[Numpy-discussion] [Announce] Numpy 1.3.0b1

[Robert Pyle]

On Mar 19, 2009, at 11:35 AM, Charles R Harris wrote:

>
>
> On Thu, Mar 19, 2009 at 9:17 AM, Robert Pyle  
> <rpyle at post.harvard.edu> wrote:
> I'm getting one test failure with 1.3.0b1 ---
>
> FAIL: test_umath.TestComplexFunctions.test_loss_of_precision(<type
> 'numpy.complex256'>,)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/Library/Frameworks/Python.framework/Versions/4.1.30101/lib/
> python2.5/site-packages/nose-0.10.3.0001-py2.5.egg/nose/case.py", line
> 182, in runTest
>     self.test(*self.arg)
>   File "/Library/Frameworks/Python.framework/Versions/4.1.30101/lib/
> python2.5/site-packages/numpy/core/tests/test_umath.py", line 498, in
> check_loss_of_precision
>     check(x_series, 2*eps)
>   File "/Library/Frameworks/Python.framework/Versions/4.1.30101/lib/
> python2.5/site-packages/numpy/core/tests/test_umath.py", line 480, in
> check
>     assert np.all(d < rtol), (np.argmax(d), x[np.argmax(d)], d.max())
> AssertionError: (0, nan, nan)
>
> Yes, that test fails on some architectures. What type of cpu do you  
> have? It would help if you could track down the cause of the nans,  
> see ticket #1038.

CPU is PPC (G5).  I added a print statement in the test to pin things  
down a bit.  The failing test appears to be

             d = np.absolute(np.arcsinh(x)/np.arcsinh(x+0j).real - 1)
             assert np.all(d < rtol), (np.argmax(d), x[np.argmax(d)],  
d.max())

with dtype =  <type 'numpy.complex256'>

It passes with dtype =  <type 'numpy.complex64'> and dtype =  <type  
'numpy.complex128'>

Is that any help?

Bob