VectorSiteContainer::VectorSiteContainer(const VectorSiteContainer& vsc) :
AbstractSequenceContainer(vsc),
sites_(0),
names_(vsc.names_),
comments_(vsc.getNumberOfSequences()),
sequences_(vsc.getNumberOfSequences())
{
// Now try to add each site:
for (size_t i = 0; i < vsc.getNumberOfSites(); i++)
{
addSite(vsc.getSite(i), false); // We assume that positions are correct.
}
// Seq comments:
for (size_t i = 0; i < vsc.getNumberOfSequences(); i++)
{
comments_[i] = new Comments(vsc.getComments(i));
}
}
int main(int args, char** argv)
{
cout << "******************************************************************" << endl;
cout << "* Bio++ Computation of site likelihoods inside mixed models *" << endl;
cout << "* Version 2.2.0. *" << endl;
cout << "* Author: L. Guéguen Last Modif.: 25/09/14 *" << endl;
cout << "******************************************************************" << endl;
cout << endl;
if (args == 1)
{
help();
return 0;
}
try
{
BppApplication bppmixedlikelihoods(args, argv, "BppMixedLikelihoods");
bppmixedlikelihoods.startTimer();
Alphabet* alphabet = SequenceApplicationTools::getAlphabet(bppmixedlikelihoods.getParams(), "", false);
auto_ptr<GeneticCode> gCode;
CodonAlphabet* codonAlphabet = dynamic_cast<CodonAlphabet*>(alphabet);
if (codonAlphabet) {
string codeDesc = ApplicationTools::getStringParameter("genetic_code", bppmixedlikelihoods.getParams(), "Standard", "", true, true);
ApplicationTools::displayResult("Genetic Code", codeDesc);
gCode.reset(SequenceApplicationTools::getGeneticCode(codonAlphabet->getNucleicAlphabet(), codeDesc));
}
// get the data
VectorSiteContainer* allSites = SequenceApplicationTools::getSiteContainer(alphabet, bppmixedlikelihoods.getParams());
VectorSiteContainer* sites = SequenceApplicationTools::getSitesToAnalyse(*allSites, bppmixedlikelihoods.getParams(), "", true, false);
delete allSites;
ApplicationTools::displayResult("Number of sequences", TextTools::toString(sites->getNumberOfSequences()));
ApplicationTools::displayResult("Number of sites", TextTools::toString(sites->getNumberOfSites()));
// Get the tree
Tree* tree = PhylogeneticsApplicationTools::getTree(bppmixedlikelihoods.getParams());
ApplicationTools::displayResult("Number of leaves", TextTools::toString(tree->getNumberOfLeaves()));
AbstractDiscreteRatesAcrossSitesTreeLikelihood* tl;
string nhOpt = ApplicationTools::getStringParameter("nonhomogeneous", bppmixedlikelihoods.getParams(), "no", "", true, false);
ApplicationTools::displayResult("Heterogeneous model", nhOpt);
MixedSubstitutionModel* model = 0;
MixedSubstitutionModelSet* modelSet = 0;
DiscreteDistribution* rDist = 0;
if (nhOpt == "no")
{
model = dynamic_cast<MixedSubstitutionModel*>(PhylogeneticsApplicationTools::getSubstitutionModel(alphabet, gCode.get(), sites, bppmixedlikelihoods.getParams()));
if (model == 0)
{
cout << "Model is not a Mixed model" << endl;
exit(0);
}
SiteContainerTools::changeGapsToUnknownCharacters(*sites);
if (model->getNumberOfStates() > model->getAlphabet()->getSize())
{
// Markov-modulated Markov model!
rDist = new ConstantRateDistribution();
}
else
{
rDist = PhylogeneticsApplicationTools::getRateDistribution(bppmixedlikelihoods.getParams());
}
tl = new RHomogeneousMixedTreeLikelihood(*tree, *sites, model, rDist, true);
}
else if (nhOpt == "one_per_branch")
{
model = dynamic_cast<MixedSubstitutionModel*>(PhylogeneticsApplicationTools::getSubstitutionModel(alphabet, gCode.get(), sites, bppmixedlikelihoods.getParams()));
if (model == 0)
{
cout << "Model is not a Mixed model" << endl;
exit(0);
}
SiteContainerTools::changeGapsToUnknownCharacters(*sites);
if (model->getNumberOfStates() > model->getAlphabet()->getSize())
{
// Markov-modulated Markov model!
