本文整理汇总了Java中beast.math.MachineAccuracy类的典型用法代码示例。如果您正苦于以下问题:Java MachineAccuracy类的具体用法?Java MachineAccuracy怎么用?Java MachineAccuracy使用的例子?那么, 这里精选的类代码示例或许可以为您提供帮助。
MachineAccuracy类属于beast.math包,在下文中一共展示了MachineAccuracy类的5个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: testRandomWalkOperator
import beast.math.MachineAccuracy; //导入依赖的package包/类
@Test
public void testRandomWalkOperator() {
Parameter parameter = new Parameter.Default("test", 0.5, 0.0, 1.0);
RandomWalkOperator rwo = new RandomWalkOperator(parameter, 1.0, RandomWalkOperator.BoundaryCondition.reflecting, 1.0, CoercionMode.COERCION_OFF);
double test1 = rwo.reflectValue(8.7654321, 3.14159265, Double.POSITIVE_INFINITY);
double test2 = rwo.reflectValue(8.7654321, Double.NEGATIVE_INFINITY, 3.14159265);
double test3 = rwo.reflectValue(1.2345678, 3.14159265, 2.0 * 3.14159265);
double test4 = rwo.reflectValue(12345678.987654321, 3.14159265, 2.0 * 3.14159265);
double test1b = rwo.reflectValueLoop(8.7654321, 3.14159265, Double.POSITIVE_INFINITY);
double test2b = rwo.reflectValueLoop(8.7654321, Double.NEGATIVE_INFINITY, 3.14159265);
double test3b = rwo.reflectValueLoop(1.2345678, 3.14159265, 2.0 * 3.14159265);
double test4b = rwo.reflectValueLoop(12345678.987654321, 3.14159265, 2.0 * 3.14159265);
assertEquals(test1, test1b, MachineAccuracy.EPSILON);
assertEquals(test2, test2b, MachineAccuracy.EPSILON);
assertEquals(test3, test3b, MachineAccuracy.EPSILON);
assertTrue(Math.abs(test4 - test4b) < 0.001);
}
示例2: likelihoodTester
import beast.math.MachineAccuracy; //导入依赖的package包/类
private void likelihoodTester(Tree tree, double birthRate, double deathRate, Variable<Double> origin, double logL) {
Variable<Double> b = new Variable.D("b", birthRate);
Variable<Double> d = new Variable.D("d", deathRate);
Variable<Double> psi = new Variable.D("psi", this.psi);
Variable<Double> p = new Variable.D("p", this.p);
Variable<Double> r = new Variable.D("r", 0.5);
Variable<Double> fTime = new Variable.D("time", 0.0);
SpeciationModel speciationModel = new BirthDeathSerialSamplingModel(b, d, psi, p, false, r, true, origin, Units.Type.YEARS);
Likelihood likelihood = new SpeciationLikelihood(tree, speciationModel, "bdss.like");
assertEquals(logL, likelihood.getLogLikelihood(), MachineAccuracy.EPSILON);
}
示例3: testPdf
import beast.math.MachineAccuracy; //导入依赖的package包/类
@Test
public void testPdf() {
final int numberOfTests = 100;
double totErr = 0;
double ptotErr = 0; int np = 0;
double qtotErr = 0;
Random random = new Random(37);
for(int i = 0; i < numberOfTests; i++){
final double mean = .01 + (3-0.01) * random.nextDouble();
final double var = .01 + (3-0.01) * random.nextDouble();
final double scale = var / mean;
final double shape = mean / scale;
final GammaDistribution gamma = new GammaDistribution(shape,scale);
final double value = gamma.nextGamma();
final double mypdf = mypdf(value, shape, scale);
final double pdf = gamma.pdf(value);
if ( Double.isInfinite(mypdf) && Double.isInfinite(pdf)) {
continue;
}
assertFalse(Double.isNaN(mypdf));
assertFalse(Double.isNaN(pdf));
totErr += mypdf != 0 ? Math.abs((pdf - mypdf)/mypdf) : pdf;
assertFalse("nan", Double.isNaN(totErr));
//assertEquals("" + shape + "," + scale + "," + value, mypdf,gamma.pdf(value),1e-10);
final double cdf = gamma.cdf(value);
UnivariateFunction f = new UnivariateFunction() {
public double value(double v) {
return mypdf(v, shape, scale);
}
};
final UnivariateIntegrator integrator = new RombergIntegrator(MachineAccuracy.SQRT_EPSILON, 1e-14, 1, 16);
double x;
try {
x = integrator.integrate(16, f, 0.0, value);
ptotErr += cdf != 0.0 ? Math.abs(x-cdf)/cdf : x;
np += 1;
//assertTrue("" + shape + "," + scale + "," + value + " " + Math.abs(x-cdf)/x + "> 1e-6", Math.abs(1-cdf/x) < 1e-6);
//System.out.println(shape + "," + scale + " " + value);
} catch(MaxCountExceededException e ) {
// can't integrate , skip test
// System.out.println(shape + "," + scale + " skipped");
}
final double q = gamma.quantile(cdf);
qtotErr += q != 0 ? Math.abs(q-value)/q : value;
// assertEquals("" + shape + "," + scale + "," + value + " " + Math.abs(q-value)/value, q, value, 1e-6);
}
//System.out.println( !Double.isNaN(totErr) );
// System.out.println(totErr);
// bad test, but I can't find a good threshold that works for all individual cases
assertTrue("failed " + totErr/numberOfTests, totErr/numberOfTests < 1e-7);
assertTrue("failed " + ptotErr/np, np > 0 ? (ptotErr/np < 1e-5) : true);
assertTrue("failed " + qtotErr/numberOfTests , qtotErr/numberOfTests < 1e-7);
}
示例4: testBirthDeathLikelihoodP0
import beast.math.MachineAccuracy; //导入依赖的package包/类
@Test
public void testBirthDeathLikelihoodP0() {
assertEquals(BirthDeathSerialSamplingModel.p0(birthRate, deathRate, p, psi, 1.0), 0.28236670080320814, MachineAccuracy.EPSILON);
}
示例5: yuleLikelihoodTester
import beast.math.MachineAccuracy; //导入依赖的package包/类
private void yuleLikelihoodTester(Tree tree, double birthRate, double logL) {
Parameter b = new Parameter.Default("b", birthRate, 0.0, Double.MAX_VALUE);
Parameter d = new Parameter.Default("d", 0.0, 0.0, Double.MAX_VALUE);
SpeciationModel speciationModel = new BirthDeathModel(b, d, null, null, BirthDeathModel.TreeType.TIMESONLY,
Units.Type.YEARS);
Likelihood likelihood = new SpeciationLikelihood(tree, speciationModel, "yule.like");
assertEquals(likelihood.getLogLikelihood(), logL, MachineAccuracy.EPSILON);
}