Examples with ParametricDistributionModel dr.inference.distribution.ParametricDistributionModel used on opensource projects

Example 6 with ParametricDistributionModel

use of dr.inference.distribution.ParametricDistributionModel in project beast-mcmc by beast-dev.

the class OrnsteinUhlenbeckPriorLikelihoodParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    Parameter mean = getParam(xo, MEAN);
    Parameter sigma = getParam(xo, SIGMA);
    Parameter lambda = getParam(xo, LAMBDA);
    final boolean logSpace = xo.getAttribute(LOG_SPACE, false);
    final boolean normalize = xo.getAttribute(NORMALIZE, false);
    VariableDemographicModel m = (VariableDemographicModel) xo.getChild(VariableDemographicModel.class);
    if (m != null) {
        ParametricDistributionModel popMeanPrior = (ParametricDistributionModel) xo.getChild(ParametricDistributionModel.class);
        return new OrnsteinUhlenbeckPriorLikelihood(mean, sigma, lambda, m, logSpace, normalize, popMeanPrior);
    }
    final XMLObject cxo1 = xo.getChild(DATA);
    Parameter dataParameter = (Parameter) cxo1.getChild(Parameter.class);
    final XMLObject cxo2 = xo.getChild(TIMES);
    final Parameter timesParameter = (Parameter) cxo2.getChild(Parameter.class);
    return new OrnsteinUhlenbeckPriorLikelihood(mean, sigma, lambda, dataParameter, timesParameter, logSpace, normalize);
}

Example 7 with ParametricDistributionModel

use of dr.inference.distribution.ParametricDistributionModel in project beast-mcmc by beast-dev.

the class MixtureModelBranchRates method handleModelChangedEvent.

public void handleModelChangedEvent(Model model, Object object, int index) {
    //System.out.println("if you dont know: " + model.getClass().getName());
    for (ParametricDistributionModel distributionModel : distributionModels) {
        if (model == distributionModel) {
            setupRates();
            fireModelChanged();
        }
    //else if (model == rateCategories) {
    // AR - commented out: if just the rate categories have changed the rates will be the same
    //            setupRates();
    //  fireModelChanged(null, index);
    //}
    }
    if (model == rateCategoryQuantiles) {
        // Maybe
        setupRates();
        //rateCategories.fireModelChanged();
        fireModelChanged(null, index);
    }
/*else if(model == distributionIndexParameter) { // Not a model
            setupRates();
        }*/
/*else if (model == treeModel) {
            setupRates(); // Maybe
        }*/
}

Example 8 with ParametricDistributionModel

use of dr.inference.distribution.ParametricDistributionModel in project beast-mcmc by beast-dev.

the class OldCoalescentSimulatorParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    CoalescentSimulator simulator = new CoalescentSimulator();
    DemographicModel demoModel = (DemographicModel) xo.getChild(DemographicModel.class);
    List<TaxonList> taxonLists = new ArrayList<TaxonList>();
    List<Tree> subtrees = new ArrayList<Tree>();
    double rootHeight = xo.getAttribute(ROOT_HEIGHT, -1.0);
    if (xo.hasAttribute(RESCALE_HEIGHT)) {
        rootHeight = xo.getDoubleAttribute(RESCALE_HEIGHT);
    }
    // should have one child that is node
    for (int i = 0; i < xo.getChildCount(); i++) {
        final Object child = xo.getChild(i);
        // AER - swapped the order of these round because Trees are TaxonLists...
        if (child instanceof Tree) {
            subtrees.add((Tree) child);
        } else if (child instanceof TaxonList) {
            taxonLists.add((TaxonList) child);
        } else if (xo.getChildName(i).equals(CONSTRAINED_TAXA)) {
            XMLObject constrainedTaxa = (XMLObject) child;
            // all taxa
            final TaxonList taxa = (TaxonList) constrainedTaxa.getChild(TaxonList.class);
            List<CoalescentSimulator.TaxaConstraint> constraints = new ArrayList<CoalescentSimulator.TaxaConstraint>();
            final String setsNotCompatibleMessage = "taxa sets not compatible";
            for (int nc = 0; nc < constrainedTaxa.getChildCount(); ++nc) {
                final Object object = constrainedTaxa.getChild(nc);
                if (object instanceof XMLObject) {
                    final XMLObject constraint = (XMLObject) object;
                    if (constraint.getName().equals(TMRCA_CONSTRAINT)) {
                        TaxonList taxaSubSet = (TaxonList) constraint.getChild(TaxonList.class);
                        ParametricDistributionModel dist = (ParametricDistributionModel) constraint.getChild(ParametricDistributionModel.class);
                        boolean isMono = constraint.getAttribute(IS_MONOPHYLETIC, true);
                        final CoalescentSimulator.TaxaConstraint taxaConstraint = new CoalescentSimulator.TaxaConstraint(taxaSubSet, dist, isMono);
                        int insertPoint;
                        for (insertPoint = 0; insertPoint < constraints.size(); ++insertPoint) {
                            // if new <= constraints[insertPoint] insert before insertPoint
                            final CoalescentSimulator.TaxaConstraint iConstraint = constraints.get(insertPoint);
                            if (iConstraint.isMonophyletic) {
                                if (!taxaConstraint.isMonophyletic) {
                                    continue;
                                }
                                final TaxonList taxonsip = iConstraint.taxons;
                                final int nIn = simulator.sizeOfIntersection(taxonsip, taxaSubSet);
                                if (nIn == taxaSubSet.getTaxonCount()) {
                                    break;
                                }
                                if (nIn > 0 && nIn != taxonsip.getTaxonCount()) {
                                    throw new XMLParseException(setsNotCompatibleMessage);
                                }
                            } else {
                                // reached non mono area
                                if (!taxaConstraint.isMonophyletic) {
                                    if (iConstraint.upper >= taxaConstraint.upper) {
                                        break;
                                    }
                                } else {
                                    break;
                                }
                            }
                        }
                        constraints.add(insertPoint, taxaConstraint);
                    }
                }
            }
            final int nConstraints = constraints.size();
            if (nConstraints == 0) {
                if (taxa != null) {
                    taxonLists.add(taxa);
                }
            } else {
                for (int nc = 0; nc < nConstraints; ++nc) {
                    CoalescentSimulator.TaxaConstraint cnc = constraints.get(nc);
                    if (!cnc.isMonophyletic) {
                        for (int nc1 = nc - 1; nc1 >= 0; --nc1) {
                            CoalescentSimulator.TaxaConstraint cnc1 = constraints.get(nc1);
                            int x = simulator.sizeOfIntersection(cnc.taxons, cnc1.taxons);
                            if (x > 0) {
                                Taxa combinedTaxa = new Taxa(cnc.taxons);
                                combinedTaxa.addTaxa(cnc1.taxons);
                                cnc = new CoalescentSimulator.TaxaConstraint(combinedTaxa, cnc.lower, cnc.upper, cnc.isMonophyletic);
                                constraints.set(nc, cnc);
                            }
                        }
                    }
                }
                // determine upper bound for each set.
                double[] upper = new double[nConstraints];
                for (int nc = nConstraints - 1; nc >= 0; --nc) {
                    final CoalescentSimulator.TaxaConstraint cnc = constraints.get(nc);
                    if (cnc.realLimits()) {
                        upper[nc] = cnc.upper;
                    } else {
                        upper[nc] = Double.POSITIVE_INFINITY;
                    }
                }
                for (int nc = nConstraints - 1; nc >= 0; --nc) {
                    final CoalescentSimulator.TaxaConstraint cnc = constraints.get(nc);
                    if (upper[nc] < Double.POSITIVE_INFINITY) {
                        for (int nc1 = nc - 1; nc1 >= 0; --nc1) {
                            final CoalescentSimulator.TaxaConstraint cnc1 = constraints.get(nc1);
                            if (simulator.contained(cnc1.taxons, cnc.taxons)) {
                                upper[nc1] = Math.min(upper[nc1], upper[nc]);
                                if (cnc1.realLimits() && cnc1.lower > upper[nc1]) {
                                    throw new XMLParseException(setsNotCompatibleMessage);
                                }
                                break;
                            }
                        }
                    }
                }
                // collect subtrees here
                List<Tree> st = new ArrayList<Tree>();
                for (int nc = 0; nc < constraints.size(); ++nc) {
                    final CoalescentSimulator.TaxaConstraint nxt = constraints.get(nc);
                    // collect all previously built subtrees which are a subset of taxa set to be added
                    List<Tree> subs = new ArrayList<Tree>();
                    Taxa newTaxons = new Taxa(nxt.taxons);
                    for (int k = 0; k < st.size(); ++k) {
                        final Tree stk = st.get(k);
                        int x = simulator.sizeOfIntersection(stk, nxt.taxons);
                        if (x == st.get(k).getTaxonCount()) {
                            final Tree tree = st.remove(k);
                            --k;
                            subs.add(tree);
                            newTaxons.removeTaxa(tree);
                        }
                    }
                    SimpleTree tree = simulator.simulateTree(newTaxons, demoModel);
                    final double lower = nxt.realLimits() ? nxt.lower : 0;
                    if (upper[nc] < Double.MAX_VALUE) {
                        simulator.attemptToScaleTree(tree, (lower + upper[nc]) / 2);
                    }
                    if (subs.size() > 0) {
                        if (tree.getTaxonCount() > 0)
                            subs.add(tree);
                        double h = -1;
                        if (upper[nc] < Double.MAX_VALUE) {
                            for (Tree t : subs) {
                                // protect against 1 taxa tree with height 0
                                final double rh = t.getNodeHeight(t.getRoot());
                                h = Math.max(h, rh > 0 ? rh : (lower + upper[nc]) / 2);
                            }
                            h = (h + upper[nc]) / 2;
                        }
                        tree = simulator.simulateTree(subs.toArray(new Tree[subs.size()]), demoModel, h, true);
                    }
                    st.add(tree);
                }
                // add a taxon list for remaining taxa
                if (taxa != null) {
                    final Taxa list = new Taxa();
                    for (int j = 0; j < taxa.getTaxonCount(); ++j) {
                        Taxon taxonj = taxa.getTaxon(j);
                        for (Tree aSt : st) {
                            if (aSt.getTaxonIndex(taxonj) >= 0) {
                                taxonj = null;
                                break;
                            }
                        }
                        if (taxonj != null) {
                            list.addTaxon(taxonj);
                        }
                    }
                    if (list.getTaxonCount() > 0) {
                        taxonLists.add(list);
                    }
                }
                if (st.size() > 1) {
                    final Tree t = simulator.simulateTree(st.toArray(new Tree[st.size()]), demoModel, -1, false);
                    subtrees.add(t);
                } else {
                    subtrees.add(st.get(0));
                }
            }
        }
    }
    if (taxonLists.size() == 0) {
        if (subtrees.size() == 1) {
            return subtrees.get(0);
        }
        throw new XMLParseException("Expected at least one taxonList or two subtrees in " + getParserName() + " element.");
    }
    try {
        Tree[] trees = new Tree[taxonLists.size() + subtrees.size()];
        // simulate each taxonList separately
        for (int i = 0; i < taxonLists.size(); i++) {
            trees[i] = simulator.simulateTree(taxonLists.get(i), demoModel);
        }
        // add the preset trees
        for (int i = 0; i < subtrees.size(); i++) {
            trees[i + taxonLists.size()] = subtrees.get(i);
        }
        return simulator.simulateTree(trees, demoModel, rootHeight, trees.length != 1);
    } catch (IllegalArgumentException iae) {
        throw new XMLParseException(iae.getMessage());
    }
}

