Minuit2Minimizer.h

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// @(#)root/minuit2:$Id$
// Author: L. Moneta Wed Oct 18 11:48:00 2006
 
/**********************************************************************
 *                                                                    *
 * Copyright (c) 2006  LCG ROOT Math Team, CERN/PH-SFT                *
 *                                                                    *
 *                                                                    *
 **********************************************************************/
 
// Header file for class Minuit2Minimizer
 
#ifndef ROOT_Minuit2_Minuit2Minimizer
#define ROOT_Minuit2_Minuit2Minimizer
 
#include "Math/Minimizer.h"
 
#include "Minuit2/MnUserParameterState.h"
 
#include "Math/IFunctionfwd.h"
 
 
 
namespace ROOT {
 
   namespace Minuit2 {
 
      class ModularFunctionMinimizer;
      class FCNBase;
      class FunctionMinimum;
      class MnTraceObject;
 
      // enumeration specifying the type of Minuit2 minimizers
      enum EMinimizerType {
         kMigrad,
         kSimplex,
         kCombined,
         kScan,
         kFumili,
         kMigradBFGS
      };
 
   }
 
   namespace Minuit2 {
//_____________________________________________________________________________________________________
/**
   Minuit2Minimizer class implementing the ROOT::Math::Minimizer interface for
   Minuit2 minimization algorithm.
   In ROOT it can be instantiated using the plug-in manager (plug-in "Minuit2")
   Using a string  (used by the plugin manager) or via an enumeration
   an one can set all the possible minimization algorithms (Migrad, Simplex, Combined, Scan and Fumili).
 
   Refer to the [guide](https://root.cern.ch/root/htmldoc/guides/minuit2/Minuit2.html) for an introduction how Minuit works.
 
   @ingroup Minuit
*/
class Minuit2Minimizer : public ROOT::Math::Minimizer {
 
public:
 
   /**
      Default constructor
   */
   Minuit2Minimizer (ROOT::Minuit2::EMinimizerType type = ROOT::Minuit2::kMigrad);
 
   /**
      Constructor with a char (used by PM)
   */
   Minuit2Minimizer (const char *  type);
 
   /**
      Destructor (no operations)
   */
   virtual ~Minuit2Minimizer ();
 
private:
   // usually copying is non trivial, so we make this unaccessible
 
   /**
      Copy constructor
   */
   Minuit2Minimizer(const Minuit2Minimizer &);
 
   /**
      Assignment operator
   */
   Minuit2Minimizer & operator = (const Minuit2Minimizer & rhs);
 
public:
 
   // clear resources (parameters) for consecutives minimizations
   virtual void Clear();
 
   /// set the function to minimize
   virtual void SetFunction(const ROOT::Math::IMultiGenFunction & func);
 
   /// set gradient the function to minimize
   virtual void SetFunction(const ROOT::Math::IMultiGradFunction & func);
 
   /// set free variable
   virtual bool SetVariable(unsigned int ivar, const std::string & name, double val, double step);
 
