Examples with DataType dr.evolution.datatype.DataType used on opensource projects

Example 21 with DataType

use of dr.evolution.datatype.DataType in project beast-mcmc by beast-dev.

the class CompleteHistorySimulatorParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    int nReplications = xo.getIntegerAttribute(REPLICATIONS);
    Tree tree = (Tree) xo.getChild(Tree.class);
    GammaSiteRateModel siteModel = (GammaSiteRateModel) xo.getChild(GammaSiteRateModel.class);
    BranchRateModel rateModel = (BranchRateModel) xo.getChild(BranchRateModel.class);
    if (rateModel == null)
        rateModel = new DefaultBranchRateModel();
    DataType dataType = siteModel.getSubstitutionModel().getDataType();
    String jumpTag = xo.getAttribute(JUMP_TAG_NAME, JUMP_TAG);
    boolean sumAcrossSites = xo.getAttribute(SUM_SITES, false);
    Parameter branchSpecificParameter = null;
    Parameter variableValueParameter = null;
    if (xo.hasChildNamed(BRANCH_SPECIFIC_SPECIFICATION)) {
        XMLObject cxo = xo.getChild(BRANCH_SPECIFIC_SPECIFICATION);
        branchSpecificParameter = (Parameter) cxo.getChild(BRANCH_VARIABLE_PARAMETER).getChild(Parameter.class);
        variableValueParameter = (Parameter) cxo.getChild(VARIABLE_VALUE_PARAMETER).getChild(Parameter.class);
    }
    CompleteHistorySimulator history = new CompleteHistorySimulator(tree, siteModel, rateModel, nReplications, sumAcrossSites, branchSpecificParameter, variableValueParameter);
    XMLObject cxo = xo.getChild(COUNTS);
    if (cxo != null) {
        MarkovJumpsTreeLikelihoodParser.parseAllChildren(cxo, history, dataType.getStateCount(), jumpTag, MarkovJumpsType.COUNTS, false);
    }
    cxo = xo.getChild(REWARDS);
    if (cxo != null) {
        MarkovJumpsTreeLikelihoodParser.parseAllChildren(cxo, history, dataType.getStateCount(), jumpTag, MarkovJumpsType.REWARDS, false);
    }
    if (dataType instanceof Codons) {
        Codons codons = (Codons) dataType;
        if (xo.getAttribute(SYN_JUMPS, false)) {
            // use base 61
            double[] synRegMatrix = CodonLabeling.getRegisterMatrix(CodonLabeling.SYN, codons, false);
            Parameter registerParameter = new Parameter.Default(synRegMatrix);
            registerParameter.setId("S");
            history.addRegister(registerParameter, MarkovJumpsType.COUNTS, false);
        }
        if (xo.getAttribute(NON_SYN_JUMPS, false)) {
            // use base 61
            double[] nonSynRegMatrix = CodonLabeling.getRegisterMatrix(CodonLabeling.NON_SYN, codons, false);
            Parameter registerParameter = new Parameter.Default(nonSynRegMatrix);
            registerParameter.setId("N");
            history.addRegister(registerParameter, MarkovJumpsType.COUNTS, false);
        }
    }
    if (xo.getAttribute(ANNOTATE_WITH_ALIGNMENT, false)) {
        history.addAlignmentTrait();
    }
    boolean alignmentOnly = xo.getAttribute(ALIGNMENT_ONLY, false);
    if (dataType instanceof Codons && !alignmentOnly) {
        System.out.println("Codon models give exception when count statistics are done on them. " + "You can supress this by setting alignmentOnly to true.");
    }
    if (alignmentOnly) {
        history.setAlignmentOnly();
    }
    history.simulate();
    return history;
}

