Counting Bits
update Jul3, 2017 11:13
Given a non negative integer number num. For every numbers i in the range 0 ≤ i ≤ num calculate the number of 1's in their binary representation and return them as an array.
Example:
For num = 5 you should return [0,1,1,2,1,2].
Follow up:
It is very easy to come up with a solution with run time O(n*sizeof(integer)). But can you do it in linear time O(n) /possibly in a single pass? Space complexity should be O(n). Can you do it like a boss? Do it without using any builtin function like __builtin_popcount
in c++ or in any other language.
Basic Idea:
仔细观察二进制数的规律就会发现有如下关系:
`dp[i] = dp[i / 2] when i % 2 == 0`
`else dp[i] = dp[i / 2] + 1`
利用这点性质,我们就可以得出我们的 O(n) dp 算法。
Python Code:
class Solution(object):
def countBits(self, num):
"""
:type num: int
:rtype: List[int]
"""
res = [0] * (num + 1)
for i in range(1, len(res)):
res[i] = res[i / 2] if i % 2 == 0 else res[i / 2] + 1
return res