排序算法实例精粹（windows c++ 验证）

//sort.hpp文件/*1.插入排序最好情况：元素数组本身是排好的；比较次数n-1;元素移动次数0;最坏情况：元素数组是倒序的；比较次数KCN=n(n-1)/2 =n*2/2;元素移动次数 （n+4）(n-1)/2=n*n/2;所以直接插入排序时间复杂度为O(n*n);直接插入排序是一种稳定排序算法;*/template<class T>void insertSort(T dataList[], const int left, const int right){T tmp;int i=0,j=0;for(i= left+1; i<=right; i++){if(dataList[i] < dataList[i-1]){tmp = dataList[i];j= i-1;do {dataList[j+1] = dataList[j];j--;}while (j>=left && tmp < dataList[j]);dataList[j+1] = tmp;}}}/*2.折半插入排序折半插入排序搜索速度比直接插入排序快。元素比较次数与待排序元素序列的初始排序无关，仅依赖元素个数。元素比较次数：n*log2n-n+1元素移动次数 （n+4）(n-1)/2=n*n/2（和直接插入排序算法一样）;数据量较大时，比直接插入排序有优势折半插入排序是稳定排序算法*/template<class T>void binaryInsertSort(T dataList[], const int left, const int right){for (int i=left+1; i<= right; i++){if (dataList[i]<dataList[i-1]){T tmp = dataList[i];int nLow = left;int nHigh = i;while(nLow < nHigh){int nMid = (nHigh-nLow)/2+nLow;if (tmp <= dataList[nMid]){nHigh = nMid-1;}else{nLow = nMid+1;}}for (int k = i; k>nLow; k--){dataList[k] = dataList[k-1];}dataList[nLow] = tmp;}}}/*3.希尔排序算法(又称为缩小增量排序 diminishing-incrementsort) 1959年希尔提出算法思想：设带排序元素序列有n个元素，首先取一个整数gap(gap<n),作为间隔，将全部元素分为gap个子序列，所有距离为gap的元素放在同一个子序列中，在每个子序列中分别进行直接插入排序。然后缩小gap,例如gap=gap/2,重复上述的子序列划分和排序工作，直到gap==1，将所有元素放在同一个序列中排序为止。元素移动次数：n的1.25次方-1.6*n的1.25次方由于即使对于规模较大的序列（n<=1000）,希尔排序都具有很高的效率，很多应用程序都选择希尔排序。希尔排序是一种不稳定排序算法*/template<class T>void shellSort(T dataList[], const int left, const int right){int i=0;int j=0;int gap = right - left + 1;//增量的初始化值T tmp = 0;do {gap = gap / 3 + 1;//求下一增量值for (i=left+gap; i<=right; i++){if (dataList[i] < dataList[i-gap]){tmp = dataList[i];j = i-gap;do {dataList[j+gap] = dataList[j];j = j - gap;} while (j > left && tmp < dataList[j]);dataList[j+gap] = tmp;}}} while (gap > 1);}/*4.快速排序算法快速排序算法是C.R.A.Hoare 于1992年提出的一种划分交换的方法，它采用分治法(divide-and-conquer)进行排序。基本思想就是任取待排序元素序列中的某个元素作为基准，将大于这个数的放在右边，将小于这个数的放在左边，。然后分别对这两个子序列重复实施上述方法，直到所有元素都排在相应的位置为止。*/template<class T>int Partion(T dataList[], const int left, const int right){T  nBaseData = dataList[left];int nPosCurBase = left;for (int i=left+1; i<=right; i++){if ( dataList[i] < nBaseData ){nPosCurBase++;if(i != nPosCurBase) {T tmp = dataList[nPosCurBase];dataList[nPosCurBase] = dataList[i];dataList[i] = tmp;}}}dataList[left] = dataList[nPosCurBase];dataList[nPosCurBase] = nBaseData;return nPosCurBase;}template<class T>voidquickSort(T dataList[], const int left, const int right){if (left >= right){return;}int nPosCurBase = Partion(dataList, left, right);quickSort(dataList, left, nPosCurBase-1);quickSort(dataList, nPosCurBase+1, right);}/*5.选择排序*/template<class T>voidselectSort(T datalist[], const int nLeft, const int nRight){for (int i=nLeft; i<nRight; i++){int minIndex = i;for (int j=i; j<=nRight; j++){if (datalist[j] < datalist[minIndex]){minIndex = j;}}if (minIndex != i){T tmp = datalist[i];datalist[i] = datalist[minIndex];datalist[minIndex] = tmp;}}}/*6.归并排序*/template<class T>void merge(T datalist[], int nLeft, int nMid, int nRight){int nLenLeft = nMid - nLeft + 1;int nLenRight = nRight - nMid;T *pLeft = new T[nLenLeft];T *pRight = new T[nLenRight];int i=0;int j=0;for ( i=0; i<nLenLeft; i++){pLeft[i] = datalist[i+nLeft];}for ( j=0; j<nLenRight; j++){pRight[j] = datalist[nMid+j+1];}i=0;j=0;int k = nLeft;for (k=nLeft; k<nRight; k++){if (!(i<nLenLeft && j <nLenRight)){break;}if (pLeft[i]<pRight[j]){datalist[k] = pLeft[i];i++;}else{datalist[k] = pRight[j];j++;}}while(i<nLenLeft){datalist[k++] = pLeft[i];i++;}while(j<nLenRight){datalist[k++] = pRight[j];j++;}if (pLeft){delete []pLeft;pLeft = NULL;}if (pRight){delete [] pRight;pRight = NULL;}}template<class T>void mergeSort(T datalist[], int nLeft, int nRight){if (nLeft>=nRight){return;}int nMid = (nRight+nLeft)/2;mergeSort(datalist, nLeft, nMid);mergeSort(datalist, nMid+1, nRight);merge(datalist, nLeft, nMid, nRight);}/*7.冒泡排序应该是最垃圾的一种排序算法，而选择排序是冒泡排序的一种升级2014年2月18日18:16:58*/template<class T>void paopaoSort(T datalist[], int nLeft, int nRight){for (int i=nLeft; i<nRight; i++){for (int j=i+1; j<=nRight; j++){if (datalist[j] < datalist[i]){T tmp = datalist[i];datalist[i] = datalist[j];datalist[j] = tmp;}}}}/*8.分配排序之桶式排序*//*9.分配排序之基数排序*//*内部排序算法的分析*///sort.hpp 完

