4.26.1 Problem
4.26.2 Solution
Use one of the two permutation algorithms discussed next.
4.26.3 Discussion
Example 4-6. pc_permute( )
function pc_permute($items, $perms = array( )) {
if (empty($items)) {
print join(' ', $perms) . "\n";
} else {
for ($i = count($items) - 1; $i >= 0; --$i) {
$newitems = $items;
$newperms = $perms;
list($foo) = array_splice($newitems, $i, 1);
array_unshift($newperms, $foo);
pc_permute($newitems, $newperms);
}
}
}
For example:
pc_permute(split(' ', 'she sells seashells'));
she sells seashells
she seashells sells
sells she seashells
sells seashells she
seashells she sells
seashells sells she
However, while this recursion is elegant, it's inefficient,
because it's making copies all over the place. Also, it's not easy to modify the
function to return the values instead of printing them out without resorting to
a global variable.
The pc_next_permutation( )
function shown in Example 4-7,
however, is a little slicker. It combines an idea of Mark-Jason Dominus from Perl
Cookbook by Tom Christianson and Nathan Torkington (O'Reilly) with an
algorithm from Edsger Dijkstra's classic text A Discipline of Programming (Prentice-Hall).
Example 4-7. pc_next_permutation( )
function pc_next_permutation($p, $size) {
// slide down the array looking for where we're smaller than the next guy
for ($i = $size - 1; $p[$i] >= $p[$i+1]; --$i) { }
// if this doesn't occur, we've finished our permutations
// the array is reversed: (1, 2, 3, 4) => (4, 3, 2, 1)
if ($i == -1) { return false; }
// slide down the array looking for a bigger number than what we found before
for ($j = $size; $p[$j] <= $p[$i]; --$j) { }
// swap them
$tmp = $p[$i]; $p[$i] = $p[$j]; $p[$j] = $tmp;
// now reverse the elements in between by swapping the ends
for (++$i, $j = $size; $i < $j; ++$i, --$j) {
$tmp = $p[$i]; $p[$i] = $p[$j]; $p[$j] = $tmp;
}
return $p;
}
$set = split(' ', 'she sells seashells'); // like array('she', 'sells', 'seashells')
$size = count($set) - 1;
$perm = range(0, $size);
$j = 0;
do {
foreach ($perm as $i) { $perms[$j][] = $set[$i]; }
} while ($perm = pc_next_permutation($perm, $size) and ++$j);
foreach ($perms as $p) {
print join(' ', $p) . "\n";
}
Dominus's idea is that instead of manipulating the array
itself, you can create permutations of integers. You then map the repositioned
integers back onto the elements of the array to calculate the true permutation —
a nifty idea.
However, this technique still has some shortcomings. Most
importantly, to us as PHP programmers, it frequently pops, pushes, and splices
arrays, something that's very Perl-centric. Next, when calculating the
permutation of integers, it goes through a series of steps to come up with each
permutation; because it doesn't remember previous permutations, it therefore
begins each time from the original permutation. Why redo work if you can help
it?
Dijkstra's algorithm solves this by taking a permutation of a
series of integers and returning the next largest permutation. The code is
optimized based upon that assumption. By starting with the smallest pattern
(which is just the integers in ascending order) and working your way upwards,
you can scroll through all permutations one at a time, by plugging the previous
permutation back into the function to get the next one. There are hardly any
swaps, even in the final swap loop in which you flip the tail.
There's a side benefit. Dominus's recipe needs the total number
of permutations for a given pattern. Since this is the factorial of the number
of elements in the set, that's a potentially expensive calculation, even with
memoization. Instead of computing that number, it's faster to return
false from pc_next_permutation( ) when you notice that
$i == -1. When that occurs, you're forced outside the
array, and you've exhausted the permutations for the phrase.
Two final notes of implementation. Since the size of the set is
invariant, you capture it once using count( ) and pass it into
pc_next_permutation( ); this is faster than repeatedly calling
count( ) inside the function. Also, since the set is guaranteed by its
construction to have unique elements, i.e., there is one and only one instance
of each integer, we don't need to need to check for equality inside the first
two for loops. However, you should include them in case you want to use
this recipe on other numeric sets, in which duplicates might occur.