void CandidateSet::recomputeLoglOfAllTrees(IQTree &treeObject) {
vector<string> allTreeStrings = getBestTreeStrings();
for (vector<string>:: iterator it = allTreeStrings.begin(); it != allTreeStrings.end(); it++) {
treeObject.readTreeString(*it);
double score = treeObject.optimizeAllBranches(1);
update(treeObject.getTreeString(), score);
}
}
void RateMeyerHaeseler::runIterativeProc(Params ¶ms, IQTree &tree) {
int i;
if (verbose_mode >= VB_MED) {
ofstream out("x");
out.close();
}
setTree(&tree);
RateHeterogeneity *backup_rate = tree.getRate();
if (backup_rate->getGammaShape() > 0 ) {
IntVector pattern_cat;
backup_rate->computePatternRates(*this, pattern_cat);
double sum = 0.0;
for (i = 0; i < size(); i++)
sum += at(i) * phylo_tree->aln->at(i).frequency;
sum /= phylo_tree->aln->getNSite();
if (fabs(sum - 1.0) > 0.0001) {
if (verbose_mode >= VB_MED)
cout << "Normalizing Gamma rates (" << sum << ")" << endl;
for (i = 0; i < size(); i++)
at(i) /= sum;
}
}
tree.getModelFactory()->site_rate = this;
tree.setRate(this);
//if (empty()) initializeRates();
//setRates(prev_rates);
//string rate_file = params.out_prefix;
//rate_file += ".mhrate";
double prev_lh = tree.getCurScore();
string dist_file = params.out_prefix;
dist_file += ".tdist";
tree.getModelFactory()->stopStoringTransMatrix();
for (i = 2; i < 100; i++) {
//DoubleVector prev_rates;
//getRates(prev_rates);
//writeSiteRates(prev_rates, rate_file.c_str());
tree.setCurScore(optimizeParameters(0.0));
//phylo_tree->aln->printDist(dist_file.c_str(), dist_mat);
tree.setCurScore(tree.optimizeAllBranches(i));
cout << "Current Log-likelihood: " << tree.getCurScore() << endl;
if (tree.getCurScore() <= prev_lh + 1e-4) {
break;
}
prev_lh = tree.getCurScore();
}
cout << "Optimization took " << i-1 << " rounds to finish" << endl;
tree.getModelFactory()->startStoringTransMatrix();
//tree.getModelFactory()->site_rate = backup_rate;
//tree.setRate(backup_rate);
}
