/// <summary>Realizes a sample function for respective stochastic domain mapper and parameters.</summary>
/// <param name="iteration">The iteration.</param>
/// <param name="domainMapper">The domain mapper.</param>
/// <param name="parameters">The parameters.</param>
/// <returns></returns>
public double Realize(int iteration, IStochasticDomainMapper domainMapper, double[] parameters)
{
ResetGeneration = (PreviousIteration != iteration);
if (ResetGeneration)
{
ResetSampleGeneration();
}
double[] stochasticDomainPoint = domainMapper.Map(parameters);
var dw = wu / (double)frequencyIntervals;
int i = 0;
double randomCoefficient = 0;
while (i < frequencyIntervals)
{
randomCoefficient += Math.Sqrt(2) * Math.Sqrt(2 * SpectralDensity(dw / 2 + i * dw) * dw) *
(Math.Cos((dw / 2 + i * dw) * stochasticDomainPoint[0] +
phi[i]));
i++;
}
if (randomCoefficient >= .9)
{
randomCoefficient = .9;
}
else if (randomCoefficient <= -.9)
{
randomCoefficient = -.9;
}
PreviousIteration = iteration;
return(MeanValue / (1 + randomCoefficient));
}
/// <summary>Realizes the specified iteration based on a stochastic domain mapper and the respective domain parameters.</summary>
/// <param name="iteration">The iteration.</param>
/// <param name="domainMapper">The domain mapper.</param>
/// <param name="parameters">The parameters.</param>
/// <returns></returns>
public double Realize(int iteration, IStochasticDomainMapper domainMapper, double[] parameters)
{
ResetGeneration = (PreviousIteration != iteration);
if (ResetGeneration)
{
ResetSampleGeneration();
}
var stochasticDomainPoint = domainMapper.Map(parameters);
double[] eigenModesAtPoint = CalculateEigenmodesAtPoint(Xcoordinates, Eigenvectors, stochasticDomainPoint[0]);
var value = KarhunenLoeveFredholm1DSampleGenerator(stochasticDomainPoint, Lambda, eigenModesAtPoint, MeanValue, MidpointMethod, IsGaussian);
PreviousIteration = iteration;
return(value);
}
public double[] GetDerivative(IStochasticDomainMapper domainMapper, double[] parameters)
{
double[] stochasticDomainPoint = domainMapper.Map(parameters);
var dk = kupper / (double)frequencyIntervals;
double[] derivative = { 0, 0 };
for (int i = 0; i < frequencyIntervals; i++)
{
for (int j = 0; j < frequencyIntervals; j++)
{
derivative[0] += -(dk / 2 + i * dk) * Math.Sqrt(2) * (Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, dk / 2 + j * dk) * dk) *
(Math.Sin((dk / 2 + i * dk) * stochasticDomainPoint[0] + (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi1[i, j])) +
Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, -(dk / 2 + j * dk)) * dk) *
(Math.Sin((dk / 2 + i * dk) * stochasticDomainPoint[0] - (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi2[i, j])));
derivative[1] += -(dk / 2 + j * dk) * Math.Sqrt(2) * (Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, dk / 2 + j * dk) * dk) *
(Math.Sin((dk / 2 + i * dk) * stochasticDomainPoint[0] + (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi1[i, j])) -
Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, -(dk / 2 + j * dk)) * dk) *
(Math.Sin((dk / 2 + i * dk) * stochasticDomainPoint[0] - (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi2[i, j])));
}
}
return(derivative);
}
public double Realize(int iteration, IStochasticDomainMapper domainMapper, double[] parameters)
{
ResetGeneration = (PreviousIteration != iteration);
if (ResetGeneration)
{
ResetSampleGeneration();
}
double[] stochasticDomainPoint = domainMapper.Map(parameters);
var dk = kupper / (double)frequencyIntervals;
double randomCoefficient = 0;
for (int i = 0; i < frequencyIntervals; i++)
{
for (int j = 0; j < frequencyIntervals; j++)
{
randomCoefficient += Math.Sqrt(2) * (Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, dk / 2 + j * dk) * dk) *
(Math.Cos((dk / 2 + i * dk) * stochasticDomainPoint[0] + (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi1[i, j])) +
Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, -(dk / 2 + j * dk)) * dk) *
(Math.Cos((dk / 2 + i * dk) * stochasticDomainPoint[0] - (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi2[i, j])));
}
}
return(randomCoefficient);
}