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authorValentin Popov <valentin@popov.link>2024-07-19 15:37:58 +0300
committerValentin Popov <valentin@popov.link>2024-07-19 15:37:58 +0300
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tree15afc392522a9e85dc3332235e311b7d39352ea9 /vendor/rayon/src/slice/mod.rs
parent3d48cd3f81164bbfc1a755dc1d4a9a02f98c8ddd (diff)
downloadfparkan-a990de90fe41456a23e58bd087d2f107d321f3a1.tar.xz
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-//! Parallel iterator types for [slices][std::slice]
-//!
-//! You will rarely need to interact with this module directly unless you need
-//! to name one of the iterator types.
-//!
-//! [std::slice]: https://doc.rust-lang.org/stable/std/slice/
-
-mod chunks;
-mod mergesort;
-mod quicksort;
-mod rchunks;
-
-mod test;
-
-use self::mergesort::par_mergesort;
-use self::quicksort::par_quicksort;
-use crate::iter::plumbing::*;
-use crate::iter::*;
-use crate::split_producer::*;
-use std::cmp;
-use std::cmp::Ordering;
-use std::fmt::{self, Debug};
-use std::mem;
-
-pub use self::chunks::{Chunks, ChunksExact, ChunksExactMut, ChunksMut};
-pub use self::rchunks::{RChunks, RChunksExact, RChunksExactMut, RChunksMut};
-
-/// Parallel extensions for slices.
-pub trait ParallelSlice<T: Sync> {
- /// Returns a plain slice, which is used to implement the rest of the
- /// parallel methods.
- fn as_parallel_slice(&self) -> &[T];
-
- /// Returns a parallel iterator over subslices separated by elements that
- /// match the separator.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let smallest = [1, 2, 3, 0, 2, 4, 8, 0, 3, 6, 9]
- /// .par_split(|i| *i == 0)
- /// .map(|numbers| numbers.iter().min().unwrap())
- /// .min();
- /// assert_eq!(Some(&1), smallest);
- /// ```
- fn par_split<P>(&self, separator: P) -> Split<'_, T, P>
- where
- P: Fn(&T) -> bool + Sync + Send,
- {
- Split {
- slice: self.as_parallel_slice(),
- separator,
- }
- }
-
- /// Returns a parallel iterator over all contiguous windows of length
- /// `window_size`. The windows overlap.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let windows: Vec<_> = [1, 2, 3].par_windows(2).collect();
- /// assert_eq!(vec![[1, 2], [2, 3]], windows);
- /// ```
- fn par_windows(&self, window_size: usize) -> Windows<'_, T> {
- Windows {
- window_size,
- slice: self.as_parallel_slice(),
- }
- }
-
- /// Returns a parallel iterator over at most `chunk_size` elements of
- /// `self` at a time. The chunks do not overlap.
- ///
- /// If the number of elements in the iterator is not divisible by
- /// `chunk_size`, the last chunk may be shorter than `chunk_size`. All
- /// other chunks will have that exact length.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_chunks(2).collect();
- /// assert_eq!(chunks, vec![&[1, 2][..], &[3, 4], &[5]]);
- /// ```
- #[track_caller]
- fn par_chunks(&self, chunk_size: usize) -> Chunks<'_, T> {
- assert!(chunk_size != 0, "chunk_size must not be zero");
- Chunks::new(chunk_size, self.as_parallel_slice())
- }
-
- /// Returns a parallel iterator over `chunk_size` elements of
- /// `self` at a time. The chunks do not overlap.
- ///
- /// If `chunk_size` does not divide the length of the slice, then the
- /// last up to `chunk_size-1` elements will be omitted and can be
- /// retrieved from the remainder function of the iterator.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_chunks_exact(2).collect();
- /// assert_eq!(chunks, vec![&[1, 2][..], &[3, 4]]);
- /// ```
- #[track_caller]
- fn par_chunks_exact(&self, chunk_size: usize) -> ChunksExact<'_, T> {
- assert!(chunk_size != 0, "chunk_size must not be zero");
- ChunksExact::new(chunk_size, self.as_parallel_slice())
- }
-
- /// Returns a parallel iterator over at most `chunk_size` elements of `self` at a time,
- /// starting at the end. The chunks do not overlap.
