/// <summary>
/// Perform DE crossover.
/// </summary>
/// <param name="crossover">Crossover variant to be performed.</param>
/// <param name="CR">Crossover probability.</param>
/// <param name="n">Dimensionality for problem.</param>
/// <param name="w">Differential weight (vector).</param>
/// <param name="x">Current agent position.</param>
/// <param name="y">Potentially new agent position.</param>
/// <param name="g">Population's best known position.</param>
/// <param name="agents">Entire population.</param>
/// <param name="randomSet">Random-set used for drawing distinct agents.</param>
public static void DoCrossover(Variant crossover, double CR, int n, double[] w, double[] x, ref double[] y, double[] g, double[][] agents, RandomOps.Set randomSet)
{
// Agents used in crossover.
double[] a, b, c;
switch (crossover)
{
case Variant.Best1Bin:
{
// The first agent used in crossover is g.
a = g;
// Pick random and distinct agent-indices.
// Also distinct from agent x.
int R1 = randomSet.Draw();
int R2 = randomSet.Draw();
b = agents[R1];
c = agents[R2];
}
break;
case Variant.Rand1Bin:
default:
{
// Pick random and distinct agent-indices.
// Also distinct from agent x.
int R1 = randomSet.Draw();
int R2 = randomSet.Draw();
int R3 = randomSet.Draw();
// Refer to the randomly picked agents as a and b.
a = agents[R1];
b = agents[R2];
c = agents[R3];
}
break;
}
// Pick a random dimension.
int R = Globals.Random.Index(n);
// Compute potentially new position.
for (int k = 0; k < n; k++)
{
if (k == R || Globals.Random.Bool(CR))
{
y[k] = a[k] + w[k] * (b[k] - c[k]);
}
else
{
y[k] = x[k];
}
}
}
static void DoTest(RandomOps.Random Rand)
{
int i;
Console.WriteLine("RNG name: {0}", Rand.Name);
Console.WriteLine();
if (TestByte)
{
Console.WriteLine("Byte()");
int[] ByteCounts = new int[Byte.MaxValue + 1];
ZeroCounts(ByteCounts);
for (i = 0; i < ByteIterations; i++)
{
ByteCounts[Rand.Byte()] += 1;
}
PrintCounts(ByteCounts);
Console.WriteLine();
}
Console.WriteLine("Bytes({0})", NumBytes);
byte[] byteArr = Rand.Bytes(NumBytes);
for (i = 0; i < NumBytes; i++)
{
Console.WriteLine(byteArr[i]);
}
Console.WriteLine();
Console.WriteLine("Uniform()");
for (i = 0; i < NumIterations; i++)
{
Console.WriteLine(Rand.Uniform());
}
Console.WriteLine();
Console.WriteLine("Uniform(-3, -1)");
for (i = 0; i < NumIterations; i++)
{
Console.WriteLine(Rand.Uniform(-3, -1));
}
Console.WriteLine();
Console.WriteLine("Uniform(-2, 2)");
for (i = 0; i < NumIterations; i++)
{
Console.WriteLine(Rand.Uniform(-2, 2));
}
Console.WriteLine();
Console.WriteLine("Uniform(3, 5)");
for (i = 0; i < NumIterations; i++)
{
Console.WriteLine(Rand.Uniform(3, 5));
}
Console.WriteLine();
Console.WriteLine("Gauss({0}, {1})", GaussMean, GaussDeviation);
for (i = 0; i < NumIterations; i++)
{
Console.WriteLine(Rand.Gauss(GaussMean, GaussDeviation));
}
Console.WriteLine();
double sum = 0;
for (i = 0; i < MeanIterations; i++)
{
sum += Rand.Uniform();
}
Console.WriteLine("Mean of {0} x Uniform(): {1:0.0000}", MeanIterations, sum / MeanIterations);
Console.WriteLine();
sum = 0;
for (i = 0; i < MeanIterations; i++)
{
sum += Rand.Gauss(0, 1);
}
Console.WriteLine("Mean of {0} x Gauss(0, 1): {1:0.0000}", MeanIterations, sum / MeanIterations);
Console.WriteLine();
Console.WriteLine("Disk()");
PrintPoint(Rand.Disk());
Console.WriteLine();
Console.WriteLine("Circle()");
PrintPoint(Rand.Circle());
Console.WriteLine();
Console.WriteLine("Sphere3()");
PrintPoint(Rand.Sphere3());
Console.WriteLine();
Console.WriteLine("Sphere4()");
PrintPoint(Rand.Sphere4());
Console.WriteLine();
Console.WriteLine("Sphere({0}, {1})", SphereDim, SphereRadius);
PrintPoint(Rand.Sphere(SphereDim, SphereRadius));
Console.WriteLine();
if (TestBool)
{
Console.WriteLine("Bool()");
