public void OptimizationLBFGSB()
{
//Rosenbrock banana function
//f(a,b)=100*(b-a^2)^2+(1-a)^2
//The minimum is at (1,1) and the function value is 0.
//using DotNumerics.Optimization;
L_BFGS_B LBFGSB = new L_BFGS_B();
double[] initialGuess = new double[2];
initialGuess[0] = 0.1;
initialGuess[1] = 2;
double[] minimum = LBFGSB.ComputeMin(BananaFunction, BananaGradient, initialGuess);
ObjectDumper.Write("Limited memory Broyden–Fletcher–Goldfarb–Shanno method.");
ObjectDumper.Write("a = " + minimum[0].ToString() + ", b = " + minimum[1].ToString());
//f(a,b) = 100*(b-a^2)^2 + (1-a)^2
//private double BananaFunction(double[] x)
//{
// double f = 0;
// f = 100 * Math.Pow((x[1] - x[0] * x[0]), 2) + Math.Pow((1 - x[0]), 2);
// return f;
//}
//double[] bananaGrad = new double[2];
//private double[] BananaGradient(double[] x)
//{
// this.bananaGrad[0] = 200 * (x[1] - x[0] * x[0]) * (-2 * x[0]) - 2 * (1 - x[0]);
// this.bananaGrad[1] = 200 * (x[1] - x[0] * x[0]);
// return bananaGrad;
//}
}
public void OptimizationLBFGSBConstrained()
{
//This example minimize the function
//f(x0,x2,...,xn)= (x0-0)^2+(x1-1)^2+...(xn-n)^2
//The minimum is at (0,1,2,3...,n) for the unconstrained case.
//using DotNumerics.Optimization;
L_BFGS_B LBFGSB = new L_BFGS_B();
int numVariables = 5;
OptBoundVariable[] variables = new OptBoundVariable[numVariables];
//Constrained Minimization on the interval (-10,10), initial Guess=-2;
for (int i = 0; i < numVariables; i++)
{
variables[i] = new OptBoundVariable("x" + i.ToString(), -2, -10, 10);
}
double[] minimum = LBFGSB.ComputeMin(ObjetiveFunction, Gradient, variables);
ObjectDumper.Write("L-BFGS-B Method. Constrained Minimization on the interval (-10,10)");
for (int i = 0; i < minimum.Length; i++)
{
ObjectDumper.Write("x" + i.ToString() + " = " + minimum[i].ToString());
}
//Constrained Minimization on the interval (-10,3), initial Guess=-2;
for (int i = 0; i < numVariables; i++)
{
variables[i].UpperBound = 3;
}
minimum = LBFGSB.ComputeMin(ObjetiveFunction, Gradient, variables);
ObjectDumper.Write("L-BFGS-B Method. Constrained Minimization on the interval (-10,3)");
for (int i = 0; i < minimum.Length; i++)
{
ObjectDumper.Write("x" + i.ToString() + " = " + minimum[i].ToString());
}
//f(x0,x2,...,xn)= (x0-0)^2+(x1-1)^2+...(xn-n)^2
//private double ObjetiveFunction(double[] x)
//{
// int numVariables = 5;
// double f = 0;
// for (int i = 0; i < numVariables; i++) f += Math.Pow(x[i] - i, 2);
// return f;
//}
//private double[] Gradient(double[] x)
//{
// int numVariables = 5;
// double[] grad = new double[x.Length];
// for (int i = 0; i < numVariables; i++) grad[i] = 2 * (x[i] - i);
// return grad;
//}
}
public double[] StartMapping(SpotParsInitBox spotParsInitBox, string minimizator, double tau)
{
OptBoundVariable[] x = new OptBoundVariable[spotParsInitBox.SpotsNumber * 4];
for (int i = 0; i < x.Length; i++)
{
x[i] = new OptBoundVariable();
}
for (int q = 0; q < this.lcObs.Length; q++)
{
this.modellers[q].StarM.RemoveAllSpots();
for (int s = 0; s < spotParsInitBox.SpotsNumber; s++)
{
this.modellers[q].StarM.AddUniformCircularSpot(
