num-complex 0.3.1

Complex numbers implementation for Rust
Documentation 
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//! Rand implementations for complex numbers

use crate::Complex;
use num_traits::Num;
use rand::distributions::Standard;
use rand::prelude::*;

impl<T> Distribution<Complex<T>> for Standard
where
    T: Num + Clone,
    Standard: Distribution<T>,
{
    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Complex<T> {
        Complex::new(self.sample(rng), self.sample(rng))
    }
}

/// A generic random value distribution for complex numbers.
#[derive(Clone, Copy, Debug)]
pub struct ComplexDistribution<Re, Im = Re> {
    re: Re,
    im: Im,
}

impl<Re, Im> ComplexDistribution<Re, Im> {
    /// Creates a complex distribution from independent
    /// distributions of the real and imaginary parts.
    pub fn new(re: Re, im: Im) -> Self {
        ComplexDistribution { re, im }
    }
}

impl<T, Re, Im> Distribution<Complex<T>> for ComplexDistribution<Re, Im>
where
    T: Num + Clone,
    Re: Distribution<T>,
    Im: Distribution<T>,
{
    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Complex<T> {
        Complex::new(self.re.sample(rng), self.im.sample(rng))
    }
}

#[cfg(test)]
fn test_rng() -> StdRng {
    StdRng::from_seed([42; 32])
}

#[test]
fn standard_f64() {
    let mut rng = test_rng();
    for _ in 0..100 {
        let c: Complex<f64> = rng.gen();
        assert!(c.re >= 0.0 && c.re < 1.0);
        assert!(c.im >= 0.0 && c.im < 1.0);
    }
}

#[test]
fn generic_standard_f64() {
    let mut rng = test_rng();
    let dist = ComplexDistribution::new(Standard, Standard);
    for _ in 0..100 {
        let c: Complex<f64> = rng.sample(&dist);
        assert!(c.re >= 0.0 && c.re < 1.0);
        assert!(c.im >= 0.0 && c.im < 1.0);
    }
}

#[test]
fn generic_uniform_f64() {
    use rand::distributions::Uniform;

    let mut rng = test_rng();
    let re = Uniform::new(-100.0, 0.0);
    let im = Uniform::new(0.0, 100.0);
    let dist = ComplexDistribution::new(re, im);
    for _ in 0..100 {
        // no type annotation required, since `Uniform` only produces one type.
        let c = rng.sample(&dist);
        assert!(c.re >= -100.0 && c.re < 0.0);
        assert!(c.im >= 0.0 && c.im < 100.0);
    }
}

#[test]
fn generic_mixed_f64() {
    use rand::distributions::Uniform;

    let mut rng = test_rng();
    let re = Uniform::new(-100.0, 0.0);
    let dist = ComplexDistribution::new(re, Standard);
    for _ in 0..100 {
        // no type annotation required, since `Uniform` only produces one type.
        let c = rng.sample(&dist);
        assert!(c.re >= -100.0 && c.re < 0.0);
        assert!(c.im >= 0.0 && c.im < 1.0);
    }
}

#[test]
fn generic_uniform_i32() {
    use rand::distributions::Uniform;

    let mut rng = test_rng();
    let re = Uniform::new(-100, 0);
    let im = Uniform::new(0, 100);
    let dist = ComplexDistribution::new(re, im);
    for _ in 0..100 {
        // no type annotation required, since `Uniform` only produces one type.
        let c = rng.sample(&dist);
        assert!(c.re >= -100 && c.re < 0);
        assert!(c.im >= 0 && c.im < 100);
    }
}