两个有序数组间相加和的Top k问题

本文主要是介绍两个有序数组间相加和的Top k问题，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

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import java.util.*;
//两个有序数组间相加和的Top k问题
public class FindArrTopK{//堆节点的定义public static class HeapNode{public int row;public int col;public int value;public HeapNode(int row,int col,int value){this.row=row;this.col=col;this.value=value;}}//获得top k问题public static int[] topKSum(int[] a1, int[] a2, int topK) {if (a1 == null || a2 == null || topK < 1) {return null;}topK = Math.min(topK, a1.length * a2.length);HeapNode[] heap = new HeapNode[topK + 1];int heapSize = 0;int headR = a1.length - 1;int headC = a2.length - 1;int uR = -1;int uC = -1;int lR = -1;int lC = -1;heapInsert(heap, heapSize++, headR, headC, a1[headR] + a2[headC]);HashSet<String> positionSet = new HashSet<String>();int[] res = new int[topK];int resIndex = 0;while (resIndex != topK) {HeapNode head = popHead(heap, heapSize--);res[resIndex++] = head.value;headR = head.row;headC = head.col;uR = headR - 1;uC = headC;if (headR != 0 && !isContains(uR, uC, positionSet)) {heapInsert(heap, heapSize++, uR, uC, a1[uR] + a2[uC]);addPositionToSet(uR, uC, positionSet);}lR = headR;lC = headC - 1;if (headC != 0 && !isContains(lR, lC, positionSet)) {heapInsert(heap, heapSize++, lR, lC, a1[lR] + a2[lC]);addPositionToSet(lR, lC, positionSet);}}return res;}public static HeapNode popHead(HeapNode[] heap, int heapSize) {HeapNode res = heap[0];swap(heap, 0, heapSize - 1);heap[--heapSize] = null;heapify(heap, 0, heapSize);return res;}public static void heapify(HeapNode[] heap, int index, int heapSize) {int left = index * 2 + 1;int right = index * 2 + 2;int largest = index;while (left < heapSize) {if (heap[left].value > heap[index].value) {largest = left;}if (right < heapSize && heap[right].value > heap[largest].value) {largest = right;}if (largest != index) {swap(heap, largest, index);} else {break;}index = largest;left = index * 2 + 1;right = index * 2 + 2;}}public static void heapInsert(HeapNode[] heap, int index, int row, int col,int value) {heap[index] = new HeapNode(row, col, value);int parent = (index - 1) / 2;while (index != 0) {if (heap[index].value > heap[parent].value) {swap(heap, parent, index);index = parent;parent = (index - 1) / 2;} else {break;}}}public static void swap(HeapNode[] heap, int index1, int index2) {HeapNode tmp = heap[index1];heap[index1] = heap[index2];heap[index2] = tmp;}public static boolean isContains(int row, int col, HashSet<String> set) {return set.contains(String.valueOf(row + "_" + col));}public static void addPositionToSet(int row, int col, HashSet<String> set) {set.add(String.valueOf(row + "_" + col));}// For test, this method is inefficient but absolutely rightpublic static int[] topKSumTest(int[] arr1, int[] arr2, int topK) {int[] all = new int[arr1.length * arr2.length];int index = 0;for (int i = 0; i != arr1.length; i++) {for (int j = 0; j != arr2.length; j++) {all[index++] = arr1[i] + arr2[j];}}Arrays.sort(all);int[] res = new int[Math.min(topK, all.length)];index = all.length - 1;for (int i = 0; i != res.length; i++) {res[i] = all[index--];}return res;}public static int[] generateRandomSortArray(int len) {int[] res = new int[len];for (int i = 0; i != res.length; i++) {res[i] = (int) (Math.random() * 50000) + 1;}Arrays.sort(res);return res;}public static boolean isEqual(int[] arr1, int[] arr2) {if (arr1 == null || arr2 == null || arr1.length != arr2.length) {return false;}for (int i = 0; i != arr1.length; i++) {if (arr1[i] != arr2[i]) {return false;}}return true;}//打印数组public static void printArray(int[] arr) {for (int i = 0; i != arr.length; i++) {System.out.print(arr[i] + " ");}System.out.println();}public static void main(String[]args){//System.out.println("Hello");int[]arr1={1,2,3,4,5};int[]arr2={3,5,7,9,11};int k=4;int[]res = topKSum(arr1,arr2,k);printArray(res);}
}