295. Find Median from Data Stream【H】【2.7】

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.

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:

add(1)add(2)findMedian() -> 1.5add(3) findMedian() -> 2

Credits:
Special thanks to @Louis1992 for adding this problem and creating all test cases.

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关键有两个，一个是使用最小堆

另一个是，算法上，把整个分成两部分，一个装较小的一半儿，一个装较大的一半儿

from heapq import *

class MedianFinder:

    def __init__(self):

        self.small = []

        self.large = []

        """

        Initialize your data structure here.

        """

    def addNum(self, num):

        s = self.small

        l = self.large

        if len(s) + len(l) < 2:

            if len(l) == 0:

                heappush(l,num)

            else:

                heappush(s,-heappushpop(l,num))

            return

        a = -heappop(s)

        b = heappop(l)

        maxx = max(a,max(b,num))

        minn = min(a,min(b,num))

        num = a + b + num - minn - maxx

        heappush(l,num)

        heappush(l,maxx)

        heappush(s,-minn)

        if len(s) < len(l) - 1:

            heappush(s, -heappop(l))

        """

        Adds a num into the data structure.

        :type num: int

        :rtype: void

        """

    def findMedian(self):

        s = self.small

        l = self.large

        if len(s) == len(l):

            return (l[0] - s[0]) / 2.0

        return l[0]/1.0

        """

        Returns the median of current data stream

        :rtype: float

        """

# Your MedianFinder object will be instantiated and called as such:

# mf = MedianFinder()

# mf.addNum(1)

# mf.findMedian()