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Reid Augustin > Algorithm-Pair-Best2-2.035 > Algorithm::Pair::Best2
Module Version: 2.035   Source   Latest Release: Algorithm-Pair-Best2-2.040

# NAME

Algorithm::Pair::Best2 - select pairings (designed for Go tournaments, but can be used for anything).

version 2.035

# SYNOPSIS

```    use Algorithm::Pair::Best2;

my \$pair = Algorithm::Pair::Best2->new( [ options ] );

\$pair->add( item, [ item, ... ] );

@new_pairs = \$pair->pick( [ window ] );```

# DESCRIPTION

This is a re-write of Algorithm::Pair::Best. The interface is simplified and the implementation is significantly streamlined.

After creating an Algorithm::Pair::Best2 object (with ->new), add items to the list of items (i.e: players) to be paired. The final list must contain an even number of items or picking the pairs will throw an exception.

Algorithm::Pair::Best2->pick explores all combinations of items and returns the pairing list with the best (lowest) score. This can be an expensive proposition - the number of combinations goes up very fast with respect to the number of items:

```    items combinations
2         1       (1)
4         3       (1 * 3)
6        15       (1 * 3 * 5)
8       105       (1 * 3 * 5 * 7)
10       945       (1 * 3 * 5 * 7 * 9
12     10395       (1 * 3 * 5 * 7 * 9 * 11)
14    135135       (1 * 3 * 5 * 7 * 9 * 11 * 13)```

It is clearly unreasonable to try to pair a significant number of items. Trying to completely pair even 30 items would take too long.

Fortunately, there is a way to get pretty good results for big lists, even if they're not perfect. Instead of trying to pair the whole list at once, Algorithm::Pair::Best2 pairs a series of smaller groups in a sliding window to get good 'local' results.

The ->new method accepts a window option to limit the number of pairs in the sliding window. The window option can also be overridden by calling pick with an explicit window argument:

`    \$pair->pick(\$window);`

The list should be at least partially sorted so that reasonable pairing candidates are within the 'sliding window' of each other. Otherwise the final results may not be globally 'best', but only locally good. For (e.g.) a tournament, sorting by rank is sufficient.

Here's how a window value of 5 works: the best list for items 1 through 10 (5 pairs) is found. Save the pairing for the top two items and then slide the window down to pair items 2 through 12. Save the top pairing from this result and slide down again to items 4 through 14. Keep sliding the window down until we reach the last 10 items (which are completed in one iteration). In this way, a large number of pairings can be completed without taking factorial time.

# METHODS

my \$pair = Algorithm::Pair::Best2->new( options )

Creates a new Algorithm::Pair::Best2 object.

\$pair->add ( item, [ item, ...] )

Add an item (or several items) to be paired. Item(s) can be any scalar or reference. They will be passed (a pair at a time) to the scoreSub callback.

@new_pairs = \$pair->pick ( ?\$window? )

Returns the best pairing found using the sliding window technique as discussed in DESCRIPTION above. window is the number of pairs in the sliding window. If no window argument is passed, the window selected in the new, or the default value is used.

pick returns the list (or a reference to the list in scalar context) of items in pairing order: new_pair[0] is paired to new_pair[1], new_pair[2] to new_pair[3], etc.

If the number of items in the list (from add) is not even, an exception is thrown.

# OPTIONS

The ->new method accepts the following options:

window => number of pairs

Sets the default number of pairs in the sliding window during pick. Can also be set by passing a window argument to pick.

Default: 5

scoreSub => reference to scoring callback

The callback is called as scoreSub(item_0, item_1), where item_0 and item_1 are members of the list created by adding items. The callback must return a positive number representing the 'badness' of this pairing. A good pairing should have a number closer to 0 than a worse pairing. If scoreSub returns a negative number, an exception is thrown.

scoreSub(A, B) should be equal to scoreSub(B, A). scoreSub(A, B) is called only one time (for any particular A and B), and the result is cached. scoreSub(B, A) is never called.

Note that scores are always positive (Algorithm::Pair::Best2 searches for the lowest combined score).

Default: a subroutine that throws an exception.

progress => reference to progress callback

Each time a pair is finalized in the pick routine, the progress(\$item_0, \$item_1) callback is called where \$item_0 and \$item_1 are the most recently finalized pair:

```  progress => sub {
my (\$item_0, \$item_1) = @_;
# assuming \$items have a 'name' method that returns a string:
print \$item_0->name, " paired with ", \$item_1->name, "\n";
},```

Default: a subroutine that does nothing.

# EXAMPLE

```  use Scalar::Util qw( refaddr );
use Algorithm::Pair::Best2;

my @players = (
Player->new(        # Player object defined elsewhere
name => "Player 1",
rank => 3.5,    # Player also has a 'rank' method
),
Player->new( ... ), # more players
...
);

# some extra information not provided by Player methods:
refaddr(\$player_1) => 1,  # player_0 played player_1
refaddr(\$player_4) => 1,  #   and player_4
},
...
);

my \$pair = Algorithm::Pair::Best2->new(
scoreSub => sub {       # score callback
my (\$player_A, \$player_B) = @_;

# Compare using the 'rating' method defined for Players.
# Closer in rating is a better match:
my \$score = abs(\$player_A->rating - \$player_B->rating);

...

# but if they have already been matched,  increase the 'badness' of
# this pair by a lot:
\$score += 50;
}

...   # other criterion that can increase \$score

return \$score;   # always positive
}
);

\$pair->add(sort { \$a->rank <=> \$b->rank } @players);

my @pairs = \$pair->pick;

...```

Games::Go::W3Gtd::Paring.pm

# AUTHOR

Reid Augustin <reid@hellosix.com>