TopK问题——求数组中第K小的数

xiaoxiao2021-02-28  102

public class Problem_01_FindMinKNums { // O(N*logK) public static int[] getMinKNumsByHeap(int[] arr, int k) { if (k < 1 || k > arr.length) { return arr; } int[] kHeap = new int[k]; for (int i = 0; i != k; i++) { heapInsert(kHeap, arr[i], i); } for (int i = k; i != arr.length; i++) { if (arr[i] < kHeap[0]) { kHeap[0] = arr[i]; heapify(kHeap, 0, k); } } return kHeap; } public static void heapInsert(int[] arr, int value, int index) { arr[index] = value; while (index != 0) { int parent = (index - 1) / 2; if (arr[parent] < arr[index]) { swap(arr, parent, index); index = parent; } else { break; } } } public static void heapify(int[] arr, int index, int heapSize) { int left = index * 2 + 1; int right = index * 2 + 2; int largest = index; while (left < heapSize) { if (arr[left] > arr[index]) { largest = left; } if (right < heapSize && arr[right] > arr[largest]) { largest = right; } if (largest != index) { swap(arr, largest, index); } else { break; } index = largest; left = index * 2 + 1; right = index * 2 + 2; } } // O(N) public static int[] getMinKNumsByBFPRT(int[] arr, int k) { if (k < 1 || k > arr.length) { return arr; } int minKth = getMinKthByBFPRT(arr, k); int[] res = new int[k]; int index = 0; for (int i = 0; i != arr.length; i++) { if (arr[i] < minKth) { res[index++] = arr[i]; } } for (; index != res.length; index++) { res[index] = minKth; } return res; } public static int getMinKthByBFPRT(int[] arr, int K) { int[] copyArr = copyArray(arr); return select(copyArr, 0, copyArr.length - 1, K - 1); } public static int[] copyArray(int[] arr) { int[] res = new int[arr.length]; for (int i = 0; i != res.length; i++) { res[i] = arr[i]; } return res; } public static int select(int[] arr, int begin, int end, int i) { if (begin == end) { return arr[begin]; } int pivot = medianOfMedians(arr, begin, end); //找中位数组的中位数 int[] pivotRange = partition(arr, begin, end, pivot); //为什么返回数组,因为要找等于的范围,因此有两个下标 if (i >= pivotRange[0] && i <= pivotRange[1]) { //如果命中,则直接返回 return arr[i]; } else if (i < pivotRange[0]) { //没命中,左边递归或右边递归 return select(arr, begin, pivotRange[0] - 1, i); } else { return select(arr, pivotRange[1] + 1, end, i); } } public static int medianOfMedians(int[] arr, int begin, int end) { int num = end - begin + 1; int offset = num % 5 == 0 ? 0 : 1; //不满5个数单独成一组 int[] mArr = new int[num / 5 + offset]; for (int i = 0; i < mArr.length; i++) { int beginI = begin + i * 5; int endI = beginI + 4; mArr[i] = getMedian(arr, beginI, Math.min(end, endI)); //保存每个组的中位数 } return select(mArr, 0, mArr.length - 1, mArr.length / 2); //返回中位数组中的中位数 } public static int[] partition(int[] arr, int begin, int end, int pivotValue) { int small = begin - 1; int cur = begin; int big = end + 1; while (cur != big) { if (arr[cur] < pivotValue) { swap(arr, ++small, cur++); } else if (arr[cur] > pivotValue) { swap(arr, cur, --big); } else { cur++; } } int[] range = new int[2]; range[0] = small + 1; range[1] = big - 1; return range; } public static int getMedian(int[] arr, int begin, int end) { insertionSort(arr, begin, end); int sum = end + begin; int mid = (sum / 2) + (sum % 2); return arr[mid]; } //5个数进行排序,选了一个常数项低的插入排序 public static void insertionSort(int[] arr, int begin, int end) { for (int i = begin + 1; i != end + 1; i++) { for (int j = i; j != begin; j--) { if (arr[j - 1] > arr[j]) { swap(arr, j - 1, j); } else { break; } } } } public static void swap(int[] arr, int index1, int index2) { int tmp = arr[index1]; arr[index1] = arr[index2]; arr[index2] = tmp; } 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) { int[] arr = { 6, 9, 1, 3, 1, 2, 2, 5, 6, 1, 3, 5, 9, 7, 2, 5, 6, 1, 9 }; // sorted : { 1, 1, 1, 1, 2, 2, 2, 3, 3, 5, 5, 5, 6, 6, 6, 7, 9, 9, 9 } printArray(getMinKNumsByHeap(arr, 10)); printArray(getMinKNumsByBFPRT(arr, 10)); } }

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