- ///
- /// If the number of elements in the iterator is not divisible by
- /// `chunk_size`, the last chunk may be shorter than `chunk_size`. All
- /// other chunks will have that exact length.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_rchunks(2).collect();
- /// assert_eq!(chunks, vec![&[4, 5][..], &[2, 3], &[1]]);
- /// ```
- #[track_caller]
- fn par_rchunks(&self, chunk_size: usize) -> RChunks<'_, T> {
- assert!(chunk_size != 0, "chunk_size must not be zero");
- RChunks::new(chunk_size, self.as_parallel_slice())
- }
-
- /// Returns a parallel iterator over `chunk_size` elements of `self` at a time,
- /// starting at the end. The chunks do not overlap.
- ///
- /// If `chunk_size` does not divide the length of the slice, then the
- /// last up to `chunk_size-1` elements will be omitted and can be
- /// retrieved from the remainder function of the iterator.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_rchunks_exact(2).collect();
- /// assert_eq!(chunks, vec![&[4, 5][..], &[2, 3]]);
- /// ```
- #[track_caller]
- fn par_rchunks_exact(&self, chunk_size: usize) -> RChunksExact<'_, T> {
- assert!(chunk_size != 0, "chunk_size must not be zero");
- RChunksExact::new(chunk_size, self.as_parallel_slice())
- }
-}
-
-impl<T: Sync> ParallelSlice<T> for [T] {
- #[inline]
- fn as_parallel_slice(&self) -> &[T] {
- self
- }
-}
-
-/// Parallel extensions for mutable slices.
-pub trait ParallelSliceMut<T: Send> {
- /// Returns a plain mutable slice, which is used to implement the rest of
- /// the parallel methods.
- fn as_parallel_slice_mut(&mut self) -> &mut [T];
-
- /// Returns a parallel iterator over mutable subslices separated by
- /// elements that match the separator.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let mut array = [1, 2, 3, 0, 2, 4, 8, 0, 3, 6, 9];
- /// array.par_split_mut(|i| *i == 0)
- /// .for_each(|slice| slice.reverse());
- /// assert_eq!(array, [3, 2, 1, 0, 8, 4, 2, 0, 9, 6, 3]);
- /// ```
- fn par_split_mut<P>(&mut self, separator: P) -> SplitMut<'_, T, P>
- where
- P: Fn(&T) -> bool + Sync + Send,
- {
- SplitMut {
- slice: self.as_parallel_slice_mut(),
- separator,
- }
- }
-
- /// Returns a parallel iterator over at most `chunk_size` elements of
- /// `self` at a time. The chunks are mutable and do not overlap.
- ///
- /// If the number of elements in the iterator is not divisible by
- /// `chunk_size`, the last chunk may be shorter than `chunk_size`. All
- /// other chunks will have that exact length.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let mut array = [1, 2, 3, 4, 5];
- /// array.par_chunks_mut(2)
- /// .for_each(|slice| slice.reverse());
- /// assert_eq!(array, [2, 1, 4, 3, 5]);
- /// ```
- #[track_caller]
- fn par_chunks_mut(&mut self, chunk_size: usize) -> ChunksMut<'_, T> {
- assert!(chunk_size != 0, "chunk_size must not be zero");
- ChunksMut::new(chunk_size, self.as_parallel_slice_mut())
- }
-
- /// Returns a parallel iterator over `chunk_size` elements of
- /// `self` at a time. The chunks are mutable and do not overlap.
- ///
- /// If `chunk_size` does not divide the length of the slice, then the
- /// last up to `chunk_size-1` elements will be omitted and can be
- /// retrieved from the remainder function of the iterator.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let mut array = [1, 2, 3, 4, 5];
- /// array.par_chunks_exact_mut(3)
- /// .for_each(|slice| slice.reverse());
- /// assert_eq!(array, [3, 2, 1, 4, 5]);
- /// ```
- #[track_caller]
- fn par_chunks_exact_mut(&mut self, chunk_size: usize) -> ChunksExactMut<'_, T> {
- assert!(chunk_size != 0, "chunk_size must not be zero");
- ChunksExactMut::new(chunk_size, self.as_parallel_slice_mut())
- }
-
- /// Returns a parallel iterator over at most `chunk_size` elements of `self` at a time,
- /// starting at the end. The chunks are mutable and do not overlap.
