Examples with Parameter dr.inference.model.Parameter used on opensource projects

Example 66 with Parameter

use of dr.inference.model.Parameter in project beast-mcmc by beast-dev.

the class SitePatternsParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    Alignment alignment = (Alignment) xo.getChild(Alignment.class);
    TaxonList taxa = null;
    int from = 0;
    int to = -1;
    int every = xo.getAttribute(EVERY, 1);
    boolean strip = xo.getAttribute(STRIP, true);
    boolean unique = xo.getAttribute(UNIQUE, true);
    if (xo.hasAttribute(FROM)) {
        from = xo.getIntegerAttribute(FROM) - 1;
        if (from < 0)
            throw new XMLParseException("illegal 'from' attribute in patterns element");
    }
    if (xo.hasAttribute(TO)) {
        to = xo.getIntegerAttribute(TO) - 1;
        if (to < 0 || to < from)
            throw new XMLParseException("illegal 'to' attribute in patterns element");
    }
    if (every <= 0)
        throw new XMLParseException("illegal 'every' attribute in patterns element");
    if (xo.hasChildNamed(TAXON_LIST)) {
        taxa = (TaxonList) xo.getElementFirstChild(TAXON_LIST);
    }
    int[] constantPatternCounts = null;
    if (xo.hasChildNamed(CONSTANT_PATTERNS)) {
        Parameter param = (Parameter) xo.getElementFirstChild(CONSTANT_PATTERNS);
        if (param.getDimension() != alignment.getStateCount()) {
            throw new XMLParseException("The " + CONSTANT_PATTERNS + " parameter length should be equal to the number of states");
        }
        constantPatternCounts = new int[param.getDimension()];
        int i = 0;
        for (double value : param.getParameterValues()) {
            constantPatternCounts[i] = (int) value;
            i++;
        }
    }
    if (from > alignment.getSiteCount())
        throw new XMLParseException("illegal 'from' attribute in patterns element");
    if (to > alignment.getSiteCount())
        throw new XMLParseException("illegal 'to' attribute in patterns element");
    SitePatterns patterns = new SitePatterns(alignment, taxa, from, to, every, strip, unique, constantPatternCounts);
    int f = from + 1;
    // fixed a *display* error by adding + 1 for consistency with f = from + 1
    int t = to + 1;
    if (to == -1)
        t = alignment.getSiteCount();
    if (xo.hasAttribute(XMLParser.ID)) {
        final Logger logger = Logger.getLogger("dr.evoxml");
        logger.info("Site patterns '" + xo.getId() + "' created from positions " + Integer.toString(f) + "-" + Integer.toString(t) + " of alignment '" + alignment.getId() + "'");
        if (every > 1) {
            logger.info("  only using every " + every + " site");
        }
        logger.info("  " + (unique ? "unique " : "") + "pattern count = " + patterns.getPatternCount());
    }
    return patterns;
}

Example 67 with Parameter

use of dr.inference.model.Parameter in project beast-mcmc by beast-dev.

the class GeoSpatialDistribution method main.

