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 void drawTreeIndex() {
// System.err.print("Drawing new tree, (old tree = " + currentTreeIndex);
currentTreeIndex = MathUtils.nextInt(trees.length);
// System.err.println(") new tree = " + currentTreeIndex);
fireModelChanged(new TreeModel.TreeChangedEvent());
}
@Override
public double doOperation() throws OperatorFailedException {
apspnet.beginNetworkEdit();
double b = (1.0 - scalingFactor) * (1.0 - scalingFactor) / scalingFactor;
double c = scalingFactor / (1.0 - scalingFactor);
double y = MathUtils.nextDouble();
double s = b * (y + c) * (y + c);
int i = MathUtils.nextInt(apspnet.getNumberOfTetraTrees());
apspnet.setOneHybPopValue(i, s * apspnet.getOneHybPopValue(i));
apspnet.endNetworkEdit();
return 0.0; // this way of scaling, with proposal proportional to x^-(1/2) has hastings ratio 1
}
/** change the parameter and return the hastings ratio. */
public double doOperation() throws OperatorFailedException {
double[] mean = sccs.getMode();
double[] currentValue = parameter.getParameterValues();
double[] newValue = new double[dim];
Set<Integer> updateSet = new HashSet<Integer>();
if (setSizeMean != -1.0) {
final int listLength = Poisson.nextPoisson(setSizeMean);
while (updateSet.size() < listLength) {
int newInt = MathUtils.nextInt(parameter.getDimension());
if (!updateSet.contains(newInt)) {
updateSet.add(newInt);
}
}
} else {
for (int i = 0; i < dim; ++i) {
updateSet.add(i);
}
}
double logq = 0;
for (Integer i : updateSet) {
newValue[i] = mean[i] + scaleFactor * MathUtils.nextGaussian();
if (UPDATE_ALL) {
parameter.setParameterValueQuietly(i, newValue[i]);
} else {
parameter.setParameterValue(i, newValue[i]);
}
logq +=
(NormalDistribution.logPdf(currentValue[i], mean[i], scaleFactor)
- NormalDistribution.logPdf(newValue[i], mean[i], scaleFactor));
}
// for (Integer i : updateSet) {
// parameter.setParameterValueQuietly(i, newValue[i]);
// }
if (UPDATE_ALL) {
parameter.setParameterValueNotifyChangedAll(0, parameter.getParameterValue(0));
}
return logq;
}
public void proposeTree() throws OperatorFailedException {
TreeModel tree = c2cLikelihood.getTreeModel();
BranchMapModel branchMap = c2cLikelihood.getBranchMap();
NodeRef i;
double oldMinAge, newMinAge, newRange, oldRange, newAge, q;
// choose a random node avoiding root, and nodes that are ineligible for this move because they
// have nowhere to
// go
final int nodeCount = tree.getNodeCount();
do {
i = tree.getNode(MathUtils.nextInt(nodeCount));
} while (tree.getRoot() == i || !eligibleForMove(i, tree, branchMap));
final NodeRef iP = tree.getParent(i);
// this one can go anywhere
NodeRef j = tree.getNode(MathUtils.nextInt(tree.getNodeCount()));
NodeRef k = tree.getParent(j);
while ((k != null && tree.getNodeHeight(k) <= tree.getNodeHeight(i)) || (i == j)) {
j = tree.getNode(MathUtils.nextInt(tree.getNodeCount()));
k = tree.getParent(j);
}
if (iP == tree.getRoot() || j == tree.getRoot()) {
throw new OperatorFailedException("Root changes not allowed!");
}
if (k == iP || j == iP || k == i) throw new OperatorFailedException("move failed");
final NodeRef CiP = getOtherChild(tree, iP, i);
NodeRef PiP = tree.getParent(iP);
newMinAge = Math.max(tree.getNodeHeight(i), tree.getNodeHeight(j));
newRange = tree.getNodeHeight(k) - newMinAge;
newAge = newMinAge + (MathUtils.nextDouble() * newRange);
oldMinAge = Math.max(tree.getNodeHeight(i), tree.getNodeHeight(CiP));
oldRange = tree.getNodeHeight(PiP) - oldMinAge;
q = newRange / Math.abs(oldRange);
// need to account for the random repainting of iP
if (branchMap.get(PiP.getNumber()) != branchMap.get(CiP.getNumber())) {
q *= 0.5;
}
if (branchMap.get(k.getNumber()) != branchMap.get(j.getNumber())) {
q *= 2;
}
tree.beginTreeEdit();
if (j == tree.getRoot()) {
// 1. remove edges <iP, CiP>
tree.removeChild(iP, CiP);
tree.removeChild(PiP, iP);
// 2. add edges <k, iP>, <iP, j>, <PiP, CiP>
tree.addChild(iP, j);
tree.addChild(PiP, CiP);
// iP is the new root
tree.setRoot(iP);
} else if (iP == tree.getRoot()) {
// 1. remove edges <k, j>, <iP, CiP>, <PiP, iP>
tree.removeChild(k, j);
tree.removeChild(iP, CiP);
// 2. add edges <k, iP>, <iP, j>, <PiP, CiP>
tree.addChild(iP, j);
tree.addChild(k, iP);
// CiP is the new root
tree.setRoot(CiP);
} else {
// 1. remove edges <k, j>, <iP, CiP>, <PiP, iP>
tree.removeChild(k, j);
tree.removeChild(iP, CiP);
tree.removeChild(PiP, iP);
// 2. add edges <k, iP>, <iP, j>, <PiP, CiP>
tree.addChild(iP, j);
tree.addChild(k, iP);
tree.addChild(PiP, CiP);
}
tree.setNodeHeight(iP, newAge);
tree.endTreeEdit();
//
logq = Math.log(q);
// repaint the parent to match either its new parent or its new child (50% chance of each).
