Examples with Taxon dr.evolution.util.Taxon used on opensource projects

Example 31 with Taxon

use of dr.evolution.util.Taxon in project beast-mcmc by beast-dev.

the class BeastGenerator method writeTaxa.

/**
     * Generate a taxa block from these beast options
     *
     * @param writer    the writer
     * @param taxonList the taxon list to write
     * @throws dr.app.util.Arguments.ArgumentException
     *          ArgumentException
     */
private void writeTaxa(TaxonList taxonList, XMLWriter writer) throws Arguments.ArgumentException {
    // -1 (single taxa), 0 (1st gene of multi-taxa)
    writer.writeComment("The list of taxa to be analysed (can also include dates/ages).", "ntax=" + taxonList.getTaxonCount());
    writer.writeOpenTag(TaxaParser.TAXA, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, TaxaParser.TAXA) });
    boolean hasAttr = options.traits.size() > 0;
    boolean firstDate = true;
    for (int i = 0; i < taxonList.getTaxonCount(); i++) {
        Taxon taxon = taxonList.getTaxon(i);
        boolean hasDate = false;
        if (options.clockModelOptions.isTipCalibrated()) {
            hasDate = TaxonList.Utils.hasAttribute(taxonList, i, dr.evolution.util.Date.DATE);
        }
        if (hasDate) {
            dr.evolution.util.Date date = (dr.evolution.util.Date) taxon.getAttribute(dr.evolution.util.Date.DATE);
            if (firstDate) {
                options.units = date.getUnits();
                firstDate = false;
            } else {
                if (options.units != date.getUnits()) {
                    System.err.println("Error: Units in dates do not match.");
                }
            }
        }
        writeTaxon(taxon, hasDate, hasAttr, writer);
    }
    writer.writeCloseTag(TaxaParser.TAXA);
}

Example 32 with Taxon

use of dr.evolution.util.Taxon in project beast-mcmc by beast-dev.

the class BeastGenerator method generateXML.

