public String toString() {
return "Constant Independent("
+ pal.misc.Utils.toString(parameterStore_)
+ " - > "
+ pal.misc.Utils.toString(getDistribution())
+ ")";
}
public String toString() {
StringBuffer sb = new StringBuffer();
for (int i = 0; i < numberOfSites_; i++) {
double[] sitePosteriors = getSitePosteriors(i);
sb.append(pal.misc.Utils.argmax(sitePosteriors));
sb.append(" - ");
sb.append("Site ");
sb.append((i + 1));
sb.append(":");
sb.append(pal.misc.Utils.toString(sitePosteriors));
sb.append("\n");
}
return sb.toString();
}
public SimpleSiteDetails(
double[][] categoryPatternConditionalProbabilities,
boolean isLoggedConditionals,
SubstitutionModel model,
int numberOfPatterns,
int[] sitePatternMatchup,
int numberOfSites,
double[] siteLikelihoods) {
final int numberOfCategories = model.getNumberOfTransitionCategories();
this.siteLikelihoods_ = pal.misc.Utils.getCopy(siteLikelihoods);
this.siteLogLikelihoods_ = new double[numberOfSites];
double llh = 0;
for (int i = 0; i < numberOfSites; i++) {
this.siteLogLikelihoods_[i] = Math.log(this.siteLikelihoods_[i]);
llh += this.siteLogLikelihoods_[i];
}
System.out.println("Total:" + llh);
if (isLoggedConditionals) {
this.categoryPatternConditionalProbabilities_ =
convertLogged(
categoryPatternConditionalProbabilities, numberOfCategories, numberOfPatterns);
} else {
this.categoryPatternConditionalProbabilities_ =
pal.misc.Utils.getCopy(categoryPatternConditionalProbabilities);
}
this.numberOfSites_ = numberOfSites;
this.sitePatternMatchup_ = pal.misc.Utils.getCopy(sitePatternMatchup);
this.patternPosteriors_ = new double[numberOfPatterns][numberOfCategories];
for (int p = 0; p < numberOfPatterns; p++) {
double total = 0;
for (int c = 0; c < numberOfCategories; c++) {
total += categoryPatternConditionalProbabilities[c][p];
}
for (int c = 0; c < numberOfCategories; c++) {
patternPosteriors_[p][c] = categoryPatternConditionalProbabilities[c][p] / total;
}
}
this.model_ = model;
}
