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Diffstat (limited to 'rand/examples/monte-carlo.rs')
-rw-r--r-- | rand/examples/monte-carlo.rs | 48 |
1 files changed, 0 insertions, 48 deletions
diff --git a/rand/examples/monte-carlo.rs b/rand/examples/monte-carlo.rs deleted file mode 100644 index 39c779f..0000000 --- a/rand/examples/monte-carlo.rs +++ /dev/null @@ -1,48 +0,0 @@ -// 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")] - -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)); -} |