[Numpy-discussion] in the NA discussion, what can we agree on?

Gary Strangman strang@nmr.mgh.harvard....
Fri Nov 4 11:37:33 CDT 2011


> On Fri, Nov 4, 2011 at 11:08 AM, Lluís <xscript@gmx.net> wrote:
>       Gary Strangman writes:
>       [...]
>
>       > destructive + non-propagating = the data point is truly
>       missing, this is the
>       > nature of that data point, such missingness should be
>       replicated in elementwise
>       > operations, but such missingness should NOT interfere with
>       reduction operations
>       > that involve that datapoint (np.sum([1,MISSING])=1)
> 
> What do you define as element-wise operations?
> 
> Is a sum on an array an element-wise operation?
> 
>  >>> [1, MISSING]+2
>  [1, MISSING]
> 
> 
> did you mean [3, MISSING]?
>  
>       Or is it just a form of reduction (after shape broadcasting)?
>
>        >>> [1, MISSING]+2
>        [3, 2]
>
>       For me it's the second, so the only time where special values
>       "propagate" in a
>       non-propagating scenario is when you slice an array.
> 
> 
> Propagation has a very specific meaning here, and I think it is causing
> confusion elsewhere.  Propagation (to me) is the *exact* same behavior that
> occurs with NaNs, but generalized to any dtype.  It seems like you are
> taking "propagate" to mean whether the mask of the inputs follow on to the
> mask of the output.  This is related, but is possibly a murkier concept and
> should probably be cleaned up.

I think different people have different notions of propagation here. Yes, 
my notion was more related to input masks "propagating" to output masks. 
It's important to know you define it differently ... and I think the 
difference in (implicit) definitions is indeed causing confusion. At least 
it is for me. ;-)

-best
Gary


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