295. Find Median from Data Stream [Hard] 大顶堆和小顶堆

原创于 2019-07-18 14:40:00 发布 · 150 阅读

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本文介绍了一种高效算法，用于处理不断变化的数据流并实时计算中位数。该算法利用两个堆数据结构来保持数据流中较小一半和较大一半数值的平衡。通过这种方式，可以在O(log n)时间内插入新元素，并在O(1)时间内查找中位数。

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295. Find Median from Data Stream

class MedianFinder(object):

    def __init__(self):
        """
        initialize your data structure here.
        """
        self.low = []
        self.high = []

    def addNum(self, num):
        """
        :type num: int
        :rtype: None
        """
        if len(self.low) == len(self.high):
            if len(self.low) == 0 or num < -self.low[0]:
                heapq.heappush(self.low, -num)
            else:
                heapq.heappush(self.high, num)
        elif len(self.low) > len(self.high):
            if num > -self.low[0]:
                heapq.heappush(self.high, num)
            else:
                temp = -self.low[0]
                heapq.heappop(self.low)
                heapq.heappush(self.low, -num)
                heapq.heappush(self.high, temp)
        else:
            if num > self.high[0]:
                temp = self.high[0]
                heapq.heappop(self.high)
                heapq.heappush(self.low, -temp)
                heapq.heappush(self.high, num)
            else:
                heapq.heappush(self.low, -num)

    def findMedian(self):
        """
        :rtype: float
        """
        if len(self.low) == len(self.high):
            return 0.5 * (self.high[0] - self.low[0])
        elif len(self.low) > len(self.high):
            return -self.low[0]
        else:
            return self.high[0]