011-03-05 CLRS Chapter6 Heapsort(下)优先队列

 

2011-03-04 CLRS Chapter6 Heapsort(下)优先队列

优先队列的概念好理解，想想进程调度中的进程队列就是了。在CLRS中，优先队列的定义如下：

A priorityqueue is a data structure for maintaining a set S of elements,each with an associated value called a key. A max-priorityqueue supports the following operations.

·        INSERT(S, x)inserts the element x into the set S. This operation could bewritten as S ← S ∪{x}.

·        MAXIMUM(S) returns theelement of S with the largest key.

·        EXTRACT-MAX(S) removesand returns the element of S with the largest key.

·        INCREASE-KEY(S, x,k) increases the value of element x's key to the new value k,which is assumed to be at least as large as x's current key value.

下面的代码由Java实现，很是别扭，如果把Heap当作数据层，PriorityQueue当作逻辑层，那最大的问题就是对于很多代码，或者说功能，究竟应该放到数据层呢，还是应该放到逻辑层？

HeapPriorityQueue.java:

package com.zy.heappriorityqueue;public class HeapPriorityQueue {private Heap heap;public HeapPriorityQueue(int queueSize) {heap = new Heap(queueSize);}//得到最大值public int heapMaximum() {return heap.getValue(0);}//取出最大值，相当于pop，原最大值结点被删除public int heapExtractMax() {return heap.popMax();}//将第i个结点的值增加xpublic boolean heapIncreaseKey(int i, int x) {if(i>heap.getHeapSize()-1) {System.out.println("overflow");return false;} else if(heap.getValue(i)>x){System.out.println("new key is smaller than current key");return true;} else {heap.setValue(i, x);//保持最大堆的性质while(i>0&&heap.getValue(heap.parent(i))<heap.getValue(i)) {int temp = heap.getValue(i);heap.setValue(i, heap.getValue(heap.parent(i)));heap.setValue(heap.parent(i), temp);i = heap.parent(i);}return true;}}//向队列中增加一个元素public void maxHeapInsert(int value) {heap.addElement(value);}} 

底层的Heap数据结构 Heap.java

package com.zy.heappriorityqueue;public class Heap {private int[] data;private int heapSize;//堆的大小，表示当前堆中有多少个元素//新建一个堆，容量为sizepublic Heap(int size) {data = new int[size];heapSize = 0;}//取得结点i的父结点public int parent(int i) {return (i-1)/2;}//取得结点i的左孩子 public int left(int i) {return 2*i+1;}//取得结点i的右孩子 public int right(int i) {return 2*i + 2;}//让i结点及其子结点保持最大堆的性质public void maxHeapity(int i) {int l = left(i);int r = right(i);int largest = i;//取得｛结点i，i的左孩子，i的右孩子｝三者当中的最大值的下标，赋给largestif(l<heapSize&&data[l]>data[i]){largest = l;}if(r<heapSize&&data[r]>data[largest]){largest = r;}//如果largest不等于i，则将i与largest两者的值交换，以保持最大堆的性质if(largest!=i){int temp = data[i];data[i] = data[largest];data[largest] = temp;maxHeapity(largest);//同时递归处理largest结点.}}//返回堆的大小，即当前堆中有多少个元素public int getHeapSize() {return heapSize;}//返回第i个结点的值public int getValue(int i) {return data[i];}//设置第i个结点的值public void setValue(int i, int x) {data[i] = x;}//增加一个结点public void addElement(int value) {// TODO Auto-generated method stubif(heapSize>data.length) {System.out.println("overflow");System.exit(-1);} else {data[heapSize-1] = value;int i = heapSize -1;//保持最大堆的性质while(i>0&&getValue(parent(i))<getValue(i)) {int temp = getValue(i);setValue(i, getValue(parent(i)));setValue(parent(i), temp);i = parent(i);}}}//取出最大值，相当于pop，原最大值结点被删除public int popMax() {// TODO Auto-generated method stubif(heapSize<1) {System.out.println("heap underflow");return Integer.MIN_VALUE;} else {int max = data[0];data[0] = data[heapSize-1];maxHeapity(0);heapSize--;return max;}}}