Java生成希尔排序代码

以下是 Java 生成希尔排序代码的示例：

public class ShellSort {
    public static void sort(int[] arr) {
        int n = arr.length;
        for (int gap = n / 2; gap > ; gap /= 2) {
            for (int i = gap; i < n; i++) {
                int temp = arr[i];
                int j = i;
                while (j >= gap && arr[j - gap] > temp) {
                    arr[j] = arr[j - gap];
                    j -= gap;
                }
                arr[j] = temp;
            }
        }
    }
}

这段代码可以对一个整数数组进行希尔排序，时间复杂度为 O(nlogn)。

相关问题

用java写一段代码，比较冒泡排序、选择排序、插入排序、希尔排序、归并排序、快速排序、堆排序在随机数据情况下的表现

好的，以下是用 Java 实现的比较排序算法在随机数据情况下的表现的代码：

import java.util.Arrays;
import java.util.Random;

public class SortingComparison {
    
    public static void main(String[] args) {
        int[] arr = generateRandomArray(10000); // 生成随机数组
        int[] arrCopy = Arrays.copyOf(arr, arr.length); // 复制数组，以便各个算法对同一数据进行排序

        long start, end;

        // 冒泡排序
        start = System.currentTimeMillis();
        bubbleSort(arrCopy);
        end = System.currentTimeMillis();
        System.out.println("冒泡排序所用时间：" + (end - start) + "ms");

        // 选择排序
        arrCopy = Arrays.copyOf(arr, arr.length); // 复制数组
        start = System.currentTimeMillis();
        selectionSort(arrCopy);
        end = System.currentTimeMillis();
        System.out.println("选择排序所用时间：" + (end - start) + "ms");

        // 插入排序
        arrCopy = Arrays.copyOf(arr, arr.length); // 复制数组
        start = System.currentTimeMillis();
        insertionSort(arrCopy);
        end = System.currentTimeMillis();
        System.out.println("插入排序所用时间：" + (end - start) + "ms");

        // 希尔排序
        arrCopy = Arrays.copyOf(arr, arr.length); // 复制数组
        start = System.currentTimeMillis();
        shellSort(arrCopy);
        end = System.currentTimeMillis();
        System.out.println("希尔排序所用时间：" + (end - start) + "ms");

        // 归并排序
        arrCopy = Arrays.copyOf(arr, arr.length); // 复制数组
        start = System.currentTimeMillis();
        mergeSort(arrCopy, 0, arrCopy.length - 1);
        end = System.currentTimeMillis();
        System.out.println("归并排序所用时间：" + (end - start) + "ms");

        // 快速排序
        arrCopy = Arrays.copyOf(arr, arr.length); // 复制数组
        start = System.currentTimeMillis();
        quickSort(arrCopy, 0, arrCopy.length - 1);
        end = System.currentTimeMillis();
        System.out.println("快速排序所用时间：" + (end - start) + "ms");

        // 堆排序
        arrCopy = Arrays.copyOf(arr, arr.length); // 复制数组
        start = System.currentTimeMillis();
        heapSort(arrCopy);
        end = System.currentTimeMillis();
        System.out.println("堆排序所用时间：" + (end - start) + "ms");
    }

    // 生成随机数组
    private static int[] generateRandomArray(int length) {
        int[] arr = new int[length];
        Random random = new Random();
        for (int i = 0; i < length; i++) {
            arr[i] = random.nextInt(10000);
        }
        return arr;
    }

    // 冒泡排序
    private static void bubbleSort(int[] arr) {
        int n = arr.length;
        for (int i = 0; i < n - 1; i++) {
            for (int j = 0; j < n - 1 - i; j++) {
                if (arr[j] > arr[j + 1]) {
                    swap(arr, j, j + 1);
                }
            }
        }
    }

    // 选择排序
    private static void selectionSort(int[] arr) {
        int n = arr.length;
        for (int i = 0; i < n - 1; i++) {
            int minIndex = i;
            for (int j = i + 1; j < n; j++) {
                if (arr[j] < arr[minIndex]) {
                    minIndex = j;
                }
            }
            swap(arr, i, minIndex);
        }
    }

    // 插入排序
    private static void insertionSort(int[] arr) {
        int n = arr.length;
        for (int i = 1; i < n; i++) {
            int current = arr[i];
            int j = i - 1;
            while (j >= 0 && arr[j] > current) {
                arr[j + 1] = arr[j];
                j--;
            }
            arr[j + 1] = current;
        }
    }

    // 希尔排序
    private static void shellSort(int[] arr) {
        int n = arr.length;
        int gap = n / 2;
        while (gap > 0) {
            for (int i = gap; i < n; i++) {
                int current = arr[i];
                int j = i - gap;
                while (j >= 0 && arr[j] > current) {
                    arr[j + gap] = arr[j];
                    j -= gap;
                }
                arr[j + gap] = current;
            }
            gap /= 2;
        }
    }

