On Mon, Apr 14, 2014 at 1:09 PM, Warren Weckesser
warren.weckes...@gmail.com wrote:
The test function numpy.testing.assert_equal fails when comparing -0.0 and
0.0:
In [16]: np.testing.assert_equal(-0.0, 0.0)
---
AssertionErrorTraceback (most recent call last)
ipython-input-16-4063bd6da228 in module()
1 np.testing.assert_equal(-0.0, 0.0)
/Users/warren/anaconda/lib/python2.7/site-packages/numpy/testing/utils.pyc
in assert_equal(actual, desired, err_msg, verbose)
309 elif desired == 0 and actual == 0:
310 if not signbit(desired) == signbit(actual):
-- 311 raise AssertionError(msg)
312 # If TypeError or ValueError raised while using isnan and
co, just handle
313 # as before
AssertionError:
Items are not equal:
ACTUAL: -0.0
DESIRED: 0.0
There is code that checks for this specific case, so this is
intentional. But this is not consistent with how negative zeros in
arrays are compared:
In [22]: np.testing.assert_equal(np.array(-0.0), np.array(0.0)) # PASS
In [23]: a = np.array([-0.0])
In [24]: b = np.array([0.0])
In [25]: np.testing.assert_array_equal(a, b) # PASS
Is there a reason the values are considered equal in an array, but not
when compared as scalars?
Unlikely to be intentional. I expect this was a fix to assert_equal that
wasn't synced to assert_array_equal.
Ralf
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