/* Minimum Priority Queue
* It is a part of heap data structure
* A heap is a specific tree based data structure
* in which all the nodes of tree are in a specific order.
* that is the children are arranged in some
* respect of their parents, can either be greater
* or less than the parent. This makes it a min priority queue
* or max priority queue.
*/
// Functions: insert, delete, peek, isEmpty, print, heapSort, sink
class MinPriorityQueue {
// calls the constructor and initializes the capacity
constructor(c) {
this.heap = []
this.capacity = c
this.size = 0
}
// inserts the key at the end and rearranges it
// so that the binary heap is in appropriate order
insert(key) {
if (this.isFull()) return
this.heap[this.size + 1] = key
let k = this.size + 1
while (k > 1) {
if (this.heap[k] < this.heap[Math.floor(k / 2)]) {
const temp = this.heap[k]
this.heap[k] = this.heap[Math.floor(k / 2)]
this.heap[Math.floor(k / 2)] = temp
}
k = Math.floor(k / 2)
}
this.size++
}
// returns the highest priority value
peek() {
return this.heap[1]
}
// returns boolean value whether the heap is empty or not
isEmpty() {
return this.size === 0
}
// returns boolean value whether the heap is full or not
isFull() {
return this.size === this.capacity
}
// prints the heap
print(output = (value) => console.log(value)) {
output(this.heap.slice(1))
}
// heap reverse can be done by performing swapping the first
// element with the last, removing the last element to
// new array and calling sink function.
heapReverse() {
const heapSort = []
while (this.size > 0) {
// swap first element with last element
;[this.heap[1], this.heap[this.size]] = [
this.heap[this.size],
this.heap[1]
]
heapSort.push(this.heap.pop())
this.size--
this.sink()
}
// first value from heap it's empty to respect
// structure with 1 as index of the first element
this.heap = [undefined, ...heapSort.reverse()]
this.size = heapSort.length
}
// this function reorders the heap after every delete function
sink() {
let k = 1
while (2 * k <= this.size || 2 * k + 1 <= this.size) {
let minIndex
if (this.heap[2 * k] >= this.heap[k]) {
if (2 * k + 1 <= this.size && this.heap[2 * k + 1] >= this.heap[k]) {
break
} else if (2 * k + 1 > this.size) {
break
}
}
if (2 * k + 1 > this.size) {
minIndex = this.heap[2 * k] < this.heap[k] ? 2 * k : k
} else {
if (
this.heap[k] > this.heap[2 * k] ||
this.heap[k] > this.heap[2 * k + 1]
) {
minIndex = this.heap[2 * k] < this.heap[2 * k + 1] ? 2 * k : 2 * k + 1
} else {
minIndex = k
}
}
const temp = this.heap[k]
this.heap[k] = this.heap[minIndex]
this.heap[minIndex] = temp
k = minIndex
}
}
// deletes the highest priority value from the heap. The last
// element goes to ahead to first position and reorder heap
delete() {
// checks empty and one element array conditions
if (this.isEmpty()) return
if (this.size === 1) {
this.size--
return this.heap.pop()
}
const min = this.heap[1]
this.heap[1] = this.heap.pop()
this.size--
this.sink()
return min
}
}
export { MinPriorityQueue }