[Numpy-discussion] ANN: Numpy 1.6.1 release candidate 1

Ralf Gommers ralf.gommers@googlemail....
Mon Jun 13 09:29:52 CDT 2011


Hi Derek,

On Mon, Jun 13, 2011 at 4:17 PM, Derek Homeier <
derek@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
>
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