Example 22 with DataType

use of dr.evolution.datatype.DataType 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.community/");
    writer.writeOpenTag("beast", new Attribute.Default<String>("version", BeautiApp.VERSION.getVersion()));
    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) {
            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 {
        // Construct pattern lists even if sampling from a null alignment
        // 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) {
            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 {
        Map<Pair<Pair<PartitionTreeModel, PartitionClockModel>, DataType>, List<PartitionData>> partitionLists = new HashMap<Pair<Pair<PartitionTreeModel, PartitionClockModel>, DataType>, List<PartitionData>>();
        options.multiPartitionLists.clear();
        options.otherPartitions.clear();
        for (AbstractPartitionData partition : options.dataPartitions) {
            // generate tree likelihoods for alignment data partitions
            if (partition.getTaxonList() != null) {
                if (treeLikelihoodGenerator.canUseMultiPartition(partition)) {
                    // all sequence partitions of the same type as the first into the list for use in a
                    // MultipartitionTreeDataLikelihood. Must also share the same tree, clock model and not be doing
                    // ancestral reconstruction or counting
                    Pair<Pair<PartitionTreeModel, PartitionClockModel>, DataType> key = new Pair(new Pair(partition.getPartitionTreeModel(), partition.getPartitionClockModel()), partition.getDataType());
                    List<PartitionData> partitions = partitionLists.get(key);
                    if (partitions == null) {
                        partitions = new ArrayList<PartitionData>();
                        options.multiPartitionLists.add(partitions);
                    }
                    partitions.add((PartitionData) partition);
                    partitionLists.put(key, partitions);
                } else {
                    options.otherPartitions.add(partition);
                }
            }
        }
        treeLikelihoodGenerator.writeAllTreeLikelihoods(writer);
        generateInsertionPoint(ComponentGenerator.InsertionPoint.AFTER_TREE_LIKELIHOOD, writer);
    } catch (Exception e) {
        e.printStackTrace();
        throw new GeneratorException("Tree likelihood 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 23 with DataType

use of dr.evolution.datatype.DataType in project beast-mcmc by beast-dev.

the class SiteModelsPanel method setCurrentModels.

private void setCurrentModels(List<PartitionSubstitutionModel> models) {
    modelPanelParent.removeAll();
    currentModel = null;
    Set<DataType> dataTypes = new HashSet<DataType>();
    for (PartitionSubstitutionModel model : models) {
        dataTypes.add(model.getDataType());
    }
    if (dataTypes.size() == 1) {
        DataType dataType = dataTypes.iterator().next();
        modelBorder.setTitle("Multiple " + dataType.getName() + " substitution models selected");
    } else {
        modelBorder.setTitle("Multiple mixed type substitution models selected");
    }
    cloneModelsAction.setEnabled(dataTypes.size() == 1);
    repaint();
}

Example 24 with DataType

use of dr.evolution.datatype.DataType in project beast-mcmc by beast-dev.

the class PartitionData method createFrequencyModel.

public FrequencyModel createFrequencyModel() {
    FrequencyModel frequencyModel = null;
    if (this.frequencyModelIndex == 0) {
        // Nucleotidefrequencies
        Parameter freqs = new Parameter.Default(new double[] { frequencyParameterValues[0], frequencyParameterValues[1], frequencyParameterValues[2], frequencyParameterValues[3] });
        DataType dataType = this.createDataType();
        frequencyModel = new FrequencyModel(dataType, freqs);
    } else if (this.frequencyModelIndex == 1) {
        Parameter freqs = new Parameter.Default(new double[] { frequencyParameterValues[4], frequencyParameterValues[5], frequencyParameterValues[6], frequencyParameterValues[7], frequencyParameterValues[8], frequencyParameterValues[9], frequencyParameterValues[10], frequencyParameterValues[11], frequencyParameterValues[12], frequencyParameterValues[13], frequencyParameterValues[14], frequencyParameterValues[15], frequencyParameterValues[16], frequencyParameterValues[17], frequencyParameterValues[18], frequencyParameterValues[19], frequencyParameterValues[20], frequencyParameterValues[21], frequencyParameterValues[22], frequencyParameterValues[23], frequencyParameterValues[24], frequencyParameterValues[25], frequencyParameterValues[26], frequencyParameterValues[27], frequencyParameterValues[28], frequencyParameterValues[29], frequencyParameterValues[30], frequencyParameterValues[31], frequencyParameterValues[32], frequencyParameterValues[33], frequencyParameterValues[34], frequencyParameterValues[35], frequencyParameterValues[36], frequencyParameterValues[37], frequencyParameterValues[38], frequencyParameterValues[39], frequencyParameterValues[40], frequencyParameterValues[41], frequencyParameterValues[42], frequencyParameterValues[43], frequencyParameterValues[44], frequencyParameterValues[45], frequencyParameterValues[46], frequencyParameterValues[47], frequencyParameterValues[48], frequencyParameterValues[49], frequencyParameterValues[50], frequencyParameterValues[51], frequencyParameterValues[52], frequencyParameterValues[53], frequencyParameterValues[54], frequencyParameterValues[55], frequencyParameterValues[56], frequencyParameterValues[57], frequencyParameterValues[58], frequencyParameterValues[59], frequencyParameterValues[60], frequencyParameterValues[61], frequencyParameterValues[62], frequencyParameterValues[63], frequencyParameterValues[64] });
        DataType dataType = this.createDataType();
        frequencyModel = new FrequencyModel(dataType, freqs);
    } else if (this.frequencyModelIndex == 2) {
        Parameter freqs = new Parameter.Default(new double[] { frequencyParameterValues[65], frequencyParameterValues[66], frequencyParameterValues[67], frequencyParameterValues[68], frequencyParameterValues[69], frequencyParameterValues[70], frequencyParameterValues[71], frequencyParameterValues[72], frequencyParameterValues[73], frequencyParameterValues[74], frequencyParameterValues[75], frequencyParameterValues[76], frequencyParameterValues[77], frequencyParameterValues[78], frequencyParameterValues[79], frequencyParameterValues[80], frequencyParameterValues[81], frequencyParameterValues[82], frequencyParameterValues[83], frequencyParameterValues[84] });
        DataType dataType = this.createDataType();
        frequencyModel = new FrequencyModel(dataType, freqs);
    } else {
        System.out.println("Not yet implemented");
    }
    return frequencyModel;
}

