LauDPDepGaussPdf.cc

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// Copyright University of Warwick 2009 - 2013.
// Distributed under the Boost Software License, Version 1.0.
// (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)

// Authors:
// Thomas Latham
// John Back
// Paul Harrison

#include <iostream>
#include <vector>
using std::cout;
using std::cerr;
using std::endl;

#include "TMath.h"
#include "TSystem.h"

#include "LauConstants.hh"
#include "LauDaughters.hh"
#include "LauDPDepGaussPdf.hh"
#include "LauKinematics.hh"

ClassImp(LauDPDepGaussPdf)


LauDPDepGaussPdf::LauDPDepGaussPdf(const TString& theVarName, const std::vector<LauAbsRValue*>& params,
                Double_t minAbscissa, Double_t maxAbscissa,
                const LauDaughters* daughters,
                const std::vector<Double_t>& meanCoeffs,
                const std::vector<Double_t>& sigmaCoeffs,
                DPAxis dpAxis) :
        LauAbsPdf(theVarName, params, minAbscissa, maxAbscissa),
        kinematics_(daughters ? daughters->getKinematics() : 0),
        mean_(0),
        sigma_(0),
        meanVal_(0.0),
        sigmaVal_(0.0),
        meanCoeffs_(meanCoeffs),
        sigmaCoeffs_(sigmaCoeffs),
        dpAxis_(dpAxis)
{
        // Constructor for the Gaussian PDF.

        // Check we have a valid kinematics object
        if ( ! kinematics_ ) {
                cerr<<"ERROR in LauDPDepGaussPdf::LauDPDepGaussPdf : Have not been provided with a valid DP kinematics object."<<endl;
                gSystem->Exit(EXIT_FAILURE);
        }

        // The parameters in params are the mean and the sigma (half the width) of the gaussian.
        // The last two arguments specify the range in which the PDF is defined, and the PDF
        // will be normalised w.r.t. these limits.

        mean_ = this->findParameter("mean");
        sigma_ = this->findParameter("sigma");

        if ((this->nParameters() != 2) || (mean_ == 0) || (sigma_ == 0)) {
                cerr<<"ERROR in LauDPDepGaussPdf constructor: LauDPDepGaussPdf requires 2 parameters: \"mean\" and \"sigma\"."<<endl;
                gSystem->Exit(EXIT_FAILURE);
        }

        // Cache the normalisation factor
        this->calcNorm();
}

LauDPDepGaussPdf::~LauDPDepGaussPdf() 
{
        // Destructor
}

void LauDPDepGaussPdf::calcNorm() 
{
        this->setNorm(1.0);
}

void LauDPDepGaussPdf::calcLikelihoodInfo(const LauAbscissas& abscissas)
{
        // Check that the given abscissa is within the allowed range
        if (!this->checkRange(abscissas)) {
                gSystem->Exit(EXIT_FAILURE);
        }

        // Get our abscissa
        Double_t abscissa = abscissas[0];

        // Get the up to date parameter values
        meanVal_ = mean_->value();
        sigmaVal_ = sigma_->value();

        // Find out the DP position
        Double_t dpPos(0.0);
        UInt_t nVars = this->nInputVars();
        if ( abscissas.size() == nVars+2 ) {
                Double_t m13Sq = abscissas[nVars];
                Double_t m23Sq = abscissas[nVars+1];

                if ( dpAxis_ == M12 ) {
                        dpPos = kinematics_->calcThirdMassSq(m13Sq,m23Sq);
                } else if ( dpAxis_ == M13 ) {
                        dpPos = m13Sq;
                } else if ( dpAxis_ == M23 ) {
                        dpPos = m23Sq;
                } else if ( dpAxis_ == MMIN ) {
                        dpPos = TMath::Min( m13Sq, m23Sq );
                } else if ( dpAxis_ == MMAX ) {
                        dpPos = TMath::Max( m13Sq, m23Sq );
                } else {
                        dpPos = kinematics_->distanceFromDPCentre(m13Sq,m23Sq);
                }
        }

        // Scale the parameters according to the DP position
        this->scalePars( dpPos );

        // Calculate the value of the Gaussian for the given value of the abscissa.
        Double_t arg = abscissa - meanVal_;

        Double_t exponent(0.0);
        if (TMath::Abs(sigmaVal_) > 1e-10) {
                exponent = -0.5*arg*arg/(sigmaVal_*sigmaVal_);
        }

        Double_t value = TMath::Exp(exponent);

        Double_t norm(0.0);
        Double_t scale = LauConstants::root2*sigmaVal_;
        if (TMath::Abs(sigmaVal_) > 1e-10) {
                norm = LauConstants::rootPiBy2*sigmaVal_*(TMath::Erf((this->getMaxAbscissa() - meanVal_)/scale) - TMath::Erf((this->getMinAbscissa() - meanVal_)/scale));
        }

        value /= norm;

        this->setUnNormPDFVal(value);
}

void LauDPDepGaussPdf::scalePars(Double_t dpPos)
{
        Int_t power = 1;
        for (std::vector<Double_t>::const_iterator iter = meanCoeffs_.begin(); iter != meanCoeffs_.end(); ++iter) {
                Double_t coeff = (*iter);
                meanVal_ += coeff * TMath::Power(dpPos,power);
                ++power;
        }

        power = 1;
        for (std::vector<Double_t>::const_iterator iter = sigmaCoeffs_.begin(); iter != sigmaCoeffs_.end(); ++iter) {
                Double_t coeff = (*iter);
                sigmaVal_ += coeff * TMath::Power(dpPos,power);
                ++power;
        }
}

void LauDPDepGaussPdf::calcPDFHeight(const LauKinematics* kinematics)
{
        // Get the up to date parameter values
        meanVal_ = mean_->value();

        // Find out the DP position
        Double_t dpPos(0.0);
        if ( dpAxis_ == M12 ) {
                dpPos = kinematics->getm12Sq();
        } else if ( dpAxis_ == M13 ) {
                dpPos = kinematics->getm13Sq();
        } else if ( dpAxis_ == M23 ) {
                dpPos = kinematics->getm23Sq();
        } else if ( dpAxis_ == MMIN ) {
                Double_t m13Sq = kinematics->getm13Sq();
                Double_t m23Sq = kinematics->getm23Sq();
                dpPos = TMath::Min( m13Sq, m23Sq );
        } else if ( dpAxis_ == MMAX ) {
                Double_t m13Sq = kinematics->getm13Sq();
                Double_t m23Sq = kinematics->getm23Sq();
                dpPos = TMath::Max( m13Sq, m23Sq );
        } else {
                dpPos = kinematics->distanceFromDPCentre();
        }

        // Scale the parameters according to the DP position
        this->scalePars( dpPos );

        LauAbscissas maxPoint(3);
        maxPoint[0] = meanVal_;
        maxPoint[1] = kinematics->getm13Sq();
        maxPoint[2] = kinematics->getm23Sq();

        // Calculate the PDF height for the Gaussian function.
        if (meanVal_>this->getMaxAbscissa()) {
                maxPoint[0] = this->getMaxAbscissa();
        } else if (meanVal_<this->getMinAbscissa()) {
                maxPoint[0] = this->getMinAbscissa();
        }
        this->calcLikelihoodInfo(maxPoint);

        Double_t height = this->getUnNormLikelihood();
        this->setMaxHeight(height);
}