Module io.jenetics.base
Package io.jenetics.stat

Class Samplers

java.lang.Object
io.jenetics.stat.Samplers
public final class Samplers extends Object
This class defines some default samplers.
Since:
8.0
Version:
8.3

  • Method Summary

    Modifier and Type
    Method
    Description
    static Sampler
    gaussian(double mean, double stddev)
    Return a Gaussian sampler with the given parameter.
    static Sampler
    gaussian(double mean, double stddev, int maxRetries)
    Return a Gaussian sampler with the given parameter.
    static Sampler
    linear(double mean)
    Return a new sampler for a linear distribution with the given mean value, when creating sample points for the normalized range [0, 1).
    static Sampler
    triangular(double c)
    Return a new sampler for a normalized triangle distribution with the points [0, c, 1].
    static Sampler
    triangular(double a, double c, double b)
    Create a new sampler for a triangle distribution with the given parameters.

    Methods inherited from class java.lang.Object

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

  • Method Details

    • linear

      public static Sampler linear(double mean)
      Return a new sampler for a linear distribution with the given mean value, when creating sample points for the normalized range [0, 1).

      Linear distribution sampler

      Parameters:
      mean - the mean value of the sampler distribution
      Returns:
      a new linear sampler with the given mean value
      Throws:
      IllegalArgumentException - if the given mean value is not within the range [0, 1)

    • triangular

      public static Sampler triangular(double a, double c, double b)
      Create a new sampler for a triangle distribution with the given parameters. All parameters must be within the normalized range [0, 1]. The sample value, returned by the Sampler.sample(RandomGenerator, DoubleRange) method, is then stretched to the desired range.

      Triangle distribution sampler

      Parameters:
      a - the normalized start point of the triangle
      c - the normalized middle point of the triangle
      b - the normalized end point of the triangle
      Returns:
      a new triangle distribution sampler
      Throws:
      IllegalArgumentException - if one of the parameters is not within the range [0, 1] or b <= a || c > b || c < a
      See Also:

    • triangular

      public static Sampler triangular(double c)
      Return a new sampler for a normalized triangle distribution with the points [0, c, 1].
      Parameters:
      c - the middle point of the triangle within the range [0, 1]
      Returns:
      a new triangle distribution sampler
      Throws:
      IllegalArgumentException - if c not within [0, 1]
      See Also:

    • gaussian

      public static Sampler gaussian(double mean, double stddev, int maxRetries)
      Return a Gaussian sampler with the given parameter. The sampler returns Double.NaN if it is not possible to create a normal distributed value within the desired range.
      Parameters:
      mean - the mean value of the Gaussian sampler
      stddev - the standard deviation of the Gaussian sampler
      maxRetries - the maximal number of retries, if a generated value is not in the desired range.
      Returns:
      a Gaussian sampler
      Throws:
      IllegalArgumentException - if maxRetries is smaller than one
      Since:
      8.3

    • gaussian

      public static Sampler gaussian(double mean, double stddev)
      Return a Gaussian sampler with the given parameter. The sampler returns Double.NaN if it is not possible to create a normal distributed value within the desired range after 25 tries.
      Parameters:
      mean - the mean value of the Gaussian sampler
      stddev - the standard deviation of the Gaussian sampler
      Returns:
      a Gaussian sampler
      Throws:
      IllegalArgumentException - if maxRetries is smaller than one
      Since:
      8.3