[Numpy-discussion] numpy.nansum() behavior in 1.3.0
josef.pktd@gmai...
josef.pktd@gmai...
Mon Jun 1 18:43:32 CDT 2009
On Mon, Jun 1, 2009 at 7:30 PM, Robert Kern <robert.kern@gmail.com> wrote:
> On Mon, Jun 1, 2009 at 15:31, <josef.pktd@gmail.com> wrote:
>> On Mon, Jun 1, 2009 at 4:06 PM, Alan G Isaac <aisaac@american.edu> wrote:
>>> On 6/1/2009 3:38 PM josef.pktd@gmail.com apparently wrote:
>>>> Here's a good one:
>>>>
>>>>>>> np.isnan([]).all()
>>>> True
>>>>>>> np.isnan([]).any()
>>>> False
>>>
>>>
>>> >>> all([])
>>> True
>>> >>> any([])
>>> False
>>
>> also:
>>
>>>>> y
>> array([], dtype=float64)
>>>>> (y>0).all()
>> True
>>>>> (y>0).any()
>> False
>>>>> ((y>0)>0).sum()
>> 0
>>
>> I don't know what's the logic, but it causes the bug in np.nansum.
>
> You will have to special-case empty arrays, then.
>
is np.size the right check for non-empty array, including subtypes?
i.e.
if y.size and mask.all():
return np.nan
or more explicit
if y.size > 0 and mask.all():
return np.nan
Josef
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