本文整理汇总了Java中org.apache.commons.math3.analysis.integration.UnivariateIntegrator类的典型用法代码示例。如果您正苦于以下问题:Java UnivariateIntegrator类的具体用法?Java UnivariateIntegrator怎么用?Java UnivariateIntegrator使用的例子?那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
UnivariateIntegrator类属于org.apache.commons.math3.analysis.integration包,在下文中一共展示了UnivariateIntegrator类的6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,您的评价将有助于我们的系统推荐出更棒的Java代码示例。
示例1: cumulativeProbabilityIsOneWithRealData
import org.apache.commons.math3.analysis.integration.UnivariateIntegrator; //导入依赖的package包/类
private void cumulativeProbabilityIsOneWithRealData(final double mu, double min, double max, boolean test)
{
double p = 0;
UnivariateIntegrator in = new SimpsonIntegrator();
p = in.integrate(20000, new UnivariateFunction()
{
public double value(double x)
{
double v;
v = PoissonCalculator.likelihood(mu, x);
//v = pgf.probability(x, mu);
//System.out.printf("x=%f, v=%f\n", x, v);
return v;
}
}, min, max);
System.out.printf("mu=%f, p=%f\n", mu, p);
if (test)
{
Assert.assertEquals(String.format("mu=%f", mu), P_LIMIT, p, 0.02);
}
}
开发者ID:aherbert,项目名称:GDSC-SMLM,代码行数:25,代码来源:PoissonCalculatorTest.java
示例2: getVelocity
import org.apache.commons.math3.analysis.integration.UnivariateIntegrator; //导入依赖的package包/类
public double getVelocity(double startSpeed, double startTime, double endTime){
UnivariateIntegrator integrator = new SimpsonIntegrator();
double integralAddition = 0;
if (!dEqual(startTime,endTime)) {
try {
integralAddition = startTime * integrator.integrate(10, v -> getAccel(v), startTime, endTime);
} catch (Exception e) {
System.err.println(e.getMessage());
}
}
return startSpeed + integralAddition;
}
开发者ID:ValisStigma,项目名称:LazyDrivers,代码行数:13,代码来源:Accel.java
示例3: cumulativeProbabilityIsOneWithRealData
import org.apache.commons.math3.analysis.integration.UnivariateIntegrator; //导入依赖的package包/类
private void cumulativeProbabilityIsOneWithRealData(final double mu, double min, double max, boolean test)
{
double p = 0;
// Test using a standard Poisson-Gaussian convolution
//min = -max;
//final PoissonGaussianFunction pgf = PoissonGaussianFunction.createWithVariance(1, 1, VAR);
UnivariateIntegrator in = new SimpsonIntegrator();
p = in.integrate(20000, new UnivariateFunction()
{
public double value(double x)
{
double v;
v = SCMOSLikelihoodWrapper.likelihood(mu, VAR, G, O, x);
//v = pgf.probability(x, mu);
//System.out.printf("x=%f, v=%f\n", x, v);
return v;
}
}, min, max);
//System.out.printf("mu=%f, p=%f\n", mu, p);
if (test)
{
Assert.assertEquals(String.format("mu=%f", mu), P_LIMIT, p, 0.02);
}
}
开发者ID:aherbert,项目名称:GDSC-SMLM,代码行数:29,代码来源:SCMOSLikelihoodWrapperTest.java
示例4: createAiryDistribution
import org.apache.commons.math3.analysis.integration.UnivariateIntegrator; //导入依赖的package包/类
private static synchronized void createAiryDistribution()
{
if (spline != null)
return;
final double relativeAccuracy = 1e-4;
final double absoluteAccuracy = 1e-8;
final int minimalIterationCount = 3;
final int maximalIterationCount = 32;
UnivariateIntegrator integrator = new SimpsonIntegrator(relativeAccuracy, absoluteAccuracy,
minimalIterationCount, maximalIterationCount);
UnivariateFunction f = new UnivariateFunction()
{
public double value(double x)
{
// The pattern profile is in one dimension.
// Multiply by the perimeter of a circle to convert to 2D volume then normalise by 4 pi
//return AiryPattern.intensity(x) * 2 * Math.PI * x / (4 * Math.PI);
return AiryPattern.intensity(x) * 0.5 * x;
}
};
// Integrate up to a set number of dark rings
int samples = 1000;
final double step = RINGS[SAMPLE_RINGS] / samples;
double to = 0, from = 0;
r = new double[samples + 1];
sum = new double[samples + 1];
for (int i = 1; i < sum.length; i++)
{
from = to;
r[i] = to = step * i;
sum[i] = integrator.integrate(2000, f, from, to) + sum[i - 1];
}
if (DoubleEquality.relativeError(sum[samples], POWER[SAMPLE_RINGS]) > 1e-3)
throw new RuntimeException("Failed to create the Airy distribution");
SplineInterpolator si = new SplineInterpolator();
spline = si.interpolate(sum, r);
}
开发者ID:aherbert,项目名称:GDSC-SMLM,代码行数:43,代码来源:AiryPSFModel.java
示例5: computeI1
import org.apache.commons.math3.analysis.integration.UnivariateIntegrator; //导入依赖的package包/类
/**
* Compute the function I1 using numerical integration. See Mortensen, et al (2010) Nature Methods 7, 377-383), SI
* equation 43.
*
* <pre>
* I1 = 1 + sum [ ln(t) / (1 + t/rho) ] dt
* = - sum [ t * ln(t) / (t + rho) ] dt
* </pre>
*
* Where sum is the integral between 0 and 1. In the case of rho=0 the function returns 1;
*
* @param rho
* @param integrationPoints
* the number of integration points for the LegendreGaussIntegrator
* @return the I1 value
*/
private static double computeI1(final double rho, int integrationPoints)
{
if (rho == 0)
return 1;
final double relativeAccuracy = 1e-4;
final double absoluteAccuracy = 1e-8;
final int minimalIterationCount = 3;
final int maximalIterationCount = 32;
// Use an integrator that does not use the boundary since log(0) is undefined.
UnivariateIntegrator i = new IterativeLegendreGaussIntegrator(integrationPoints, relativeAccuracy,
absoluteAccuracy, minimalIterationCount, maximalIterationCount);
// Specify the function to integrate
UnivariateFunction f = new UnivariateFunction()
{
public double value(double x)
{
return x * Math.log(x) / (x + rho);
}
};
final double i1 = -i.integrate(2000, f, 0, 1);
//System.out.printf("I1 = %f (%d)\n", i1, i.getEvaluations());
// The function requires more evaluations and sometimes does not converge,
// presumably because log(x) significantly changes as x -> 0 where as x log(x) in the function above
// is more stable
// UnivariateFunction f2 = new UnivariateFunction()
// {
// @Override
// public double value(double x)
// {
// return Math.log(x) / ( 1 + x / rho);
// }
// };
// double i2 = 1 + i.integrate(2000, f2, 0, 1);
// System.out.printf("I1 (B) = %f (%d)\n", i2, i.getEvaluations());
return i1;
}
开发者ID:aherbert,项目名称:GDSC-SMLM,代码行数:59,代码来源:Gaussian2DPeakResultHelper.java
示例6: testPdf
import org.apache.commons.math3.analysis.integration.UnivariateIntegrator; //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);
}
开发者ID:armanbilge,项目名称:B3,代码行数:68,代码来源:GammaDistributionTest.java
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