Examples with ClusterTree beast.util.ClusterTree used on opensource projects

Example 6 with ClusterTree

use of beast.util.ClusterTree in project bacter by tgvaughan.

the class SimulatedAlignmentTest method test.

@Test
public void test() throws Exception {
    // Randomizer.setSeed(26);
    Randomizer.setSeed(7);
    Locus locus = new Locus("locus", 100000);
    TaxonSet taxonSet = getTaxonSet(10);
    ConstantPopulation popFunc = new ConstantPopulation();
    popFunc.initByName("popSize", new RealParameter("1.0"));
    ConversionGraph acg = new SimulatedACG();
    acg.initByName("rho", 1.0 / 100000, "delta", 1000.0, "populationModel", popFunc, "locus", locus, "taxonset", taxonSet);
    System.out.println(acg);
    // Site model:
    JukesCantor jc = new JukesCantor();
    jc.initByName();
    SiteModel siteModel = new SiteModel();
    siteModel.initByName("mutationRate", new RealParameter("1.0"), "substModel", jc);
    // Simulate alignment:
    SimulatedAlignment alignment = new SimulatedAlignment();
    alignment.initByName("acg", acg, "siteModel", siteModel, "outputFileName", "simulated_alignment.nexus", "useNexus", true);
    for (Region region : acg.getRegions(locus)) System.out.println(new MarginalTree(acg, region));
    // (Should be enough info here for precise agreement)
    for (Region region : acg.getRegions(locus)) {
        Alignment margAlign = createMarginalAlignment(alignment, region);
        ClusterTree upgmaTree = new ClusterTree();
        upgmaTree.initByName("clusterType", "upgma", "taxa", margAlign);
        MarginalTree marginalTree = new MarginalTree(acg, region);
        // outfMarg.println(marginalTree.getRoot() + ";");
        // outfMarg.flush();
        // 
        // outfUPGMA.println(upgmaTree.getRoot() + ";");
        // outfUPGMA.flush();
        assertTrue(topologiesEquivalent(marginalTree.getRoot(), upgmaTree.getRoot()));
    }
// outfMarg.close();
// outfUPGMA.close();
}

Example 7 with ClusterTree

use of beast.util.ClusterTree in project bacter by tgvaughan.

the class SerializationDeserializationTest method testExtendedNewick.

@Test
public void testExtendedNewick() throws Exception {
    Alignment alignment = getAlignment();
    alignment.setID("alignment");
    Locus locus = new Locus("locus", alignment.getSiteCount());
    // ConversionGraph
    ConversionGraph acg = new ConversionGraph();
    ClusterTree tree = new ClusterTree();
    tree.initByName("clusterType", "upgma", "taxa", alignment);
    acg.assignFrom(tree);
    acg.initByName("locus", locus);
    // Add recombination event 1
    Node node1 = acg.getExternalNodes().get(0);
    Node node2 = node1.getParent();
    double height1 = 0.5 * (node1.getHeight() + node1.getParent().getHeight());
    double height2 = 0.5 * (node2.getHeight() + node2.getParent().getHeight());
    int startLocus = 100;
    int endLocus = 200;
    Conversion conv1 = new Conversion(node1, height1, node2, height2, startLocus, endLocus, acg, locus);
    acg.addConversion(conv1);
    // Add recombination event 2
    node1 = acg.getExternalNodes().get(8);
    node2 = acg.getRoot();
    height1 = 0.5 * (node1.getHeight() + node1.getParent().getHeight());
    height2 = node2.getHeight() + 1.0;
    startLocus = 300;
    endLocus = 400;
    Conversion conv2 = new Conversion(node1, height1, node2, height2, startLocus, endLocus, acg, locus);
    acg.addConversion(conv2);
    String newickString = acg.getExtendedNewick();
    System.out.println(newickString);
    ConversionGraph acgNew = new ConversionGraph();
    acgNew.initByName("locus", locus);
    acgNew.fromExtendedNewick(newickString);
    // Check that new ACG matches old
    Conversion newConv1 = acgNew.getConversions(locus).get(0);
    assertEquals(newConv1.getNode1().getNr(), conv1.getNode1().getNr());
    assertEquals(newConv1.getNode2().getNr(), conv1.getNode2().getNr());
    assertEquals(newConv1.getHeight1(), conv1.getHeight1(), 1e-15);
    assertEquals(newConv1.getHeight2(), conv1.getHeight2(), 1e-15);
    assertEquals(newConv1.getStartSite(), conv1.getStartSite());
    assertEquals(newConv1.getEndSite(), conv1.getEndSite());
    Conversion newConv2 = acgNew.getConversions(locus).get(1);
    assertEquals(newConv2.getNode1().getNr(), conv2.getNode1().getNr());
    assertEquals(newConv2.getNode2().getNr(), conv2.getNode2().getNr());
    assertEquals(newConv2.getHeight1(), conv2.getHeight1(), 1e-15);
    assertEquals(newConv2.getHeight2(), conv2.getHeight2(), 1e-15);
    assertEquals(newConv2.getStartSite(), conv2.getStartSite());
    assertEquals(newConv2.getEndSite(), conv2.getEndSite());
}

