MATH-1335 Use new RNG API.
Project: http://git-wip-us.apache.org/repos/asf/commons-math/repo Commit: http://git-wip-us.apache.org/repos/asf/commons-math/commit/a9fdcd64 Tree: http://git-wip-us.apache.org/repos/asf/commons-math/tree/a9fdcd64 Diff: http://git-wip-us.apache.org/repos/asf/commons-math/diff/a9fdcd64 Branch: refs/heads/develop Commit: a9fdcd64bf0a982901d298596151d13e56442a11 Parents: b720481 Author: Gilles <er...@apache.org> Authored: Thu May 12 15:13:06 2016 +0200 Committer: Gilles <er...@apache.org> Committed: Tue May 17 15:30:23 2016 +0200 ---------------------------------------------------------------------- .../math4/random/GaussianRandomGenerator.java | 34 +++++++++++--------- .../MultiStartMultivariateOptimizerTest.java | 20 +++++------- .../CorrelatedRandomVectorGeneratorTest.java | 16 +++------ .../random/GaussianRandomGeneratorTest.java | 9 ++---- .../UncorrelatedRandomVectorGeneratorTest.java | 8 ++--- .../GLSMultipleLinearRegressionTest.java | 13 ++++---- 6 files changed, 45 insertions(+), 55 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/commons-math/blob/a9fdcd64/src/main/java/org/apache/commons/math4/random/GaussianRandomGenerator.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/random/GaussianRandomGenerator.java b/src/main/java/org/apache/commons/math4/random/GaussianRandomGenerator.java index f3172c2..c70a7df 100644 --- a/src/main/java/org/apache/commons/math4/random/GaussianRandomGenerator.java +++ b/src/main/java/org/apache/commons/math4/random/GaussianRandomGenerator.java @@ -17,31 +17,35 @@ package org.apache.commons.math4.random; +import org.apache.commons.math4.rng.UniformRandomProvider; +import org.apache.commons.math4.distribution.RealDistribution; +import org.apache.commons.math4.distribution.NormalDistribution; + /** - * This class is a gaussian normalized random generator for scalars. - * <p>This class is a simple wrapper around the {@link - * RandomGenerator#nextGaussian} method.</p> + * Random generator that generates normally distributed samples. + * * @since 1.2 */ - public class GaussianRandomGenerator implements NormalizedRandomGenerator { + /** Gaussian distribution sampler. */ + private final RealDistribution.Sampler sampler; - /** Underlying generator. */ - private final RandomGenerator generator; - - /** Create a new generator. - * @param generator underlying random generator to use + /** + * Creates a new generator. + * + * @param generator Underlying random generator. */ - public GaussianRandomGenerator(final RandomGenerator generator) { - this.generator = generator; + public GaussianRandomGenerator(final UniformRandomProvider generator) { + sampler = new NormalDistribution().createSampler(generator); } - /** Generate a random scalar with null mean and unit standard deviation. - * @return a random scalar with null mean and unit standard deviation + /** + * Generates a random scalar with zero mean and unit standard deviation. + * + * @return a random value sampled from a normal distribution. */ @Override public double nextNormalizedDouble() { - return generator.nextGaussian(); + return sampler.sample(); } - } http://git-wip-us.apache.org/repos/asf/commons-math/blob/a9fdcd64/src/test/java/org/apache/commons/math4/optim/nonlinear/scalar/MultiStartMultivariateOptimizerTest.java ---------------------------------------------------------------------- diff --git a/src/test/java/org/apache/commons/math4/optim/nonlinear/scalar/MultiStartMultivariateOptimizerTest.java b/src/test/java/org/apache/commons/math4/optim/nonlinear/scalar/MultiStartMultivariateOptimizerTest.java index cdaf3b9..d5b2b84 100644 --- a/src/test/java/org/apache/commons/math4/optim/nonlinear/scalar/MultiStartMultivariateOptimizerTest.java +++ b/src/test/java/org/apache/commons/math4/optim/nonlinear/scalar/MultiStartMultivariateOptimizerTest.java @@ -30,8 +30,9 @@ import org.apache.commons.math4.optim.nonlinear.scalar.gradient.CircleScalar; import org.apache.commons.math4.