknn.py b/examples/under-sampling/plot_allknn.py index 8e7a0208e..660185e88 100644 --- a/examples/under-sampling/plot_allknn.py +++ b/examples/under-sampling/plot_allknn.py @@ -11,18 +11,19 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import (AllKNN, EditedNearestNeighbours, + RepeatedEditedNearestNeighbours) + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import EditedNearestNeighbours -from imblearn.under_sampling import RepeatedEditedNearestNeighbours -from imblearn.under_sampling import AllKNN # Generate the dataset X, y = make_classification(n_classes=2, class_sep=1.25, weights=[0.3, 0.7], diff --git a/examples/under-sampling/plot_cluster_centroids.py b/examples/under-sampling/plot_cluster_centroids.py index caf654b91..3e0e5f9d2 100644 --- a/examples/under-sampling/plot_cluster_centroids.py +++ b/examples/under-sampling/plot_cluster_centroids.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import ClusterCentroids + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import ClusterCentroids # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/under-sampling/plot_condensed_nearest_neighbour.py b/examples/under-sampling/plot_condensed_nearest_neighbour.py index d8afd5b7e..cfdebd915 100644 --- a/examples/under-sampling/plot_condensed_nearest_neighbour.py +++ b/examples/under-sampling/plot_condensed_nearest_neighbour.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import CondensedNearestNeighbour + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import CondensedNearestNeighbour # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/under-sampling/plot_edited_nearest_neighbours.py b/examples/under-sampling/plot_edited_nearest_neighbours.py index bbfea90ca..c00fc0abf 100644 --- a/examples/under-sampling/plot_edited_nearest_neighbours.py +++ b/examples/under-sampling/plot_edited_nearest_neighbours.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import EditedNearestNeighbours + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import EditedNearestNeighbours # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/under-sampling/plot_instance_hardness_threshold.py b/examples/under-sampling/plot_instance_hardness_threshold.py index 00189abee..72b848acc 100644 --- a/examples/under-sampling/plot_instance_hardness_threshold.py +++ b/examples/under-sampling/plot_instance_hardness_threshold.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import InstanceHardnessThreshold + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import InstanceHardnessThreshold # Generate the dataset X, y = make_classification(n_classes=2, class_sep=1., weights=[0.05, 0.95], diff --git a/examples/under-sampling/plot_nearmiss_1.py b/examples/under-sampling/plot_nearmiss_1.py index 58b292aff..0617e7c16 100644 --- a/examples/under-sampling/plot_nearmiss_1.py +++ b/examples/under-sampling/plot_nearmiss_1.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import NearMiss + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import NearMiss # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/under-sampling/plot_nearmiss_2.py b/examples/under-sampling/plot_nearmiss_2.py index 3125f501c..465580b48 100644 --- a/examples/under-sampling/plot_nearmiss_2.py +++ b/examples/under-sampling/plot_nearmiss_2.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import NearMiss + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import NearMiss # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/under-sampling/plot_nearmiss_3.py b/examples/under-sampling/plot_nearmiss_3.py index 2c81832c9..3b7233716 100644 --- a/examples/under-sampling/plot_nearmiss_3.py +++ b/examples/under-sampling/plot_nearmiss_3.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import NearMiss + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import NearMiss # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/under-sampling/plot_neighbourhood_cleaning_rule.py b/examples/under-sampling/plot_neighbourhood_cleaning_rule.py index e41d37ff3..ad4b9d98a 100644 --- a/examples/under-sampling/plot_neighbourhood_cleaning_rule.py +++ b/examples/under-sampling/plot_neighbourhood_cleaning_rule.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import NeighbourhoodCleaningRule + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import NeighbourhoodCleaningRule # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/under-sampling/plot_one_sided_selection.py b/examples/under-sampling/plot_one_sided_selection.py index 8e5b08e7c..f9155675e 100644 --- a/examples/under-sampling/plot_one_sided_selection.py +++ b/examples/under-sampling/plot_one_sided_selection.