private double onePoint(double x0, double x1, double[] point) {
final IMonteCarloModel<Double, Double> mc = factory.createModel(x0, x1, point);
mc.addSamples(samples);
final double value = mc.getStats().value();
return FastMath.log(value);
}
public void testMeanAndVariance() throws MathException {
long ms = System.currentTimeMillis();
int iters = mcm.addSamples(500000);
ms = System.currentTimeMillis() - ms;
System.out.println(ms + " ms");
double rate = iters * 1000.0 / ms;
System.out.format("%f iters/s %n", rate);
double mean = summary.stats.getMean();
double stddev = summary.stats.getStandardDeviation();
System.out.println(iters);
System.out.println(mean);
System.out.println(stddev);
assertEquals(expectedMean, mean, 0.01);
// assertEquals(expectedStdDev, stddev, 0.05);
}
public void testMeanAndVarianceParallel() throws MathException {
LogArrivedPointValuation apv = new LogArrivedPointValuation();
mcm =
new ParallelMonteCarloModel<Double>(
new FastRandomFactory(), process, 1.0, 100, apv, summary, true, false);
long ms = System.currentTimeMillis();
int iters = mcm.addSamples(500000);
ms = System.currentTimeMillis() - ms;
System.out.println(ms + " ms");
double rate = iters * 1000.0 / ms;
System.out.format("%f iters/s %n", rate);
double mean = summary.stats.getMean();
double stddev = summary.stats.getStandardDeviation();
System.out.println(iters);
System.out.println(mean);
System.out.println(stddev);
assertEquals(expectedMean, mean, 0.01);
assertEquals(expectedStdDev, stddev, 0.02);
}
