Path: utzoo!utgpu!watmath!clyde!att!rutgers!deimos!uxc!uxc.cso.uiuc.edu!uxg.cso.uiuc.edu!uicsrd.csrd.uiuc.edu!jaxon
From: jaxon@uicsrd.csrd.uiuc.edu
Newsgroups: comp.lang.apl
Subject: Re: Visualization of arrays
Message-ID: <49700008@uicsrd.csrd.uiuc.edu>
Date: 8 Feb 89 20:28:00 GMT
References: <121@infbsgr.infbs>
Lines: 23
Nf-ID: #R:infbsgr.infbs:121:uicsrd.csrd.uiuc.edu:49700008:000:1188
Nf-From: uicsrd.csrd.uiuc.edu!jaxon    Feb  8 14:28:00 1989


The default display of rank 4 arrays isn't particularly good.  I prefer
enclosing them along the last two dimensions before they are displayed.
I find the resulting display (a 2D array of 2D arrays) lets me compute
the index of an element visually, and lets me notice adjacency along the
leading axes more easily.

In expressions I seldom 'use' more than 3 axes, the rest are just carried
along through the pervasive functions or others derived from the Each
operator.  To visualize those expressions, I generally enclose either
the axes I'm working on, or the complementary set.

In every APL I've known, arrays are stored in row-major order.  On most
high performance equipment,  the innermost loops should access items
along the trailing dimensions, so I also try to keep data that are used
together adjacent along some trailing axis.   If you are doing  Reductions
or Scans, however, you might want to test the relative performance of
different reduction axes.   This storage order is the "opposite" of
Fortran, so where you might prefer pre-multiplication inner products
in F77, you will want to convert to post-multiplication for APL.  

regards
Greg Jaxon  (jaxon@uicsrd.uiuc.edu)