4.19. Program: permuteProblemHave you ever wanted to generate all possible permutations of an array or to execute some code for every possible permutation? For example: % echo man bites dog | permute The number of permutations of a set is the factorial of the size of the set. This grows big extremely fast, so you don't want to run it on many permutations: Set Size Permutations 1 1 2 2 3 6 4 24 5 120 6 720 7 5040 8 40320 9 362880 10 3628800 11 39916800 12 479001600 13 6227020800 14 87178291200 15 1307674368000 Doing something for each alternative takes a correspondingly large amount of time. In fact, factorial algorithms exceed the number of particles in the universe with very small inputs. The factorial of 500 is greater than ten raised to the thousandth power!
use Math::BigInt;
sub factorial {
my $n = shift;
my $s = 1;
$s *= $n-- while $n > 0;
return $s;
}
print factorial(Math::BigInt->new("500"));
The two solutions that follow differ in the order of the permutations they return. The solution in Example 4.3 uses a classic list permutation algorithm used by Lisp hackers. It's relatively straightforward but makes unnecessary copies. It's also hardwired to do nothing but print out its permutations. Example 4.3: tsc-permute#!/usr/bin/perl -n # tsc_permute: permute each word of input permute([split], []); sub permute { my @items = @{ $_[0] }; my @perms = @{ $_[1] }; unless (@items) { print "@perms\n"; } else { my(@newitems,@newperms,$i); foreach $i (0 .. $#items) { @newitems = @items; @newperms = @perms; unshift(@newperms, splice(@newitems, $i, 1)); permute([@newitems], [@newperms]); } } } The solution in Example 4.4 , provided by Mark-Jason Dominus, is faster (by around 25%) and more elegant. Rather than precalculate all permutations, his code generates the n th particular permutation. It is elegant in two ways. First, it avoids recursion except to calculate the factorial, which the permutation algorithm proper does not use. Second, it generates a permutation of integers rather than permute the actual data set.
He also uses a time-saving technique called
memoizing
. The idea is that a function that always returns a particular answer when called with a particular argument memorizes that answer. That way, the next time it's called with the same argument, no further calculations are required. The
You call Example 4.4: mjd-permute
#!/usr/bin/perl -w
#
mjd_permute: permute each word of input
use strict;
while (<>) {
my @data = split;
my $num_permutations = factorial(scalar @data);
for (my $i=0; $i < $num_permutations; $i++) {
my @permutation = @data[n2perm($i, $#data)];
print "@permutation\n";
}
}
# Utility function: factorial with memoizing
BEGIN {
my @fact = (1);
sub factorial($) {
my $n = shift;
return $fact[$n] if defined $fact[$n];
$fact[$n] = $n * factorial($n - 1);
}
}
# n2pat($N, $len) : produce the $N-th pattern of length $len
sub n2pat {
my $i = 1;
my $N = shift;
my $len = shift;
my @pat;
while ($i <= $len + 1) { # Should really be just while ($N) { ...
push @pat, $N % $i;
$N = int($N/$i);
$i++;
}
return @pat;
}
# pat2perm(@pat) : turn pattern returned by
See Also
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