现实生活中,人们处理的数字都是十进制的,但计算机中存储的都是二进制,因为了解二进制对于理解计算机很有帮助,同样的问题,换一个角度,可能就会有不一样的效果。
Calculate the sum of two integers a and b, but you are not allowed to use the operator + and -.
Example 1:
Input: a = 1, b = 2
Output: 3Example 2:
Input: a = -2, b = 3
Output: 1
Write a function that takes an unsigned integer and return the number of '1' bits it has(also knownas the Hamming weight).
Example 1:
Input: 00000000000000000000000000001011
Output: 3
Explanation: The input binary string 00000000000000000000000000001011 has a total of three '1' bits.
Example 2:
Input: 00000000000000000000000010000000
Output: 1
Explanation: The input binary string 00000000000000000000000010000000 has a total of one '1' bit.
Example 3:
Input: 11111111111111111111111111111101
Output: 31
Explanation: The input binary string 11111111111111111111111111111101 has a total of thirty one '1' bits.
最直观的方法就是遍历 32 位数字的每一位,查看是否为 1, 如果是1,输入数字中含 1-bit 的个数加1。
class Solution:
def hammingWeight(self, n: int) -> int:
retval = 0
for i in range(32):
if n & (1 << i):
retval = retval + 1
return retval
复杂度分析:
时间复杂度:O(1)
空间复杂度: O(1)
上面的方法是对给定整数的每一位进行了计算,如果输入是 0000000000000000000000000000001
,计算完第一位后,后面的所有操作不会增加1的个数,因为我们可以没检测完一位后,将该位置零,然后查看最后结果是否为零,如果为零,则中止计算即可。
class Solution:
def hammingWeight(self, n: int) -> int:
retval = 0
while n:
retval = retval + 1
n &= (n - 1)
return retval
复杂度分析:
时间复杂度:O(1)
空间复杂度: O(1)
利用python的内置函数完成,首先将输入的整数转换为字符串,然后计算字符串中 1 的个数。
class Solution:
def hammingWeight(self, n: int) -> int:
"""
:type n: int
:rtype: int
"""
binary_str_n = bin(n)
retval = binary_str_n.count('1')
return retval