G4FPYSamplingOps Class Reference

#include <G4FPYSamplingOps.hh>

Collaboration diagram for G4FPYSamplingOps:

Public Member Functions
	G4FPYSamplingOps (void)
	G4FPYSamplingOps (G4int Verbosity)
G4int	G4SampleIntegerGaussian (G4double Mean, G4double StdDev)
G4int	G4SampleIntegerGaussian (G4double Mean, G4double StdDev, G4FFGEnumerations::GaussianRange Range)
G4double	G4SampleGaussian (G4double Mean, G4double StdDev)
G4double	G4SampleGaussian (G4double Mean, G4double StdDev, G4FFGEnumerations::GaussianRange Range)
G4double	G4SampleUniform (void)
G4double	G4SampleUniform (G4double Lower, G4double Upper)
G4double	G4SampleWatt (G4int WhatIsotope, G4FFGEnumerations::FissionCause WhatCause, G4double WhatEnergy)
void	G4SetVerbosity (G4int WhatVerbosity)
	~G4FPYSamplingOps (void)

Protected Member Functions
void	Initialize (void)
G4bool	CheckAndSetParameters (void)
void	EvaluateWattConstants (void)
G4double	SampleGaussian (void)
void	ShiftParameters (G4FFGEnumerations::GaussianReturnType Type)

Protected Attributes
G4double	Mean_
G4double	StdDev_
G4ShiftedGaussian *	ShiftedGaussianValues_
G4int	Verbosity_
WattSpectrumConstants *	WattConstants_
CLHEP::HepRandomEngine *	RandomEngine_
G4bool	NextGaussianIsStoredInMemory_
G4double	GaussianOne_
G4double	GaussianTwo_
G4double	Tolerance_

Detailed Description

G4FPYSamplingOps performs all the uniform and Gaussian distribution sampling operations

Definition at line 52 of file G4FPYSamplingOps.hh.

Constructor & Destructor Documentation

G4FPYSamplingOps::G4FPYSamplingOps

(

void

)

Default constructor

• Usage: No arguments required
• Notes:

Definition at line 49 of file G4FPYSamplingOps.cc.

{
    // Set the default verbosity
    Verbosity_ = G4FFGDefaultValues::Verbosity;
    
    // Initialize the class
    Initialize();
}

Here is the call graph for this function:

G4FPYSamplingOps::G4FPYSamplingOps

(

G4int

Verbosity

)

Overloaded constructor

• Usage:
  • Verbosity: Verbosity level
• Notes:

Definition at line 59 of file G4FPYSamplingOps.cc.

{
    // Set the default verbosity
    Verbosity_ = Verbosity;
    
    // Initialize the class
    Initialize();
}

Here is the call graph for this function:

G4FPYSamplingOps::~G4FPYSamplingOps

(

void

)

Default deconstructor.

Definition at line 678 of file G4FPYSamplingOps.cc.

{
G4FFG_FUNCTIONENTER__

    delete ShiftedGaussianValues_;
    delete WattConstants_;
    
G4FFG_FUNCTIONLEAVE__
}

Member Function Documentation

G4bool G4FPYSamplingOps::CheckAndSetParameters ( void  )

protected

Check to see if the user requested parameters have already been calculated. If they have, it recalls the stored parameters and sets them as the current values.

Definition at line 341 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    G4double ShiftedMean = ShiftedGaussianValues_->G4FindShiftedMean(Mean_, StdDev_);
    if(ShiftedMean == 0)
    {
G4FFG_SAMPLING_FUNCTIONLEAVE__
        return FALSE;
    }

    Mean_ = ShiftedMean;

G4FFG_SAMPLING_FUNCTIONLEAVE__
    return TRUE;
}

Here is the call graph for this function:

Here is the caller graph for this function:

void G4FPYSamplingOps::EvaluateWattConstants ( void  )

protected

Evaluates the constants that are required for the Watt fission spectrum sampling.

