Hi,
On Sat, Aug 9, 2014 at 2:18 PM, Thomas Caswell wrote:
> I have tagged the third (and hopefully last) RC for 1.4.
>
> The outstanding issues are documentation related (rebase guide which I
> need to edit a bit more, a what's new entry, a decision if we have
> improved the install documentation enough, and to make sure that docs
> for backend_bases gets added to sphinx) and the re-design of the front
> page.
Thanks for doing this.
I did a full test against the scipy stack:
https://travis-ci.org/matthew-brett/scipy-stack-osx-testing/builds/32131131
It turns out there's a new failure testing pandas against mpl,
reproduced with ``nosetests pandas.tseries.tests.test_converter``
after installing pandas:
==
ERROR: test_dateindex_conversion
(pandas.tseries.tests.test_converter.TestDateTimeConverter)
--
Traceback (most recent call last):
File
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/tseries/tests/test_converter.py",
line 77, in test_dateindex_conversion
xp = converter.dates.date2num(dateindex)
File
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/dates.py",
line 310, in date2num
return _to_ordinalf_np_vectorized(d)
File
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/lib/function_base.py",
line 1573, in __call__
return self._vectorize_call(func=func, args=vargs)
File
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/lib/function_base.py",
line 1633, in _vectorize_call
ufunc, otypes = self._get_ufunc_and_otypes(func=func, args=args)
File
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/lib/function_base.py",
line 1597, in _get_ufunc_and_otypes
outputs = func(*inputs)
File
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/dates.py",
line 204, in _to_ordinalf
base = float(dt.toordinal())
AttributeError: 'numpy.datetime64' object has no attribute 'toordinal'
I confirmed that the same command running against mpl 1.3.1 passes.
Same error with numpy 1.7.1 and numpy 1.8.2. Does this ring any
bells?
Cheers,
Matthew
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