[Numpy-discussion] using the same vocabulary for missing value ideas

[Benjamin Root]

On Wednesday, July 6, 2011, Christopher Jordan-Squire <cjordan1 at uw.edu> wrote:
>
>
> On Wed, Jul 6, 2011 at 5:03 PM, Benjamin Root <ben.root at ou.edu> wrote:
>
> On Wednesday, July 6, 2011, Dag Sverre Seljebotn
> <d.s.seljebotn at astro.uio.no> wrote:
>> On 07/06/2011 08:25 PM, Christopher Barker wrote:
>>> Mark Wiebe wrote:
>>>> 1) NA vs IGNORE and bitpattern vs mask are completely independent. Any
>>>> combination of NA as bitpattern, NA as mask, IGNORE as bitpattern, and
>>>> IGNORE as mask are reasonable.
>>>
>>> Is this really true? if you use a bitpattern for IGNORE, haven't you
>>> just lost the ability to get the original value back if you want to stop
>>> ignoring it? Maybe that's not inherent to what an IGNORE means, but it
>>> seems pretty key to me.
>>
>> There's the question of how reductions treats the value. IIUC, IGNORE as
>> bitpattern would imply that reductions treat the value as 0, which is a
>> question orthogonal to whether the value can possibly be unmasked or not.
>>
>> Dag Sverre
>>
>
> Just because we are trying to be exact here, the reductions would
> treat IGNORE as the operation's identity.  Therefore, for addition, it
> would be treated like 0, but for multiplication, it is treated like a
> 1.
>
> Ben Root
>
> Yes. But, as discussed on another thread, that can lead to unexpected results when it's propagated through several operations.
>
>

If you are talking about means, for example, then the count is
adjusted before dividing.  It is like they never existed. Same with
standard deviation. Of course, there are issues with having fewer
samples, but that isn't a problem caused by the underlying concept of
skipping elements.

As long as the underlying mathematical support for array math is still
valid, I am not certain what the issue is.  Matrix math on the other
hand...

Ben Root