Definition at line 359 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    G4double A, K;
    A = K = 0;
    // Use the default values if IsotopeIndex is not reset
    G4int IsotopeIndex = 0;

    if(WattConstants_->Cause == G4FFGEnumerations::SPONTANEOUS)
    {
        // Determine if the isotope requested exists in the lookup tables
        for(G4int i = 0; SpontaneousWattIsotopesIndex[i] != -1; i++)
        {
            if(SpontaneousWattIsotopesIndex[i] ==
                    WattConstants_->Product)
            {
                IsotopeIndex = i;

                break;
            }
        }

        // Get A and B
        A = SpontaneousWattConstants[IsotopeIndex][0];
        WattConstants_->B = SpontaneousWattConstants[IsotopeIndex][1];
    } else if (WattConstants_->Cause == G4FFGEnumerations::NEUTRON_INDUCED)
    {
        // Determine if the isotope requested exists in the lookup tables
        for(G4int i = 0; NeutronInducedWattIsotopesIndex[i] != -1; i++)
        {
            if(NeutronInducedWattIsotopesIndex[i] == WattConstants_->Product)
            {
                IsotopeIndex = i;
                break;
            }
        }

        // Determine the Watt fission spectrum constants based on the energy of
        // the incident neutron
        if(WattConstants_->Energy == G4FFGDefaultValues::ThermalNeutronEnergy)
        {
            A = NeutronInducedWattConstants[IsotopeIndex][0][0];
            WattConstants_->B = NeutronInducedWattConstants[IsotopeIndex][0][1];
        } else if (WattConstants_->Energy > 14.0 * CLHEP::MeV)
        {
            G4Exception("G4FPYSamplingOps::G4SampleWatt()",
                        "Incident neutron energy above 14 MeV requested.",
                        JustWarning,
                        "Using Watt fission constants for 14 Mev.");

            A = NeutronInducedWattConstants[IsotopeIndex][2][0];
            WattConstants_->B = NeutronInducedWattConstants[IsotopeIndex][2][1];
        } else
        {
            G4int EnergyIndex = 0;
            G4double EnergyDifference = 0;
            G4double RangeDifference, ConstantDifference;

            for(G4int i = 1; IncidentEnergyBins[i] != -1; i++)
            {
                if(WattConstants_->Energy <= IncidentEnergyBins[i])
                {
                    EnergyIndex = i;
                    EnergyDifference = IncidentEnergyBins[EnergyIndex] - WattConstants_->Energy;
                    if(EnergyDifference != 0)
                    {
                        std::ostringstream Temp;
                        Temp << "Incident neutron energy of ";
                        Temp << WattConstants_->Energy << " MeV is not ";
                        Temp << "explicitly listed in the data tables";
//                        G4Exception("G4FPYSamplingOps::G4SampleWatt()",
//                                    Temp.str().c_str(),
//                                    JustWarning,
//                                    "Using linear interpolation.");
                    }
                    break;
                }
            }

            RangeDifference = IncidentEnergyBins[EnergyIndex] - IncidentEnergyBins[EnergyIndex - 1];

            // Interpolate the value for 'a'
            ConstantDifference =
                NeutronInducedWattConstants[IsotopeIndex][EnergyIndex][0] -
                NeutronInducedWattConstants[IsotopeIndex]
                                           [EnergyIndex - 1][0];
            A = (EnergyDifference / RangeDifference) * ConstantDifference +
                NeutronInducedWattConstants[IsotopeIndex]
                                           [EnergyIndex - 1][0];

            // Interpolate the value for 'b'
            ConstantDifference =
                NeutronInducedWattConstants[IsotopeIndex][EnergyIndex][1] -
                NeutronInducedWattConstants[IsotopeIndex]
                                           [EnergyIndex - 1][1];
            WattConstants_->B =
                (EnergyDifference / RangeDifference) * ConstantDifference +
                NeutronInducedWattConstants[IsotopeIndex]
                                           [EnergyIndex - 1][1];
        }
    } else
    {
        // Produce an error since an unsupported fission type was requested and
        // abort the current run
        G4String Temp = "Watt fission spectra data not available for ";
        if(WattConstants_->Cause == G4FFGEnumerations::PROTON_INDUCED)
        {
            Temp += "proton induced fission.";
        } else if(WattConstants_->Cause == G4FFGEnumerations::GAMMA_INDUCED)
        {
            Temp += "gamma induced fission.";
        } else
        {
            Temp += "!Warning! unknown cause.";
        }
        G4Exception("G4FPYSamplingOps::G4SampleWatt()",
                    Temp,
                    RunMustBeAborted,
                    "Fission events will not be sampled in this run.");
    }

    // Calculate the constants
    K = 1 + (WattConstants_->B / (8.0 * A));
    WattConstants_->L = (K + G4Pow::GetInstance()->powA((K * K - 1), 0.5)) / A;
    WattConstants_->M = A * WattConstants_->L - 1;

G4FFG_SAMPLING_FUNCTIONLEAVE__
}

Here is the call graph for this function:

Here is the caller graph for this function:

G4double G4FPYSamplingOps::G4SampleGaussian	(	G4double	Mean,
		G4double	StdDev
	)

Returns a double value taken from a Gaussian distribution about Mean and with a standard deviation of StdDev.

