排序是计算机算法中非常重要的一项,而排序算法又有不少实现方法,那么哪些排序算法比较有效率,哪些算法在特定场合比较有效,下面将用C++实现各种算法,并且比较他们的效率,让我们对各种排序有个更深入的了解。
冒泡排序
插入排序
快速排序
希尔排序
计数排序
基数排序
minheap.h
maintest.cpp
冒泡排序
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//n^2
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//冒泡排序V[n]不参与排序
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void BubbleSort (int V[], int n )
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{
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bool exchange; //设置交换标志置
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for ( int i = 0; i < n; i++ ){
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exchange=false;
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for (int j=n-1; j>i; j--) { //反向检测,检查是否逆序
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if (V[j-1] > V[j]) //发生逆序,交换相邻元素
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{
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int temp=V[j-1];
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V[j-1]=V[j];
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V[j]=temp;
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exchange=true;//交换标志置位
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}
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}
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if (exchange == false)
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return; //本趟无逆序,停止处理
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}
- }
插入排序
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//插入排序,L[begin],L[end]都参与排序
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void InsertionSort ( int L[], const int begin, const int end)
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{
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//按关键码 Key 非递减顺序对表进行排序
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int temp;
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int i, j;
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for ( i = begin; i < end; i++ )
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{
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if (L[i]>L[i+1])
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{
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temp = L[i+1];
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j=i;
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do
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{
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L[j+1]=L[j];
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if(j == 0)
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{
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j--;
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break;
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}
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j--;
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} while(temp<L[j]);
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L[j+1]=temp;
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}
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}
- }
快速排序
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//n*logn
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//快速排序A[startingsub],A[endingsub]都参与排序
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void QuickSort( int A[], int startingsub, int endingsub)
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{
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if ( startingsub >= endingsub )
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;
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else{
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int partition;
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int q = startingsub;
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int p = endingsub;
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int hold;
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do{
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for(partition = q ; p > q ; p--){
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if( A[q] > A[p]){
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hold = A[q];
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A[q] = A[p];
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A[p] = hold;
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break;
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}
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}
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for(partition = p; p > q; q++){
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if(A[p] < A[q]){
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hold = A[q];
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A[q] = A[p];
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A[p] = hold;
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break;
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}
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}
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}while( q < p );
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QuickSort( A, startingsub, partition - 1 );
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QuickSort( A, partition + 1, endingsub );
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}
- }
希尔排序
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//希尔排序,L[left],L[right]都参与排序
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void Shellsort( int L[], const int left, const int right)
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{
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int i, j, gap=right-left+1; //增量的初始值
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int temp;
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do{
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gap=gap/3+1; //求下一增量值
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for(i=left+gap; i<=right; i++)
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//各子序列交替处理
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if( L[i]<L[i-gap]){ //逆序
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temp=L[i]; j=i-gap;
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do{
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L[j+gap]=L[j]; //后移元素
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j=j-gap; //再比较前一元素
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}while(j>left&&temp<L[j]);
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L[j+gap]=temp; //将vector[i]回送
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}
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}while(gap>1);
- }
计数排序
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//n
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//计数排序,L[n]不参与排序
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void CountingSort( int L[], const int n )
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{
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int i,j;
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const int k =1001;
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int tmp[k];
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int *R;
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R = new int[n];
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for(i=0;i<k;i++) tmp[i]= 0;