rDist = new ConstantRateDistribution();
}
else
{
rDist = PhylogeneticsApplicationTools::getRateDistribution(bppmixedlikelihoods.getParams());
}
vector<double> rateFreqs;
if (model->getNumberOfStates() != alphabet->getSize())
{
// Markov-Modulated Markov Model...
unsigned int n = (unsigned int)(model->getNumberOfStates() / alphabet->getSize());
rateFreqs = vector<double>(n, 1. / (double)n); // Equal rates assumed for now, may be changed later (actually, in the most general case,
// we should assume a rate distribution for the root also!!!
}
std::map<std::string, std::string> aliasFreqNames;
FrequenciesSet* rootFreqs = PhylogeneticsApplicationTools::getRootFrequenciesSet(alphabet, gCode.get(), sites, bppmixedlikelihoods.getParams(), aliasFreqNames, rateFreqs);
vector<string> globalParameters = ApplicationTools::getVectorParameter<string>("nonhomogeneous_one_per_branch.shared_parameters", bppmixedlikelihoods.getParams(), ',', "");
modelSet = dynamic_cast<MixedSubstitutionModelSet*>(SubstitutionModelSetTools::createNonHomogeneousModelSet(model, rootFreqs, tree, aliasFreqNames, globalParameters));
model = 0;
tl = new RNonHomogeneousMixedTreeLikelihood(*tree, *sites, modelSet, rDist, true);
}
else if (nhOpt == "general")
{
modelSet = dynamic_cast<MixedSubstitutionModelSet*>(PhylogeneticsApplicationTools::getSubstitutionModelSet(alphabet, gCode.get(), sites, bppmixedlikelihoods.getParams()));
if (modelSet == 0)
{
cout << "Missing a Mixed model" << endl;
exit(0);
}
SiteContainerTools::changeGapsToUnknownCharacters(*sites);
if (modelSet->getNumberOfStates() > modelSet->getAlphabet()->getSize())
{
// Markov-modulated Markov model!
rDist = new ConstantDistribution(1.);
}
else
{
rDist = PhylogeneticsApplicationTools::getRateDistribution(bppmixedlikelihoods.getParams());
}
tl = new RNonHomogeneousMixedTreeLikelihood(*tree, *sites, modelSet, rDist, true);
}
else
throw Exception("Unknown option for nonhomogeneous: " + nhOpt);
tl->initialize();
double logL = tl->getValue();
if (isinf(logL))
{
// This may be due to null branch lengths, leading to null likelihood!
ApplicationTools::displayWarning("!!! Warning!!! Likelihood is zero.");
ApplicationTools::displayWarning("!!! This may be due to branch length == 0.");
ApplicationTools::displayWarning("!!! All null branch lengths will be set to 0.000001.");
ParameterList pl = tl->getBranchLengthsParameters();
for (unsigned int i = 0; i < pl.size(); i++)
{
if (pl[i].getValue() < 0.000001)
pl[i].setValue(0.000001);
}
tl->matchParametersValues(pl);
logL = tl->getValue();
}
if (isinf(logL))
{
ApplicationTools::displayError("!!! Unexpected likelihood == 0.");
ApplicationTools::displayError("!!! Looking at each site:");
for (unsigned int i = 0; i < sites->getNumberOfSites(); i++)
{
(*ApplicationTools::error << "Site " << sites->getSite(i).getPosition() << "\tlog likelihood = " << tl->getLogLikelihoodForASite(i)).endLine();
}
ApplicationTools::displayError("!!! 0 values (inf in log) may be due to computer overflow, particularily if datasets are big (>~500 sequences).");
exit(-1);
}
// Write parameters to screen:
ApplicationTools::displayResult("Log likelihood", TextTools::toString(tl->getValue(), 15));
ParameterList parameters = tl->getSubstitutionModelParameters();
for (unsigned int i = 0; i < parameters.size(); i++)
{
ApplicationTools::displayResult(parameters[i].getName(), TextTools::toString(parameters[i].getValue()));
}
parameters = tl->getRateDistributionParameters();
