This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-rng.git
commit ef4cee1eb58d44f134ccb74bbcfc7e17c97fb3f0
Author: Alex Herbert <aherb...@apache.org>
AuthorDate: Fri Jul 9 17:13:33 2021 +0100
Added a test for sequential calls to the ziggurat sampler
---
.../distribution/ZigguratSamplerPerformance.java | 251 ++++++++++++++++++++-
1 file changed, 247 insertions(+), 4 deletions(-)
diff --git
a/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/sampling/distribution/ZigguratSamplerPerformance.java
b/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/sampling/distribution/ZigguratSamplerPerformance.java
index 7a2f8af..45e56c1 100644
---
a/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/sampling/distribution/ZigguratSamplerPerformance.java
+++
b/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/sampling/distribution/ZigguratSamplerPerformance.java
@@ -48,6 +48,13 @@ import java.util.concurrent.TimeUnit;
@State(Scope.Benchmark)
@Fork(value = 1, jvmArgs = {"-server", "-Xms128M", "-Xmx128M"})
public class ZigguratSamplerPerformance {
+ /** The name for the {@link ZigguratNormalizedGaussianSampler}. */
+ private static final String GAUSSIAN_128 = "Gaussian128";
+ /** The name for a copy of the {@link ZigguratNormalizedGaussianSampler}
with a table of size 256. */
+ private static final String GAUSSIAN_256 = "Gaussian256";
+ /** The name for the {@link ZigguratSampler.NormalizedGaussian}. */
+ private static final String MOD_GAUSSIAN = "ModGaussian";
+
/**
* The value.
*
@@ -177,7 +184,7 @@ public class ZigguratSamplerPerformance {
/**
* The sampler type.
*/
- @Param({"Gaussian128", "Gaussian256", "Exponential", "ModGaussian",
"ModExponential",
+ @Param({GAUSSIAN_128, GAUSSIAN_256, "Exponential", MOD_GAUSSIAN,
"ModExponential",
"ModGaussian2", "ModExponential2"})
private String type;
@@ -196,13 +203,13 @@ public class ZigguratSamplerPerformance {
public void setup() {
final RandomSource randomSource =
RandomSource.valueOf(randomSourceName);
final UniformRandomProvider rng = randomSource.create();
- if ("Gaussian128".equals(type)) {
+ if (GAUSSIAN_128.equals(type)) {
sampler = ZigguratNormalizedGaussianSampler.of(rng);
- } else if ("Gaussian256".equals(type)) {
+ } else if (GAUSSIAN_256.equals(type)) {
sampler = new ZigguratNormalizedGaussianSampler256(rng);
} else if ("Exponential".equals(type)) {
sampler = new ZigguratExponentialSampler(rng);
- } else if ("ModGaussian".equals(type)) {
+ } else if (MOD_GAUSSIAN.equals(type)) {
sampler = ZigguratSampler.NormalizedGaussian.of(rng);
} else if ("ModExponential".equals(type)) {
sampler = ZigguratSampler.Exponential.of(rng);
@@ -217,6 +224,231 @@ public class ZigguratSamplerPerformance {
}
/**
+ * The samplers to use for testing the ziggurat method with sequential
sample generation.
+ * Defines the RandomSource and the sampler type.
+ *
+ * <p>This specifically targets the Gaussian sampler. The modified
ziggurat sampler
+ * for the exponential distribution is always faster than the standard
zigurat sampler.
+ * The modified ziggurat sampler is faster on single samples than the
standard sampler
+ * but on repeat calls to generate multiple deviates the standard sampler
can be faster
+ * depending on the JDK (modern JDKs are faster with the 'old' sampler).
+ */
+ @State(Scope.Benchmark)
+ public static class SequentialSources {
+ /**
+ * RNG providers.
+ *
+ * <p>Use different speeds.</p>
+ *
+ * @see <a
href="https://commons.apache.org/proper/commons-rng/userguide/rng.html";>
+ * Commons RNG user guide</a>
+ */
+ @Param({"XO_RO_SHI_RO_128_PP",
+ //"MWC_256",
+ //"JDK"
+ })
+ private String randomSourceName;
+
+ /** The sampler type. */
+ @Param({GAUSSIAN_128, GAUSSIAN_256, MOD_GAUSSIAN})
+ private String type;
+
+ /** The size. */
+ @Param({"1", "2", "3", "4", "5", "10", "20", "40"})
+ private int size;
+
+ /** The sampler. */
+ private ContinuousSampler sampler;
+
+ /**
+ * @return the sampler.