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import OneSidedSelection + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import OneSidedSelection # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/under-sampling/plot_random_under_sampler.py b/examples/under-sampling/plot_random_under_sampler.py index 275a0d366..e48e88045 100644 --- a/examples/under-sampling/plot_random_under_sampler.py +++ b/examples/under-sampling/plot_random_under_sampler.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import RandomUnderSampler + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import RandomUnderSampler # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/examples/under-sampling/plot_repeated_edited_nearest_neighbours.py b/examples/under-sampling/plot_repeated_edited_nearest_neighbours.py index deb5ed847..0704be367 100644 --- a/examples/under-sampling/plot_repeated_edited_nearest_neighbours.py +++ b/examples/under-sampling/plot_repeated_edited_nearest_neighbours.py @@ -11,17 +11,19 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import (EditedNearestNeighbours, + RepeatedEditedNearestNeighbours) + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import EditedNearestNeighbours -from imblearn.under_sampling import RepeatedEditedNearestNeighbours # Generate the dataset X, y = make_classification(n_classes=2, class_sep=1.25, weights=[0.3, 0.7], diff --git a/examples/under-sampling/plot_tomek_links.py b/examples/under-sampling/plot_tomek_links.py index 85d469124..0747fff1f 100644 --- a/examples/under-sampling/plot_tomek_links.py +++ b/examples/under-sampling/plot_tomek_links.py @@ -11,16 +11,18 @@ import matplotlib.pyplot as plt import seaborn as sns +from sklearn.datasets import make_classification +from sklearn.decomposition import PCA + +from imblearn.under_sampling import TomekLinks + sns.set() # Define some color for the plotting almost_black = '#262626' palette = sns.color_palette() -from sklearn.datasets import make_classification -from sklearn.decomposition import PCA -from imblearn.under_sampling import TomekLinks # Generate the dataset X, y = make_classification(n_classes=2, class_sep=2, weights=[0.1, 0.9], diff --git a/imblearn/base.py b/imblearn/base.py index 4ec8fe11d..610896113 100644 --- a/imblearn/base.py +++ b/imblearn/base.py @@ -1,23 +1,18 @@ """Base class for sampling""" -from __future__ import division -from __future__ import print_function +from __future__ import division, print_function -import warnings import logging - -import numpy as np - +import warnings from abc import ABCMeta, abstractmethod - from collections import Counter +import numpy as np +from six import string_types from sklearn.base import BaseEstimator +from sklearn.externals import six from sklearn.utils import check_X_y from sklearn.utils.multiclass import type_of_target -from sklearn.externals import six - -from six import string_types class SamplerMixin(six.with_metaclass(ABCMeta, BaseEstimator)): diff --git a/imblearn/combine/smote_enn.py b/imblearn/combine/smote_enn.py index baa2ceed9..7261e1fd7 100644 --- a/imblearn/combine/smote_enn.py +++ b/imblearn/combine/smote_enn.py @@ -1,10 +1,9 @@ """Class to perform over-sampling using SMOTE and cleaning using ENN.""" -from __future__ import print_function -from __future__ import division +from __future__ import division, print_function +from ..base import BaseBinarySampler from ..over_sampling import SMOTE from ..under_sampling import EditedNearestNeighbours -from ..base import BaseBinarySampler class SMOTEENN(BaseBinarySampler): diff --git a/imblearn/combine/smote_tomek.py b/imblearn/combine/smote_tomek.py index 96615d3bf..a91b318a5 100644 --- a/imblearn/combine/smote_tomek.py +++ b/imblearn/combine/smote_tomek.py @@ -1,11 +1,10 @@ """Class to perform over-sampling using SMOTE and cleaning using Tomek links.""" -from __future__ import print_function -from __future__ import division +from __future__ import division, print_function +from ..base import BaseBinarySampler from ..over_sampling import SMOTE from ..under_sampling import TomekLinks -from ..base import BaseBinarySampler class SMOTETomek(BaseBinarySampler): diff --git a/imblearn/combine/tests/test_smote_enn.py b/imblearn/combine/tests/test_smote_enn.py index a09bd78ce..f3506eab4 100644 --- a/imblearn/combine/tests/test_smote_enn.py +++ b/imblearn/combine/tests/test_smote_enn.py @@ -4,12 +4,8 @@ import os import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_array_almost_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_almost_equal, assert_array_equal, + assert_equal, assert_raises, assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator