| use core::array; |
| use core::borrow::BorrowMut; |
| use std::fmt; |
| use std::iter::FusedIterator; |
| |
| use super::lazy_buffer::LazyBuffer; |
| use alloc::vec::Vec; |
| |
| use crate::adaptors::checked_binomial; |
| |
| /// Iterator for `Vec` valued combinations returned by [`.combinations()`](crate::Itertools::combinations) |
| pub type Combinations<I> = CombinationsGeneric<I, Vec<usize>>; |
| /// Iterator for const generic combinations returned by [`.array_combinations()`](crate::Itertools::array_combinations) |
| pub type ArrayCombinations<I, const K: usize> = CombinationsGeneric<I, [usize; K]>; |
| |
| /// Create a new `Combinations` from a clonable iterator. |
| pub fn combinations<I: Iterator>(iter: I, k: usize) -> Combinations<I> |
| where |
| I::Item: Clone, |
| { |
| Combinations::new(iter, (0..k).collect()) |
| } |
| |
| /// Create a new `ArrayCombinations` from a clonable iterator. |
| pub fn array_combinations<I: Iterator, const K: usize>(iter: I) -> ArrayCombinations<I, K> |
| where |
| I::Item: Clone, |
| { |
| ArrayCombinations::new(iter, array::from_fn(|i| i)) |
| } |
| |
| /// An iterator to iterate through all the `k`-length combinations in an iterator. |
| /// |
| /// See [`.combinations()`](crate::Itertools::combinations) and [`.array_combinations()`](crate::Itertools::array_combinations) for more information. |
| #[must_use = "iterator adaptors are lazy and do nothing unless consumed"] |
| pub struct CombinationsGeneric<I: Iterator, Idx> { |
| indices: Idx, |
| pool: LazyBuffer<I>, |
| first: bool, |
| } |
| |
| /// A type holding indices of elements in a pool or buffer of items from an inner iterator |
| /// and used to pick out different combinations in a generic way. |
| pub trait PoolIndex<T>: BorrowMut<[usize]> { |
| type Item; |
| |
| fn extract_item<I: Iterator<Item = T>>(&self, pool: &LazyBuffer<I>) -> Self::Item |
| where |
| T: Clone; |
| |
| fn len(&self) -> usize { |
| self.borrow().len() |
| } |
| } |
| |
| impl<T> PoolIndex<T> for Vec<usize> { |
| type Item = Vec<T>; |
| |
| fn extract_item<I: Iterator<Item = T>>(&self, pool: &LazyBuffer<I>) -> Vec<T> |
| where |
| T: Clone, |
| { |
| pool.get_at(self) |
| } |
| } |
| |
| impl<T, const K: usize> PoolIndex<T> for [usize; K] { |
| type Item = [T; K]; |
| |
| fn extract_item<I: Iterator<Item = T>>(&self, pool: &LazyBuffer<I>) -> [T; K] |
| where |
| T: Clone, |
| { |
| pool.get_array(*self) |
| } |
| } |
| |
| impl<I, Idx> Clone for CombinationsGeneric<I, Idx> |
| where |
| I: Iterator + Clone, |
| I::Item: Clone, |
| Idx: Clone, |
| { |
| clone_fields!(indices, pool, first); |
| } |
| |
| impl<I, Idx> fmt::Debug for CombinationsGeneric<I, Idx> |
| where |
| I: Iterator + fmt::Debug, |
| I::Item: fmt::Debug, |
| Idx: fmt::Debug, |
| { |
| debug_fmt_fields!(Combinations, indices, pool, first); |
| } |
| |
| impl<I: Iterator, Idx: PoolIndex<I::Item>> CombinationsGeneric<I, Idx> { |
| /// Constructor with arguments the inner iterator and the initial state for the indices. |
| fn new(iter: I, indices: Idx) -> Self { |
| Self { |
| indices, |
| pool: LazyBuffer::new(iter), |
| first: true, |
| } |
| } |
| |
| /// Returns the length of a combination produced by this iterator. |
| #[inline] |
| pub fn k(&self) -> usize { |
| self.indices.len() |
| } |
| |
| /// Returns the (current) length of the pool from which combination elements are |
| /// selected. This value can change between invocations of [`next`](Combinations::next). |
| #[inline] |
| pub fn n(&self) -> usize { |
| self.pool.len() |
| } |
| |
| /// Returns a reference to the source pool. |
| #[inline] |
| pub(crate) fn src(&self) -> &LazyBuffer<I> { |
| &self.pool |
| } |
| |
| /// Return the length of the inner iterator and the count of remaining combinations. |
| pub(crate) fn n_and_count(self) -> (usize, usize) { |
| let Self { |
| indices, |
| pool, |
| first, |
| } = self; |
| let n = pool.count(); |
| (n, remaining_for(n, first, indices.borrow()).unwrap()) |
| } |
| |
| /// Initialises the iterator by filling a buffer with elements from the |
| /// iterator. Returns true if there are no combinations, false otherwise. |
| fn init(&mut self) -> bool { |
| self.pool.prefill(self.k()); |
| let done = self.k() > self.n(); |
| if !done { |
| self.first = false; |
| } |
| |
| done |
| } |
| |
| /// Increments indices representing the combination to advance to the next |
| /// (in lexicographic order by increasing sequence) combination. For example |
| /// if we have n=4 & k=2 then `[0, 1] -> [0, 2] -> [0, 3] -> [1, 2] -> ...` |
| /// |
| /// Returns true if we've run out of combinations, false otherwise. |
| fn increment_indices(&mut self) -> bool { |
| // Borrow once instead of noise each time it's indexed |