- ///
- /// If the number of elements in the iterator is not divisible by
- /// `chunk_size`, the last chunk may be shorter than `chunk_size`. All
- /// other chunks will have that exact length.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let mut array = [1, 2, 3, 4, 5];
- /// array.par_rchunks_mut(2)
- /// .for_each(|slice| slice.reverse());
- /// assert_eq!(array, [1, 3, 2, 5, 4]);
- /// ```
- #[track_caller]
- fn par_rchunks_mut(&mut self, chunk_size: usize) -> RChunksMut<'_, T> {
- assert!(chunk_size != 0, "chunk_size must not be zero");
- RChunksMut::new(chunk_size, self.as_parallel_slice_mut())
- }
-
- /// Returns a parallel iterator over `chunk_size` elements of `self` at a time,
- /// starting at the end. The chunks are mutable and do not overlap.
- ///
- /// If `chunk_size` does not divide the length of the slice, then the
- /// last up to `chunk_size-1` elements will be omitted and can be
- /// retrieved from the remainder function of the iterator.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- /// let mut array = [1, 2, 3, 4, 5];
- /// array.par_rchunks_exact_mut(3)
- /// .for_each(|slice| slice.reverse());
- /// assert_eq!(array, [1, 2, 5, 4, 3]);
- /// ```
- #[track_caller]
- fn par_rchunks_exact_mut(&mut self, chunk_size: usize) -> RChunksExactMut<'_, T> {
- assert!(chunk_size != 0, "chunk_size must not be zero");
- RChunksExactMut::new(chunk_size, self.as_parallel_slice_mut())
- }
-
- /// Sorts the slice in parallel.
- ///
- /// This sort is stable (i.e., does not reorder equal elements) and *O*(*n* \* log(*n*)) worst-case.
- ///
- /// When applicable, unstable sorting is preferred because it is generally faster than stable
- /// sorting and it doesn't allocate auxiliary memory.
- /// See [`par_sort_unstable`](#method.par_sort_unstable).
- ///
- /// # Current implementation
- ///
- /// The current algorithm is an adaptive merge sort inspired by
- /// [timsort](https://en.wikipedia.org/wiki/Timsort).
- /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
- /// two or more sorted sequences concatenated one after another.
- ///
- /// Also, it allocates temporary storage the same size as `self`, but for very short slices a
- /// non-allocating insertion sort is used instead.
- ///
- /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and
- /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending
- /// or descending runs are concatenated. Finally, the remaining chunks are merged together using
- /// parallel subdivision of chunks and parallel merge operation.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- ///
- /// let mut v = [-5, 4, 1, -3, 2];
- ///
- /// v.par_sort();
- /// assert_eq!(v, [-5, -3, 1, 2, 4]);
- /// ```
- fn par_sort(&mut self)
- where
- T: Ord,
- {
- par_mergesort(self.as_parallel_slice_mut(), T::lt);
- }
-
- /// Sorts the slice in parallel with a comparator function.
- ///
- /// This sort is stable (i.e., does not reorder equal elements) and *O*(*n* \* log(*n*)) worst-case.
- ///
- /// The comparator function must define a total ordering for the elements in the slice. If
- /// the ordering is not total, the order of the elements is unspecified. An order is a
- /// total order if it is (for all `a`, `b` and `c`):
- ///
- /// * total and antisymmetric: exactly one of `a < b`, `a == b` or `a > b` is true, and
- /// * transitive, `a < b` and `b < c` implies `a < c`. The same must hold for both `==` and `>`.
- ///
- /// For example, while [`f64`] doesn't implement [`Ord`] because `NaN != NaN`, we can use
- /// `partial_cmp` as our sort function when we know the slice doesn't contain a `NaN`.
- ///
- /// ```
- /// use rayon::prelude::*;
- ///
- /// let mut floats = [5f64, 4.0, 1.0, 3.0, 2.0];
- /// floats.par_sort_by(|a, b| a.partial_cmp(b).unwrap());
- /// assert_eq!(floats, [1.0, 2.0, 3.0, 4.0, 5.0]);
- /// ```
- ///
- /// When applicable, unstable sorting is preferred because it is generally faster than stable
- /// sorting and it doesn't allocate auxiliary memory.
- /// See [`par_sort_unstable_by`](#method.par_sort_unstable_by).
- ///
- /// # Current implementation
- ///
- /// The current algorithm is an adaptive merge sort inspired by
- /// [timsort](https://en.wikipedia.org/wiki/Timsort).
- /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
- /// two or more sorted sequences concatenated one after another.
- ///
- /// Also, it allocates temporary storage the same size as `self`, but for very short slices a
- /// non-allocating insertion sort is used instead.
