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#include "suffStatGammaMixture.h"
#include "mixtureDistribution.h"
#include "computePijComponent.h"
#include "likelihoodComputation.h"
#include "gammaUtilities.h"
#include "uniDistribution.h"
#include <cmath>
#include <fstream>
using namespace likelihoodComputation;
suffStatGammaMixture::suffStatGammaMixture(const stochasticProcess& cur_sp, const sequenceContainer& sc, const tree& inTree)
{
_pSp = &cur_sp;
_pSc = ≻
_pTree = &inTree;
}
suffStatGammaMixture::~suffStatGammaMixture()
{
}
void suffStatGammaMixture::allocatePlaceForSuffStat() {
mixtureDistribution* pMixture = static_cast<mixtureDistribution*>(_pSp->distr());
int componentNum = pMixture->getComponentsNum();
_MkVec.clear();
_MkVec.resize(componentNum, 0);
_AkVec.clear();
_AkVec.resize(componentNum, 0);
_BkVec.clear();
_BkVec.resize(componentNum, 0);
}
void suffStatGammaMixture::computePijForEachComponent(vector<computePijGam>& cpgVec,
vector<stochasticProcess>& spVec) {
mixtureDistribution* pMixture = static_cast<mixtureDistribution*>(_pSp->distr());
int componentNum = pMixture->getComponentsNum();
for (int comp = 0; comp < componentNum; ++comp) {
//create a local sp so to compute likelihoods of this component only
stochasticProcess compSp(pMixture->getComponent(comp), _pSp->getPijAccelerator());
cpgVec[comp].fillPij(*_pTree, compSp);
spVec.push_back(compSp);
}
}
void suffStatGammaMixture::computeStatistics()
{
///////////////as in getTreeLikelihoodAllPosAlphTheSame
//computePijGam pi;
//pi.fillPij(*_pTree, *_pSp);
//MDOUBLE res =0;
//doubleRep LofPos;
//int k;
//for (k=0; k < _pSc->seqLen(); ++k)
//{
// doubleRep tmp=0;
// for (int i=0; i < _pSp->categories();++i)
// {
// tmp += getLofPos(k, *_pTree, *_pSc, pi[i], *_pSp) * _pSp->ratesProb(i);
// }
// LofPos = tmp;
// res += log(LofPos);
//}
//////////////////////////////////////////////
//mixtureDistribution* pMixture = static_cast<mixtureDistribution*>(_pSp->distr());
//int componentNum = pMixture->getComponentsNum();
//MDOUBLE res2 = 0.0;
//vector<computePijGam> cpgVec(componentNum);
//vector<stochasticProcess> spVec;
//
//for (int comp = 0; comp < componentNum; ++comp) {
// //create a local sp so to compute likelihoods of this component only
// stochasticProcess compSp(pMixture->getComponent(comp), _pSp->getPijAccelerator());
// cpgVec[comp].fillPij(*_pTree, compSp);
// spVec.push_back(compSp);
//}
//
//for (int pos = 0; pos < _pSc->seqLen(); ++pos)
//{
// int comp;
// for (comp = 0; comp < componentNum; ++comp)
// {
// const generalGammaDistribution* pDist = pMixture->getComponent(comp);
// for (int cat=0; cat < pDist->categories(); ++cat)
// {
// MDOUBLE tmp = pDist->ratesProb(cat) * getLofPos(pos, *_pTree, *_pSc, cpgVec[comp][cat], *_pSp);
// res2 += log(tmp);
// }
// }
//}
//////////////////////////////////////////////
allocatePlaceForSuffStat();
mixtureDistribution* pMixture = static_cast<mixtureDistribution*>(_pSp->distr());
int componentNum = pMixture->getComponentsNum();
//compute Pij for each component
vector<computePijGam> cpgVec(componentNum);
vector<stochasticProcess> spVec;
computePijForEachComponent(cpgVec,spVec);
//compute statistics: M_k, A_k, B_k
//Here we sum over all positions.
//go over all positions [pos] and compute for each component [k]: M_k(pos), E[R]_k(pos), E[logR]_k(pos)
//Then compute A_k and B_k for that position.
