From 7fa40ad5023c8f2a35bdecbce9c4193141aec203 Mon Sep 17 00:00:00 2001
From: Fabian Pedregosa <fabian.pedregosa@inria.fr>
Date: Wed, 9 Mar 2011 09:16:26 +0100
Subject: [PATCH] Remain compatible with numpy 1.2
---
scikits/learn/linear_model/tests/test_least_angle.py | 4 ++--
scikits/learn/tests/test_neighbors.py | 9 ++++-----
2 files changed, 6 insertions(+), 7 deletions(-)
diff --git a/scikits/learn/linear_model/tests/test_least_angle.py b/scikits/learn/linear_model/tests/test_least_angle.py
index 4521dbbab5..022905793f 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 3921fadf6b..79577a3ea6 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():
--
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