/// <summary>
/// Random Walks for Simulation Problems.
/// Creating sequences.
/// Output needs to run in Grasshopper.
/// But metric calculation again here.
/// </summary>
/// <param name="args"></param>
static void RandomWalksSequenceCreation()
{
// n=4,10,11,13,17,18,20,35
int n = 10; // problem dimension
int k = n * 100; // sequence size
int walks = 20; // number of random walks
Random rnd = new Random(42);
string path = @"C:\temp\";
// parameters for sequence generation
Sequences.parameters param = new Sequences.parameters();
param.distribution = "normal";
param.stepsize = 0.02;
param.verbose = false;
// create sequences (random walks)
// and run on test functions
string[] strxAll = new string[k * walks];
int counter = 0;
for (int w = 0; w < walks; w++)
{
param.x0 = new double[n];
param.seed = w;
for (int i = 0; i < n; i++)
{
param.x0[i] = rnd.NextDouble();
}
double[][] x = Sequences.RandomWalk(n, k, param);
for (int j = 0; j < k; j++)
{
strxAll[counter] += x[j][0];
for (int i = 1; i < n; i++)
{
strxAll[counter] += ";" + x[j][i];
}
counter++;
}
}
Misc.IO.WriteTextFile(path, "input_n" + n + "_allWalks.csv", strxAll);
}
/// <summary>
/// Random Walks for Mathematical test functions
/// </summary>
/// <param name="args"></param>
static void RandomWalksTestFuncs()
{
int n = 20; // problem dimension
int k = n * 100; // sequence size
int walks = 20; // number of random walks
Random rnd = new Random(42);
string path = @"C:\";
List <Func <double[], double> > tf = new List <Func <double[], double> >();
tf.Add(SO.B_Sphere); // [-1, 1] for all x
tf.Add(SO.L_Ackley); // [-32.768, 32.768] for all x
tf.Add(SO.L_Rastrigin); // [-5.12, 5.12] for all x
tf.Add(SO.V_Rosenbrock); // [-2.048, 2.048] for all x
double[] lb = new double[tf.Count];
double[] ub = new double[tf.Count];
lb[0] = -1;
lb[1] = -32.768;
lb[2] = -5.12;
lb[3] = -2.048;
ub[0] = 1;
ub[1] = 32.768;
ub[2] = 5.12;
ub[3] = 2.048;
//tf.Add(FitnessLandscapeAnalysis.Testfunctions.SO.C_MichalewiczSchoenauer); // only for n=13. domain: [0,1] for i=0-8 and 12; [0,100] for i=9-11
//double[] lb = new double[13];
//double[] ub = new double[13];
//for (int i = 0; i < 9; i++)
//{
// lb[i] = 0;
// ub[i] = 1;
//}
//lb[12] = 0;
//ub[12] = 1;
//for (int i = 9; i < 12; i++)
//{
// lb[i] = 0;
// ub[i] = 100;
//}
// parameters for sequence generation
Sequences.parameters param = new Sequences.parameters();
param.distribution = "normal";
param.stepsize = 0.02;
param.verbose = false;
// create sequences (random walks)
// and run on test functions
for (int w = 0; w < walks; w++)
{
param.seed = w;
param.x0 = new double[n];
for (int i = 0; i < n; i++)
{
param.x0[i] = rnd.NextDouble();
}
double[][] x = Sequences.RandomWalk(n, k, param);
Console.WriteLine(" ");
string[] strx = new string[k];
for (int j = 0; j < k; j++)
{
for (int i = 0; i < n; i++)
{
strx[j] += x[j][i] + ";";
}
}
Misc.IO.WriteTextFile(path, "input_n" + n + "_" + w + ".txt", strx);
//compute outputs for x for every test function.