diff --git a/imblearn/combine/tests/test_smote_tomek.py b/imblearn/combine/tests/test_smote_tomek.py index 17c040e4d..423faf3f6 100644 --- a/imblearn/combine/tests/test_smote_tomek.py +++ b/imblearn/combine/tests/test_smote_tomek.py @@ -4,12 +4,8 @@ import os import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_array_almost_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_almost_equal, assert_array_equal, + assert_equal, assert_raises, assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator diff --git a/imblearn/datasets/imbalance.py b/imblearn/datasets/imbalance.py index 3fb2467eb..b36c2904c 100644 --- a/imblearn/datasets/imbalance.py +++ b/imblearn/datasets/imbalance.py @@ -1,13 +1,10 @@ """Transform a dataset into an imbalanced dataset.""" import logging - -import numpy as np - from collections import Counter -from sklearn.utils import check_X_y -from sklearn.utils import check_random_state +import numpy as np +from sklearn.utils import check_random_state, check_X_y LOGGER = logging.getLogger(__name__) diff --git a/imblearn/datasets/tests/test_make_imbalance.py b/imblearn/datasets/tests/test_make_imbalance.py index 113ff1d40..5ebb2d176 100644 --- a/imblearn/datasets/tests/test_make_imbalance.py +++ b/imblearn/datasets/tests/test_make_imbalance.py @@ -1,12 +1,11 @@ """Test the module easy ensemble.""" from __future__ import print_function +from collections import Counter + import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal from nose.tools import assert_true - -from collections import Counter +from numpy.testing import assert_equal, assert_raises from imblearn.datasets import make_imbalance diff --git a/imblearn/ensemble/balance_cascade.py b/imblearn/ensemble/balance_cascade.py index d0ca37bec..8cd0cbbb5 100644 --- a/imblearn/ensemble/balance_cascade.py +++ b/imblearn/ensemble/balance_cascade.py @@ -2,12 +2,10 @@ from __future__ import print_function import numpy as np - from sklearn.utils import check_random_state from ..base import BaseBinarySampler - ESTIMATOR_KIND = ('knn', 'decision-tree', 'random-forest', 'adaboost', 'gradient-boosting', 'linear-svm') diff --git a/imblearn/ensemble/easy_ensemble.py b/imblearn/ensemble/easy_ensemble.py index 0db68697b..d9dc58946 100644 --- a/imblearn/ensemble/easy_ensemble.py +++ b/imblearn/ensemble/easy_ensemble.py @@ -2,13 +2,11 @@ from __future__ import print_function import numpy as np - from sklearn.utils import check_random_state from ..base import BaseMulticlassSampler from ..under_sampling import RandomUnderSampler - MAX_INT = np.iinfo(np.int32).max diff --git a/imblearn/ensemble/tests/test_balance_cascade.py b/imblearn/ensemble/tests/test_balance_cascade.py index dd8680c69..eff8a809c 100644 --- a/imblearn/ensemble/tests/test_balance_cascade.py +++ b/imblearn/ensemble/tests/test_balance_cascade.py @@ -4,11 +4,8 @@ import os import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator diff --git a/imblearn/ensemble/tests/test_easy_ensemble.py b/imblearn/ensemble/tests/test_easy_ensemble.py index a831c8827..9852cf2f3 100644 --- a/imblearn/ensemble/tests/test_easy_ensemble.py +++ b/imblearn/ensemble/tests/test_easy_ensemble.py @@ -2,18 +2,14 @@ from __future__ import print_function import os +from collections import Counter import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.ensemble import EasyEnsemble # Generate a global dataset to use diff --git a/imblearn/over_sampling/adasyn.py b/imblearn/over_sampling/adasyn.py index d55c22e7e..4474d9d38 100644 --- a/imblearn/over_sampling/adasyn.py +++ b/imblearn/over_sampling/adasyn.py @@ -1,11 +1,9 @@ """Class to perform random over-sampling.""" -from __future__ import print_function -from __future__ import division - -import numpy as np +from __future__ import division, print_function from collections import Counter +import numpy as np from sklearn.neighbors import NearestNeighbors from sklearn.utils import check_random_state diff --git a/imblearn/over_sampling/random_over_sampler.py b/imblearn/over_sampling/random_over_sampler.py index e40490495..980d23e3a 100644 --- a/imblearn/over_sampling/random_over_sampler.py +++ b/imblearn/over_sampling/random_over_sampler.py @@ -1,11 +1,9 @@ """Class to perform random over-sampling.""" -from __future__ import print_function -from __future__ import division - -import numpy as np +from __future__ import division, print_function from collections import Counter +import numpy as np from sklearn.utils import check_random_state from ..base import BaseMulticlassSampler diff --git a/imblearn/over_sampling/smote.py