criterion-stats 0.2.1

#[macro_use]
extern crate criterion;
extern crate criterion_stats as stats;
extern crate itertools_num;
extern crate rand;

mod common_bench;

macro_rules! bench {
    ($ty:ident) => {
        pub mod $ty {
            use stats::univariate::Sample;
            use stats::univariate::kde::kernel::Gaussian;
            use stats::univariate::kde::{Bandwidth, Kde};
            use criterion::Criterion;

            const KDE_POINTS: usize = 100;
            const SAMPLE_SIZE: usize = 100_000;

            fn call(c: &mut Criterion) {
                let data = ::common_bench::vec::<$ty>();

                c.bench_function(&format!("univariate_kde_call_{}", stringify!($ty)), move |b| {
                    let kde = Kde::new(Sample::new(&data), Gaussian, Bandwidth::Silverman);
                    let x = Sample::new(&data).mean();
                    b.iter(|| {
                        kde.estimate(x)
                    })
                });
            }

            fn map(c: &mut Criterion) {
                let data = ::common_bench::vec_sized(SAMPLE_SIZE).unwrap();
                let xs: Vec<_> = ::itertools_num::linspace::<$ty>(0., 1., KDE_POINTS).collect();

                c.bench_function(&format!("univariate_kde_map_{}", stringify!($ty)), move |b| {
                    let kde = Kde::new(Sample::new(&data), Gaussian, Bandwidth::Silverman);
                    b.iter(|| {
                        kde.map(&xs)
                    })
                });
            }

            criterion_group!(
                name = benches;
                config = ::common_bench::reduced_samples();
                targets = call, map);
        }
    }
}

mod bench {
    bench!(f32);
    bench!(f64);
}

criterion_main!(bench::f32::benches, bench::f64::benches);