    // 归并排序
    private static void mergeSort(int[] arr, int left, int right) {
        if (left >= right) {
            return;
        }
        int mid = (left + right) / 2;
        mergeSort(arr, left, mid);
        mergeSort(arr, mid + 1, right);
        merge(arr, left, mid, right);
    }

    private static void merge(int[] arr, int left, int mid, int right) {
        int[] temp = new int[right - left + 1];
        int i = left, j = mid + 1, k = 0;
        while (i <= mid && j <= right) {
            if (arr[i] <= arr[j]) {
                temp[k++] = arr[i++];
            } else {
                temp[k++] = arr[j++];
            }
        }
        while (i <= mid) {
            temp[k++] = arr[i++];
        }
        while (j <= right) {
            temp[k++] = arr[j++];
        }
        for (i = 0; i < temp.length; i++) {
            arr[left + i] = temp[i];
        }
    }

    // 快速排序
    private static void quickSort(int[] arr, int left, int right) {
        if (left >= right) {
            return;
        }
        int pivot = partition(arr, left, right);
        quickSort(arr, left, pivot - 1);
        quickSort(arr, pivot + 1, right);
    }

    private static int partition(int[] arr, int left, int right) {
        int pivot = arr[right];
        int i = left;
        for (int j = left; j < right; j++) {
            if (arr[j] < pivot) {
                swap(arr, i, j);
                i++;
            }
        }
        swap(arr, i, right);
        return i;
    }

    // 堆排序
    private static void heapSort(int[] arr) {
        int n = arr.length;
        for (int i = n / 2 - 1; i >= 0; i--) {
            heapify(arr, n, i);
        }
        for (int i = n - 1; i > 0; i--) {
            swap(arr, 0, i);
            heapify(arr, i, 0);
        }
    }

    private static void heapify(int[] arr, int n, int i) {
        int largest = i;
        int left = 2 * i + 1;
        int right = 2 * i + 2;
        if (left < n && arr[left] > arr[largest]) {
            largest = left;
        }
        if (right < n && arr[right] > arr[largest]) {
            largest = right;
        }
        if (largest != i) {
            swap(arr, i, largest);
            heapify(arr, n, largest);
        }
    }

    private static void swap(int[] arr, int i, int j) {
        int temp = arr[i];
        arr[i] = arr[j];
        arr[j] = temp;
    }
}

这段代码将会生成一个长度为 10000 的随机数组，并对其进行冒泡排序、选择排序、插入排序、希尔排序、归并排序、快速排序、堆排序，输出各个算法的耗时。你可以根据实际情况修改数组长度，或者增加其他排序算法的实现。

用java写一段代码，比较冒泡排序、选择排序、插入排序、希尔排序、归并排序、快速排序、堆排序在有序数据情况下的表现

好的，下面是一段Java代码，实现了对以上七种排序算法在有序数据情况下的性能比较：

import java.util.Arrays;

public class SortingComparison {
    public static void main(String[] args) {
        // 生成有序数据
        int[] arr = new int[10000];
        for (int i = 0; i < arr.length; i++) {
            arr[i] = i;
        }

        // 冒泡排序
        int[] arr1 = Arrays.copyOf(arr, arr.length);
        long start1 = System.nanoTime();
        bubbleSort(arr1);
        long end1 = System.nanoTime();
        System.out.println("冒泡排序耗时：" + (end1 - start1) + "纳秒");

        // 选择排序
        int[] arr2 = Arrays.copyOf(arr, arr.length);
        long start2 = System.nanoTime();
        selectionSort(arr2);
        long end2 = System.nanoTime();
        System.out.println("选择排序耗时：" + (end2 - start2) + "纳秒");

        // 插入排序
        int[] arr3 = Arrays.copyOf(arr, arr.length);
        long start3 = System.nanoTime();
        insertionSort(arr3);
        long end3 = System.nanoTime();
        System.out.println("插入排序耗时：" + (end3 - start3) + "纳秒");

        // 希尔排序
        int[] arr4 = Arrays.copyOf(arr, arr.length);
        long start4 = System.nanoTime();
        shellSort(arr4);
        long end4 = System.nanoTime();
        System.out.println("希尔排序耗时：" + (end4 - start4) + "纳秒");

        // 归并排序
        int[] arr5 = Arrays.copyOf(arr, arr.length);
        long start5 = System.nanoTime();
        mergeSort(arr5);
        long end5 = System.nanoTime();
        System.out.println("归并排序耗时：" + (end5 - start5) + "纳秒");

        // 快速排序
        int[] arr6 = Arrays.copyOf(arr, arr.length);
        long start6 = System.nanoTime();
        quickSort(arr6, 0, arr6.length - 1);
        long end6 = System.nanoTime();
        System.out.println("快速排序耗时：" + (end6 - start6) + "纳秒");

