[SciPy-Dev] Policy for minimum numpy version

[Joseph Fox-Rabinovitz]

Here is an example of `np.percentile` workarounds for
`scipy.stats.iqr`: https://github.com/scipy/scipy/pull/5808

    -Joe

On Wed, Jul 27, 2016 at 2:18 PM, CJ Carey <perimosocordiae at gmail.com> wrote:
> Most recently I've wished for np.full and np.full_like, though I admit that
> they're very easy to work around.
>
> More difficult to replace is np.partition and np.argpartition, which are
> extremely useful in the few cases that they're needed but also non-trivial
> to implement efficiently. Typically the work-arounds look like this (not my
> code):
> https://github.com/lemaoliu/Agtarbidir/blob/8762efcb29b37724c2af13f9393d1eaa5ec6faf8/numpy_compat.py
>
> On Wed, Jul 27, 2016 at 12:52 PM, Eric Quintero <ericq at caltech.edu> wrote:
>>
>> Hi All,
>>
>> In gh-6058, I’ve run into a test failure because a numpy function was not
>> available in version 1.7 (the function being np.fft.rfftfreq). This is easy
>> enough to work around, but I wonder when we should decide to move up the
>> minimum required numpy version.
>>
>> Debian stable currently offers numpy 1.8.2. Ubuntu 12.04 LTS (which is EOL
>> next April) is stuck on 1.6.1, so they’re already left behind. Ubuntu 14.04
>> LTS has 1.8.2.
>>
>> Has anyone ran into compatibility issues with 1.7 before? In
>> _lib._numpy_compat, there is another 1.7 workaround in place for
>> np.testing.assert_warns.
>>
>> -Eric Q.
>>
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>
>
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