/**
     * Generate a beast xml file from these beast options
     *
     * @param file File
     * @throws java.io.IOException IOException
     * @throws dr.app.util.Arguments.ArgumentException
     *                             ArgumentException
     */
public void generateXML(File file) throws GeneratorException, IOException, Arguments.ArgumentException {
    XMLWriter writer = new XMLWriter(new BufferedWriter(new FileWriter(file)));
    writer.writeText("<?xml version=\"1.0\" standalone=\"yes\"?>");
    writer.writeComment("Generated by BEAUTi " + version.getVersionString(), "      by Alexei J. Drummond, Andrew Rambaut and Marc A. Suchard", "      Department of Computer Science, University of Auckland and", "      Institute of Evolutionary Biology, University of Edinburgh", "      David Geffen School of Medicine, University of California, Los Angeles", "      http://beast.bio.ed.ac.uk/");
    writer.writeOpenTag("beast");
    writer.writeText("");
    // this gives any added implementations of the 'Component' interface a
    // chance to generate XML at this point in the BEAST file.
    generateInsertionPoint(ComponentGenerator.InsertionPoint.BEFORE_TAXA, writer);
    if (options.originDate != null) {
        // Create a dummy taxon whose job is to specify the origin date
        Taxon originTaxon = new Taxon("originTaxon");
        options.originDate.setUnits(options.units);
        originTaxon.setDate(options.originDate);
        writeTaxon(originTaxon, true, false, writer);
    }
    //++++++++++++++++ Taxon List ++++++++++++++++++
    try {
        // write complete taxon list
        writeTaxa(options.taxonList, writer);
        writer.writeText("");
        if (!options.hasIdenticalTaxa()) {
            // write all taxa in each gene tree regarding each data partition,
            for (AbstractPartitionData partition : options.dataPartitions) {
                if (partition.getTaxonList() != null) {
                    writeDifferentTaxa(partition, writer);
                }
            }
        } else {
            // microsat
            for (PartitionPattern partitionPattern : options.getPartitionPattern()) {
                if (partitionPattern.getTaxonList() != null && partitionPattern.getPatterns().hasMask()) {
                    writeDifferentTaxa(partitionPattern, writer);
                }
            }
        }
    } catch (Exception e) {
        e.printStackTrace(System.err);
        throw new GeneratorException("Taxon list generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ Taxon Sets ++++++++++++++++++
    List<Taxa> taxonSets = options.taxonSets;
    try {
        if (taxonSets != null && taxonSets.size() > 0 && !options.useStarBEAST) {
            tmrcaStatisticsGenerator.writeTaxonSets(writer, taxonSets);
        }
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Taxon sets generation has failed:\n" + e.getMessage());
    }
    generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_TAXA, writer);
    //++++++++++++++++ Alignments ++++++++++++++++++
    List<Alignment> alignments = new ArrayList<Alignment>();
    try {
        for (AbstractPartitionData partition : options.dataPartitions) {
            Alignment alignment = null;
            if (partition instanceof PartitionData) {
                // microsat has no alignment
                alignment = ((PartitionData) partition).getAlignment();
            }
            if (alignment != null && !alignments.contains(alignment)) {
                alignments.add(alignment);
            }
        }
        if (alignments.size() > 0) {
            alignmentGenerator.writeAlignments(alignments, writer);
            generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_SEQUENCES, writer);
        }
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Alignments generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ Pattern Lists ++++++++++++++++++
    try {
        if (!options.samplePriorOnly) {
            List<Microsatellite> microsatList = new ArrayList<Microsatellite>();
            for (AbstractPartitionData partition : options.dataPartitions) {
                // Each PD has one TreeLikelihood
                if (partition.getTaxonList() != null) {
                    switch(partition.getDataType().getType()) {
                        case DataType.NUCLEOTIDES:
                        case DataType.AMINO_ACIDS:
                        case DataType.CODONS:
                        case DataType.COVARION:
                        case DataType.TWO_STATES:
                            patternListGenerator.writePatternList((PartitionData) partition, writer);
                            break;
                        case DataType.GENERAL:
                        case DataType.CONTINUOUS:
                            // attribute patterns which is generated next bit of this method.
                            break;
                        case DataType.MICRO_SAT:
                            // microsat does not have alignment
                            patternListGenerator.writePatternList((PartitionPattern) partition, microsatList, writer);
                            break;
                        default:
                            throw new IllegalArgumentException("Unsupported data type");
                    }
                    writer.writeText("");
                }
            }
        }
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Pattern lists generation has failed:\n" + e.getMessage());
    }
    generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_PATTERNS, writer);
    //++++++++++++++++ Tree Prior Model ++++++++++++++++++
    try {
        for (PartitionTreePrior prior : options.getPartitionTreePriors()) {
            treePriorGenerator.writeTreePriorModel(prior, writer);
            writer.writeText("");
        }
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Tree prior model generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ Starting Tree ++++++++++++++++++
    try {
        for (PartitionTreeModel model : options.getPartitionTreeModels()) {
            initialTreeGenerator.writeStartingTree(model, writer);
            writer.writeText("");
        }
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Starting tree generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ Tree Model +++++++++++++++++++
    try {
        for (PartitionTreeModel model : options.getPartitionTreeModels()) {
            treeModelGenerator.writeTreeModel(model, writer);
            writer.writeText("");
        }
        generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_TREE_MODEL, writer);
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Tree model generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ Statistics ++++++++++++++++++
    try {
        if (taxonSets != null && taxonSets.size() > 0 && !options.useStarBEAST) {
            tmrcaStatisticsGenerator.writeTMRCAStatistics(writer);
        }
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("TMRCA statistics generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ Tree Prior Likelihood ++++++++++++++++++
    try {
        for (PartitionTreeModel model : options.getPartitionTreeModels()) {
            treePriorGenerator.writePriorLikelihood(model, writer);
            writer.writeText("");
        }
        for (PartitionTreePrior prior : options.getPartitionTreePriors()) {
            treePriorGenerator.writeMultiLociTreePriors(prior, writer);
        }
        generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_TREE_PRIOR, writer);
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Tree prior likelihood generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ Branch Rates Model ++++++++++++++++++
    try {
        for (PartitionClockModel model : options.getPartitionClockModels()) {
            clockModelGenerator.writeBranchRatesModel(model, writer);
            writer.writeText("");
        }