- ///
- /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and
- /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending
- /// or descending runs are concatenated. Finally, the remaining chunks are merged together using
- /// parallel subdivision of chunks and parallel merge operation.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- ///
- /// let mut v = [5, 4, 1, 3, 2];
- /// v.par_sort_by(|a, b| a.cmp(b));
- /// assert_eq!(v, [1, 2, 3, 4, 5]);
- ///
- /// // reverse sorting
- /// v.par_sort_by(|a, b| b.cmp(a));
- /// assert_eq!(v, [5, 4, 3, 2, 1]);
- /// ```
- fn par_sort_by<F>(&mut self, compare: F)
- where
- F: Fn(&T, &T) -> Ordering + Sync,
- {
- par_mergesort(self.as_parallel_slice_mut(), |a, b| {
- compare(a, b) == Ordering::Less
- });
- }
-
- /// Sorts the slice in parallel with a key extraction function.
- ///
- /// This sort is stable (i.e., does not reorder equal elements) and *O*(*m* \* *n* \* log(*n*))
- /// worst-case, where the key function is *O*(*m*).
- ///
- /// For expensive key functions (e.g. functions that are not simple property accesses or
- /// basic operations), [`par_sort_by_cached_key`](#method.par_sort_by_cached_key) is likely to
- /// be significantly faster, as it does not recompute element keys.
- ///
- /// When applicable, unstable sorting is preferred because it is generally faster than stable
- /// sorting and it doesn't allocate auxiliary memory.
- /// See [`par_sort_unstable_by_key`](#method.par_sort_unstable_by_key).
- ///
- /// # Current implementation
- ///
- /// The current algorithm is an adaptive merge sort inspired by
- /// [timsort](https://en.wikipedia.org/wiki/Timsort).
- /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
- /// two or more sorted sequences concatenated one after another.
- ///
- /// Also, it allocates temporary storage the same size as `self`, but for very short slices a
- /// non-allocating insertion sort is used instead.
- ///
- /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and
- /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending
- /// or descending runs are concatenated. Finally, the remaining chunks are merged together using
- /// parallel subdivision of chunks and parallel merge operation.
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- ///
- /// let mut v = [-5i32, 4, 1, -3, 2];
- ///
- /// v.par_sort_by_key(|k| k.abs());
- /// assert_eq!(v, [1, 2, -3, 4, -5]);
- /// ```
- fn par_sort_by_key<K, F>(&mut self, f: F)
- where
- K: Ord,
- F: Fn(&T) -> K + Sync,
- {
- par_mergesort(self.as_parallel_slice_mut(), |a, b| f(a).lt(&f(b)));
- }
-
- /// Sorts the slice in parallel with a key extraction function.
- ///
- /// During sorting, the key function is called at most once per element, by using
- /// temporary storage to remember the results of key evaluation.
- /// The key function is called in parallel, so the order of calls is completely unspecified.
- ///
- /// This sort is stable (i.e., does not reorder equal elements) and *O*(*m* \* *n* + *n* \* log(*n*))
- /// worst-case, where the key function is *O*(*m*).
- ///
- /// For simple key functions (e.g., functions that are property accesses or
- /// basic operations), [`par_sort_by_key`](#method.par_sort_by_key) is likely to be
- /// faster.
- ///
- /// # Current implementation
- ///
- /// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters,
- /// which combines the fast average case of randomized quicksort with the fast worst case of
- /// heapsort, while achieving linear time on slices with certain patterns. It uses some
- /// randomization to avoid degenerate cases, but with a fixed seed to always provide
- /// deterministic behavior.
- ///
- /// In the worst case, the algorithm allocates temporary storage in a `Vec<(K, usize)>` the
- /// length of the slice.
- ///
- /// All quicksorts work in two stages: partitioning into two halves followed by recursive
- /// calls. The partitioning phase is sequential, but the two recursive calls are performed in
- /// parallel. Finally, after sorting the cached keys, the item positions are updated sequentially.
- ///
- /// [pdqsort]: https://github.com/orlp/pdqsort
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- ///
- /// let mut v = [-5i32, 4, 32, -3, 2];
- ///
- /// v.par_sort_by_cached_key(|k| k.to_string());
- /// assert!(v == [-3, -5, 2, 32, 4]);
- /// ```
- fn par_sort_by_cached_key<K, F>(&mut self, f: F)
- where
- F: Fn(&T) -> K + Sync,
- K: Ord + Send,
- {
- let slice = self.as_parallel_slice_mut();
- let len = slice.len();
- if len < 2 {
- return;
- }
-
- // Helper macro for indexing our vector by the smallest possible type, to reduce allocation.
