Class FastGaussianDistributionF

Creates random values using an approximate Gaussian distribution (single-precision).

Inheritance

System.Object

Distribution<System.Single>

FastGaussianDistributionF

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: Mars.Numerics.Statistics

Assembly: Mars.Numerics.dll

Syntax

public class FastGaussianDistributionF : Distribution<float>

Remarks

Gaussian distribution is also known as Normal distribution.

The random values generated by this class follow only an approximate Gaussian distribution. The distribution curve can be imagined as a typical Gaussian bell curve within +/- 3 standard deviations. All random values lie in the interval [ExpectedValue - 3 * StandardDeviation, ExpectedValue + 3 * StandardDeviation]. No random values outside the +/- 3 standard deviation interval are returned.

This approximation is faster and makes the random values more controllable for game applications. For example, if in a game tree heights are determined using a real Gaussian distribution with an expected value of 10m and a standard deviation of 1m, then most trees will have a height near 10m. But it would also be possible - unlikely but possible - that a tree with height 30m is generated. This would look very odd. Therefore, it is desirable that the created random values do not exceed 3 standard deviations.

Constructors

FastGaussianDistributionF()

Initializes a new instance of the FastGaussianDistributionF class.

Declaration

public FastGaussianDistributionF()

Remarks

Gaussian distribution is also known as Normal distribution.

The random values generated by this class follow only an approximate Gaussian distribution. The distribution curve can be imagined as a typical Gaussian bell curve within +/- 3 standard deviations. All random values lie in the interval [ExpectedValue - 3 * StandardDeviation, ExpectedValue + 3 * StandardDeviation]. No random values outside the +/- 3 standard deviation interval are returned.

This approximation is faster and makes the random values more controllable for game applications. For example, if in a game tree heights are determined using a real Gaussian distribution with an expected value of 10m and a standard deviation of 1m, then most trees will have a height near 10m. But it would also be possible - unlikely but possible - that a tree with height 30m is generated. This would look very odd. Therefore, it is desirable that the created random values do not exceed 3 standard deviations.

FastGaussianDistributionF(Single, Single)

Initializes a new instance of the FastGaussianDistributionF class.

Declaration

public FastGaussianDistributionF(float expectedValue, float standardDeviation)

Parameters

Type	Name	Description
System.Single	expectedValue	The expected value.
System.Single	standardDeviation	The standard deviation.

Remarks

Gaussian distribution is also known as Normal distribution.

The random values generated by this class follow only an approximate Gaussian distribution. The distribution curve can be imagined as a typical Gaussian bell curve within +/- 3 standard deviations. All random values lie in the interval [ExpectedValue - 3 * StandardDeviation, ExpectedValue + 3 * StandardDeviation]. No random values outside the +/- 3 standard deviation interval are returned.

This approximation is faster and makes the random values more controllable for game applications. For example, if in a game tree heights are determined using a real Gaussian distribution with an expected value of 10m and a standard deviation of 1m, then most trees will have a height near 10m. But it would also be possible - unlikely but possible - that a tree with height 30m is generated. This would look very odd. Therefore, it is desirable that the created random values do not exceed 3 standard deviations.

Properties

ExpectedValue

Gets or sets the expected value.

Declaration

public float ExpectedValue { get; set; }

Property Value

Type	Description
System.Single	The expected value. The default is 0.

Remarks

Gaussian distribution is also known as Normal distribution.

The random values generated by this class follow only an approximate Gaussian distribution. The distribution curve can be imagined as a typical Gaussian bell curve within +/- 3 standard deviations. All random values lie in the interval [ExpectedValue - 3 * StandardDeviation, ExpectedValue + 3 * StandardDeviation]. No random values outside the +/- 3 standard deviation interval are returned.

This approximation is faster and makes the random values more controllable for game applications. For example, if in a game tree heights are determined using a real Gaussian distribution with an expected value of 10m and a standard deviation of 1m, then most trees will have a height near 10m. But it would also be possible - unlikely but possible - that a tree with height 30m is generated. This would look very odd. Therefore, it is desirable that the created random values do not exceed 3 standard deviations.

StandardDeviation

Gets or sets the standard deviation.

Declaration

public float StandardDeviation { get; set; }

Property Value

Type	Description
System.Single	The standard deviation. The default is 1.

Remarks

Gaussian distribution is also known as Normal distribution.

The random values generated by this class follow only an approximate Gaussian distribution. The distribution curve can be imagined as a typical Gaussian bell curve within +/- 3 standard deviations. All random values lie in the interval [ExpectedValue - 3 * StandardDeviation, ExpectedValue + 3 * StandardDeviation]. No random values outside the +/- 3 standard deviation interval are returned.

This approximation is faster and makes the random values more controllable for game applications. For example, if in a game tree heights are determined using a real Gaussian distribution with an expected value of 10m and a standard deviation of 1m, then most trees will have a height near 10m. But it would also be possible - unlikely but possible - that a tree with height 30m is generated. This would look very odd. Therefore, it is desirable that the created random values do not exceed 3 standard deviations.

Methods

Next(FastRandom)

Creates random values using an approximate Gaussian distribution (single-precision).

Declaration

public override float Next(FastRandom random)

Parameters

Type	Name	Description
Mars.Common.Core.Random.FastRandom	random

Returns

Type	Description
System.Single

Overrides

Mars.Numerics.Statistics.Distribution<System.Single>.Next(Mars.Common.Core.Random.FastRandom)

Remarks

Gaussian distribution is also known as Normal distribution.

The random values generated by this class follow only an approximate Gaussian distribution. The distribution curve can be imagined as a typical Gaussian bell curve within +/- 3 standard deviations. All random values lie in the interval [ExpectedValue - 3 * StandardDeviation, ExpectedValue + 3 * StandardDeviation]. No random values outside the +/- 3 standard deviation interval are returned.

This approximation is faster and makes the random values more controllable for game applications. For example, if in a game tree heights are determined using a real Gaussian distribution with an expected value of 10m and a standard deviation of 1m, then most trees will have a height near 10m. But it would also be possible - unlikely but possible - that a tree with height 30m is generated. This would look very odd. Therefore, it is desirable that the created random values do not exceed 3 standard deviations.

Extension Methods

Serializer.Save<T>(T, out Byte[], SerializerCompression)

Serializer.Save<T>(T, Stream, SerializerCompression)

Serializer.Save<T>(T, BinaryFormatter, Stream, SerializerCompression)

Serializer.Save<T>(T, String, SerializerCompression)

Serializer.Save<T>(T, String)

Matrix.Concatenate<T>(T, T[])

Matrix.Replace<T>(T, Object, Object)

DomainDataImporter.Import(Object, InputConfiguration)

ObjectSerialize.Serialize(Object)

Matrix.IsEqual(Object, Object, Decimal, Decimal)