Examples with StructuredCoalescentTreeDensity multitypetree.distributions.StructuredCoalescentTreeDensity used on opensource projects

Example 1 with StructuredCoalescentTreeDensity

use of multitypetree.distributions.StructuredCoalescentTreeDensity in project MultiTypeTree by tgvaughan.

the class SCLikelihoodTest method testCalculateLogP.

/**
 * Test of calculateLogP method, of class StructuredCoalescentLikelihood.
 */
@Test
public void testCalculateLogP() throws Exception {
    System.out.println("SCLikelihoodTest");
    // Assemble test MultiTypeTree:
    String newickStr = "(((A[&state=1]:0.25)[&state=0]:0.25,B[&state=0]:0.5)[&state=0]:1.5," + "(C[&state=0]:1.0,D[&state=0]:1.0)[&state=0]:1.0)[&state=0]:0.0;";
    MultiTypeTreeFromNewick mtTree = new MultiTypeTreeFromNewick();
    mtTree.initByName("value", newickStr, "typeLabel", "state");
    // Assemble migration model:
    RealParameter rateMatrix = new RealParameter();
    rateMatrix.initByName("value", "2.0 1.0");
    RealParameter popSizes = new RealParameter();
    popSizes.initByName("value", "5.0 10.0");
    SCMigrationModel migrationModel = new SCMigrationModel();
    migrationModel.initByName("rateMatrix", rateMatrix, "popSizes", popSizes, "typeSet", new TypeSet("A", "B"));
    // Set up likelihood instance:
    StructuredCoalescentTreeDensity likelihood = new StructuredCoalescentTreeDensity();
    likelihood.initByName("migrationModel", migrationModel, "multiTypeTree", mtTree);
    // Calculated by hand
    double expResult = -16.52831;
    double result = likelihood.calculateLogP();
    System.out.println(result);
    assertEquals(expResult, result, 1e-5);
}

Example 2 with StructuredCoalescentTreeDensity

use of multitypetree.distributions.StructuredCoalescentTreeDensity in project MultiTypeTree by tgvaughan.

the class NSR_Test method test.

@Test
public void test() throws Exception {
    System.out.println("NSR test");
    // Fix seed.
    Randomizer.setSeed(42);
    // Assemble migration model:
    RealParameter rateMatrix = new RealParameter("0.1 0.1");
    RealParameter popSizes = new RealParameter("7.0 7.0");
    SCMigrationModel migModel = new SCMigrationModel();
    migModel.initByName("rateMatrix", rateMatrix, "popSizes", popSizes, "typeSet", new TypeSet("A", "B"));
    // Assemble initial MultiTypeTree
    MultiTypeTree mtTree = new StructuredCoalescentMultiTypeTree();
    mtTree.initByName("typeLabel", "deme", "migrationModel", migModel, "leafTypes", "1 0");
    // Set up state:
    State state = new State();
    state.initByName("stateNode", mtTree);
    // Assemble distribution:
    StructuredCoalescentTreeDensity distribution = new StructuredCoalescentTreeDensity();
    distribution.initByName("migrationModel", migModel, "multiTypeTree", mtTree);
    // Set up operators:
    Operator operatorNSR = new NodeShiftRetype();
    operatorNSR.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel);
    // Set up stat analysis logger:
    MultiTypeTreeStatLogger logger = new MultiTypeTreeStatLogger();
    logger.initByName("multiTypeTree", mtTree, "burninFrac", 0.1, "logEvery", 100);
    // Set up MCMC:
    MCMC mcmc = new MCMC();
    mcmc.initByName("chainLength", "1000000", "state", state, "distribution", distribution, "operator", operatorNSR, "logger", logger);
    // Run MCMC:
    mcmc.run();
    System.out.format("height mean = %s\n", logger.getHeightMean());
    System.out.format("height var = %s\n", logger.getHeightVar());
    System.out.format("height ESS = %s\n", logger.getHeightESS());
    // Compare analysis results with truth:
    boolean withinTol = (logger.getHeightESS() > 2000) && (Math.abs(logger.getHeightMean() - 19.0) < 0.5) && (Math.abs(logger.getHeightVar() - 291) < 30);
    Assert.assertTrue(withinTol);
}

Example 3 with StructuredCoalescentTreeDensity

use of multitypetree.distributions.StructuredCoalescentTreeDensity in project MultiTypeTree by tgvaughan.

the class STXR_NRR_MTU_TS_Test method test.

