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lib/Algorithm/DBSCAN.pm  view on Meta::CPAN

	
	my $self = {};
	$self->{dataset_object} = $dataset;
	$self->{dataset} = $dataset->{points};
	@{$self->{id_list}} = keys %{$dataset->{points}};
	$self->{eps} = $eps;
	$self->{min_points} = $min_points;
	$self->{current_cluster} = 1;
	$self->{use_external_region_index} = 0;
		
	bless($self, $type);

	return($self);
}

=head2 FindClusters

The main method that will run the DBSCAN algorithm on the Dataset.

=cut

lib/Algorithm/DBSCAN/Dataset.pm  view on Meta::CPAN

package Algorithm::DBSCAN::Dataset;


sub new {
	my($type) = @_;
	
	my $self = {};
	$self->{points} = {};
		
	bless($self, $type);

	return($self);
}

sub AddPoint {
	my ($self, $point) = @_;
	
	my $nb_points = scalar(keys %{$self->{points}});
	$point->{visited} = 0;
	$point->{id} = $nb_points;

lib/Algorithm/DBSCAN/Point.pm  view on Meta::CPAN

sub new {
	my($type, $point_id, @coordinates) = @_;
	
	my $self = {};
	
	$self->{cluster_id} = 0;
	$self->{point_id} = $point_id;
	$self->{coordinates} = \@coordinates;
	
	bless($self, $type);

	return($self);
}

sub Distance {
	my ($self, $point) = @_;
	
	my $distance;
	
	my $i = 0;