Example 8 with ClusterTree

use of beast.util.ClusterTree in project bacter by tgvaughan.

the class ACGLikelihoodApproxTest method testPairwiseDistances.

@Test
public void testPairwiseDistances() throws Exception {
    List<Sequence> sequences = new ArrayList<>();
    // 01234567890123456789
    sequences.add(new Sequence("t1", "AAAAAAAAAAAAAAAAAAAA"));
    sequences.add(new Sequence("t2", "AAAACAAAAAAGAAAAAAAA"));
    sequences.add(new Sequence("t3", "CCCCCCCCCCCCCCCCCCCC"));
    Alignment alignment = new Alignment(sequences, "nucleotide");
    Locus locus = new Locus("locus", alignment);
    ConversionGraph acg = new ConversionGraph();
    ClusterTree tree = new ClusterTree();
    tree.initByName("clusterType", "upgma", "taxa", locus.getAlignment());
    acg.assignFrom(tree);
    acg.initByName("locus", locus);
    ACGLikelihoodApprox likelihoodApprox = new ACGLikelihoodApprox();
    likelihoodApprox.initByName("acg", acg, "substitutionRate", "1.0", "alignment", alignment, "locus", locus);
    Assert.assertEquals(0, likelihoodApprox.getPairwiseDistance(0, 1, 0, 4));
    Assert.assertEquals(1, likelihoodApprox.getPairwiseDistance(0, 1, 0, 5));
    Assert.assertEquals(1, likelihoodApprox.getPairwiseDistance(0, 1, 0, 11));
    Assert.assertEquals(2, likelihoodApprox.getPairwiseDistance(0, 1, 0, 12));
    Assert.assertEquals(2, likelihoodApprox.getPairwiseDistance(0, 1, 0, 20));
    Assert.assertEquals(5, likelihoodApprox.getPairwiseDistance(1, 2, 2, 8));
    Assert.assertEquals(19, likelihoodApprox.getPairwiseDistance(1, 2, 0, 20));
    Assert.assertEquals(6, likelihoodApprox.getPairwiseDistance(0, 2, 2, 8));
    Assert.assertEquals(20, likelihoodApprox.getPairwiseDistance(0, 2, 0, 20));
}

Example 9 with ClusterTree

use of beast.util.ClusterTree in project bacter by tgvaughan.

the class ACGLikelihoodTest method testBeagleLikelihood.

