criterion/stats/univariate/
mod.rs

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1//! Univariate analysis
2
3mod bootstrap;
4mod percentiles;
5mod resamples;
6mod sample;
7
8pub mod kde;
9pub mod mixed;
10pub mod outliers;
11
12use rayon::prelude::*;
13use stats::float::Float;
14use std::cmp;
15
16use stats::tuple::{Tuple, TupledDistributionsBuilder};
17
18use self::resamples::Resamples;
19
20pub use self::percentiles::Percentiles;
21pub use self::sample::Sample;
22
23/// Performs a two-sample bootstrap
24///
25/// - Multithreaded
26/// - Time: `O(nresamples)`
27/// - Memory: `O(nresamples)`
28#[cfg_attr(feature = "cargo-clippy", allow(clippy::cast_lossless))]
29pub fn bootstrap<A, B, T, S>(
30    a: &Sample<A>,
31    b: &Sample<B>,
32    nresamples: usize,
33    statistic: S,
34) -> T::Distributions
35where
36    A: Float,
37    B: Float,
38    S: Fn(&Sample<A>, &Sample<B>) -> T,
39    S: Sync,
40    T: Tuple + Send,
41    T::Distributions: Send,
42    T::Builder: Send,
43{
44    let nresamples_sqrt = (nresamples as f64).sqrt().ceil() as usize;
45    let per_chunk = (nresamples + nresamples_sqrt - 1) / nresamples_sqrt;
46
47    (0..nresamples_sqrt)
48        .into_par_iter()
49        .map_init(
50            || (Resamples::new(a), Resamples::new(b)),
51            |(a_resamples, b_resamples), i| {
52                let start = i * per_chunk;
53                let end = cmp::min((i + 1) * per_chunk, nresamples);
54                let a_resample = a_resamples.next();
55
56                let mut sub_distributions: T::Builder =
57                    TupledDistributionsBuilder::new(end - start);
58
59                for _ in start..end {
60                    let b_resample = b_resamples.next();
61                    sub_distributions.push(statistic(a_resample, b_resample));
62                }
63                sub_distributions
64            },
65        )
66        .reduce(
67            || T::Builder::new(0),
68            |mut a, mut b| {
69                a.extend(&mut b);
70                a
71            },
72        )
73        .complete()
74}
criterion/stats/univariate/mod.rs

criterion/stats/univariate/
mod.rs