public static void main(String[] args) {
    //test reading in KML file with multiple polygons and fillValue attribute
    List<AbstractPolygon2D> polygons = Polygon2D.readKMLFile("Multiple_polygons/9.285_105.7244444.kml");
    System.out.println(polygons.size() + " polygons found.");
    //check if all the polygons have either a fillValue or do not have this fillValue
    AbstractPolygon2D first = polygons.get(0);
    boolean equalFills = first.hasFillValue();
    if (polygons.size() > 1) {
        for (int i = 1; i < polygons.size(); i++) {
            if (!(equalFills == polygons.get(i).hasFillValue())) {
                System.out.println("Inconsistent fillValue attributes provided.");
            }
        }
    }
    if (equalFills) {
        double sum = 0.0;
        for (AbstractPolygon2D region : polygons) {
            sum += region.getFillValue();
        }
        if (Math.abs(sum - 1.0) > 1E-12) {
            System.out.println("\nFill values do not sum to 1 : " + sum);
        }
    }
    boolean overAllFill = equalFills;
    List<GeoSpatialDistribution> geoSpatialDistributions = new ArrayList<GeoSpatialDistribution>();
    for (AbstractPolygon2D region : polygons) {
        geoSpatialDistributions.add(new GeoSpatialDistribution("test", region, false));
    }
    MultivariateDistributionLikelihood likelihood = new MultivariateDistributionLikelihood(new MultiRegionGeoSpatialDistribution("multi", geoSpatialDistributions, false, overAllFill));
    Parameter.Default parameter = new Parameter.Default("coordinate", 2);
    likelihood.addData(parameter);
    double logL = likelihood.calculateLogLikelihood();
    System.out.println("\n(" + parameter.getParameterValue(0) + "," + parameter.getParameterValue(1) + ")");
    System.out.println("logL = " + logL);
    System.out.println("L = " + Math.exp(logL));
    parameter.setParameterValue(0, 11.40);
    parameter.setParameterValue(1, 106.90);
    likelihood.makeDirty();
    logL = likelihood.calculateLogLikelihood();
    System.out.println("\n(" + parameter.getParameterValue(0) + "," + parameter.getParameterValue(1) + ")");
    System.out.println("logL = " + logL);
    System.out.println("L = " + Math.exp(logL));
    //test reading in KML file with a single polygon without fillValue attribute
    polygons = Polygon2D.readKMLFile("Districts_polygons/21.035_106.063.kml");
    System.out.println("\n" + polygons.size() + " polygons found.");
    first = polygons.get(0);
    equalFills = first.hasFillValue();
    if (polygons.size() > 1) {
        for (int i = 1; i < polygons.size(); i++) {
            if (!(equalFills == polygons.get(i).hasFillValue())) {
                System.out.println("Inconsistent fillValue attributes provided.");
            }
        }
    }
    if (equalFills) {
        double sum = 0.0;
        for (AbstractPolygon2D region : polygons) {
            sum += region.getFillValue();
        }
        if (Math.abs(sum - 1.0) > 1E-12) {
            System.out.println("\nFill values do not sum to 1 : " + sum);
        }
    }
    overAllFill = equalFills;
    geoSpatialDistributions = new ArrayList<GeoSpatialDistribution>();
    for (AbstractPolygon2D region : polygons) {
        geoSpatialDistributions.add(new GeoSpatialDistribution("test", region, false));
    }
    likelihood = new MultivariateDistributionLikelihood(new MultiRegionGeoSpatialDistribution("multi", geoSpatialDistributions, false, overAllFill));
    likelihood.addData(parameter);
    logL = likelihood.calculateLogLikelihood();
    System.out.println("\n(" + parameter.getParameterValue(0) + "," + parameter.getParameterValue(1) + ")");
    System.out.println("logL = " + logL);
    System.out.println("L = " + Math.exp(logL));
    parameter.setParameterValue(0, 21.0);
    parameter.setParameterValue(1, 106.03);
    likelihood.makeDirty();
    logL = likelihood.calculateLogLikelihood();
    System.out.println("\n(" + parameter.getParameterValue(0) + "," + parameter.getParameterValue(1) + ")");
    System.out.println("logL = " + logL);
    System.out.println("L = " + Math.exp(logL));
    parameter.setParameterValue(0, 21.0);
    parameter.setParameterValue(1, 106.10);
    likelihood.makeDirty();
    logL = likelihood.calculateLogLikelihood();
    System.out.println("\n(" + parameter.getParameterValue(0) + "," + parameter.getParameterValue(1) + ")");
    System.out.println("logL = " + logL);
    System.out.println("L = " + Math.exp(logL));
}

Example 68 with Parameter

use of dr.inference.model.Parameter in project beast-mcmc by beast-dev.

the class EmpiricalCodonModelParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    Codons codons = Codons.UNIVERSAL;
    if (xo.hasAttribute(GeneticCode.GENETIC_CODE)) {
        String codeStr = xo.getStringAttribute(GeneticCode.GENETIC_CODE);
        if (codeStr.equals(GeneticCode.UNIVERSAL.getName())) {
            codons = Codons.UNIVERSAL;
        } else if (codeStr.equals(GeneticCode.VERTEBRATE_MT.getName())) {
            codons = Codons.VERTEBRATE_MT;
        } else if (codeStr.equals(GeneticCode.YEAST.getName())) {
            codons = Codons.YEAST;
        } else if (codeStr.equals(GeneticCode.MOLD_PROTOZOAN_MT.getName())) {
            codons = Codons.MOLD_PROTOZOAN_MT;
        } else if (codeStr.equals(GeneticCode.INVERTEBRATE_MT.getName())) {
            codons = Codons.INVERTEBRATE_MT;
        } else if (codeStr.equals(GeneticCode.CILIATE.getName())) {
            codons = Codons.CILIATE;
        } else if (codeStr.equals(GeneticCode.ECHINODERM_MT.getName())) {
            codons = Codons.ECHINODERM_MT;
        } else if (codeStr.equals(GeneticCode.EUPLOTID_NUC.getName())) {
            codons = Codons.EUPLOTID_NUC;
        } else if (codeStr.equals(GeneticCode.BACTERIAL.getName())) {
            codons = Codons.BACTERIAL;
        } else if (codeStr.equals(GeneticCode.ALT_YEAST.getName())) {
            codons = Codons.ALT_YEAST;
        } else if (codeStr.equals(GeneticCode.ASCIDIAN_MT.getName())) {
            codons = Codons.ASCIDIAN_MT;
        } else if (codeStr.equals(GeneticCode.FLATWORM_MT.getName())) {
            codons = Codons.FLATWORM_MT;
        } else if (codeStr.equals(GeneticCode.BLEPHARISMA_NUC.getName())) {
            codons = Codons.BLEPHARISMA_NUC;
        } else if (codeStr.equals(GeneticCode.NO_STOPS.getName())) {
            codons = Codons.NO_STOPS;
        }
    }
    Parameter omegaParam = (Parameter) xo.getElementFirstChild(OMEGA);
    Parameter kappaParam = null;
    Parameter mntParam = null;
    if (xo.hasChildNamed(KAPPATSTV)) {
        kappaParam = (Parameter) xo.getElementFirstChild(KAPPATSTV);
        if (kappaParam.getDimension() != 2 && kappaParam.getDimension() != 9) {
            throw new XMLParseException("If you use the kappa parameter, you need to enter exactly\n" + "two values for ts and tv or nine values\n" + "according to the Kosiol ECM+F+omega+9k model");
        }
    } else {
        mntParam = (Parameter) xo.getElementFirstChild(MULTI_NT_CHANGE);
    }
    String dirString = xo.getStringAttribute(ECM_DATA_DIR);
    String freqString = xo.getStringAttribute(ECM_FREQ_MATRIX);
    String matString = xo.getStringAttribute(ECM_DATA_MATRIX);
    EmpiricalCodonRateMatrix rateMat = new EmpiricalCodonRateMatrix(EMPIRICAL_RATE_MATRIX, codons, dirString, freqString, matString);
    // get frequencies from XML, from frequency csv file or estimate from data
    FrequencyModel freqModel = null;
    if (xo.getChild(FrequencyModel.class) != null) {
        freqModel = (FrequencyModel) xo.getChild(FrequencyModel.class);
    } else {
        freqModel = createNewFreqModel(codons, rateMat);
    }
    return new EmpiricalCodonModel(codons, omegaParam, kappaParam, mntParam, rateMat, freqModel);
}