@Test
public void test() throws Exception {
    System.out.println("STXR_NRR_MTU_TS test");
    // Fix seed.
    Randomizer.setSeed(42);
    // Assemble migration model:
    RealParameter rateMatrix = new RealParameter("0.1 0.1");
    RealParameter popSizes = new RealParameter("7.0 7.0");
    SCMigrationModel migModel = new SCMigrationModel();
    migModel.initByName("rateMatrix", rateMatrix, "popSizes", popSizes, "typeSet", new TypeSet("A", "B"));
    // Assemble initial MultiTypeTree
    MultiTypeTree mtTree = new StructuredCoalescentMultiTypeTree();
    mtTree.initByName("typeLabel", "deme", "migrationModel", migModel, "leafTypes", "1 1 0 0");
    // Set up state:
    State state = new State();
    state.initByName("stateNode", mtTree);
    // Assemble distribution:
    StructuredCoalescentTreeDensity distribution = new StructuredCoalescentTreeDensity();
    distribution.initByName("migrationModel", migModel, "multiTypeTree", mtTree);
    // Set up operators:
    Operator operatorSTXR = new TypedSubtreeExchangeRandom();
    operatorSTXR.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel, "mu", 0.2);
    Operator operatorNRR = new NodeRetypeRandom();
    operatorNRR.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel, "mu", 0.2);
    Operator operatorMTU = new MultiTypeUniform();
    operatorMTU.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel);
    Operator operatorMTTS = new MultiTypeTreeScale();
    operatorMTTS.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel, "scaleFactor", 1.5, "useOldTreeScaler", false);
    // Set up stat analysis logger:
    MultiTypeTreeStatLogger logger = new MultiTypeTreeStatLogger();
    logger.initByName("multiTypeTree", mtTree, "burninFrac", 0.1, "logEvery", 1000);
    // Set up MCMC:
    MCMC mcmc = new MCMC();
    mcmc.initByName("chainLength", "10000000", "state", state, "distribution", distribution, "operator", operatorSTXR, "operator", operatorNRR, "operator", operatorMTU, "operator", operatorMTTS, "logger", logger);
    // Run MCMC:
    mcmc.run();
    System.out.format("height mean = %s\n", logger.getHeightMean());
    System.out.format("height var = %s\n", logger.getHeightVar());
    System.out.format("height ESS = %s\n", logger.getHeightESS());
    // Compare analysis results with truth:
    boolean withinTol = (logger.getHeightESS() > 2000) && (Math.abs(logger.getHeightMean() - 25.8) < 0.5) && (Math.abs(logger.getHeightVar() - 320) < 30);
    Assert.assertTrue(withinTol);
}

Example 4 with StructuredCoalescentTreeDensity

use of multitypetree.distributions.StructuredCoalescentTreeDensity in project MultiTypeTree by tgvaughan.

the class TWBR_TS_Test method test2.

