[Numpy-discussion] Re: ndarray.fill and ma.array.filled

[Pierre GM]

> If you sum along a particular dimension and encounter a masked value,
> the result is masked.  

That's not how it currently works (still on 0.9.6):

x=arange(12).reshape(3,4)
MA.masked_where((x%5==0) | (x%3==0),x).sum(0)
array(data = [12  1  2 18],
         mask =  [False False False False],
         fill_value=999999)

and frankly, I'd be quite frustrated if it had to change:
- `filled` is not a ndarray method, which means that a.filled(0).sum() fails 
if a is not MA. Right now, I can use a.sum() without having to check the 
nature of a first. 
- this behavior was already in Numeric
- All my scripts rely on it (but I guess that's my problem)
- The current way reflects how mask are used in GIS or image processing.

> If you would like to ignore masked values, you write 
> a.filled(0).sum() instead of a.sum(). In 1d case, you can also use
> a.compress().sum().

Once again, Sasha, I'd agree with you if it wasn't a major difference

> In other words, what in R you achieve with a 
> flag, such as in sum(a, na.rm=TRUE), in numpy you achieve by an
> explicit call to "fill".  This is not quite the same as na.actions in
> R, but that is what I had in mind.

I kinda like the idea of a flag, though