- macro_rules! sort_by_key {
- ($t:ty) => {{
- let mut indices: Vec<_> = slice
- .par_iter_mut()
- .enumerate()
- .map(|(i, x)| (f(&*x), i as $t))
- .collect();
- // The elements of `indices` are unique, as they are indexed, so any sort will be
- // stable with respect to the original slice. We use `sort_unstable` here because
- // it requires less memory allocation.
- indices.par_sort_unstable();
- for i in 0..len {
- let mut index = indices[i].1;
- while (index as usize) < i {
- index = indices[index as usize].1;
- }
- indices[i].1 = index;
- slice.swap(i, index as usize);
- }
- }};
- }
-
- let sz_u8 = mem::size_of::<(K, u8)>();
- let sz_u16 = mem::size_of::<(K, u16)>();
- let sz_u32 = mem::size_of::<(K, u32)>();
- let sz_usize = mem::size_of::<(K, usize)>();
-
- if sz_u8 < sz_u16 && len <= (std::u8::MAX as usize) {
- return sort_by_key!(u8);
- }
- if sz_u16 < sz_u32 && len <= (std::u16::MAX as usize) {
- return sort_by_key!(u16);
- }
- if sz_u32 < sz_usize && len <= (std::u32::MAX as usize) {
- return sort_by_key!(u32);
- }
- sort_by_key!(usize)
- }
-
- /// Sorts the slice in parallel, but might not preserve the order of equal elements.
- ///
- /// This sort is unstable (i.e., may reorder equal elements), in-place
- /// (i.e., does not allocate), and *O*(*n* \* log(*n*)) worst-case.
- ///
- /// # Current implementation
- ///
- /// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters,
- /// which combines the fast average case of randomized quicksort with the fast worst case of
- /// heapsort, while achieving linear time on slices with certain patterns. It uses some
- /// randomization to avoid degenerate cases, but with a fixed seed to always provide
- /// deterministic behavior.
- ///
- /// It is typically faster than stable sorting, except in a few special cases, e.g., when the
- /// slice consists of several concatenated sorted sequences.
- ///
- /// All quicksorts work in two stages: partitioning into two halves followed by recursive
- /// calls. The partitioning phase is sequential, but the two recursive calls are performed in
- /// parallel.
- ///
- /// [pdqsort]: https://github.com/orlp/pdqsort
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- ///
- /// let mut v = [-5, 4, 1, -3, 2];
- ///
- /// v.par_sort_unstable();
- /// assert_eq!(v, [-5, -3, 1, 2, 4]);
- /// ```
- fn par_sort_unstable(&mut self)
- where
- T: Ord,
- {
- par_quicksort(self.as_parallel_slice_mut(), T::lt);
- }
-
- /// Sorts the slice in parallel with a comparator function, but might not preserve the order of
- /// equal elements.
- ///
- /// This sort is unstable (i.e., may reorder equal elements), in-place
- /// (i.e., does not allocate), and *O*(*n* \* log(*n*)) worst-case.
- ///
- /// The comparator function must define a total ordering for the elements in the slice. If
- /// the ordering is not total, the order of the elements is unspecified. An order is a
- /// total order if it is (for all `a`, `b` and `c`):
- ///
- /// * total and antisymmetric: exactly one of `a < b`, `a == b` or `a > b` is true, and
- /// * transitive, `a < b` and `b < c` implies `a < c`. The same must hold for both `==` and `>`.
- ///
- /// For example, while [`f64`] doesn't implement [`Ord`] because `NaN != NaN`, we can use
- /// `partial_cmp` as our sort function when we know the slice doesn't contain a `NaN`.
- ///
- /// ```
- /// use rayon::prelude::*;
- ///
- /// let mut floats = [5f64, 4.0, 1.0, 3.0, 2.0];
- /// floats.par_sort_unstable_by(|a, b| a.partial_cmp(b).unwrap());
- /// assert_eq!(floats, [1.0, 2.0, 3.0, 4.0, 5.0]);
- /// ```
- ///
- /// # Current implementation
- ///
- /// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters,
- /// which combines the fast average case of randomized quicksort with the fast worst case of
- /// heapsort, while achieving linear time on slices with certain patterns. It uses some
- /// randomization to avoid degenerate cases, but with a fixed seed to always provide
- /// deterministic behavior.
- ///
- /// It is typically faster than stable sorting, except in a few special cases, e.g., when the
- /// slice consists of several concatenated sorted sequences.
