Add logsumexp and comb to utils.fixes (scikit-learn#9046)

sklearn/decomposition/online_lda.py

@@ -13,13 +13,13 @@
 
 import numpy as np
 import scipy.sparse as sp
-from scipy.misc import logsumexp
 from scipy.special import gammaln
 import warnings
 
 from ..base import BaseEstimator, TransformerMixin
 from ..utils import (check_random_state, check_array,
  gen_batches, gen_even_slices, _get_n_jobs)
+from ..utils.fixes import logsumexp
 from ..utils.validation import check_non_negative
 from ..externals.joblib import Parallel, delayed
 from ..externals.six.moves import xrange

sklearn/ensemble/gradient_boosting.py

@@ -27,7 +27,6 @@
 from abc import abstractmethod
 
 from .base import BaseEnsemble
-from ..base import BaseEstimator
 from ..base import ClassifierMixin
 from ..base import RegressorMixin
 from ..externals import six
@@ -40,7 +39,6 @@
 import numpy as np
 
 from scipy import stats
-from scipy.misc import logsumexp
 from scipy.sparse import csc_matrix
 from scipy.sparse import csr_matrix
 from scipy.sparse import issparse
@@ -57,6 +55,7 @@
 from ..utils import column_or_1d
 from ..utils import check_consistent_length
 from ..utils import deprecated
+from ..utils.fixes import logsumexp
 from ..utils.stats import _weighted_percentile
 from ..utils.validation import check_is_fitted
 from ..utils.multiclass import check_classification_targets

sklearn/ensemble/tests/test_forest.py

@@ -14,7 +14,6 @@
 from itertools import product
 
 import numpy as np
-from scipy.misc import comb
 from scipy.sparse import csr_matrix
 from scipy.sparse import csc_matrix
 from scipy.sparse import coo_matrix
@@ -42,6 +41,7 @@
 from sklearn.model_selection import GridSearchCV
 from sklearn.svm import LinearSVC
 from sklearn.utils.validation import check_random_state
+from sklearn.utils.fixes import comb
 
 from sklearn.tree.tree import SPARSE_SPLITTERS
 

sklearn/linear_model/logistic.py

@@ -15,7 +15,6 @@
 
 import numpy as np
 from scipy import optimize, sparse
-from scipy.misc import logsumexp
 from scipy.special import expit
 
 from .base import LinearClassifierMixin, SparseCoefMixin, BaseEstimator
@@ -27,6 +26,7 @@
 from ..utils.extmath import (log_logistic, safe_sparse_dot, softmax,
  squared_norm)
 from ..utils.extmath import row_norms
+from ..utils.fixes import logsumexp
 from ..utils.optimize import newton_cg
 from ..utils.validation import check_X_y
 from ..exceptions import NotFittedError

sklearn/linear_model/tests/test_sag.py

@@ -6,14 +6,14 @@
 import math
 import numpy as np
 import scipy.sparse as sp
-from scipy.misc import logsumexp
 
 from sklearn.linear_model.sag import get_auto_step_size
 from sklearn.linear_model.sag_fast import _multinomial_grad_loss_all_samples
 from sklearn.linear_model import LogisticRegression, Ridge
 from sklearn.linear_model.base import make_dataset
 from sklearn.linear_model.logistic import _multinomial_loss_grad
 
+from sklearn.utils.fixes import logsumexp
 from sklearn.utils.extmath import row_norms
 from sklearn.utils.testing import assert_almost_equal
 from sklearn.utils.testing import assert_array_almost_equal

sklearn/metrics/cluster/supervised.py

@@ -18,11 +18,11 @@
 from math import log
 
 import numpy as np
-from scipy.misc import comb
 from scipy import sparse as sp
 
 from .expected_mutual_info_fast import expected_mutual_information
 from ...utils.validation import check_array
+from ...utils.fixes import comb
 
 
 def comb2(n):

sklearn/mixture/base.py

@@ -11,14 +11,14 @@
 from time import time
 
 import numpy as np
-from scipy.misc import logsumexp
 
 from .. import cluster
 from ..base import BaseEstimator
 from ..base import DensityMixin
 from ..externals import six
 from ..exceptions import ConvergenceWarning
 from ..utils import check_array, check_random_state
+from ..utils.fixes import logsumexp
 
 
 def _check_shape(param, param_shape, name):

sklearn/mixture/dpgmm.py

@@ -21,11 +21,11 @@
 from scipy.special import digamma as _digamma, gammaln as _gammaln
 from scipy import linalg
 from scipy.linalg import pinvh
-from scipy.misc import logsumexp
 from scipy.spatial.distance import cdist
 
 from ..externals.six.moves import xrange
 from ..utils import check_random_state, check_array, deprecated
+from ..utils.fixes import logsumexp
 from ..utils.extmath import squared_norm, stable_cumsum
 from ..utils.validation import check_is_fitted
 from .. import cluster

