Class: DbClustering::Algorithms::Dbscan

Inherits:
Object
  • Object
show all
Defined in:
lib/algorithms/density_based/dbscan.rb

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(datasource:, distance_metric:) ⇒ Dbscan

Returns a new instance of Dbscan.



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# File 'lib/algorithms/density_based/dbscan.rb', line 9

def initialize(datasource:, distance_metric:)
  @datasource = datasource
  @distance_metric = distance_metric
  @clusters = []
end

Instance Attribute Details

#clusters ⇒ Object

Returns the value of attribute clusters.



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# File 'lib/algorithms/density_based/dbscan.rb', line 7

def clusters
  @clusters
end

#datasource ⇒ Object

Returns the value of attribute datasource.



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# File 'lib/algorithms/density_based/dbscan.rb', line 7

def datasource
  @datasource
end

Instance Method Details

#cluster(max_distance:, min_neighbors:, debug: false) ⇒ Object 



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# File 'lib/algorithms/density_based/dbscan.rb', line 15

def cluster(max_distance:, min_neighbors:, debug: false)
  @clusters = []
  cluster = nil

  @datasource.iterate_all_points do |point, current_index, points_count|
    neighbors = @datasource.neighbors(point: point, distance_metric: @distance_metric, max_distance: max_distance)

    if neighbors.count < min_neighbors
      point.is_noise = true
    elsif point.cluster.nil?
      cluster = DbClustering::Models::Cluster.new
      @clusters << cluster

      neighbors.each do |neighbor|
        if neighbor.cluster.nil?
          cluster.add(neighbor)

          if debug
            print "+"
          end

          # add the neighbors of the neighbor to the neighbors to fully expand the cluster
          neighbors |= @datasource.neighbors(point: neighbor, distance_metric: @distance_metric, max_distance: max_distance)
        end
      end
    end

    yield(point, current_index, points_count) if block_given?
  end
end