FumiliStandardChi2FCN.h

Go to the documentation of this file.

// @(#)root/minuit2:$Id$
// Authors: M. Winkler, F. James, L. Moneta, A. Zsenei   2003-2005
 
/**********************************************************************
 *                                                                    *
 * Copyright (c) 2005 LCG ROOT Math team,  CERN/PH-SFT                *
 *                                                                    *
 **********************************************************************/
 
#ifndef ROOT_Minuit2_FumiliStandardChi2FCN
#define ROOT_Minuit2_FumiliStandardChi2FCN
 
#include "Minuit2/FumiliChi2FCN.h"
#include "Minuit2/ParametricFunction.h"
 
#include <ROOT/RSpan.hxx>
 
#include <cassert>
#include <vector>
#include <cmath>
 
namespace ROOT {
 
namespace Minuit2 {
 
/**
 
Class implementing the standard chi square function, which
is the sum of the squares of the figures-of-merit calculated for each measurement
point, the individual figures-of-merit being: (the Value predicted by the
model-measured Value)/standard deviation.
 
@author Andras Zsenei and Lorenzo Moneta, Creation date: 31 Aug 2004
 
@see FumiliChi2FCN
 
@ingroup Minuit
 
\todo nice formula for the documentation...
 
*/
 
class FumiliStandardChi2FCN : public FumiliChi2FCN {
 
public:
   /**
 
   Constructor which initializes chi square function for one-dimensional model function
 
   @param modelFCN the model function used for describing the data.
 
   @param meas vector containing the measured values.
 
   @param pos vector containing the x values corresponding to the
   measurements
 
   @param mvar vector containing the variances corresponding to each
   measurement (where the variance equals the standard deviation squared).
   If the variances are zero, a Value of 1 is used (as it is done in ROOT/PAW)
 
   */
 
   FumiliStandardChi2FCN(const ParametricFunction &modelFCN, std::span<const double> meas,
                         std::span<const double> pos, std::span<const double> mvar)
   { // this->fModelFCN = &modelFunction;
      this->SetModelFunction(modelFCN);
 
      assert(meas.size() == pos.size());
      assert(meas.size() == mvar.size());
      fMeasurements.assign(meas.begin(), meas.end());
      std::vector<double> x(1);
      unsigned int n = mvar.size();
      fPositions.reserve(n);
      // correct for variance == 0
      fInvErrors.resize(n);
      for (unsigned int i = 0; i < n; ++i) {
         x[0] = pos[i];
         fPositions.push_back(x);
         // PAW/ROOT hack : use 1 for 0 entries bins
         if (mvar[i] == 0)
            fInvErrors[i] = 1;
         else
            fInvErrors[i] = 1.0 / std::sqrt(mvar[i]);
      }
   }
 
   /**
 
   Constructor which initializes the multi-dimensional model function.
 
   @param modelFCN the model function used for describing the data.
 
   @param meas vector containing the measured values.
 
   @param pos vector containing the x values corresponding to the
   measurements
 
   @param mvar vector containing the variances corresponding to each
   measurement (where the variance equals the standard deviation squared).
   If the variances are zero, a Value of 1 is used (as it is done in ROOT/PAW)
 
   */
 
   FumiliStandardChi2FCN(const ParametricFunction &modelFCN, std::span<const double> meas,
                         std::span<const std::vector<double>> pos, std::span<const double> mvar)
   { // this->fModelFCN = &modelFunction;
      this->SetModelFunction(modelFCN);
 
      assert(meas.size() == pos.size());
      assert(meas.size() == mvar.size());
      fMeasurements.assign(meas.begin(), meas.end());
      fPositions.assign(pos.begin(), pos.end());
      // correct for variance == 0
      unsigned int n = mvar.size();
      fInvErrors.resize(n);
      for (unsigned int i = 0; i < n; ++i) {
         // PAW/ROOT hack : use 1 for 0 entries bins
         if (mvar[i] == 0)
            fInvErrors[i] = 1;
         else
            fInvErrors[i] = 1.0 / std::sqrt(mvar[i]);
      }
   }
 
   /**
 
   Evaluates the model function for the different measurement points and
   the Parameter values supplied, calculates a figure-of-merit for each
   measurement and returns a vector containing the result of this
   evaluation. The figure-of-merit is (Value predicted by the model
   function-measured Value)/standard deviation.
 
   @param par vector of Parameter values to feed to the model function.
 
   @return A vector containing the figures-of-merit for the model function evaluated
   for each set of measurements.
 
   \todo What to do when the variances are 0???!! (right now just pushes back 0...)
 
   */
 
   std::vector<double> Elements(std::vector<double> const &par) const override;
 
   /**
 
   Accessor to the position of the measurement (x coordinate).
 
   @param Index Index of the measuerement the position of which to return.
 
   @return the position of the measurement.
 
   */
 
   const std::vector<double> &GetMeasurement(int Index) const override;
 
   /**
 
   Accessor to the number of measurements used for calculating
   the chi-square.
 
   @return the number of measurements.
 
   */
 
   int GetNumberOfMeasurements() const override;
 
   /**
 
   Evaluate function Value, Gradient and Hessian using Fumili approximation, for values of parameters p
   The result is cached inside and is return from the FumiliFCNBase::Value ,  FumiliFCNBase::Gradient and
   FumiliFCNBase::Hessian methods
 
   @param par vector of parameters
 
   **/
 
   void EvaluateAll(std::vector<double> const &par) override;
 
private:
   std::vector<double> fMeasurements;
   // support multi dim coordinates
   std::vector<std::vector<double>> fPositions;
   std::vector<double> fInvErrors;
};
 
} // namespace Minuit2
 
} // namespace ROOT
 
#endif // ROOT_Minuit2_FumiliStandardChi2FCN