diff --git a/scikits/learn/linear_model/tests/test_least_angle.py b/scikits/learn/linear_model/tests/test_least_angle.py index 4521dbbab5931b3c784856e4e40485f06611ba97..022905793fd70517a94151296e73d4b1d6fe774d 100644 --- a/scikits/learn/linear_model/tests/test_least_angle.py +++ b/scikits/learn/linear_model/tests/test_least_angle.py @@ -1,5 +1,5 @@ import numpy as np -from numpy.testing import assert_, assert_array_almost_equal +from numpy.testing import assert_array_almost_equal from scikits.learn import linear_model, datasets @@ -84,7 +84,7 @@ def test_collinearity(): y = np.array([1., 0., 0]) _, _, coef_path_ = linear_model.lars_path(X, y) - assert_(not np.isnan(coef_path_).any()) + assert (not np.isnan(coef_path_).any()) assert_array_almost_equal(np.dot(X, coef_path_[:,-1]), y) diff --git a/scikits/learn/tests/test_neighbors.py b/scikits/learn/tests/test_neighbors.py index 3921fadf6b74c090b2f8610915eb18784a8f0815..79577a3ea651a84193c4c23cb74fdc92e0fb2215 100644 --- a/scikits/learn/tests/test_neighbors.py +++ b/scikits/learn/tests/test_neighbors.py @@ -1,6 +1,5 @@ import numpy as np -from numpy.testing import assert_array_almost_equal, assert_array_equal, \ - assert_ +from numpy.testing import assert_array_almost_equal, assert_array_equal from scikits.learn import neighbors, datasets @@ -58,13 +57,13 @@ def test_neighbors_iris(): assert_array_equal(clf.predict(iris.data), iris.target) clf.fit(iris.data, iris.target, n_neighbors=9, algorithm=s) - assert_(np.mean(clf.predict(iris.data)== iris.target) > 0.95) + assert np.mean(clf.predict(iris.data)== iris.target) > 0.95 for m in ('barycenter', 'mean'): rgs = neighbors.NeighborsRegressor() rgs.fit(iris.data, iris.target, mode=m, algorithm=s) - assert_(np.mean( - rgs.predict(iris.data).round() == iris.target) > 0.95) + assert np.mean( + rgs.predict(iris.data).round() == iris.target) > 0.95 def test_kneighbors_graph():