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Branch rates model generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ Substitution Model & Site Model ++++++++++++++++++
    try {
        for (PartitionSubstitutionModel model : options.getPartitionSubstitutionModels()) {
            substitutionModelGenerator.writeSubstitutionSiteModel(model, writer);
            writer.writeText("");
        }
        generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_SUBSTITUTION_MODEL, writer);
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Substitution model or site model generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ AllMus parameter ++++++++++++++++++
    try {
        for (PartitionClockModel model : options.getPartitionClockModels()) {
            clockModelGenerator.writeAllMus(model, writer);
        }
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Clock model generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ Site Model ++++++++++++++++++
    //        for (PartitionSubstitutionModel model : options.getPartitionSubstitutionModels()) {
    //            substitutionModelGenerator.writeSiteModel(model, writer); // site model
    //            substitutionModelGenerator.writeAllMus(model, writer); // allMus
    //            writer.writeText("");
    //        }
    generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_SITE_MODEL, writer);
    //++++++++++++++++ Tree Likelihood ++++++++++++++++++
    try {
        AncestralStatesComponentOptions ancestralStatesOptions = (AncestralStatesComponentOptions) options.getComponentOptions(AncestralStatesComponentOptions.class);
        Map<Pair<PartitionTreeModel, DataType>, List<PartitionData>> partitionLists = new HashMap<Pair<PartitionTreeModel, DataType>, List<PartitionData>>();
        List<AbstractPartitionData> otherPartitions = new ArrayList<AbstractPartitionData>();
        for (AbstractPartitionData partition : options.dataPartitions) {
            // generate tree likelihoods for alignment data partitions
            if (partition.getTaxonList() != null) {
                if (partition.getDataType().getType() == DataType.NUCLEOTIDES || partition.getDataType().getType() != DataType.AMINO_ACIDS) {
                    // all sequence partitions of the same type as the first into the list for use in a
                    // MultipartitionTreeDataLikelihood. Must also share the same tree and not be doing
                    // ancestral reconstruction or counting
                    Pair<PartitionTreeModel, DataType> key = new Pair(partition.getPartitionTreeModel(), partition.getDataType());
                    List<PartitionData> partitions = partitionLists.get(key);
                    if (partitions == null) {
                        partitions = new ArrayList<PartitionData>();
                    }
                    partitions.add((PartitionData) partition);
                    partitionLists.put(key, partitions);
                } else {
                    otherPartitions.add(partition);
                }
            }
        }
        for (List<PartitionData> partitions : partitionLists.values()) {
            treeLikelihoodGenerator.writeTreeDataLikelihood(partitions, writer);
            writer.writeText("");
        }
        for (AbstractPartitionData partition : otherPartitions) {
            // generate tree likelihoods for the other data partitions
            if (partition.getTaxonList() != null) {
                if (partition instanceof PartitionData) {
                    treeLikelihoodGenerator.writeTreeLikelihood((PartitionData) partition, writer);
                    writer.writeText("");
                } else if (partition instanceof PartitionPattern) {
                    // microsat
                    treeLikelihoodGenerator.writeTreeLikelihood((PartitionPattern) partition, writer);
                    writer.writeText("");
                } else {
                    throw new GeneratorException("Find unrecognized partition:\n" + partition.getName());
                }
            }
        }
        generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_TREE_LIKELIHOOD, writer);
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Tree likelihood generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ *BEAST ++++++++++++++++++
    if (options.useStarBEAST) {
        //++++++++++++++++ species ++++++++++++++++++
        try {
            starBeastGenerator.writeSpecies(writer);
        } catch (Exception e) {
            e.printStackTrace();
            throw new GeneratorException("*BEAST species section generation has failed:\n" + e.getMessage());
        }
        //++++++++++++++++ Species Sets ++++++++++++++++++
        List<Taxa> speciesSets = options.speciesSets;
        try {
            if (speciesSets != null && speciesSets.size() > 0) {
                tmrcaStatisticsGenerator.writeTaxonSets(writer, speciesSets);
            }
        } catch (Exception e) {
            e.printStackTrace();
            throw new GeneratorException("Species sets generation has failed:\n" + e.getMessage());
        }
        //++++++++++++++++ trees ++++++++++++++++++
        try {
            if (speciesSets != null && speciesSets.size() > 0) {
                starBeastGenerator.writeStartingTreeForCalibration(writer);
            }
            starBeastGenerator.writeSpeciesTree(writer, speciesSets != null && speciesSets.size() > 0);
        } catch (Exception e) {
            e.printStackTrace();
            throw new GeneratorException("*BEAST trees generation has failed:\n" + e.getMessage());
        }
        //++++++++++++++++ Statistics ++++++++++++++++++
        try {
            if (speciesSets != null && speciesSets.size() > 0) {
                tmrcaStatisticsGenerator.writeTMRCAStatistics(writer);
            }
        } catch (Exception e) {
            e.printStackTrace();
            throw new GeneratorException("*BEAST TMRCA statistics generation has failed:\n" + e.getMessage());
        }
        //++++++++++++++++ prior and likelihood ++++++++++++++++++
        try {
            starBeastGenerator.writeSTARBEAST(writer);
        } catch (Exception e) {
            e.printStackTrace();
            throw new GeneratorException("*BEAST trees section generation has failed:\n" + e.getMessage());
        }
    }
    generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_TRAITS, writer);
    //++++++++++++++++ Operators ++++++++++++++++++
    try {
        generateInsertionPoint(ComponentGenerator.InsertionPoint.BEFORE_OPERATORS, writer);
        List<Operator> operators = options.selectOperators();
        operatorsGenerator.writeOperatorSchedule(operators, writer);
        writer.writeText("");
        generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_OPERATORS, writer);
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Operators generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++ MCMC ++++++++++++++++++
    try {
        // XMLWriter writer, List<PartitionSubstitutionModel> models,
        writeMCMC(writer);
        writer.writeText("");
        generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_MCMC, writer);
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("MCMC or log generation has failed:\n" + e.getMessage());
    }
    //++++++++++++++++  ++++++++++++++++++
    try {
        writeTimerReport(writer);
        writer.writeText("");
        if (options.performTraceAnalysis) {
            writeTraceAnalysis(writer);
        }
        if (options.generateCSV) {
            for (PartitionTreePrior prior : options.getPartitionTreePriors()) {
                treePriorGenerator.writeEBSPAnalysisToCSVfile(prior, writer);
            }
        }
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("The last part of XML generation has failed:\n" + e.getMessage());
    }
    writer.writeCloseTag("beast");
    writer.flush();
    writer.close();
}

