public double[] SuggestXs(int count, PhiEquationSolution[] solutions, Random rand)
{
const double randomness = 4; // TODO: could this value be optimized?
PhiEquationSolution BestSolution = solutions[0];
double[] suggestedXs = BestSolution.Phis.Select(x => x * (rand.NextDouble() - 0.5) * randomness).ToArray();
return(suggestedXs);
}
public double[] SuggestXs(int count, PhiEquationSolution[] solutions, Random rand)
{
if (solutions.Length < count + 1)
{
return(new NearBestSolution().SuggestXs(count, solutions, rand));
}
double[] suggestedXs = new double[count];
PhiEquationSolution referenceSolution = solutions[count];
// 2D array of error differences vs. the Nth solution
double[,] Mm = new double[count, count];
for (int j = 0; j < count; j++)
{
for (int k = 0; k < count; k++)
{
Mm[j, k] = solutions[k].Errors[j] - referenceSolution.Errors[j];
}
}
// 1d array of errors for the worst solution known
double[] mF0 = new double[count];
for (int j = 0; j < count; j++)
{
mF0[j] = -referenceSolution.Errors[j];
}
// 2D array of phis differences vs. the worst solution
double[,] Vm = new double[count, count];
for (int j = 0; j < count; j++)
{
for (int k = 0; k < count; k++)
{
Vm[j, k] = solutions[k].Phis[j] - referenceSolution.Phis[j];
}
}
double[] u = LinearAlgebra.Solve(Mm, mF0);
double[] delta = LinearAlgebra.Product(Vm, u);
for (int j = 0; j < count; j++)
{
suggestedXs[j] = referenceSolution.Phis[j] + delta[j];
}
return(suggestedXs);
}