Remove unimportant # type: ignore in code

eli5/_feature_names.py

@@ -5,8 +5,8 @@
     Union, Callable, Pattern
 )
 
-import numpy as np  # type: ignore
-import scipy.sparse as sp  # type: ignore
+import numpy as np
+import scipy.sparse as sp
 
 
 class FeatureNames(Sized, Iterable):

eli5/_feature_weights.py

@@ -1,7 +1,7 @@
 # -*- coding: utf-8 -*-
 from __future__ import absolute_import
 
-import numpy as np  # type: ignore
+import numpy as np
 
 from eli5.base import FeatureWeights, FeatureWeight
 from .utils import argsort_k_largest_positive, argsort_k_smallest, mask

eli5/_graphviz.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-import graphviz  # type: ignore
+import graphviz
 
 
 def is_supported():

eli5/base.py

@@ -1,7 +1,7 @@
 # -*- coding: utf-8 -*-
 from typing import Any, List, Tuple, Union, Optional
 
-import numpy as np # type: ignore
+import numpy as np
 
 from .base_utils import attrs
 from .formatters.features import FormattedFeatureName

eli5/base_utils.py

@@ -1,9 +1,9 @@
 import inspect
 
-import attr  # type: ignore
+import attr
 
 try:
-    from functools import singledispatch  # type: ignore
+    from functools import singledispatch
 except ImportError:
     from singledispatch import singledispatch  # type: ignore
 

eli5/catboost.py

@@ -1,7 +1,7 @@
 from __future__ import absolute_import, division
 
-import numpy as np  # type: ignore
-import catboost # type: ignore
+import numpy as np
+import catboost
 
 from eli5.explain import explain_weights
 from eli5._feature_importances import get_feature_importance_explanation

eli5/formatters/as_dataframe.py

@@ -2,7 +2,7 @@
 from typing import Any, Dict, List, Optional
 import warnings
 
-import pandas as pd  # type: ignore
+import pandas as pd
 
 import eli5
 from eli5.base import (

eli5/formatters/as_dict.py

@@ -1,7 +1,7 @@
 import six
 
-import attr   # type: ignore
-import numpy as np   # type: ignore
+import attr
+import numpy as np
 
 from .features import FormattedFeatureName
 

eli5/formatters/html.py

@@ -3,8 +3,8 @@
 from itertools import groupby
 from typing import List, Optional, Tuple
 
-import numpy as np  # type: ignore
-from jinja2 import Environment, PackageLoader  # type: ignore
+import numpy as np
+from jinja2 import Environment, PackageLoader
 
 from eli5 import _graphviz
 from eli5.base import (Explanation, TargetExplanation, FeatureWeights,

eli5/formatters/image.py

@@ -2,9 +2,9 @@
 from __future__ import absolute_import
 from typing import Union, Optional, Callable
 
-import numpy as np # type: ignore
-from PIL import Image # type: ignore
-import matplotlib.cm # type: ignore
+import numpy as np
+from PIL import Image
+import matplotlib.cm
 
 from eli5.base import Explanation
 

eli5/formatters/text_helpers.py

@@ -1,7 +1,7 @@
 from collections import Counter
 from typing import List, Optional
 
-import numpy as np  # type: ignore
+import numpy as np
 
 from eli5.base import TargetExplanation, WeightedSpans, DocWeightedSpans
 from eli5.base_utils import attrs

eli5/formatters/utils.py

@@ -2,10 +2,9 @@
 from itertools import chain
 import re
 import six
-from numbers import Real
 from typing import Any, Union, List, Dict, Callable, Match, Optional
 
-import numpy as np  # type: ignore
+import numpy as np
 
 from eli5.base import Explanation
 from .features import FormattedFeatureName

eli5/ipython.py

@@ -3,15 +3,15 @@
 from typing import Any, Dict, Tuple
 import warnings
 
-from IPython.display import HTML, Image  # type: ignore
+from IPython.display import HTML, Image
 
 from .explain import explain_weights, explain_prediction
 from .formatters import format_as_html, fields
 try:
     from .formatters.image import format_as_image
 except ImportError as e:
     # missing dependencies
-    format_as_image = e # type: ignore
+    format_as_image = e  # type: ignore
 
