DistEmpiricalDiscreteDouble.java
package nl.tudelft.simulation.jstats.distributions;
import nl.tudelft.simulation.jstats.distributions.empirical.DiscreteEmpiricalDistribution;
import nl.tudelft.simulation.jstats.distributions.empirical.DistributionEntry;
import nl.tudelft.simulation.jstats.streams.StreamInterface;
/**
* The empirical distribution is a distribution where the information is stored in an EmpiricalDistribution, consisting of pairs
* of values and cumulative probabilities. <br>
* Note that interpolated is false for the EmpiricalDistribution to be used in this class, so the function in essence behaves as
* a <b>discrete</b> distribution, albeit with double values as the outcome. The probability density function returns the
* equivalent of the discrete distribution function; of course the real probability density function from the viewpoint of a
* continuous distribution does not exist.
* <p>
* Copyright (c) 2002-2024 Delft University of Technology, Jaffalaan 5, 2628 BX Delft, the Netherlands. All rights reserved. See
* for project information <a href="https://simulation.tudelft.nl/" target="_blank"> https://simulation.tudelft.nl</a>. The DSOL
* project is distributed under a three-clause BSD-style license, which can be found at
* <a href="https://https://simulation.tudelft.nl/dsol/docs/latest/license.html" target="_blank">
* https://https://simulation.tudelft.nl/dsol/docs/latest/license.html</a>.
* </p>
* @author <a href="https://www.tudelft.nl/averbraeck">Alexander Verbraeck</a>
*/
public class DistEmpiricalDiscreteDouble extends DistContinuous
{
/** */
private static final long serialVersionUID = 20210403L;
/** is the distribution grouped? */
private final DiscreteEmpiricalDistribution empiricalDistribution;
/**
* constructs a new DistEmpirical.
* @param stream StreamInterface; the stream to use
* @param empiricalDistribution EmpiricalDistributionInterface; the cumulative distribution to use
*/
public DistEmpiricalDiscreteDouble(final StreamInterface stream, final DiscreteEmpiricalDistribution empiricalDistribution)
{
super(stream);
this.empiricalDistribution = empiricalDistribution;
}
/** {@inheritDoc} */
@Override
public double draw()
{
double u = this.stream.nextDouble();
return this.empiricalDistribution.getCeilingEntry(u).getValue().doubleValue();
}
/** {@inheritDoc} */
@Override
public double getProbabilityDensity(final double x)
{
DistributionEntry entry0 = this.empiricalDistribution.getFloorEntryForValue(x);
if (entry0 == null || entry0.getValue().longValue() != x)
{
return 0.0;
}
double c1 = entry0.getCumulativeProbability();
DistributionEntry entryp = this.empiricalDistribution.getPrevEntry(c1);
return (entryp == null) ? c1 : c1 - entryp.getCumulativeProbability();
}
}