LeetCode #295

# Description:

Median is the middle value in an ordered integer list. If the size of the list is even, there is no middle value. So the median is the mean of the two middle value.

## Example:

``````Examples:
[2,3,4] , the median is 3

[2,3], the median is (2 + 3) / 2 = 2.5

Design a data structure that supports the following two operations:

void addNum(int num) - Add a integer number from the data stream to the data structure.
double findMedian() - Return the median of all elements so far.
For example:

findMedian() -> 1.5
findMedian() -> 2
``````

# Idea:

max_heap存小的一半，min_heap存大的一半，保持两个size相同，或者max_heap比min_heap多一个。

# Code:

``````class MedianFinder {
public:
/** initialize your data structure here. */
MedianFinder() {

}

if(max_heap.empty()){
max_heap.push(num);
return;
}

if(num<=max_heap.top()){
max_heap.push(num);
}
else{
min_heap.push(num);
}

// 注意， heap.size() is unsigned int!!!
if(max_heap.size() > min_heap.size() + 1){
int val = max_heap.top();
max_heap.pop();
min_heap.push(val);
}
else if(min_heap.size() > max_heap.size()){
int val = min_heap.top();
min_heap.pop();
max_heap.push(val);
}

}

double findMedian() {
if(max_heap.size()==min_heap.size()){
return (max_heap.top() + min_heap.top())/2.0;
}
else
return max_heap.top();

}
private:
priority_queue<int> max_heap;
priority_queue<int, vector<int>, greater<int> > min_heap;
};
``````