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|
#!/usr/bin/perl
use strict;
use warnings;
package Graph::Implicit;
use Heap::Simple;
use List::MoreUtils qw/apply/;
=for example
sub {
map { [$_, $_->intrinsic_cost] }
shift->grep_adjacent(sub { shift->is_walkable })
}
=cut
sub new {
my $class = shift;
my $edge_calculator = shift;
return bless $edge_calculator, $class;
}
# generic information
sub vertices {
my $self = shift;
my ($start) = @_;
my @vertices;
$self->dfs($start, sub { push @vertices, $_[1] });
return @vertices;
}
# XXX: probably pretty inefficient... can we do better?
sub edges {
my $self = shift;
my ($start) = @_;
map { my $v = $_; map { [$v, $_] } $self->neighbors($v) }
$self->vertices($start);
}
sub neighbors {
my $self = shift;
my ($from) = @_;
return map { $$_[0] } $self->($from);
}
# more complicated graph properties
sub is_bipartite {
my $self = shift;
my ($from) = @_;
my $ret = 1;
BIPARTITE: {
my %colors = ($from => 0);
no warnings 'exiting';
$self->bfs($from, sub {
my $vertex = $_[1];
apply {
last BIPARTITE if $colors{$vertex} == $colors{$_};
$colors{$_} = not $colors{$vertex};
} $self->neighbors($vertex)
});
return 1;
}
return 0;
}
# traversal
# XXX: if we can generalize @bag to allow for a heap, then we can implement
# prim with this too
sub _traversal {
my $self = shift;
my ($start, $code, $insert, $remove) = @_;
my @bag;
my %marked;
my %pred;
$insert->(\@bag, [undef, $start]);
while (@bag) {
my ($pred, $vertex) = @{ $remove->(\@bag) };
if (not exists $marked{$vertex}) {
$code->($pred, $vertex);
$pred{$vertex} = $pred if defined wantarray;
$marked{$vertex} = 1;
$insert->(\@bag, $_) for $self->neighbors($vertex);
}
}
return \%pred;
}
sub bfs {
my $self = shift;
my ($start, $code) = @_;
return $self->_traversal($start, $code,
sub { push @{ $_[0] }, $_[1] },
sub { shift @{ $_[0] } });
}
sub dfs {
my $self = shift;
my ($start, $code) = @_;
return $self->_traversal($start, $code,
sub { push @{ $_[0] }, $_[1] },
sub { pop @{ $_[0] } });
}
sub iddfs {
}
# minimum spanning tree
sub boruvka {
}
sub prim {
}
sub kruskal {
}
# single source shortest path
sub dijkstra {
my $self = shift;
my ($from, $scorer) = @_;
return $self->astar($from, sub { 0 }, $scorer);
}
sub astar {
my $self = shift;
my ($from, $heuristic, $scorer) = @_;
my $pq = Heap::Simple->new(elements => "Any");
my %neighbors;
my ($max_vert, $max_score) = (undef, 0);
my %dist = ($from => 0);
my %pred = ($from => undef);
$pq->key_insert(0, $from);
while ($pq->count) {
my $cost = $pq->top_key;
my $vertex = $pq->extract_top;
if ($scorer) {
my $score = $scorer->($vertex);
return (\%pred, $vertex) if $score eq 'q';
($max_vert, $max_score) = ($vertex, $score)
if ($score > $max_score);
}
$neighbors{$vertex} = [$self->($vertex)]
unless exists $neighbors{$vertex};
for my $neighbor (@{ $neighbors{$vertex} }) {
my ($vert_n, $weight_n) = @{ $neighbor };
my $dist = $cost + $weight_n + $heuristic->($vertex, $vert_n);
if (!defined $dist{$vert_n} || $dist < $dist{$vert_n}) {
$dist{$vert_n} = $dist;
$pred{$vert_n} = $vertex;
$pq->key_insert($dist, $vert_n);
}
}
}
return \%pred, $max_vert;
}
sub bellman_ford {
}
# all pairs shortest path
sub johnson {
}
sub floyd_warshall {
}
# other (?)
sub topological_sort {
}
# misc utility functions
sub make_path {
my ($pred, $end) = @_;
my @path;
while (defined $end) {
push @path, $end;
$end = $pred->{$end};
}
return reverse @path;
}
1;
|