 
 FORMAT_KWARGS = {'include_styles', 'force_weights',

eli5/keras/explain_prediction.py

@@ -2,21 +2,21 @@
 from __future__ import absolute_import
 from typing import Union, Optional, Callable, Tuple, List, TYPE_CHECKING
 if TYPE_CHECKING:
-    import PIL # type: ignore
-
-import numpy as np # type: ignore
-import keras # type: ignore
-import keras.backend as K # type: ignore
-from keras.models import Model # type: ignore
-from keras.layers import Layer # type: ignore
-from keras.layers import (  # type: ignore
+    import PIL
+
+import numpy as np
+import keras
+import keras.backend as K
+from keras.models import Model
+from keras.layers import Layer
+from keras.layers import (
     Conv2D,
     MaxPooling2D,
     AveragePooling2D,
     GlobalMaxPooling2D,
     GlobalAveragePooling2D,
 )
-from keras.preprocessing.image import array_to_img # type: ignore
+from keras.preprocessing.image import array_to_img
 
 from eli5.base import Explanation, TargetExplanation
 from eli5.explain import explain_prediction

eli5/keras/gradcam.py

@@ -2,11 +2,11 @@
 from __future__ import absolute_import
 from typing import Union, Optional, Tuple, List
 
-import numpy as np # type: ignore
-import keras # type: ignore
-import keras.backend as K # type: ignore
-from keras.models import Model # type: ignore
-from keras.layers import Layer # type: ignore
+import numpy as np
+import keras
+import keras.backend as K
+from keras.models import Model
+from keras.layers import Layer
 
 
 def gradcam(weights, activations):

eli5/lightgbm.py

@@ -3,8 +3,8 @@
 from collections import defaultdict
 from typing import DefaultDict, Optional
 
-import numpy as np  # type: ignore
-import lightgbm  # type: ignore
+import numpy as np
+import lightgbm
 
 from eli5.explain import explain_weights, explain_prediction
 from eli5._feature_importances import get_feature_importance_explanation

eli5/lightning.py

@@ -1,9 +1,9 @@
 # -*- coding: utf-8 -*-
 from __future__ import absolute_import
 
-from lightning.impl.base import BaseEstimator  # type: ignore
-from lightning import classification, regression   # type: ignore
-from sklearn.multiclass import OneVsRestClassifier   # type: ignore
+from lightning.impl.base import BaseEstimator
+from lightning import classification, regression
+from sklearn.multiclass import OneVsRestClassifier
 
 from eli5.base import Explanation
 from eli5.base_utils import singledispatch

eli5/lime/_vectorizer.py

@@ -2,8 +2,8 @@
 from __future__ import absolute_import
 from typing import Tuple, Callable, Dict, Optional, List
 
-import numpy as np  # type: ignore
-from sklearn.base import BaseEstimator, TransformerMixin  # type: ignore
+import numpy as np
+from sklearn.base import BaseEstimator, TransformerMixin
 
 from eli5.base import DocWeightedSpans, FeatureWeights
 from eli5.sklearn.text import _get_feature_weights_dict

eli5/lime/lime.py

@@ -6,12 +6,12 @@
 from __future__ import absolute_import
 from typing import Any, Callable, Dict, Optional
 
-import numpy as np  # type: ignore
-from sklearn.feature_extraction.text import CountVectorizer  # type: ignore
-from sklearn.linear_model import SGDClassifier  # type: ignore
-from sklearn.model_selection import train_test_split  # type: ignore
-from sklearn.utils import check_random_state  # type: ignore
-from sklearn.base import clone, BaseEstimator  # type: ignore
+import numpy as np
+from sklearn.feature_extraction.text import CountVectorizer
+from sklearn.linear_model import SGDClassifier
+from sklearn.model_selection import train_test_split
+from sklearn.utils import check_random_state
+from sklearn.base import clone, BaseEstimator
 
 import eli5
 from eli5.sklearn.utils import sklearn_version

eli5/lime/samplers.py

@@ -5,13 +5,13 @@
 from typing import List, Tuple, Any, Union, Dict, Optional
 import six
 
-import numpy as np  # type: ignore
-from scipy.stats import itemfreq  # type: ignore
-from sklearn.base import BaseEstimator, clone  # type: ignore
-from sklearn.neighbors import KernelDensity  # type: ignore
-from sklearn.metrics import pairwise_distances  # type: ignore
-from sklearn.model_selection import GridSearchCV, KFold  # type: ignore
-from sklearn.utils import check_random_state  # type: ignore
+import numpy as np
+from scipy.stats import itemfreq
+from sklearn.base import BaseEstimator, clone
+from sklearn.neighbors import KernelDensity
+from sklearn.metrics import pairwise_distances
+from sklearn.model_selection import GridSearchCV, KFold
+from sklearn.utils import check_random_state
 
 from eli5.utils import vstack
 from eli5.lime.utils import rbf

eli5/lime/textutils.py

@@ -7,8 +7,8 @@
 import math
 from typing import List, Tuple, Union, Optional
 
-import numpy as np  # type: ignore
-from sklearn.utils import check_random_state  # type: ignore
+import numpy as np
+from sklearn.utils import check_random_state
 
 from eli5.utils import indices_to_bool_mask, vstack
 

eli5/lime/utils.py

@@ -2,12 +2,12 @@
 from __future__ import absolute_import
 from typing import List, Any
 
