Examples with Operator beast.core.Operator used on opensource projects

Example 6 with Operator

use of beast.core.Operator 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 7 with Operator

use of beast.core.Operator 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 8 with Operator

use of beast.core.Operator 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);
}

Example 9 with Operator

use of beast.core.Operator in project MultiTypeTree by tgvaughan.

the class STX_NR_MTU_TS_Test method test.

@Test
public void test() throws Exception {
    System.out.println("STX_NR_MTU_TS test");
    // Test passing locally, not on Travis.  WHY!?
    // Fix seed.
    Randomizer.setSeed(53);
    // 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 operatorSTX = new TypedSubtreeExchange();
    operatorSTX.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel);
    Operator operatorNR = new NodeRetype();
    operatorNR.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel);
    Operator operatorMTU = new MultiTypeUniform();
    operatorMTU.initByName("weight", 1.0, "migrationModel", migModel, "multiTypeTree", mtTree);
    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", "1000000", "state", state, "distribution", distribution, "operator", operatorSTX, "operator", operatorNR, "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());
    // Direct simulation:
    double[] heights = UtilMethods.getSimulatedHeights(migModel, new IntegerParameter("1 1 0 0"));
    double simHeightMean = DiscreteStatistics.mean(heights);
    double simHeightVar = DiscreteStatistics.variance(heights);
    // Compare analysis results with truth:
    boolean withinTol = (logger.getHeightESS() > 500) && (Math.abs(logger.getHeightMean() - simHeightMean) < 2.0) && (Math.abs(logger.getHeightVar() - simHeightVar) < 50);
    Assert.assertTrue(withinTol);
}

Example 10 with Operator

use of beast.core.Operator in project MultiTypeTree by tgvaughan.

the class TWB_TS_Test method test1.

@Test
public void test1() throws Exception {
    System.out.println("TWB_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:
    TypedWilsonBalding operatorTWB = new TypedWilsonBalding();
    operatorTWB.initByName("weight", 1.0, "multiTypeTree", mtTree, "migrationModel", migModel, "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", operatorTWB, "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());
    // Direct simulation:
    double[] heights = UtilMethods.getSimulatedHeights(migModel, new IntegerParameter("0 0 0"));
    double simHeightMean = DiscreteStatistics.mean(heights);
    double simHeightVar = DiscreteStatistics.variance(heights);
    // Compare results with simulation results:
    boolean withinTol = (logger.getHeightESS() > 400) && (Math.abs(logger.getHeightMean() - simHeightMean) < 1.0) && (Math.abs(logger.getHeightVar() - simHeightVar) < 30);
    Assert.assertTrue(withinTol);
}