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use super::heap::Heap;
use crate::{positions::none::HeapPositionsNone, PriorityQueue};
/// Type alias for `DaryHeap<N, K, 2>`; see [`DaryHeap`] for details.
pub type BinaryHeap<N, K> = DaryHeap<N, K, 2>;
/// Type alias for `DaryHeap<N, K, 3>`; see [`DaryHeap`] for details.
pub type TernaryHeap<N, K> = DaryHeap<N, K, 3>;
/// Type alias for `DaryHeap<N, K, 4>`; see [`DaryHeap`] for details.
pub type QuarternaryHeap<N, K> = DaryHeap<N, K, 4>;
/// A d-ary heap which implements `PriorityQueue`, but not `PriorityQueueDecKey`.
///
/// *Its interface is similar to `std::collections:BinaryHeap; however, provides a generalization by allowing different d values.
/// `DaryHeapMap` and DaryHeapOfIndices` on the other hand, provides the additonal functionality of `PriorityQueueDecKey`
/// which are crucial for providing better space complexity in algorithms such as the Dijkstra's shortest path algorithm.*
///
/// # Examples
///
/// ## Heap as a `PriorityQueue`
///
/// Usage of d-ary heap as a basic priority queue.
///
/// ```
/// use orx_priority_queue::*;
///
/// fn test_priority_queue<P>(mut pq: P)
/// where
/// P: PriorityQueue<usize, f64>
/// {
/// pq.clear();
///
/// pq.push(0, 42.0);
/// assert_eq!(Some(&(0, 42.0)), pq.peek());
///
/// pq.push(1, 7.0);
/// assert_eq!(Some(&(1, 7.0)), pq.peek());
///
/// let popped = pq.pop();
/// assert_eq!(Some((1, 7.0)), popped);
///
/// let popped = pq.pop();
/// assert_eq!(Some((0, 42.0)), popped);
///
/// assert!(pq.is_empty());
/// }
///
/// // basic d-heap without any means to located existing nodes
/// test_priority_queue(DaryHeap::<_, _, 4>::default());
/// test_priority_queue(DaryHeap::<_, _, 3>::with_capacity(16));
/// // using type aliases to simplify signatures
/// test_priority_queue(BinaryHeap::default());
/// test_priority_queue(BinaryHeap::with_capacity(16));
/// test_priority_queue(TernaryHeap::default());
/// test_priority_queue(TernaryHeap::with_capacity(16));
/// test_priority_queue(QuarternaryHeap::default());
/// test_priority_queue(QuarternaryHeap::with_capacity(16));
/// ```
#[derive(Clone, Debug)]
pub struct DaryHeap<N, K, const D: usize = 2>
where
N: Clone,
K: PartialOrd + Clone,
{
heap: Heap<N, K, HeapPositionsNone, D>,
}
impl<N, K, const D: usize> Default for DaryHeap<N, K, D>
where
N: Clone,
K: PartialOrd + Clone,
{
fn default() -> Self {
Self {
heap: Heap::new(None, HeapPositionsNone),
}
}
}
impl<N, K, const D: usize> DaryHeap<N, K, D>
where
N: Clone,
K: PartialOrd + Clone,
{
/// Creates a new d-ary heap with the given initial `capacity` on the number of nodes to simultaneously exist on the heap.
///
/// # Examples
///
/// ```
/// use orx_priority_queue::*;
///
/// // create a queue with an expected space complexity of 4
/// let mut queue = DaryHeap::<_, _, 4>::with_capacity(4);
/// queue.push('a', 4);
/// assert_eq!(Some('a'), queue.pop_node());
/// ```
pub fn with_capacity(capacity: usize) -> Self {
Self {
heap: Heap::new(Some(capacity), HeapPositionsNone),
}
}
/// Returns the 'd' of the d-ary heap.
/// In other words, it represents the maximum number of children that each node on the heap can have.
pub const fn d() -> usize {
D
}
}
impl<N, K, const D: usize> PriorityQueue<N, K> for DaryHeap<N, K, D>
where
N: Clone,
K: PartialOrd + Clone,
{
#[inline(always)]
fn len(&self) -> usize {
self.heap.len()
}
#[inline(always)]
fn capacity(&self) -> usize {
self.heap.capacity()
}
fn as_slice(&self) -> &[(N, K)] {
self.heap.as_slice()
}
fn peek(&self) -> Option<&(N, K)> {
self.heap.peek()
}
fn clear(&mut self) {
self.heap.clear()
}
#[inline(always)]
fn pop(&mut self) -> Option<(N, K)> {
self.heap.pop()
}
#[inline(always)]
fn pop_node(&mut self) -> Option<N> {
self.heap.pop_node()
}
#[inline(always)]
fn pop_key(&mut self) -> Option<K> {
self.heap.pop_key()
}
#[inline(always)]
fn push(&mut self, node: N, key: K) {
self.heap.push(node, key)
}
#[inline(always)]
fn push_then_pop(&mut self, node: N, key: K) -> (N, K) {
self.heap.push_then_pop(node, key)
}
#[cfg(test)]
fn is_valid(&self) -> bool {
self.heap.is_valid()
}
}