[Numpy-discussion] Use-case for np.choose

[David Goldsmith]

OK, let me see if I'm interpreting this example correctly:

>>> c1=np.arange(2).reshape(2,1,1); c1
array([[[0]],

       [[1]]])
>>> c2=2+np.arange(2).reshape(1,1,2); c2
array([[[2, 3]]])
>>> a=np.eye(2,dtype=int)
>>> np.choose(a, [c1, c2])
array([[[2, 0],
        [0, 3]],

       [[2, 1],
        [1, 3]]])

First, everything is being broadcast to (2,2,2); a is broadcast to [[[1,0],
[0,1]], [[1,0], [0,1]]], c1 is broadcast to [[[0,0], [0,0]], [[1,1], [1,1]]]
and c2 is broadcast to [[[2,3], [2,3]], [[2,3], [2,3]]].  Now result is
created by "stepping through" broadcast a and using, respectively, the
positionally corresponding element from broadcast c1 (resp. c2) if the value
in a at the position is 0 (resp. 1).  At least, this gives the result above
(but I have not examined other possible broadcasts of the arguments to see
if they would also give the result - I conjectured what appeared to me to be
the most "natural" broadcasts and checked to see if it worked and it does;
is there something I should know - e.g., uniqueness of the result, or a rule
governing how choose broadcasts - to *know* that the broadcasts above are
indeed the broadcasts choose is using?)

Thanks again,

DG
On Sun, Nov 8, 2009 at 8:19 PM, Anne Archibald <peridot.faceted at gmail.com>wrote:

> 2009/11/8 David Goldsmith <d.l.goldsmith at gmail.com>:
> > On Sun, Nov 8, 2009 at 7:40 PM, Anne Archibald <
> peridot.faceted at gmail.com>
> > wrote:
> >>
> >> As Josef said, this is not correct. I think the key point of confusion
> is
> >> this:
> >>
> >> Do not pass choose two arrays.
> >>
> >> Pass it one array and a *list* of arrays. The fact that choices can be
> >> an array is a quirk we can't change, but you should think of the
> >> second argument as a list of arrays,
> >
> > Fine, but as you say, one *can* pass choose an array as the second
> argument
> > and it doesn't raise an exception, so if someone is stupid/careless
> enough
> > to pass an array for `choices`, how is choose interpreting it as a list?
> Is
> > the first dimension "list converted" (so that, e.g., my (2,1,2) example
> is
> > interpreted as a two element list, each of whose elements is a (1,2)
> array)?
>
> It seems to me that this is the only reasonable interpretation, yes.
> After all, arrays behave like sequences along the first axis, whose
> elements are arrays of one less dimension. Thus if you pass an array,
> any broadcasting happens ignoring the first axis, which is a rather
> abnormal pattern for numpy broadcasting, but necessary here.
>
> As a bonus, I think this is what is implemented in current versions of
> numpy. (In 1.2.1 it raises an exception if broadcasting is necessary.)
>
> Anne
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