int countTrue = 0;
int countFalse = 0;
for (i = 0; i < BoolIterations; i++)
{
if (Rand.Bool())
{
countTrue++;
}
else
{
countFalse++;
}
}
Console.WriteLine("True: {0}", countTrue);
Console.WriteLine("False: {0}", countFalse);
Console.WriteLine();
}
Console.WriteLine("Index({0})", MaxIndex);
ZeroCounts(IndexCounts);
for (i = 0; i < IndexIterations; i++)
{
int idx = Rand.Index(MaxIndex);
IndexCounts[idx] += 1;
}
PrintCounts(IndexCounts);
Console.WriteLine();
Console.WriteLine("Index2({0}, ...)", MaxIndex);
ZeroCounts(IndexCounts);
for (i = 0; i < IndexIterations; i++)
{
int idx1, idx2;
Rand.Index2(MaxIndex, out idx1, out idx2);
Debug.Assert(idx1 != idx2);
IndexCounts[idx1] += 1;
IndexCounts[idx2] += 1;
}
PrintCounts(IndexCounts);
Console.WriteLine();
RandomOps.Set RandSet = new RandomOps.Set(Rand, RandSetSize);
Console.WriteLine("RandSet.Reset()");
RandSet.Reset();
Console.WriteLine();
Console.WriteLine("RandSet.Draw() with set of size {0} and {1} iterations", RandSetSize, SetIterations / 2);
for (i = 0; i < SetIterations / 2; i++)
{
Console.WriteLine(RandSet.Draw());
}
Console.WriteLine();
Console.WriteLine("RandSet.Reset()");
Console.WriteLine("RandSet.Draw() with set of size {0}", RandSetSize);
RandSet.Reset();
for (i = 0; i < SetIterations; i++)
{
Console.WriteLine(RandSet.Draw());
}
Console.WriteLine();
//RandSet.Draw(); // Assertion fails.
Console.WriteLine("RandSet.ResetExclude({0})", RandSetExclude);
Console.WriteLine("RandSet.Draw() with set of size {0}", RandSetSize);
RandSet.ResetExclude(RandSetExclude);
for (i = 0; i < SetIterations - 1; i++)
{
Console.WriteLine(RandSet.Draw());
}
Console.WriteLine();
//RandSet.Draw(); // Assertion fails.
ZeroCounts(SetCounts);
Console.WriteLine("RandSet.Draw() with set of size {0}", RandSetSize);
for (i = 0; i < SetIterations2; i++)
{
RandSet.Reset();
while (RandSet.Size > 0)
{
int idx = RandSet.Draw();
SetCounts[idx] += 1;
}
}
PrintCounts(SetCounts);
Console.WriteLine();
InitSetProbabilities(Rand);
ZeroCounts(IndexDistributionCounts);
Console.WriteLine("Rand.Index() with probability distribution");
for (i = 0; i < IndexDistributionIterations; i++)
{
int idx = Rand.Index(IndexProbabilities);
IndexDistributionCounts[idx] += 1;
}
PrintDistributionCounts();
Console.WriteLine();
RandomOps.IndexDistribution IndexDistribution = new RandomOps.IndexDistribution(Rand, IndexProbabilities);
ZeroCounts(IndexDistributionCounts);
Console.WriteLine("IndexDistribution.DrawLinearSearch()");
for (i = 0; i < IndexDistributionIterations; i++)
{
int idx = IndexDistribution.DrawLinearSearch();
IndexDistributionCounts[idx] += 1;
}
PrintDistributionCounts();
Console.WriteLine();
ZeroCounts(IndexDistributionCounts);
Console.WriteLine("IndexDistribution.DrawBinarySearch()");
for (i = 0; i < IndexDistributionIterations; i++)
{
int idx = IndexDistribution.DrawBinarySearch();
IndexDistributionCounts[idx] += 1;
}
PrintDistributionCounts();
Console.WriteLine();
}
static void Test(RandomOps.Random rand)
{
DateTime t1 = DateTime.Now;
DoTest(rand);
DateTime t2 = DateTime.Now;
Console.WriteLine("Time usage: {0}", t2.Subtract(t1));
}
static void TestArraySeed(RandomOps.RanUInt32Array rand)
{
RandomOps.Ran2 ran2 = new RandomOps.Ran2();
RandomOps.RandomDotOrg randInternet = new RandomOps.RandomDotOrg(rand.SeedLength, ran2, rand.SeedLength);
rand.Seed(randInternet);
Test(rand);
}
static void InitSetProbabilities(RandomOps.Random Rand)
{
int i;
double sum = 0;
// Initialize probabilities to random values.
for (i = 0; i < IndexProbabilities.Length; i++)
{
double r = Rand.Uniform();
IndexProbabilities[i] = r;
sum += r;
}
// Normalize so sum of probabilities is one.
for (i = 0; i < IndexProbabilities.Length; i++)
{
IndexProbabilities[i] /= sum;
}
}