| let indices = self.indices.borrow_mut(); |
| |
| if indices.is_empty() { |
| return true; // Done |
| } |
| // Scan from the end, looking for an index to increment |
| let mut i: usize = indices.len() - 1; |
| |
| // Check if we need to consume more from the iterator |
| if indices[i] == self.pool.len() - 1 { |
| self.pool.get_next(); // may change pool size |
| } |
| |
| while indices[i] == i + self.pool.len() - indices.len() { |
| if i > 0 { |
| i -= 1; |
| } else { |
| // Reached the last combination |
| return true; |
| } |
| } |
| |
| // Increment index, and reset the ones to its right |
| indices[i] += 1; |
| for j in i + 1..indices.len() { |
| indices[j] = indices[j - 1] + 1; |
| } |
| // If we've made it this far, we haven't run out of combos |
| false |
| } |
| |
| /// Returns the n-th item or the number of successful steps. |
| pub(crate) fn try_nth(&mut self, n: usize) -> Result<<Self as Iterator>::Item, usize> |
| where |
| I: Iterator, |
| I::Item: Clone, |
| { |
| let done = if self.first { |
| self.init() |
| } else { |
| self.increment_indices() |
| }; |
| if done { |
| return Err(0); |
| } |
| for i in 0..n { |
| if self.increment_indices() { |
| return Err(i + 1); |
| } |
| } |
| Ok(self.indices.extract_item(&self.pool)) |
| } |
| } |
| |
| impl<I, Idx> Iterator for CombinationsGeneric<I, Idx> |
| where |
| I: Iterator, |
| I::Item: Clone, |
| Idx: PoolIndex<I::Item>, |
| { |
| type Item = Idx::Item; |
| fn next(&mut self) -> Option<Self::Item> { |
| let done = if self.first { |
| self.init() |
| } else { |
| self.increment_indices() |
| }; |
| |
| if done { |
| return None; |
| } |
| |
| Some(self.indices.extract_item(&self.pool)) |
| } |
| |
| fn nth(&mut self, n: usize) -> Option<Self::Item> { |
| self.try_nth(n).ok() |
| } |
| |
| fn size_hint(&self) -> (usize, Option<usize>) { |
| let (mut low, mut upp) = self.pool.size_hint(); |
| low = remaining_for(low, self.first, self.indices.borrow()).unwrap_or(usize::MAX); |
| upp = upp.and_then(|upp| remaining_for(upp, self.first, self.indices.borrow())); |
| (low, upp) |
| } |
| |
| #[inline] |
| fn count(self) -> usize { |
| self.n_and_count().1 |
| } |
| } |
| |
| impl<I, Idx> FusedIterator for CombinationsGeneric<I, Idx> |
| where |
| I: Iterator, |
| I::Item: Clone, |
| Idx: PoolIndex<I::Item>, |
| { |
| } |
| |
| impl<I: Iterator> Combinations<I> { |
| /// Resets this `Combinations` back to an initial state for combinations of length |
| /// `k` over the same pool data source. If `k` is larger than the current length |
| /// of the data pool an attempt is made to prefill the pool so that it holds `k` |
| /// elements. |
| pub(crate) fn reset(&mut self, k: usize) { |
| self.first = true; |
| |
| if k < self.indices.len() { |
| self.indices.truncate(k); |
| for i in 0..k { |
| self.indices[i] = i; |
| } |
| } else { |
| for i in 0..self.indices.len() { |
| self.indices[i] = i; |
| } |
| self.indices.extend(self.indices.len()..k); |
| self.pool.prefill(k); |
| } |
| } |
| } |
| |
| /// For a given size `n`, return the count of remaining combinations or None if it would overflow. |
| fn remaining_for(n: usize, first: bool, indices: &[usize]) -> Option<usize> { |
| let k = indices.len(); |
| if n < k { |
| Some(0) |
| } else if first { |
| checked_binomial(n, k) |
| } else { |
| // https://en.wikipedia.org/wiki/Combinatorial_number_system |
| // http://www.site.uottawa.ca/~lucia/courses/5165-09/GenCombObj.pdf |
| |
| // The combinations generated after the current one can be counted by counting as follows: |
| // - The subsequent combinations that differ in indices[0]: |
| // If subsequent combinations differ in indices[0], then their value for indices[0] |
| // must be at least 1 greater than the current indices[0]. |
| // As indices is strictly monotonically sorted, this means we can effectively choose k values |
| // from (n - 1 - indices[0]), leading to binomial(n - 1 - indices[0], k) possibilities. |
| // - The subsequent combinations with same indices[0], but differing indices[1]: |
| // Here we can choose k - 1 values from (n - 1 - indices[1]) values, |
| // leading to binomial(n - 1 - indices[1], k - 1) possibilities. |
| // - (...) |
| // - The subsequent combinations with same indices[0..=i], but differing indices[i]: |
| // Here we can choose k - i values from (n - 1 - indices[i]) values: binomial(n - 1 - indices[i], k - i). |
| // Since subsequent combinations can in any index, we must sum up the aforementioned binomial coefficients. |
| |
| // Below, `n0` resembles indices[i]. |
| indices.iter().enumerate().try_fold(0usize, |sum, (i, n0)| { |
| sum.checked_add(checked_binomial(n - 1 - *n0, k - i)?) |
| }) |
| } |
| } |