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

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Here is the source code for org.onebusaway.nyc.vehicle_tracking.impl.particlefilter.SensorModelResult.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 com.google.common.base.Objects;

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

import java.util.ArrayList;
import java.util.List;

public class SensorModelResult {

    private String name;

    private double logProbability = 0.0;

    private double probability = 1.0;

    private List<SensorModelResult> results;

    private boolean refresh = true;

    public SensorModelResult(String name) throws BadProbabilityParticleFilterException {
        this(name, 1.0);
    }

    public SensorModelResult(String name, double probability) throws BadProbabilityParticleFilterException {
        if (Double.isNaN(probability) || probability < 0d || probability > 1d)
            throw new BadProbabilityParticleFilterException("invalid weight assignment: weight=" + probability);
        this.name = name;
        this.logProbability = FastMath.log(probability);
        this.probability = probability;
        this.refresh = false;
    }

    public String getName() {
        return name;
    }

    public void setName(String name) {
        this.name = name;
    }

    /**
     * Returns, and lazily computes, the non-log probability. <br>
     * XXX Note that this "compute-on-demand" approach is not thread-safe.
     * 
     * @return non-log probability
     */
    public double getProbability() {
        if (this.refresh) {
            this.probability = FastMath.exp(logProbability);
            this.refresh = false;
        }
        return this.probability;
    }

    public double getLogProbability() {
        return logProbability;
    }

    public void setProbability(double probability) throws BadProbabilityParticleFilterException {
        if (Double.isNaN(probability) || probability < 0d || probability > 1d)
            throw new BadProbabilityParticleFilterException("invalid weight assignment: weight=" + probability);
        this.logProbability = FastMath.log(probability);
        this.probability = probability;
        this.refresh = false;
    }

    public void setLogProbability(double probability) throws BadProbabilityParticleFilterException {
        if (Double.isNaN(probability) || probability > 0d)
            throw new BadProbabilityParticleFilterException("invalid weight assignment: weight=" + probability);
        this.logProbability = probability;
        this.refresh = true;
    }

    public List<SensorModelResult> getResults() {
        return results;
    }

    public void setResults(List<SensorModelResult> results) {
        this.results = results;
    }

    public SensorModelResult addResult(String name, double probability)
            throws BadProbabilityParticleFilterException {
        return addResult(new SensorModelResult(name, probability));
    }

    public SensorModelResult addLogResultAsAnd(String name, double logProbability)
            throws BadProbabilityParticleFilterException {
        final SensorModelResult newResult = new SensorModelResult(name);
        newResult.setLogProbability(logProbability);
        return addResultAsAnd(newResult);
    }

    public SensorModelResult addResultAsAnd(String name, double probability)
            throws BadProbabilityParticleFilterException {
        return addResultAsAnd(new SensorModelResult(name, probability));
    }

    public SensorModelResult addResult(SensorModelResult result) {
        if (results == null)
            results = new ArrayList<SensorModelResult>();
        results.add(result);

        return result;
    }

    public SensorModelResult addResultAsAnd(SensorModelResult result) {
        this.logProbability += result.logProbability;
        this.refresh = true;
        return addResult(result);
    }

    @Override
    public String toString() {
        final Objects.ToStringHelper toStringHelper = Objects.toStringHelper("SensorModelResult");
        toStringHelper.add(name, getProbability());
        if (results != null) {
            for (final SensorModelResult res : results) {
                toStringHelper.addValue("\n\t" + res.toString());
            }
        }
        return toStringHelper.toString();
    }

}