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lib/AI/Pathfinding/AStar/AStarNode.pm  view on Meta::CPAN

	my $self = {};
	$self->{id}     = $id;
	$self->{g}      = $g;
	$self->{h}      = $h;
	$self->{f}      = $g+$h;
	$self->{parent} = undef;
	$self->{cost}   = 0;
	$self->{inopen} = 0;
	$self->{heap} = undef;

	bless ($self, $class);
	return $self;
}

sub heap {
	my ($self, $val) = @_;
	$self->{heap} = $val if (defined $val);
	return $self->{heap};
}

sub cmp {

t/01_AI-Pathfinding-AStar.t  view on Meta::CPAN

#Where . represents open squares and | represents walls.  The @ represents our
#starting square and the * the target square.  This module assumes that
#orthogonal moves cost 10 points and diagonal moves cost 140.  The heuristic
#used is Manhattan, which simply counts the orthogonal distance between any 2
#squares whilst disregarding any barriers.

sub new
{
    my $invocant = shift;
    my $class = ref($invocant) || $invocant;
    my $self = bless {}, $class;

	$self->{map} = {};
	for(my $x=1; $x<=7; $x++)
	{
		for(my $y=1; $y<=5; $y++)
			{$self->{map}->{$x.'.'.$y} = 1;}
	}
	$self->{map}->{'4.2'} = 0;
	$self->{map}->{'4.3'} = 0;
	$self->{map}->{'4.4'} = 0;