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ModelMath.cpp
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219 lines (186 loc) · 7.57 KB
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//---------------------------------------------------------------------------
#include <stdlib.h>
#include <math.h>
#include <gsl/gsl_rng.h>
#include <gsl/gsl_randist.h>
#include <string.h>
#include "ModelMath.h"
#include "Messages.h"
gsl_rng *clModelMath::randgen = gsl_rng_alloc(gsl_rng_mt19937);
/////////////////////////////////////////////////////////////////////////////
// GetRand()
/////////////////////////////////////////////////////////////////////////////
float clModelMath::GetRand() {
return (gsl_rng_uniform(randgen));
}
/////////////////////////////////////////////////////////////////////////////
// CalcPointValue()
//////////////////////////////////////////////////////////////////////////////
float clModelMath::CalcPointValue(float fX, float fSlope, float fIntercept) {
return ( fSlope * fX + fIntercept );
}
//---------------------------------------------------------------------------
/////////////////////////////////////////////////////////////////////////////
// CalculateBasalArea()
/////////////////////////////////////////////////////////////////////////////
float clModelMath::CalculateBasalArea(float fDbh) {
float SQ_M_PER_SQ_CM = 0.0001; //conversion factor for sq cm to sq m
if ( fDbh <= 0 )
{ //throw error
modelErr stcErr;
stcErr.sFunction = "clModelMath::CalculateBasalArea" ;
stcErr.sMoreInfo = "DBH is not a positive number.";
stcErr.iErrorCode = BAD_DATA;
throw( stcErr );
}
return ( pow( fDbh * 0.5, 2 ) * M_PI * SQ_M_PER_SQ_CM );
}
//---------------------------------------------------------------------------
/////////////////////////////////////////////////////////////////////////////
// Round()
/////////////////////////////////////////////////////////////////////////////
float clModelMath::Round(float fNumber, int iNumDigits) {
double fIntegerPart, //we'll split a float number into integer and
//fractional parts - this is the integer part
fBigNumber; //for calculations
//Take the number to round and multiply by 10^ number of digits +1
fBigNumber = fNumber * pow( 10.0, ( float )( iNumDigits + 1 ) );
//Adjust the number depending on whether or not the original number was neg
if ( fNumber < 0.0 )
fBigNumber -= 5.0;
else
fBigNumber += 5.0;
fBigNumber /= 10.0;
//Split off the integer part - discard fractional part
modf( fBigNumber, & fIntegerPart );
//Divide by 10 ^ num digits to get our number back
return fIntegerPart / pow( 10.0, ( float )iNumDigits );
}
//---------------------------------------------------------------------------
/////////////////////////////////////////////////////////////////////////////
// RandomRound()
/////////////////////////////////////////////////////////////////////////////
int clModelMath::RandomRound(float fNumber) {
double fIntegerPart = 0, //we'll split a float number into integer and
//fractional parts - this is the integer part
fFractionalPart = 0; //fractional part
//Split the number into integer and fractional part
fFractionalPart = modf( fNumber, & fIntegerPart );
return ( GetRand() <= fFractionalPart ? ( int )( fIntegerPart + 1 ) : ( int )fIntegerPart );
}
//---------------------------------------------------------------------------
/////////////////////////////////////////////////////////////////////////////
// CalculateWeibullFunction()
/////////////////////////////////////////////////////////////////////////////
float clModelMath::CalculateWeibullFunction(float fDispersal, float fTheta,
float fDistance) {
//prevent underflow
float fTemp = -fDispersal * pow( fDistance , fTheta );
if (fTemp < -50) return 0;
else return exp(fTemp);
}
//---------------------------------------------------------------------------
