标签:tree sorted api i+1 number help rac orm end
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) } } }
标签:tree sorted api i+1 number help rac orm end
原文地址:https://www.cnblogs.com/johnnyzhao/p/12813279.html