第六章 堆排序 6.5 优先队列

package chap06_Heap_Sort;

import static org.junit.Assert.*;

import java.util.ArrayList;
import java.util.Arrays;

import org.junit.Test;

/**
 * 优先队列，二叉堆数组实现，数组的size最好大一些，至少比里面的堆大一些，来实现堆的扩展（插入元素）
 * 
 * @author xiaojintao
 * 
 */
public class PriorityQueue {

    /**
     * 返回当前下标下父节点的下标
     * 
     * @param i
     * @return
     */
    protected static int parent(int i) {
        if (i == 0)
            return i;
        return (i - 1) / 2;
    }

    /**
     * 
     * @param i
     * @return
     */
    protected static int left(int i) {
        return 2 * i + 1;
    }

    /**
     * 
     * @param i
     * @return
     */
    protected static int right(int i) {
        return 2 * (i + 1);
    }

    /**
     * 重建最大堆，从i开始到size（不包含size索引），size为堆的大小
     * 
     * @param a
     * @param i
     * @param size
     */
    protected static void maxHeapify(int[] a, int i, int heapsize) {
        int l = left(i);
        int r = right(i);
        int tmp;
        while (l < heapsize & r < heapsize) {
            if (a[i] >= a[l] & a[i] >= a[r])
                return;
            else if (a[l] > a[r]) {
                tmp = a[i];
                a[i] = a[l];
                a[l] = tmp;
                i = l;
            } else {
                tmp = a[i];
                a[i] = a[r];
                a[r] = tmp;
                i = r;
            }
            l = left(i);
            r = right(i);
        }
        if (l < heapsize) {
            if (a[i] < a[l]) {
                tmp = a[i];
                a[i] = a[l];
                a[l] = tmp;
                i = l;
            }
        }
        return;
    }

    /**
     * 
     * @param a
     * @return
     */
    static int heapMaximum(int[] a) {

        return a[0];
    }

    /**
     * 
     * @param a
     * @param heapsize
     * @return
     */
    static int heapExtractMax(int[] a, int heapsize) {
        if (heapsize < 1)
            return -1;
        int max = a[0];
        a[0] = a[heapsize];
        heapsize--;
        maxHeapify(a, 0, heapsize);
        return -1;
    }

    /**
     * 将数组a转换成最大堆,不要用递归方法，尽量用迭代方法实现
     * 
     * @param a
     */
    protected static void buildMaxHeap(int[] a) {
        int n = a.length;

        for (int i = n / 2; i >= 0; i--) {
            maxHeapify(a, i, n);
        }
    }

    /**
     * 将堆上x位置处的值增加为key
     * 
     * @param a
     * @param x
     * @param key
     */
    static void heapIncreaseKey(int[] a, int x, int key) {
        a[x] = key;
        if (x == 0)
            return;
        int i;
        int tmp;
        do {
            i = parent(x);
            if (a[i] >= a[x])
                break;
            else {
                tmp = a[i];
                a[i] = a[x];
                a[x] = tmp;
                x = i;
            }
        } while (i != 0);

    }

    /**
     * 向堆中插入元素，size为当前堆的尺寸,插入后，空位置处为int的最小值，min_value
     * 
     * @param n
     * @param size
     * @param key
     */
    static void maxHeapInsert(int[] n, int key, int heapsize) {
        if (heapsize == n.length)
            System.err.println("heap is full");
        heapsize++;
        n[heapsize-1] = key;
        buildMaxHeap(n);

    }

    @Test
    public void testName() throws Exception {
        int[] a = { 2, 5, 3, 7, 8, 12, 0, 2, 45, 32 };
        int[] a1 = new int[12];
        for (int i = 0; i < a1.length; i++) {
            if (i < a.length)
                a1[i] = a[i];
            else
                a1[i] = Integer.MIN_VALUE;
        }
        System.out.println(Arrays.toString(a1));
        // heapIncreaseKey(a, 3, 50);
        maxHeapInsert(a1, 65, 10);
        System.out.println(Arrays.toString(a1));
    }
}

转载于:https://my.oschina.net/xiaojintao/blog/817357