Subsets
- leetcode: Subsets
- lintcode:
Given a set of distinct integers, nums, return all possible subsets.
Note: The solution set must not contain duplicate subsets.
For example,
If nums = , a solution is:
[1] -> [1, 2] -> [1, 2, 3]
[2] -> [2, 3]
[3]
将上述过程转化为代码即为对数组遍历,每一轮都保存之前的结果并将其依次加入到最终返回结果中。
Iterative
Python
class Solution:
"""
@param S: The set of numbers.
@return: A list of lists. See example.
"""
def subsets(self, S):
if not S:
return []
S.sort()
n = len(S)
# 000 -> []
# 001 -> [1]
# 010 -> [2]
# ...
# 111 -> [1, 2, 3]
for i in xrange(2**n):
tmp = []
for j in xrange(n):
if i & (1 << j):
tmp.append(S[j])
ret.append(tmp)
return ret
利用类似bit map
的原理, 将 0 ~ 2^n - 1个数值map到每个index上,如果index数值为1,就将该number加入。比如输入是[1 ,2 ,3]
, 那么当时,0
也就是000
, 那么000 -> []
; 当i = 1
时, 001 -> [1]
; 直到i = 7
, 111 -> [1, 2, 3]
.
Recursive
Python
less code style
class Solution:
"""
@param S: The set of numbers.
@return: A list of lists. See example.
"""
def subsets(self, S):
ret = []
self.helper(sorted(S), ret, [])
return ret
def helper(self, vals, ret, tmp):
ret.append(tmp[:])
for i, val in enumerate(vals):
Java
public class Solution {
public List<List<Integer>> subsets(int[] nums) {
List<List<Integer>> result = new ArrayList<List<Integer>>();
List<Integer> list = new ArrayList<Integer>();
if (nums == null || nums.length == 0) {
return result;
}
dfs(nums, 0, list, result);
return result;
}
private void dfs(int[] nums, int pos, List<Integer> list,
List<List<Integer>> ret) {
// add temp result first
ret.add(new ArrayList<Integer>(list));
for (int i = pos; i < nums.length; i++) {
list.add(nums[i]);
dfs(nums, i + 1, list, ret);
list.remove(list.size() - 1);
}
}
}
源码分析
Java 和 Python 的代码中在将临时list 添加到最终结果时新生成了对象,(Python 使用[] +
), 否则最终返回结果将随着list
的变化而变化。
回溯法可用图示和函数运行的堆栈图来理解,强烈建议使用图形和递归的思想分析,以数组[1, 2, 3]
进行分析。下图所示为list
及result
动态变化的过程,箭头向下表示list.add
及result.add
操作,箭头向上表示list.remove
操作。
对原有数组排序,时间复杂度近似为 O(n \log n). 状态数为所有可能的组合数 O(2^n), 生成每个状态所需的时间复杂度近似为 O(1), 如[1] -> [1, 2]
, 故总的时间复杂度近似为 O(2^n).