 

//main.cpp -------------------------------------------------------------------------------------------------------------------#include "sort.hpp"template<class T>void show(T *p, int nlen){for (int i=0; i<nlen; i++){std::cout<<p[i]<<"-";}std::cout<<std::endl;}int a[]={2,3,4,5,4,3,3,3,4,5,6,5,3,56,7,7,5,3};int b[]={2,3,4,5,4,3,3,3,4,5,6,5,3,56,7,7,5,3};int c[]={2,3,4,5,4,3,3,3,4,5,6,5,3,56,7,7,5,3};int d[]={2,3,4,5,4,3,3,3,4,5,6,5,3,56,7,7,5,3};int e[]={2,3,4,5,4,3,3,3,4,5,6,5,3,56,7,7,5,3};int f[]={2,3,4,5,4,3,3,3,4,5,6,5,3,56,7,7,5,3};int g[]={2,3,4,5,4,3,3,3,4,5,6,5,3,56,7,7,5,3};int _tmain(int argc, _TCHAR* argv[]){int nLen = sizeof(a)/sizeof(int);insertSort(a, 0, nLen-1);show<int>(a, nLen);binaryInsertSort<int>(b, 0, nLen-1);show<int>(b, nLen);shellSort<int>(c, 0, nLen-1);show<int>(c, nLen);quickSort<int>(d, 0, nLen-1);show<int>(d, nLen);selectSort<int>(e, 0, nLen-1);show<int>(e, nLen);mergeSort<int>(f, 0, nLen-1);show<int>(f, nLen);paopaoSort<int>(g, 0, nLen-1);show<int>(g, nLen);return 0;}//main.cpp完

输出结果：

2-3-3-3-3-3-3-4-4-4-5-5-5-5-6-7-7-56-
3-3-3-2-3-4-3-4-5-3-5-4-5-5-7-6-7-56-
2-3-3-3-3-3-3-4-4-4-5-5-5-5-6-7-7-56-
2-3-3-3-3-3-3-4-4-4-5-5-5-5-6-7-7-56-
2-3-3-3-3-3-3-4-4-4-5-5-5-5-6-7-7-56-
2-3-3-3-3-3-3-4-4-4-5-5-5-5-6-7-7-56-
2-3-3-3-3-3-3-4-4-4-5-5-5-5-6-7-7-56-
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