Package org.cloudbus.cloudsim.distributions

Class LogNormalDistr

java.lang.Object
org.apache.commons.math3.distribution.AbstractRealDistribution
org.apache.commons.math3.distribution.LogNormalDistribution
org.cloudbus.cloudsim.distributions.LogNormalDistr
All Implemented Interfaces:
Serializable, org.apache.commons.math3.distribution.RealDistribution, ContinuousDistribution, StatisticalDistribution
public class LogNormalDistr extends org.apache.commons.math3.distribution.LogNormalDistribution implements ContinuousDistribution
A Pseudo-Random Number Generator following the Log-normal distribution.
Since:
CloudSim Toolkit 1.0
Author:
Marcos Dias de Assuncao
See Also:

  • Field Summary

    Fields inherited from class org.apache.commons.math3.distribution.LogNormalDistribution

    DEFAULT_INVERSE_ABSOLUTE_ACCURACY

    Fields inherited from class org.apache.commons.math3.distribution.AbstractRealDistribution

    random, randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY

    Fields inherited from interface org.cloudbus.cloudsim.distributions.ContinuousDistribution

    NULL

  • Constructor Summary

    Constructors
    Constructor
    Description
    LogNormalDistr(double shape, double scale)
    Creates a Log-normal Pseudo-Random Number Generator (PRNG).
    LogNormalDistr(double shape, double scale, long seed)
    Creates a Log-normal Pseudo-Random Number Generator (PRNG).
    LogNormalDistr(double shape, double scale, long seed, org.apache.commons.math3.random.RandomGenerator rng)
    Creates a Log-normal Pseudo-Random Number Generator (PRNG).

  • Method Summary

    Modifier and Type
    Method
    Description
    long
    getSeed()
    Gets the seed used to initialize the generator
    boolean
    isApplyAntitheticVariates()
    Indicates if the Pseudo-Random Number Generator (RNG) applies the Antithetic Variates Technique in order to reduce variance of experiments using the generated numbers.
    double
    originalSample()
    Generate a new pseudo random number directly from the RealDistribution.sample() method.
    void
    reseedRandomGenerator(long seed)
     
    LogNormalDistr
    setApplyAntitheticVariates(boolean applyAntitheticVariates)
    Indicates if the Pseudo-Random Number Generator (RNG) applies the Antithetic Variates Technique in order to reduce variance of experiments using the generated numbers.

    Methods inherited from class org.apache.commons.math3.distribution.LogNormalDistribution

    cumulativeProbability, cumulativeProbability, density, getNumericalMean, getNumericalVariance, getScale, getShape, getSolverAbsoluteAccuracy, getSupportLowerBound, getSupportUpperBound, isSupportConnected, isSupportLowerBoundInclusive, isSupportUpperBoundInclusive, logDensity, probability, sample

    Methods inherited from class org.apache.commons.math3.distribution.AbstractRealDistribution

    inverseCumulativeProbability, probability, sample

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    Methods inherited from interface org.cloudbus.cloudsim.distributions.ContinuousDistribution

    sample

    Methods inherited from interface org.apache.commons.math3.distribution.RealDistribution

    cumulativeProbability, cumulativeProbability, density, getNumericalMean, getNumericalVariance, getSupportLowerBound, getSupportUpperBound, inverseCumulativeProbability, isSupportConnected, isSupportLowerBoundInclusive, isSupportUpperBoundInclusive, probability, sample

  • Constructor Details

    • LogNormalDistr

      public LogNormalDistr(double shape, double scale)
      Creates a Log-normal Pseudo-Random Number Generator (PRNG).
      Parameters:
      shape - the shape parameter of this distribution
      scale - the scale parameter of this distribution

    • LogNormalDistr

      public LogNormalDistr(double shape, double scale, long seed)
      Creates a Log-normal Pseudo-Random Number Generator (PRNG).
      Parameters:
      shape - the shape parameter of this distribution
      scale - the scale parameter of this distribution
      seed - the seed

    • LogNormalDistr

      public LogNormalDistr(double shape, double scale, long seed, org.apache.commons.math3.random.RandomGenerator rng)
      Creates a Log-normal Pseudo-Random Number Generator (PRNG).
      Parameters:
      shape - the shape parameter of this distribution
      scale - the scale parameter of this distribution
      seed - the seed

  • Method Details

    • reseedRandomGenerator

      public void reseedRandomGenerator(long seed)
      Specified by:
      reseedRandomGenerator in interface org.apache.commons.math3.distribution.RealDistribution
      Overrides:
      reseedRandomGenerator in class org.apache.commons.math3.distribution.AbstractRealDistribution

    • getSeed

      public long getSeed()
      Description copied from interface: StatisticalDistribution
      Gets the seed used to initialize the generator
      Specified by:
      getSeed in interface StatisticalDistribution
      Returns:

    • isApplyAntitheticVariates

      public boolean isApplyAntitheticVariates()
      Description copied from interface: StatisticalDistribution
      Indicates if the Pseudo-Random Number Generator (RNG) applies the Antithetic Variates Technique in order to reduce variance of experiments using the generated numbers. This technique doesn't work for all the cases. However, in the cases it can be applied, in order to it work, one have to perform some actions. Consider an experiment that has to run "n" times. The first half of these experiments has to use the seeds the developer want. However, the second half of the experiments have to set the applyAntitheticVariates attribute to true and use the seeds of the first half of experiments. Thus, the first half of experiments are run using PRNGs that return random numbers as U(0, 1)[seed_1], ..., U(0, 1)[seed_n]. The second half of experiments then uses the seeds of the first half of experiments, returning random numbers as 1 - U(0, 1)[seed_1], ..., 1 - U(0, 1)[seed_n].
      Specified by:
      isApplyAntitheticVariates in interface StatisticalDistribution
      Returns:
      true if the technique is applied, false otherwise
      See Also:

    • setApplyAntitheticVariates

      public LogNormalDistr setApplyAntitheticVariates(boolean applyAntitheticVariates)
      Description copied from interface: StatisticalDistribution
      Indicates if the Pseudo-Random Number Generator (RNG) applies the Antithetic Variates Technique in order to reduce variance of experiments using the generated numbers.
      Specified by:
      setApplyAntitheticVariates in interface StatisticalDistribution
      Parameters:
      applyAntitheticVariates - true if the technique is to be applied, false otherwise
      See Also:

    • originalSample

      public double originalSample()
      Description copied from interface: StatisticalDistribution
      Generate a new pseudo random number directly from the RealDistribution.sample() method. This way, the Antithetic Variates Technique is ignored if enabled.

      Usually you shouldn't call this method but StatisticalDistribution.sample() instead.

      Specified by:
      originalSample in interface StatisticalDistribution
      Returns:
      the next pseudo random number in the sequence, following the implemented distribution, ignoring the Antithetic Variates Technique if enabled