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// $Id: siteSpecificRate.cpp 3658 2008-03-05 09:25:46Z cohenofi $
#include "siteSpecificRateGL.h"
#include "numRec.h"
#include "checkcovFanctors.h"
#include "definitions.h"
using namespace siteSpecificRateGL;
MDOUBLE siteSpecificRateGL::computeML_siteSpecificRate(Vdouble & ratesV,
Vdouble & likelihoodsV,
const sequenceContainer& sc,
const stochasticProcess& sp,
const tree& et,
const MDOUBLE maxRate,//20.0f
const MDOUBLE tol){//=0.0001f;
ratesV.resize(sc.seqLen());
likelihoodsV.resize(sc.seqLen());
MDOUBLE Lsum = 0.0;
for (int pos=0; pos < sc.seqLen(); ++pos) {
siteSpecificRateGL::computeML_siteSpecificRate(pos,sc,sp,et,ratesV[pos],likelihoodsV[pos],maxRate,tol);
assert(likelihoodsV[pos]>0.0);
Lsum += log(likelihoodsV[pos]);
LOG(5,<<" rate of pos: "<<pos<<" = "<<ratesV[pos]<<endl);
}
LOG(5,<<" number of sites: "<<sc.seqLen()<<endl);
return Lsum;
}
MDOUBLE siteSpecificRateGL::computeML_siteSpecificRate(Vdouble & ratesV,
Vdouble & likelihoodsV,
const Vint& spAttributesVec,
const Vint& treeAttributesVec,
const vector<tree> & etVec,
const vector<const stochasticProcess *> & spVec,
const sequenceContainer& sc,
const MDOUBLE maxRate,
const MDOUBLE tol){
MDOUBLE Lsum = 0.0;
ratesV.resize(sc.seqLen()); // the rates themselves
likelihoodsV.resize(sc.seqLen()); // the log likelihood of each position
for (int pos=0; pos < sc.seqLen(); ++pos) {
LOG(5,<<".");
MDOUBLE bestR=-1.0; // tree1
// MDOUBLE LmaxR1=0;
// getting the right tree for the specific position:
const tree* treeForThisPosition=NULL;
if ((etVec.size() >0 ) && (treeAttributesVec[pos]>0)) {
treeForThisPosition = & etVec[ treeAttributesVec[pos] -1];
} else {
errorMsg::reportError("tree vector is empty, or treeAttribute is empty, or treeAttribute[pos] is zero (it should be one)");
}
// getting the right stochastic process for the specific position:
const stochasticProcess* spForThisPosition=NULL;
if ((spVec.size() >0 ) && (spAttributesVec[pos]>0)) {
spForThisPosition = spVec[ spAttributesVec[pos] -1];
} else {
errorMsg::reportError("stochastic process vector is empty, or spAttributesVec is empty, or spAttribute[pos] is zero (it should be one)");
}
siteSpecificRateGL::computeML_siteSpecificRate(pos,sc,*spForThisPosition,*treeForThisPosition,bestR,likelihoodsV[pos],maxRate,tol);
ratesV[pos] = bestR;
assert(likelihoodsV[pos]>0.0);
Lsum += log(likelihoodsV[pos]);
LOG(5,<<" rate of pos: "<<pos<<" = "<<ratesV[pos]<<endl);
}
LOG(5,<<" number of sites: "<<sc.seqLen()<<endl);
return Lsum;
}
// note that this places the likelihood, rather then the *log*likelihood into posL
void siteSpecificRateGL::computeML_siteSpecificRate(int pos,
const sequenceContainer& sc,
const stochasticProcess& sp,
const tree &et,
MDOUBLE& bestRate,
MDOUBLE& posL,
const MDOUBLE maxRate,
const MDOUBLE tol) {
LOG(5,<<".");
MDOUBLE ax=0.00001f,bx=maxRate*0.25,cx=maxRate; // MN
posL=-brent(ax,bx,cx,Cevaluate_L_given_r(sc,et,sp,pos),tol,&bestRate);
}
MDOUBLE siteSpecificRateGL::computeML_siteSpecificRate(Vdouble & ratesV,
