/**
* @param tree
* @param node
* @return and array of the total amount of time spent in each of the discrete states along the
* branch above the given node.
*/
private double[] getProcessValues(final Tree tree, final NodeRef node) {
double[] processValues = null;
double branchTime = tree.getBranchLength(node);
if (mode == Mode.MARKOV_JUMP_PROCESS) {
processValues = (double[]) trait.getTrait(tree, node);
} else if (mode == Mode.PARSIMONY) {
// an approximation to dwell times using parsimony, assuming
// the state changes midpoint on the tree. Does a weighted
// average of the equally parsimonious state reconstructions
// at the top and bottom of each branch.
if (treeChanged) {
fitchParsimony.initialize(tree);
// Debugging test to count work
// treeInitializeCounter += 1;
// if (treeInitializeCounter % 10 == 0) {
// System.err.println("Cnt: "+treeInitializeCounter);
// }
treeChanged = false;
}
int[] states = fitchParsimony.getStates(tree, node);
int[] parentStates = fitchParsimony.getStates(tree, tree.getParent(node));
processValues = new double[fitchParsimony.getPatterns().getStateCount()];
for (int state : states) {
processValues[state] += branchTime / 2;
}
for (int state : parentStates) {
processValues[state] += branchTime / 2;
}
for (int i = 0; i < processValues.length; i++) {
// normalize by the number of equally parsimonious states at each end of the branch
// processValues should add up to the total branch length
processValues[i] /= (states.length + parentStates.length) / 2;
}
} else if (mode == Mode.NODE_STATES) {
processValues = new double[dataType.getStateCount()];
// if (indicatorParameter != null) {
// // this array should be size #states NOT #rates
// processValues = new double[indicatorParameter.getDimension()];
// } else {
// // this array should be size #states NOT #rates
// processValues = new double[rateParameter.getDimension()];
// }
// if the states are being sampled - then there is only one possible state at each
// end of the branch.
int state = ((int[]) trait.getTrait(tree, node))[traitIndex];
processValues[state] += branchTime / 2;
int parentState = ((int[]) trait.getTrait(tree, tree.getParent(node)))[traitIndex];
processValues[parentState] += branchTime / 2;
}
return processValues;
}
/**
* A constructor for a node-sampled discrete trait
*
* @param treeModel
* @param trait
* @param traitIndex
* @param rateParameter
* @param relativeRatesParameter
* @param indicatorParameter
*/
public DiscreteTraitBranchRateModel(
TreeTraitProvider traitProvider,
DataType dataType,
TreeModel treeModel,
TreeTrait trait,
int traitIndex,
Parameter rateParameter,
Parameter relativeRatesParameter,
Parameter indicatorParameter) {
this(treeModel, traitIndex, rateParameter, relativeRatesParameter, indicatorParameter);
// if (trait.getTreeModel() != treeModel)
// throw new IllegalArgumentException("Tree Models for ancestral state tree
// likelihood and target model of these rates must match!");
this.trait = trait;
this.dataType = dataType;
if (trait.getTraitName().equals("states")) {
// Assume the trait is one or more discrete traits reconstructed at nodes
mode = Mode.NODE_STATES;
} else /*if (double[].class.isAssignableFrom(trait.getClass()))*/ {
// Assume the trait itself is the dwell times for the individual states on the branch above
// the node
mode = Mode.MARKOV_JUMP_PROCESS;
} /* else {
throw new IllegalArgumentException("The trait class type is not suitable for use in this class.");
} */
if (traitProvider instanceof Model) {
addModel((Model) traitProvider);
}
if (trait instanceof Model) {
addModel((Model) trait); // MAS: Does this ever occur?
}
}