Example 9 with ParametricDistributionModel

use of dr.inference.distribution.ParametricDistributionModel in project beast-mcmc by beast-dev.

the class BMPriorLikelihoodParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    // Parameter mean = getParam(xo, MEAN);
    Parameter sigma = getParam(xo, SIGMA);
    //  Parameter lambda = getParam(xo, LAMBDA);
    final boolean logSpace = xo.getAttribute(LOG_SPACE, false);
    //   final boolean normalize = xo.getAttribute(NORMALIZE, false);
    VariableDemographicModel m = (VariableDemographicModel) xo.getChild(VariableDemographicModel.class);
    ParametricDistributionModel popMeanPrior = (ParametricDistributionModel) xo.getChild(ParametricDistributionModel.class);
    return new BMPriorLikelihood(sigma, m, logSpace, popMeanPrior);
}

Example 10 with ParametricDistributionModel

use of dr.inference.distribution.ParametricDistributionModel in project beast-mcmc by beast-dev.

the class TipHeightLikelihoodParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    ParametricDistributionModel model = (ParametricDistributionModel) xo.getElementFirstChild(DISTRIBUTION);
    Parameter tipHeights = (Parameter) xo.getElementFirstChild(TIP_HEIGHTS);
    return new TipHeightLikelihood(model, tipHeights);
}