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NumericalMinimization.C File Reference

## Detailed Description  Example on how to use the new Minimizer class in ROOT Show usage with all the possible minimizers.

Minimize the Rosenbrock function (a 2D -function)

input : minimizer name + algorithm name randomSeed: = <0 : fixed value: 0 random with seed 0; >0 random with given seed

#include "Math/Minimizer.h"
#include "Math/Factory.h"
#include "Math/Functor.h"
#include "TRandom2.h"
#include "TError.h"
#include <iostream>
double RosenBrock(const double *xx )
{
const double x = xx;
const double y = xx;
const double tmp1 = y-x*x;
const double tmp2 = 1-x;
return 100*tmp1*tmp1+tmp2*tmp2;
}
int NumericalMinimization(const char * minName = "Minuit2",
const char *algoName = "" ,
int randomSeed = -1)
{
// create minimizer giving a name and a name (optionally) for the specific
// algorithm
// possible choices are:
// minName algoName
// Minuit2 Fumili2
// Fumili
// GSLMultiMin ConjugateFR, ConjugatePR, BFGS,
// BFGS2, SteepestDescent
// GSLMultiFit
// GSLSimAn
// Genetic
if (!minimum) {
std::cerr << "Error: cannot create minimizer \"" << minName
<< "\". Maybe the required library was not built?" << std::endl;
return 1;
}
// set tolerance , etc...
minimum->SetMaxFunctionCalls(1000000); // for Minuit/Minuit2
minimum->SetMaxIterations(10000); // for GSL
minimum->SetTolerance(0.001);
minimum->SetPrintLevel(1);
// create function wrapper for minimizer
// a IMultiGenFunction type
ROOT::Math::Functor f(&RosenBrock,2);
double step = {0.01,0.01};
// starting point
double variable = { -1.,1.2};
if (randomSeed >= 0) {
TRandom2 r(randomSeed);
variable = r.Uniform(-20,20);
variable = r.Uniform(-20,20);
}
minimum->SetFunction(f);
// Set the free variables to be minimized !
minimum->SetVariable(0,"x",variable, step);
minimum->SetVariable(1,"y",variable, step);
// do the minimization
minimum->Minimize();
const double *xs = minimum->X();
std::cout << "Minimum: f(" << xs << "," << xs << "): "
<< minimum->MinValue() << std::endl;
// expected minimum is 0
if ( minimum->MinValue() < 1.E-4 )
std::cout << "Minimizer " << minName << " - " << algoName
<< " converged to the right minimum" << std::endl;
else {
std::cout << "Minimizer " << minName << " - " << algoName
<< " failed to converge !!!" << std::endl;
Error("NumericalMinimization","fail to converge");
}
return 0;
}
#define f(i)
Definition RSha256.hxx:104
void Error(const char *location, const char *msgfmt,...)
Use this function in case an error occurred.
Definition TError.cxx:188
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t r
static ROOT::Math::Minimizer * CreateMinimizer(const std::string &minimizerType="", const std::string &algoType="")
static method to create the corresponding Minimizer given the string Supported Minimizers types are: ...
Definition Factory.cxx:63
Documentation for class Functor class.
Definition Functor.h:47
Abstract Minimizer class, defining the interface for the various minimizer (like Minuit2,...
Definition Minimizer.h:78
virtual const double * X() const =0
return pointer to X values at the minimum
void SetMaxIterations(unsigned int maxiter)
set maximum iterations (one iteration can have many function calls)
Definition Minimizer.h:449
virtual void SetFunction(const ROOT::Math::IMultiGenFunction &func)=0
set the function to minimize
void SetTolerance(double tol)
set the tolerance
Definition Minimizer.h:452
virtual bool Minimize()=0
method to perform the minimization
void SetPrintLevel(int level)
set print level
Definition Minimizer.h:443
virtual bool SetVariable(unsigned int ivar, const std::string &name, double val, double step)=0
set a new free variable
void SetMaxFunctionCalls(unsigned int maxfcn)
set maximum of function calls
Definition Minimizer.h:446
virtual double MinValue() const =0
return minimum function value
Random number generator class based on the maximally quidistributed combined Tausworthe generator by ...
Definition TRandom2.h:27
Double_t y[n]
Definition legend1.C:17
Double_t x[n]
Definition legend1.C:17

Definition in file NumericalMinimization.C.