+ */
+ public ContinuousSampler getSampler() {
+ return sampler;
+ }
+
+ /** Instantiates sampler. */
+ @Setup
+ public void setup() {
+ final RandomSource randomSource =
RandomSource.valueOf(randomSourceName);
+ final UniformRandomProvider rng = randomSource.create();
+ ContinuousSampler s = null;
+ if (GAUSSIAN_128.equals(type)) {
+ s = ZigguratNormalizedGaussianSampler.of(rng);
+ } else if (GAUSSIAN_256.equals(type)) {
+ s = new ZigguratNormalizedGaussianSampler256(rng);
+ } else if (MOD_GAUSSIAN.equals(type)) {
+ s = ZigguratSampler.NormalizedGaussian.of(rng);
+ } else {
+ throwIllegalStateException(type);
+ }
+ sampler = createSampler(size, s);
+ }
+
+ /**
+ * Creates the sampler for the specified number of samples.
+ *
+ * @param size the size
+ * @param s the sampler to create the samples
+ * @return the sampler
+ */
+ private static ContinuousSampler createSampler(int size,
ContinuousSampler s) {
+ // Create size samples
+ switch (size) {
+ case 1:
+ return new Size1Sampler(s);
+ case 2:
+ return new Size2Sampler(s);
+ case 3:
+ return new Size3Sampler(s);
+ case 4:
+ return new Size4Sampler(s);
+ case 5:
+ return new Size5Sampler(s);
+ default:
+ return new SizeNSampler(s, size);
+ }
+ }
+
+ /**
+ * Create a specified number of samples from an underlying sampler.
+ */
+ abstract static class SizeSampler implements ContinuousSampler {
+ /** The sampler. */
+ protected ContinuousSampler delegate;
+
+ /**
+ * @param delegate the sampler to create the samples
+ */
+ SizeSampler(ContinuousSampler delegate) {
+ this.delegate = delegate;
+ }
+ }
+
+ /**
+ * Create 1 sample from the sampler.
+ */
+ static class Size1Sampler extends SizeSampler {
+ /**
+ * @param delegate the sampler to create the samples
+ */
+ Size1Sampler(ContinuousSampler delegate) {
+ super(delegate);
+ }
+
+ @Override
+ public double sample() {
+ return delegate.sample();
+ }
+ }
+
+ /**
+ * Create 2 samples from the sampler.
+ */
+ static class Size2Sampler extends SizeSampler {
+ /**
+ * @param delegate the sampler to create the samples
+ */
+ Size2Sampler(ContinuousSampler delegate) {
+ super(delegate);
+ }
+
+ @Override
+ public double sample() {
+ delegate.sample();
+ return delegate.sample();
+ }
+ }
+
+ /**
+ * Create 3 samples from the sampler.
+ */
+ static class Size3Sampler extends SizeSampler {
+ /**
+ * @param delegate the sampler to create the samples
+ */
+ Size3Sampler(ContinuousSampler delegate) {
+ super(delegate);
+ }
+
+ @Override
+ public double sample() {
+ delegate.sample();
+ delegate.sample();
+ return delegate.sample();
+ }
+ }
+
+ /**
+ * Create 4 samples from the sampler.
+ */
+ static class Size4Sampler extends SizeSampler {
+ /**
+ * @param delegate the sampler to create the samples
+ */
+ Size4Sampler(ContinuousSampler delegate) {
+ super(delegate);
+ }
+
+ @Override
+ public double sample() {
+ delegate.sample();
+ delegate.sample();
+ delegate.sample();
+ return delegate.sample();
+ }
+ }
+
+ /**
+ * Create 5 samples from the sampler.
+ */
+ static class Size5Sampler extends SizeSampler {
+ /**
+ * @param delegate the sampler to create the samples
+ */
+ Size5Sampler(ContinuousSampler delegate) {
+ super(delegate);
+ }
+
+ @Override
+ public double sample() {
+ delegate.sample();
+ delegate.sample();
+ delegate.sample();
+ return delegate.sample();
+ }
+ }
+
+ /**
+ * Create N samples from the sampler.
+ */
+ static class SizeNSampler extends SizeSampler {
+ /** The number of samples. */
+ private final int size;
+
+ /**
+ * @param delegate the sampler to create the samples
+ * @param size the size
+ */
+ SizeNSampler(ContinuousSampler delegate, int size) {
+ super(delegate);
+ if (size < 1) {
+ throw new IllegalArgumentException("Size must be above
zero: " + size);
+ }
+ this.size = size;
+ }
+
+ @Override
+ public double sample() {
+ for (int i = size - 1; i != 0; i--) {
+ delegate.sample();
+ }
+ return delegate.sample();
+ }
+ }
+ }
+
+ /**
* <a href="https://en.wikipedia.org/wiki/Ziggurat_algorithm";>
* Marsaglia and Tsang "Ziggurat" method</a> for sampling from a
NormalizedGaussian
* distribution with mean 0 and standard deviation 1.
@@ -1255,4 +1487,15 @@ public class ZigguratSamplerPerformance {
public double sample(Sources sources) {
return sources.getSampler().sample();
}
+
+ /**
+ * Run the sampler to generate a number of samples sequentially.
+ *
+ * @param sources Source of randomness.
+ * @return the sample value
+ */
+ @Benchmark
+ public double sequentialSample(SequentialSources sources) {
+ return sources.getSampler().sample();
+ }
}
