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// MARKER(update_precomp.py): autogen include statement, do not remove
#include "precompiled_sc.hxx"

// #include <math.h>

#include <tools/debug.hxx>
#include <rtl/logfile.hxx>
#include "interpre.hxx"

double const fHalfMachEps = 0.5 * ::std::numeric_limits<double>::epsilon();

// The idea how this group of gamma functions is calculated, is
// based on the Cephes library
// online http://www.moshier.net/#Cephes [called 2008-02]

/** You must ensure fA>0.0 && fX>0.0
    valid results only if fX > fA+1.0
    uses continued fraction with odd items */
double ScInterpreter::GetGammaContFraction( double fA, double fX )
{
    RTL_LOGFILE_CONTEXT_AUTHOR( aLogger, "sc", "er", "ScInterpreter::GetGammaContFraction" );

    double const fBigInv = ::std::numeric_limits<double>::epsilon();
    double const fBig = 1.0/fBigInv;
    double fCount = 0.0;
    double fNum = 0.0;  // dummy value
    double fY = 1.0 - fA;
    double fDenom = fX + 2.0-fA;
    double fPk = 0.0;   // dummy value
    double fPkm1 = fX + 1.0;
    double fPkm2 = 1.0;
    double fQk = 1.0;   // dummy value
    double fQkm1 = fDenom * fX;
    double fQkm2 = fX;
    double fApprox = fPkm1/fQkm1;
    bool bFinished = false;
    double fR = 0.0;    // dummy value
    do
    {
        fCount = fCount +1.0;
        fY = fY+ 1.0;
        fNum = fY * fCount;
        fDenom = fDenom +2.0;
        fPk = fPkm1 * fDenom  -  fPkm2 * fNum;
        fQk = fQkm1 * fDenom  -  fQkm2 * fNum;
        if (fQk != 0.0)
        {
            fR = fPk/fQk;
            bFinished = (fabs( (fApprox - fR)/fR ) <= fHalfMachEps);
            fApprox = fR;
        }
        fPkm2 = fPkm1;
        fPkm1 = fPk;
        fQkm2 = fQkm1;
        fQkm1 = fQk;
        if (fabs(fPk) > fBig)
        {
            // reduce a fraction does not change the value
            fPkm2 = fPkm2 * fBigInv;
            fPkm1 = fPkm1 * fBigInv;
            fQkm2 = fQkm2 * fBigInv;
            fQkm1 = fQkm1 * fBigInv;
        }
    } while (!bFinished && fCount<10000);
    // most iterations, if fX==fAlpha+1.0; approx sqrt(fAlpha) iterations then
    if (!bFinished)
    {
        SetError(errNoConvergence);
    }
    return fApprox;
}

/** You must ensure fA>0.0 && fX>0.0
    valid results only if fX <= fA+1.0
    uses power series */
double ScInterpreter::GetGammaSeries( double fA, double fX )
{
    RTL_LOGFILE_CONTEXT_AUTHOR( aLogger, "sc", "er", "ScInterpreter::GetGammaSeries" );
    double fDenomfactor = fA;
    double fSummand = 1.0/fA;
    double fSum = fSummand;
    int nCount=1;
    do
    {
        fDenomfactor = fDenomfactor + 1.0;
        fSummand = fSummand * fX/fDenomfactor;
        fSum = fSum + fSummand;
        nCount = nCount+1;
    } while ( fSummand/fSum > fHalfMachEps && nCount<=10000);
    // large amount of iterations will be carried out for huge fAlpha, even
    // if fX <= fAlpha+1.0
    if (nCount>10000)
    {
        SetError(errNoConvergence);
    }
    return fSum;
}

/** You must ensure fA>0.0 && fX>0.0) */
double ScInterpreter::GetLowRegIGamma( double fA, double fX )
{
    RTL_LOGFILE_CONTEXT_AUTHOR( aLogger, "sc", "er", "ScInterpreter::GetLowRegIGamma" );
    double fLnFactor = fA * log(fX) - fX - GetLogGamma(fA);
    double fFactor = exp(fLnFactor);    // Do we need more accuracy than exp(ln()) has?
    if (fX>fA+1.0)  // includes fX>1.0; 1-GetUpRegIGamma, continued fraction
        return 1.0 - fFactor * GetGammaContFraction(fA,fX);
    else            // fX<=1.0 || fX<=fA+1.0, series
        return fFactor * GetGammaSeries(fA,fX);
}

/** You must ensure fA>0.0 && fX>0.0) */
double ScInterpreter::GetUpRegIGamma( double fA, double fX )
{
    RTL_LOGFILE_CONTEXT_AUTHOR( aLogger, "sc", "er", "ScInterpreter::GetUpRegIGamma" );

    double fLnFactor= fA*log(fX)-fX-GetLogGamma(fA);
    double fFactor = exp(fLnFactor); //Do I need more accuracy than exp(ln()) has?;
    if (fX>fA+1.0) // includes fX>1.0
            return fFactor * GetGammaContFraction(fA,fX);
    else //fX<=1 || fX<=fA+1, 1-GetLowRegIGamma, series
            return 1.0 -fFactor * GetGammaSeries(fA,fX);
}

/** Gamma distribution, probability density function.
    fLambda is "scale" parameter
    You must ensure fAlpha>0.0 and fLambda>0.0 */
double ScInterpreter::GetGammaDistPDF( double fX, double fAlpha, double fLambda )
{
    RTL_LOGFILE_CONTEXT_AUTHOR( aLogger, "sc", "er", "ScInterpreter::GetGammaDistPDF" );
    if (fX <= 0.0)
        return 0.0;     // see ODFF
    else
    {
        double fXr = fX / fLambda;
        // use exp(ln()) only for large arguments because of less accuracy
        if (fXr > 1.0)
        {
            const double fLogDblMax = log( ::std::numeric_limits<double>::max());
            if (log(fXr) * (fAlpha-1.0) < fLogDblMax && fAlpha < fMaxGammaArgument)
            {
                return pow( fXr, fAlpha-1.0) * exp(-fXr) / fLambda / GetGamma(fAlpha);
            }
            else
            {
                return exp( (fAlpha-1.0) * log(fXr) - fXr - log(fLambda) - GetLogGamma(fAlpha));
            }
        }
        else    // fXr near to zero
        {
            if (fAlpha<fMaxGammaArgument)
            {
                return pow( fXr, fAlpha-1.0) * exp(-fXr) / fLambda / GetGamma(fAlpha);
            }
            else
            {
                return pow( fXr, fAlpha-1.0) * exp(-fXr) / fLambda / exp( GetLogGamma(fAlpha));
            }
        }
    }
}

/** Gamma distribution, cumulative distribution function.
    fLambda is "scale" parameter
    You must ensure fAlpha>0.0 and fLambda>0.0 */
double ScInterpreter::GetGammaDist( double fX, double fAlpha, double fLambda )
{
    RTL_LOGFILE_CONTEXT_AUTHOR( aLogger, "sc", "er", "ScInterpreter::GetGammaDist" );
    if (fX <= 0.0)
        return 0.0;
    else
        return GetLowRegIGamma( fAlpha, fX / fLambda);
}