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for(j=0;j<n;j++) tmp[L[j]]++;
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//执行完上面的循环后,tmp[i]的值是L中等于i的元素的个数
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for(i=1;i<k;i++)
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tmp[i]=tmp[i]+tmp[i-1]; //执行完上面的循环后,
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//tmp[i]的值是L中小于等于i的元素的个数
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for(j=n-1;j>=0;j--) //这里是逆向遍历,保证了排序的稳定性
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{
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R[tmp[L[j]]-1] = L[j];
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//L[j]存放在输出数组R的第tmp[L[j]]个位置上
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tmp[L[j]]--;
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//tmp[L[j]]表示L中剩余的元素中小于等于L[j]的元素的个数
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}
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for(j=0;j<n;j++) L[j] = R[j];
- }
基数排序
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//基数排序
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void printArray( const int Array[], const int arraySize );
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int getDigit(int num, int dig);
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const int radix=10; //基数
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void RadixSort(int L[], int left, int right, int d){
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//MSD排序算法的实现。从高位到低位对序列划分,实现排序。d是第几位数,d=1是最低位。left和right是待排序元素子序列的始端与尾端。
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int i, j, count[radix], p1, p2;
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int *auxArray;
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int M = 5;
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auxArray = new int[right-left+1];
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if (d<=0) return; //位数处理完递归结束
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if (right-left+1<M){//对于小序列可调用直接插入排序
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InsertionSort(L,left,right); return;
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}
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for (j=0; j<radix; j++) count[j]=0;
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for (i=left; i<=right; i++) //统计各桶元素的存放位置
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count[getDigit(L[i],d)]++;
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for (j=1; j<radix; j++) //安排各桶元素的存放位置
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count[j]=count[j]+count[j-1];
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for (i=right; i>=left; i--){ //将待排序序列中的元素按位置分配到各个桶中,存于助数组auxArray中
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j=getDigit(L[i],d); //取元素L[i]第d位的值
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auxArray[count[j]-1]=L[i]; //按预先计算位置存放
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count[j]--; //计数器减1
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}
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for (i=left, j=0; i<=right; i++, j++)
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L[i]=auxArray[j]; //从辅助数组顺序写入原数组
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delete []auxArray;
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for (j=0; j<radix; j++){ //按桶递归对d-1位处理
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p1=count[j]+left; //取桶始端,相对位置,需要加上初值$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
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(j+1 <radix )?(p2=count[j+1]-1+left):(p2=right) ; //取桶尾端
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// delete []count;
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if(p1<p2){
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RadixSort(L, p1, p2, d-1); //对桶内元素进行基数排序
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// printArray(L,10);
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}
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}
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}
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int getDigit(int num, int dig)
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{
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int myradix = 1;
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/* for(int i = 1;i<dig;i++)
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{
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myradix *= radix;
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}*/
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switch(dig)
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{
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case 1:
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myradix = 1;
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break;
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case 2:
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myradix = 10;
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break;
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case 3:
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myradix = 1000;
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break;
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case 4:
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myradix = 10000;
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break;
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default:
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myradix = 1;
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break;
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}
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return (num/myradix)%radix;
- }
minheap.h
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//使用时注意将关键码加入
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#ifndef MINHEAP_H
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#define MINHEAP_H
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#include <assert.h>
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#include <iostream>
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using std::cout;
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using std::cin;
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using std::endl;
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using std::cerr;
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#include <stdlib.h>
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//const int maxPQSize = 50;
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template <class Type> class MinHeap {
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public:
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MinHeap ( int maxSize );//根据最大长度建堆
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MinHeap ( Type arr[], int n );//根据数组arr[]建堆
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~MinHeap ( ) { delete [] heap; }
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const MinHeap<Type> & operator = ( const MinHeap &R );//重载赋值运算符
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int Insert ( const Type &x );//插入元素
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int RemoveMin ( Type &x );//移除关键码最小的元素,并赋给x
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int IsEmpty ( ) const { return CurrentSize == 0; }//检查堆是否为空
