#![cfg(test)] use crate::prelude::*; use rand::distributions::Uniform; use rand::seq::SliceRandom; use rand::{thread_rng, Rng}; use std::cmp::Ordering::{Equal, Greater, Less}; macro_rules! sort { ($f:ident, $name:ident) => { #[test] fn $name() { let mut rng = thread_rng(); for len in (0..25).chain(500..501) { for &modulus in &[5, 10, 100] { let dist = Uniform::new(0, modulus); for _ in 0..100 { let v: Vec = rng.sample_iter(&dist).take(len).collect(); // Test sort using `<` operator. let mut tmp = v.clone(); tmp.$f(|a, b| a.cmp(b)); assert!(tmp.windows(2).all(|w| w[0] <= w[1])); // Test sort using `>` operator. let mut tmp = v.clone(); tmp.$f(|a, b| b.cmp(a)); assert!(tmp.windows(2).all(|w| w[0] >= w[1])); } } } // Test sort with many duplicates. for &len in &[1_000, 10_000, 100_000] { for &modulus in &[5, 10, 100, 10_000] { let dist = Uniform::new(0, modulus); let mut v: Vec = rng.sample_iter(&dist).take(len).collect(); v.$f(|a, b| a.cmp(b)); assert!(v.windows(2).all(|w| w[0] <= w[1])); } } // Test sort with many pre-sorted runs. for &len in &[1_000, 10_000, 100_000] { let len_dist = Uniform::new(0, len); for &modulus in &[5, 10, 1000, 50_000] { let dist = Uniform::new(0, modulus); let mut v: Vec = rng.sample_iter(&dist).take(len).collect(); v.sort(); v.reverse(); for _ in 0..5 { let a = rng.sample(&len_dist); let b = rng.sample(&len_dist); if a < b { v[a..b].reverse(); } else { v.swap(a, b); } } v.$f(|a, b| a.cmp(b)); assert!(v.windows(2).all(|w| w[0] <= w[1])); } } // Sort using a completely random comparison function. // This will reorder the elements *somehow*, but won't panic. let mut v: Vec<_> = (0..100).collect(); v.$f(|_, _| *[Less, Equal, Greater].choose(&mut thread_rng()).unwrap()); v.$f(|a, b| a.cmp(b)); for i in 0..v.len() { assert_eq!(v[i], i); } // Should not panic. [0i32; 0].$f(|a, b| a.cmp(b)); [(); 10].$f(|a, b| a.cmp(b)); [(); 100].$f(|a, b| a.cmp(b)); let mut v = [0xDEAD_BEEFu64]; v.$f(|a, b| a.cmp(b)); assert!(v == [0xDEAD_BEEF]); } }; } sort!(par_sort_by, test_par_sort); sort!(par_sort_unstable_by, test_par_sort_unstable); #[test] fn test_par_sort_stability() { for len in (2..25).chain(500..510).chain(50_000..50_010) { for _ in 0..10 { let mut counts = [0; 10]; // Create a vector like [(6, 1), (5, 1), (6, 2), ...], // where the first item of each tuple is random, but // the second item represents which occurrence of that // number this element is, i.e. the second elements // will occur in sorted order. let mut rng = thread_rng(); let mut v: Vec<_> = (0..len) .map(|_| { let n: usize = rng.gen_range(0, 10); counts[n] += 1; (n, counts[n]) }) .collect(); // Only sort on the first element, so an unstable sort // may mix up the counts. v.par_sort_by(|&(a, _), &(b, _)| a.cmp(&b)); // This comparison includes the count (the second item // of the tuple), so elements with equal first items // will need to be ordered with increasing // counts... i.e. exactly asserting that this sort is // stable. assert!(v.windows(2).all(|w| w[0] <= w[1])); } } } #[test] fn test_par_chunks_exact_remainder() { let v: &[i32] = &[0, 1, 2, 3, 4]; let c = v.par_chunks_exact(2); assert_eq!(c.remainder(), &[4]); assert_eq!(c.len(), 2); } #[test] fn test_par_chunks_exact_mut_remainder() { let v: &mut [i32] = &mut [0, 1, 2, 3, 4]; let mut c = v.par_chunks_exact_mut(2); assert_eq!(c.remainder(), &[4]); assert_eq!(c.len(), 2); assert_eq!(c.into_remainder(), &[4]); let mut c = v.par_chunks_exact_mut(2); assert_eq!(c.take_remainder(), &[4]); assert_eq!(c.take_remainder(), &[]); assert_eq!(c.len(), 2); }