private void ClearExtrapolation()
{
for (int i = 0; i < extrapolators.Length; i++)
{
extrapolators[i].Clear();
}
errorExtrapolator.Clear();
}
public virtual void Clear()
{
extrapolator.Clear();
}
public void Clear()
{
yExtrapolator.Clear();
ypExtrapolator.Clear();
}
public override void Step()
{
yExtrapolator.Clear();
ypExtrapolator.Clear();
int work = 1;
double bestEfficiency = 0.0;
double bestFactor = 1.0;
int bestK = -1;
for (int k = 0; k < N.Length; k++)
{
double y1, yp1;
TrialStep(N[k], out y1, out yp1);
yExtrapolator.Add(MoreMath.Sqr(1.0 / N[k]), y1);
ypExtrapolator.Add(MoreMath.Sqr(1.0 / N[k]), yp1);
work += N[k];
if (k < 1)
{
continue;
}
UncertainValue yEstimate = yExtrapolator.Estimate;
double error = yEstimate.Uncertainty;
double tol = Settings.ComputePrecision(yEstimate.Value);
double factor = Math.Pow(tol / error, 1.0 / (2 * k + 1));
double efficiency = factor / work;
if (((k + 1) < N.Length) && (efficiency > bestEfficiency))
{
bestEfficiency = efficiency;
bestFactor = factor;
bestK = k;
}
if (error <= tol)
{
X += DeltaX;
Y = yEstimate.Value;
YPrime = ypExtrapolator.Estimate.Value;
YPrimePrime = Evaluate(X, Y);
if ((k + 2) < N.Length)
{
double extrapolatedError = MoreMath.Sqr(1.0 * N[0] / N[k + 1]) * error;
int extrapolatedWork = work + N[k + 1];
double extrapolatedFactor = Math.Pow(tol / extrapolatedError, 1.0 / (2 * k + 3));
double extrapolatedEfficiency = extrapolatedFactor / extrapolatedWork;
if (extrapolatedEfficiency > bestEfficiency)
{
bestEfficiency = extrapolatedEfficiency;
bestFactor = extrapolatedFactor;
bestK = k + 1;
}
}
break;
}
}
if (bestFactor < 0.2)
{
bestFactor = 0.2;
}
if (bestFactor > 5.0)
{
bestFactor = 5.0;
}
DeltaX *= 0.9375 * bestFactor;
}