public PopsIOSpeciesTreeModel(
PopsIOSpeciesBindings piosb, Parameter popPriorScale, PriorComponent[] priorComponents) {
super(PopsIOSpeciesTreeModelParser.PIO_SPECIES_TREE);
this.piosb = piosb;
this.popPriorScale = popPriorScale;
addVariable(popPriorScale);
popPriorScale.addBounds(new Parameter.DefaultBounds(Double.POSITIVE_INFINITY, 0.0, 1));
this.priorComponents = priorComponents;
PopsIOSpeciesBindings.SpInfo[] species = piosb.getSpecies();
int nTaxa = species.length;
int nNodes = 2 * nTaxa - 1;
pionodes = new PopsIONode[nNodes];
for (int n = 0; n < nNodes; n++) {
pionodes[n] = new PopsIONode(n);
}
ArrayList<Integer> tojoin = new ArrayList<Integer>(nTaxa);
for (int n = 0; n < nTaxa; n++) {
pionodes[n].setTaxon(species[n].name);
pionodes[n].setHeight(0.0);
pionodes[n].setUnion(piosb.tipUnionFromTaxon(pionodes[n].getTaxon()));
tojoin.add(n);
}
double rate = 1.0;
double treeheight = 0.0;
for (int i = 0; i < nTaxa - 1; i++) {
int numtojoin = tojoin.size();
int j = MathUtils.nextInt(numtojoin);
Integer child0 = tojoin.get(j);
tojoin.remove(j);
int k = MathUtils.nextInt(numtojoin - 1);
Integer child1 = tojoin.get(k);
tojoin.remove(k);
pionodes[nTaxa + i].addChildren(pionodes[child0], pionodes[child1]);
pionodes[nTaxa + i].setHeight(treeheight + randomnodeheight(numtojoin * rate));
treeheight = pionodes[nTaxa + i].getHeight();
tojoin.add(nTaxa + i);
}
rootn = pionodes.length - 1;
double scale = 0.99 * piosb.initialMinGeneNodeHeight() / pionodes[rootn].height;
scaleAllHeights(scale);
pionodes[rootn].fillinUnionsInSubtree(piosb.getSpecies().length);
stree = makeSimpleTree();
Logger.getLogger("dr.evomodel.speciation.popsio")
.info(
"\tConstructing a PopsIO Species Tree Model, please cite:\n"
+ Citable.Utils.getCitationString(this));
}
public WeightedMixtureModel(
List<AbstractModelLikelihood> likelihoodList, Parameter mixtureWeights) {
super(MIXTURE_MODEL);
this.likelihoodList = likelihoodList;
this.mixtureWeights = mixtureWeights;
for (AbstractModelLikelihood model : likelihoodList) {
addModel(model);
}
addVariable(mixtureWeights);
StringBuilder sb = new StringBuilder();
sb.append("Constructing a finite mixture model\n");
sb.append("\tComponents:\n");
for (AbstractModelLikelihood model : likelihoodList) {
sb.append("\t\t\t").append(model.getId()).append("\n");
}
sb.append("\tMixing parameter: ").append(mixtureWeights.getId()).append("\n");
sb.append("\tPlease cite:\n");
sb.append(Citable.Utils.getCitationString((this)));
Logger.getLogger("dr.inference.model").info(sb.toString());
}
public static Transform[] parseListOfTransforms(XMLObject xo, int maxDim)
throws XMLParseException {
Transform[] transforms = null;
boolean anyTransforms = false;
for (int i = 0; i < xo.getChildCount(); ++i) {
if (xo.getChild(i) instanceof Transform.ParsedTransform) {
Transform.ParsedTransform t = (Transform.ParsedTransform) xo.getChild(i);
if (transforms == null) {
transforms = Transform.Util.getListOfNoTransforms(maxDim);
}
t.end = Math.max(t.end, maxDim);
if (t.start < 0 || t.end < 0 || t.start > t.end) {
throw new XMLParseException("Invalid bounds for transform in " + xo.getId());
}
for (int j = t.start; j < t.end; j += t.every) {
transforms[j] = t.transform;
anyTransforms = true;
}
}
}
if (anyTransforms) {
StringBuilder sb =
new StringBuilder("Using distributional transforms in " + xo.getId() + "\n");
for (int i = 0; i < transforms.length; ++i) {
if (transforms[i] != Transform.NONE) {
sb.append("\t")
.append(transforms[i].getTransformName())
.append(" on index ")
.append(i + 1)
.append("\n");
}
}
sb.append("Please cite:\n").append(Citable.Utils.getCitationString(Transform.LOG));
Logger.getLogger("dr.utils.Transform").info(sb.toString());
}
return transforms;
}