for (unsigned int i = 0; i < parameters.size(); i++)
{
ApplicationTools::displayResult(parameters[i].getName(), TextTools::toString(parameters[i].getValue()));
}
// /////////////////////////////////////////////
// Getting likelihoods per submodel
string outputFile;
outputFile = ApplicationTools::getAFilePath("output.likelihoods.file", bppmixedlikelihoods.getParams(), true, false);
ApplicationTools::displayResult("Output file for likelihoods", outputFile);
ofstream out(outputFile.c_str(), ios::out);
size_t nSites = sites->getNumberOfSites();
size_t nummodel = ApplicationTools::getParameter<size_t>("likelihoods.model_number", bppmixedlikelihoods.getParams(), 1, "", true, true);
string parname = ApplicationTools::getStringParameter("likelihoods.parameter_name", bppmixedlikelihoods.getParams(), "", "", true, false);
if (modelSet && ((nummodel <= 0) || (nummodel > modelSet->getNumberOfModels())))
{
ApplicationTools::displayError("Bad number of model " + TextTools::toString(nummodel) + ".");
exit(-1);
}
MixedSubstitutionModel* p0 = dynamic_cast<MixedSubstitutionModel*>(model ? model : modelSet->getModel(nummodel - 1));
if (!p0)
{
ApplicationTools::displayError("Model " + TextTools::toString(nummodel) + " is not a Mixed Model.");
exit(-1);
}
const AbstractBiblioMixedSubstitutionModel* ptmp = dynamic_cast<const AbstractBiblioMixedSubstitutionModel*>(p0);
if (ptmp) {
p0 = ptmp->getMixedModel().clone();
if (nhOpt == "no")
model = p0;
else {
modelSet->replaceModel(nummodel-1, p0);
modelSet->isFullySetUpFor(*tree);
}
}
//////////////////////////////////////////////////
// Case of a MixtureOfSubstitutionModels
MixtureOfSubstitutionModels* pMSM = dynamic_cast<MixtureOfSubstitutionModels*>(p0);
if (pMSM)
{
vector<string> colNames;
colNames.push_back("Sites");
size_t nummod = pMSM->getNumberOfModels();
for (unsigned int i = 0; i < nummod; i++)
{
colNames.push_back(pMSM->getNModel(i)->getName());
}
DataTable* rates = new DataTable(nSites, colNames.size());
rates->setColumnNames(colNames);
for (unsigned int i = 0; i < nSites; i++)
{
const Site* currentSite = &sites->getSite(i);
int currentSitePosition = currentSite->getPosition();
(*rates)(i, "Sites") = string("[" + TextTools::toString(currentSitePosition) + "]");
}
Vdouble vprob = pMSM->getProbabilities();
for (unsigned int i = 0; i < nummod; i++)
{
string modname = pMSM->getNModel(i)->getName();
for (unsigned int j = 0; j < nummod; j++)
{
pMSM->setNProbability(j, (j == i) ? 1 : 0);
}
if (tl)
delete tl;
if (nhOpt == "no")
tl = new RHomogeneousMixedTreeLikelihood(*tree, *sites, model, rDist, true, false, true);
else
tl = new RNonHomogeneousMixedTreeLikelihood(*tree, *sites, modelSet, rDist, false, true);
tl->initialize();
logL = tl->getValue();
Vdouble Vd = tl->getLogLikelihoodForEachSite();
for (unsigned int j = 0; j < nSites; j++)
{
(*rates)(j, modname) = TextTools::toString(Vd[j]);
}
ApplicationTools::displayMessage("\n");
ApplicationTools::displayMessage("Model " + modname + ":");
ApplicationTools::displayResult("Log likelihood", TextTools::toString(tl->getValue(), 15));
ApplicationTools::displayResult("Probability", TextTools::toString(vprob[i], 15));
}
DataTable::write(*rates, out, "\t");
}
//////////////////////////////////////////////////
// Case of a MixtureOfASubstitutionModel
else
{
MixtureOfASubstitutionModel* pMSM2 = dynamic_cast<MixtureOfASubstitutionModel*>(p0);
if (pMSM2 != NULL)
{
size_t nummod = pMSM2->getNumberOfModels();
if (parname == "")
{
ParameterList pl=pMSM2->getParameters();