• Usage:
  • Mean: Mean about which the Gaussian distribution will be sampled
  • StdDev: Standard deviation of the Gaussian distribution. 68.3% of the values will lie within the first standard deviation, 95.4% within the second standard deviation, etc...
• Notes:

Definition at line 92 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    // Determine if the parameters have changed
    G4bool ParametersChanged = (Mean_ != Mean || StdDev_ != StdDev);
    if(ParametersChanged == TRUE)
    {
        // Set the new values if the parameters have changed
        NextGaussianIsStoredInMemory_ = FALSE;

        Mean_ = Mean;
        StdDev_ = StdDev;
    }
    
    G4double Sample = SampleGaussian();
    
G4FFG_SAMPLING_FUNCTIONLEAVE__
    return Sample;
}

Here is the call graph for this function:

Here is the caller graph for this function:

G4double G4FPYSamplingOps::G4SampleGaussian	(	G4double	Mean,
		G4double	StdDev,
		G4FFGEnumerations::GaussianRange	Range
	)

Returns a double value taken from a Gaussian distribution about Mean and with a standard deviation of StdDev.

• Usage:
  • Mean: Mean about which the Gaussian distribution will be sampled
  • StdDev: Standard deviation of the Gaussian distribution. 68.3% of the values will lie within the first standard deviation, 95.4% within the second standard deviation, etc...
  • Range: POSITIVE or ALL
• Notes:

Definition at line 115 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    if(Range == G4FFGEnumerations::ALL)
    {
        // Call the overloaded function
        G4double Sample = G4SampleGaussian(Mean, StdDev);
        
G4FFG_SAMPLING_FUNCTIONLEAVE__
        return Sample;
    }

    // Determine if the parameters have changed
    G4bool ParametersChanged = (Mean_ != Mean ||
                                StdDev_ != StdDev);
    if(ParametersChanged == TRUE)
    {
        if(Mean <= 0)
        {
            std::ostringstream Temp;
            Temp << "Mean value of " << Mean << " out of range";
            G4Exception("G4FPYGaussianOps::G4SampleIntegerGaussian()",
            Temp.str().c_str(),
            JustWarning,
            "A value of '0' will be used instead.");

G4FFG_SAMPLING_FUNCTIONLEAVE__
            return 0;
        }

        // Set the new values if the parameters have changed and then perform
        // the shift
        Mean_ = Mean;
        StdDev_ = StdDev;

        ShiftParameters(G4FFGEnumerations::DOUBLE);
    }

    // Sample the Gaussian distribution
    G4double Rand;
    do
    {
        Rand = SampleGaussian();
    } while(Rand < 0); // Loop checking, 11.05.2015, T. Koi

G4FFG_SAMPLING_FUNCTIONLEAVE__
    return Rand;
}

Here is the call graph for this function:

G4int G4FPYSamplingOps::G4SampleIntegerGaussian	(	G4double	Mean,
		G4double	StdDev
	)

Returns an integer value taken from a Gaussian distribution. This overloaded version assumes that the range is not restricted to positive values only.

• Usage:
  • Mean: Mean about which the Gaussian distribution will be sampled
  • StdDev: Standard deviation of the Gaussian distribution. 68.3% of the values will lie within the first standard deviation, 95.4% within the second standard deviation, etc...
• Notes:

Definition at line 168 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    // Determine if the parameters have changed
    G4bool ParametersChanged = (Mean_ != Mean || StdDev_ != StdDev);
    if(ParametersChanged == TRUE)
    {
        // Set the new values if the parameters have changed
        NextGaussianIsStoredInMemory_ = FALSE;

        Mean_ = Mean;
        StdDev_ = StdDev;
    }

    // Return the sample integer value
    G4int Sample = (G4int)(std::floor(SampleGaussian()));

G4FFG_SAMPLING_FUNCTIONLEAVE__
    return Sample;
}

Here is the call graph for this function:

Here is the caller graph for this function:

G4int G4FPYSamplingOps::G4SampleIntegerGaussian	(	G4double	Mean,
		G4double	StdDev,
		G4FFGEnumerations::GaussianRange	Range
	)

Returns an integer value taken from a Gaussian distribution about Mean and with a standard deviation of StdDev.

