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authorJulian Taylor <jtaylor.debian@googlemail.com>2014-03-12 20:44:14 +0100
committerJulian Taylor <jtaylor.debian@googlemail.com>2014-03-13 21:10:31 +0100
commit7d53c812d3e68ff28320ee7e32bc9816937b4142 (patch)
tree8906807748186d9d5217a15656cc01059dacf3bc /numpy/lib/tests/test_function_base.py
parenteea1a9c49024c18fda3ad9782dee3956492cfa1a (diff)
downloadnumpy-7d53c812d3e68ff28320ee7e32bc9816937b4142.tar.gz
MAINT: revert back to separate median implementation
Merging median and percentile make would break astropy and quantities as we don't call mean anymore. These packages rely on overriding mean to add their own median behavior.
Diffstat (limited to 'numpy/lib/tests/test_function_base.py')
-rw-r--r--numpy/lib/tests/test_function_base.py14
1 files changed, 14 insertions, 0 deletions
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
index 27e7302ce..fcf89cb90 100644
--- a/numpy/lib/tests/test_function_base.py
+++ b/numpy/lib/tests/test_function_base.py
@@ -1919,6 +1919,20 @@ class TestMedian(TestCase):
assert_almost_equal(np.median(x2), 2)
assert_allclose(np.median(x2, axis=0), x)
+ def test_subclass(self):
+ # gh-3846
+ class MySubClass(np.ndarray):
+ def __new__(cls, input_array, info=None):
+ obj = np.asarray(input_array).view(cls)
+ obj.info = info
+ return obj
+
+ def mean(self, axis=None, dtype=None, out=None):
+ return -7
+
+ a = MySubClass([1,2,3])
+ assert_equal(np.median(a), -7)
+
def test_extended_axis(self):
o = np.random.normal(size=(71, 23))
x = np.dstack([o] * 10)