sklearn/mixture/gmm.py

@@ -19,10 +19,10 @@
 
 import numpy as np
 from scipy import linalg
-from scipy.misc import logsumexp
 
 from ..base import BaseEstimator
 from ..utils import check_random_state, check_array, deprecated
+from ..utils.fixes import logsumexp
 from ..utils.validation import check_is_fitted
 from .. import cluster
 

sklearn/model_selection/_split.py

@@ -22,14 +22,13 @@
 
 import numpy as np
 
-from scipy.misc import comb
 from ..utils import indexable, check_random_state, safe_indexing
 from ..utils.validation import _num_samples, column_or_1d
 from ..utils.validation import check_array
 from ..utils.multiclass import type_of_target
 from ..externals.six import with_metaclass
 from ..externals.six.moves import zip
-from ..utils.fixes import signature
+from ..utils.fixes import signature, comb
 from ..base import _pprint
 
 __all__ = ['BaseCrossValidator',

sklearn/model_selection/tests/test_split.py

@@ -5,7 +5,6 @@
 import numpy as np
 from scipy.sparse import coo_matrix, csc_matrix, csr_matrix
 from scipy import stats
-from scipy.misc import comb
 from itertools import combinations
 from itertools import combinations_with_replacement
 
@@ -57,6 +56,8 @@
 from sklearn.externals import six
 from sklearn.externals.six.moves import zip
 
+from sklearn.utils.fixes import comb
+
 from sklearn.svm import SVC
 
 X = np.ones(10)

sklearn/naive_bayes.py

@@ -19,7 +19,6 @@
 from abc import ABCMeta, abstractmethod
 
 import numpy as np
-from scipy.misc import logsumexp
 from scipy.sparse import issparse
 
 from .base import BaseEstimator, ClassifierMixin
@@ -28,6 +27,7 @@
 from .preprocessing import label_binarize
 from .utils import check_X_y, check_array, check_consistent_length
 from .utils.extmath import safe_sparse_dot
+from .utils.fixes import logsumexp
 from .utils.multiclass import _check_partial_fit_first_call
 from .utils.validation import check_is_fitted
 from .externals import six

sklearn/utils/extmath.py

@@ -17,10 +17,10 @@
 import numpy as np
 from scipy import linalg
 from scipy.sparse import issparse, csr_matrix
-from scipy.misc import logsumexp as scipy_logsumexp
 
 from . import check_random_state, deprecated
 from .fixes import np_version
+from .fixes import logsumexp as scipy_logsumexp
 from ._logistic_sigmoid import _log_logistic_sigmoid
 from ..externals.six.moves import xrange
 from .sparsefuncs_fast import csr_row_norms

sklearn/utils/fixes.py

@@ -11,8 +11,6 @@
 # License: BSD 3 clause
 
 import warnings
-import sys
-import functools
 import os
 import errno
 
@@ -36,6 +34,7 @@ def _parse_version(version_string):
  version.append(x)
  return tuple(version)
 
+
 euler_gamma = getattr(np, 'euler_gamma',
  0.577215664901532860606512090082402431)
 
@@ -142,11 +141,17 @@ def sparse_min_max(X, axis):
  # Backport fix for scikit-learn/scikit-learn#2986 / scipy/scipy#4142
  from ._scipy_sparse_lsqr_backport import lsqr as sparse_lsqr
 else:
- from scipy.sparse.linalg import lsqr as sparse_lsqr
+ from scipy.sparse.linalg import lsqr as sparse_lsqr # noqa
+
+
+try: # SciPy >= 0.19
+ from scipy.special import comb, logsumexp
+except ImportError:
+ from scipy.misc import comb, logsumexp # noqa
 
 
 def parallel_helper(obj, methodname, *args, **kwargs):
- """Helper to workaround Python 2 limitations of pickling instance methods"""
+ """Workaround for Python 2 limitations of pickling instance methods"""
  return getattr(obj, methodname)(*args, **kwargs)
 
 

sklearn/utils/tests/test_random.py

@@ -2,10 +2,10 @@
 
 import numpy as np
 import scipy.sparse as sp
-from scipy.misc import comb as combinations
 from numpy.testing import assert_array_almost_equal
 from sklearn.utils.random import sample_without_replacement
 from sklearn.utils.random import random_choice_csc
+from sklearn.utils.fixes import comb
 
 from sklearn.utils.testing import (
  assert_raises,
@@ -88,7 +88,7 @@ def check_sample_int_distribution(sample_without_replacement):
  # Counting the number of combinations is not as good as counting the
  # the number of permutations. However, it works with sampling algorithm
  # that does not provide a random permutation of the subset of integer.
- n_expected = combinations(n_population, n_samples, exact=True)
+ n_expected = comb(n_population, n_samples, exact=True)
 
  output = {}
  for i in range(n_trials):