org.onebusaway.nyc.vehicle_tracking.impl.particlefilter.CategoricalDistTest.java Source code

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Here is the source code for org.onebusaway.nyc.vehicle_tracking.impl.particlefilter.CategoricalDistTest.java

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/**
 * Copyright (c) 2011 Metropolitan Transportation Authority
 * 
 * Licensed under the Apache License, Version 2.0 (the "License"); you may not
 * use this file except in compliance with the License. You may obtain a copy of
 * the License at
 * 
 * http://www.apache.org/licenses/LICENSE-2.0
 * 
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
 * License for the specific language governing permissions and limitations under
 * the License.
 */
package org.onebusaway.nyc.vehicle_tracking.impl.particlefilter;

import static org.junit.Assert.assertEquals;

import org.onebusaway.collections.Counter;
import org.onebusaway.nyc.vehicle_tracking.impl.inference.CategoricalDist;

import com.google.common.collect.HashMultiset;
import com.google.common.collect.Multiset;

import org.apache.commons.math.util.FastMath;
import org.junit.Test;

public class CategoricalDistTest {

    @Test
    public void testSampleA() throws ParticleFilterException {

        final CategoricalDist<String> cdf = new CategoricalDist<String>();
        cdf.logPut(FastMath.log(0.3 * 1e-5), "c");
        cdf.logPut(FastMath.log(0.3), "c");
        cdf.logPut(FastMath.log(0.2), "c");
        cdf.logPut(FastMath.log(0.01), "a");
        cdf.logPut(FastMath.log(0.001), "a");
        cdf.logPut(FastMath.log(0.2 * 1e-7), "b");

        final Counter<String> counter = new Counter<String>();
        final int iterations = 1000;

        for (int i = 0; i < iterations; i++)
            counter.increment(cdf.sample());

        final double a = counter.getCount("a") / (double) iterations;
        final double b = counter.getCount("b") / (double) iterations;
        final double c = counter.getCount("c") / (double) iterations;

        final double cummulativeProb = cdf.getCummulativeProb();
        assertEquals(a, cdf.density("a") / cummulativeProb, .05);
        assertEquals(b, cdf.density("b") / cummulativeProb, .05);
        assertEquals(c, cdf.density("c") / cummulativeProb, .05);

        cdf.logPut(FastMath.log(0.001), "d");

        final Multiset<String> res = cdf.sample(iterations);
        assertEquals(res.count("a") / (double) iterations, cdf.density("a") / cummulativeProb, .05);
        assertEquals(res.count("b") / (double) iterations, cdf.density("b") / cummulativeProb, .05);
        assertEquals(res.count("c") / (double) iterations, cdf.density("c") / cummulativeProb, .05);
        assertEquals(res.count("d") / (double) iterations, cdf.density("d") / cummulativeProb, .05);

        final Multiset<Particle> testSet = HashMultiset.create();
        final Particle p1 = new Particle(0, null, cdf.density("a"));
        testSet.add(p1);
        final Particle p2 = new Particle(0, null, cdf.density("b"));
        testSet.add(p2);
        final Particle p3 = new Particle(0, null, cdf.density("c"));
        testSet.add(p3);
        final Particle p4 = new Particle(0, null, cdf.density("d"));
        testSet.add(p4);
        final Multiset<Particle> resSet = ParticleFilter.lowVarianceSampler(testSet, iterations);
        final Counter<Particle> counter2 = new Counter<Particle>();
        for (final Particle p : resSet)
            counter2.increment(p);
        final double a2 = counter2.getCount(p1) / (double) iterations;
        final double b2 = counter2.getCount(p2) / (double) iterations;
        final double c2 = counter2.getCount(p3) / (double) iterations;
        final double d2 = counter2.getCount(p4) / (double) iterations;
        assertEquals(a2, cdf.density("a") / cummulativeProb, .05);
        assertEquals(b2, cdf.density("b") / cummulativeProb, .05);
        assertEquals(c2, cdf.density("c") / cummulativeProb, .05);
        assertEquals(d2, cdf.density("d") / cummulativeProb, .05);

    }

    /*
     * 
     * private final int TRIES = 10000000;
     * 
     * @Test public void testSamples() {
     * 
     * CDFMap<String> cdf = new CDFMap<String>(); cdf.put(0.1, "a"); cdf.put(0.2,
     * "b"); cdf.put(0.3, "c");
     * 
     * List<String> values = cdf.sample(TRIES); Counter<String> counter = new
     * Counter<String>(); for (String value : values) counter.increment(value);
     * 
     * double expectedA = TRIES*0.1/0.6; double expectedB = TRIES*0.2/0.6; double
     * expectedC = TRIES*0.3/0.6;
     * 
     * double chi2 = Math.pow((double)counter.getCount("a") - expectedA,
     * 2)/expectedA; chi2 += Math.pow((double)counter.getCount("b") - expectedB,
     * 2)/expectedB; chi2 += Math.pow((double)counter.getCount("c") - expectedC,
     * 2)/expectedC;
     * 
     * double testStat = ChiSquareDist.barF(2, 6, chi2); assertTrue(testStat >
     * 0.05); }
     */
}