/////////////////////////////////////////////////////////////////////////////
// CalculateLognormalFunction()
/////////////////////////////////////////////////////////////////////////////
float clModelMath::CalculateLognormalFunction(float fX0, float fXb,
float fDistance) {
//Error if either fX0 or fXb is zero
if ( 0 == fXb )
{
modelErr stcErr;
stcErr.iErrorCode = BAD_DATA;
stcErr.sFunction = "clModelMath::CalculateLognormalFunction" ;
stcErr.sMoreInfo = "Xb cannot be zero.";
throw( stcErr );
}
if (0 >= fX0 || 0 > fDistance) {
modelErr stcErr;
stcErr.iErrorCode = BAD_DATA;
stcErr.sFunction = "clModelMath::CalculateLognormalFunction" ;
stcErr.sMoreInfo = "X0 and distance must be greater than zero.";
throw( stcErr );
}
if (fDistance == 0) return 0.0;
//prevent underflow
float fTemp = -0.5 * pow( ( log( ( fDistance ) / fX0 ) / fXb ), 2 );
if (fTemp < -50) return 0;
else return exp(fTemp);
}
/////////////////////////////////////////////////////////////////////////////
// PoissonRandomDraw()
/////////////////////////////////////////////////////////////////////////////
int clModelMath::PoissonRandomDraw(float fLambda) {
return (gsl_ran_poisson(randgen, fLambda));
}
/////////////////////////////////////////////////////////////////////////////
// LognormalRandomDraw()
/////////////////////////////////////////////////////////////////////////////
float clModelMath::LognormalRandomDraw(float fMean, float fStdDev) {
return (gsl_ran_lognormal(randgen, fMean, fStdDev));
}
/////////////////////////////////////////////////////////////////////////////
// NegBinomialRandomDraw()
/////////////////////////////////////////////////////////////////////////////
int clModelMath::NegBinomialRandomDraw(float fMean, float fClumping) {
double fPDF, fCDF;
float fRand = GetRand();
int iCount = 0;
fPDF = pow((fClumping/(fClumping+fMean)), fClumping); //term for PDF for zero counts
fCDF = fPDF;
while (fRand > fCDF) {
iCount++;
//Uses recursive eqn. from Hilborn and Mangel pg 87
fPDF = ((iCount+fClumping-1)/iCount)*(fMean/(fClumping+fMean))*fPDF;
fCDF = fCDF + fPDF;
}
return iCount;
}
/////////////////////////////////////////////////////////////////////////////
// NormalRandomDraw()
/////////////////////////////////////////////////////////////////////////////
float clModelMath::NormalRandomDraw(float fStdDev) {
return gsl_ran_gaussian(randgen, fStdDev);
}
/////////////////////////////////////////////////////////////////////////////
// AddBarkToDBH()
/////////////////////////////////////////////////////////////////////////////
float clModelMath::AddBarkToDBH(float fDIB, float fA, float fB, float fC) {
if (fDIB <= 0) {
modelErr stcErr;
stcErr.sFunction = "clModelMath::AddBarkToDBH";
stcErr.sMoreInfo = "DBH is not a positive number.";
stcErr.iErrorCode = BAD_DATA;
throw( stcErr );
}
if (fDIB >= 1E18) {
modelErr stcErr;
stcErr.sFunction = "clModelMath::AddBarkToDBH";
stcErr.sMoreInfo = "DBH is too large.";
stcErr.iErrorCode = BAD_DATA;
throw( stcErr );
}
return (fA + (fB * fDIB) + (fC * (fDIB * fDIB)));
}
/////////////////////////////////////////////////////////////////////////////
// InverseGaussianRandomDraw()
/////////////////////////////////////////////////////////////////////////////
float clModelMath::InverseGaussianRandomDraw(float fMu, float fLambda) {
float n, v, w, c, x, p;
n = gsl_ran_gaussian(randgen, 1);
v = n*n;
w = fMu*v;
c = fMu/(2.0*fLambda);
x = fMu + c*(w - sqrt(w*(4.0*fLambda + w)));
p = fMu/(fMu + x);
if (p > gsl_rng_uniform(randgen))
return (x);
else
return (fMu*fMu/x);
}
/////////////////////////////////////////////////////////////////////////////
// GammaRandomDraw()
/////////////////////////////////////////////////////////////////////////////
float clModelMath::GammaRandomDraw(float fMean, float fScale) {
return gsl_ran_gamma(randgen, fMean / fScale, fScale);
}