if (MathUtils.nextInt(2) == 0) {
branchMap.set(iP.getNumber(), branchMap.get(k.getNumber()), true);
} else {
branchMap.set(iP.getNumber(), branchMap.get(j.getNumber()), true);
}
if (DEBUG) {
c2cLikelihood.checkPartitions();
}
}
/** change the parameter and return the hastings ratio. */
public final double doOperation() {
int index = MathUtils.nextInt(links.getDimension());
int oldGroup = (int) assignments.getParameterValue(index);
/*
* Set index customer link to index and all connected to it to a new assignment (min value empty)
*/
int minEmp = minEmpty(modelLikelihood.getLogLikelihoodsVector());
links.setParameterValue(index, index);
int[] visited = connected(index, links);
int ii = 0;
while (visited[ii] != 0) {
assignments.setParameterValue(visited[ii] - 1, minEmp);
ii++;
}
/*
* Adjust likvector for group separated
*/
modelLikelihood.setLogLikelihoodsVector(oldGroup, getLogLikGroup(oldGroup));
modelLikelihood.setLogLikelihoodsVector(minEmp, getLogLikGroup(minEmp));
int maxFull = maxFull(modelLikelihood.getLogLikelihoodsVector());
double[] liks = modelLikelihood.getLogLikelihoodsVector();
/*
* computing likelihoods of joint groups
*/
double[] crossedLiks = new double[maxFull + 1];
for (int ll = 0; ll < maxFull + 1; ll++) {
if (ll != minEmp) {
crossedLiks[ll] = getLogLik2Group(ll, minEmp);
}
}
/*
* Add logPrior
*/
double[] logP = new double[links.getDimension()];
for (int jj = 0; jj < links.getDimension(); jj++) {
logP[jj] += depMatrix[index][jj];
int n = (int) assignments.getParameterValue(jj);
if (n != minEmp) {
logP[jj] += crossedLiks[n] - liks[n] - liks[minEmp];
}
}
logP[index] = Math.log(chiParameter.getParameterValue(0));
/*
* possibilidade de mandar p zero as probs muito pequenas
*/
/*
* Gibbs sampling
*/
this.rescale(logP); // Improve numerical stability
this.exp(logP); // Transform back to probability-scale
int k = MathUtils.randomChoicePDF(logP);
links.setParameterValue(index, k);
int newGroup = (int) assignments.getParameterValue(k);
ii = 0;
while (visited[ii] != 0) {
assignments.setParameterValue(visited[ii] - 1, newGroup);
ii++;
}
/*
* updating conditional likelihood vector
*/
modelLikelihood.setLogLikelihoodsVector(newGroup, getLogLikGroup(newGroup));
if (newGroup != minEmp) {
modelLikelihood.setLogLikelihoodsVector(minEmp, 0);
}
sampleMeans(maxFull);
return 0.0;
}
public void operateOneNode(final double factor) throws OperatorFailedException {
// #print "operate: tree", ut.treerep(t)
// if( verbose) System.out.println(" Mau at start: " + tree.getSimpleTree());
final int count = multree.getExternalNodeCount();
assert count == species.nSpSeqs();
NodeRef[] order = new NodeRef[2 * count - 1];
boolean[] swapped = new boolean[count - 1];
mauCanonical(multree, order, swapped);
// internal node to change
// count-1 - number of internal nodes
int which = MathUtils.nextInt(count - 1);
FixedBitSet left = new FixedBitSet(count);
FixedBitSet right = new FixedBitSet(count);
for (int k = 0; k < 2 * which + 1; k += 2) {
left.set(multree.speciesIndex(order[k]));
}
for (int k = 2 * (which + 1); k < 2 * count; k += 2) {
right.set(multree.speciesIndex(order[k]));
}
double newHeight;
if (factor > 0) {
newHeight = multree.getNodeHeight(order[2 * which + 1]) * factor;
} else {
final double limit = species.speciationUpperBound(left, right);
newHeight = MathUtils.nextDouble() * limit;
}
multree.beginTreeEdit();
multree.setPreorderIndices(preOrderIndexBefore);
final NodeRef node = order[2 * which + 1];
multree.setNodeHeight(node, newHeight);
mauReconstruct(multree, order, swapped);
// restore pre-order of pops -
{
multree.setPreorderIndices(preOrderIndexAfter);
double[] splitPopValues = null;
for (int k = 0; k < preOrderIndexBefore.length; ++k) {
final int b = preOrderIndexBefore[k];
if (b >= 0) {
final int a = preOrderIndexAfter[k];
if (a != b) {
// if( verbose) System.out.println("pops: " + a + " <- " + b);
final Parameter p1 = multree.sppSplitPopulations;
if (splitPopValues == null) {
splitPopValues = p1.getParameterValues();
}
if (multree.constPopulation()) {
p1.setParameterValue(count + a, splitPopValues[count + b]);
} else {
for (int i = 0; i < 2; ++i) {
p1.setParameterValue(count + 2 * a + i, splitPopValues[count + 2 * b + i]);
}
}
}
}
}
}
multree.endTreeEdit();
}