/// Consumes a given iterator, returning the minimum elements in **ascending** order. pub(crate) fn k_smallest_general<I, F>(iter: I, k: usize, mut comparator: F) -> Vec<I::Item> where
I: Iterator,
F: FnMut(&I::Item, &I::Item) -> Ordering,
{ /// Sift the element currently at `origin` away from the root until it is properly ordered. /// /// This will leave **larger** elements closer to the root of the heap. fn sift_down<T, F>(heap: &mut [T], is_less_than: &mut F, mut origin: usize) where
F: FnMut(&T, &T) -> bool,
{ #[inline] fn children_of(n: usize) -> (usize, usize) {
(2 * n + 1, 2 * n + 2)
}
while origin < heap.len() { let (left_idx, right_idx) = children_of(origin); if left_idx >= heap.len() { return;
}
let replacement_idx = if right_idx < heap.len() && is_less_than(&heap[left_idx], &heap[right_idx]) {
right_idx
} else {
left_idx
};
// Rearrange the storage into a valid heap by reordering from the second-bottom-most layer up to the root. // Slightly faster than ordering on each insert, but only by a factor of lg(k). // The resulting heap has the **largest** item on top. for i in (0..=(storage.len() / 2)).rev() {
sift_down(&mut storage, &mut is_less_than, i);
}
iter.for_each(|val| {
debug_assert_eq!(storage.len(), k); if is_less_than(&val, &storage[0]) { // Treating this as an push-and-pop saves having to write a sift-up implementation. // https://en.wikipedia.org/wiki/Binary_heap#Insert_then_extract
storage[0] = val; // We retain the smallest items we've seen so far, but ordered largest first so we can drop the largest efficiently.
sift_down(&mut storage, &mut is_less_than, 0);
}
});
// Ultimately the items need to be in least-first, strict order, but the heap is currently largest-first. // To achieve this, repeatedly, // 1) "pop" the largest item off the heap into the tail slot of the underlying storage, // 2) shrink the logical size of the heap by 1, // 3) restore the heap property over the remaining items. letmut heap = &mut storage[..]; while heap.len() > 1 { let last_idx = heap.len() - 1;
heap.swap(0, last_idx); // Sifting over a truncated slice means that the sifting will not disturb already popped elements.
heap = &mut heap[..last_idx];
sift_down(heap, &mut is_less_than, 0);
}
storage
}
pub(crate) fn k_smallest_relaxed_general<I, F>(iter: I, k: usize, mut comparator: F) -> Vec<I::Item> where
I: Iterator,
F: FnMut(&I::Item, &I::Item) -> Ordering,
{ if k == 0 {
iter.last(); return Vec::new();
}
letmut iter = iter.fuse(); letmut buf = iter.by_ref().take(2 * k).collect::<Vec<_>>();
if buf.len() < k {
buf.sort_unstable_by(&mut comparator); return buf;
}
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