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int IsFull ( ) const { return CurrentSize == MaxHeapSize; }//检查对是否满
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void MakeEmpty ( ) { CurrentSize = 0; }//使堆空
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private:
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enum { DefaultSize = 50 };//默认堆的大小
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Type *heap;
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int CurrentSize;
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int MaxHeapSize;
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void FilterDown ( int i, int m );//自上向下调整堆
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void FilterUp ( int i );//自下向上调整堆
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};
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template <class Type> MinHeap <Type>::MinHeap ( int maxSize )
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{
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//根据给定大小maxSize,建立堆对象
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MaxHeapSize = (DefaultSize < maxSize ) ? maxSize : DefaultSize; //确定堆大小
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heap = new Type [MaxHeapSize]; //创建堆空间
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CurrentSize = 0; //初始化
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}
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template <class Type> MinHeap <Type>::MinHeap ( Type arr[], int n )
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{
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//根据给定数组中的数据和大小,建立堆对象
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MaxHeapSize = DefaultSize < n ? n : DefaultSize;
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heap = new Type [MaxHeapSize];
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if(heap==NULL){cerr <<"fail" <<endl;exit(1);}
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for(int i =0; i< n; i++)
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heap[i] = arr[i]; //数组传送
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CurrentSize = n; //当前堆大小
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int currentPos = (CurrentSize-2)/2; //最后非叶
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while ( currentPos >= 0 ) {
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//从下到上逐步扩大,形成堆
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FilterDown ( currentPos, CurrentSize-1 );
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currentPos-- ;
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//从currentPos开始,到0为止, 调整currentPos--; }
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}
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}
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template <class Type> void MinHeap<Type>::FilterDown ( const int start, const int EndOfHeap )
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{
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// 结点i的左、右子树均为堆,调整结点i
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int i = start, j = 2*i+1; // j 是 i 的左子女
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Type temp = heap[i];
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while ( j <= EndOfHeap ) {
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if ( j < EndOfHeap && heap[j] > heap[j+1] )
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j++;//两子女中选小者
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if ( temp<= heap[j] ) break;
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else { heap[i] = heap[j]; i = j; j = 2*j+1; }
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}
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heap[i] = temp;
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}
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template <class Type> int MinHeap<Type>::Insert ( const Type &x )
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{
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//在堆中插入新元素 x
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if ( CurrentSize == MaxHeapSize ) //堆满
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{
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cout << "堆已满" << endl; return 0;
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}
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heap[CurrentSize] = x; //插在表尾
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FilterUp (CurrentSize); //向上调整为堆
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CurrentSize++; //堆元素增一
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return 1;
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}
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template <class Type> void MinHeap<Type>::FilterUp ( int start )
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{
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//从 start 开始,向上直到0,调整堆
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int j = start, i = (j-1)/2; // i 是 j 的双亲
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Type temp = heap[j];
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while ( j > 0 ) {
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if ( (heap[i].root->data.key )<= (temp.root->data.key) ) break;
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else { heap[j] = heap[i]; j = i; i = (i -1)/2; }
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}
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heap[j] = temp;
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}
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template <class Type> int MinHeap <Type>::RemoveMin ( Type &x )
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{
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if ( !CurrentSize )
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{
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cout << "堆已空 " << endl;
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return 0;
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}
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x = heap[0]; //最小元素出队列
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heap[0] = heap[CurrentSize-1];
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CurrentSize--; //用最小元素填补
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FilterDown ( 0, CurrentSize-1 );
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//从0号位置开始自顶向下调整为堆
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return 1;
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}
- #endif
maintest.cpp
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#include<iostream>
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using std::cout;
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using std::cin;
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using std::endl;
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#include <cstdlib>
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#include <ctime>
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#include<iostream>
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using std::cout;
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using std::cin;
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using std::ios;
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using std::cerr;
