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convert-sorted-array-to-binary-search-tree.py
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convert-sorted-array-to-binary-search-tree.py
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# Time: O(n)
# Space: O(logn)
#
# Given an array where elements are sorted in ascending order,
# convert it to a height balanced BST.
#
# Definition for a binary tree node
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
# @param num, a list of integers
# @return a tree node
def sortedArrayToBST(self, num):
return self.sortedArrayToBSTRecu(num, 0, len(num))
@staticmethod
def perfect_tree_pivot(n):
"""
Find the point to partition n keys for a perfect binary search tree
"""
x = 1
# find a power of 2 <= n//2
# while x <= n//2: # this loop could probably be written more elegantly :)
# x *= 2
x = 1 << (n.bit_length() - 1) # use the left bit shift, same as multiplying x by 2**n-1
if x // 2 - 1 <= (n - x):
return x - 1 # case 1: the left subtree of the root is perfect and the right subtree has less nodes
else:
return n - x // 2 # case 2 == n - (x//2 - 1) - 1 : the left subtree of the root
# has more nodes and the right subtree is perfect.
def sortedArrayToBSTRecu(self, num, start, end):
if start == end:
return None
mid = start + self.perfect_tree_pivot(end - start)
node = TreeNode(num[mid])
node.left = self.sortedArrayToBSTRecu(num, start, mid)
node.right = self.sortedArrayToBSTRecu(num, mid + 1, end)
return node
if __name__ == "__main__":
num = [1, 2, 3]
result = Solution().sortedArrayToBST(num)
print result.val
print result.left.val
print result.right.val