Example 69 with Parameter

use of dr.inference.model.Parameter in project beast-mcmc by beast-dev.

the class FrequencyModelParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    DataType dataType = DataTypeUtils.getDataType(xo);
    Parameter freqsParam = (Parameter) xo.getElementFirstChild(FREQUENCIES);
    double[] frequencies = null;
    for (int i = 0; i < xo.getChildCount(); i++) {
        Object obj = xo.getChild(i);
        if (obj instanceof PatternList) {
            frequencies = ((PatternList) obj).getStateFrequencies();
            break;
        }
    }
    StringBuilder sb = new StringBuilder("Creating state frequencies model '" + freqsParam.getParameterName() + "': ");
    if (frequencies != null) {
        if (freqsParam.getDimension() != frequencies.length) {
            throw new XMLParseException("dimension of frequency parameter and number of sequence states don't match!");
        }
        for (int j = 0; j < frequencies.length; j++) {
            freqsParam.setParameterValue(j, frequencies[j]);
        }
        sb.append("Using empirical frequencies from data ");
    } else {
        sb.append("Initial frequencies ");
    }
    sb.append("= {");
    double sum = 0;
    for (int j = 0; j < freqsParam.getDimension(); j++) {
        sum += freqsParam.getParameterValue(j);
    }
    if (xo.getAttribute(NORMALIZE, false)) {
        for (int j = 0; j < freqsParam.getDimension(); j++) {
            if (sum != 0)
                freqsParam.setParameterValue(j, freqsParam.getParameterValue(j) / sum);
            else
                freqsParam.setParameterValue(j, 1.0 / freqsParam.getDimension());
        }
        sum = 1.0;
    }
    if (Math.abs(sum - 1.0) > 1e-8) {
        throw new XMLParseException("Frequencies do not sum to 1 (they sum to " + sum + ")");
    }
    NumberFormat format = NumberFormat.getNumberInstance();
    format.setMaximumFractionDigits(5);
    sb.append(format.format(freqsParam.getParameterValue(0)));
    for (int j = 1; j < freqsParam.getDimension(); j++) {
        sb.append(", ");
        sb.append(format.format(freqsParam.getParameterValue(j)));
    }
    sb.append("}");
    Logger.getLogger("dr.evomodel").info(sb.toString());
    return new FrequencyModel(dataType, freqsParam);
}

Example 70 with Parameter

use of dr.inference.model.Parameter in project beast-mcmc by beast-dev.

the class SampleStateAndCategoryModelParser method parseXMLObject.

public Object parseXMLObject(XMLObject xo) throws XMLParseException {
    XMLObject cxo = xo.getChild(MUTATION_RATE);
    Parameter muParam = (Parameter) cxo.getChild(Parameter.class);
    cxo = xo.getChild(CATEGORY_PARAMETER);
    Parameter catParam = (Parameter) cxo.getChild(Parameter.class);
    Vector subModels = new Vector();
    for (int i = 0; i < xo.getChildCount(); i++) {
        if (xo.getChild(i) instanceof SubstitutionModel) {
            subModels.addElement(xo.getChild(i));
        }
    }
    return new SampleStateAndCategoryModel(muParam, catParam, subModels);
}