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using std::endl;
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#include<iomanip>
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using std::setw;
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using std::fixed;
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#include<fstream>
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using std::ifstream;
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using std::ofstream;
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using std::flush;
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#include<string>
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using std::string;
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#include <stdio.h>
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#include <stdlib.h>
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#include <time.h>
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#include"minheap.h"
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void BubbleSort(int arr[], int size);//冒泡排序
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void QuickSort( int A[], int startingsub, int endingsub);//快速排序
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void InsertionSort ( int L[], const int begin,const int n);//插入排序
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void Shellsort( int L[], const int left, const int right);//希尔排序
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void CountingSort( int L[], const int n );//计数排序
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int getDigit(int num, int dig);//基数排序中获取第dig位的数字
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void RadixSort(int L[], int left, int right, int d);//基数排序
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void printArray( const int Array[], const int arraySize );//输出数组
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int main()
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{
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clock_t start, finish;
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double duration;
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/* 测量一个事件持续的时间*/
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ofstream *ofs;
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string fileName = "sortResult.txt";
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ofs = new ofstream(fileName.c_str(),ios::out|ios::app);
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const int size = 100000;
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int a[size];
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int b[size];
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srand(time(0));
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ofs->close();
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for(int i = 0; i < 20;i++)
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{
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ofs->open(fileName.c_str(),ios::out|ios::app);
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if( ofs->fail()){
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cout<<"!!";
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ofs->close();
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}
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for(int k =0; k <size;k++)
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{
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a[k] = rand()%1000;
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b[k] = a[k];
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}
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/* for( k =0; k <size;k++)
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{
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a[k] = k;
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b[k] = a[k];
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} */
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//printArray(a,size);
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//计数排序
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for( k =0; k <size;k++)
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{
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a[k] = b[k];
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}
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start = clock();
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CountingSort(a,size);
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finish = clock();
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// printArray(a,size);
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duration = (double)(finish - start) / CLOCKS_PER_SEC;
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printf( "%s%f secondsn", "计数排序:",duration );
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*ofs<<"第"<<i<<"次:n " <<"排序内容:0~999共" << size << " 个整数n" ;
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*ofs<<"第"<<i<<"次计数排序:n " <<" Time: " <<fixed<< duration << " secondsn";
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//基数排序
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for( k =0; k <size;k++)
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{
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a[k] = b[k];
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}
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start = clock();
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RadixSort(a, 0,size-1, 3);
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finish = clock();
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// printArray(a,size);
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duration = (double)(finish - start) / CLOCKS_PER_SEC;
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printf( "%s%f secondsn", "基数排序:",duration );
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*ofs<<"第"<<i<<"次基数排序:n " <<" Time: " << duration << " secondsn";
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//堆排序
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MinHeap<int> mhp(a,size);
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start = clock();
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for( k =0; k <size;k++)
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{
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mhp.RemoveMin(a[k]);
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}
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finish = clock();
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// printArray(a,size);
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duration = (double)(finish - start) / CLOCKS_PER_SEC;
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printf( "%s%f secondsn", "堆排序:",duration );
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*ofs<<"第"<<i<<"次堆排序:n " <<" Time: " << duration << " secondsn";
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//快速排序
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for( k =0; k <size;k++)
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{
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a[k] = b[k];
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}
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//printArray(a,size);
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start = clock();
