[Numpy-discussion] in the NA discussion, what can we agree on?
Gary Strangman
strang@nmr.mgh.harvard....
Fri Nov 4 15:03:02 CDT 2011
> > NAN and NA apparently fall into the PdS class.
> >
>
> Here is where I think we need ot be a bit more careful. It is true that we want
> NAN and MISSING to propagate, but then we additionally want to ignore it
> sometimes. This is precisely why we have functions like nansum. Although people
> are well-aware of this desire, I think this thread has largely conflated the
> issues when discussing "propagation".
>
> To push this forward a bit, can I propose that IGNORE behave as: PnC
>
> >>> x = np.array([1, 2, 3])
> >>> y = np.array([10, 20, 30])
> >>> ignore(x[2])
> >>> x
> [1, IGNORED(2), 3]
> >>> x + 2
> [3, IGNORED(4), 5]
> >>> x + y
> [11, IGNORED(22), 33]
> >>> z = x.sum()
> >>> z
> IGNORED(6)
> >>> unignore(z)
> >>> z
> 6
> >>> x.sum(skipIGNORED=True)
> 4
>
> When done in this fashion, I think it is perfectly fine for "masks to be
> unmasked".
In my mind, IGNORED items should be skipped by default (i.e., skipIGNORED
seems redundant ... isn't that what ignoring is all about?). Thus I might
instead suggest the opposite (default) behavior at the end:
>>> x = np.array([1, 2, 3])
>>> y = np.array([10, 20, 30])
>>> ignore(x[2])
>>> x
[1, IGNORED(2), 3]
>>> x + 2
[3, IGNORED(4), 5]
>>> x + y
[11, IGNORED(22), 33]
>>> z = x.sum()
>>> z
4
>>> unignore(x).sum()
6
>>> x.sum(keepIGNORED=True)
6
(Obviously all the syntax is totally up for debate.)
-best
Gary
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