b/imblearn/over_sampling/smote.py index 533670075..c79c55304 100644 --- a/imblearn/over_sampling/smote.py +++ b/imblearn/over_sampling/smote.py @@ -1,17 +1,13 @@ """Class to perform over-sampling using SMOTE.""" -from __future__ import print_function -from __future__ import division +from __future__ import division, print_function import numpy as np - -from sklearn.utils import check_array -from sklearn.utils import check_random_state from sklearn.neighbors import NearestNeighbors from sklearn.svm import SVC +from sklearn.utils import check_array, check_random_state from ..base import BaseBinarySampler - SMOTE_KIND = ('regular', 'borderline1', 'borderline2', 'svm') diff --git a/imblearn/over_sampling/tests/test_adasyn.py b/imblearn/over_sampling/tests/test_adasyn.py index c80d1cb99..7937cebdc 100644 --- a/imblearn/over_sampling/tests/test_adasyn.py +++ b/imblearn/over_sampling/tests/test_adasyn.py @@ -4,12 +4,8 @@ import os import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_array_almost_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_almost_equal, assert_array_equal, + assert_equal, assert_raises, assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator diff --git a/imblearn/over_sampling/tests/test_random_over_sampler.py b/imblearn/over_sampling/tests/test_random_over_sampler.py index acecab3c5..20a65b9fd 100644 --- a/imblearn/over_sampling/tests/test_random_over_sampler.py +++ b/imblearn/over_sampling/tests/test_random_over_sampler.py @@ -1,17 +1,14 @@ """Test the module under sampler.""" from __future__ import print_function -import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns +from collections import Counter +import numpy as np +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.over_sampling import RandomOverSampler # Generate a global dataset to use diff --git a/imblearn/over_sampling/tests/test_smote.py b/imblearn/over_sampling/tests/test_smote.py index 20351e393..33c93620e 100644 --- a/imblearn/over_sampling/tests/test_smote.py +++ b/imblearn/over_sampling/tests/test_smote.py @@ -4,12 +4,8 @@ import os import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_array_almost_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_almost_equal, assert_array_equal, + assert_equal, assert_raises, assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator diff --git a/imblearn/pipeline.py b/imblearn/pipeline.py index a0851b161..c8e855c5a 100644 --- a/imblearn/pipeline.py +++ b/imblearn/pipeline.py @@ -12,13 +12,12 @@ # chkoar # License: BSD -from __future__ import print_function -from __future__ import division +from __future__ import division, print_function from warnings import warn -from sklearn.externals import six from sklearn import pipeline +from sklearn.externals import six from sklearn.utils import tosequence from sklearn.utils.metaestimators import if_delegate_has_method diff --git a/imblearn/tests/test_pipeline.py b/imblearn/tests/test_pipeline.py index 8f67d6d13..739e932ce 100644 --- a/imblearn/tests/test_pipeline.py +++ b/imblearn/tests/test_pipeline.py @@ -2,33 +2,23 @@ Test the pipeline module. """ import numpy as np - -from sklearn.utils.testing import assert_raises -from sklearn.utils.testing import assert_raises_regex -from sklearn.utils.testing import assert_raise_message -from sklearn.utils.testing import assert_equal -from sklearn.utils.testing import assert_false -from sklearn.utils.testing import assert_true -from sklearn.utils.testing import assert_array_equal -from sklearn.utils.testing import assert_array_almost_equal -from sklearn.utils.testing import assert_warns_message - from sklearn.base import clone -from sklearn.svm import SVC -from sklearn.linear_model import LogisticRegression -from sklearn.linear_model import LinearRegression from sklearn.cluster import KMeans -from sklearn.feature_selection import SelectKBest, f_classif +from sklearn.datasets import load_iris, make_classification from sklearn.decomposition import PCA -from sklearn.datasets import load_iris +from sklearn.feature_selection import SelectKBest, f_classif +from sklearn.linear_model import LinearRegression, LogisticRegression from sklearn.preprocessing import StandardScaler -from sklearn.datasets import make_classification +from sklearn.svm import SVC +from sklearn.utils.testing import (assert_array_almost_equal, + assert_array_equal, assert_equal, + assert_false, assert_raise_message, + assert_raises, assert_raises_regex, + assert_true, assert_warns_message) -from imblearn.pipeline import Pipeline -from imblearn.pipeline import make_pipeline +from imblearn.pipeline import Pipeline, make_pipeline