@Test
public void test2() throws Exception {
    System.out.println("TWBR_test 2");
    // Fix seed.
    Randomizer.setSeed(42);
    // Assemble initial MultiTypeTree
    String newickStr = "((1[&deme=1]:1,2[&deme=0]:1)[&deme=0]:1," + "3[&deme=0]:2)[&deme=0]:0;";
    MultiTypeTreeFromNewick mtTree = new MultiTypeTreeFromNewick();
    mtTree.initByName("value", newickStr, "typeLabel", "deme");
    // Assemble migration model:
    RealParameter rateMatrix = new RealParameter("0.1 0.1");
    RealParameter popSizes = new RealParameter("7.0 7.0");
    SCMigrationModel migModel = new SCMigrationModel();
    migModel.initByName("rateMatrix", rateMatrix, "popSizes", popSizes, "typeSet", new TypeSet("A", "B"));
    // Assemble distribution:
    StructuredCoalescentTreeDensity distribution = new StructuredCoalescentTreeDensity();
    distribution.initByName("migrationModel", migModel, "multiTypeTree", mtTree);
    // Set up state:
    State state = new State();
    state.initByName("stateNode", mtTree);
    // Set up operator:
    TypedWilsonBaldingRandom operatorTWBR = new TypedWilsonBaldingRandom();
    operatorTWBR.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel, "mu", 0.2, "alpha", 0.2);
    Operator operatorMTTS = new MultiTypeTreeScale();
    operatorMTTS.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel, "scaleFactor", 0.8, "useOldTreeScaler", false);
    // Set up stat analysis logger:
    MultiTypeTreeStatLogger logger = new MultiTypeTreeStatLogger();
    logger.initByName("multiTypeTree", mtTree, "burninFrac", 0.1, "logEvery", 1000);
    // Set up MCMC:
    MCMC mcmc = new MCMC();
    mcmc.initByName("chainLength", "1000000", "state", state, "distribution", distribution, "operator", operatorTWBR, "operator", operatorMTTS, "logger", logger);
    // Run MCMC:
    mcmc.run();
    System.out.format("height mean = %s\n", logger.getHeightMean());
    System.out.format("height var = %s\n", logger.getHeightVar());
    System.out.format("height ESS = %s\n", logger.getHeightESS());
    // Compare analysis results with truth:
    boolean withinTol = (logger.getHeightESS() > 200) && (Math.abs(logger.getHeightMean() - 23) < 1) && (Math.abs(logger.getHeightVar() - 300) < 30);
    Assert.assertTrue(withinTol);
}

Example 5 with StructuredCoalescentTreeDensity

use of multitypetree.distributions.StructuredCoalescentTreeDensity in project MultiTypeTree by tgvaughan.

the class TWBR_TS_Test method test1.

@Test
public void test1() throws Exception {
    System.out.println("TWBR_test 1");
    // Fix seed.
    Randomizer.setSeed(42);
    // Assemble initial MultiTypeTree
    String newickStr = "((1[&deme=0]:1,2[&deme=0]:1)[&deme=0]:1," + "3[&deme=0]:2)[&deme=0]:0;";
    MultiTypeTreeFromNewick mtTree = new MultiTypeTreeFromNewick();
    mtTree.initByName("value", newickStr, "typeLabel", "deme");
    // Assemble migration model:
    RealParameter rateMatrix = new RealParameter("0.1 0.1");
    RealParameter popSizes = new RealParameter("7.0 7.0");
    SCMigrationModel migModel = new SCMigrationModel();
    migModel.initByName("rateMatrix", rateMatrix, "popSizes", popSizes, "typeSet", new TypeSet("A", "B"));
    // Assemble distribution:
    StructuredCoalescentTreeDensity distribution = new StructuredCoalescentTreeDensity();
    distribution.initByName("migrationModel", migModel, "multiTypeTree", mtTree);
    // Set up state:
    State state = new State();
    state.initByName("stateNode", mtTree);
    // Set up operator:
    TypedWilsonBaldingRandom operatorTWBR = new TypedWilsonBaldingRandom();
    operatorTWBR.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel, "mu", 0.2, "alpha", 0.2);
    Operator operatorMTTS = new MultiTypeTreeScale();
    operatorMTTS.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel, "scaleFactor", 0.8, "useOldTreeScaler", false);
    // Set up stat analysis logger:
    MultiTypeTreeStatLogger logger = new MultiTypeTreeStatLogger();
    logger.initByName("multiTypeTree", mtTree, "burninFrac", 0.2, "logEvery", 1000);
    // Set up MCMC:
    MCMC mcmc = new MCMC();
    mcmc.initByName("chainLength", "1000000", "state", state, "distribution", distribution, "operator", operatorTWBR, "operator", operatorMTTS, "logger", logger);
    // Run MCMC:
    mcmc.run();
    System.out.format("height mean = %s\n", logger.getHeightMean());
    System.out.format("height var = %s\n", logger.getHeightVar());
    System.out.format("height ESS = %s\n", logger.getHeightESS());
    // Compare analysis results with truth:
    boolean withinTol = (logger.getHeightESS() > 500) && (Math.abs(logger.getHeightMean() - 19) < 0.5) && (Math.abs(logger.getHeightVar() - 300) < 50);
    Assert.assertTrue(withinTol);
}