Struct rand_distr::Zipf

pub struct Zipf<F>
where
    F: Float,
    Standard: Distribution<F>,
{ /* private fields */ }

Samples integers according to the Zipf distribution.

The samples follow Zipf’s law: The frequency of each sample from a finite set of size n is inversely proportional to a power of its frequency rank (with exponent s).

For large n, this converges to the Zeta distribution.

For s = 0, this becomes a uniform distribution.

Example

use rand::prelude::*;
use rand_distr::Zipf;

let val: f64 = thread_rng().sample(Zipf::new(10, 1.5).unwrap());
println!("{}", val);

Implementation details

Implemented via rejection sampling, due to Jason Crease1.

Implementations

impl<F> Zipf<F>

where F: Float, Standard: Distribution<F>,

pub fn new(n: u64, s: F) -> Result<Zipf<F>, ZipfError>

Construct a new Zipf distribution for a set with n elements and a frequency rank exponent s.

For large n, rounding may occur to fit the number into the float type.

Trait Implementations

impl<F> Clone for Zipf<F>

where F: Float + Clone, Standard: Distribution<F>,

fn clone(&self) -> Zipf<F>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<F> Debug for Zipf<F>

where F: Float + Debug, Standard: Distribution<F>,

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

Formats the value using the given formatter.

impl<F> Distribution<F> for Zipf<F>

where F: Float, Standard: Distribution<F>,

fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> F

Generate a random value of T, using rng as the source of randomness.

fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T>

where R: Rng, Self: Sized,

Create an iterator that generates random values of T, using rng as the source of randomness.

fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S>

where F: Fn(T) -> S, Self: Sized,

Create a distribution of values of ‘S’ by mapping the output of Self through the closure F

impl<F> Copy for Zipf<F>

where F: Float + Copy, Standard: Distribution<F>,