- ///
- /// All quicksorts work in two stages: partitioning into two halves followed by recursive
- /// calls. The partitioning phase is sequential, but the two recursive calls are performed in
- /// parallel.
- ///
- /// [pdqsort]: https://github.com/orlp/pdqsort
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- ///
- /// let mut v = [5, 4, 1, 3, 2];
- /// v.par_sort_unstable_by(|a, b| a.cmp(b));
- /// assert_eq!(v, [1, 2, 3, 4, 5]);
- ///
- /// // reverse sorting
- /// v.par_sort_unstable_by(|a, b| b.cmp(a));
- /// assert_eq!(v, [5, 4, 3, 2, 1]);
- /// ```
- fn par_sort_unstable_by<F>(&mut self, compare: F)
- where
- F: Fn(&T, &T) -> Ordering + Sync,
- {
- par_quicksort(self.as_parallel_slice_mut(), |a, b| {
- compare(a, b) == Ordering::Less
- });
- }
-
- /// Sorts the slice in parallel with a key extraction function, but might not preserve the order
- /// of equal elements.
- ///
- /// This sort is unstable (i.e., may reorder equal elements), in-place
- /// (i.e., does not allocate), and *O*(m \* *n* \* log(*n*)) worst-case,
- /// where the key function is *O*(*m*).
- ///
- /// # Current implementation
- ///
- /// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters,
- /// which combines the fast average case of randomized quicksort with the fast worst case of
- /// heapsort, while achieving linear time on slices with certain patterns. It uses some
- /// randomization to avoid degenerate cases, but with a fixed seed to always provide
- /// deterministic behavior.
- ///
- /// Due to its key calling strategy, `par_sort_unstable_by_key` is likely to be slower than
- /// [`par_sort_by_cached_key`](#method.par_sort_by_cached_key) in cases where the key function
- /// is expensive.
- ///
- /// All quicksorts work in two stages: partitioning into two halves followed by recursive
- /// calls. The partitioning phase is sequential, but the two recursive calls are performed in
- /// parallel.
- ///
- /// [pdqsort]: https://github.com/orlp/pdqsort
- ///
- /// # Examples
- ///
- /// ```
- /// use rayon::prelude::*;
- ///
- /// let mut v = [-5i32, 4, 1, -3, 2];
- ///
- /// v.par_sort_unstable_by_key(|k| k.abs());
- /// assert_eq!(v, [1, 2, -3, 4, -5]);
- /// ```
- fn par_sort_unstable_by_key<K, F>(&mut self, f: F)
- where
- K: Ord,
- F: Fn(&T) -> K + Sync,
- {
- par_quicksort(self.as_parallel_slice_mut(), |a, b| f(a).lt(&f(b)));
- }
-}
-
-impl<T: Send> ParallelSliceMut<T> for [T] {
- #[inline]
- fn as_parallel_slice_mut(&mut self) -> &mut [T] {
- self
- }
-}
-
-impl<'data, T: Sync + 'data> IntoParallelIterator for &'data [T] {
- type Item = &'data T;
- type Iter = Iter<'data, T>;
-
- fn into_par_iter(self) -> Self::Iter {
- Iter { slice: self }
- }
-}
-
-impl<'data, T: Send + 'data> IntoParallelIterator for &'data mut [T] {
- type Item = &'data mut T;
- type Iter = IterMut<'data, T>;
-
- fn into_par_iter(self) -> Self::Iter {
- IterMut { slice: self }
- }
-}
-
-/// Parallel iterator over immutable items in a slice
-#[derive(Debug)]
-pub struct Iter<'data, T: Sync> {
- slice: &'data [T],
-}
-
-impl<'data, T: Sync> Clone for Iter<'data, T> {
- fn clone(&self) -> Self {
- Iter { ..*self }
- }
-}
-
-impl<'data, T: Sync + 'data> ParallelIterator for Iter<'data, T> {
- type Item = &'data T;
-
- fn drive_unindexed<C>(self, consumer: C) -> C::Result
- where
- C: UnindexedConsumer<Self::Item>,
- {
- bridge(self, consumer)
- }
-
- fn opt_len(&self) -> Option<usize> {
- Some(self.len())
- }
-}
-
-impl<'data, T: Sync + 'data> IndexedParallelIterator for Iter<'data, T> {
- fn drive<C>(self, consumer: C) -> C::Result
- where