• Usage:
  • Mean: Mean about which the Gaussian distribution will be sampled
  • StdDev: Standard deviation of the Gaussian distribution. 68.3% of the values will lie within the first standard deviation, 95.4% within the second standard deviation, etc...
  • Range: POSITIVE or ALL
• Notes:

Definition at line 192 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    if(Range == G4FFGEnumerations::ALL)
    {
        // Call the overloaded function
        G4int Sample = G4SampleIntegerGaussian(Mean, StdDev);

G4FFG_SAMPLING_FUNCTIONLEAVE__
        return Sample;
    } else
    {
        // ParameterShift() locks up if the mean is less than 1.
        std::ostringstream Temp;
        if(Mean < 1)
        {
        //    Temp << "Mean value of " << Mean << " out of range";
        //    G4Exception("G4FPYGaussianOps::G4SampleIntegerGaussian()",
        //                Temp.str().c_str(),
        //                JustWarning,
        //                "A value of '0' will be used instead.");

        //    return 0;
        }
        
        if(Mean / StdDev < 2)
        {
            //Temp << "Non-ideal conditions:\tMean:" << Mean << "\tStdDev: "
            //        << StdDev;
            //G4Exception("G4FPYGaussianOps::G4SampleIntegerGaussian()",
            //            Temp.str().c_str(),
            //            JustWarning,
            //            "Results not guaranteed: Consider tightening the standard deviation");
        }

        // Determine if the parameters have changed
        G4bool ParametersChanged = (Mean_ != Mean ||
                                    StdDev_ != StdDev);
        if(ParametersChanged == TRUE)
        {
            // Set the new values if the parameters have changed and then perform
            // the shift
            Mean_ = Mean;
            StdDev_ = StdDev;

            ShiftParameters(G4FFGEnumerations::INT);
        }

        G4int RandInt;
        // Sample the Gaussian distribution - only non-negative values are
        // accepted
        do
        {
            RandInt = (G4int)floor(SampleGaussian());
        } while (RandInt < 0); // Loop checking, 11.05.2015, T. Koi

G4FFG_SAMPLING_FUNCTIONLEAVE__
        return RandInt;
    }
}

Here is the call graph for this function:

G4double G4FPYSamplingOps::G4SampleUniform

(

void

)

Returns a double value evenly distributed in the range (0, 1].

• Usage: No arguments required
• Notes:

Definition at line 257 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    G4double Sample = RandomEngine_->flat();
    
G4FFG_SAMPLING_FUNCTIONLEAVE__
    return Sample;
}

Here is the call graph for this function:

Here is the caller graph for this function:

G4double G4FPYSamplingOps::G4SampleUniform	(	G4double	Lower,
		G4double	Upper
	)

Returns a double value evenly distributed in the range (Lower, Upper].

• Usage:
  • Lower: Lower bounds of the distribution
  • Upper: Upper bounds of the distribution
• Notes:

Definition at line 268 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    // Calculate the difference
    G4double Difference = Upper - Lower;

    // Scale appropriately and return the value
    G4double Sample = G4SampleUniform() * Difference + Lower;

G4FFG_SAMPLING_FUNCTIONLEAVE__
    return Sample;
}

Here is the call graph for this function:

G4double G4FPYSamplingOps::G4SampleWatt	(	G4int	WhatIsotope,
		G4FFGEnumerations::FissionCause	WhatCause,
		G4double	WhatEnergy
	)

Samples the Watt fission spectrum for the selected isotope, using an algorithm adopted from Ref. 1

• Usage:
  • WhatIsotope: The isotope that is to be sampled
  • WhatCause: The cause of the isotope to be sampled
  • WhatEnergy: The energy, in MeV of the incident particle
• Notes:
  • All variables needed for this function are grouped together in WattConstants_.

