criterion/stats/bivariate/
mod.rs

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1//! Bivariate analysis
2
3mod bootstrap;
4pub mod regression;
5mod resamples;
6
7use crate::stats::bivariate::resamples::Resamples;
8use crate::stats::float::Float;
9use crate::stats::tuple::{Tuple, TupledDistributionsBuilder};
10use crate::stats::univariate::Sample;
11#[cfg(feature = "rayon")]
12use rayon::iter::{IntoParallelIterator, ParallelIterator};
13
14/// Bivariate `(X, Y)` data
15///
16/// Invariants:
17///
18/// - No `NaN`s in the data
19/// - At least two data points in the set
20pub struct Data<'a, X, Y>(&'a [X], &'a [Y]);
21
22impl<'a, X, Y> Copy for Data<'a, X, Y> {}
23
24#[cfg_attr(feature = "cargo-clippy", allow(clippy::expl_impl_clone_on_copy))]
25impl<'a, X, Y> Clone for Data<'a, X, Y> {
26    fn clone(&self) -> Data<'a, X, Y> {
27        *self
28    }
29}
30
31impl<'a, X, Y> Data<'a, X, Y> {
32    /// Returns the length of the data set
33    pub fn len(&self) -> usize {
34        self.0.len()
35    }
36
37    /// Iterate over the data set
38    pub fn iter(&self) -> Pairs<'a, X, Y> {
39        Pairs {
40            data: *self,
41            state: 0,
42        }
43    }
44}
45
46impl<'a, X, Y> Data<'a, X, Y>
47where
48    X: Float,
49    Y: Float,
50{
51    /// Creates a new data set from two existing slices
52    pub fn new(xs: &'a [X], ys: &'a [Y]) -> Data<'a, X, Y> {
53        assert!(
54            xs.len() == ys.len()
55                && xs.len() > 1
56                && xs.iter().all(|x| !x.is_nan())
57                && ys.iter().all(|y| !y.is_nan())
58        );
59
60        Data(xs, ys)
61    }
62
63    // TODO Remove the `T` parameter in favor of `S::Output`
64    /// Returns the bootstrap distributions of the parameters estimated by the `statistic`
65    ///
66    /// - Multi-threaded
67    /// - Time: `O(nresamples)`
68    /// - Memory: `O(nresamples)`
69    pub fn bootstrap<T, S>(&self, nresamples: usize, statistic: S) -> T::Distributions
70    where
71        S: Fn(Data<X, Y>) -> T + Sync,
72        T: Tuple + Send,
73        T::Distributions: Send,
74        T::Builder: Send,
75    {
76        #[cfg(feature = "rayon")]
77        {
78            (0..nresamples)
79                .into_par_iter()
80                .map_init(
81                    || Resamples::new(*self),
82                    |resamples, _| statistic(resamples.next()),
83                )
84                .fold(
85                    || T::Builder::new(0),
86                    |mut sub_distributions, sample| {
87                        sub_distributions.push(sample);
88                        sub_distributions
89                    },
90                )
91                .reduce(
92                    || T::Builder::new(0),
93                    |mut a, mut b| {
94                        a.extend(&mut b);
95                        a
96                    },
97                )
98                .complete()
99        }
100        #[cfg(not(feature = "rayon"))]
101        {
102            let mut resamples = Resamples::new(*self);
103            (0..nresamples)
104                .map(|_| statistic(resamples.next()))
105                .fold(T::Builder::new(0), |mut sub_distributions, sample| {
106                    sub_distributions.push(sample);
107                    sub_distributions
108                })
109                .complete()
110        }
111    }
112
113    /// Returns a view into the `X` data
114    pub fn x(&self) -> &'a Sample<X> {
115        Sample::new(self.0)
116    }
117
118    /// Returns a view into the `Y` data
119    pub fn y(&self) -> &'a Sample<Y> {
120        Sample::new(self.1)
121    }
122}
123
124/// Iterator over `Data`
125pub struct Pairs<'a, X: 'a, Y: 'a> {
126    data: Data<'a, X, Y>,
127    state: usize,
128}
129
130impl<'a, X, Y> Iterator for Pairs<'a, X, Y> {
131    type Item = (&'a X, &'a Y);
132
133    fn next(&mut self) -> Option<(&'a X, &'a Y)> {
134        if self.state < self.data.len() {
135            let i = self.state;
136            self.state += 1;
137
138            // This is safe because i will always be < self.data.{0,1}.len()
139            debug_assert!(i < self.data.0.len());
140            debug_assert!(i < self.data.1.len());
141            unsafe { Some((self.data.0.get_unchecked(i), self.data.1.get_unchecked(i))) }
142        } else {
143            None
144        }
145    }
146}
criterion/stats/bivariate/mod.rs

criterion/stats/bivariate/
mod.rs
