On Thursday 19 May 2005 12:48, Uri Guttman wrote:
> >>>>> "LP" == Luke Palmer <[EMAIL PROTECTED]> writes:
> LP> On 5/18/05, Anthony Heading <[EMAIL PROTECTED]> wrote:
> >> Is there a way to target hyperoperators at different axes
> >> of a multi-dimensional array? This is an attractive
> >> feature of various APL-like languages, viz. e.g. in J:
> >> a =. 2 5 $ i. 7 - a simple 2-by-5 array
> >> a
> >> 0 1 2 3 4 - like this
> >> 5 6 0 1 2
> >> +/"1 a - sum reduce over axis 1
> >> 10 14
That is, break the array into rows, and reduce each row.
> LP> [+]<< @a
> >> +/"2 a - sum reduce over axis 2
> >> 5 7 2 4 6
Actually, that's sum reduce over planes, which gives the default
behavior when applied to a single plane, of breaking the plane
into rows, and adding the rows to each other. The result is the
same as from +/a .
The rank conjunction (") is tersely explained at
and more fully in The J Primer, J for C Programmers, and other
online publications at
> LP> Can't think of any for this one. Or maybe it's this one
> that I can LP> think of it for, and the other one which I
> i can't spit out the syntax but here is the conceptual way i
> would do it. we do have multidimensional slices so we could
> grab each slice (maybe with zip?) and pass that to [+] and
> then grab the list of results back into a array/matrix with
> one less dimension than the original.
Exactly how Iverson conceived rank for reduction.
> so it would be something like this: (very wacko pseudo code):
> @in[ * ; 2 ; * ] ==>
> map [+] ==>
> that was an (bad) attempt to slice the third entry in the
> second dimension to be summed.
You might find it useful to examine this published source code
for an early version of J
to see how Iverson's crew implemented rank.
The numbering is confusing, because they restarted at some point,
so J5.0.4 is current.
> LP> I think we're beginning to re-invent PDL.
APL and J, too.
> but is there a p6 pdl yet? they may not need much with
> multi-dim ops, slices, hyper and reduce all built in! also
> with type int (patform ints), they can get the dense storage
> needed (but losing any dimensional flexibility).
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