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# Copyright 2016 Egor Tensin <Egor.Tensin@gmail.com>
# This file is licensed under the terms of the MIT License.
# See LICENSE.txt for details.
from heapq import *
def calc_median_heaps(xs):
cur_median = 0.0
min_heap, max_heap = [], []
for x in xs:
if x < cur_median:
heappush(max_heap, -x)
elif x > cur_median or len(max_heap) > len(min_heap):
heappush(min_heap, x)
else:
heappush(max_heap, -x)
if len(max_heap) > len(min_heap) + 1:
heappush(min_heap, -heappop(max_heap))
elif len(min_heap) > len(max_heap) + 1:
heappush(max_heap, -heappop(min_heap))
if len(max_heap) > len(min_heap):
cur_median = -max_heap[0]
elif len(max_heap) == len(min_heap):
cur_median = -max_heap[0] / 2 + min_heap[0] / 2
else:
cur_median = min_heap[0]
return cur_median
def calc_median_sort_first(xs):
if not xs:
return 0.0
xs.sort()
if len(xs) % 2:
return xs[len(xs) // 2]
else:
return xs[len(xs) // 2 - 1] / 2 + xs[len(xs) // 2] / 2
if __name__ == '__main__':
import sys
xs = list(map(int, sys.argv[1:]))
print(calc_median_sort_first(list(xs)))
print(calc_median_heaps(list(xs)))
else:
from algorithms.algorithm import Algorithm
_ALGORITHMS = [
Algorithm('median_sort_first', 'Median (input is sorted first)', calc_median_sort_first),
Algorithm('median_heaps', 'Median (using heaps)', calc_median_heaps),
]
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