Definition at line 284 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    // Determine if the parameters are different
    //TK modified 131108 
    //if(WattConstants_->Product != WhatIsotope
    if(WattConstants_->Product != WhatIsotope/10
            || WattConstants_->Cause != WhatCause
            || WattConstants_->Energy!= WhatEnergy )
    {
        // If the parameters are different or have not yet been defined then we
        // need to re-evaluate the constants
        //TK modified 131108 
        //WattConstants_->Product = WhatIsotope;
        WattConstants_->Product = WhatIsotope/10;
        WattConstants_->Cause = WhatCause;
        WattConstants_->Energy = WhatEnergy;

        EvaluateWattConstants();
    }

    G4double X = -G4Log(G4SampleUniform());
    G4double Y = -G4Log(G4SampleUniform());
    G4int icounter=0;
    G4int icounter_max=1024;
    while(G4Pow::GetInstance()->powN(Y - WattConstants_->M*(X + 1), 2)
            > WattConstants_->B * WattConstants_->L * X) // Loop checking, 11.05.2015, T. Koi
    {
        icounter++;
        if ( icounter > icounter_max ) {
           G4cout << "Loop-counter exceeded the threshold value at " << __LINE__ << "th line of " << __FILE__ << "." << G4endl;
           break;
        }
        X = -G4Log(G4SampleUniform());
        Y = -G4Log(G4SampleUniform());
    }

G4FFG_SAMPLING_FUNCTIONLEAVE__
    return WattConstants_->L * X;
}

Here is the call graph for this function:

Here is the caller graph for this function:

void G4FPYSamplingOps::G4SetVerbosity

(

G4int

WhatVerbosity

)

Sets the verbosity levels

• Usage:
  • WhichVerbosity: Combination of levels
• Notes:
  • SILENT: All verbose output is repressed
  • UPDATES: Only high-level internal changes are reported
  • DAUGHTER_INFO: Displays information about daughter product sampling
  • NEUTRON_INFO: Displays information about neutron sampling
  • GAMMA_INFO: Displays information about gamma sampling
  • ALPHA_INFO: Displays information about alpha sampling
  • MOMENTUM_INFO: Displays information about momentum balancing
  • EXTRAPOLATION_INTERPOLATION_INFO: Displays information about any data extrapolation or interpolation that occurs
  • DEBUG: Reports program flow as it steps through functions
  • PRINT_ALL: Displays any and all output

Definition at line 329 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    Verbosity_ = Verbosity;
    
    ShiftedGaussianValues_->G4SetVerbosity(Verbosity_);

G4FFG_SAMPLING_FUNCTIONLEAVE__
}

Here is the call graph for this function:

Here is the caller graph for this function:

void G4FPYSamplingOps::Initialize ( void  )

protected

Initialize is a common function called by all constructors.

Definition at line 69 of file G4FPYSamplingOps.cc.

{
G4FFG_FUNCTIONENTER__

    // Get the pointer to the random number generator
    //RandomEngine_ = CLHEP::HepRandom::getTheEngine();
    RandomEngine_ = G4Random::getTheEngine();

    // Initialize the data members
    ShiftedGaussianValues_ = new G4ShiftedGaussian;
    Mean_ = 0;
    StdDev_ = 0;
    NextGaussianIsStoredInMemory_ = FALSE;
    GaussianOne_ = 0;
    GaussianTwo_ = 0;
    Tolerance_ = 0.000001;
    WattConstants_ = new WattSpectrumConstants;
    WattConstants_->Product = 0;

G4FFG_FUNCTIONLEAVE__
}

Here is the caller graph for this function:

G4double G4FPYSamplingOps::SampleGaussian ( void  )

protected

Samples a Gaussian distribution defined by the internal class variables NewMean_ and NewStdDev_.