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer; import org.apache.commons.math4.optim.nonlinear.scalar.noderiv.NelderMeadSimplex; import org.apache.commons.math4.optim.nonlinear.scalar.noderiv.SimplexOptimizer; +import org.apache.commons.math4.rng.UniformRandomProvider; +import org.apache.commons.math4.rng.RandomSource; import org.apache.commons.math4.random.GaussianRandomGenerator; -import org.apache.commons.math4.random.JDKRandomGenerator; import org.apache.commons.math4.random.RandomVectorGenerator; import org.apache.commons.math4.random.UncorrelatedRandomVectorGenerator; import org.junit.Assert; @@ -52,8 +53,7 @@ public class MultiStartMultivariateOptimizerTest { GradientMultivariateOptimizer underlying = new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE, new SimpleValueChecker(1e-10, 1e-10)); - JDKRandomGenerator g = new JDKRandomGenerator(); - g.setSeed(753289573253l); + UniformRandomProvider g = RandomSource.create(RandomSource.MT_64, 753289573253l); RandomVectorGenerator generator = new UncorrelatedRandomVectorGenerator(new double[] { 50, 50 }, new double[] { 10, 10 }, @@ -73,15 +73,12 @@ public class MultiStartMultivariateOptimizerTest { for (PointValuePair o : optima) { // we check the results of all intermediate restarts here (there are 10 such results) Vector2D center = new Vector2D(o.getPointRef()[0], o.getPointRef()[1]); - Assert.assertTrue(69.9592 < circle.getRadius(center)); - Assert.assertTrue(69.9602 > circle.getRadius(center)); - Assert.assertTrue(96.0745 < center.getX()); - Assert.assertTrue(96.0762 > center.getX()); - Assert.assertTrue(48.1344 < center.getY()); - Assert.assertTrue(48.1354 > center.getY()); + Assert.assertEquals(69.9597, circle.getRadius(center), 1e-3); + Assert.assertEquals(96.07535, center.getX(), 1.4e-3); + Assert.assertEquals(48.1349, center.getY(), 5e-3); } - Assert.assertTrue(optimizer.getEvaluations() > 850); + Assert.assertTrue(optimizer.getEvaluations() > 800); Assert.assertTrue(optimizer.getEvaluations() < 900); Assert.assertEquals(3.1267527, optimum.getValue(), 1e-8); @@ -97,8 +94,7 @@ public class MultiStartMultivariateOptimizerTest { { 0.9, 1.2 } , { 3.5, -2.3 } }); - JDKRandomGenerator g = new JDKRandomGenerator(); - g.setSeed(16069223052l); + UniformRandomProvider g = RandomSource.create(RandomSource.MT_64, 16069223052l); RandomVectorGenerator generator = new UncorrelatedRandomVectorGenerator(2, new GaussianRandomGenerator(g)); int nbStarts = 10; http://git-wip-us.apache.org/repos/asf/commons-math/blob/a9fdcd64/src/test/java/org/apache/commons/math4/random/CorrelatedRandomVectorGeneratorTest.java ---------------------------------------------------------------------- diff --git a/src/test/java/org/apache/commons/math4/random/CorrelatedRandomVectorGeneratorTest.java b/src/test/java/org/apache/commons/math4/random/CorrelatedRandomVectorGeneratorTest.java index 9b2dd82..18b6543 100644 --- a/src/test/java/org/apache/commons/math4/random/CorrelatedRandomVectorGeneratorTest.java +++ b/src/test/java/org/apache/commons/math4/random/CorrelatedRandomVectorGeneratorTest.java @@ -25,9 +25,9 @@ import org.apache.commons.math4.linear.MatrixUtils; import org.apache.commons.math4.linear.RealMatrix; import org.apache.commons.math4.random.CorrelatedRandomVectorGenerator; import org.apache.commons.math4.random.GaussianRandomGenerator; -import org.apache.commons.math4.random.JDKRandomGenerator; import org.apache.commons.math4.random.NormalizedRandomGenerator; -import org.apache.commons.math4.random.RandomGenerator; +import org.apache.commons.math4.rng.UniformRandomProvider; +import org.apache.commons.math4.rng.RandomSource; import org.apache.commons.math4.stat.correlation.StorelessCovariance; import org.apache.commons.math4.stat.descriptive.moment.VectorialCovariance; import