 | FastGaussianDistributionF Class |
Inheritance HierarchyDigitalRune.Mathematics.StatisticsDistributionSingle
DigitalRune.Mathematics.StatisticsFastGaussianDistributionF
Namespace: DigitalRune.Mathematics.Statistics
Assembly: DigitalRune.Mathematics (in DigitalRune.Mathematics.dll) Version: 1.14.0.0 (1.14.0.14427)
SyntaxThe FastGaussianDistributionF type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | FastGaussianDistributionF |
Initializes a new instance of the FastGaussianDistributionF class.
|
| FastGaussianDistributionF(Single, Single) |
Initializes a new instance of the FastGaussianDistributionF class.
|
Methods| Name | Description | |
|---|---|---|
| Equals | (Inherited from Object.) |
 | Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) |
| GetHashCode | Serves as a hash function for a particular type. (Inherited from Object.) |
| GetType | Gets the Type of the current instance. (Inherited from Object.) |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) |
| Next |
Gets a new random value for the underlying probability distribution.
(Overrides DistributionTNext(Random).) |
| ToString | Returns a string that represents the current object. (Inherited from Object.) |
Properties| Name | Description | |
|---|---|---|
 | ExpectedValue |
Gets or sets the expected value.
|
| NextValue | Obsolete.
Gets a new random value for the underlying probability distribution.
(Inherited from DistributionT.) |
| Random | Obsolete.
Gets or sets the random number generator.
(Inherited from DistributionT.) |
| StandardDeviation |
Gets or sets the standard deviation.
|
RemarksGaussian 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.
See Also