private IntermediatePointResult IntermediatePoint(
MultidimensionalFunctionFDF fdf,
Vector <double> x,
Vector <double> p,
double lambda,
double pg,
double stepa,
double stepc,
double fa,
double fc,
Vector <double> x1,
Vector <double> dx,
double step,
double f)
{
double stepb = 0, fb;
Trial:
{
double u = Math.Abs(pg * lambda * stepc);
stepb = 0.5 * stepc * u / ((fc - fa) + u);
}
TakeStep(x, p, stepb, lambda, x1, dx);
if (x.Equals(x1))
{
return(new IntermediatePointResult
{
Step = 0,
F = fa,
Gradient = fdf.DF(x1)
});
}
fb = fdf.F(x1);
if (fb >= fa && stepb > 0)
{
fc = fb;
stepc = stepb;
goto Trial;
}
var gradient = fdf.DF(x1);
return(null);
}
public IterationResult Iterate(
MultidimensionalFunctionFDF fdf,
double fa,
Vector <double> gradient,
Vector <double> x,
Vector <double> dx)
{
var p = State.P;
if (State.PNorm == 0 || State.G0Norm == 0)
{
dx.SetValue(0);
return(new IterationResult
{
State = IterationResultStates.ERROR
});
}
double pg = p.Multiply(gradient);
var dir = (pg > 0) ? 1 : -1;
TakeStep(x, p, State.Step, dir / State.PNorm, State.X1, dx);
double fc = fdf.F(State.X1);
if (fc < fa)
{
State.Step = State.Step * 2;
State.X1.CopyTo(x);
return(new IterationResult
{
F = fc,
State = IterationResultStates.SUCCESS
});
}
return(null);
}
public MultidimensionalMinimizer(int n, IMultidimensionalIterator iterator, MultidimensionalFunctionFDF fdf)
{
Init(n);
Iterator = iterator;
FDF = fdf;
}