spotParsInitBox.spots[s].longitude * Math.PI / 180,
spotParsInitBox.spots[s].colatutude * Math.PI / 180,
spotParsInitBox.spots[s].radius * Math.PI / 180,
spotParsInitBox.spots[s].teff,
spotParsInitBox.spots[s].beltsCount,
spotParsInitBox.spots[s].nearEquatorialPatchesCount);
}
}
this.fixedParsMask = new bool[x.Length];
for (int s = 0; s < spotParsInitBox.SpotsNumber; s++)
{
x[0 + s * 4].InitialGuess = spotParsInitBox.spots[s].longitude * Math.PI / 180;
x[0 + s * 4].UpperBound = spotParsInitBox.spots[s].longitudeUpperLimit * Math.PI / 180;
x[0 + s * 4].LowerBound = spotParsInitBox.spots[s].longitudeLowerLimit * Math.PI / 180;
x[0 + s * 4].Fixed = spotParsInitBox.spots[s].longitudeFixed;
this.fixedParsMask[0 + s * 4] = spotParsInitBox.spots[s].longitudeFixed;
x[1 + s * 4].InitialGuess = spotParsInitBox.spots[s].colatutude * Math.PI / 180;
x[1 + s * 4].UpperBound = spotParsInitBox.spots[s].colatitudeUpperLimit * Math.PI / 180;
x[1 + s * 4].LowerBound = spotParsInitBox.spots[s].colatitudeLowerLimit * Math.PI / 180;
x[1 + s * 4].Fixed = spotParsInitBox.spots[s].colatitudeFixed;
this.fixedParsMask[1 + s * 4] = spotParsInitBox.spots[s].colatitudeFixed;
x[2 + s * 4].InitialGuess = spotParsInitBox.spots[s].radius * Math.PI / 180;
x[2 + s * 4].UpperBound = spotParsInitBox.spots[s].radiusUpperLimit * Math.PI / 180;
x[2 + s * 4].LowerBound = spotParsInitBox.spots[s].radiusLowerLimit * Math.PI / 180;
x[2 + s * 4].Fixed = spotParsInitBox.spots[s].radiusFixed;
this.fixedParsMask[2 + s * 4] = spotParsInitBox.spots[s].radiusFixed;
x[3 + s * 4].InitialGuess = spotParsInitBox.spots[s].teff;
x[3 + s * 4].UpperBound = spotParsInitBox.spots[s].teffUpperLimit;
x[3 + s * 4].LowerBound = spotParsInitBox.spots[s].teffLowerLimit;
x[3 + s * 4].Fixed = spotParsInitBox.spots[s].teffFixed;
this.fixedParsMask[3 + s * 4] = spotParsInitBox.spots[s].teffFixed;
}
double[] res = new double[4];
if (minimizator == "Simplex")
{
Simplex simplex = new Simplex();
res = simplex.ComputeMin(this.Khi2, x);
}
if (minimizator == "TN")
{
//DotNumerics.Optimization.TruncatedNewton tn = new TruncatedNewton();
DotNumerics.Optimization.L_BFGS_B bfgs = new L_BFGS_B();
//tn.SearchSeverity = 1;
//res = tn.ComputeMin(this.Khi2, this.GradKhi2, x);
res = bfgs.ComputeMin(this.Khi2, this.GradKhi2, x);
}
if (minimizator == "LM")
{
LevenbergMaquard gn = new LevenbergMaquard();
gn.MinimizedFunction = this.ResudalVector;
double[] step = new double[x.Length];
double[] xinit = new double[x.Length];
bool[] isFixed = new bool[x.Length];
double[] lowLimits = new double[x.Length];
double[] highLimits = new double[x.Length];
for (int i = 0; i < xinit.Length; i++)
{
xinit[i] = x[i].InitialGuess;
isFixed[i] = x[i].Fixed;
lowLimits[i] = x[i].LowerBound;
highLimits[i] = x[i].UpperBound;
if (i != 0 && (i + 1) % 4 == 0)
{
step[i] = 10; // step for temperature;
}
else
{
step[i] = 0.02;
}
}
gn.StepForDer = step;
gn.IterMax = 100;
gn.Tau = tau;
res = gn.ComputeMin(xinit, isFixed, lowLimits, highLimits);
}
this.khi2 = this.Khi2(res);
this.GenerateModLightCurve();
return(res);
}