from imblearn.under_sampling import RandomUnderSampler - JUNK_FOOD_DOCS = ( "the pizza pizza beer copyright", "the pizza burger beer copyright", diff --git a/imblearn/under_sampling/cluster_centroids.py b/imblearn/under_sampling/cluster_centroids.py index da973c925..e504d3a12 100644 --- a/imblearn/under_sampling/cluster_centroids.py +++ b/imblearn/under_sampling/cluster_centroids.py @@ -1,12 +1,10 @@ """Class to perform under-sampling by generating centroids based on clustering.""" -from __future__ import print_function -from __future__ import division - -import numpy as np +from __future__ import division, print_function from collections import Counter +import numpy as np from sklearn.cluster import KMeans from sklearn.utils import check_random_state diff --git a/imblearn/under_sampling/condensed_nearest_neighbour.py b/imblearn/under_sampling/condensed_nearest_neighbour.py index 10ab37999..8cf5d9fd2 100644 --- a/imblearn/under_sampling/condensed_nearest_neighbour.py +++ b/imblearn/under_sampling/condensed_nearest_neighbour.py @@ -1,14 +1,12 @@ """Class to perform under-sampling based on the condensed nearest neighbour method.""" -from __future__ import print_function -from __future__ import division - -import numpy as np +from __future__ import division, print_function from collections import Counter -from sklearn.utils import check_random_state +import numpy as np from sklearn.neighbors import KNeighborsClassifier +from sklearn.utils import check_random_state from ..base import BaseMulticlassSampler diff --git a/imblearn/under_sampling/edited_nearest_neighbours.py b/imblearn/under_sampling/edited_nearest_neighbours.py index d887e61ab..90436365c 100644 --- a/imblearn/under_sampling/edited_nearest_neighbours.py +++ b/imblearn/under_sampling/edited_nearest_neighbours.py @@ -1,19 +1,15 @@ """Class to perform under-sampling based on the edited nearest neighbour method.""" -from __future__ import print_function -from __future__ import division - -import numpy as np +from __future__ import division, print_function from collections import Counter +import numpy as np from scipy.stats import mode - from sklearn.neighbors import NearestNeighbors from ..base import BaseMulticlassSampler - SEL_KIND = ('all', 'mode') diff --git a/imblearn/under_sampling/instance_hardness_threshold.py b/imblearn/under_sampling/instance_hardness_threshold.py index 5951c0773..ab11046b5 100644 --- a/imblearn/under_sampling/instance_hardness_threshold.py +++ b/imblearn/under_sampling/instance_hardness_threshold.py @@ -1,17 +1,14 @@ """Class to perform under-sampling based on the instance hardness threshold.""" -from __future__ import print_function -from __future__ import division - -import numpy as np +from __future__ import division, print_function from collections import Counter +import numpy as np from sklearn.cross_validation import StratifiedKFold from ..base import BaseBinarySampler - ESTIMATOR_KIND = ('knn', 'decision-tree', 'random-forest', 'adaboost', 'gradient-boosting', 'linear-svm') diff --git a/imblearn/under_sampling/nearmiss.py b/imblearn/under_sampling/nearmiss.py index f6efda905..817dca8cf 100644 --- a/imblearn/under_sampling/nearmiss.py +++ b/imblearn/under_sampling/nearmiss.py @@ -1,13 +1,10 @@ """Class to perform under-sampling based on nearmiss methods.""" -from __future__ import print_function -from __future__ import division +from __future__ import division, print_function import warnings - -import numpy as np - from collections import Counter +import numpy as np from sklearn.neighbors import NearestNeighbors from ..base import BaseMulticlassSampler diff --git a/imblearn/under_sampling/neighbourhood_cleaning_rule.py b/imblearn/under_sampling/neighbourhood_cleaning_rule.py index 017b0388f..4b02330a4 100644 --- a/imblearn/under_sampling/neighbourhood_cleaning_rule.py +++ b/imblearn/under_sampling/neighbourhood_cleaning_rule.py @@ -1,11 +1,9 @@ """Class performing under-sampling based on the neighbourhood cleaning rule.""" -from __future__ import print_function -from __future__ import division - -import numpy as np +from __future__ import division, print_function from collections import Counter +import numpy as np from sklearn.neighbors import NearestNeighbors from ..base import BaseMulticlassSampler diff --git a/imblearn/under_sampling/one_sided_selection.py b/imblearn/under_sampling/one_sided_selection.py index 5d6ffdc13..6c044f346 100644 --- a/imblearn/under_sampling/one_sided_selection.py +++ b/imblearn/under_sampling/one_sided_selection.py @@ -1,13 +1,10 @@ """Class to perform under-sampling based on one-sided selection