Definition at line 490 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    if(NextGaussianIsStoredInMemory_ == TRUE)
    {
        NextGaussianIsStoredInMemory_ = FALSE;

G4FFG_SAMPLING_FUNCTIONLEAVE__
        return GaussianTwo_;
    }

    // Define the variables to be used
    G4double Radius;
    G4double MappingFactor;

    // Sample from the unit circle (21.4% rejection probability)
    do
    {
        GaussianOne_ = 2.0 * G4SampleUniform() - 1.0;
        GaussianTwo_ = 2.0 * G4SampleUniform() - 1.0;
        Radius = GaussianOne_*GaussianOne_ + GaussianTwo_*GaussianTwo_;
    } while (Radius > 1.0); // Loop checking, 11.05.2015, T. Koi

    // Translate the values to Gaussian space
    MappingFactor = std::sqrt(-2.0*G4Log(Radius)/Radius) * StdDev_;
    GaussianOne_ = Mean_ + GaussianOne_*MappingFactor;
    GaussianTwo_ = Mean_ + GaussianTwo_*MappingFactor;

    // Set the flag that a value is now stored in memory
    NextGaussianIsStoredInMemory_ = TRUE;

G4FFG_SAMPLING_FUNCTIONLEAVE__
    return GaussianOne_;
}

Here is the call graph for this function:

Here is the caller graph for this function:

void G4FPYSamplingOps::ShiftParameters ( G4FFGEnumerations::GaussianReturnType  Type )

protected

Sets the mean and standard deviation of the Gaussian distribution sampled by this class when POSITIVE values are requested. ShiftMean() performs two different operations based on the requested data type.

• INTEGER: Iteratively searches for an adjusted mean that produces the same result as the mean requested by the implementor. In this instance the standard deviation is not adjusted.
• DOUBLE: Adjusts the standard deviation of the Gaussian distribution so that the first seven standard deviations occur are all positive. The chance that a negative value will result using this method is 2.56E^-12

Definition at line 527 of file G4FPYSamplingOps.cc.

{
G4FFG_SAMPLING_FUNCTIONENTER__

    // Set the flag that any second value stored is no longer valid
    NextGaussianIsStoredInMemory_ = FALSE;

    // Check if the requested parameters have already been calculated
    if(CheckAndSetParameters() == TRUE)
    {
G4FFG_SAMPLING_FUNCTIONLEAVE__
        return;
    }

    // If the requested type is INT, then perform an iterative refinement of the
    // mean that is going to be sampled
    if(Type == G4FFGEnumerations::INT)
    {
        // Return if the mean is greater than 7 standard deviations away from 0
        // since there is essentially 0 probability that a sampled number will
        // be less than 0
        if(Mean_ > 7 * StdDev_)
        {
G4FFG_SAMPLING_FUNCTIONLEAVE__
            return;
        }
        // Variables that contain the area and weighted area information for
        // calculating the statistical mean of the Gaussian distribution when
        // converted to a step function
        G4double ErfContainer, AdjustedErfContainer, Container;

        // Variables that store lower and upper bounds information
        G4double LowErf, HighErf;

        // Values for determining the convergence of the solution
        G4double AdjMean = Mean_;
        G4double Delta = 1.0;
        G4bool HalfDelta = false;
        G4bool ToleranceCheck = false;


        // Normalization constant for use with erf()
        const G4double Normalization = StdDev_ * std::sqrt(2.0);

        // Determine the upper limit of the estimates
        const G4int UpperLimit = (G4int) std::ceil(Mean_ + 9 * StdDev_);

        // Calculate the integral of the Gaussian distribution

        G4int icounter=0;
        G4int icounter_max=1024;
        do
        {
            icounter++;
            if ( icounter > icounter_max ) {
           G4cout << "Loop-counter exceeded the threshold value at " << __LINE__ << "th line of " << __FILE__ << "." << G4endl;
               break;
            }
            // Set the variables
            ErfContainer = 0;
            AdjustedErfContainer = 0;

            // Calculate the area and weighted area
            for(G4int i = 0; i <= UpperLimit; i++)
            {
                // Determine the lower and upper bounds
                LowErf = ((AdjMean - i) / Normalization);
                HighErf = ((AdjMean - (i + 1.0)) / Normalization);

                // Correct the bounds for how they lie on the x-axis with
                // respect to the mean
                if(LowErf <= 0)
                {
                    LowErf *= -1;
                    HighErf *= -1;
                    //Container = (erf(HighErf) - erf(LowErf))/2.0;
                    #if defined WIN32-VC
            Container = (CLHEP::HepStat::erf(HighErf) - CLHEP::HepStat::erf(LowErf))/2.0;
                    #else
                        Container = (erf(HighErf) - erf(LowErf))/2.0;
                    #endif              
                } else if (HighErf < 0)
                {
                    HighErf *= -1;

