How to use

selectSeeds

method

in

org.ddogleg.clustering.kmeans.InitializeKMeans_F64

seedSelector.selectSeeds(points, clusters.toList());
      System.out.println(iteration+"  Reseeding: "+sumDistance);
    seedSelector.selectSeeds(points, clusters.toList());
    previousSum = Double.MAX_VALUE;
    lastConverge = iteration;

seedSelector.selectSeeds(points, clusters.toList());
      System.out.println(iteration+"  Reseeding: "+sumDistance);
    seedSelector.selectSeeds(points, clusters.toList());
    previousSum = Double.MAX_VALUE;
    lastConverge = iteration;

/**
 * In this situation there are not enough unique points which can act as unique seeds
 */
@Test
public void notEnoughUniquePoints() {
  int DOF = 20;
  List<double[]> points = TestStandardKMeans_F64.createPoints(DOF,30,true);
  for (int i = 1; i < points.size(); i += 2) {
    System.arraycopy(points.get(i-1),0,points.get(i),0,DOF);
  }
  List<double[]> seeds = TestStandardKMeans_F64.createPoints(DOF,20,false);
  InitializeKMeans_F64 alg = createAlg();
  alg.init(DOF,0xBEEF);
  alg.selectSeeds(points, seeds);
  // just make sure it found a match in the input set
  for( double[] a : seeds ) {
    findMatch( a , points );
  }
}

alg.selectSeeds(points,seeds);

@Test
public void selectSeeds() {
  int DOF = 20;
  InitializeKMeans_F64 alg = createAlg();
  alg.init(DOF,0xBEEF);
  List<double[]> points = TestStandardKMeans_F64.createPoints(DOF,100,true);
  List<double[]> seeds = TestStandardKMeans_F64.createPoints(DOF,20,false);
  alg.selectSeeds(points,seeds);
  // make sure nothing was added to the list
  assertEquals(20,seeds.size());
  for (int i = 0; i < seeds.size(); i++) {
    double[] s = seeds.get(i);
    // make sure the seed was written to
    for (int j = 0; j < DOF; j++) {
      assertTrue(s[j]!=0);
    }
    // make sure it wasn't swapped with one of the points
    for (int j = 0; j < points.size(); j++) {
      assertTrue(points.get(j) != s);
    }
  }
}

/**
 * In this situation there are not enough unique points which can act as unique seeds.
 *
 * This is a stricter version of generic test
 */
@Test
public void notEnoughUniquePoints_strict() {
  int DOF = 20;
  List<double[]> points = TestStandardKMeans_F64.createPoints(DOF,30,true);
  for (int i = 1; i < points.size(); i += 2) {
    System.arraycopy(points.get(i-1),0,points.get(i),0,DOF);
  }
  List<double[]> seeds = TestStandardKMeans_F64.createPoints(DOF,20,false);
  InitializeKMeans_F64 alg = createAlg();
  alg.init(DOF,0xBEEF);
  alg.selectSeeds(points, seeds);
  int hits[] = new int[15];
  for( double[] a : seeds ) {
    int match = findMatch( a , points )/2;
    hits[match]++;
  }
  // make sure each one was selected at least once
  for (int i = 0; i < hits.length; i++) {
    assertTrue(hits[i] > 0);
  }
}

/**
 * Request more seeds than there are points.  This is impossible to do and ensure the seeds are
 * unique.
 */
@Test
public void impossible() {
  try {
    int DOF = 20;
    InitializeKMeans_F64 alg = createAlg();
    alg.init(DOF,0xBEEF);
    // 4 points and 4 seeds.  Each point must be a seed
    List<double[]> points = TestStandardKMeans_F64.createPoints(DOF,3,true);
    List<double[]> seeds = TestStandardKMeans_F64.createPoints(DOF,4,false);
    alg.selectSeeds(points,seeds);
    fail("Should have thrown an exception!");
  } catch( Exception e ) {
  }
}