- C: Consumer<Self::Item>,
- {
- bridge(self, consumer)
- }
-
- fn len(&self) -> usize {
- self.slice.len()
- }
-
- fn with_producer<CB>(self, callback: CB) -> CB::Output
- where
- CB: ProducerCallback<Self::Item>,
- {
- callback.callback(IterProducer { slice: self.slice })
- }
-}
-
-struct IterProducer<'data, T: Sync> {
- slice: &'data [T],
-}
-
-impl<'data, T: 'data + Sync> Producer for IterProducer<'data, T> {
- type Item = &'data T;
- type IntoIter = ::std::slice::Iter<'data, T>;
-
- fn into_iter(self) -> Self::IntoIter {
- self.slice.iter()
- }
-
- fn split_at(self, index: usize) -> (Self, Self) {
- let (left, right) = self.slice.split_at(index);
- (IterProducer { slice: left }, IterProducer { slice: right })
- }
-}
-
-/// Parallel iterator over immutable overlapping windows of a slice
-#[derive(Debug)]
-pub struct Windows<'data, T: Sync> {
- window_size: usize,
- slice: &'data [T],
-}
-
-impl<'data, T: Sync> Clone for Windows<'data, T> {
- fn clone(&self) -> Self {
- Windows { ..*self }
- }
-}
-
-impl<'data, T: Sync + 'data> ParallelIterator for Windows<'data, T> {
- type Item = &'data [T];
-
- fn drive_unindexed<C>(self, consumer: C) -> C::Result
- where
- C: UnindexedConsumer<Self::Item>,
- {
- bridge(self, consumer)
- }
-
- fn opt_len(&self) -> Option<usize> {
- Some(self.len())
- }
-}
-
-impl<'data, T: Sync + 'data> IndexedParallelIterator for Windows<'data, T> {
- fn drive<C>(self, consumer: C) -> C::Result
- where
- C: Consumer<Self::Item>,
- {
- bridge(self, consumer)
- }
-
- fn len(&self) -> usize {
- assert!(self.window_size >= 1);
- self.slice.len().saturating_sub(self.window_size - 1)
- }
-
- fn with_producer<CB>(self, callback: CB) -> CB::Output
- where
- CB: ProducerCallback<Self::Item>,
- {
- callback.callback(WindowsProducer {
- window_size: self.window_size,
- slice: self.slice,
- })
- }
-}
-
-struct WindowsProducer<'data, T: Sync> {
- window_size: usize,
- slice: &'data [T],
-}
-
-impl<'data, T: 'data + Sync> Producer for WindowsProducer<'data, T> {
- type Item = &'data [T];
- type IntoIter = ::std::slice::Windows<'data, T>;
-
- fn into_iter(self) -> Self::IntoIter {
- self.slice.windows(self.window_size)
- }
-
- fn split_at(self, index: usize) -> (Self, Self) {
- let left_index = cmp::min(self.slice.len(), index + (self.window_size - 1));
- let left = &self.slice[..left_index];
- let right = &self.slice[index..];
- (
- WindowsProducer {
- window_size: self.window_size,
- slice: left,
- },
- WindowsProducer {
- window_size: self.window_size,
- slice: right,
- },
- )
- }
-}
-
-/// Parallel iterator over mutable items in a slice
-#[derive(Debug)]
-pub struct IterMut<'data, T: Send> {
- slice: &'data mut [T],
-}
-
-impl<'data, T: Send + 'data> ParallelIterator for IterMut<'data, T> {
- type Item = &'data mut T;
-
- fn drive_unindexed<C>(self, consumer: C) -> C::Result
- where
- C: UnindexedConsumer<Self::Item>,
- {
- bridge(self, consumer)
- }
-
- fn opt_len(&self) -> Option<usize> {
- Some(self.len())
- }
-}
-
-impl<'data, T: Send + 'data> IndexedParallelIterator for IterMut<'data, T> {
- fn drive<C>(self, consumer: C) -> C::Result
- where
- C: Consumer<Self::Item>,
- {
- bridge(self, consumer)
- }
-
- fn len(&self) -> usize {
- self.slice.len()
- }
-
- fn with_producer<CB>(self, callback: CB) -> CB::Output
- where
- CB: ProducerCallback<Self::Item>,
- {
- callback.callback(IterMutProducer { slice: self.slice })
- }
-}
-
-struct IterMutProducer<'data, T: Send> {
- slice: &'data mut [T],
-}
-
-impl<'data, T: 'data + Send> Producer for IterMutProducer<'data, T> {
- type Item = &'data mut T;
