Class FastGaussianDistributionD

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

Inheritance

System.Object

Distribution<System.Double>

FastGaussianDistributionD

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 FastGaussianDistributionD : Distribution<double>

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

FastGaussianDistributionD()

Initializes a new instance of the FastGaussianDistributionD class.

Declaration

public FastGaussianDistributionD()

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.

FastGaussianDistributionD(Double, Double)

Initializes a new instance of the FastGaussianDistributionF class.

Declaration

public FastGaussianDistributionD(double expectedValue, double standardDeviation)

Parameters

Type	Name	Description
System.Double	expectedValue	The expected value.
System.Double	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 double ExpectedValue { get; set; }

Property Value

Type	Description
System.Double	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 double StandardDeviation { get; set; }

Property Value

Type	Description
System.Double	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, Double, Double)

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

Declaration

public double Next(FastRandom random, double expectedValue, double standardDeviation)

Parameters

Type	Name	Description
Mars.Common.Core.Random.FastRandom	random
System.Double	expectedValue
System.Double	standardDeviation

Returns

Type	Description
System.Double

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.

Next(FastRandom)

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

Declaration

public override double Next(FastRandom random)

Parameters

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

Returns

Type	Description
System.Double

Overrides

Mars.Numerics.Statistics.Distribution<System.Double>.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)