for (size_t i2 = 0; i2 < pl.size(); i2++)
{
string pl2n = pl[i2].getName();
if (dynamic_cast<const ConstantDistribution*>(pMSM2->getDistribution(pl2n))==NULL)
{
parname=pl2n;
while (parname.size()>0 && pMSM2->getDistribution(parname)==NULL)
parname=pl2n.substr(0,pl2n.rfind("_"));
if (parname.size()>0){
ApplicationTools::displayResult("likelihoods.parameter_name", parname);
break;
}
}
}
}
if (parname == "")
{
ApplicationTools::displayError("Argument likelihoods.parameter_name is required.");
exit(-1);
}
vector< Vint > vvnmod;
size_t i2 = 0;
while (i2 < nummod)
{
string par2 = parname + "_" + TextTools::toString(i2 + 1);
Vint vnmod = pMSM2->getSubmodelNumbers(par2);
if (vnmod.size() == 0)
break;
vvnmod.push_back(vnmod);
i2++;
}
size_t nbcl = vvnmod.size();
if (nbcl==0)
throw Exception("Parameter " + parname + " is not mixed.");
Vdouble vprob = pMSM2->getProbabilities();
vector<vector<double> > vvprob;
vector<double> vsprob;
for (size_t i = 0; i < nbcl; i++)
{
vector<double> vprob2;
for (size_t j = 0; j < vvnmod[i].size(); j++)
{
vprob2.push_back(vprob[static_cast<size_t>(vvnmod[i][j])]);
}
vvprob.push_back(vprob2);
vsprob.push_back(VectorTools::sum(vvprob[i]));
}
vector<string> colNames;
colNames.push_back("Sites");
Vdouble dval;
for (unsigned int i = 0; i < nbcl; i++)
{
SubstitutionModel* pSM = pMSM2->getNModel(static_cast<size_t>(vvnmod[i][0]));
double valPar = pSM->getParameterValue(pSM->getParameterNameWithoutNamespace(parname));
dval.push_back(valPar);
colNames.push_back("Ll_" + parname + "=" + TextTools::toString(valPar));
}
for (unsigned int i = 0; i < nbcl; i++)
colNames.push_back("Pr_" + parname + "=" + TextTools::toString(dval[i]));
colNames.push_back("mean");
DataTable* rates = new DataTable(nSites, colNames.size());
rates->setColumnNames(colNames);
for (unsigned int i = 0; i < nSites; i++)
{
const Site* currentSite = &sites->getSite(i);
int currentSitePosition = currentSite->getPosition();
(*rates)(i,"Sites")=TextTools::toString(currentSitePosition);
}
VVdouble vvd;
vector<double> vRates = pMSM2->getVRates();
for (size_t i = 0; i < nbcl; ++i)
{
string par2 = parname + "_" + TextTools::toString(i + 1);
for (unsigned int j = 0; j < nummod; ++j)
pMSM2->setNProbability(j, 0);
for (size_t j = 0; j < vvprob[i].size(); ++j)
pMSM2->setNProbability(static_cast<size_t>(vvnmod[i][j]), vvprob[i][j] / vsprob[i]);
if (tl)
delete tl;
if (nhOpt == "no")
tl = new RHomogeneousMixedTreeLikelihood(*tree, *sites, model, rDist, true, false, true);
else
tl = new RNonHomogeneousMixedTreeLikelihood(*tree, *sites, modelSet, rDist, false, true);
tl->initialize();
logL = tl->getValue();
Vdouble vd = tl->getLogLikelihoodForEachSite();
for (unsigned int j = 0; j < nSites; j++)
(*rates)(j, i + 1) = TextTools::toString(vd[j]);
vvd.push_back(vd);
ApplicationTools::displayMessage("\n");
ApplicationTools::displayMessage("Parameter " + par2 + "=" + TextTools::toString(dval[i]) + " with rate=" + TextTools::toString(vRates[i]));
ApplicationTools::displayResult("Log likelihood", TextTools::toString(tl->getValue(), 15));
ApplicationTools::displayResult("Probability", TextTools::toString(vsprob[i], 15));
}
for (unsigned int j = 0; j < nSites; j++)
{
Vdouble vd;
for (unsigned int i = 0; i < nbcl; i++)
vd.push_back(std::log(vsprob[i])+vvd[i][j]);
VectorTools::logNorm(vd);
for (unsigned int i = 0; i < nbcl; i++)
(*rates)(j,nbcl + i + 1) = TextTools::toString(std::exp(vd[i]));
(*rates)(j, 2 * nbcl + 1) = TextTools::toString(VectorTools::sumExp(vd, dval));
