PDL::Tips - Small tidbits of useful arcana. Programming tidbits and such.

        use PDL;

        # Whatever happens here.

This page documents useful idioms, helpful hints and tips for using Perl Data Language v2.0.

Use CWhelp help within perldl or the CWpdldoc program from the command line for access to the PerlDL documentation. HTML versions of the pages should also be present, in the HtmlDocs/PDL directory of the PDL distribution. To find this directory, try the following

 perldl> foreach ( map{"$_/PDL/HtmlDocs"}@INC ) { p "$_\n" if -d $_ }

The following code normalizes a bunch of vectors in CW$a. This works regardless of the dimensionality of CW$a.

        $a /= $a->sumover->dummy(0);

If you want to see what the code is actually doing, try the command

        PDL::Core::set_debugging(1);

somewhere. This spews out a huge amount of debug info for PDL into STDOUT. It is planned to eventually make this redirectable and the messages selectable more accurately.

Many of the messages come from CWBasic/Core/pdlapi.c and you can look at the source to see what is going on.

If you have any extra time to work on these mechanisms, infrom the pdl-porters mailing list.

If you are running recursively something that selects certain indices of a large piddle, like

        while(1) {
                $inds = where($a>0);
                $a = $a->index($inds);
                $b = $b->index($inds);
                func($b,$a);
        }

If you are not writing to CW$b, it saves a lot of memory to change this to

                $b = $b->index($inds)->sever;

The new method CWsever is a causes the write-back relation to be forgotten. It is like copy except it changes the original piddle and returns it).

Of course, the probably best way to do the above is

        $inds = xvals ($a->long);
        while(1) {
                $inds0 = where($a>0);
                $inds1 = $inds->index($inds)->sever;
                $a = $a0->index($inds1);
                $b = $b->index($inds1)->sever;
                func($b,$a);
        }

which doesn't save all the temporary instances of CW$a in memory. See CWmandel.pl in the Demos subdirectory of the PerlDL distribution for an example.

If you really want to write speedy PP code, the first thing you need to do is to make sure that your C compiler is allowed to do the necessary optimizations.

What this means is that you have to allow as many variables as possible to go into registers:

        loop(a) %{
                $a() += $COMP(foo_member) * $b()
        %}

expands to

        for(i=0; i<10000; i++) {
                a[i] += __privtrans->foo_member * b[i];
        }

is about the worst you can do, since your C compiler is not allowed to assume that CWa doesn't clobber CWfoo_member which completely inhibits vectorization. Instead, do

        float foo = $COMP(foo_member);
        loop(a) %{
                $a() += foo * $b();
        %}

This is not a restriction caused by PP but by ANSI C semantics. Of course, we could copy the struct into local varibles and back but that could cause very strange things sometimes.

There are many other issues on organizing loops.

We are currently planning to make PP able to do fixed-width things as well as physical piddles (where looping over the first dimensions would be cheaper as there are less distinct increments, which might make a difference on machines with a small number of registers).

Copyright (C) Tuomas J. Lukka 1997. All rights reserved. Duplication in the same form and printing a copy for yourself allowed.