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Unneeded dependency (unit test).

This commit is contained in:
Gilles Sadowski 2021-06-05 14:49:01 +02:00
parent 839f8b45a3
commit dd73a1ba80
1 changed files with 21 additions and 9 deletions
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30
commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/filter/KalmanFilterTest.java
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@ -14,17 +14,18 @@
package org.apache.commons.math4.legacy.filter;
import org.apache.commons.statistics.distribution.ContinuousDistribution;
import org.apache.commons.statistics.distribution.NormalDistribution;
import org.apache.commons.rng.simple.RandomSource;
import org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler;
import org.apache.commons.rng.sampling.distribution.GaussianSampler;
import org.apache.commons.rng.sampling.distribution.ContinuousSampler;
import org.apache.commons.numbers.core.Precision;
import org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix;
import org.apache.commons.math4.legacy.linear.ArrayRealVector;
import org.apache.commons.math4.legacy.linear.MatrixDimensionMismatchException;
import org.apache.commons.math4.legacy.linear.MatrixUtils;
import org.apache.commons.math4.legacy.linear.RealMatrix;
import org.apache.commons.math4.legacy.linear.RealVector;
import org.apache.commons.rng.simple.RandomSource;
import org.apache.commons.math4.legacy.core.jdkmath.AccurateMath;
import org.apache.commons.numbers.core.Precision;
import org.junit.Assert;
import org.junit.Test;
@ -121,7 +122,7 @@ public class KalmanFilterTest {
RealVector pNoise = new ArrayRealVector(1);
RealVector mNoise = new ArrayRealVector(1);
final ContinuousDistribution.Sampler rand = new NormalDistribution(0, 1).createSampler(RandomSource.create(RandomSource.WELL_19937_C));
final ContinuousSampler rand = createGaussianSampler(0, 1);
// iterate 60 steps
for (int i = 0; i < 60; i++) {
@ -210,7 +211,7 @@ public class KalmanFilterTest {
double[] expectedInitialState = new double[] { 0.0, 0.0 };
assertVectorEquals(expectedInitialState, filter.getStateEstimation());
final ContinuousDistribution.Sampler rand = new NormalDistribution(0, 1).createSampler(RandomSource.create(RandomSource.WELL_19937_C));
final ContinuousSampler rand = createGaussianSampler(0, 1);
RealVector tmpPNoise = new ArrayRealVector(
new double[] { AccurateMath.pow(dt, 2d) / 2d, dt });
@ -387,7 +388,7 @@ public class KalmanFilterTest {
final MeasurementModel mm = new DefaultMeasurementModel(H, R);
final KalmanFilter filter = new KalmanFilter(pm, mm);
final ContinuousDistribution.Sampler dist = new NormalDistribution(0, measurementNoise).createSampler(RandomSource.create(RandomSource.WELL_19937_C));
final ContinuousSampler rand = createGaussianSampler(0, measurementNoise);
for (int i = 0; i < iterations; i++) {
// get the "real" cannonball position
@ -395,8 +396,8 @@ public class KalmanFilterTest {
double y = cannonball.getY();
// apply measurement noise to current cannonball position
double nx = x + dist.sample();
double ny = y + dist.sample();
double nx = x + rand.sample();
double ny = y + rand.sample();
cannonball.step();
@ -439,4 +440,15 @@ public class KalmanFilterTest {
}
}
}
/**
* @param mu Mean
* @param sigma Standard deviation.
* @return a sampler that follows the N(mu,sigma) distribution.
*/
private ContinuousSampler createGaussianSampler(double mu,
double sigma) {
return GaussianSampler.of(ZigguratNormalizedGaussianSampler.of(RandomSource.create(RandomSource.JSF_64)),
mu, sigma);
}
}