Example 33 with Taxon

use of dr.evolution.util.Taxon in project beast-mcmc by beast-dev.

the class BeastGenerator method writeDifferentTaxa.

public void writeDifferentTaxa(AbstractPartitionData dataPartition, XMLWriter writer) {
    TaxonList taxonList = dataPartition.getTaxonList();
    String name = dataPartition.getPartitionTreeModel().getName();
    writer.writeComment("gene name = " + name + ", ntax= " + taxonList.getTaxonCount());
    writer.writeOpenTag(TaxaParser.TAXA, new Attribute[] { new Attribute.Default<String>(XMLParser.ID, name + "." + TaxaParser.TAXA) });
    for (int i = 0; i < taxonList.getTaxonCount(); i++) {
        if (!(dataPartition instanceof PartitionPattern && ((PartitionPattern) dataPartition).getPatterns().isMasked(i))) {
            final Taxon taxon = taxonList.getTaxon(i);
            writer.writeIDref(TaxonParser.TAXON, taxon.getId());
        }
    }
    writer.writeCloseTag(TaxaParser.TAXA);
}

Example 34 with Taxon

use of dr.evolution.util.Taxon in project beast-mcmc by beast-dev.

the class DateGuesser method guessDates.

public void guessDates(TaxonList taxonList, Map<Taxon, String> taxonDateMap) {
    // To avoid duplicating code, add all the taxa into a list and
    // pass it to guessDates(List<Taxon> taxonList)
    List<Taxon> taxa = new ArrayList<Taxon>();
    for (Taxon taxon : taxonList) {
        taxa.add(taxon);
    }
    guessDates(taxa, taxonDateMap);
}

Example 35 with Taxon

use of dr.evolution.util.Taxon in project beast-mcmc by beast-dev.

the class TipDateSamplingComponentOptions method selectOperators.

public void selectOperators(final ModelOptions modelOptions, final List<Operator> ops) {
    if (tipDateSamplingType == TipDateSamplingType.SAMPLE_INDIVIDUALLY || tipDateSamplingType == TipDateSamplingType.SAMPLE_PRECISION) {
        TaxonList taxa = getTaxonSet();
        String description = "Random walk for the age of this tip";
        //OperatorType type = OperatorType.RANDOM_WALK_ABSORBING;
        OperatorType type = OperatorType.UNIFORM;
        if (tipDateSamplingType == TipDateSamplingType.SAMPLE_PRECISION) {
            description = "Uniform sample from precision of age of this tip";
        //type = OperatorType.UNIFORM;
        }
        for (int i = 0; i < taxa.getTaxonCount(); i++) {
            Taxon taxon = taxa.getTaxon(i);
            Operator operator = tipDateOperators.get(taxon);
            if (operator == null) {
                Parameter parameter = getTipDateParameter(taxon);
                //                    operator = new Operator("age(" + taxon.getId() + ")", "", parameter, OperatorType.SCALE, 0.75, 1.0);
                operator = new Operator.Builder("age(" + taxon.getId() + ")", description, parameter, type, 1.0, 1.0).build();
                if (tipDateSamplingType == TipDateSamplingType.SAMPLE_INDIVIDUALLY) {
                    operator.setWeight(2.0);
                }
                tipDateOperators.put(taxon, operator);
            }
            ops.add(operator);
        }
    } else if (tipDateSamplingType == TipDateSamplingType.SAMPLE_JOINT) {
        ops.add(modelOptions.getOperator("treeModel.tipDates"));
    }
}