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、堆排序等算法在随机数据的情况下的比较

好的，我来给您写一段Java代码，比较几种排序算法在随机数据情况下的性能：

import java.util.*;

public class SortComparison {
    private static final int ARRAY_SIZE = 10000;
    private static final int MAX_RANDOM_NUM = 100000;
    private static final int[] RANDOM_ARRAY = new int[ARRAY_SIZE];

    public static void main(String[] args) {
        // 生成随机数组
        Random rand = new Random();
        for (int i = 0; i < ARRAY_SIZE; i++) {
            RANDOM_ARRAY[i] = rand.nextInt(MAX_RANDOM_NUM);
        }

        // 冒泡排序
        int[] bubbleSortedArray = Arrays.copyOf(RANDOM_ARRAY, RANDOM_ARRAY.length);
        long bubbleSortStartTime = System.nanoTime();
        bubbleSort(bubbleSortedArray);
        long bubbleSortEndTime = System.nanoTime();
        System.out.println("冒泡排序用时：" + (bubbleSortEndTime - bubbleSortStartTime) + " 纳秒");

        // 选择排序
        int[] selectionSortedArray = Arrays.copyOf(RANDOM_ARRAY, RANDOM_ARRAY.length);
        long selectionSortStartTime = System.nanoTime();
        selectionSort(selectionSortedArray);
        long selectionSortEndTime = System.nanoTime();
        System.out.println("选择排序用时：" + (selectionSortEndTime - selectionSortStartTime) + " 纳秒");

        // 插入排序
        int[] insertionSortedArray = Arrays.copyOf(RANDOM_ARRAY, RANDOM_ARRAY.length);
        long insertionSortStartTime = System.nanoTime();
        insertionSort(insertionSortedArray);
        long insertionSortEndTime = System.nanoTime();
        System.out.println("插入排序用时：" + (insertionSortEndTime - insertionSortStartTime) + " 纳秒");

        // 希尔排序
        int[] shellSortedArray = Arrays.copyOf(RANDOM_ARRAY, RANDOM_ARRAY.length);
        long shellSortStartTime = System.nanoTime();
        shellSort(shellSortedArray);
        long shellSortEndTime = System.nanoTime();
        System.out.println("希尔排序用时：" + (shellSortEndTime - shellSortStartTime) + " 纳秒");

        // 归并排序
        int[] mergeSortedArray = Arrays.copyOf(RANDOM_ARRAY, RANDOM_ARRAY.length);
        long mergeSortStartTime = System.nanoTime();
        mergeSort(mergeSortedArray, 0, mergeSortedArray.length - 1);
        long mergeSortEndTime = System.nanoTime();
        System.out.println("归并排序用时：" + (mergeSortEndTime - mergeSortStartTime) + " 纳秒");

        // 快速排序
        int[] quickSortedArray = Arrays.copyOf(RANDOM_ARRAY, RANDOM_ARRAY.length);
        long quickSortStartTime = System.nanoTime();
        quickSort(quickSortedArray, 0, quickSortedArray.length - 1);
        long quickSortEndTime = System.nanoTime();
        System.out.println("快速排序用时：" + (quickSortEndTime - quickSortStartTime) + " 纳秒");

        // 堆排序
        int[] heapSortedArray = Arrays.copyOf(RANDOM_ARRAY, RANDOM_ARRAY.length);
        long heapSortStartTime = System.nanoTime();
        heapSort(heapSortedArray);
        long heapSortEndTime = System.nanoTime();
        System.out.println("堆排序用时：" + (heapSortEndTime - heapSortStartTime) + " 纳秒");
    }

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

    // 选择排序
    private 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) {
                int temp = arr[minIndex];
                arr[minIndex] = arr[i];
                arr[i] = temp;
            }
        }
    }

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

    // 希尔排序
    private 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 = i - gap;
                while (j >= 0 && arr[j] > temp) {
                    arr[j + gap] = arr[j];
                    j -= gap;
                }
                arr[j + gap] = temp;
            }
            gap /= 2;
        }
    }

    // 归并排序
    private static void mergeSort(int[] arr, int left, int right) {
        if (left < right) {
            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;
        int j = mid + 1;
        int 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 (int p = 0; p < temp.length; p++) {
            arr[left + p] = temp[p];
        }
    }

    // 快速排序
    private static void quickSort(int[] arr, int left, int right) {
        if (left < right) {
            int pivotIndex = partition(arr, left, right);
            quickSort(arr, left, pivotIndex - 1);
            quickSort(arr, pivotIndex + 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) {
                int temp = arr[i];
                arr[i] = arr[j];
                arr[j] = temp;
                i++;
            }
        }
        int temp = arr[i];
        arr[i] = arr[right];
        arr[right] = temp;
        return i;
    }

    // 堆排序
    private 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--) {
            int temp = arr[0];
            arr[0] = arr[i];
            arr[i] = temp;
            heapify(arr, 0, i);
        }
    }

    private static void heapify(int[] arr, int i, int length) {
        int temp = arr[i];
        for (int j = 2 * i + 1; j < length; j = 2 * j + 1) {
            if (j + 1 < length && arr[j + 1] > arr[j]) {
                j++;
            }
            if (arr[j] > temp) {
                arr[i] = arr[j];
                i = j;
            } else {
                break;
            }
        }
        arr[i] = temp;
    }
}

这段代码会生成一个大小为10000的随机数组，然后分别对这个数组进行冒泡排序、选择排序、插入排序、希尔排序、归并排序、快速排序、堆排序，并统计每种排序算法的执行时间。您可以在自己的本地环境中运行这段代码，观察不同排序算法的性能表现。