Ejemplo n.º 1
0
  /** Calculates the actual rates corresponding to the category indices. */
  protected void setupRates() {

    // System.out.println("BRRRTTZZZ " + distributionIndexParameter.getValue(0));
    for (int i = 0; i < tree.getNodeCount(); i++) {
      // rates[i] = distributionModel.quantile(rateCategoryQuantiles.getNodeValue(
      // rateCategoryQuantiles.getTreeModel(), rateCategoryQuantiles.getTreeModel().getNode(i) ));
      if (!tree.isRoot(tree.getNode(i))) {

        if (useQuantilesForRates) {
            /* Using quantiles to represent rates */
          rates[tree.getNode(i).getNumber()] =
              distributionModels[(int) Math.round(distributionIndexParameter.getValue(0))].quantile(
                  rateCategoryQuantiles.getNodeValue(tree, tree.getNode(i)));
        } else {
            /* Not using quantiles to represent rates. This is practically useless for anything else other than simulation */
          rates[tree.getNode(i).getNumber()] =
              rateCategoryQuantiles.getNodeValue(tree, tree.getNode(i));
        }
      }
    }
    /*System.out.print(distributionModels[(int) Math.round(distributionIndexParameter.getValue(0))].getClass().getName() + "\t" + (int) Math.round(distributionIndexParameter.getValue(0)) + "\t" + rates[1] + "\t" + rateCategoryQuantiles.getNodeValue(tree, tree.getNode(1)));// + "\t" + distributionModels[(int) Math.round(distributionIndexParameter.getValue(0))].);
    if(distributionModels[(int) Math.round(distributionIndexParameter.getValue(0))].getClass().getName().equals("dr.inference.distribution.LogNormalDistributionModel")) {
        LogNormalDistributionModel lndm = (LogNormalDistributionModel) distributionModels[(int) Math.round(distributionIndexParameter.getValue(0))];
        System.out.println("\t" + lndm.getS());
    }
    else if (distributionModels[(int) Math.round(distributionIndexParameter.getValue(0))].getClass().getName().equals("dr.inference.distribution.InverseGaussianDistributionModel")) {
        InverseGaussianDistributionModel lndm = (InverseGaussianDistributionModel) distributionModels[(int) Math.round(distributionIndexParameter.getValue(0))];
        System.out.println("\t" + lndm.getS());
    }*/
    if (normalize) computeFactor();
  }
 /** @return cenancestor */
 public final double getCenancestorBranch() {
   return cenancestorBranch.getValue(0);
 }
 /** @return cenancestor */
 public final double getCenancestorHeight() {
   return cenancestorHeight.getValue(0);
 }