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209 lines
7.8 KiB
C++
209 lines
7.8 KiB
C++
// $Id: likelihoodComputation.h 9899 2011-10-11 19:56:48Z rubi $
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#ifndef ___LIKELIHOOD_COMPUTATION
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#define ___LIKELIHOOD_COMPUTATION
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#include "definitions.h"
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#include "computePijComponent.h"
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#include "sequenceContainer.h"
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#include "suffStatComponent.h"
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#include "unObservableData.h"
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#include "multipleStochasticProcess.h"
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#include "gammaDistribution.h"
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#include "distribution.h"
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namespace likelihoodComputation {
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// likelihood computation - full data (1)
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MDOUBLE getTreeLikelihoodAllPosAlphTheSame(const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp,
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const Vdouble * const weights = NULL,
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unObservableData *unObservableData_p=NULL);
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// likelihood computation - per pos (1.1)
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doubleRep getLofPos(const int pos, // this function is used
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const tree& et, // when gamma, and the br-len
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const sequenceContainer& sc, // are the same for all pos.
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const computePijGam& pi,
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const stochasticProcess& sp,
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unObservableData *unObservableData_p=NULL);
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// likelihood computation - per pos, per cat (1.1.1)
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doubleRep getLofPos(const int pos, // this function is used
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const tree& et, // when the br-len
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const sequenceContainer& sc, // are the same for all
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const computePijHom& pi, // positions.
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const stochasticProcess& sp,
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unObservableData *unObservableData_p=NULL);
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//r4s_Proportional
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// likelihood computation - full data (1)
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Vdouble getTreeLikelihoodProportionalAllPosAlphTheSame(const tree& et,
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const vector<sequenceContainer>& sc,
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multipleStochasticProcess* msp,
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const gammaDistribution* pProportionDist,
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const Vdouble * const weights = NULL);
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// likelihood computation - per pos (1.1)
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//Old - remove when QA is done
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doubleRep getLofPosProportional(const int pos, // this function is used
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const tree& et, // when gamma, and the br-len
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const sequenceContainer& sc, // are the same for all pos.
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const computePijGam& pi,
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const stochasticProcess& sp,
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const MDOUBLE globalRateProb);
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doubleRep getLofPosProportional(const int pos, // this function is used
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const tree& et, // when gamma, and the br-len
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const sequenceContainer& sc, // are the same for all pos.
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const computePijGam& pi,
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const stochasticProcess& sp);
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//r4s_Proportional
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// used when the likelihood given each category is needed, not only the sum
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Vdouble getLofPosPerCat(const int pos,
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const tree& et,
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const sequenceContainer& sc,
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const computePijGam& pi,
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const stochasticProcess& sp);
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// used to fill the likelihood for the unobservable for each category
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doubleRep getLofPos(const int pos,
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const tree& et,
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const sequenceContainer& sc,
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const computePijGam& pi,
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const stochasticProcess& sp,
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Vdouble& likePerCat); // all the likdelhoodsPerCat and rateProb are filled
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// --------------------------------------------------------------------------------
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// this function should be used only when the branch lengths are not the same for
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// all positions. Otherwise, computePijHom should be calculated once,
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// and be used for all calls. In this function, computePijHom is being computed for
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// each position.
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doubleRep getLofPosHomModelEachSiteDifferentRate(const int pos,
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const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp);
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// ---------------------------------------------------------------------------------
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// --------------------------------------------------------------------------------
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// this function should be used only when the branch lengths are not the same for
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// all positions. Otherwise, computePijHom should be calculated once,
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// and be used for all calls. In this function, computePijHom is being computed for
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// each position.
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doubleRep getLofPosGamModelEachSiteDifferentRate(const int pos,
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const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp);
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// --------------------------------------------------------------------------------
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doubleRep getLofPos(const int pos, // with a site specific rate.
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const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp,
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const MDOUBLE gRate);
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doubleRep getProbOfPosWhenUpIsFilledHom(const int pos, // to be used for homogenous model
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const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp,
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const suffStatGlobalHomPos& ssc);
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doubleRep getProbOfPosWhenUpIsFilledGam(const int pos, // to be used for Gamma model.
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const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp,
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const suffStatGlobalGamPos& cup);
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doubleRep getLofPosAndPosteriorOfRates(const int pos,
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const tree& et,
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const sequenceContainer& sc,
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const computePijGam& pi,
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const stochasticProcess& sp,
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VdoubleRep& postrior);
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MDOUBLE getTreeLikelihoodFromUp(const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp,
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const suffStatGlobalGam& cup,
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const Vdouble * weights =0 );
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MDOUBLE getTreeLikelihoodFromUp2(const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp,
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const suffStatGlobalGam& cup,
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VdoubleRep& posLike, // fill this vector with each position likelihood but without the weights.
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const Vdouble * weights=0,
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unObservableData* unObservableData_p=NULL);
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//old
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MDOUBLE getTreeLikelihoodFromUp2(const tree& et,
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const sequenceContainer& sc,
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stochasticProcess& sp,
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const suffStatGlobalGamProportional& cup,
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const gammaDistribution* pProportionDist,
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VdoubleRep& posLike, // fill this vector with each position likelihood but without the weights.
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const Vdouble * weights=0);
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//new
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MDOUBLE getTreeLikelihoodFromUp2(const tree& et,
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const sequenceContainer& sc,
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stochasticProcess& sp,
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const suffStatGlobalGamProportional& cup,
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const gammaDistribution* pProportionDist,
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VVdoubleRep& posLike, // fill this vector with each position likelihood but without the weights.
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const Vdouble * weights=0);
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// fill this vector with each position posterior rate (p(r|D))
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// but without the weights.
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// the weights are used only because we return the likelihood
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// (this takes these weights into account).
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MDOUBLE getPosteriorOfRates(const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp,
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const suffStatGlobalGam& cup,
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VVdoubleRep& posteriorLike,
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const Vdouble * weights = NULL);
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MDOUBLE getPosteriorOfRates(const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp,
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VVdoubleRep& posteriorLike,
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const Vdouble * weights = NULL);
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// fill the posteriorLike matrix with each position posterior rate (p(r|D))
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// and the LLPP, but without the weights.
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MDOUBLE getPosteriorOfRatesAndLLPP(const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp,
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const suffStatGlobalGam& cup,
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VVdoubleRep& posteriorLike,
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VdoubleRep& LLPerPos,
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const Vdouble * weights=NULL);
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// From Itay M.
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// this function forces non gamma computation of likelihoods from up.
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// i.e., even if the stochastic process is really gamma - the likelihood is computed as if there's no gamma.
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MDOUBLE getTreeLikelihoodFromUpSpecifcRates(const tree& et,
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const sequenceContainer& sc,
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const stochasticProcess& sp,
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const suffStatGlobalHom& cup,
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VdoubleRep& posLike, // fill this vector with each position likelihood but without the weights.
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const Vdouble * weights = NULL);
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// added from main semphy on 23.5.2005 (eyal privman + matan ninio).
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MDOUBLE computeLikelihoodAndLikelihoodPerPosition(const sequenceContainer &sc, const tree &et,
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const stochasticProcess &sp, Vdouble &LLPerPos);
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MDOUBLE getTreeLikelihoodFromPosteriorAndAlpha(const MDOUBLE alpha,
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const Vdouble originalBounderi,
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const VVdouble& posteriorLike,
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const VdoubleRep& LLPP,
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const Vdouble* weights);
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};
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#endif
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