[root] View of /trunk/math/minuit/inc/TLinearMinimizer.h

Revision 25486 - (download) (as text) (annotate)
Mon Sep 22 12:43:03 2008 UTC (6 years, 4 months ago) by moneta
File size: 4036 byte(s)

import changes from math development branches for subdirectory math. List of changes in detail: 

mathcore: 
---------
  MinimizerOptions: 
	new  class for storing Minimizer option, with static default values that can be 
	changed by the user

  FitConfig: 
   	- use default values from MinimizerOption class
   	- rename method to create parameter settings from a function

  FitUtil.cxx:   
    	improve the derivative calculations used in the effective chi2 and in Fumili and 
	fix a bug for evaluation of likelihood or chi2 terms. 
	In  EvaluatePdf() work and return  the log of the pdf. 
      
  FitResult:
	- improve the class by adding extra information like, num. of free parameters, 
	minimizer status, global correlation coefficients, information about fixed 
	and bound parameters. 
   	- add method for getting fit confidence intervals 
  	- improve print method   

  DataRange: 
	add method SetRange to distinguish from AddRange. SetRange deletes the existing 
	ranges. 

  ParamsSettings: make few methods const

  FCN functions (Chi2FCN, LogLikelihoodFCN, etc..) 
	move some common methods and data members in base class (FitMethodFunction)

  RootFinder: add template Solve() for any callable function.  

mathmore:
--------
  minimizer classes: fill status information
  GSLNLSMinimizer: return error and covariance matrix 

minuit2: 
-------
  Minuit2Minimizer: fill  status information 
  DavidonErrorUpdator: check that delgam or gvg are not zero ( can happen when dg = 0)
  FumiliFCNAdapter: work on the log of pdf

minuit:
------- 
  TLinearMinimizer: add support for robust fitting
  TMinuitMinimizer: fill status information and fix a bug in filling the correlation matrix. 
 fumili:
 ------ 
  add TFumiliMinimizer: 
	wrapper class for TFumili using Minimizer interface

// @(#)root/minuit:$Id$
// Author: L. Moneta Wed Oct 25 16:28:55 2006

/**********************************************************************
 *                                                                    *
 * Copyright (c) 2006  LCG ROOT Math Team, CERN/PH-SFT                *
 *                                                                    *
 *                                                                    *
 **********************************************************************/

// Header file for class TLinearMinimizer

#ifndef ROOT_TLinearMinimizer
#define ROOT_TLinearMinimizer

#ifndef ROOT_Math_Minimizer
#include "Math/Minimizer.h"
#endif

#ifndef ROOT_Rtypes
#include "Rtypes.h"
#endif

#include <vector>

class TLinearFitter; 


 

/** 
   TLinearMinimizer class: minimizer implementation based on TMinuit.
*/ 
class TLinearMinimizer  : public ROOT::Math::Minimizer {

public: 

   /** 
      Default constructor
   */ 
   TLinearMinimizer (int type = 0); 

   /** 
      Constructor from a char * (used by PM)
   */ 
   TLinearMinimizer ( const char * type ); 

   /** 
      Destructor (no operations)
   */ 
   virtual ~TLinearMinimizer (); 

private:
   // usually copying is non trivial, so we make this unaccessible

   /** 
      Copy constructor
   */ 
   TLinearMinimizer(const TLinearMinimizer &); 

   /** 
      Assignment operator
   */ 
   TLinearMinimizer & operator = (const TLinearMinimizer & rhs); 

public: 

   /// set the fit model function
   virtual void SetFunction(const ROOT::Math::IMultiGenFunction & func); 

   /// set the function to minimize
   virtual void SetFunction(const ROOT::Math::IMultiGradFunction & func); 

   /// set free variable (dummy impl. )
   virtual bool SetVariable(unsigned int , const std::string & , double , double ) { return false; } 

   /// set fixed variable (override if minimizer supports them )
   virtual bool SetFixedVariable(unsigned int /* ivar */, const std::string & /* name */, double /* val */);  

   /// method to perform the minimization
   virtual  bool Minimize(); 

   /// return minimum function value
   virtual double MinValue() const { return fMinVal; } 

   /// return expected distance reached from the minimum
   virtual double Edm() const { return 0; }

   /// return  pointer to X values at the minimum 
   virtual const double *  X() const { return &fParams.front(); }

   /// return pointer to gradient values at the minimum 
   virtual const double *  MinGradient() const { return 0; } // not available in Minuit2 

   /// number of function calls to reach the minimum 
   virtual unsigned int NCalls() const { return 0; } 

   /// this is <= Function().NDim() which is the total 
   /// number of variables (free+ constrained ones) 
   virtual unsigned int NDim() const { return fDim; }   

   /// number of free variables (real dimension of the problem) 
   /// this is <= Function().NDim() which is the total 
   virtual unsigned int NFree() const { return fNFree; }  

   /// minimizer provides error and error matrix
   virtual bool ProvidesError() const { return true; } 

   /// return errors at the minimum 
   virtual const double * Errors() const { return  &fErrors.front(); }

   /** return covariance matrices elements 
       if the variable is fixed the matrix is zero
       The ordering of the variables is the same as in errors
   */ 
   virtual double CovMatrix(unsigned int i, unsigned int j) const { 
      return fCovar[i + fDim* j]; 
   }

   /// return reference to the objective function
   ///virtual const ROOT::Math::IGenFunction & Function() const; 


   

protected: 

private: 

   bool fRobust; 
   unsigned int fDim; 
   unsigned int fNFree;
   double fMinVal;
   std::vector<double> fParams;
   std::vector<double> fErrors;
   std::vector<double> fCovar; 

   const ROOT::Math::IMultiGradFunction * fObjFunc;
   TLinearFitter * fFitter; 

   ClassDef(TLinearMinimizer,1)  //Implementation of the Minimizer interface using TLinearFitter 

}; 



#endif /* ROOT_TLinearMinimizer */