-import numpy as np  # type: ignore
-from scipy.stats import entropy  # type: ignore
-from sklearn.pipeline import Pipeline  # type: ignore
-from sklearn.utils import check_random_state, issparse  # type: ignore
-from sklearn.utils.metaestimators import if_delegate_has_method  # type: ignore
-from sklearn.utils import shuffle as _shuffle  # type: ignore
+import numpy as np
+from scipy.stats import entropy
+from sklearn.pipeline import Pipeline
+from sklearn.utils import check_random_state, issparse
+from sklearn.utils.metaestimators import if_delegate_has_method
+from sklearn.utils import shuffle as _shuffle
 
 from eli5.utils import vstack
 from eli5.sklearn.utils import sklearn_version

eli5/permutation_importance.py

@@ -13,8 +13,8 @@
 from __future__ import absolute_import
 from typing import Tuple, List, Callable, Any
 
-import numpy as np  # type: ignore
-from sklearn.utils import check_random_state  # type: ignore
+import numpy as np
+from sklearn.utils import check_random_state
 
 
 def iter_shuffled(X, columns_to_shuffle=None, pre_shuffle=False,

eli5/sklearn/explain_prediction.py

@@ -1,18 +1,18 @@
 # -*- coding: utf-8 -*-
 from functools import partial
 
-import numpy as np  # type: ignore
-import scipy.sparse as sp  # type: ignore
-from sklearn.base import BaseEstimator  # type: ignore
-from sklearn.ensemble import (  # type: ignore
+import numpy as np
+import scipy.sparse as sp
+from sklearn.base import BaseEstimator
+from sklearn.ensemble import (
     ExtraTreesClassifier,
     ExtraTreesRegressor,
     GradientBoostingClassifier,
     GradientBoostingRegressor,
     RandomForestClassifier,
     RandomForestRegressor,
 )
-from sklearn.linear_model import (  # type: ignore
+from sklearn.linear_model import (
     ElasticNet,  # includes Lasso, MultiTaskElasticNet, etc.
     ElasticNetCV,
     HuberRegressor,
@@ -34,7 +34,7 @@
     SGDRegressor,
     TheilSenRegressor,
 )
-from sklearn.svm import (  # type: ignore
+from sklearn.svm import (
     LinearSVC,
     LinearSVR,
     SVC,
@@ -43,8 +43,8 @@
     NuSVR,
     OneClassSVM,
 )
-from sklearn.multiclass import OneVsRestClassifier  # type: ignore
-from sklearn.tree import (   # type: ignore
+from sklearn.multiclass import OneVsRestClassifier
+from sklearn.tree import (
     DecisionTreeClassifier,
     DecisionTreeRegressor
 )

eli5/sklearn/explain_weights.py

@@ -1,11 +1,11 @@
 # -*- coding: utf-8 -*-
 from __future__ import absolute_import
 
-import numpy as np  # type: ignore
+import numpy as np
 
-from sklearn.base import BaseEstimator, RegressorMixin  # type: ignore
-from sklearn.pipeline import Pipeline  # type: ignore
-from sklearn.linear_model import (   # type: ignore
+from sklearn.base import BaseEstimator, RegressorMixin
+from sklearn.pipeline import Pipeline
+from sklearn.linear_model import (
     ElasticNet,  # includes Lasso, MultiTaskElasticNet, etc.
     ElasticNetCV,
     HuberRegressor,
@@ -27,8 +27,8 @@
     SGDRegressor,
     TheilSenRegressor,
 )
-from sklearn.multiclass import OneVsRestClassifier  # type: ignore
-from sklearn.svm import (  # type: ignore
+from sklearn.multiclass import OneVsRestClassifier
+from sklearn.svm import (
     LinearSVC,
     LinearSVR,
     SVC,
@@ -38,8 +38,8 @@
     OneClassSVM,
 )
 # TODO: see https://github.com/scikit-learn/scikit-learn/pull/2250
-from sklearn.naive_bayes import BernoulliNB, MultinomialNB    # type: ignore
-from sklearn.ensemble import (  # type: ignore
+from sklearn.naive_bayes import BernoulliNB, MultinomialNB
+from sklearn.ensemble import (
     GradientBoostingClassifier,
     GradientBoostingRegressor,
     AdaBoostClassifier,
@@ -49,7 +49,7 @@
     ExtraTreesClassifier,
     ExtraTreesRegressor,
 )
-from sklearn.tree import (  # type: ignore
+from sklearn.tree import (
     DecisionTreeClassifier,
     DecisionTreeRegressor,
 )