andreacavalli/rust-average
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Update benchmarks

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This commit is contained in:
Vinzent Steinberg 2019-05-22 14:45:04 +02:00
parent 3f82a320f9
commit 5b8ace3fb4
4 changed files with 18 additions and 11 deletions
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1
Cargo.toml
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@ -40,6 +40,7 @@ version = "0.3"
[dev-dependencies] [dev-dependencies]
bencher = "0.1" bencher = "0.1"
rand = "0.6" rand = "0.6"
rand_xoshiro = "0.1"
serde_json = "1" serde_json = "1"
streaming-stats = "0.2" streaming-stats = "0.2"
quantiles = "0.7" quantiles = "0.7"

8
benches/kurtosis.rs
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@ -2,6 +2,7 @@
#[macro_use] extern crate bencher; #[macro_use] extern crate bencher;
extern crate rand; extern crate rand;
extern crate rand_xoshiro;
extern crate average; extern crate average;
@ -10,12 +11,13 @@ use bencher::Bencher;
/// Create a random vector by sampling from a normal distribution. /// Create a random vector by sampling from a normal distribution.
fn initialize_vec() -> Vec<f64> { fn initialize_vec() -> Vec<f64> {
use rand::distributions::{Normal, Distribution}; use rand::distributions::{Normal, Distribution};
use rand::{XorShiftRng, SeedableRng}; use rand::SeedableRng;
let normal = Normal::new(2.0, 3.0); let normal = Normal::new(2.0, 3.0);
let n = 1_000_000; let n = 1_000_000;
let mut values = Vec::with_capacity(n); let mut values = Vec::with_capacity(n);
let mut rng = XorShiftRng::from_seed( let mut rng = rand_xoshiro::Xoshiro256StarStar::from_seed(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]); [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]);
for _ in 0..n { for _ in 0..n {
values.push(normal.sample(&mut rng)); values.push(normal.sample(&mut rng));
} }

8
benches/mean.rs
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@ -2,6 +2,7 @@
#[macro_use] extern crate bencher; #[macro_use] extern crate bencher;
extern crate rand; extern crate rand;
extern crate rand_xoshiro;
extern crate average; extern crate average;
extern crate stats; extern crate stats;
@ -11,12 +12,13 @@ use bencher::Bencher;
/// Create a random vector by sampling from a normal distribution. /// Create a random vector by sampling from a normal distribution.
fn initialize_vec() -> Vec<f64> { fn initialize_vec() -> Vec<f64> {
use rand::distributions::{Normal, Distribution}; use rand::distributions::{Normal, Distribution};
use rand::{XorShiftRng, SeedableRng}; use rand::SeedableRng;
let normal = Normal::new(2.0, 3.0); let normal = Normal::new(2.0, 3.0);
let n = 1_000_000; let n = 1_000_000;
let mut values = Vec::with_capacity(n); let mut values = Vec::with_capacity(n);
let mut rng = XorShiftRng::from_seed( let mut rng = rand_xoshiro::Xoshiro256StarStar::from_seed(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]); [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]);
for _ in 0..n { for _ in 0..n {
values.push(normal.sample(&mut rng)); values.push(normal.sample(&mut rng));
} }

12
benches/min.rs
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@ -2,6 +2,7 @@
#[macro_use] extern crate bencher; #[macro_use] extern crate bencher;
extern crate rand; extern crate rand;
extern crate rand_xoshiro;
extern crate average; extern crate average;
extern crate stats; extern crate stats;
@ -10,13 +11,14 @@ use bencher::Bencher;
/// Create a random vector of random floats in [0, 1]. /// Create a random vector of random floats in [0, 1].
fn initialize_vec() -> Vec<f64> { fn initialize_vec() -> Vec<f64> {
use rand::distributions::{Range, Distribution}; use rand::distributions::{Uniform, Distribution};
use rand::{XorShiftRng, SeedableRng}; use rand::SeedableRng;
let range = Range::new(0.0, 1.0); let range = Uniform::new(0.0, 1.0);
let n = 1_000_000; let n = 1_000_000;
let mut values = Vec::with_capacity(n); let mut values = Vec::with_capacity(n);
let mut rng = XorShiftRng::from_seed( let mut rng = rand_xoshiro::Xoshiro256StarStar::from_seed(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]); [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]);
for _ in 0..n { for _ in 0..n {
values.push(range.sample(&mut rng)); values.push(range.sample(&mut rng));
} }