Package com.github.tommyettinger.random.distribution

Class KnobDistribution

java.lang.Object
com.github.tommyettinger.random.distribution.Distribution
com.github.tommyettinger.random.distribution.KnobDistribution
All Implemented Interfaces:
Externalizable, Serializable
public class KnobDistribution extends Distribution
A three-parameter distribution with infinite range, which allows interpolating between a normal distribution and a uniform distribution. The first two parameters control mu and sigma for the normal distribution, and also affect alpha and beta for the uniform one (though differently). The amount of interpolation is the third parameter, called iota here.
This provides an extra "knob" to slide between a flat uniform distribution and a central-biased normal one.
See Also:

  • Constructor Details

    • KnobDistribution

      public KnobDistribution()
      Uses an AceRandom, mu = 0.0, sigma = 1.0, iota = 0.5 .

    • KnobDistribution

      public KnobDistribution(double mu, double sigma, double iota)
      Uses an AceRandom and the given mu sigma, and iota.

    • KnobDistribution

      public KnobDistribution(EnhancedRandom generator, double mu, double sigma, double iota)
      Uses the given EnhancedRandom directly. Uses the given mu, sigma, and iota.

  • Method Details

    • getTag

      public String getTag()
      Description copied from class: Distribution
      Gets the tag used to identify this type of Distribution, as a String. This tag should be unique. Unlike the tags for EnhancedRandom types, the names here can vary in length.
      Specified by:
      getTag in class Distribution
      Returns:
      a unique String identifier for this type of Distribution; must be non-null, can be any non-zero length

    • copy

      public KnobDistribution copy()
      Description copied from class: Distribution
      Returns an exact copy of this Distribution, with the same parameters and a copy of the generator.
      Specified by:
      copy in class Distribution
      Returns:
      an exact copy of this Distribution

    • getMu

      public double getMu()

    • getSigma

      public double getSigma()

    • getIota

      public double getIota()

    • getParameterA

      public double getParameterA()
      Description copied from class: Distribution
      Gets the value of parameter "A" as a double. This corresponds to parameter "A" in Distribution.setParameters(double, double, double); it is usually called by some other name in the generator, and may not be stored as a double internally.
      This defaults to always returning Double.NaN, but any parameters a distribution actually uses should be overridden to return the actual parameter, which is almost certainly not going to be NaN. If a getParameter method returns NaN, you can generally safely assume that the parameter is not used by this distribution.
      Overrides:
      getParameterA in class Distribution
      Returns:
      the value of parameter "A" as a double.

    • getParameterB

      public double getParameterB()
      Description copied from class: Distribution
      Gets the value of parameter "B" as a double. This corresponds to parameter "B" in Distribution.setParameters(double, double, double); it is usually called by some other name in the generator, and may not be stored as a double internally.
      This defaults to always returning Double.NaN, but any parameters a distribution actually uses should be overridden to return the actual parameter, which is almost certainly not going to be NaN. If a getParameter method returns NaN, you can generally safely assume that the parameter is not used by this distribution.
      Overrides:
      getParameterB in class Distribution
      Returns:
      the value of parameter "B" as a double.

    • getParameterC

      public double getParameterC()
      Description copied from class: Distribution
      Gets the value of parameter "C" as a double. This corresponds to parameter "C" in Distribution.setParameters(double, double, double); it is usually called by some other name in the generator, and may not be stored as a double internally.
      This defaults to always returning Double.NaN, but any parameters a distribution actually uses should be overridden to return the actual parameter, which is almost certainly not going to be NaN. If a getParameter method returns NaN, you can generally safely assume that the parameter is not used by this distribution.
      Overrides:
      getParameterC in class Distribution
      Returns:
      the value of parameter "C" as a double.

    • getMaximum

      public double getMaximum()
      Description copied from class: Distribution
      Gets the maximum possible value of distributed random numbers.
      Specified by:
      getMaximum in class Distribution
      Returns:
      the maximum possible value of distributed random numbers

    • getMean

      public double getMean()
      Description copied from class: Distribution
      Gets the mean of distributed random numbers.
      Specified by:
      getMean in class Distribution
      Returns:
      the mean of distributed random numbers

    • getMedian

      public double getMedian()
      Description copied from class: Distribution
      Gets the median of distributed random numbers.
      Specified by:
      getMedian in class Distribution
      Returns:
      the median of distributed random numbers

    • getMinimum

      public double getMinimum()
      Description copied from class: Distribution
      Gets the minimum possible value of distributed random numbers.
      Specified by:
      getMinimum in class Distribution
      Returns:
      the minimum possible value of distributed random numbers

    • getMode

      public double[] getMode()
      Description copied from class: Distribution
      Gets the mode(s) of distributed random numbers.
      Specified by:
      getMode in class Distribution
      Returns:
      the mode(s) of distributed random numbers

    • getVariance

      public double getVariance()
      Description copied from class: Distribution
      Gets the variance of distributed random numbers.
      Specified by:
      getVariance in class Distribution
      Returns:
      the variance of distributed random numbers

    • setParameters

      public boolean setParameters(double a, double b, double c)
      Sets all parameters and returns true if they are valid, otherwise leaves parameters unchanged and returns false.
      Specified by:
      setParameters in class Distribution
      Parameters:
      a - mu; must not be NaN
      b - sigma; should be greater than 0.0
      c - iota; must be between 0.0 and 1.0, both inclusive
      Returns:
      true if the parameters given are valid and will be used

    • nextDouble

      public double nextDouble()
      Description copied from class: Distribution
      Generates a double using this distribution.
      Specified by:
      nextDouble in class Distribution
      Returns:
      a distributed double

    • sample

      public static double sample(EnhancedRandom generator, double mu, double sigma, double iota)