191. Number of 1 Bits

Problem

Given a positive integer n, write a function that returns the number of set bits in its binary representation (also known as the Hamming weight).

A set bit refers to a bit in the binary representation of a number that has a value of 1.

https://leetcode.com/problems/number-of-1-bits/

Example 1:

Input: n = 11
Output: 3
Explanation:
The input binary string 1011 has a total of three set bits.

Example 2:

Input: n = 128
Output: 1
Explanation:
The input binary string 10000000 has a total of one set bit.

Example 3:

Input: n = 2147483645
Output: 30
Explanation:
The input binary string 1111111111111111111111111111101 has a total of thirty set bits.

Constraints:

1 <= n <= 2³¹ - 1

Follow up: If this function is called many times, how would you optimize it?

Test Cases

solution_test.py下载完整源码
py
import pytest

from solution import Solution
from solution2 import Solution as Solution2
from solution3 import Solution as Solution3


@pytest.mark.parametrize('n, expected', [
    (11, 3),
    (128, 1),
    (2147483645, 30),
])
class Test:
    def test_solution(self, n, expected):
        sol = Solution()
        assert sol.hammingWeight(n) == expected

    def test_solution2(self, n, expected):
        sol = Solution2()
        assert sol.hammingWeight(n) == expected

    def test_solution3(self, n, expected):
        sol = Solution3()
        assert sol.hammingWeight(n) == expected

Thoughts

判断最低位是否是 1，然后右移一位，直到数字变为 0。

Code

python
class Solution:
    def hammingWeight(self, n: int) -> int:

solution.py下载完整源码
py
class Solution:
    def hammingWeight(self, n: int) -> int:
        cnt = 0
        while n > 0:
            cnt += n & 1
            n >>= 1

        return cnt

Faster

考虑更「二进制」的计算方法。

对于一个 4 bits 二进制数，一共 16 个不同的数字，每个数字中 1 的个数可以先算好，保存在数组中，数组下标就是数字本身。

对于一个 32 bits 二进制数，可以分成 8 段，每段是一个 4 bit 二进制数，直接查表得到这一段内 1 的个数，8 段的结果累加即可。

solution2.py下载完整源码
py
class Solution:
    def hammingWeight(self, n: int) -> int:
        table = [
            0, 1, 1, 2,
            1, 2, 2, 3,
            1, 2, 2, 3,
            2, 3, 3, 4,
        ]
        cnt = 0
        while n > 0:
            cnt += table[n & 0x0f]
            n >>= 4

        return cnt

Another Way

回到开始的循环移位法，循环次数跟 n 的位数一致。看有没有可能没循环一次都去掉一个 1。

对于奇数 n，最低位是 1，那么 n - 1 的最低位变成 0，而所有的高位都不变。二者取 bit-and，结果会少一个 1。

对于偶数 n（大于 0），最低位是 0，那么 n - 1 会把最低的连续的 0 都变成 1，而原来最后一个 1 变成 0（如 0b1011100 - 1 = 0b1011011），再和 n 取 bit-and，原来最后一个 1 以及所有的低位都会变成 0（如 0b1011100 & 0b1011011 = 0b1011000）。

这样每次都让 n 和 n - 1 取 bit-and，每次会去掉最后一个 1，直到得到 0。

循环的次数跟 n 中 1 的个数一致。

solution3.py下载完整源码
py
class Solution:
    def hammingWeight(self, n: int) -> int:
        cnt = 0
        while n > 0:
            cnt += 1
            n &= n - 1

        return cnt

#Problem

#Test Cases

#Thoughts

#Code

#Faster

#Another Way