1 基于快排中 partition函数的思想
一定要注意那里是对容器的地址 或者引用操作 否则传不出来!!!
public:
vector<int> GetLeastNumbers_Solution(vector<int> input, int k) {
vector<int> result;
if(input.empty() || k>input.size() || k<=0) return result;
int start = 0;
int end = input.size()-1;
int index = partition(input,start,end);
while(index != (k-1))
{
if(index > (k-1))
{
end = index - 1;
index = partition(input,start,end);
}
else
{
start = index + 1;
index = partition(input,start,end);
}
}
for(int i=0;i<k;++i)
{
result.push_back(input[i]);
}
return result;
}
int partition(vector<int> &numbers,int low,int high)
{
int pivotkey=numbers[low];//当参考值
while(low<high)
{
while(low<high&&numbers[high]>pivotkey)
{high--;}
swap(numbers[low],numbers[high]);
while(low<high&&numbers[low]<=pivotkey)
{ low++;}
swap(numbers[low],numbers[high]);
}
return low;
}
void swap(int &A,int &B)
{
int temp;
temp=A;
A=B;
B=temp;
}
方法2 基于muiltiset 红黑树 最大堆排序
// ====================方法2====================
typedef multiset<int, greater<int> > intSet;//greater函数和less相反,这个谓词
typedef multiset<int, greater<int> >::iterator setIterator;//设置迭代器
void GetLeastNumbers_Solution2(const vector<int>& data, intSet& leastNumbers, int k)
{
leastNumbers.clear();//清空
if (k < 1 || data.size() < k)
return;
vector<int>::const_iterator iter = data.begin();//vector迭代器
for (; iter != data.end(); ++iter)
{
if ((leastNumbers.size()) < k)
leastNumbers.insert(*iter);
else
{
setIterator iterGreatest = leastNumbers.begin();//multiset迭代器
if (*iter < *(leastNumbers.begin()))
{
leastNumbers.erase(iterGreatest);//删除该条目
leastNumbers.insert(*iter);//插入新的,自动排序
}
}
}
}