Struct std::random::Normal

Normal (Gaussian) distribution over the real numbers.

This distribution is parameterized by a mean and a standard deviation. The mean is the center of the distribution, and the standard deviation controls the spread.

Example

use std::random::{thread_rng, Normal};

let dist: Normal<f64> = Normal::new(2.0, 3.0);
// Prints a random number from a normal distribution with mean 2 and
// standard deviation 3
println!("{}", dist.sample(thread_rng()));
Run this example

Methods

• fn new(mean: F, std_dev: F) -> Normal<F>

  source

  Create a normal distribution with a given mean and standard deviation.

• fn standard() -> Normal<F>

  source

  Create a standard normal distribution

  Standard normal distribution has a mean of 0 and standard deviation of 1.

• fn sample<R>(self: &Normal<F>, rng: &mut R) -> F

  R: Rng<R>

  source

  Samples a distribution using a provided random number generator.

Mixins

• mixin<R> Distribution<Normal<F>, F, R>

  R: Rng<R>

• fn sample_iter(self: &Self, rng: &mut R) -> DistIterator<Self, T, R>

  source

  Raturns an iterator producing an infinite stream of values sampled from the distribution.

  Example

  use std::random::{thread_rng, UniformInteger};
  
  let dist = UniformInteger::new(0..=5);
  
  // Prints 10 random numbers between 0 and 5 inclusive
  for i in dist.sample_iter(thread_rng()).take(10) {
      println!("{}", i);
  }
  Run this example