Vdouble & likelihoodsV,
const Vint& treeAttributesVec,
const vector<tree> & etVec,
const stochasticProcess& sp,
const sequenceContainer& sc,
const MDOUBLE maxRate,
const MDOUBLE tol) {
Vint spAttributesVec(sc.seqLen(),1);
vector<const stochasticProcess* > spVec;
spVec.push_back(&sp);
return computeML_siteSpecificRate(ratesV,likelihoodsV,
spAttributesVec,treeAttributesVec,etVec,spVec,sc,maxRate,tol);
}
MDOUBLE siteSpecificRateGL::computeML_siteSpecificRate(Vdouble & ratesV,
Vdouble & likelihoodsV,
const Vint& spAttributesVec,
const tree & et,
const vector<const stochasticProcess* > & spVec,
const sequenceContainer& sc,
const MDOUBLE maxRate,
const MDOUBLE tol){
Vint treeAttributesVec(sc.seqLen(),1);
vector<tree> etVec;
etVec.push_back(et);
return siteSpecificRateGL::computeML_siteSpecificRate(ratesV,likelihoodsV,
spAttributesVec,treeAttributesVec,etVec,spVec,sc,maxRate,tol);
}
// THE BAYESIAN EB_EXP PART OF RATE ESTIMATION. //
void siteSpecificRateGL::computeEB_EXP_siteSpecificRate(int pos,
const sequenceContainer& sc,
const stochasticProcess& sp,
const computePijGam& cpg,
const tree &et,
MDOUBLE& bestRate,
MDOUBLE & stdRate,
MDOUBLE & lowerConf,
MDOUBLE & upperConf,
const MDOUBLE alphaConf, // alpha of 0.05 is considered 0.025 for each side.
VVdouble* LpostPerCat,
Vdouble* pLforMissingDataPerCat)
{
// here we compute P(r | data)
VdoubleRep pGivenR(sp.categories(),0.0);
doubleRep sum=0;
MDOUBLE LofPos_givenRateCat;
LOG(8,<<pos+1<<"\t"); //DEBUG
for (int cat=0; cat < sp.categories(); ++cat) {
LofPos_givenRateCat = convert(likelihoodComputation::getLofPos(pos,et,sc,cpg[cat],sp));
if(pLforMissingDataPerCat){
LofPos_givenRateCat = LofPos_givenRateCat/(1- (*pLforMissingDataPerCat)[cat]);
}
pGivenR[cat] = LofPos_givenRateCat*sp.ratesProb(cat);
LOG(8,<<cat<<"\t"<<LofPos_givenRateCat<<"\t"); //DEBUG
sum+=pGivenR[cat];
}
LOG(8,<<"\n"); //DEBUG
assert(sum!=0);
// here we compute sigma r * P(r | data)
doubleRep sumOfSquares(0.0);
doubleRep bestRate_dblRep(0.0);
LOG(5,<<"Pos "<<pos<<" content = "<<sc[0][pos]<<" ,total likelihood = "<<sum<<endl); //DEBUG
for (int j=0; j < sp.categories(); ++j) {
pGivenR[j]/=sum; // So that pGivenR is probability.
// From here on we can convert it back
// to MDOUBLE because it's not a very
// small likelihood any more
if (LpostPerCat){
(*LpostPerCat)[j][pos]= convert(pGivenR[j]);
}
doubleRep tmp = pGivenR[j]*sp.rates(j);
bestRate_dblRep += tmp;
sumOfSquares += (tmp*sp.rates(j));
}
bestRate = convert(bestRate_dblRep);
MDOUBLE varRate = convert(sumOfSquares) - convert(bestRate*bestRate);
MDOUBLE tolerance = 0.0001; // tolerance for variance is not very exact, and also exact computation not very important
if (varRate<-tolerance)
errorMsg::reportError("Error in computeEB_EXP_siteSpecificRate, varRate < 0");
if ((varRate<0) && (varRate>=-tolerance))
varRate = 0;
stdRate = sqrt(varRate);
// detecting the confidence intervals.
MDOUBLE oneSideConfAlpha = alphaConf/2.0; // because we are computing the two tail.
doubleRep cdf = 0.0; // cumulative density function.
