c++测试

1.vector deque排序效率对比

bool sortbydesc(int a, int b){    return a > b;}void funcsorttest(){    std::deque<int> quetest;    vector<int> vttest;    srand(time(NULL));    for (int i = 0; i < 150000; ++i)    {        int tmp = rand();        quetest.push_back(tmp);        vttest.push_back(tmp);        //printf("%d ", tmp);    }    //printf("\n");    time_t timer = time(NULL);    struct tm *tblock = localtime(&timer);    printf("ctime is %d\n", tblock->tm_sec);//得到日历时间    sort(quetest.begin(), quetest.end(), sortbydesc);    timer = time(NULL);    tblock = localtime(&timer);    printf("ctime is %d\n", tblock->tm_sec);//得到日历时间        timer = time(NULL);    tblock = localtime(&timer);    printf("ctime vec is %d\n", tblock->tm_sec);//得到日历时间    sort(vttest.begin(), vttest.end(), sortbydesc);    timer = time(NULL);    tblock = localtime(&timer);    printf("ctime vec is %d\n", tblock->tm_sec);//得到日历时间    /*for (int i = 0; i < 150; i++)    {           printf("%d ", vttest[i]);    }    printf("\n\n\n");    while (quetest.size() > 0)    {              printf("%d ", quetest.front());        quetest.pop_front();    }    printf("\n");*/    return ;}

window运行结果<img 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linux运行结果<img src="data:image/png;base64,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" alt="" />