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doc: More efficient Monty Hall simulation

This commit is contained in:
Jonas Hietala 2014-07-28 15:04:21 +02:00
parent bf1ba83292
commit 42ca8a70d6

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@ -95,12 +95,11 @@ use std::rand::distributions::{IndependentSample, Range};
struct SimulationResult {
win: bool,
switch: bool
switch: bool,
}
// Run a single simulation of the Monty Hall problem.
fn simulate<R: Rng>(rng: &mut R) -> SimulationResult {
let random_door = Range::new(0u, 3);
fn simulate<R: Rng>(random_door: &Range<uint>, rng: &mut R) -> SimulationResult {
let car = random_door.ind_sample(rng);
// This is our initial choice
@ -121,32 +120,33 @@ fn simulate<R: Rng>(rng: &mut R) -> SimulationResult {
// Returns the door the game host opens given our choice and knowledge of
// where the car is. The game host will never open the door with the car.
fn game_host_open<R: Rng>(car: uint, choice: uint, rng: &mut R) -> uint {
let choices = free_doors(vec![car, choice]);
let choices = free_doors(&[car, choice]);
rand::sample(rng, choices.move_iter(), 1)[0]
}
// Returns the door we switch to, given our current choice and
// the open door. There will only be one valid door.
fn switch_door(choice: uint, open: uint) -> uint {
free_doors(vec![choice, open])[0]
free_doors(&[choice, open])[0]
}
fn free_doors(blocked: Vec<uint>) -> Vec<uint> {
fn free_doors(blocked: &[uint]) -> Vec<uint> {
range(0u, 3).filter(|x| !blocked.contains(x)).collect()
}
fn main() {
// The estimation will be more accuraty with more simulations
// The estimation will be more accurate with more simulations
let num_simulations = 10000u;
let mut rng = rand::task_rng();
let random_door = Range::new(0u, 3);
let (mut switch_wins, mut switch_losses) = (0u, 0u);
let (mut keep_wins, mut keep_losses) = (0u, 0u);
println!("Running {} simulations...", num_simulations);
for _ in range(0, num_simulations) {
let result = simulate(&mut rng);
let result = simulate(&random_door, &mut rng);
match (result.win, result.switch) {
(true, true) => switch_wins += 1,