- type IntoIter = ::std::slice::IterMut<'data, T>;
-
- fn into_iter(self) -> Self::IntoIter {
- self.slice.iter_mut()
- }
-
- fn split_at(self, index: usize) -> (Self, Self) {
- let (left, right) = self.slice.split_at_mut(index);
- (
- IterMutProducer { slice: left },
- IterMutProducer { slice: right },
- )
- }
-}
-
-/// Parallel iterator over slices separated by a predicate
-pub struct Split<'data, T, P> {
- slice: &'data [T],
- separator: P,
-}
-
-impl<'data, T, P: Clone> Clone for Split<'data, T, P> {
- fn clone(&self) -> Self {
- Split {
- separator: self.separator.clone(),
- ..*self
- }
- }
-}
-
-impl<'data, T: Debug, P> Debug for Split<'data, T, P> {
- fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
- f.debug_struct("Split").field("slice", &self.slice).finish()
- }
-}
-
-impl<'data, T, P> ParallelIterator for Split<'data, T, P>
-where
- P: Fn(&T) -> bool + Sync + Send,
- T: Sync,
-{
- type Item = &'data [T];
-
- fn drive_unindexed<C>(self, consumer: C) -> C::Result
- where
- C: UnindexedConsumer<Self::Item>,
- {
- let producer = SplitProducer::new(self.slice, &self.separator);
- bridge_unindexed(producer, consumer)
- }
-}
-
-/// Implement support for `SplitProducer`.
-impl<'data, T, P> Fissile<P> for &'data [T]
-where
- P: Fn(&T) -> bool,
-{
- fn length(&self) -> usize {
- self.len()
- }
-
- fn midpoint(&self, end: usize) -> usize {
- end / 2
- }
-
- fn find(&self, separator: &P, start: usize, end: usize) -> Option<usize> {
- self[start..end].iter().position(separator)
- }
-
- fn rfind(&self, separator: &P, end: usize) -> Option<usize> {
- self[..end].iter().rposition(separator)
- }
-
- fn split_once(self, index: usize) -> (Self, Self) {
- let (left, right) = self.split_at(index);
- (left, &right[1..]) // skip the separator
- }
-
- fn fold_splits<F>(self, separator: &P, folder: F, skip_last: bool) -> F
- where
- F: Folder<Self>,
- Self: Send,
- {
- let mut split = self.split(separator);
- if skip_last {
- split.next_back();
- }
- folder.consume_iter(split)
- }
-}
-
-/// Parallel iterator over mutable slices separated by a predicate
-pub struct SplitMut<'data, T, P> {
- slice: &'data mut [T],
- separator: P,
-}
-
-impl<'data, T: Debug, P> Debug for SplitMut<'data, T, P> {
- fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
- f.debug_struct("SplitMut")
- .field("slice", &self.slice)
- .finish()
- }
-}
-
-impl<'data, T, P> ParallelIterator for SplitMut<'data, T, P>
-where
- P: Fn(&T) -> bool + Sync + Send,
- T: Send,
-{
- type Item = &'data mut [T];
-
- fn drive_unindexed<C>(self, consumer: C) -> C::Result
- where
- C: UnindexedConsumer<Self::Item>,
- {
- let producer = SplitProducer::new(self.slice, &self.separator);
- bridge_unindexed(producer, consumer)
- }
-}
-
-/// Implement support for `SplitProducer`.
-impl<'data, T, P> Fissile<P> for &'data mut [T]
-where
- P: Fn(&T) -> bool,
-{
- fn length(&self) -> usize {
- self.len()
- }
-
- fn midpoint(&self, end: usize) -> usize {
- end / 2
- }
-
- fn find(&self, separator: &P, start: usize, end: usize) -> Option<usize> {
- self[start..end].iter().position(separator)
- }
-
- fn rfind(&self, separator: &P, end: usize) -> Option<usize> {
- self[..end].iter().rposition(separator)
- }
-
- fn split_once(self, index: usize) -> (Self, Self) {
- let (left, right) = self.split_at_mut(index);
- (left, &mut right[1..]) // skip the separator
- }
-
- fn fold_splits<F>(self, separator: &P, folder: F, skip_last: bool) -> F
- where
- F: Folder<Self>,
- Self: Send,
- {
- let mut split = self.split_mut(separator);
- if skip_last {
- split.next_back();
- }
- folder.consume_iter(split)
- }
-}