Better treatment for complex numbers #1098
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Oops I have NOSE_DOCTEST_TESTS=t and NOSE_WITH_DOCTEST=t and that's why I had failing tests. There is no fail/error when I remove these envvars. |
It looks like sorting by dtype itself does not work.
To see that, try this snippet:
>>> from numpy import dtype
>>> sorted([dtype('bool'), dtype('float64'), dtype('complex64'),
... dtype('float64'), dtype('object')])
[dtype('bool'),
dtype('float64'),
dtype('complex64'),
dtype('float64'),
dtype('object')]
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The bug I fixed in bae8155 is very serious one and it could have effect even without complex number implementation I added. It is probably a bug in numpy. Try the following code and observe sorting fails. I checked with numpy 1.6.1. >>> from numpy import dtype
>>> sorted([dtype('bool'), dtype('float64'), dtype('complex64'),
... dtype('float64'), dtype('object')])
[dtype('bool'),
dtype('float64'),
dtype('complex64'),
dtype('float64'),
dtype('object')] |
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BTW, I am using complex64 here but it should be complex128, right? |
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Yes, should be complex128 |
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Merged this in. Should make a sweep and change complex64 -> complex128 at some point, though |
tkf
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May 16, 2012
As mentioned in pandas-dev#1098.
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This fixes #1083. I checked that the number of failing tests (SKIP=38, errors=5, failures=34) do not increase with these change sets.
BTW, in form_blocks why not simply do
instead of calculating length?: