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find-median-from-data-stream.py 1.20 KB
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Allen Liu 提交于 2018-10-13 13:24 +08:00 . update
# Time: O(nlogn) for total n addNums, O(logn) per addNum, O(1) per findMedian.
# Space: O(n), total space
from heapq import heappush, heappop
class MedianFinder(object):
def __init__(self):
"""
Initialize your data structure here.
"""
self.__max_heap = []
self.__min_heap = []
def addNum(self, num):
"""
Adds a num into the data structure.
:type num: int
:rtype: void
"""
# Balance smaller half and larger half.
if not self.__max_heap or num > -self.__max_heap[0]:
heappush(self.__min_heap, num)
if len(self.__min_heap) > len(self.__max_heap) + 1:
heappush(self.__max_heap, -heappop(self.__min_heap))
else:
heappush(self.__max_heap, -num)
if len(self.__max_heap) > len(self.__min_heap):
heappush(self.__min_heap, -heappop(self.__max_heap))
def findMedian(self):
"""
Returns the median of current data stream
:rtype: float
"""
return (-self.__max_heap[0] + self.__min_heap[0]) / 2.0 \
if len(self.__min_heap) == len(self.__max_heap) \
else self.__min_heap[0]
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