Enum DistType

pub enum DistType {
    Uniform {
        low: f64,
        high: f64,
    },
    Normal {
        mean: f64,
        stdev: f64,
    },
    SkewNormal {
        location: f64,
        scale: f64,
        shape: f64,
    },
    LogNormal {
        mu: f64,
        sigma: f64,
    },
    Binomial {
        trials: u64,
        probability: f64,
    },
    Geometric {
        probability: f64,
    },
    Pareto {
        scale: f64,
        shape: f64,
    },
    Poisson {
        lambda: f64,
    },
    Weibull {
        scale: f64,
        shape: f64,
    },
    Gamma {
        scale: f64,
        shape: f64,
    },
    Beta {
        alpha: f64,
        beta: f64,
    },
}

DistType represents the type of a Dist. Supports a wide range of different distributions. Some are probably useless and some are probably missing. Uses the rand_distr crate for sampling.

Variants

Uniform

Uniformly random [low, high). If low == high, constant.

Fields

low: f64

The lower bound of the distribution.

high: f64

The upper bound of the distribution.

Normal

Normal distribution with set mean and standard deviation. Useful for real-valued quantities.

Fields

mean: f64

The mean of the distribution.

stdev: f64

The standard deviation of the distribution.

SkewNormal

SkewNormal distribution with set location, scale, and shape. Useful for real-valued quantities.

Fields

location: f64

The location of the distribution.

scale: f64

The scale of the distribution.

shape: f64

The shape of the distribution.

LogNormal

LogNormal distribution with set mu and sigma. Useful for real-valued quantities.

Fields

mu: f64

The mu of the distribution.

sigma: f64

The sigma of the distribution.

Binomial

Binomial distribution with set trials and probability. Useful for yes/no events.

Fields

trials: u64

The number of trials.

probability: f64

The probability of success.

Geometric

Geometric distribution with set probability. Useful for yes/no events.

Fields

probability: f64

The probability of success.

Pareto

Pareto distribution with set scale and shape. Useful for occurrence of independent events at a given rate.

Fields

scale: f64

The scale of the distribution.

shape: f64

The shape of the distribution.

Poisson

Poisson distribution with set lambda. Useful for occurrence of independent events at a given rate.

Fields

lambda: f64

The lambda of the distribution.

Weibull

Weibull distribution with set scale and shape. Useful for occurrence of independent events at a given rate.

Fields

scale: f64

The scale of the distribution.

shape: f64

The shape of the distribution.

Gamma

Gamma distribution with set scale and shape.

Fields

scale: f64

The scale of the distribution.

shape: f64

The shape of the distribution.

Beta

Beta distribution with set alpha and beta.

Fields

alpha: f64

The alpha of the distribution.

beta: f64

The beta of the distribution.

Trait Implementations

impl Clone for DistType

fn clone(&self) -> DistType

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for DistType

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for DistType

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for DistType

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for DistType

fn eq(&self, other: &DistType) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for DistType

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Copy for DistType

impl StructuralPartialEq for DistType