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146 lines
4.0 KiB
C++
146 lines
4.0 KiB
C++
// $Id: fastStartTree.cpp 962 2006-11-07 15:13:34Z privmane $
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#include "definitions.h"
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#include "tree.h"
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#include "treeUtil.h"
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#include "fastStartTree.h"
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#include "bblEM.h"
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#include "likeDist.h"
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#include "likelihoodComputation.h"
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#include "getRandomWeights.h"
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#include "distanceTable.h"
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#include "nj.h"
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#include "logFile.h"
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#include <algorithm>
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using namespace std;
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using namespace likelihoodComputation;
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vector<tree> eliminateHalf(vector<tree>& tVec,
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sequenceContainer& orginal,
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stochasticProcess& sp,
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ostream& out,
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const int maxIterEM){
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vector<MDOUBLE> likeScore(tVec.size(),0.0);
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int i;
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for (i=0; i < tVec.size(); ++i) {
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bblEM bblEM1(tVec[i],orginal,sp,NULL,maxIterEM,0.01);
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likeScore[i] = bblEM1.getTreeLikelihood();
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LOG(5,<<"~");
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}
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vector<MDOUBLE> sortedL = likeScore;
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sort(sortedL.begin(),sortedL.end());
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MDOUBLE median = sortedL[sortedL.size()/2];
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// printing the top ten with their scores;
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// int toPrint = sortedL.size()>10? 10 : sortedL.size();
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// MDOUBLE treshToPrint = sortedL[sortedL.size()-toPrint];
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// out<<"current best 10 (or less) trees: "<<endl;
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// for (int h=0; h < likeScore.size(); ++h) {
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// if (likeScore[h]>treshToPrint) {
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// out<<"likelihood of tree: "<<h<<" = "<<likeScore[h]<<endl;
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// tVec[h].output(out);
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// }
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// }
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for (int p=0; p < sortedL.size(); ++p ){
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out<<"L["<<p<<"]= "<<sortedL[p]<<endl;
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}
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out<<endl;
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vector<tree> newTreeVec;
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for (i=0;i < tVec.size(); ++i) {
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if (likeScore[i]>=median) newTreeVec.push_back(tVec[i]); // ok this is a heck to mark trees
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}
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if (newTreeVec.size() == 0 ) newTreeVec.push_back(tVec[0]); // in case for example that all have the same L
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return newTreeVec;
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}
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//------------------ get N starting different NJ trees --------------------
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tree getBestMLTreeFromManyNJtrees(sequenceContainer & allTogether,
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stochasticProcess& sp,
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const int numOfNJtrees,
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const MDOUBLE tmpForStartingTreeSearch,
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const MDOUBLE epslionWeights,
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ostream& out) {
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likeDist pd1(sp,0.01);
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vector<tree> tVec;
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int treeTries = 0;
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while (tVec.size() < numOfNJtrees) {
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++treeTries;
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if (treeTries == 5000) break;
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Vdouble startingTreeWeights(allTogether.seqLen(),1.0);
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if (treeTries>1) {// the first is the regular NJ tree
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getRandomWeights::randomWeightsGamma(startingTreeWeights,
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tmpForStartingTreeSearch);
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}
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for (int p=0; p < startingTreeWeights.size(); ++p){
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if (startingTreeWeights[p]<epslionWeights) startingTreeWeights[p]=0.0;
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}
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#ifdef VERBOS
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if (treeTries ==2){ LOG(5,<<" weights for the 25 positions"<<endl);
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for (int h=0; h < 25; ++h) LOG(5,<<startingTreeWeights[h]<<" ");
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}
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#endif
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VVdouble disTab;
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vector<string> vNames;
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giveDistanceTable(&pd1,
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allTogether,
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disTab,
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vNames,
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&startingTreeWeights);
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NJalg nj1;
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tree et = nj1.computeTree(disTab,vNames);
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bool treeAlreadyThere = false;
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for (int z=0; z< tVec.size();++z) {
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if (sameTreeTolopogy(tVec[z],et)) treeAlreadyThere=true;
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}
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if (treeAlreadyThere == false) {
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tVec.push_back(et);
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}
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}
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LOG(5,<<"from number of tree tried: "<<treeTries<<" got: "<<numOfNJtrees<<" trees"<<endl);
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out<<"from number of tree tried: "<<treeTries<<" got: "<<numOfNJtrees<<" trees"<<endl;
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int numOfTreesToPrint = tVec.size()<10?tVec.size():10;
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out<<"starting with: "<<tVec.size()<<" trees! "<<endl;
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for (int g=0; g < numOfTreesToPrint; ++g) tVec[g].output(out);
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//------------------ chossing the ML tree from these NJ trees --------------------
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int maxIterEM=0;
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while (tVec.size() > 1) {
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LOG(5,<<" current size = "<<tVec.size()<<endl);
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tVec = eliminateHalf(tVec,allTogether,sp,out,maxIterEM);
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maxIterEM=1; // first round without bbl at all.
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}
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LOG(5,<<" final size = "<<tVec.size()<<endl);
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bblEM bblEM1(tVec[0],allTogether,sp,NULL,100,0.01);
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MDOUBLE res = bblEM1.getTreeLikelihood();
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LOGDO(5,tVec[0].output(myLog::LogFile()));
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LOG(5,<<"likelihood = "<<res<<endl);
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tVec[0].output(out);
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out<<"likelihood = "<<res<<endl;
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return tVec[0];
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}
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