List <double[]> ytf = new List <double[]>();
int counterr = 0;
foreach (Func <double[], double> f in tf)
{
ytf.Add(new double[x.Length]);
for (int i = 0; i < x.Length; i++)
{
double[] xin = new double[n];
for (int nn = 0; nn < n; nn++)
{
// NOT FOR MICHALEWICZ FUNCTION
xin[nn] = (x[i][nn] * (ub[counterr] - lb[counterr])) + lb[counterr];
//// ONLY MICHALEWICZ
//xin[nn] = (x[i][nn] * (ub[nn] - lb[nn])) + lb[nn];
}
ytf[counterr][i] = f(xin);
}
counterr++;
}
//write outputs
for (int f = 0; f < tf.Count; f++)
{
string[] stry = new string[k];
for (int j = 0; j < k; j++)
{
stry[j] = ytf[f][j] + ";";
}
Misc.IO.WriteTextFile(path, "output_n" + n + "_tf" + f + "_walk" + w + ".txt", stry);
//////MICHALEWICZ FUNCTION ONLY
//writetextfile(path, "output_n" + n + "_tf" + 4 + "_walk" + w + ".txt", stry);
}
Console.WriteLine("walk {0} done", w);
}
Console.WriteLine("Done");
Console.ReadKey();
}
/// <summary>
/// Sample test functions using input sequence
/// </summary>
/// <param name="args"></param>
static void SampleTestFunctions()
{
int n = 40; // problem dimension. do it for n=10 and n=20. only for constraint, only for n=13
List <Func <double[], double> > tf = new List <Func <double[], double> >();
//________________________________________________________________________________________________________
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////////////////
// for BS19 paper
//int k = (n + 1) * 10; // sequence size. Morris is (n+1)*10. sobol is (n+2)*100 or 10000
//string filepath = @"C:\Users\chwaibel\DATA\PROJEKTE\18_FitnessLandscapeAnalysis\04_CASESTUDY\BS19 CaseStudies\TestFuncs\MorrisAnalysis\Input\Morris_inputs_n13_large.csv";
//string outputpath = @"C:\Users\chwaibel\DATA\PROJEKTE\18_FitnessLandscapeAnalysis\04_CASESTUDY\BS19 CaseStudies\TestFuncs\MorrisAnalysis\Output\";
//tf.Add(FitnessLandscapeAnalysis.Testfunctions.SO.B_Sphere); // [-1, 1] for all x
//tf.Add(FitnessLandscapeAnalysis.Testfunctions.SO.L_Ackley); // [-32.768, 32.768] for all x
//tf.Add(FitnessLandscapeAnalysis.Testfunctions.SO.L_Rastrigin); // [-5.12, 5.12] for all x
//tf.Add(FitnessLandscapeAnalysis.Testfunctions.SO.V_Rosenbrock); // [-2.048, 2.048] for all x
//double[] lb = new double[tf.Count];
//double[] ub = new double[tf.Count];
//lb[0] = -1;
//lb[1] = -32.768;
//lb[2] = -5.12;
//lb[3] = -2.048;
//ub[0] = 1;
//ub[1] = 32.768;
//ub[2] = 5.12;
//ub[3] = 2.048;
//tf.Add(FitnessLandscapeAnalysis.Testfunctions.SO.C_MichalewiczSchoenauer); // only for n=13. domain: [0,1] for i=0-8 and 12; [0,100] for i=9-11
//double[] lb = new double[13];
//double[] ub = new double[13];
//for (int i = 0; i < 9; i++)
//{
// lb[i] = 0;
// ub[i] = 1;
//}
//lb[12] = 0;
//ub[12] = 1;
//for (int i = 9; i < 12; i++)
//{
// lb[i] = 0;
// ub[i] = 100;
//}
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//________________________________________________________________________________________________________
//________________________________________________________________________________________________________
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////////////////
// for JBPS paper
int k = (n + 2) * 10000; // sequence size. Morris is (n+1)*10. sobol is (n+2)*100 or 10000
string filepath = @"C:\Users\chwaibel\DATA\PROJEKTE\18_FitnessLandscapeAnalysis\04_CASESTUDY\TestFunctions_JBPS\Sobol\N40_input_large.csv";
string outputpath = @"C:\Users\chwaibel\DATA\PROJEKTE\18_FitnessLandscapeAnalysis\04_CASESTUDY\TestFunctions_JBPS\Sobol\";
tf.Add(SO.B_Sphere); //
tf.Add(SO.L_Ackley); //
tf.Add(SO.L_Rastrigin); //
tf.Add(SO.V_Rosenbrock); //
double[] lb = new double[tf.Count];
double[] ub = new double[tf.Count];
for (int i = 0; i < tf.Count(); i++)
{
lb[i] = -5;
ub[i] = 5;
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//________________________________________________________________________________________________________
Sequences.parameters param = new Sequences.parameters();
// loading sequences (pre-defined)
// and run on test functions
double[][] x = Sequences.LoadInputSequence(n, k, filepath, param);
Console.WriteLine(" ");
//compute outputs for x for every test function.
List <double[]> ytf = new List <double[]>();
int counterr = 0;
foreach (Func <double[], double> f in tf)
{
ytf.Add(new double[x.Length]);
for (int j = 0; j < x.Length; j++)
{
double[] xin = new double[n];
for (int i = 0; i < n; i++)
{
xin[i] = x[j][i] * (ub[counterr] - lb[counterr]) + lb[counterr];
}
ytf[counterr][j] = f(xin);
}
counterr++;
}
//write outputs
for (int f = 0; f < tf.Count; f++)
{
string[] stry = new string[k];
for (int j = 0; j < k; j++)
{
stry[j] = ytf[f][j] + ";";
}
Misc.IO.WriteTextFile(outputpath, "output_n" + n + "_tf" + f + ".csv", stry);
//////MICHALEWICZ FUNCTION ONLY
//writetextfile(outputpath, "output_n" + n + "_tf" + 4 + "_large.csv", stry);
Console.WriteLine("tf {0} done", f);
}
Console.WriteLine("All Sampling done");
Console.ReadKey();
}
