On Tue, Aug 31, 2010 at 10:13 PM, David Huard <david.hu...@gmail.com> wrote:
>
>
> On Tue, Aug 31, 2010 at 7:02 AM, Ralf Gommers <ralf.gomm...@googlemail.com
> > wrote:
>
>>
>>
>> On Tue, Aug 31, 2010 at 3:44 AM, David Huard <david.hu...@gmail.com>wrote:
>>
>>>
>>> I just added a warning alerting concerned users (r8674), so this takes
>>> care of the bug fix and Nils wish to avoid a silent change in behavior.
>>> These two changes could be included in 1.5 if Ralf feels this is
>>> worthwhile.
>>>
>>> That looks like a reasonable solution. I haven't got a strong opinion on
>> whether or not to change the 'normed' keyword to 'density'.
>>
>> Looking at the changes, I don't think that is the right way to do the
>> filtering in the tests. resetwarnings() removes all filters including the
>> ones previously set by users, and should therefore not be used. Better to
>> either raise a specific warning and filter on that, or to filter on the
>> message content with:
>> warnings.filterwarnings('ignore' , message="This release of NumPy
>> fixes a normalization bug in histogram").
>> I found one more place where resetwarnings() is used, in
>> test_arraysetops.py, I'll change that in trunk. Related problem there is
>> that the warning in warnings.warn is not a DeprecationWarning.
>>
>> The above problem is easy to fix, but in any case it's too late to go into
>> 1.5.0 - I'll tag the final release tonight.
>>
>>
> Ralf,
>
> test_function_base and test_arraysetops now do not use resetwarnings. What
> I did is added a warning filter and popped it out of the filters list
> afterwards. Is this OK ?
>
That looks like the best solution to me (besides the catch_warnings context
manager, which we can't use).
>
> In other tests, what is done is rather
>
> warnings.simplefilter('ignore', DeprecationWarning)
> test_function()
> warnings.simplefilter('default', DeprecationWarning)
>
> but that will also override any user-defined setup, no ?
>
Yes, it's less invasive than resetwarnings() but could also be annoying for
some users. Would be good to do this in a consistent way for all warnings
and tests, and describe that in
http://projects.scipy.org/numpy/wiki/ApiDeprecation.
Ralf
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