LauLinearPdf.cc

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// Copyright University of Warwick 2006 - 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;
using std::vector;

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

#include "LauConstants.hh"
#include "LauLinearPdf.hh"

ClassImp(LauLinearPdf)


        LauLinearPdf::LauLinearPdf(const TString& theVarName, const vector<LauAbsRValue*>& params, Double_t minAbscissa, Double_t maxAbscissa) :
                LauAbsPdf(theVarName, params, minAbscissa, maxAbscissa),
                slope_(0),posflag_(kTRUE)
{
        // Constructor for the linear PDF.
        //
        // The parameters in params are the slope and y-intercept of the line.
        // The last two arguments specify the range in which the PDF is defined, and the PDF
        // will be normalised w.r.t. these limits.

        slope_ = this->findParameter("slope");

        if ((this->nParameters() != 1) || (slope_ == 0)) {
                cerr<<"Warning. LauLinearPdf requires 1 parameter: \"slope\"."<<endl;
                gSystem->Exit(EXIT_FAILURE);
        }

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

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

LauLinearPdf::LauLinearPdf(const LauLinearPdf& other) : LauAbsPdf(other.varName(), other.getParameters(), other.getMinAbscissa(), other.getMaxAbscissa())
{
        // Copy constructor
        this->setRandomFun(other.getRandomFun());
        this->calcNorm();
}

void LauLinearPdf::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
        Double_t slope = slope_->value();

        // Calculate the value of the straight line for the given value of the abscissa.
        Double_t constVal = 1.0/(this->getMaxAbscissa() - this->getMinAbscissa());
        constVal -= slope * (this->getMaxAbscissa() + this->getMinAbscissa()) * 0.5;

        Double_t value = slope*abscissa + constVal;

        // Make sure the PDF doesn't go negative
        if ( value < 0.0 ) {
                if ( posflag_ ) {
                        std::cerr << "WARNING in LauLinearPdf::calcLikelihoodInfo : The PDF is negative, setting to zero" << std::endl;
                }
                value = 0.0;
                posflag_= kFALSE;
        }

        this->setUnNormPDFVal(value);
}

void LauLinearPdf::calcNorm() 
{
        // Nothing to calculate here since the PDF is already normalised to 1
        this->setNorm(1.0);
}

void LauLinearPdf::calcPDFHeight( const LauKinematics* /*kinematics*/ )
{
        if (this->heightUpToDate()) {
                return;
        }

        // Get the up to date parameter values
        Double_t slope = slope_->value();

        // Calculate the PDF height for the straight line
        LauAbscissas maxPoint(1);
        if (slope>0.0) {
                maxPoint[0] = this->getMaxAbscissa();
        } else {
                maxPoint[0] = this->getMinAbscissa();
        }
        this->calcLikelihoodInfo(maxPoint);

        Double_t height = this->getUnNormLikelihood();

        this->setMaxHeight(height);
}