[Numpy-discussion] numpy.nansum() behavior in 1.3.0

[josef.pktd at gmail.com]

On Mon, Jun 1, 2009 at 2:45 PM, Keith Goodman <kwgoodman at gmail.com> wrote:
> On Mon, Jun 1, 2009 at 11:34 AM,  <josef.pktd at gmail.com> wrote:
>> On Mon, Jun 1, 2009 at 2:26 PM, Keith Goodman <kwgoodman at gmail.com> wrote:
>>> On Mon, Jun 1, 2009 at 11:16 AM,  <josef.pktd at gmail.com> wrote:
>>>> On Mon, Jun 1, 2009 at 1:43 PM, Keith Goodman <kwgoodman at gmail.com> wrote:
>>>>> On Mon, Jun 1, 2009 at 9:55 AM, Michael Hearne <mhearne at usgs.gov> wrote:
>>>>>> A question (and possibly a bug):
>>>>>>
>>>>>> What should be returned when I do:
>>>>>>
>>>>>> numpy.nansum([])
>>>>>>
>>>>>> In my copy of numpy 1.1.1, I get 0.0.  This is what I would expect to
>>>>>> see.
>>>>>> However, this behavior seems to have changed in 1.3.0, in which I get
>>>>>> nan.
>>>>>
>>>>> Here's a weird one. This is in numpy 1.2:
>>>>>
>>>>>>> np.sum(9)
>>>>>   9
>>>>>>> np.sum(9.0)
>>>>>   9.0
>>>>>>> np.nansum(9)
>>>>>   9
>>>>>>> np.nansum(9.0)
>>>>> ---------------------------------------------------------------------------
>>>>> IndexError: 0-d arrays can't be indexed.
>>>>
>>>> wrong argument in isnan, I think
>>>>
>>>> Josef
>>>>
>>>> In file: C:\Programs\Python25\Lib\site-packages\numpy\lib\function_base.py
>>>>
>>>> def _nanop(op, fill, a, axis=None):
>>>>    """
>>>> ...
>>>>
>>>>    """
>>>>    y = array(a,subok=True)
>>>> -    mask = isnan(a)
>>>> +   mask = isnan(y)
>>>>    if mask.all():
>>>>        return np.nan
>>>>
>>>>    if not issubclass(y.dtype.type, np.integer):
>>>>        y[mask] = fill
>>>>
>>>>    return op(y, axis=axis)
>>>
>>> The problem I came across, np.nansum(float), is caused by this line
>>>
>>> y[mask] = fill
>>>
>>> when y is 0-d.
>>
>> if mask is an array then this works, my initial solution was mask =
>> np.array(mask).  then I thought it works also the other way, but it
>> doesn't. I shouldn't have changed my mind
>>
>>>>> y
>> array(9.0)
>>>>> y[np.array(np.isnan(9))] = 0
>>>>> y
>> array(9.0)
>>>>> y[np.isnan(np.array(9))] = 0
>> Traceback (most recent call last):
>>  File "<pyshell#45>", line 1, in <module>
>>    y[np.isnan(np.array(9))] = 0
>> IndexError: 0-d arrays can't be indexed.
>
> Nice!
>
> Are you going to make the change?

Not me,

the original problem was more difficult to track down
>>> np.nansum(np.array([]))
1.#QNAN

Here's a good one:

>>> np.isnan([]).all()
True
>>> np.isnan([]).any()
False

Josef