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101 lines
3.8 KiB
C++
101 lines
3.8 KiB
C++
#ifndef ___LIKELIHOOD_COMPUTATION_GL
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#define ___LIKELIHOOD_COMPUTATION_GL
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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 "computeUpAlg.h"
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namespace likelihoodComputationGL {
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MDOUBLE getTreeLikelihoodAllPosAlphTheSame(const tree& tr,
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const sequenceContainer& sc,
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const vector<vector<stochasticProcess*> >& spVVec,
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const distribution * distGain, const distribution * distLoss,
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const Vdouble * const weights,
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unObservableData *unObservableData_p =NULL);
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void fillPijAndUp(const tree& tr,
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const sequenceContainer& sc,
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const vector<vector<stochasticProcess*> >& spVVec,
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const distribution * distGain, const distribution * distLoss,
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vector<computePijGam>& pi_vec,
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vector<suffStatGlobalGam>& ssc_vec,
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vector<computeUpAlg>& cup_vec);
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MDOUBLE getProbOfPosUpIsFilledSelectionGam(const int pos,const tree& tr,
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const sequenceContainer& sc,
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const vector<vector<stochasticProcess*> >& spVVec, // only needed for sp.freq(let)
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const suffStatGlobalGamPos& cup,
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const distribution * distGain, const distribution * distLoss);
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MDOUBLE getTreeLikelihoodFromUp2(const tree& tr,
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const sequenceContainer& sc,
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const vector<vector<stochasticProcess*> >& spVVec,// only needed for sp.freq(let)
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const suffStatGlobalGam& cup,
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const distribution * distGain, const distribution * distLoss,
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const Vdouble * weights,
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unObservableData *unObservableData_p,
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Vdouble* posLike =NULL);
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MDOUBLE getTreeLikelihoodFromUp2(const tree& tr,
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const sequenceContainer& sc,
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const vector<vector<stochasticProcess*> >& spVVec,// only needed for sp.freq(let)
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const vector<suffStatGlobalGam>& cup_vec,
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const distribution * distGain, const distribution * distLoss,
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const Vdouble * weights,
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unObservableData *unObservableData_p,
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Vdouble* posLike =NULL);
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// Error
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//MDOUBLE getTreeLikelihoodAllPosAlphTheSameNoComputeUp(const tree& tr,
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// const sequenceContainer& sc,
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// const vector<vector<stochasticProcess*> >& spVVec,
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// const distribution * distGain, const distribution * distLoss,
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// unObservableData *unObservableData_p);
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///********************************************************************************************
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//un-obervable data
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//*********************************************************************************************/
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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& tr,
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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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//// likelihood computation - full data (1)
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// MDOUBLE getTreeLikelihoodAllPosAlphTheSame(const tree& tr,
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// const sequenceContainer& sc,
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// const stochasticProcess& sp,
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// const Vdouble * const weights,
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// Vdouble *pLforMissingDataPerCat=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& tr, // 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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// Vdouble *pLforMissingDataPerCat=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& tr, // 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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//
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// Vdouble getLofPosPerCat(const int pos, // used when the likelihood given each category is needed, not only the sum
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// const tree& tr,
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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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};
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#endif
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