info.debatty.java.graphs.examples.StronglyConnectedExample Maven / Gradle / Ivy

Go to download

Show more of this group Show more artifacts with this name
Show all versions of java-graphs Show documentation

Algorithms that build k-nearest neighbors graph (k-nn graph): Brute-force, NN-Descent,...

There is a newer version: 0.41

/*
 * The MIT License
 *
 * Copyright 2015 Thibault Debatty.
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
 * THE SOFTWARE.
 */

package info.debatty.java.graphs.examples;

import info.debatty.java.graphs.Graph;
import info.debatty.java.graphs.Node;
import info.debatty.java.graphs.SimilarityInterface;
import info.debatty.java.graphs.build.Brute;
import java.util.ArrayList;
import java.util.Random;

/**
 *
 * @author Thibault Debatty
 */
public class StronglyConnectedExample {

    /**
     * @param args the command line arguments
     */
    public static void main(String[] args) {
        // Create some nodes
        Random rand = new Random();
        ArrayList> nodes = new ArrayList>();
        for (int i = 0; i < 100; i++) {
            nodes.add(new Node(
                    String.valueOf(i),
                    rand.nextDouble() * 100));
            
            nodes.add(new Node(
                    String.valueOf(100 + i),
                    1000000 + rand.nextDouble() * 100));
        }

        // Build the graph
        Brute builder = new Brute();
        builder.setK(10);
        builder.setSimilarity(new SimilarityInterface() {

            public double similarity(Double value1, Double value2) {
                return 1 / (1 + Math.abs(value1 - value2));
            }
        });
        Graph graph = builder.computeGraph(nodes);
        
        
        ArrayList> stronglyConnectedComponents = graph.stronglyConnectedComponents();
        
        System.out.printf("Found %d strongly connected components\n", stronglyConnectedComponents.size());
        
        for (Graph component : stronglyConnectedComponents) {
            System.out.printf("Contains %d nodes\n", component.size());
            System.out.println(component);
        }
    }
    
}