public void LinkageTreeTestAdd() {
MersenneTwister rand = new MersenneTwister();
LinkageTree tree = new LinkageTree(Length, rand);
tree.Add(solutions[0]);
tree.Add(solutions[1]);
PrivateObject hidden = new PrivateObject(tree);
int[][][] result = (int[][][])hidden.GetField("occurances");
Assert.AreEqual(1, result[1][0][0]); // Positions 0 and 1 had value 00 exactly once
Assert.AreEqual(2, result[Length - 1][Length - 2][0]); // Positions 0 and 1 had value 00 exactly once
Assert.AreEqual(0, result[Length - 1][Length - 2][1]); // Positions 7 and 8 never had value 10
Assert.AreEqual(1, result[1][0][3]); // Positions 0 and 1 had value 11 exactly once
}
// In the GECCO paper, Figure 3
public static double ImproveUsingTree(LinkageTree tree, IList<BinaryVector> donors, BinaryVector solution, double fitness, BinaryProblem problem, IRandom rand) {
var options = Enumerable.Range(0, donors.Count).ToArray();
foreach (var cluster in tree.Clusters) {
// Find a donor which has at least one gene value different
// from the current solution for this cluster of genes
bool donorFound = false;
foreach (var donorIndex in options.ShuffleList(rand)) {
// Attempt the donation
fitness = Donate(solution, fitness, donors[donorIndex], cluster, problem, rand, out donorFound);
if (donorFound) break;
}
}
return fitness;
}
public void LinkageTreeTestEntropyDistance() {
MersenneTwister rand = new MersenneTwister();
LinkageTree tree = new LinkageTree(Length, rand);
PrivateObject hidden = new PrivateObject(tree);
// No information should result in a distance of 0
Assert.AreEqual((double)0, hidden.Invoke("EntropyDistance", new object[] { 0, 1 }));
foreach (var solution in solutions) {
tree.Add(solution);
}
// Check that 0 and 1 are closer than 0 and 2
var linked = (double)hidden.Invoke("EntropyDistance", new object[] { 0, 1 });
var unlinked = (double)hidden.Invoke("EntropyDistance", new object[] { 0, 2 });
Assert.IsTrue(linked < unlinked);
// Reversing the arguments should not change the result
var forward = hidden.Invoke("EntropyDistance", new object[] { Length - 1, Length - 2 });
var backward = hidden.Invoke("EntropyDistance", new object[] { Length - 2, Length - 1 });
Assert.AreEqual(forward, backward);
}
protected LinkageTree(LinkageTree original, Cloner cloner) : base(original, cloner)
{
occurances = new int[original.occurances.Length][][];
//mkommend: first entry is not used, cf. ctor line 83
for (int i = 1; i < original.occurances.Length; i++)
{
occurances[i] = new int[original.occurances[i].Length][];
for (int j = 0; j < original.occurances[i].Length; j++)
{
occurances[i][j] = original.occurances[i][j].ToArray();
}
}
clusters = original.clusters.Select(c => c.ToList()).ToArray();
clusterOrdering = new List <int>(original.clusterOrdering);
length = original.length;
rand = cloner.Clone(original.rand);
rebuildRequired = original.rebuildRequired;
}
// In the GECCO paper, Figure 3
public static double ImproveUsingTree(LinkageTree tree, IList <BinaryVector> donors, BinaryVector solution, double fitness, BinaryProblem problem, IRandom rand)
{
var options = Enumerable.Range(0, donors.Count).ToArray();
foreach (var cluster in tree.Clusters)
{
// Find a donor which has at least one gene value different
// from the current solution for this cluster of genes
bool donorFound = false;
foreach (var donorIndex in options.ShuffleList(rand))
{
// Attempt the donation
fitness = Donate(solution, fitness, donors[donorIndex], cluster, problem, rand, out donorFound);
if (donorFound)
{
break;
}
}
}
return(fitness);
}
public Population(int length, IRandom rand) {
Solutions = new List<BinaryVector>();
Tree = new LinkageTree(length, rand);
}
public Population(int length, IRandom rand)
{
Solutions = new List <BinaryVector>();
Tree = new LinkageTree(length, rand);
}
protected Population(Population original, Cloner cloner) : base(original, cloner)
{
Solutions = original.Solutions.Select(cloner.Clone).ToList();
Tree = cloner.Clone(original.Tree);
}
public void LinkageTreeTestRebuild() {
// The seed matters as equal sized clusters can appear in any order
MersenneTwister rand = new MersenneTwister(123);
LinkageTree tree = new LinkageTree(Length, rand);
foreach (var solution in solutions) {
tree.Add(solution);
}
// Check if the clusters created contain the expected variables.
var found = tree.Clusters.ToArray();
Assert.AreEqual(correctClusters.Length, found.Length);
for (int i = 0; i < found.Length; i++) {
found[i].Sort();
Assert.IsTrue(found[i].SequenceEqual(correctClusters[i]), string.Format("Failed On Cluster {0}", i));
}
}