method.""" -from __future__ import print_function -from __future__ import division - -import numpy as np +from __future__ import division, print_function from collections import Counter -from sklearn.neighbors import KNeighborsClassifier -from sklearn.neighbors import NearestNeighbors +import numpy as np +from sklearn.neighbors import KNeighborsClassifier, NearestNeighbors from sklearn.utils import check_random_state from ..base import BaseBinarySampler diff --git a/imblearn/under_sampling/random_under_sampler.py b/imblearn/under_sampling/random_under_sampler.py index 09ef5fca3..c936ba383 100644 --- a/imblearn/under_sampling/random_under_sampler.py +++ b/imblearn/under_sampling/random_under_sampler.py @@ -1,11 +1,9 @@ """Class to perform random under-sampling.""" -from __future__ import print_function -from __future__ import division - -import numpy as np +from __future__ import division, print_function from collections import Counter +import numpy as np from sklearn.utils import check_random_state from ..base import BaseMulticlassSampler diff --git a/imblearn/under_sampling/tests/test_allknn.py b/imblearn/under_sampling/tests/test_allknn.py index 4c8ab9190..e8afa702e 100644 --- a/imblearn/under_sampling/tests/test_allknn.py +++ b/imblearn/under_sampling/tests/test_allknn.py @@ -2,19 +2,14 @@ from __future__ import print_function import os +from collections import Counter import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_array_almost_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_almost_equal, assert_array_equal, + assert_equal, assert_raises, assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import AllKNN # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_cluster_centroids.py b/imblearn/under_sampling/tests/test_cluster_centroids.py index f5d4295b0..eb0a4cbdc 100644 --- a/imblearn/under_sampling/tests/test_cluster_centroids.py +++ b/imblearn/under_sampling/tests/test_cluster_centroids.py @@ -1,18 +1,14 @@ """Test the module cluster centroids.""" from __future__ import print_function -import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_array_almost_equal -from numpy.testing import assert_warns +from collections import Counter +import numpy as np +from numpy.testing import (assert_array_almost_equal, assert_array_equal, + assert_equal, assert_raises, assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import ClusterCentroids # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_condensed_nearest_neighbour.py b/imblearn/under_sampling/tests/test_condensed_nearest_neighbour.py index 14a5fdf96..60f078609 100644 --- a/imblearn/under_sampling/tests/test_condensed_nearest_neighbour.py +++ b/imblearn/under_sampling/tests/test_condensed_nearest_neighbour.py @@ -2,18 +2,14 @@ from __future__ import print_function import os +from collections import Counter import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import CondensedNearestNeighbour # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_edited_nearest_neighbours.py b/imblearn/under_sampling/tests/test_edited_nearest_neighbours.py index 5d8720294..4b8240552 100644 --- a/imblearn/under_sampling/tests/test_edited_nearest_neighbours.py +++ b/imblearn/under_sampling/tests/test_edited_nearest_neighbours.py @@ -2,18 +2,14 @@ from __future__ import print_function import os +from collections import Counter import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import EditedNearestNeighbours # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_instance_hardness_threshold.py b/imblearn/under_sampling/tests/test_instance_hardness_threshold.py index 216b6f8a4..8ab19f9ad 100644 --- a/imblearn/under_sampling/tests/test_instance_hardness_threshold.py +++ b/imblearn/under_sampling/tests/test_instance_hardness_threshold.py @@ -4,17 +4,13 @@ import os import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator from imblearn.under_sampling import InstanceHardnessThreshold - # Generate a global dataset to use RND_SEED = 0 X = np.array([[-0.3879569, 0.6894251], diff --git a/imblearn/under_sampling/tests/test_nearmiss_1.py b/imblearn/under_sampling/tests/test_nearmiss_1.py index a2c742fec..1852e93a4 100644 --- a/imblearn/under_sampling/tests/test_nearmiss_1.py +++ b/imblearn/under_sampling/tests/test_nearmiss_1.py @@ -2,18 +2,14 @@ from __future__ import print_function import os +from collections import Counter import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import NearMiss # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_nearmiss_2.py b/imblearn/under_sampling/tests/test_nearmiss_2.py index 452735e0b..cf23c0af6 100644 --- a/imblearn/under_sampling/tests/test_nearmiss_2.py +++ b/imblearn/under_sampling/tests/test_nearmiss_2.py @@ -2,18 +2,14 @@ from __future__ import print_function import os +from collections import Counter import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import NearMiss # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_nearmiss_3.py b/imblearn/under_sampling/tests/test_nearmiss_3.py index 3a8509e6e..62fc7c297 100644 --- a/imblearn/under_sampling/tests/test_nearmiss_3.py +++ b/imblearn/under_sampling/tests/test_nearmiss_3.py @@ -2,18 +2,14 @@ from __future__ import print_function import os +from collections import Counter import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import NearMiss # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_neighbourhood_cleaning_rule.py b/imblearn/under_sampling/tests/test_neighbourhood_cleaning_rule.py index b29a55b57..e8997e55a 100644 --- a/imblearn/under_sampling/tests/test_neighbourhood_cleaning_rule.py +++ b/imblearn/under_sampling/tests/test_neighbourhood_cleaning_rule.py @@ -2,18 +2,14 @@ from __future__ import print_function import os +from collections import Counter import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import NeighbourhoodCleaningRule # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_one_sided_selection.py b/imblearn/under_sampling/tests/test_one_sided_selection.py index 307dd460b..09269df7c 100644 --- a/imblearn/under_sampling/tests/test_one_sided_selection.py +++ b/imblearn/under_sampling/tests/test_one_sided_selection.py @@ -2,18 +2,14 @@ from __future__ import print_function import os +from collections import Counter import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import OneSidedSelection # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_random_under_sampler.py b/imblearn/under_sampling/tests/test_random_under_sampler.py index 6af598edd..5d1a714ca 100644 --- a/imblearn/under_sampling/tests/test_random_under_sampler.py +++ b/imblearn/under_sampling/tests/test_random_under_sampler.py @@ -1,16 +1,13 @@ """Test the module random under sampler.""" from __future__ import print_function -import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns +from collections import Counter +import numpy as np +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import RandomUnderSampler # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_repeated_edited_nearest_neighbours.py b/imblearn/under_sampling/tests/test_repeated_edited_nearest_neighbours.py index 9b0078329..1f5536b06 100644 --- a/imblearn/under_sampling/tests/test_repeated_edited_nearest_neighbours.py +++ b/imblearn/under_sampling/tests/test_repeated_edited_nearest_neighbours.py @@ -2,18 +2,14 @@ from __future__ import print_function import os +from collections import Counter import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator -from collections import Counter - from imblearn.under_sampling import RepeatedEditedNearestNeighbours # Generate a global dataset to use diff --git a/imblearn/under_sampling/tests/test_tomek_links.py b/imblearn/under_sampling/tests/test_tomek_links.py index 5d89aea49..670dfe58a 100644 --- a/imblearn/under_sampling/tests/test_tomek_links.py +++ b/imblearn/under_sampling/tests/test_tomek_links.py @@ -4,11 +4,8 @@ import os import numpy as np -from numpy.testing import assert_raises -from numpy.testing import assert_equal -from numpy.testing import assert_array_equal -from numpy.testing import assert_warns - +from numpy.testing import (assert_array_equal, assert_equal, assert_raises, + assert_warns) from sklearn.datasets import make_classification from sklearn.utils.estimator_checks import check_estimator diff --git a/imblearn/under_sampling/tomek_links.py b/imblearn/under_sampling/tomek_links.py index 7086d0184..42b36ce89 100644 --- a/imblearn/under_sampling/tomek_links.py +++ b/imblearn/under_sampling/tomek_links.py @@ -1,11 +1,9 @@ """Class to perform under-sampling by removing Tomek's links.""" -from __future__ import print_function -from __future__ import division - -import numpy as np +from __future__ import division, print_function from collections import Counter +import numpy as np from sklearn.neighbors import NearestNeighbors from ..base import BaseBinarySampler diff --git a/setup.py b/setup.py index 9aafdef89..8fe0c0781 100644 --- a/setup.py +++ b/setup.py @@ -1,11 +1,11 @@ #! /usr/bin/env python """Toolbox for imbalanced dataset in machine learning.""" -import sys -import os import codecs +import os +import sys -from setuptools import setup, find_packages +from setuptools import find_packages, setup def load_version():