int k=0;
while (k < sp.categories()){
cdf += convert(pGivenR[k]);
if (cdf >oneSideConfAlpha) {
lowerConf = sp.rates(k);
break;
}
k++;
}
while (k < sp.categories()) {
if (cdf >(1.0-oneSideConfAlpha)) {
upperConf = sp.rates(k);
break;
}
++k;
cdf += convert(pGivenR[k]);
}
if (k==sp.categories()) upperConf = sp.rates(k-1);
}
void siteSpecificRateGL::computeEB_EXP_siteSpecificRate(Vdouble & ratesV,
Vdouble & stdV,
Vdouble & lowerBoundV,
Vdouble & upperBoundV,
const sequenceContainer& sc,
const stochasticProcess& sp,
const tree& et,
const MDOUBLE alphaConf,
VVdouble* LpostPerCat,
Vdouble* pLforMissingDataPerCat)
{
ratesV.resize(sc.seqLen());
stdV.resize(sc.seqLen());
lowerBoundV.resize(sc.seqLen());
upperBoundV.resize(sc.seqLen());
computePijGam cpg;
cpg.fillPij(et,sp);
for (int pos=0; pos < sc.seqLen(); ++pos) {
siteSpecificRateGL::computeEB_EXP_siteSpecificRate(pos,sc,sp,cpg, et,ratesV[pos],stdV[pos],lowerBoundV[pos],upperBoundV[pos],alphaConf,LpostPerCat,pLforMissingDataPerCat);
LOG(5,<<" rate of pos: "<<pos<<" = "<<ratesV[pos]<<endl);
}
LOG(5,<<" number of sites: "<<sc.seqLen()<<endl);
}
void computeEB_EXP_siteSpecificRate(Vdouble & ratesV,
Vdouble & stdV,
Vdouble & lowerBoundV,
Vdouble & upperBoundV,
const Vint& spAttributesVec,
const Vint& treeAttributesVec,
const sequenceContainer& sc,
const vector<tree> & etVec,
const vector<const stochasticProcess *> & spVec,
const MDOUBLE alphaConf){
ratesV.resize(sc.seqLen());
stdV.resize(sc.seqLen());
lowerBoundV.resize(sc.seqLen());
upperBoundV.resize(sc.seqLen());
for (int treeNum=0; treeNum<etVec.size(); ++treeNum) {
for (int spNum = 0; spNum<spVec.size(); ++spNum) {
computePijGam cpg;
cpg.fillPij(etVec[treeNum],*(spVec[spNum]));
for (int pos=0; pos < sc.seqLen(); ++pos) {
if (((spAttributesVec[pos]-1)!=spNum ) || ((treeAttributesVec[pos]-1)!=treeNum )) continue;
const tree* treeForThisPosition=NULL;
assert ((etVec.size() >0 ) && (treeAttributesVec[pos]>0));
treeForThisPosition = & etVec[ treeAttributesVec[pos] -1];
const stochasticProcess* spForThisPosition=NULL;
assert ((spVec.size() >0 ) && (spAttributesVec[pos]>0));
spForThisPosition = spVec[ spAttributesVec[pos] -1];
siteSpecificRateGL::computeEB_EXP_siteSpecificRate(pos,sc,*spForThisPosition,cpg, *treeForThisPosition,ratesV[pos],stdV[pos],lowerBoundV[pos],upperBoundV[pos],alphaConf);
LOG(5,<<" rate of pos: "<<pos<<" = "<<ratesV[pos]<<endl);
}
}
}
LOG(5,<<" number of sites: "<<sc.seqLen()<<endl);
}
// one tree many sps
void siteSpecificRateGL::computeEB_EXP_siteSpecificRate(Vdouble & ratesV,
Vdouble & stdV,
Vdouble & lowerBoundV,
Vdouble & upperBoundV,
const Vint& spAttributesVec,
const sequenceContainer& sc,
const tree & et,
const vector<const stochasticProcess *> & spVec,
const MDOUBLE alphaConf){
Vint etAttributesVec(sc.seqLen(),1);
vector<tree> etVec;
etVec.push_back(et);
siteSpecificRateGL::computeEB_EXP_siteSpecificRate(ratesV,stdV,lowerBoundV,upperBoundV,spAttributesVec,etAttributesVec,sc,etVec,spVec,alphaConf);
}
// one sp many trees
void siteSpecificRateGL::computeEB_EXP_siteSpecificRate(Vdouble & ratesV,
Vdouble & stdV,
Vdouble & lowerBoundV,
Vdouble & upperBoundV,
const Vint& treeAttributesVec,
const sequenceContainer& sc,
const vector<tree> & etVec,
const stochasticProcess & sp,
const MDOUBLE alphaConf){
Vint spAttributesVec(sc.seqLen(),1);
vector<const stochasticProcess* > spVec;
spVec.push_back(&sp);
siteSpecificRateGL::computeEB_EXP_siteSpecificRate(ratesV,stdV,lowerBoundV,upperBoundV,spAttributesVec,treeAttributesVec,sc,etVec,spVec,alphaConf);
}
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