   /// set lower limit variable  (override if minimizer supports them )
   virtual bool SetLowerLimitedVariable(unsigned int  ivar , const std::string & name , double val , double step , double lower );
   /// set upper limit variable (override if minimizer supports them )
   virtual bool SetUpperLimitedVariable(unsigned int ivar , const std::string & name , double val , double step , double upper );
   /// set upper/lower limited variable (override if minimizer supports them )
   virtual bool SetLimitedVariable(unsigned int ivar , const std::string & name , double val , double step , double /* lower */, double /* upper */);
   /// set fixed variable (override if minimizer supports them )
   virtual bool SetFixedVariable(unsigned int /* ivar */, const std::string & /* name */, double /* val */);
   /// set variable
   virtual bool SetVariableValue(unsigned int ivar, double val);
   // set variable values
   virtual bool SetVariableValues(const double * val);
   /// set the step size of an already existing variable
   virtual bool SetVariableStepSize(unsigned int ivar, double step );
   /// set the lower-limit of an already existing variable
   virtual bool SetVariableLowerLimit(unsigned int ivar, double lower);
   /// set the upper-limit of an already existing variable
   virtual bool SetVariableUpperLimit(unsigned int ivar, double upper);
   /// set the limits of an already existing variable
   virtual bool SetVariableLimits(unsigned int ivar, double lower, double upper);
   /// fix an existing variable
   virtual bool FixVariable(unsigned int ivar);
   /// release an existing variable
   virtual bool ReleaseVariable(unsigned int ivar);
   /// query if an existing variable is fixed (i.e. considered constant in the minimization)
   /// note that by default all variables are not fixed
   virtual bool IsFixedVariable(unsigned int ivar)  const;
   /// get variable settings in a variable object (like ROOT::Fit::ParamsSettings)
   virtual bool GetVariableSettings(unsigned int ivar, ROOT::Fit::ParameterSettings & varObj) const;
   /// get name of variables (override if minimizer support storing of variable names)
   virtual std::string VariableName(unsigned int ivar) const;
   /// get index of variable given a variable given a name
   /// return -1 if variable is not found
   virtual int VariableIndex(const std::string & name) const;
 
   /**
       method to perform the minimization.
       Return false in case the minimization did not converge. In this case a
       status code different than zero is set
       (retrieved by the derived method Minimizer::Status() )"
 
       status = 1    : Covariance was made pos defined
       status = 2    : Hesse is invalid
       status = 3    : Edm is above max
       status = 4    : Reached call limit
       status = 5    : Any other failure
   */
   virtual  bool Minimize();
 
   /// return minimum function value
   virtual double MinValue() const { return fState.Fval(); }
 
   /// return expected distance reached from the minimum
   virtual double Edm() const { return fState.Edm(); }
 
   /// return  pointer to X values at the minimum
   virtual const double *  X() const { return  &fValues.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 fState.NFcn(); }
 
   /// 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 fState.VariableParameters(); }
 
   /// minimizer provides error and error matrix
   virtual bool ProvidesError() const { return true; }
 
   /// return errors at the minimum
   virtual const double * Errors() const;
 
   /**
       return covariance matrix elements
       if the variable is fixed or const the value is zero
       The ordering of the variables is the same as in errors and parameter value.
       This is different from the direct interface of Minuit2 or TMinuit where the
       values were obtained only to variable parameters
   */
   virtual double CovMatrix(unsigned int i, unsigned int j) const;
 
 
   /**
       Fill the passed array with the  covariance matrix elements
       if the variable is fixed or const the value is zero.
       The array will be filled as cov[i *ndim + j]
       The ordering of the variables is the same as in errors and parameter value.
       This is different from the direct interface of Minuit2 or TMinuit where the
       values were obtained only to variable parameters
   */
   virtual bool GetCovMatrix(double * cov) const;
 
   /**
       Fill the passed array with the Hessian matrix elements
       The Hessian matrix is the matrix of the second derivatives
       and is the inverse of the covariance matrix
       If the variable is fixed or const the values for that variables are zero.
       The array will be filled as h[i *ndim + j]
   */
   virtual bool GetHessianMatrix(double * h) const;
 
 
   /**
      return the status of the covariance matrix
       status = -1 :  not available (inversion failed or Hesse failed)
       status =  0 : available but not positive defined
       status =  1 : covariance only approximate
       status =  2 : full matrix but forced pos def
       status =  3 : full accurate matrix
 
    */
   virtual int CovMatrixStatus() const;
   /**
      return correlation coefficient between variable i and j.
      If the variable is fixed or const the return value is zero
    */
   virtual double Correlation(unsigned int i, unsigned int j ) const;
 
   /**
      get global correlation coefficient for the variable i. This is a number between zero and one which gives
      the correlation between the i-th variable  and that linear combination of all other variables which
      is most strongly correlated with i.
      If the variable is fixed or const the return value is zero
    */
   virtual double GlobalCC(unsigned int i) const;
 
