Struct rv::dist::VonMises

pub struct VonMises { /* fields omitted */ }

VonMises distirbution on the circular interval (0, 2π]

Example

use rv::prelude::*;

let vm = VonMises::new(1.0, 2.0).unwrap();

// x is in (0, 2π]
assert!(!vm.supports(&-0.001_f64));
assert!(!vm.supports(&6.3_f64));

// 103 VonMises draws
let mut rng = rand::thread_rng();
let xs: Vec<f64> = vm.sample(103, &mut rng);
assert_eq!(xs.len(), 103);

Implementations

impl VonMises

pub fn new(mu: f64, k: f64) -> Result<Self, VonMisesError>

Create a new VonMises distribution with mean mu, and precision, k.

pub fn new_unchecked(mu: f64, k: f64) -> Self

Creates a new VonMises without checking whether the parameters are valid.

pub fn mu(&self) -> f64

Get the mean parameter, mu

Example

let vm = VonMises::new(0.0, 1.0).unwrap();
assert_eq!(vm.mu(), 0.0);

pub fn set_mu(&mut self, mu: f64) -> Result<(), VonMisesError>

Set the value of mu

Example

use rv::dist::VonMises;
let mut vm = VonMises::new(2.0, 1.5).unwrap();
assert_eq!(vm.mu(), 2.0);

vm.set_mu(1.3).unwrap();
assert_eq!(vm.mu(), 1.3);

Will error for invalid values

assert!(vm.set_mu(1.3).is_ok());
assert!(vm.set_mu(0.0).is_ok());
assert!(vm.set_mu(2.0 * std::f64::consts::PI).is_ok());

assert!(vm.set_mu(0.0 - 0.001).is_err());
assert!(vm.set_mu(2.0 * std::f64::consts::PI + 0.001).is_err());

assert!(vm.set_mu(std::f64::NEG_INFINITY).is_err());
assert!(vm.set_mu(std::f64::INFINITY).is_err());
assert!(vm.set_mu(std::f64::NAN).is_err());

pub fn set_mu_unchecked(&mut self, mu: f64)

Set the value of mu without input validation

pub fn k(&self) -> f64

Get the precision parameter, k

Example

let vm = VonMises::new(0.0, 1.0).unwrap();
assert_eq!(vm.k(), 1.0);

pub fn set_k(&mut self, k: f64) -> Result<(), VonMisesError>

Set the value of k

Example

let mut vm = VonMises::new(0.0, 1.0).unwrap();
let v1: f64 = vm.variance().unwrap();
assert::close(v1, 0.5536100341034653, 1E-10);

vm.set_mu(0.2);
vm.set_k(2.0);

let v2: f64 = vm.variance().unwrap();
assert::close(v2, 0.3022253420359917, 1E-10);

Will error for invalid values

assert!(vm.set_k(0.1).is_ok());

// Must be greater than zero
assert!(vm.set_k(0.0).is_err());
assert!(vm.set_k(-1.0).is_err());

assert!(vm.set_k(std::f64::INFINITY).is_err());
assert!(vm.set_k(std::f64::NEG_INFINITY).is_err());
assert!(vm.set_k(std::f64::NAN).is_err());

pub fn set_k_unchecked(&mut self, k: f64)

Set the value of k without input validation

Trait Implementations

impl Cdf<f32> for VonMises

fn cdf(&self, x: &f32) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Cdf<f64> for VonMises

fn cdf(&self, x: &f64) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Clone for VonMises

fn clone(&self) -> VonMises

Returns a copy of the value.

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

Performs copy-assignment from source.

impl ContinuousDistr<f32> for VonMises

fn pdf(&self, x: &X) -> f64

The value of the Probability Density Function (PDF) at x

fn ln_pdf(&self, x: &X) -> f64

The value of the log Probability Density Function (PDF) at x

impl ContinuousDistr<f64> for VonMises

fn pdf(&self, x: &X) -> f64

The value of the Probability Density Function (PDF) at x

fn ln_pdf(&self, x: &X) -> f64

The value of the log Probability Density Function (PDF) at x

impl Debug for VonMises

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

Formats the value using the given formatter.

impl Default for VonMises

fn default() -> Self

Returns the “default value” for a type.

impl Display for VonMises

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

Formats the value using the given formatter.

impl Entropy for VonMises

fn entropy(&self) -> f64

The entropy, H(X)

impl Mean<f32> for VonMises

fn mean(&self) -> Option<f32>

Returns None if the mean is undefined

impl Mean<f64> for VonMises

fn mean(&self) -> Option<f64>

Returns None if the mean is undefined

impl Median<f32> for VonMises

fn median(&self) -> Option<f32>

Returns None if the median is undefined

impl Median<f64> for VonMises

fn median(&self) -> Option<f64>

Returns None if the median is undefined

impl Mode<f32> for VonMises

fn mode(&self) -> Option<f32>

Returns None if the mode is undefined or is not a single value

impl Mode<f64> for VonMises

fn mode(&self) -> Option<f64>

Returns None if the mode is undefined or is not a single value

impl PartialEq<VonMises> for VonMises

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

This method tests for self and other values to be equal, and is used by ==.

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

This method tests for !=.

impl Rv<f32> for VonMises

fn ln_f(&self, x: &f32) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> f32

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

fn sample_stream<'r, R: Rng>(
    &'r self,
    rng: &'r mut R
) -> Box<dyn Iterator<Item = X> + 'r>

Create a never-ending iterator of samples

impl Rv<f64> for VonMises

fn ln_f(&self, x: &f64) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> f64

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

fn sample_stream<'r, R: Rng>(
    &'r self,
    rng: &'r mut R
) -> Box<dyn Iterator<Item = X> + 'r>

Create a never-ending iterator of samples

impl StructuralPartialEq for VonMises

impl Support<f32> for VonMises

fn supports(&self, x: &f32) -> bool

Returns true if x is in the support of the Rv

impl Support<f64> for VonMises

fn supports(&self, x: &f64) -> bool

Returns true if x is in the support of the Rv

impl Variance<f32> for VonMises

fn variance(&self) -> Option<f32>

Returns None if the variance is undefined

impl Variance<f64> for VonMises

fn variance(&self) -> Option<f64>

Returns None if the variance is undefined