Heap Sort

Posted 2021-02-20 johnnyzhao

package _Sort.Algorithm

/**
 * https://www.geeksforgeeks.org/heap-sort/
 * https://www.cnblogs.com/chengxiao/p/6129630.html
 *
 * Heap Sort is an in-place algorithm. the typical implementation is not stable,but can be made stable.
 * Time complexity of heapify is O(Logn), Time complexity of Create and BuildHelp is O(N) and overall
 * time complexity of HeapSort is O(nLogn).
 * Heap Sort is a comparision base sorting technique base on BinaryHeap data structure.
 *
 * ==Why array based representation for Binary Heap?
 * Since Binary Heap is a Complete Binary Tree, it can easy represented as array and array based representation is
 * space different.
 * if the parent node is sorted at index I,the left child can be calculated by 2*I+1, and the right child can be calculated
 * by 2*I+2 (assuming the indexing start at 0).
 *
 *  MaxHeap: arr[i]>=arr[i*2+1] && arr[i]>=arr[i*2+2]
    MinHeap: arr[i]<=arr[i*2+1] && arr[i]<=arr[i*2+2]
 *
 * ==Heap Sort algorithm for sorting in increasing order:
 * 1. Build a Max or Min head from input array.
 * 2. At this point, the largest item is sorted at the root of the heap. replace it with the last item of the
 * heap followed by reducing the size of heap by 1. finally, heapify the root of tree.
 * 3. repeat above steps while size of heap is greater than 1.
 *
 * ==How to build heap?
 * Heapify procedure can be applied to a node only if its children nodes are heapified. so the heapification must
 * be performed in the bottom up order.
 *
 * Lets understand with the help of an example:
 *
 * Input data: 4, 10, 3, 5, 1
      4(0)
     /     10(1)   3(2)
  /   5(3) 1(4)

The numbers in bracket represent the indices in the array representation of data.

Applying heapify procedure to index 1:
      4(0)
     /     10(1)   3(2)
  /   5(3)  1(4)

Applying heapify procedure to index 0:
      10(0)
      /      5(1) 3(2)
   /    4(3) 1(4)
The heapify procedure calls itself recursively to build heap in top down manner.
 * */
class HeapSort {

    fun sort(array:IntArray){
        val n = array.size
        //build heap, bottom to up
        for (i in n/2-1 downTo 0){
            heapify(array,n,i)
        }
        //one by one extract an element from heap
        for (i in n-1 downTo 1){
            //move current node to end
            val temp = array[0]
            array[0] = array[i]
            array[i] = temp
            //call max heapify on the reduced heap
            heapify(array,i,0)
        }
        printArray(array)
    }

    private fun printArray(array: IntArray) {
        for (item in array) {
            print("$item ,")
        }
    }

    /**
     *To heapify sub tree rooted with node i which is an index in array[].
     * n is size of heap.
     * */
    private fun heapify(array: IntArray, n:Int, i:Int){
        var largest  = i
        val left = 2*i+1
        val right = 2*i+2

        //if left child is largest than root
        if (left < n && array[left] > array[largest]){
            largest = left
        }

        //if right child is largest than root
        if (right < n && array[right] > array[largest]){
            largest = right
        }

        //if largest is not root
        if (largest != i ){
            val temp = array[i]
            array[i] = array[largest]
            array[largest] = temp
            //recursively heapify the affected sub-tree
            heapify(array,n,largest)
        }
    }
}