use alloc::vec::Vec; use std::fmt; use std::iter::FusedIterator; use super::lazy_buffer::LazyBuffer; use crate::adaptors::checked_binomial; /// An iterator to iterate through all the `n`-length combinations in an iterator, with replacement. /// /// See [`.combinations_with_replacement()`](crate::Itertools::combinations_with_replacement) /// for more information. #[derive(Clone)] #[must_use = "iterator adaptors are lazy and do nothing unless consumed"] pub struct CombinationsWithReplacement where I: Iterator, I::Item: Clone, { indices: Vec, pool: LazyBuffer, first: bool, } impl fmt::Debug for CombinationsWithReplacement where I: Iterator + fmt::Debug, I::Item: fmt::Debug + Clone, { debug_fmt_fields!(CombinationsWithReplacement, indices, pool, first); } impl CombinationsWithReplacement where I: Iterator, I::Item: Clone, { /// Map the current mask over the pool to get an output combination fn current(&self) -> Vec { self.indices.iter().map(|i| self.pool[*i].clone()).collect() } } /// Create a new `CombinationsWithReplacement` from a clonable iterator. pub fn combinations_with_replacement(iter: I, k: usize) -> CombinationsWithReplacement where I: Iterator, I::Item: Clone, { let indices: Vec = alloc::vec![0; k]; let pool: LazyBuffer = LazyBuffer::new(iter); CombinationsWithReplacement { indices, pool, first: true, } } impl Iterator for CombinationsWithReplacement where I: Iterator, I::Item: Clone, { type Item = Vec; fn next(&mut self) -> Option { // If this is the first iteration, return early if self.first { // In empty edge cases, stop iterating immediately return if !(self.indices.is_empty() || self.pool.get_next()) { None // Otherwise, yield the initial state } else { self.first = false; Some(self.current()) }; } // Check if we need to consume more from the iterator // This will run while we increment our first index digit self.pool.get_next(); // Work out where we need to update our indices let mut increment: Option<(usize, usize)> = None; for (i, indices_int) in self.indices.iter().enumerate().rev() { if *indices_int < self.pool.len() - 1 { increment = Some((i, indices_int + 1)); break; } } match increment { // If we can update the indices further Some((increment_from, increment_value)) => { // We need to update the rightmost non-max value // and all those to the right for indices_index in increment_from..self.indices.len() { self.indices[indices_index] = increment_value; } Some(self.current()) } // Otherwise, we're done None => None, } } fn size_hint(&self) -> (usize, Option) { let (mut low, mut upp) = self.pool.size_hint(); low = remaining_for(low, self.first, &self.indices).unwrap_or(usize::MAX); upp = upp.and_then(|upp| remaining_for(upp, self.first, &self.indices)); (low, upp) } fn count(self) -> usize { let Self { indices, pool, first, } = self; let n = pool.count(); remaining_for(n, first, &indices).unwrap() } } impl FusedIterator for CombinationsWithReplacement where I: Iterator, I::Item: Clone, { } /// For a given size `n`, return the count of remaining combinations with replacement or None if it would overflow. fn remaining_for(n: usize, first: bool, indices: &[usize]) -> Option { // With a "stars and bars" representation, choose k values with replacement from n values is // like choosing k out of k + n − 1 positions (hence binomial(k + n - 1, k) possibilities) // to place k stars and therefore n - 1 bars. // Example (n=4, k=6): ***|*||** represents [0,0,0,1,3,3]. let count = |n: usize, k: usize| { let positions = if n == 0 { k.saturating_sub(1) } else { (n - 1).checked_add(k)? }; checked_binomial(positions, k) }; let k = indices.len(); if first { count(n, k) } else { // The algorithm is similar to the one for combinations *without replacement*, // except we choose values *with replacement* and indices are *non-strictly* monotonically sorted. // 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 monotonically sorted, this means we can effectively choose k values with // replacement from (n - 1 - indices[0]), leading to count(n - 1 - indices[0], k) possibilities. // - The subsequent combinations with same indices[0], but differing indices[1]: // Here we can choose k - 1 values with replacement from (n - 1 - indices[1]) values, // leading to count(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 with replacement from (n - 1 - indices[i]) values: count(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(count(n - 1 - *n0, k - i)?) }) } }