for (int pos = 0; pos < _pSc->seqLen(); ++pos)
{
MDOUBLE sumAllComponents = 0.0;
Vdouble MkPosVec(componentNum, 0.0); //the contribution of position pos to the M_K statistic
Vdouble Exp_RkVec(componentNum, 0.0);
Vdouble Exp_LogRkVec(componentNum, 0.0);
int comp;
for (comp = 0; comp < componentNum; ++comp)
{
// here we compute P(H[i]=k, data| cur_mixtureDistribution)
//P(H[i]=k, data| teta) = P(H[i]=k)* (sum_over_all_categories{P(data|r)P(r))
///////////////////////////
const generalGammaDistribution* pDist = pMixture->getComponent(comp);
MDOUBLE Exp_Rk, Exp_LogRk, sum;
Exp_Rk = Exp_LogRk = sum = 0.0;
for (int cat=0; cat < pDist->categories(); ++cat)
{
MDOUBLE LofP = convert(likelihoodComputation::getLofPos(pos, *_pTree, *_pSc, cpgVec[comp][cat], spVec[comp]));
MDOUBLE Pr = pDist->ratesProb(cat) * LofP;
sum += Pr;
Exp_RkVec[comp] += Pr * pDist->rates(cat);
Exp_LogRkVec[comp] += Pr * log(pDist->rates(cat));
}
MkPosVec[comp] = sum;
sumAllComponents += MkPosVec[comp] * pMixture->getComponentProb(comp);;
}
for (comp = 0; comp < componentNum; ++comp)
{
MDOUBLE factor = pMixture->getComponentProb(comp)/ sumAllComponents;
_MkVec[comp] += factor* MkPosVec[comp] ;
_AkVec[comp] += factor * Exp_RkVec[comp];
_BkVec[comp] += factor * Exp_LogRkVec[comp];
}
}// end of loop over positions
spVec.clear();
cpgVec.clear();
}
#include "uniformDistribution.h"
void suffStatGammaMixture::plotStatistics(ofstream& outFile)
{
mixtureDistribution* pMixture = static_cast<mixtureDistribution*>(_pSp->distr());
if (pMixture->getComponentsNum() != 1)
errorMsg::reportError("Sorry, I plot only 1 component");
outFile <<"R"<<"\t"<<"Postr"<<"\t"<<"Er"<<"\t"<<"Elog_r"<<endl;
const generalGammaDistribution* pDist = pMixture->getComponent(0);
int numCat = 200, maxR = 10;
uniformDistribution uniDist(numCat, 0, maxR);
/////////calc the prior of each interval
Vdouble priorProbs(uniDist.categories());
MDOUBLE upperP, lowerP = 0;
for (int i = 0; i<uniDist.categories();++i)
{
upperP = pDist->getCumulativeProb(uniDist.getBorder(i+1));
priorProbs[i] = upperP - lowerP;
lowerP = upperP;
}
distribution * pUni = new uniDistribution;
stochasticProcess uniSp(pUni, _pSp->getPijAccelerator());
//loop over all r
for (int ri=0; ri < uniDist.categories(); ++ri)
{
MDOUBLE Exp_R = 0.0;
MDOUBLE Exp_LogR = 0.0;
MDOUBLE PosteriorR = 0.0;
MDOUBLE rate = uniDist.rates(ri);
if (rate == 0.0)
rate = 0.000001;
//Here we sum over all positions.
//go over all positions [pos] and compute: PosrteriorR(=P(D|r)*P(r)), E[R]_k(pos), E[logR]_k(pos)
for (int pos = 0; pos < _pSc->seqLen(); ++pos)
{
MDOUBLE PrPos = priorProbs[ri] * convert(likelihoodComputation::getLofPos(pos, *_pTree, *_pSc, uniSp, rate));
PosteriorR += PrPos;
Exp_R += PrPos * rate;
Exp_LogR += PrPos * log(rate);
}
outFile <<rate<<"\t"<<PosteriorR<<"\t"<<Exp_R<<"\t"<<Exp_LogR<<endl;
}
delete pUni;
}
MDOUBLE suffStatGammaMixture::computeQ2()
{
MDOUBLE res=0;
return res;
}
MDOUBLE suffStatGammaMixture::computeQ()
{
mixtureDistribution* pMixture = static_cast<mixtureDistribution*>(_pSp->distr());
MDOUBLE res = 0.0;
//////////////////////////////////
MDOUBLE res2 = 0.0;
int compNum = pMixture->getComponentsNum();
///////////////////////////////////
for (int comp = 0;comp < compNum ; ++comp)
{
MDOUBLE P_k = pMixture->getComponentProb(comp);
MDOUBLE alpha_k = pMixture->getAlpha(comp);
MDOUBLE beta_k = pMixture->getBeta(comp);
MDOUBLE first = _MkVec[comp] * log(P_k);
MDOUBLE second = _MkVec[comp] * alpha_k*log(beta_k);
MDOUBLE third = -_MkVec[comp] * gammln(alpha_k);
MDOUBLE fourth = -_AkVec[comp]*beta_k;
MDOUBLE fifth = _BkVec[comp]*(alpha_k-1.0);
res += _MkVec[comp] * (log(P_k) + alpha_k*log(beta_k) - gammln(alpha_k))
- (_AkVec[comp]*beta_k)
+ _BkVec[comp]*(alpha_k-1);
////////////////////////////////////
}
res2 = computeQ2();
return res;
}
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