Class DistributionHelpers

Defines functions that assist in dealing with RNG distributions.

Inheritance

System.Object

DistributionHelpers

Inherited Members

System.Object.Equals(System.Object)

System.Object.Equals(System.Object, System.Object)

System.Object.GetHashCode()

System.Object.GetType()

System.Object.MemberwiseClone()

System.Object.ReferenceEquals(System.Object, System.Object)

System.Object.ToString()

Namespace: GoRogue.Random

Assembly: GoRogue.dll

Syntax

public static class DistributionHelpers

Methods

CreateNormalDistribution(Double, Double, Double)

Creates a normal distribution based on a lower and upper value, and a distance to place those points from the mean. The mean is placed precisely in between the upper and lower values given, and the upper and lower values will both be exactly deviationsFromMean deviations away from the mean.

Declaration

public static NormalDistribution CreateNormalDistribution(double lower = -1, double upper = 1, double deviationsFromMean = 3.5)

Parameters

Type	Name	Description
System.Double	lower	Lower value by which to define the distribution.
System.Double	upper	Upper value by which to define the distribution.
System.Double	deviationsFromMean	Number of deviations from the mean at which to place the lower and upper values given.

Returns

Type	Description
Troschuetz.Random.Distributions.Continuous.NormalDistribution	A Troschuetz.Random.Distributions.Continuous.NormalDistribution constructed such that the mean is precisely in between the lower and upper values given, and the lower and upper values are exatly the specified number of deviations away from the mean.

CreateNormalDistribution(UInt32, Double, Double, Double)

Creates a normal distribution based on a lower and upper value, and a distance to place those points from the mean. The mean is placed precisely in between the upper and lower values given, and the upper and lower values will both be exactly deviationsFromMean deviations away from the mean.

Declaration

public static NormalDistribution CreateNormalDistribution(uint seed, double lower = -1, double upper = 1, double deviationsFromMean = 3.5)

Parameters

Type	Name	Description
System.UInt32	seed	The seed to pass the default Troschuetz.Random.Generators.XorShift128Generator that is created.
System.Double	lower	Lower value by which to define the distribution.
System.Double	upper	Upper value by which to define the distribution.
System.Double	deviationsFromMean	Number of deviations from the mean at which to place the lower and upper values given.

Returns

Type	Description
Troschuetz.Random.Distributions.Continuous.NormalDistribution	A Troschuetz.Random.Distributions.Continuous.NormalDistribution constructed such that the mean is precisely in between the lower and upper values given, and the lower and upper values are exatly the specified number of deviations away from the mean.

CreateNormalDistribution(IGenerator, Double, Double, Double)

Creates a normal distribution based on a lower and upper value, and a distance to place those points from the mean. The mean is placed precisely in between the upper and lower values given, and the upper and lower values will both be exactly deviationsFromMean deviations away from the mean.

Declaration

public static NormalDistribution CreateNormalDistribution(IGenerator generator = null, double lower = -1, double upper = 1, double deviationsFromMean = 3.5)

Parameters

Type	Name	Description
Troschuetz.Random.IGenerator	generator	Generator to use. If null is specified, the DefaultRNG will be used.
System.Double	lower	Lower value by which to define the distribution.
System.Double	upper	Upper value by which to define the distribution.
System.Double	deviationsFromMean	Number of deviations from the mean at which to place the lower and upper values given.

Returns

Type	Description
Troschuetz.Random.Distributions.Continuous.NormalDistribution	A Troschuetz.Random.Distributions.Continuous.NormalDistribution constructed such that the mean is precisely in between the lower and upper values given, and the lower and upper values are exatly the specified number of deviations away from the mean.