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QuickSort(a,0,size-1);
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finish = clock();
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// printArray(a,size);
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duration = (double)(finish - start) / CLOCKS_PER_SEC;
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printf( "%s%f secondsn", "快速排序:",duration );
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*ofs<<"第"<<i<<"次快速排序:n " <<" Time: " << duration << " secondsn";
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//希尔排序
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for( k =0; k <size;k++)
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{
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a[k] = b[k];
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}
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start = clock();
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Shellsort(a,0,size-1);
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finish = clock();
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// printArray(a,size);
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duration = (double)(finish - start) / CLOCKS_PER_SEC;
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printf( "%s%f secondsn", "希尔排序:",duration );
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*ofs<<"第"<<i<<"次希尔排序:n " <<" Time: " << duration << " secondsn";
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//插入排序
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for( k =0; k <size;k++)
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{
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a[k] = b[k];
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}
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start = clock();
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InsertionSort (a,0,size-1);
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finish = clock();
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// printArray(a,size);
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duration = (double)(finish - start) / CLOCKS_PER_SEC;
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printf( "%s%f secondsn", "插入排序:",duration );
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*ofs<<"第"<<i<<"次插入排序:n " <<" Time: " << duration << " secondsn";
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//冒泡排序
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for( k =0; k <size;k++)
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{
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a[k] = b[k];
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}
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start = clock();
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BubbleSort(a,size);
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finish = clock();
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// printArray(a,size);
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duration = (double)(finish - start) / CLOCKS_PER_SEC;
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printf( "%s%f secondsn", "冒泡排序:",duration );
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*ofs<<"第"<<i<<"次冒泡排序:n " <<" Time: " << duration << " secondsn";
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ofs->close();
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}
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return 0;
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}
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void printArray( const int Array[], const int arraySize )
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{
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for( int i = 0; i < arraySize; i++ ) {
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cout << Array[ i ] << " ";
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if ( i % 20 == 19 )
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cout << endl;
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}
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cout << endl;
- }
排序算法性能仿真:
排序内容:从0~999中随机产生,共100000 个整数,该表中单位为秒。
| 次数 | 计数排序 | 基数排序 | 堆排序 | 快速排序 | 希尔排序 | 直接插入排序 | 冒泡排序 |
| 1 | 0.0000 | 0.0310 | 0.0470 | 0.0470 | 0.0310 | 14.7970 | 58.0930 |
| 2 | 0.0000 | 0.0470 | 0.0310 | 0.0470 | 0.0470 | 16.2500 | 53.3280 |
| 3 | 0.0000 | 0.0310 | 0.0310 | 0.0310 | 0.0310 | 14.4850 | 62.4380 |
| 4 | 0.0000 | 0.0320 | 0.0320 | 0.0470 | 0.0310 | 17.1090 | 61.8440 |
| 5 | 0.0000 | 0.0310 | 0.0470 | 0.0470 | 0.0310 | 16.9380 | 62.3280 |
| 6 | 0.0000 | 0.0310 | 0.0310 | 0.0470 | 0.0310 | 16.9380 | 57.7030 |
| 7 | 0.0000 | 0.0310 | 0.0470 | 0.0310 | 0.0310 | 16.8750 | 61.9380 |
| 8 | 0.0150 | 0.0470 | 0.0310 | 0.0470 | 0.0320 | 17.3910 | 62.8600 |
| 9 | 0.0000 | 0.0320 | 0.0470 | 0.0460 | 0.0310 | 16.9530 | 62.2660 |
| 10 | 0.0000 | 0.0470 | 0.0310 | 0.0470 | 0.0310 | 17.0160 | 60.1410 |
| 11 | 0.0000 | 0.0930 | 0.0780 | 0.0320 | 0.0310 | 14.6090 | 54.6570 |
| 12 | 0.0000 | 0.0310 | 0.0320 | 0.0310 | 0.0310 | 15.0940 | 62.3430 |
| 13 | 0.0000 | 0.0310 | 0.0310 | 0.0470 | 0.0310 | 17.2340 | 61.9530 |
| 14 | 0.0000 | 0.0320 | 0.0470 | 0.0470 | 0.0310 | 16.9060 | 61.0620 |
| 15 | 0.0000 | 0.0320 | 0.0320 | 0.0460 | 0.0320 | 16.7810 | 62.5310 |
| 16 | 0.0000 | 0.0470 | 0.0470 | 0.0620 | 0.0310 | 17.2350 | 57.1720 |
| 17 | 0.0150 | 0.0160 | 0.0320 | 0.0470 | 0.0310 | 14.1400 | 52.0320 |
| 18 | 0.0150 | 0.0160 | 0.0310 | 0.0310 | 0.0310 | 14.1100 | 52.3590 |
| 19 | 0.0000 | 0.0310 | 0.0320 | 0.0460 | 0.0320 | 14.1090 | 51.8750 |
| 20 | 0.0000 | 0.0310 | 0.0320 | 0.0460 | 0.0320 | 14.0780 | 52.4840 |
| 21 | 0.0150 | 0.0780 | 0.0470 | 0.0470 | 0.0310 | 16.3750 | 59.5150 |
| 22 | 0.0000 | 0.0310 | 0.0310 | 0.0470 | 0.0320 | 16.8900 | 60.3440 |
| 23 | 0.0000 | 0.0310 | 0.0310 | 0.0310 | 0.0310 | 16.3440 | 60.0930 |
| 24 | 0.0000 | 0.0310 | 0.0310 | 0.0470 | 0.0310 | 16.3440 | 60.5780 |
| 25 | 0.0000 | 0.0320 | 0.0470 | 0.0470 | 0.0470 | 16.3590 | 59.7810 |
| 26 | 0.0160 | 0.0470 | 0.0310 | 0.0470 | 0.0310 | 16.1250 | 61.0620 |
| 27 | 0.0000 | 0.0310 | 0.0470 | 0.0470 | 0.0310 | 16.7810 | 59.6100 |
| 28 | 0.0150 | 0.0320 | 0.0320 | 0.0470 | 0.0310 | 16.9220 | 56.8130 |
| 29 | 0.0000 | 0.0310 | 0.0310 | 0.0310 | 0.0310 | 15.0790 | 57.8120 |
| 30 | 0.0000 | 0.0310 | 0.0320 | 0.0460 | 0.0320 | 14.7810 | 58.8280 |
| 31 | 0.0000 | 0.0310 | 0.0310 | 0.0470 | 0.0310 | 15.8590 | 59.1400 |
| 32 | 0.0000 | 0.0470 | 0.0320 | 0.0310 | 0.0310 | 16.0940 | 59.1560 |
| 33 | 0.0000 | 0.0470 | 0.0310 | 0.0310 | 0.0310 | 15.9850 | 59.1400 |
| 34 | 0.0000 | 0.0310 | 0.0310 | 0.0470 | 0.0320 | 16.0150 | 59.2500 |
| 35 | 0.0000 | 0.0310 | 0.0470 | 0.0470 | 0.0310 | 16.7660 | 57.9840 |
| 36 | 0.0000 | 0.0310 | 0.0320 | 0.0470 | 0.0310 | 15.3750 | 59.0470 |
| 37 | 0.0000 | 0.0320 | 0.0460 | 0.0470 | 0.0320 | 16.0310 | 58.9060 |
| 38 | 0.0000 | 0.0310 | 0.0310 | 0.0470 | 0.0310 | 15.9530 | 57.2650 |
| 39 | 0.0160 | 0.0310 | 0.0470 | 0.0470 | 0.0310 | 15.9530 | 57.5160 |
| 40 | 0.0150 | 0.0310 | 0.0320 | 0.0470 | 0.0310 | 14.7030 | 56.6710 |
| 平均值 | 0.0031 | 0.0360 | 0.0372 | 0.0437 | 0.0320 | 15.9946 | 58.7480 |
| 最小值 | 0.0000 | 0.0160 | 0.0310 | 0.0310 | 0.0310 | 14.0780 | 51.8750 |
| 最大值 | 0.0160 | 0.0930 | 0.0780 | 0.0620 | 0.0470 | 17.3910 | 62.8600 |