}
DataTable::write(*rates, out, "\t");
}
}
delete alphabet;
delete sites;
if (model)
delete model;
if (modelSet)
delete modelSet;
delete rDist;
delete tl;
delete tree;
ApplicationTools::displayMessage("\n");
bppmixedlikelihoods.done();
}
catch (exception& e)
{
cout << e.what() << endl;
return 1;
}
return 0;
}
int main(int args, char ** argv)
{
cout << "******************************************************************" << endl;
cout << "* Bio++ Distance Methods, version 2.2.0 *" << endl;
cout << "* Author: J. Dutheil Created 05/05/07 *" << endl;
cout << "* Last Modif. 04/02/15 *" << endl;
cout << "******************************************************************" << endl;
cout << endl;
if(args == 1)
{
help();
return 0;
}
try {
BppApplication bppdist(args, argv, "BppDist");
bppdist.startTimer();
Alphabet* alphabet = SequenceApplicationTools::getAlphabet(bppdist.getParams(), "", false);
auto_ptr<GeneticCode> gCode;
CodonAlphabet* codonAlphabet = dynamic_cast<CodonAlphabet*>(alphabet);
if (codonAlphabet) {
string codeDesc = ApplicationTools::getStringParameter("genetic_code", bppdist.getParams(), "Standard", "", true, true);
ApplicationTools::displayResult("Genetic Code", codeDesc);
gCode.reset(SequenceApplicationTools::getGeneticCode(codonAlphabet->getNucleicAlphabet(), codeDesc));
}
VectorSiteContainer* allSites = SequenceApplicationTools::getSiteContainer(alphabet, bppdist.getParams());
VectorSiteContainer* sites = SequenceApplicationTools::getSitesToAnalyse(* allSites, bppdist.getParams());
delete allSites;
ApplicationTools::displayResult("Number of sequences", TextTools::toString(sites->getNumberOfSequences()));
ApplicationTools::displayResult("Number of sites", TextTools::toString(sites->getNumberOfSites()));
SubstitutionModel* model = PhylogeneticsApplicationTools::getSubstitutionModel(alphabet, gCode.get(), sites, bppdist.getParams());
DiscreteDistribution* rDist = 0;
if (model->getNumberOfStates() > model->getAlphabet()->getSize())
{
//Markov-modulated Markov model!
rDist = new ConstantRateDistribution();
}
else
{
rDist = PhylogeneticsApplicationTools::getRateDistribution(bppdist.getParams());
}
DistanceEstimation distEstimation(model, rDist, sites, 1, false);
string method = ApplicationTools::getStringParameter("method", bppdist.getParams(), "nj");
ApplicationTools::displayResult("Tree reconstruction method", method);
TreeTemplate<Node>* tree;
AgglomerativeDistanceMethod* distMethod = 0;
if(method == "wpgma")
{
PGMA* wpgma = new PGMA(true);
distMethod = wpgma;
}
else if(method == "upgma")
{
PGMA* upgma = new PGMA(false);
distMethod = upgma;
}
else if(method == "nj")
{
NeighborJoining* nj = new NeighborJoining();
nj->outputPositiveLengths(true);
distMethod = nj;
}
else if(method == "bionj")
{
BioNJ* bionj = new BioNJ();
bionj->outputPositiveLengths(true);
distMethod = bionj;
}
else throw Exception("Unknown tree reconstruction method.");
string type = ApplicationTools::getStringParameter("optimization.method", bppdist.getParams(), "init");
ApplicationTools::displayResult("Model parameters estimation method", type);
if (type == "init") type = OptimizationTools::DISTANCEMETHOD_INIT;
else if (type == "pairwise") type = OptimizationTools::DISTANCEMETHOD_PAIRWISE;
else if (type == "iterations") type = OptimizationTools::DISTANCEMETHOD_ITERATIONS;
else throw Exception("Unknown parameter estimation procedure '" + type + "'.");
unsigned int optVerbose = ApplicationTools::getParameter<unsigned int>("optimization.verbose", bppdist.getParams(), 2);