                    //Container = (erf(HighErf) + erf(LowErf))/2.0;
                    #if defined WIN32-VC
                Container = (CLHEP::HepStat::erf(HighErf) + CLHEP::HepStat::erf(LowErf))/2.0;
                    #else
                        Container = (erf(HighErf) + erf(LowErf))/2.0;
                    #endif
                } else
                {
                    //Container = (erf(LowErf) - erf(HighErf))/2.0;
                    #if defined WIN32-VC
            Container = (CLHEP::HepStat::erf(LowErf) - CLHEP::HepStat::erf(HighErf))/2.0;
                    #else
                        Container = (erf(LowErf) - erf(HighErf))/2.0;
                    #endif
                }

                #if defined WIN32-VC
                //TK modified to avoid problem caused by QNAN
            if ( Container != Container) Container = 0;
                #endif

                // Add up the weighted area
                ErfContainer += Container;
                AdjustedErfContainer += Container * i;
            }

            // Calculate the statistical mean
            Container = AdjustedErfContainer / ErfContainer;

            // Is it close enough to what we want?
            ToleranceCheck = (std::fabs(Mean_ - Container) < Tolerance_);
            if(ToleranceCheck == TRUE)
            {
                break;
            }

            // Determine the step size
            if(HalfDelta == TRUE)
            {
                Delta /= 2;
            }

            // Step in the appropriate direction
            if(Container > Mean_)
            {
                AdjMean -= Delta;
            } else
            {
                HalfDelta = TRUE;
                AdjMean += Delta;
            }
        } while(TRUE); // Loop checking, 11.05.2015, T. Koi

        ShiftedGaussianValues_->G4InsertShiftedMean(AdjMean, Mean_, StdDev_);
        Mean_ = AdjMean;
    } else if(Mean_ / 7 < StdDev_)
    {
        // If the requested type is double, then just re-define the standard
        // deviation appropriately - chances are approximately 2.56E-12 that
        // the value will be negative using this sampling scheme
        StdDev_ = Mean_ / 7;
    }
    
G4FFG_SAMPLING_FUNCTIONLEAVE__
}

Here is the call graph for this function:

Here is the caller graph for this function:

Member Data Documentation

G4double G4FPYSamplingOps::GaussianOne_

protected

Contains the first of the two paired random numbers from the Gaussian distribution sampling.

Definition at line 203 of file G4FPYSamplingOps.hh.

G4double G4FPYSamplingOps::GaussianTwo_

protected

Contains the second of the two paired random numbers from the Gaussian distribution sampling.

Definition at line 207 of file G4FPYSamplingOps.hh.

G4double G4FPYSamplingOps::Mean_

protected

Mean for sampling a Gaussian distribution

Definition at line 177 of file G4FPYSamplingOps.hh.

G4bool G4FPYSamplingOps::NextGaussianIsStoredInMemory_

protected

Declares whether the second paired random number has been already returned.

Definition at line 199 of file G4FPYSamplingOps.hh.

CLHEP::HepRandomEngine* G4FPYSamplingOps::RandomEngine_

protected

Pointer to the CLHEP random number generator.

Definition at line 193 of file G4FPYSamplingOps.hh.

G4ShiftedGaussian* G4FPYSamplingOps::ShiftedGaussianValues_

protected

Structure chain that contains the all the previous values used for sampling a Gaussian distribution

Definition at line 183 of file G4FPYSamplingOps.hh.

G4double G4FPYSamplingOps::StdDev_

protected

Standard deviation for sampling a GaussianDistribution

Definition at line 179 of file G4FPYSamplingOps.hh.

G4double G4FPYSamplingOps::Tolerance_

protected

Defines the tolerance that ShiftParameters() must match.

Definition at line 209 of file G4FPYSamplingOps.hh.

G4int G4FPYSamplingOps::Verbosity_

protected

Verbosity level

Definition at line 185 of file G4FPYSamplingOps.hh.

WattSpectrumConstants* G4FPYSamplingOps::WattConstants_

protected

Structure that contains the values for sampling the Watt fission spectrum

Definition at line 189 of file G4FPYSamplingOps.hh.

---

The documentation for this class was generated from the following files:

• source/geant4.10.03.p03/source/processes/hadronic/models/particle_hp/include/G4FPYSamplingOps.hh
• source/geant4.10.03.p03/source/processes/hadronic/models/particle_hp/src/G4FPYSamplingOps.cc