org.apache.commons.math4.stat.descriptive.moment.VectorialMean; @@ -61,9 +61,7 @@ public class CorrelatedRandomVectorGeneratorTest { } } - RandomGenerator rg = new JDKRandomGenerator(); - rg.setSeed(17399225432l); - GaussianRandomGenerator rawGenerator = new GaussianRandomGenerator(rg); + GaussianRandomGenerator rawGenerator = new GaussianRandomGenerator(RandomSource.create(RandomSource.WELL_1024_A, 17399225432l)); generator = new CorrelatedRandomVectorGenerator(mean, covariance, 1.0e-12 * covariance.getNorm(), @@ -85,9 +83,7 @@ public class CorrelatedRandomVectorGeneratorTest { { 6, 2, -1, 197 } }; RealMatrix covRM = MatrixUtils.createRealMatrix(cov); - JDKRandomGenerator jg = new JDKRandomGenerator(); - jg.setSeed(5322145245211l); - NormalizedRandomGenerator rg = new GaussianRandomGenerator(jg); + NormalizedRandomGenerator rg = new GaussianRandomGenerator(RandomSource.create(RandomSource.WELL_1024_A, 5322145245211l)); CorrelatedRandomVectorGenerator sg = new CorrelatedRandomVectorGenerator(mean, covRM, 0.00001, rg); @@ -181,7 +177,7 @@ public class CorrelatedRandomVectorGeneratorTest { new double[cov.length], matrix, small, - new GaussianRandomGenerator(new Well1024a(0x366a26b94e520f41l))); + new GaussianRandomGenerator(RandomSource.create(RandomSource.WELL_1024_A, 0x366a26b94e520f41l))); } private void testSampler(final double[][] covMatrix, int samples, double epsilon) { @@ -196,7 +192,5 @@ public class CorrelatedRandomVectorGeneratorTest { for (int r = 0; r < covMatrix.length; ++r) { TestUtils.assertEquals(covMatrix[r], sampleCov[r], epsilon); } - } - } http://git-wip-us.apache.org/repos/asf/commons-math/blob/a9fdcd64/src/test/java/org/apache/commons/math4/random/GaussianRandomGeneratorTest.java ---------------------------------------------------------------------- diff --git a/src/test/java/org/apache/commons/math4/random/GaussianRandomGeneratorTest.java b/src/test/java/org/apache/commons/math4/random/GaussianRandomGeneratorTest.java index 9c46f0d..031f55d 100644 --- a/src/test/java/org/apache/commons/math4/random/GaussianRandomGeneratorTest.java +++ b/src/test/java/org/apache/commons/math4/random/GaussianRandomGeneratorTest.java @@ -18,8 +18,8 @@ package org.apache.commons.math4.random; import org.apache.commons.math4.random.GaussianRandomGenerator; -import org.apache.commons.math4.random.JDKRandomGenerator; -import org.apache.commons.math4.random.RandomGenerator; +import org.apache.commons.math4.rng.UniformRandomProvider; +import org.apache.commons.math4.rng.RandomSource; import org.apache.commons.math4.stat.StatUtils; import org.junit.Assert; import org.junit.Test; @@ -29,9 +29,7 @@ public class GaussianRandomGeneratorTest { @Test public void testMeanAndStandardDeviation() { - RandomGenerator rg = new JDKRandomGenerator(); - rg.setSeed(17399225432l); - GaussianRandomGenerator generator = new GaussianRandomGenerator(rg); + GaussianRandomGenerator generator = new GaussianRandomGenerator(RandomSource.create(RandomSource.MT, 17399225432l)); double[] sample = new double[10000]; for (int i = 0; i < sample.length; ++i) { sample[i] = generator.nextNormalizedDouble(); @@ -39,5 +37,4 @@ public class GaussianRandomGeneratorTest { Assert.assertEquals(0.0, StatUtils.mean(sample), 0.012); Assert.assertEquals(1.0, StatUtils.variance(sample), 0.01); } - } http://git-wip-us.apache.org/repos/asf/commons-math/blob/a9fdcd64/src/test/java/org/apache/commons/math4/random/UncorrelatedRandomVectorGeneratorTest.java ---------------------------------------------------------------------- diff --git a/src/test/java/org/apache/commons/math4/random/UncorrelatedRandomVectorGeneratorTest.java b/src/test/java/org/apache/commons/math4/random/UncorrelatedRandomVectorGeneratorTest.java index bc80769..2c2df9d 100644 --- a/src/test/java/org/apache/commons/math4/random/UncorrelatedRandomVectorGeneratorTest.java +++ b/src/test/java/org/apache/commons/math4/random/UncorrelatedRandomVectorGeneratorTest.java @@ -18,9 +18,8 @@ package org.apache.commons.math4.random; import org.apache.commons.math4.linear.RealMatrix; +import org.apache.commons.math4.rng.RandomSource; import org.apache.commons.math4.random.GaussianRandomGenerator; -import org.apache.commons.math4.random.JDKRandomGenerator; -import org.apache.commons.math4.random.RandomGenerator; import org.apache.commons.math4.random.UncorrelatedRandomVectorGenerator; import org.apache.commons.math4.stat.descriptive.moment.VectorialCovariance; import org.apache.commons.math4.stat.descriptive.moment.VectorialMean; @@ -35,11 +34,10 @@ public class UncorrelatedRandomVectorGeneratorTest { public UncorrelatedRandomVectorGeneratorTest() { mean = new double[] {0.0, 1.0, -3.0, 2.3}; standardDeviation = new double[] {1.0, 2.0, 10.0, 0.1}; - RandomGenerator rg = new JDKRandomGenerator(); - rg.setSeed(17399225432l); generator = new UncorrelatedRandomVectorGenerator(mean, standardDeviation, - new GaussianRandomGenerator(rg)); + new GaussianRandomGenerator(RandomSource.create(RandomSource.MT, + 17399225432l))); } @Test http://git-wip-us.apache.org/repos/asf/commons-math/blob/a9fdcd64/src/test/java/org/apache/commons/math4/stat/regression/GLSMultipleLinearRegressionTest.java ---------------------------------------------------------------------- diff --git a/src/test/java/org/apache/commons/math4/stat/regression/GLSMultipleLinearRegressionTest.java b/src/test/java/org/apache/commons/math4/stat/regression/GLSMultipleLinearRegressionTest.java index 06fbc26..a5b61d1 100644 --- a/src/test/java/org/apache/commons/math4/stat/regression/GLSMultipleLinearRegressionTest.java +++ b/src/test/java/org/apache/commons/math4/stat/regression/GLSMultipleLinearRegressionTest.java @@ -27,8 +27,10 @@ import org.apache.commons.math4.linear.RealMatrix; import org.apache.commons.math4.linear.RealVector; import org.apache.commons.math4.random.CorrelatedRandomVectorGenerator; import org.apache.commons.math4.random.GaussianRandomGenerator; -import org.apache.commons.math4.random.JDKRandomGenerator; -import org.apache.commons.math4.random.RandomGenerator; +import org.apache.commons.math4.rng.UniformRandomProvider; +import org.apache.commons.math4.rng.RandomSource; +import org.apache.commons.math4.distribution.RealDistribution; +import org.apache.commons.math4.distribution.NormalDistribution; import org.apache.commons.math4.stat.correlation.Covariance; import org.apache.commons.math4.stat.descriptive.DescriptiveStatistics; import org.apache.commons.math4.stat.regression.GLSMultipleLinearRegression; @@ -220,8 +222,8 @@ public class GLSMultipleLinearRegressionTest extends MultipleLinearRegressionAbs */ @Test public void testGLSEfficiency() { - RandomGenerator rg = new JDKRandomGenerator(); - rg.setSeed(200); // Seed has been selected to generate non-trivial covariance + final UniformRandomProvider rg = RandomSource.create(RandomSource.MT, 123456789L); + final RealDistribution.Sampler gauss = new NormalDistribution().createSampler(rg); // Assume model has 16 observations (will use Longley data). Start by generating // non-constant variances for the 16 error terms. @@ -237,7 +239,7 @@ public class GLSMultipleLinearRegressionTest extends MultipleLinearRegressionAbs RealMatrix errorSeeds = MatrixUtils.createRealMatrix(numSeeds, nObs); for (int i = 0; i < numSeeds; i++) { for (int j = 0; j < nObs; j++) { - errorSeeds.setEntry(i, j, rg.nextGaussian() * sigma[j]); + errorSeeds.setEntry(i, j, gauss.sample() * sigma[j]); } } @@ -297,5 +299,4 @@ public class GLSMultipleLinearRegressionTest extends MultipleLinearRegressionAbs assert(olsBetaStats.getMean() > 1.5 * glsBetaStats.getMean()); assert(olsBetaStats.getStandardDeviation() > glsBetaStats.getStandardDeviation()); } - }
