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Diffstat (limited to 'rand/examples/monte-carlo.rs')
-rw-r--r-- | rand/examples/monte-carlo.rs | 51 |
1 files changed, 51 insertions, 0 deletions
diff --git a/rand/examples/monte-carlo.rs b/rand/examples/monte-carlo.rs new file mode 100644 index 0000000..9162996 --- /dev/null +++ b/rand/examples/monte-carlo.rs @@ -0,0 +1,51 @@ +// Copyright 2018 Developers of the Rand project. +// Copyright 2013-2018 The Rust Project Developers. +// +// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or +// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license +// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your +// option. This file may not be copied, modified, or distributed +// except according to those terms. + +//! # Monte Carlo estimation of π +//! +//! Imagine that we have a square with sides of length 2 and a unit circle +//! (radius = 1), both centered at the origin. The areas are: +//! +//! ```text +//! area of circle = πr² = π * r * r = π +//! area of square = 2² = 4 +//! ``` +//! +//! The circle is entirely within the square, so if we sample many points +//! randomly from the square, roughly π / 4 of them should be inside the circle. +//! +//! We can use the above fact to estimate the value of π: pick many points in +//! the square at random, calculate the fraction that fall within the circle, +//! and multiply this fraction by 4. + +#![cfg(feature="std")] + + +extern crate rand; + +use rand::distributions::{Distribution, Uniform}; + +fn main() { + let range = Uniform::new(-1.0f64, 1.0); + let mut rng = rand::thread_rng(); + + let total = 1_000_000; + let mut in_circle = 0; + + for _ in 0..total { + let a = range.sample(&mut rng); + let b = range.sample(&mut rng); + if a*a + b*b <= 1.0 { + in_circle += 1; + } + } + + // prints something close to 3.14159... + println!("π is approximately {}", 4. * (in_circle as f64) / (total as f64)); +} |