@Test
public void testBeagleLikelihood() throws Exception {
    Locus locus = new Locus("locus", getAlignment());
    // ConversionGraph
    ConversionGraph acg = new ConversionGraph();
    ClusterTree tree = new ClusterTree();
    tree.initByName("clusterType", "upgma", "taxa", locus.getAlignment());
    acg.assignFrom(tree);
    acg.initByName("locus", locus);
    // Site model:
    JukesCantor jc = new JukesCantor();
    jc.initByName();
    SiteModel siteModel = new SiteModel();
    siteModel.initByName("substModel", jc);
    // Likelihood
    ACGLikelihoodBeagle argLikelihood = new ACGLikelihoodBeagle();
    argLikelihood.initByName("locus", locus, "tree", acg, "siteModel", siteModel);
    ACGLikelihoodSlow argLikelihoodSlow = new ACGLikelihoodSlow();
    argLikelihoodSlow.initByName("locus", locus, "tree", acg, "siteModel", siteModel);
    acg.setEverythingDirty(true);
    try {
        double logP = argLikelihood.calculateLogP();
        double logPtrue = argLikelihoodSlow.calculateLogP();
        double relativeDiff = Math.abs(2.0 * (logPtrue - logP) / (logPtrue + logP));
        assertTrue(relativeDiff < 1e-14);
        // Add a single recombination event
        Node node1 = acg.getExternalNodes().get(0);
        Node node2 = node1.getParent();
        double height1 = 0.5 * (node1.getHeight() + node1.getParent().getHeight());
        double height2 = 0.5 * (node2.getHeight() + node2.getParent().getHeight());
        int startLocus = 100;
        int endLocus = 200;
        Conversion recomb1 = new Conversion(node1, height1, node2, height2, startLocus, endLocus, acg, locus);
        acg.addConversion(recomb1);
        logP = argLikelihood.calculateLogP();
        logPtrue = argLikelihoodSlow.calculateLogP();
        relativeDiff = Math.abs(2.0 * (logPtrue - logP) / (logPtrue + logP));
        assertTrue(relativeDiff < 1e-14);
        // Add another recombination event
        node1 = acg.getExternalNodes().get(0);
        node2 = acg.getNode(20);
        height1 = 0.75 * (node1.getHeight() + node1.getParent().getHeight());
        height2 = 0.5 * (node2.getHeight() + node2.getParent().getHeight());
        startLocus = 250;
        endLocus = 300;
        Conversion recomb2 = new Conversion(node1, height1, node2, height2, startLocus, endLocus, acg, locus);
        acg.addConversion(recomb2);
        logP = argLikelihood.calculateLogP();
        logPtrue = argLikelihoodSlow.calculateLogP();
        relativeDiff = Math.abs(2.0 * (logPtrue - logP) / (logPtrue + logP));
        assertTrue(relativeDiff < 1e-14);
    } catch (RuntimeException ex) {
        System.err.println("Beagle library not found: skipping beagle likelihood test.");
    }
}

Example 10 with ClusterTree

use of beast.util.ClusterTree in project bacter by tgvaughan.

the class ACGLikelihoodTest method testLikelihoodFixedData.

@Test
public void testLikelihoodFixedData() throws Exception {
    Locus locus = new Locus("locus", getAlignment());
    // ConversionGraph
    ConversionGraph acg = new ConversionGraph();
    ClusterTree tree = new ClusterTree();
    tree.initByName("clusterType", "upgma", "taxa", locus.getAlignment());
    acg.assignFrom(tree);
    acg.initByName("locus", locus);
    // Site model:
    JukesCantor jc = new JukesCantor();
    jc.initByName();
    SiteModel siteModel = new SiteModel();
    siteModel.initByName("substModel", jc);
    // Likelihood
    ACGLikelihood argLikelihood = new ACGLikelihood();
    argLikelihood.initByName("locus", locus, "tree", acg, "siteModel", siteModel);
    ACGLikelihoodSlow argLikelihoodSlow = new ACGLikelihoodSlow();
    argLikelihoodSlow.initByName("locus", locus, "tree", acg, "siteModel", siteModel);
    acg.setEverythingDirty(true);
    double logP = argLikelihood.calculateLogP();
    double logPtrue = argLikelihoodSlow.calculateLogP();
    double relativeDiff = Math.abs(2.0 * (logPtrue - logP) / (logPtrue + logP));
    assertTrue(relativeDiff < 1e-14);
    // Add a single recombination event
    Node node1 = acg.getExternalNodes().get(0);
    Node node2 = node1.getParent();
    double height1 = 0.5 * (node1.getHeight() + node1.getParent().getHeight());
    double height2 = 0.5 * (node2.getHeight() + node2.getParent().getHeight());
    int startLocus = 100;
    int endLocus = 200;
    Conversion recomb1 = new Conversion(node1, height1, node2, height2, startLocus, endLocus, acg, locus);
    acg.addConversion(recomb1);
    logP = argLikelihood.calculateLogP();
    logPtrue = argLikelihoodSlow.calculateLogP();
    relativeDiff = Math.abs(2.0 * (logPtrue - logP) / (logPtrue + logP));
    assertTrue(relativeDiff < 1e-14);
    // Add another recombination event
    node1 = acg.getExternalNodes().get(0);
    node2 = acg.getNode(20);
    height1 = 0.75 * (node1.getHeight() + node1.getParent().getHeight());
    height2 = 0.5 * (node2.getHeight() + node2.getParent().getHeight());
    startLocus = 250;
    endLocus = 300;
    Conversion recomb2 = new Conversion(node1, height1, node2, height2, startLocus, endLocus, acg, locus);
    acg.addConversion(recomb2);
    logP = argLikelihood.calculateLogP();
    logPtrue = argLikelihoodSlow.calculateLogP();
    relativeDiff = Math.abs(2.0 * (logPtrue - logP) / (logPtrue + logP));
    assertTrue(relativeDiff < 1e-14);
}