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126 lines
4.1 KiB
C++
126 lines
4.1 KiB
C++
// $Id: ussrvModel.cpp 962 2006-11-07 15:13:34Z privmane $
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#include "ussrvModel.h"
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ussrvModel::ussrvModel(const stochasticProcess& baseSp, const stochasticProcessSSRV& ssrvSp, const MDOUBLE& f)
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: _f(f),_baseSp(NULL),_ssrvSp(NULL)
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{
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_baseSp = new stochasticProcess(baseSp);
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_ssrvSp = new stochasticProcessSSRV(ssrvSp);
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// get alpha from sp
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replacementModelSSRV* pMulRM = static_cast<replacementModelSSRV*>(_ssrvSp->getPijAccelerator()->getReplacementModel());
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_alpha = static_cast<gammaDistribution*>(pMulRM->getDistribution())->getAlpha();
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// check that alpha is equal the baseSp alpha
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MDOUBLE baseSpAlpha = static_cast<gammaDistribution*>(baseSp.distr())->getAlpha();
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if (_alpha != baseSpAlpha)
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errorMsg::reportError("Error in the constructor of ussrvModel. alpha of the ssrv stochastic process is different from that of the base model");
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}
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ussrvModel::~ussrvModel()
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{
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if (_baseSp) delete _baseSp;
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if (_ssrvSp) delete _ssrvSp;
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}
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ussrvModel::ussrvModel(const ussrvModel& other)
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{
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_f = other._f;
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_baseSp = new stochasticProcess(*other._baseSp);
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_ssrvSp = new stochasticProcessSSRV(*other._ssrvSp);
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}
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ussrvModel& ussrvModel::operator=(const ussrvModel& other)
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{
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if (_baseSp) delete _baseSp;
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if (_ssrvSp) delete _ssrvSp;
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_f = other._f;
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_alpha = other._alpha;
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_baseSp = new stochasticProcess(*other._baseSp);
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_ssrvSp = new stochasticProcessSSRV(*other._ssrvSp);
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return *this;
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}
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void ussrvModel::updateAlpha(const MDOUBLE& alpha)
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{
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_alpha = alpha;
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if (alpha<0)
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{
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LOG(4, << "ussrvModel::updateAlpha , alpha is < 0 " << endl);
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return;
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}
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// update alpha of the ssrv model
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replacementModelSSRV* pMulRM = static_cast<replacementModelSSRV*>(_ssrvSp->getPijAccelerator()->getReplacementModel());
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gammaDistribution* gammaDist = static_cast<gammaDistribution*>(pMulRM->getDistribution());
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gammaDist->setAlpha(alpha);
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pMulRM->updateQ();
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// update alpha of the base model
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(static_cast<gammaDistribution*>(_baseSp->distr()))->setAlpha(alpha);
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}
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void ussrvModel::updateNu(const MDOUBLE& nu)
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{
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if (nu<0)
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{
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LOG(4,<<"ussrvModel::updateNu , nu is < 0 " <<endl);
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return;
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}
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static_cast<replacementModelSSRV*>(_ssrvSp->getPijAccelerator()->getReplacementModel())->setRateOfRate(nu);
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}
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MDOUBLE ussrvModel::getNu() const
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{
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return (static_cast<replacementModelSSRV*>(_ssrvSp->getPijAccelerator()->getReplacementModel())->getRateOfRate());
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}
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void ussrvModel::updateF(const MDOUBLE& f)
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{
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if ((f<0) || (f>1))
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{
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LOG(4,<<"ussrvModel::updateF , f must be between 0 to 1. f is: "<< f << endl);
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return;
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}
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_f=f;
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}
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// In order for the branch lengths and the nu parameter to be meaningfull, one must normalize the
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// matrices of both the replacement models (the base model and the ssrv model)
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// so that f*Sigma[i](PiQij) + (1-f)*Sigma[i](P`iQ`ij) = 1 (for i!=j)
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// where Q and P belong to the ssrv model, P` and Q` belong to the base model. (Q` doesn't include the rates)
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// The normalization doesn't affect the likelihood.
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// see below for more explanations.
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// Theoretically, we should therefore calculate this weighted sumPijQij (Denote by x), and then:
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// 1) devide nu by x.
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// 2) devide all the rates (of the base model and of the ssrv model) by x.
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// (this could be done using the _globalRate member of the gammaDistribution class)
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// 3) multiply every branch length by x.
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// Instead, we just report x, so that the user can do all this whenever he wishes to.
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MDOUBLE ussrvModel::calcNormalizeFactor()
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{
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// calculate sumPijQij
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MDOUBLE sumPijQij = 0.0;
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int i;
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// of the base model
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int baseAlphabetSize = _baseSp->alphabetSize();
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for (i=0; i < baseAlphabetSize; ++i)
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sumPijQij-= _baseSp->freq(i) * _baseSp->dPij_dt(i,i,0);
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sumPijQij*=(1-_f);
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// of the ssrv model
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sumPijQij+=_f*static_cast<replacementModelSSRV*>(_ssrvSp->getPijAccelerator()->getReplacementModel())->sumPijQij();
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return sumPijQij;
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}
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// This is not done when using normal sp (instead of ussrvModel), since:
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// average(rates)=1 -->
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// (for 2 categories, f=0.5, 1-f =0.5) 0.5*r1*Sigma[i](PiQij) + 0.5*r2*Sigma[i](PiQij) = 1 -->
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// (since (r1+r2)*0.5 = 1) Sigma[i](PiQij) = 1 . This is always true, and taken care of in the readMatrix
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// method.
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