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Diffstat (limited to 'vendor/rayon/src/slice/mod.rs')
| -rw-r--r-- | vendor/rayon/src/slice/mod.rs | 1041 |
1 files changed, 0 insertions, 1041 deletions
diff --git a/vendor/rayon/src/slice/mod.rs b/vendor/rayon/src/slice/mod.rs deleted file mode 100644 index dab56de..0000000 --- a/vendor/rayon/src/slice/mod.rs +++ /dev/null @@ -1,1041 +0,0 @@ -//! 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) - } -} |