90. Subsets II

Description

Given an integer array nums that may contain duplicates, return all possible subsets (the power set).

The solution set must not contain duplicate subsets. Return the solution in any order.

Example 1:

Input: nums = [1,2,2]
Output: [[],[1],[1,2],[1,2,2],[2],[2,2]]

Example 2:

Input: nums = [0]
Output: [[],[0]]

Constraints:

1 <= nums.length <= 10
-10 <= nums[i] <= 10

Solutions

Solution 1: Sorting + DFS

We can first sort the array $nums$ to facilitate deduplication.

Then, we design a function $dfs(i)$, which represents searching for subsets starting from the $i$-th element. The execution logic of the function $dfs(i)$ is as follows:

If $i \geq n$, it means that all elements have been searched, and the current subset is added to the answer array, and the recursion ends.

If $i < n$, add the $i$-th element to the subset, execute $dfs(i + 1)$, and then remove the $i$-th element from the subset. Next, we judge whether the $i$-th element is the same as the next element. If it is the same, we loop to skip this element until we find the first element that is different from the $i$-th element, and execute $dfs(i + 1)$.

Finally, we only need to call $dfs(0)$ and return the answer array.

The time complexity is $O(n \times 2^n)$, and the space complexity is $O(n)$. Here, $n$ is the length of the array.

Python Code

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class Solution:
    def subsetsWithDup(self, nums: List[int]) -> List[List[int]]:
        def dfs(i: int):
            if i == len(nums):
                ans.append(t[:])
                return
            t.append(nums[i])
            dfs(i + 1)
            x = t.pop()
            while i + 1 < len(nums) and nums[i + 1] == x:
                i += 1
            dfs(i + 1)

        nums.sort()
        ans = []
        t = []
        dfs(0)
        return ans

Java Code

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class Solution {
    private List<List<Integer>> ans = new ArrayList<>();
    private List<Integer> t = new ArrayList<>();
    private int[] nums;

    public List<List<Integer>> subsetsWithDup(int[] nums) {
        Arrays.sort(nums);
        this.nums = nums;
        dfs(0);
        return ans;
    }

    private void dfs(int i) {
        if (i >= nums.length) {
            ans.add(new ArrayList<>(t));
            return;
        }
        t.add(nums[i]);
        dfs(i + 1);
        int x = t.remove(t.size() - 1);
        while (i + 1 < nums.length && nums[i + 1] == x) {
            ++i;
        }
        dfs(i + 1);
    }
}

C++ Code

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class Solution {
public:
    vector<vector<int>> subsetsWithDup(vector<int>& nums) {
        sort(nums.begin(), nums.end());
        vector<vector<int>> ans;
        vector<int> t;
        int n = nums.size();
        function<void(int)> dfs = [&](int i) {
            if (i >= n) {
                ans.push_back(t);
                return;
            }
            t.push_back(nums[i]);
            dfs(i + 1);
            t.pop_back();
            while (i + 1 < n && nums[i + 1] == nums[i]) {
                ++i;
            }
            dfs(i + 1);
        };
        dfs(0);
        return ans;
    }
};

Go Code

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func subsetsWithDup(nums []int) (ans [][]int) {
	sort.Ints(nums)
	n := len(nums)
	t := []int{}
	var dfs func(int)
	dfs = func(i int) {
		if i >= n {
			ans = append(ans, slices.Clone(t))
			return
		}
		t = append(t, nums[i])
		dfs(i + 1)
		t = t[:len(t)-1]
		for i+1 < n && nums[i+1] == nums[i] {
			i++
		}
		dfs(i + 1)
	}
	dfs(0)
	return
}

TypeScript Code

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function subsetsWithDup(nums: number[]): number[][] {
    nums.sort((a, b) => a - b);
    const n = nums.length;
    const t: number[] = [];
    const ans: number[][] = [];
    const dfs = (i: number): void => {
        if (i >= n) {
            ans.push([...t]);
            return;
        }
        t.push(nums[i]);
        dfs(i + 1);
        t.pop();
        while (i + 1 < n && nums[i] === nums[i + 1]) {
            i++;
        }
        dfs(i + 1);
    };
    dfs(0);
    return ans;
}

Rust Code

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impl Solution {
    pub fn subsets_with_dup(nums: Vec<i32>) -> Vec<Vec<i32>> {
        let mut nums = nums;
        nums.sort();
        let mut ans = Vec::new();
        let mut t = Vec::new();

        fn dfs(i: usize, nums: &Vec<i32>, t: &mut Vec<i32>, ans: &mut Vec<Vec<i32>>) {
            if i >= nums.len() {
                ans.push(t.clone());
                return;
            }
            t.push(nums[i]);
            dfs(i + 1, nums, t, ans);
            t.pop();
            let mut i = i;
            while i + 1 < nums.len() && nums[i + 1] == nums[i] {
                i += 1;
            }
            dfs(i + 1, nums, t, ans);
        }

        dfs(0, &nums, &mut t, &mut ans);
        ans
    }
}

Solution 2: Sorting + Binary Enumeration

Similar to Solution 1, we first sort the array $nums$ to facilitate deduplication.

Next, we enumerate a binary number $mask$ in the range of $[0, 2^n)$, where the binary representation of $mask$ is an $n$-bit bit string. If the $i$-th bit of $mask$ is $1$, it means to select $nums[i]$, and $0$ means not to select $nums[i]$. Note that if the $i - 1$ bit of $mask$ is $0$, and $nums[i] = nums[i - 1]$, it means that in the current enumerated scheme, the $i$-th element and the $i - 1$-th element are the same. To avoid repetition, we skip this situation. Otherwise, we add the subset corresponding to $mask$ to the answer array.

After the enumeration ends, we return the answer array.