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binary_search.py
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#!/usr/bin/env python
class Solution(object):
def findMedianSortedArrays(self, nums1, nums2):
"""
:type nums1: List[int]
:type nums2: List[int]
:rtype: float
"""
# Make the list nums1 always longger than nums2
if len(nums1) < len(nums2):
nums1, nums2 = nums2, nums1
# Extented nums1 with element of nums2 by using binary search
for n in nums2:
x, y = self.get_median(nums1)
p = self.binary_search(nums1, x ,n)
nums1.insert(p, n)
# Get median
x, y = self.get_median(nums1)
if y == -1:
return float(nums1[x])
return (float(nums1[x]) + float(nums1[y] - nums1[x])/2.0)
def binary_search(self, array, m, n):
# Binary search with recursive
if len(array) == 1:
return (m+1) if n >= array[0] else m
if len(array) == 2:
if n < array[0]:
return 0
elif n > array[1]:
return 2
return 1
print "m={}, array_leng: {}".format(m, len(array))
if n == array[m]:
return (m+1)
if n > array[m]:
x, y = self.get_median(array[m+1:])
print "next array: {}".format(array[m+1:])
return self.binary_search(array[m+1:], x, n) + m + 1
x, y = self.get_median(array[:m])
print "next array: {}".format(array[:m])
return self.binary_search(array[:m], x, n)
def get_median(self, array):
if len(array) <= 1:
return 0, -1
if len(array)%2 == 0:
m = len(array)/2
return (m-1, m)
return (len(array)-1)/2, -1
if __name__ == "__main__":
obj = Solution()
print obj.findMedianSortedArrays([1,3], [2])
print obj.findMedianSortedArrays([1], [2, 3, 4, 5, 6, 7 ,8])
print obj.findMedianSortedArrays(range(55,90,3), range(100,600,7))
# vim: ts=4 sw=4 expandtab