| 1 | use std::fmt; | 
| 2 | use std::iter::FusedIterator; | 
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| 3 |  | 
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| 4 | use super::lazy_buffer::LazyBuffer; | 
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| 5 | use alloc::vec::Vec; | 
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| 6 |  | 
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| 7 | use crate::adaptors::checked_binomial; | 
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| 8 |  | 
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| 9 | /// An iterator to iterate through all the `k`-length combinations in an iterator. | 
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| 10 | /// | 
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| 11 | /// See [`.combinations()`](crate::Itertools::combinations) for more information. | 
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| 12 | #[ must_use= "iterator adaptors are lazy and do nothing unless consumed"] | 
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| 13 | pub struct Combinations<I: Iterator> { | 
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| 14 | indices: Vec<usize>, | 
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| 15 | pool: LazyBuffer<I>, | 
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| 16 | first: bool, | 
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| 17 | } | 
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| 18 |  | 
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| 19 | impl<I> Clone for Combinations<I> | 
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| 20 | where | 
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| 21 | I: Clone + Iterator, | 
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| 22 | I::Item: Clone, | 
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| 23 | { | 
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| 24 | clone_fields!(indices, pool, first); | 
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| 25 | } | 
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| 26 |  | 
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| 27 | impl<I> fmt::Debug for Combinations<I> | 
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| 28 | where | 
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| 29 | I: Iterator + fmt::Debug, | 
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| 30 | I::Item: fmt::Debug, | 
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| 31 | { | 
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| 32 | debug_fmt_fields!(Combinations, indices, pool, first); | 
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| 33 | } | 
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| 34 |  | 
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| 35 | /// Create a new `Combinations` from a clonable iterator. | 
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| 36 | pub fn combinations<I>(iter: I, k: usize) -> Combinations<I> | 
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| 37 | where | 
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| 38 | I: Iterator, | 
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| 39 | { | 
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| 40 | Combinations { | 
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| 41 | indices: (0..k).collect(), | 
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| 42 | pool: LazyBuffer::new(it:iter), | 
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| 43 | first: true, | 
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| 44 | } | 
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| 45 | } | 
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| 46 |  | 
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| 47 | impl<I: Iterator> Combinations<I> { | 
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| 48 | /// Returns the length of a combination produced by this iterator. | 
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| 49 | #[ inline] | 
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| 50 | pub fn k(&self) -> usize { | 
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| 51 | self.indices.len() | 
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| 52 | } | 
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| 53 |  | 
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| 54 | /// Returns the (current) length of the pool from which combination elements are | 
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| 55 | /// selected. This value can change between invocations of [`next`](Combinations::next). | 
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| 56 | #[ inline] | 
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| 57 | pub fn n(&self) -> usize { | 
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| 58 | self.pool.len() | 
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| 59 | } | 
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| 60 |  | 
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| 61 | /// Returns a reference to the source pool. | 
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| 62 | #[ inline] | 
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| 63 | pub(crate) fn src(&self) -> &LazyBuffer<I> { | 
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| 64 | &self.pool | 
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| 65 | } | 
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| 66 |  | 
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| 67 | /// Resets this `Combinations` back to an initial state for combinations of length | 
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| 68 | /// `k` over the same pool data source. If `k` is larger than the current length | 
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| 69 | /// of the data pool an attempt is made to prefill the pool so that it holds `k` | 
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| 70 | /// elements. | 
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| 71 | pub(crate) fn reset(&mut self, k: usize) { | 
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| 72 | self.first = true; | 
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| 73 |  | 
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| 74 | if k < self.indices.len() { | 
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| 75 | self.indices.truncate(k); | 
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| 76 | for i in 0..k { | 
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| 77 | self.indices[i] = i; | 
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| 78 | } | 
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| 79 | } else { | 
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| 80 | for i in 0..self.indices.len() { | 
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| 81 | self.indices[i] = i; | 
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| 82 | } | 
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| 83 | self.indices.extend(self.indices.len()..k); | 
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| 84 | self.pool.prefill(k); | 
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| 85 | } | 
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| 86 | } | 
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| 87 |  | 
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| 88 | pub(crate) fn n_and_count(self) -> (usize, usize) { | 
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| 89 | let Self { | 
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| 90 | indices, | 
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| 91 | pool, | 
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| 92 | first, | 
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| 93 | } = self; | 
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| 94 | let n = pool.count(); | 
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| 95 | (n, remaining_for(n, first, &indices).unwrap()) | 
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| 96 | } | 
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| 97 | } | 
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| 98 |  | 
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| 99 | impl<I> Iterator for Combinations<I> | 
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| 100 | where | 
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| 101 | I: Iterator, | 
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| 102 | I::Item: Clone, | 
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| 103 | { | 
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| 104 | type Item = Vec<I::Item>; | 
