/*
   * Copyright (c) 2003, The JUNG Authors 
   *
   * All rights reserved.
   *
   * This software is open-source under the BSD license; see either
   * "license.txt" or
   * https://github.com/jrtom/jung/blob/master/LICENSE for a description.
   */
  package edu.uci.ics.jung.algorithms.importance;
  
  import java.util.HashMap;
  import java.util.HashSet;
  import java.util.List;
  import java.util.Map;
  import java.util.Set;
  
  import junit.framework.Test;
  import junit.framework.TestCase;
  import junit.framework.TestSuite;
  import edu.uci.ics.jung.graph.DirectedGraph;
  import edu.uci.ics.jung.graph.DirectedSparseMultigraph;
  
  
  /**
   * @author Scott White
   * @author Tom Nelson - adapted to jung2
   */
  public class TestKStepMarkov extends TestCase {
      public final static String EDGE_WEIGHT = "edu.uci.ics.jung.edge_weight";
  	DirectedGraph<Number,Number> mGraph;
      double[][] mTransitionMatrix;
      Map<Number,Number> edgeWeights = new HashMap<Number,Number>();
  
      public static Test suite() {
          return new TestSuite(TestKStepMarkov.class);
      }
  
      @Override
      protected void setUp()
      {
          mGraph = new DirectedSparseMultigraph<Number,Number>();
          mTransitionMatrix = new double[][]
             {{0.0, 0.5, 0.5},
              {1.0/3.0, 0.0, 2.0/3.0},
              {1.0/3.0, 2.0/3.0, 0.0}};
  
          for (int i = 0; i < mTransitionMatrix.length; i++)
          	mGraph.addVertex(i);
  
          for (int i = 0; i < mTransitionMatrix.length; i++) {
              for (int j = 0; j < mTransitionMatrix[i].length; j++)
              {
                  if (mTransitionMatrix[i][j] > 0)
                  {
                  	int edge = i*mTransitionMatrix.length+j;
                  	mGraph.addEdge(edge, i, j);
                  	edgeWeights.put(edge, mTransitionMatrix[i][j]);
                  }
              }
          }
      }
  
      public void testRanker() {
  
          Set<Number> priors = new HashSet<Number>();
          priors.add(1);
          priors.add(2);
          KStepMarkov<Number,Number> ranker = new KStepMarkov<Number,Number>(mGraph,priors,2,edgeWeights);
  //        ranker.evaluate();
  //        System.out.println(ranker.getIterations());
  
          for (int i = 0; i < 10; i++) 
          {
  //            System.out.println(ranker.getIterations());
  //	        for (Number n : mGraph.getVertices())
  //	        	System.out.println(n + ": " + ranker.getVertexRankScore(n));
              
  	        ranker.step();
          }
          
          
          List<Ranking<?>> rankings = ranker.getRankings();
  //        System.out.println(rankings);
      }
  }