blob: 8fb3a832f2298d78c67fac745ab2292e0814f752 [file] [log] [blame]
// Copyright 2018 Developers of the Rand project.
//
// 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.
#![feature(test)]
extern crate test;
extern crate rand;
const RAND_BENCH_N: u64 = 1000;
use test::Bencher;
use rand::prelude::*;
#[bench]
fn misc_gen_bool_const(b: &mut Bencher) {
let mut rng = StdRng::from_rng(&mut thread_rng()).unwrap();
b.iter(|| {
let mut accum = true;
for _ in 0..::RAND_BENCH_N {
accum ^= rng.gen_bool(0.18);
}
accum
})
}
#[bench]
fn misc_gen_bool_var(b: &mut Bencher) {
let mut rng = StdRng::from_rng(&mut thread_rng()).unwrap();
b.iter(|| {
let mut accum = true;
let mut p = 0.18;
for _ in 0..::RAND_BENCH_N {
accum ^= rng.gen_bool(p);
p += 0.0001;
}
accum
})
}
#[bench]
fn misc_gen_ratio_const(b: &mut Bencher) {
let mut rng = StdRng::from_rng(&mut thread_rng()).unwrap();
b.iter(|| {
let mut accum = true;
for _ in 0..::RAND_BENCH_N {
accum ^= rng.gen_ratio(2, 3);
}
accum
})
}
#[bench]
fn misc_gen_ratio_var(b: &mut Bencher) {
let mut rng = StdRng::from_rng(&mut thread_rng()).unwrap();
b.iter(|| {
let mut accum = true;
for i in 2..(::RAND_BENCH_N as u32 + 2) {
accum ^= rng.gen_ratio(i, i + 1);
}
accum
})
}
#[bench]
fn misc_bernoulli_const(b: &mut Bencher) {
let mut rng = StdRng::from_rng(&mut thread_rng()).unwrap();
b.iter(|| {
let d = rand::distributions::Bernoulli::new(0.18);
let mut accum = true;
for _ in 0..::RAND_BENCH_N {
accum ^= rng.sample(d);
}
accum
})
}
#[bench]
fn misc_bernoulli_var(b: &mut Bencher) {
let mut rng = StdRng::from_rng(&mut thread_rng()).unwrap();
b.iter(|| {
let mut accum = true;
let mut p = 0.18;
for _ in 0..::RAND_BENCH_N {
let d = rand::distributions::Bernoulli::new(p);
accum ^= rng.sample(d);
p += 0.0001;
}
accum
})
}
macro_rules! sample_binomial {
($name:ident, $n:expr, $p:expr) => {
#[bench]
fn $name(b: &mut Bencher) {
let mut rng = SmallRng::from_rng(&mut thread_rng()).unwrap();
let (n, p) = ($n, $p);
b.iter(|| {
let d = rand::distributions::Binomial::new(n, p);
rng.sample(d)
})
}
}
}
sample_binomial!(misc_binomial_1, 1, 0.9);
sample_binomial!(misc_binomial_10, 10, 0.9);
sample_binomial!(misc_binomial_100, 100, 0.99);
sample_binomial!(misc_binomial_1000, 1000, 0.01);
sample_binomial!(misc_binomial_1e12, 1000_000_000_000, 0.2);
#[bench]
fn gen_1k_iter_repeat(b: &mut Bencher) {
use std::iter;
let mut rng = SmallRng::from_rng(&mut thread_rng()).unwrap();
b.iter(|| {
let v: Vec<u64> = iter::repeat(()).map(|()| rng.gen()).take(128).collect();
v
});
b.bytes = 1024;
}
#[bench]
fn gen_1k_sample_iter(b: &mut Bencher) {
use rand::distributions::{Distribution, Standard};
let mut rng = SmallRng::from_rng(&mut thread_rng()).unwrap();
b.iter(|| {
let v: Vec<u64> = Standard.sample_iter(&mut rng).take(128).collect();
v
});
b.bytes = 1024;
}
#[bench]
fn gen_1k_gen_array(b: &mut Bencher) {
let mut rng = SmallRng::from_rng(&mut thread_rng()).unwrap();
b.iter(|| {
// max supported array length is 32!
let v: [[u64; 32]; 4] = rng.gen();
v
});
b.bytes = 1024;
}
#[bench]
fn gen_1k_fill(b: &mut Bencher) {
let mut rng = SmallRng::from_rng(&mut thread_rng()).unwrap();
let mut buf = [0u64; 128];
b.iter(|| {
rng.fill(&mut buf[..]);
buf
});
b.bytes = 1024;
}