string mhPath = ApplicationTools::getAFilePath("optimization.message_handler", bppdist.getParams(), false, false);
OutputStream* messenger =
(mhPath == "none") ? 0 :
(mhPath == "std") ? ApplicationTools::message :
new StlOutputStream(new ofstream(mhPath.c_str(), ios::out));
ApplicationTools::displayResult("Message handler", mhPath);
string prPath = ApplicationTools::getAFilePath("optimization.profiler", bppdist.getParams(), false, false);
OutputStream* profiler =
(prPath == "none") ? 0 :
(prPath == "std") ? ApplicationTools::message :
new StlOutputStream(new ofstream(prPath.c_str(), ios::out));
if(profiler) profiler->setPrecision(20);
ApplicationTools::displayResult("Profiler", prPath);
// Should I ignore some parameters?
ParameterList allParameters = model->getParameters();
allParameters.addParameters(rDist->getParameters());
ParameterList parametersToIgnore;
string paramListDesc = ApplicationTools::getStringParameter("optimization.ignore_parameter", bppdist.getParams(), "", "", true, false);
bool ignoreBrLen = false;
StringTokenizer st(paramListDesc, ",");
while (st.hasMoreToken())
{
try
{
string param = st.nextToken();
if (param == "BrLen")
ignoreBrLen = true;
else
{
if (allParameters.hasParameter(param))
{
Parameter* p = &allParameters.getParameter(param);
parametersToIgnore.addParameter(*p);
}
else ApplicationTools::displayWarning("Parameter '" + param + "' not found.");
}
}
catch (ParameterNotFoundException& pnfe)
{
ApplicationTools::displayError("Parameter '" + pnfe.getParameter() + "' not found, and so can't be ignored!");
}
}
unsigned int nbEvalMax = ApplicationTools::getParameter<unsigned int>("optimization.max_number_f_eval", bppdist.getParams(), 1000000);
ApplicationTools::displayResult("Max # ML evaluations", TextTools::toString(nbEvalMax));
double tolerance = ApplicationTools::getDoubleParameter("optimization.tolerance", bppdist.getParams(), .000001);
ApplicationTools::displayResult("Tolerance", TextTools::toString(tolerance));
//Here it is:
ofstream warn("warnings", ios::out);
ApplicationTools::warning = new StlOutputStreamWrapper(&warn);
tree = OptimizationTools::buildDistanceTree(distEstimation, *distMethod, parametersToIgnore, !ignoreBrLen, type, tolerance, nbEvalMax, profiler, messenger, optVerbose);
warn.close();
delete ApplicationTools::warning;
ApplicationTools::warning = ApplicationTools::message;
string matrixPath = ApplicationTools::getAFilePath("output.matrix.file", bppdist.getParams(), false, false, "", false);
if (matrixPath != "none")
{
ApplicationTools::displayResult("Output matrix file", matrixPath);
string matrixFormat = ApplicationTools::getAFilePath("output.matrix.format", bppdist.getParams(), false, false, "", false);
string format = "";
bool extended = false;
std::map<std::string, std::string> unparsedArguments_;
KeyvalTools::parseProcedure(matrixFormat, format, unparsedArguments_);
if (unparsedArguments_.find("type") != unparsedArguments_.end())
{
if (unparsedArguments_["type"] == "extended")
{
extended = true;
}
else if (unparsedArguments_["type"] == "classic")
extended = false;
else
ApplicationTools::displayWarning("Argument '" +
unparsedArguments_["type"] + "' for parameter 'Phylip#type' is unknown. " +
"Default used instead: not extended.");
}
else
ApplicationTools::displayWarning("Argument 'Phylip#type' not found. Default used instead: not extended.");
ODistanceMatrix* odm = IODistanceMatrixFactory().createWriter(IODistanceMatrixFactory::PHYLIP_FORMAT, extended);
