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) > --------------------------------------------------------------------------- > AssertionError Traceback (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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