<snip>
> Please, no. It's another thing to remember and another way to shoot
> yourself in the foot and introduce casual bugs.
>
> FWIW, my vote is to raise an error or return a nan, which will likely
> eventually raise an error. If I have all nans, it's usually the case
> that something's off, and I'd like to know sooner rather than later.
>
>
Here is what I have currently implemented. First, define an AllNanError
class AllNanError(ValueError):
def __init__(self, msg, result):
ValueError.__init__(self, msg)
self.result = result
For nanmax/nanmin/nanargmax/nanargmin this error is raised for all-nan axis
and the result is attached. The exception can then be caught and the result
examined. A ValueError is what amax, amin return for empty arrays.
For nanmax/nanmin the result for an empty slice is nan. For
argnanmax/argnanmin the result of an empty slice is -1, which is easier to
read and remember than intp.min. A ValueError is what argmin, argmax
currently return for empty arrays. Note that both of these functions can
give wrong results if they contain some min/max values respectively. That
is an old bug and I haven't fixed it.
The nanmean/nanvar/nanstd functions currently raise a warning for all-nan
slices and the result for such is nan. These could also be made to raise an
error.
Thoughts?
Chuck
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