odm->write(*distEstimation.getMatrix(), matrixPath, true);
delete odm;
}
PhylogeneticsApplicationTools::writeTree(*tree, bppdist.getParams());
//Output some parameters:
if (type == OptimizationTools::DISTANCEMETHOD_ITERATIONS)
{
// Write parameters to screen:
ParameterList parameters = model->getParameters();
for (unsigned int i = 0; i < parameters.size(); i++)
{
ApplicationTools::displayResult(parameters[i].getName(), TextTools::toString(parameters[i].getValue()));
}
parameters = rDist->getParameters();
for (unsigned int i = 0; i < parameters.size(); i++)
{
ApplicationTools::displayResult(parameters[i].getName(), TextTools::toString(parameters[i].getValue()));
}
// Write parameters to file:
string parametersFile = ApplicationTools::getAFilePath("output.estimates", bppdist.getParams(), false, false);
if (parametersFile != "none")
{
ofstream out(parametersFile.c_str(), ios::out);
parameters = model->getParameters();
for (unsigned int i = 0; i < parameters.size(); i++)
{
out << parameters[i].getName() << " = " << parameters[i].getValue() << endl;
}
parameters = rDist->getParameters();
for (unsigned int i = 0; i < parameters.size(); i++)
{
out << parameters[i].getName() << " = " << parameters[i].getValue() << endl;
}
out.close();
}
}
//Bootstrap:
unsigned int nbBS = ApplicationTools::getParameter<unsigned int>("bootstrap.number", bppdist.getParams(), 0);
if(nbBS > 0)
{
ApplicationTools::displayResult("Number of bootstrap samples", TextTools::toString(nbBS));
bool approx = ApplicationTools::getBooleanParameter("bootstrap.approximate", bppdist.getParams(), true);
ApplicationTools::displayResult("Use approximate bootstrap", TextTools::toString(approx ? "yes" : "no"));
if(approx)
{
type = OptimizationTools::DISTANCEMETHOD_INIT;
parametersToIgnore = allParameters;
ignoreBrLen = true;
}
bool bootstrapVerbose = ApplicationTools::getBooleanParameter("bootstrap.verbose", bppdist.getParams(), false, "", true, false);
string bsTreesPath = ApplicationTools::getAFilePath("bootstrap.output.file", bppdist.getParams(), false, false);
ofstream *out = NULL;
if(bsTreesPath != "none")
{
ApplicationTools::displayResult("Bootstrap trees stored in file", bsTreesPath);
out = new ofstream(bsTreesPath.c_str(), ios::out);
}
Newick newick;
vector<Tree *> bsTrees(nbBS);
ApplicationTools::displayTask("Bootstrapping", true);
for(unsigned int i = 0; i < nbBS; i++)
{
ApplicationTools::displayGauge(i, nbBS-1, '=');
VectorSiteContainer * sample = SiteContainerTools::bootstrapSites(*sites);
if(approx) model->setFreqFromData(*sample);
distEstimation.setData(sample);
bsTrees[i] = OptimizationTools::buildDistanceTree(
distEstimation,
*distMethod,
parametersToIgnore,
ignoreBrLen,
type,
tolerance,
nbEvalMax,
NULL,
NULL,
(bootstrapVerbose ? 1 : 0)
);
if(out && i == 0) newick.write(*bsTrees[i], bsTreesPath, true);
if(out && i > 0) newick.write(*bsTrees[i], bsTreesPath, false);
delete sample;
}
if(out) out->close();
if(out) delete out;
ApplicationTools::displayTaskDone();
ApplicationTools::displayTask("Compute bootstrap values");
TreeTools::computeBootstrapValues(*tree, bsTrees);
ApplicationTools::displayTaskDone();
for(unsigned int i = 0; i < nbBS; i++) delete bsTrees[i];
//Write resulting tree:
PhylogeneticsApplicationTools::writeTree(*tree, bppdist.getParams());
}
delete alphabet;
delete sites;
delete distMethod;
delete tree;
bppdist.done();}
catch(exception & e)
{
cout << e.what() << endl;
return 1;
}
return 0;
}