Example 25 with DataType

use of dr.evolution.datatype.DataType in project beast-mcmc by beast-dev.

the class XMLGenerator method writeFrequencyModel.

// END: writeBranchModel
private void writeFrequencyModel(PartitionData data, XMLWriter writer) {
    DataType dataType = null;
    String frequencies = null;
    // int dataTypeIndex = data.dataTypeIndex;
    int frequencyModelIndex = data.frequencyModelIndex;
    switch(frequencyModelIndex) {
        case // Nucleotide
        0:
            dataType = data.createDataType();
            // dataType = Nucleotides.INSTANCE;
            frequencies = data.frequencyParameterValues[0] + "";
            for (int i = 1; i < 4; i++) {
                frequencies += " " + data.frequencyParameterValues[i];
            }
            // tagname
            writer.writeOpenTag(// tagname
            FrequencyModelParser.FREQUENCY_MODEL, new Attribute[] { // attributes[]
            new Attribute.Default<String>(XMLParser.ID, // id
            data.frequencyModelIdref), new Attribute.Default<String>(DataType.DATA_TYPE, // dataType
            dataType.getDescription()) });
            writeParameter(FrequencyModelParser.FREQUENCIES, null, dataType.getStateCount(), frequencies, writer);
            writer.writeCloseTag(FrequencyModelParser.FREQUENCY_MODEL);
            break;
        case // Codon
        1:
            dataType = data.createDataType();
            // dataType = Codons.UNIVERSAL;
            frequencies = data.frequencyParameterValues[4] + "";
            for (int i = 5; i < 65; i++) {
                frequencies += " " + data.frequencyParameterValues[i];
            }
            // tagname
            writer.writeOpenTag(// tagname
            FrequencyModelParser.FREQUENCY_MODEL, new Attribute[] { // attributes[]
            new Attribute.Default<String>(XMLParser.ID, // id
            data.frequencyModelIdref), new Attribute.Default<String>(DataType.DATA_TYPE, // dataType.getDescription()
            Utils.CODON_UNIVERSAL) // dataType
            });
            writeParameter(FrequencyModelParser.FREQUENCIES, null, dataType.getStateCount(), frequencies, writer);
            writer.writeCloseTag(FrequencyModelParser.FREQUENCY_MODEL);
            break;
        case // Amino acid
        2:
            dataType = data.createDataType();
            // dataType = AminoAcids.INSTANCE;
            frequencies = data.frequencyParameterValues[65] + "";
            for (int i = 66; i < 85; i++) {
                frequencies += " " + data.frequencyParameterValues[i];
            }
            // tagname
            writer.writeOpenTag(// tagname
            FrequencyModelParser.FREQUENCY_MODEL, new Attribute[] { // attributes[]
            new Attribute.Default<String>(XMLParser.ID, // id
            data.frequencyModelIdref), new Attribute.Default<String>(DataType.DATA_TYPE, // dataType.getDescription()
            AminoAcids.DESCRIPTION) // dataType
            });
            writeParameter(FrequencyModelParser.FREQUENCIES, null, dataType.getStateCount(), frequencies, writer);
            writer.writeCloseTag(FrequencyModelParser.FREQUENCY_MODEL);
            break;
    }
// END: switch
}