use of dr.evomodel.speciation.CalibrationPoints in project beast-mcmc by beast-dev.
the class SpeciationLikelihoodParser method parseXMLObject.
public Object parseXMLObject(XMLObject xo) throws XMLParseException {
XMLObject cxo = xo.getChild(MODEL);
final SpeciationModel specModel = (SpeciationModel) cxo.getChild(SpeciationModel.class);
cxo = xo.getChild(TREE);
final Tree tree = (Tree) cxo.getChild(Tree.class);
Set<Taxon> excludeTaxa = null;
if (xo.hasChildNamed(INCLUDE)) {
excludeTaxa = new HashSet<Taxon>();
for (int i = 0; i < tree.getTaxonCount(); i++) {
excludeTaxa.add(tree.getTaxon(i));
}
cxo = xo.getChild(INCLUDE);
for (int i = 0; i < cxo.getChildCount(); i++) {
TaxonList taxonList = (TaxonList) cxo.getChild(i);
for (int j = 0; j < taxonList.getTaxonCount(); j++) {
excludeTaxa.remove(taxonList.getTaxon(j));
}
}
}
if (xo.hasChildNamed(EXCLUDE)) {
excludeTaxa = new HashSet<Taxon>();
cxo = xo.getChild(EXCLUDE);
for (int i = 0; i < cxo.getChildCount(); i++) {
TaxonList taxonList = (TaxonList) cxo.getChild(i);
for (int j = 0; j < taxonList.getTaxonCount(); j++) {
excludeTaxa.add(taxonList.getTaxon(j));
}
}
}
if (excludeTaxa != null) {
Logger.getLogger("dr.evomodel").info("Speciation model excluding " + excludeTaxa.size() + " taxa from prior - " + (tree.getTaxonCount() - excludeTaxa.size()) + " taxa remaining.");
}
final XMLObject cal = xo.getChild(CALIBRATION);
if (cal != null) {
if (excludeTaxa != null) {
throw new XMLParseException("Sorry, not implemented: internal calibration prior + excluded taxa");
}
List<Distribution> dists = new ArrayList<Distribution>();
List<Taxa> taxa = new ArrayList<Taxa>();
List<Boolean> forParent = new ArrayList<Boolean>();
// (Statistic) cal.getChild(Statistic.class);
Statistic userPDF = null;
for (int k = 0; k < cal.getChildCount(); ++k) {
final Object ck = cal.getChild(k);
if (DistributionLikelihood.class.isInstance(ck)) {
dists.add(((DistributionLikelihood) ck).getDistribution());
} else if (Distribution.class.isInstance(ck)) {
dists.add((Distribution) ck);
} else if (Taxa.class.isInstance(ck)) {
final Taxa tx = (Taxa) ck;
taxa.add(tx);
forParent.add(tx.getTaxonCount() == 1);
} else if (Statistic.class.isInstance(ck)) {
if (userPDF != null) {
throw new XMLParseException("more than one userPDF correction???");
}
userPDF = (Statistic) cal.getChild(Statistic.class);
} else {
XMLObject cko = (XMLObject) ck;
assert cko.getChildCount() == 2;
for (int i = 0; i < 2; ++i) {
final Object chi = cko.getChild(i);
if (DistributionLikelihood.class.isInstance(chi)) {
dists.add(((DistributionLikelihood) chi).getDistribution());
} else if (Distribution.class.isInstance(chi)) {
dists.add((Distribution) chi);
} else if (Taxa.class.isInstance(chi)) {
taxa.add((Taxa) chi);
boolean fp = ((Taxa) chi).getTaxonCount() == 1;
if (cko.hasAttribute(PARENT)) {
boolean ufp = cko.getBooleanAttribute(PARENT);
if (fp && !ufp) {
throw new XMLParseException("forParent==false for a single taxon?? (must be true)");
}
fp = ufp;
}
forParent.add(fp);
} else {
assert false;
}
}
}
}
if (dists.size() != taxa.size()) {
throw new XMLParseException("Mismatch in number of distributions and taxa specs");
}
try {
final String correction = cal.getAttribute(CORRECTION, EXACT);
final CalibrationPoints.CorrectionType type = correction.equals(EXACT) ? CalibrationPoints.CorrectionType.EXACT : (correction.equals(APPROX) ? CalibrationPoints.CorrectionType.APPROXIMATED : (correction.equals(NONE) ? CalibrationPoints.CorrectionType.NONE : (correction.equals(PEXACT) ? CalibrationPoints.CorrectionType.PEXACT : null)));
if (cal.hasAttribute(CORRECTION) && type == null) {
throw new XMLParseException("correction type == " + correction + "???");
}
final CalibrationPoints calib = new CalibrationPoints(tree, specModel.isYule(), dists, taxa, forParent, userPDF, type);
final SpeciationLikelihood speciationLikelihood = new SpeciationLikelihood(tree, specModel, null, calib);
return speciationLikelihood;
} catch (IllegalArgumentException e) {
throw new XMLParseException(e.getMessage());
}
}
return new SpeciationLikelihood(tree, specModel, excludeTaxa, null);
}
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