        // 堆排序
        int[] arr7 = Arrays.copyOf(arr, arr.length);
        long start7 = System.nanoTime();
        heapSort(arr7);
        long end7 = System.nanoTime();
        System.out.println("堆排序耗时：" + (end7 - start7) + "纳秒");
    }

    // 冒泡排序
    public static void bubbleSort(int[] arr) {
        for (int i = 0; i < arr.length - 1; i++) {
            boolean swapped = false;
            for (int j = 0; j < arr.length - i - 1; j++) {
                if (arr[j] > arr[j + 1]) {
                    swap(arr, j, j + 1);
                    swapped = true;
                }
            }
            if (!swapped) {
                break;
            }
        }
    }

    // 选择排序
    public static void selectionSort(int[] arr) {
        for (int i = 0; i < arr.length - 1; i++) {
            int minIndex = i;
            for (int j = i + 1; j < arr.length; j++) {
                if (arr[j] < arr[minIndex]) {
                    minIndex = j;
                }
            }
            if (minIndex != i) {
                swap(arr, i, minIndex);
            }
        }
    }

    // 插入排序
    public static void insertionSort(int[] arr) {
        for (int i = 1; i < arr.length; i++) {
            int temp = arr[i];
            int j;
            for (j = i - 1; j >= 0 && arr[j] > temp; j--) {
                arr[j + 1] = arr[j];
            }
            arr[j + 1] = temp;
        }
    }

    // 希尔排序
    public static void shellSort(int[] arr) {
        int gap = arr.length / 2;
        while (gap > 0) {
            for (int i = gap; i < arr.length; i++) {
                int temp = arr[i];
                int j;
                for (j = i - gap; j >= 0 && arr[j] > temp; j -= gap) {
                    arr[j + gap] = arr[j];
                }
                arr[j + gap] = temp;
            }
            gap /= 2;
        }
    }

    // 归并排序
    public static void mergeSort(int[] arr) {
        mergeSort(arr, 0, arr.length - 1);
    }

    private static void mergeSort(int[] arr, int start, int end) {
        if (start >= end) {
            return;
        }
        int mid = (start + end) / 2;
        mergeSort(arr, start, mid);
        mergeSort(arr, mid + 1, end);
        merge(arr, start, mid, end);
    }

    private static void merge(int[] arr, int start, int mid, int end) {
        int[] temp = new int[end - start + 1];
        int i = start, j = mid + 1, k = 0;
        while (i <= mid && j <= end) {
            if (arr[i] <= arr[j]) {
                temp[k++] = arr[i++];
            } else {
                temp[k++] = arr[j++];
            }
        }
        while (i <= mid) {
            temp[k++] = arr[i++];
        }
        while (j <= end) {
            temp[k++] = arr[j++];
        }
        for (int p = 0; p < temp.length; p++) {
            arr[start + p] = temp[p];
        }
    }

    // 快速排序
    public static void quickSort(int[] arr, int start, int end) {
        if (start >= end) {
            return;
        }
        int pivotIndex = partition(arr, start, end);
        quickSort(arr, start, pivotIndex - 1);
        quickSort(arr, pivotIndex + 1, end);
    }

    private static int partition(int[] arr, int start, int end) {
        int pivot = arr[start];
        int left = start + 1;
        int right = end;
        while (left <= right) {
            while (left <= right && arr[left] <= pivot) {
                left++;
            }
            while (left <= right && arr[right] >= pivot) {
                right--;
            }
            if (left <= right) {
                swap(arr, left, right);
            }
        }
        swap(arr, start, right);
        return right;
    }

    // 堆排序
    public static void heapSort(int[] arr) {
        for (int i = arr.length / 2 - 1; i >= 0; i--) {
            heapify(arr, i, arr.length);
        }
        for (int i = arr.length - 1; i >= 0; i--) {
            swap(arr, 0, i);
            heapify(arr, 0, i);
        }
    }

    private static void heapify(int[] arr, int i, int n) {
        int left = i * 2 + 1;
        int right = i * 2 + 2;
        int largest = i;
        if (left < n && arr[left] > arr[largest]) {
            largest = left;
        }
        if (right < n && arr[right] > arr[largest]) {
            largest = right;
        }
        if (largest != i) {
            swap(arr, i, largest);
            heapify(arr, largest, n);
        }
    }

    // 交换数组中的两个元素
    private static void swap(int[] arr, int i, int j) {
        int temp = arr[i];
        arr[i] = arr[j];
        arr[j] = temp;
    }
}

这段代码会生成一个长度为10000的有序数组，并对该数组进行冒泡排序、选择排序、插入排序、希尔排序、归并排序、快速排序、堆排序，分别计算它们的耗时，并输出结果。由于数组是有序的，所有排序算法的性能都应该比较好，但不同算法的耗时也会有所差异。