   /**
      get the minos error for parameter i, return false if Minos failed
      A minimizaiton must be performed befre, return false if no minimization has been done
      In case of Minos failed the status error is updated as following
      status += 10 * minosStatus. 
      The Minos status of last Minos run can also be retrieved by calling MinosStatus()
   */
   virtual bool GetMinosError(unsigned int i, double & errLow, double & errUp, int = 0);
 
   /** 
      MINOS status code of last Minos run
       `status & 1 > 0`  : invalid lower error
       `status & 2 > 0`  : invalid upper error
       `status & 4 > 0`  : invalid because maximum number of function calls exceeded
       `status & 8 > 0`  : a new minimum has been found
       `status & 16 > 0` : error is truncated because parameter is at lower/upper limit
   */
   virtual int MinosStatus() const { return fMinosStatus; }
 
   /**
      scan a parameter i around the minimum. A minimization must have been done before,
      return false if it is not the case
    */
   virtual bool Scan(unsigned int i, unsigned int & nstep, double * x, double * y, double xmin = 0, double xmax = 0);
 
   /**
      find the contour points (xi,xj) of the function for parameter i and j around the minimum
      The contour will be find for value of the function = Min + ErrorUp();
    */
   virtual bool Contour(unsigned int i, unsigned int j, unsigned int & npoints, double *xi, double *xj);
 
 
   /**
      perform a full calculation of the Hessian matrix for error calculation
      If a valid minimum exists the calculation is done on the minimum point otherwise is performed
      in the current set values of parameters
      Status code of minimizer is updated according to the following convention (in case Hesse failed)
      status += 100*hesseStatus where hesse status is:
      status = 1 : hesse failed
      status = 2 : matrix inversion failed
      status = 3 : matrix is not pos defined
    */
   virtual bool Hesse();
 
 
   /// return reference to the objective function
   ///virtual const ROOT::Math::IGenFunction & Function() const;
 
   /// print result of minimization
   virtual void PrintResults();
 
   /// set an object to trace operation for each iteration
   /// The object must be a (or inherit from) ROOT::Minuit2::MnTraceObject and implement operator() (int, const MinimumState & state)
   void SetTraceObject(MnTraceObject & obj);
 
   /// set storage level   = 1 : store all iteration states (default)
   ///                     = 0 : store only first and last state to save memory
   void SetStorageLevel(int level);
 
   /// return the minimizer state (containing values, step size , etc..)
   const ROOT::Minuit2::MnUserParameterState & State() { return fState; }
 
protected:
 
   // protected function for accessing the internal Minuit2 object. Needed for derived classes
 
   virtual const ROOT::Minuit2::ModularFunctionMinimizer * GetMinimizer() const { return fMinimizer; }
 
   virtual void SetMinimizer( ROOT::Minuit2::ModularFunctionMinimizer * m)  { fMinimizer = m; }
 
   void SetMinimizerType( ROOT::Minuit2::EMinimizerType type);
 
   virtual const  ROOT::Minuit2::FCNBase * GetFCN() const { return fMinuitFCN; }
 
   /// examine the minimum result
   bool ExamineMinimum(const ROOT::Minuit2::FunctionMinimum & min);
 
   // internal function to compute Minos errors
   int RunMinosError(unsigned int i, double & errLow, double & errUp, int runopt);
 
private:
 
   unsigned int fDim;       // dimension of the function to be minimized
   bool fUseFumili;
   int fMinosStatus = -1;  // Minos status code
 
   ROOT::Minuit2::MnUserParameterState fState;
   // std::vector<ROOT::Minuit2::MinosError> fMinosErrors;
   ROOT::Minuit2::ModularFunctionMinimizer * fMinimizer;
   ROOT::Minuit2::FCNBase * fMinuitFCN;
   ROOT::Minuit2::FunctionMinimum * fMinimum;
   mutable std::vector<double> fValues;
   mutable std::vector<double> fErrors;
 
};
 
   } // end namespace Fit
 
} // end namespace ROOT
 
 
 
#endif /* ROOT_Minuit2_Minuit2Minimizer */