/* 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 }