cosmit

agramfort · agramfort · commit 27b09f8d4c43 · 2015-09-09T08:37:27.000+02:00
diff --git a/sklearn/ensemble/iforest.py b/sklearn/ensemble/iforest.py
@@ -5,7 +5,6 @@
 from __future__ import division
 
 import numpy as np
-from warnings import warn
 
 from scipy.sparse import issparse
 
@@ -126,7 +125,7 @@ def fit(self, X, y=None, sample_weight=None):
 
         Parameters
         ----------
-        X : array-like or sparse matrix, shape=(n_samples, n_features)
+        X : array-like or sparse matrix, shape (n_samples, n_features)
             The input samples. Use ``dtype=np.float32`` for maximum
             efficiency. Sparse matrices are also supported, use sparse
             ``csc_matrix`` for maximum efficieny.
@@ -151,8 +150,8 @@ def fit(self, X, y=None, sample_weight=None):
         # ensure that max_sample is in [1, n_samples]:
         n_samples = X.shape[0]
         if not (self.max_samples <= n_samples):
-            raise ValueError("max_samples (default=256) is greater than the total" 
-                             " number of samples")
+            raise ValueError("max_samples (default=256) is greater than the "
+                             "total number of samples")
         if not (0 < self.max_samples):
             raise ValueError("max_samples has to be positive")
 
diff --git a/sklearn/ensemble/tests/test_iforest.py b/sklearn/ensemble/tests/test_iforest.py
@@ -12,7 +12,6 @@
 from sklearn.utils.testing import assert_array_equal
 from sklearn.utils.testing import assert_array_almost_equal
 from sklearn.utils.testing import assert_raises
-from sklearn.utils.testing import assert_warns
 
 from sklearn.grid_search import GridSearchCV, ParameterGrid
 from sklearn.ensemble import IsolationForest
@@ -96,7 +95,7 @@ def test_iforest_error():
     assert_raises(ValueError,
                   IsolationForest(max_samples=2.0).fit, X)
     assert_raises(ValueError,
-                 IsolationForest(max_samples=1000).fit, X)
+                  IsolationForest(max_samples=1000).fit, X)
     # cannot check for string values
 
 
