Hi Derek,
On Mon, Jun 13, 2011 at 4:17 PM, Derek Homeier <
de...@astro.physik.uni-goettingen.de> wrote:
> Hi Ralf,
>
> > I am pleased to announce the availability of the first release candidate
> of NumPy 1.6.1. This is a bugfix release, list of fixed bugs:
> > #1834 einsum fails for specific shapes
> > #1837 einsum throws nan or freezes python for specific array shapes
> > #1838 object <-> structured type arrays regression
> > #1851 regression for SWIG based code in 1.6.0
> > #1863 Buggy results when operating on array copied with astype()
>
> there are a bunch of test failures under Python3, mostly with new datetime
> tests
> trivially fixed by 'str' -> asbytes('str') conversions (I can send a patch
> or pull request
> for that), and two more I can't provide a fix for yet:
Thanks for testing.
>
> FAIL: Test custom format function for each element in array.
> ----------------------------------------------------------------------
>
This test is not in 1.6.x, only in master. I suspect the same is true for
the datetime tests, but perhaps not for the S5/U5 thing. Can you clean your
install dir and try again?
Thanks,
Ralf
> Traceback (most recent call last):
> File
> "/Users/derek/lib/python3.2/site-packages/numpy/core/tests/test_arrayprint.py",
> line 86, in test_format_function
> "[0x0L 0x1L 0x2L]")
> File "/Users/derek/lib/python3.2/site-packages/numpy/testing/utils.py",
> line 313, in assert_equal
> raise AssertionError(msg)
> AssertionError:
> Items are not equal:
> ACTUAL: '[0x0 0x1 0x2]'
> DESIRED: '[0x0L 0x1L 0x2L]'
>
> - this is
> x = np.arange(3)
> assert_(np.array2string(x, formatter={'all':_format_function}) == \
> "[. o O]")
> assert_(np.array2string(x, formatter={'int_kind':_format_function})
> ==\
> "[. o O]")
> assert_(np.array2string(x, formatter={'all':lambda x: "%.4f" % x})
> == \
> "[0.0000 1.0000 2.0000]")
> assert_equal(np.array2string(x, formatter={'int':lambda x: hex(x)}),
> \
> "[0x0L 0x1L 0x2L]")
>
> (btw. these were all assert_(a == b) before, which do not give a useful
> error message
> by default - any reason not to change them to assert_equal(, b)?)
>
> and
> FAIL: Ticket #1748
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/derek/lib/python3.2/site-packages/numpy/core/tests/test_regression.py",
> line 1549, in test_string_astype
> assert_equal(b.dtype, np.dtype('S5'))
> File "/Users/derek/lib/python3.2/site-packages/numpy/testing/utils.py",
> line 313, in assert_equal
> raise AssertionError(msg)
> AssertionError:
> Items are not equal:
> ACTUAL: dtype('<U5')
> DESIRED: dtype('|S5')
>
> for
>
> s1 = asbytes('black')
> s2 = asbytes('white')
> s3 = asbytes('other')
> a = np.array([[s1],[s2],[s3]])
> assert_equal(a.dtype, np.dtype('S5'))
> b = a.astype('str')
> assert_equal(b.dtype, np.dtype('S5'))
>
> I can get around this by changing the last lines to
>
> b = a.astype(np.dtype('S5'))
> assert_equal(b.dtype, np.dtype('S5'))
>
> but am not sure if this preserves the purpose of the test...
>
> HTH,
> Derek
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion
