Benchmark generic vs. handwritten implementation of kurtosis

Also restore no_std and remove printing left over from debugging.
This commit is contained in:
Vinzent Steinberg 2018-01-11 19:37:25 +01:00
parent 785e2141e0
commit a6a477d621
4 changed files with 46 additions and 3 deletions

View File

@ -18,6 +18,10 @@ name = "mean"
harness = false harness = false
name = "min" name = "min"
[[bench]]
harness = false
name = "kurtosis"
[dependencies] [dependencies]
num-traits = "0.1" num-traits = "0.1"
num-integer = "0.1" num-integer = "0.1"

41
benches/kurtosis.rs Normal file
View File

@ -0,0 +1,41 @@
#![cfg_attr(feature = "cargo-clippy", allow(float_cmp, map_clone))]
#[macro_use] extern crate bencher;
extern crate rand;
extern crate average;
use bencher::Bencher;
/// Create a random vector by sampling from a normal distribution.
fn initialize_vec() -> Vec<f64> {
use rand::distributions::{Normal, IndependentSample};
use rand::{XorShiftRng, SeedableRng};
let normal = Normal::new(2.0, 3.0);
let n = 1_000_000;
let mut values = Vec::with_capacity(n);
let mut rng = XorShiftRng::from_seed([1, 2, 3, 4]);
for _ in 0..n {
values.push(normal.ind_sample(&mut rng));
}
values
}
fn bench_kurtosis(b: &mut Bencher) {
let values = initialize_vec();
b.iter(|| {
let m: average::Kurtosis = values.iter().map(|x| *x).collect();
m
});
}
fn bench_moments(b: &mut Bencher) {
let values = initialize_vec();
b.iter(|| {
let m: average::Moments = values.iter().map(|x| *x).collect();
m
});
}
benchmark_group!(benches, bench_kurtosis, bench_moments);
benchmark_main!(benches);

View File

@ -74,8 +74,7 @@
#![cfg_attr(feature = "cargo-clippy", allow(float_cmp))] #![cfg_attr(feature = "cargo-clippy", allow(float_cmp))]
//#![no_std] #![no_std]
extern crate core;
extern crate conv; extern crate conv;
extern crate quickersort; extern crate quickersort;

View File

@ -46,7 +46,6 @@ impl Kurtosis {
+ 6. * delta_n_sq * self.avg.avg.sum_2 + 6. * delta_n_sq * self.avg.avg.sum_2
- 4. * delta_n * self.avg.sum_3; - 4. * delta_n * self.avg.sum_3;
self.avg.add_inner(delta, delta_n); self.avg.add_inner(delta, delta_n);
println!("skewness={} kurtosis={}", self.skewness(), self.kurtosis());
} }
/// Determine whether the sample is empty. /// Determine whether the sample is empty.