Struct BinomialSampler 

pub struct BinomialSampler {
    pub distr: Binomial,
    pub rng: SamplerRng,
}

Enables sampling a Z according to the binomial distribution Bin(n, p).

Attributes:

• distr: defines the binomial distribution with parameters n and p to sample from
• rng: defines the ThreadRng or seeded StdRng that’s used to sample from distr

Examples

use qfall_math::utils::sample::binomial::BinomialSampler;
let n = 2;
let p = 0.5;

let mut bin_sampler = BinomialSampler::init(n, p, None).unwrap();

let sample = bin_sampler.sample();

assert!(0 <= sample);
assert!(sample <= n);

Fields

distr: Binomial

rng: SamplerRng

Implementations

impl BinomialSampler

pub fn init( n: impl Into<Z>, p: impl Into<Q>, seed: Option<[u8; 32]>, ) -> Result<Self, MathError>

Initializes the BinomialSampler with

• distr as the binomial distribution with n tries and success probability p for each try, and
• rng as a StdRng seeded with seed if seed is provided, and as a fresh ThreadRng otherwise.

Parameters:

• n: specifies the number of tries
• p: specifies the success probability
• seed: specifies an optional 256-bit seed for the internal StdRng. If None is provided, a fresh ThreadRng is used instead.

Returns a BinomialSampler or a MathError if n < 0, p ∉ (0,1), or n does not fit into an i64.

Examples

use qfall_math::utils::sample::binomial::BinomialSampler;
let n = 2;
let p = 0.5;

let bin_sampler = BinomialSampler::init(n, p, None).unwrap();

let mut bin_sampler_seeded_0 = BinomialSampler::init(n, p, Some([42; 32])).unwrap();
let mut bin_sampler_seeded_1 = BinomialSampler::init(n, p, Some([42; 32])).unwrap();
assert_eq!(bin_sampler_seeded_0.sample(), bin_sampler_seeded_1.sample());

Errors and Failures

• Returns a MathError of type InvalidIntegerInput if n < 0.
• Returns a MathError of type InvalidInterval if p ∉ (0,1).
• Returns a MathError of type ConversionError if n does not fit into an i64.

pub fn sample(&mut self) -> Z

Samples a Z according to the binomial distribution Bin(n, p).

Examples

use qfall_math::utils::sample::binomial::BinomialSampler;
let n = 2;
let p = 0.5;

let mut bin_sampler = BinomialSampler::init(n, p, None).unwrap();

let sample = bin_sampler.sample();

assert!(0 <= sample);
assert!(sample <= n);