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| 105 | fn next(&mut self) -> Option<Self::Item> { | 
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| 106 | if self.first { | 
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| 107 | self.pool.prefill(self.k()); | 
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| 108 | if self.k() > self.n() { | 
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| 109 | return None; | 
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| 110 | } | 
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| 111 | self.first = false; | 
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| 112 | } else if self.indices.is_empty() { | 
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| 113 | return None; | 
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| 114 | } else { | 
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| 115 | // Scan from the end, looking for an index to increment | 
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| 116 | let mut i: usize = self.indices.len() - 1; | 
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| 117 |  | 
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| 118 | // Check if we need to consume more from the iterator | 
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| 119 | if self.indices[i] == self.pool.len() - 1 { | 
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| 120 | self.pool.get_next(); // may change pool size | 
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| 121 | } | 
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| 122 |  | 
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| 123 | while self.indices[i] == i + self.pool.len() - self.indices.len() { | 
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| 124 | if i > 0 { | 
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| 125 | i -= 1; | 
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| 126 | } else { | 
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| 127 | // Reached the last combination | 
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| 128 | return None; | 
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| 129 | } | 
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| 130 | } | 
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| 131 |  | 
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| 132 | // Increment index, and reset the ones to its right | 
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| 133 | self.indices[i] += 1; | 
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| 134 | for j in i + 1..self.indices.len() { | 
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| 135 | self.indices[j] = self.indices[j - 1] + 1; | 
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| 136 | } | 
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| 137 | } | 
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| 138 |  | 
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| 139 | // Create result vector based on the indices | 
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| 140 | Some(self.indices.iter().map(|i| self.pool[*i].clone()).collect()) | 
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| 141 | } | 
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| 142 |  | 
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| 143 | fn size_hint(&self) -> (usize, Option<usize>) { | 
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| 144 | let (mut low, mut upp) = self.pool.size_hint(); | 
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| 145 | low = remaining_for(low, self.first, &self.indices).unwrap_or(usize::MAX); | 
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| 146 | upp = upp.and_then(|upp| remaining_for(upp, self.first, &self.indices)); | 
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| 147 | (low, upp) | 
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| 148 | } | 
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| 149 |  | 
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| 150 | #[ inline] | 
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| 151 | fn count(self) -> usize { | 
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| 152 | self.n_and_count().1 | 
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| 153 | } | 
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| 154 | } | 
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| 155 |  | 
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| 156 | impl<I> FusedIterator for Combinations<I> | 
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| 157 | where | 
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| 158 | I: Iterator, | 
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| 159 | I::Item: Clone, | 
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| 160 | { | 
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| 161 | } | 
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| 162 |  | 
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| 163 | /// For a given size `n`, return the count of remaining combinations or None if it would overflow. | 
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| 164 | fn remaining_for(n: usize, first: bool, indices: &[usize]) -> Option<usize> { | 
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| 165 | let k = indices.len(); | 
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| 166 | if n < k { | 
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| 167 | Some(0) | 
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| 168 | } else if first { | 
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| 169 | checked_binomial(n, k) | 
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| 170 | } else { | 
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| 171 | // https://en.wikipedia.org/wiki/Combinatorial_number_system | 
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| 172 | // http://www.site.uottawa.ca/~lucia/courses/5165-09/GenCombObj.pdf | 
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| 173 |  | 
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| 174 | // The combinations generated after the current one can be counted by counting as follows: | 
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| 175 | // - The subsequent combinations that differ in indices[0]: | 
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| 176 | //   If subsequent combinations differ in indices[0], then their value for indices[0] | 
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| 177 | //   must be at least 1 greater than the current indices[0]. | 
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| 178 | //   As indices is strictly monotonically sorted, this means we can effectively choose k values | 
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| 179 | //   from (n - 1 - indices[0]), leading to binomial(n - 1 - indices[0], k) possibilities. | 
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| 180 | // - The subsequent combinations with same indices[0], but differing indices[1]: | 
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| 181 | //   Here we can choose k - 1 values from (n - 1 - indices[1]) values, | 
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| 182 | //   leading to binomial(n - 1 - indices[1], k - 1) possibilities. | 
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| 183 | // - (...) | 
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| 184 | // - The subsequent combinations with same indices[0..=i], but differing indices[i]: | 
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| 185 | //   Here we can choose k - i values from (n - 1 - indices[i]) values: binomial(n - 1 - indices[i], k - i). | 
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| 186 | //   Since subsequent combinations can in any index, we must sum up the aforementioned binomial coefficients. | 
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| 187 |  | 
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| 188 | // Below, `n0` resembles indices[i]. | 
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| 189 | indices.iter().enumerate().try_fold(0usize, |sum, (i, n0)| { | 
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| 190 | sum.checked_add(checked_binomial(n - 1 - *n0, k - i)?) | 
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| 191 | }) | 
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| 192 | } | 
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| 193 | } | 
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| 194 |  | 
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