2588. Count the Number of Beautiful Subarrays

Description

You are given a 0-indexed integer array nums. In one operation, you can:

• Choose two different indices i and j such that 0 <= i, j < nums.length.
• Choose a non-negative integer k such that the kth bit (0-indexed) in the binary representation of nums[i] and nums[j] is 1.
• Subtract 2k from nums[i] and nums[j].

A subarray is beautiful if it is possible to make all of its elements equal to 0 after applying the above operation any number of times.

Return the number of beautiful subarrays in the array nums.

A subarray is a contiguous non-empty sequence of elements within an array.

 

Example 1:

Input: nums = [4,3,1,2,4]
Output: 2
Explanation: There are 2 beautiful subarrays in nums: [4,3,1,2,4] and [4,3,1,2,4].
- We can make all elements in the subarray [3,1,2] equal to 0 in the following way:
  - Choose [3, 1, 2] and k = 1. Subtract 21 from both numbers. The subarray becomes [1, 1, 0].
  - Choose [1, 1, 0] and k = 0. Subtract 20 from both numbers. The subarray becomes [0, 0, 0].
- We can make all elements in the subarray [4,3,1,2,4] equal to 0 in the following way:
  - Choose [4, 3, 1, 2, 4] and k = 2. Subtract 22 from both numbers. The subarray becomes [0, 3, 1, 2, 0].
  - Choose [0, 3, 1, 2, 0] and k = 0. Subtract 20 from both numbers. The subarray becomes [0, 2, 0, 2, 0].
  - Choose [0, 2, 0, 2, 0] and k = 1. Subtract 21 from both numbers. The subarray becomes [0, 0, 0, 0, 0].

Example 2:

Input: nums = [1,10,4]
Output: 0
Explanation: There are no beautiful subarrays in nums.

 

Constraints:

• 1 <= nums.length <= 105
• 0 <= nums[i] <= 106

Solutions

Solution 1: Prefix XOR + Hash Table

We observe that a subarray can become an array of all $0$s if and only if the number of $1$s on each binary bit of all elements in the subarray is even.

If there exist indices $i$ and $j$ such that $i \lt j$ and the subarrays $nums[0,..,i]$ and $nums[0,..,j]$ have the same parity of the number of $1$s on each binary bit, then we can turn the subarray $nums[i + 1,..,j]$ into an array of all $0$s.

Therefore, we can use the prefix XOR method and a hash table $cnt$ to count the occurrences of each prefix XOR value. We traverse the array, for each element $x$, we calculate its prefix XOR value $mask$, then add the number of occurrences of $mask$ to the answer. Then, we increase the number of occurrences of $mask$ by $1$.

Finally, we return the answer.

The time complexity is $O(n)$, and the space complexity is $O(n)$. Here, $n$ is the length of the array $nums$.

Python3JavaC++GoTypeScript

class Solution:
    def beautifulSubarrays(self, nums: List[int]) -> int:
        cnt = Counter({0: 1})
        ans = mask = 0
        for x in nums:
            mask ^= x
            ans += cnt[mask]
            cnt[mask] += 1
        return ans

class Solution {
    public long beautifulSubarrays(int[] nums) {
        Map<Integer, Integer> cnt = new HashMap<>();
        cnt.put(0, 1);
        long ans = 0;
        int mask = 0;
        for (int x : nums) {
            mask ^= x;
            ans += cnt.getOrDefault(mask, 0);
            cnt.merge(mask, 1, Integer::sum);
        }
        return ans;
    }
}

class Solution {
public:
    long long beautifulSubarrays(vector<int>& nums) {
        unordered_map<int, int> cnt{{0, 1}};
        long long ans = 0;
        int mask = 0;
        for (int x : nums) {
            mask ^= x;
            ans += cnt[mask];
            ++cnt[mask];
        }
        return ans;
    }
};

func beautifulSubarrays(nums []int) (ans int64) {
    cnt := map[int]int{0: 1}
    mask := 0
    for _, x := range nums {
        mask ^= x
        ans += int64(cnt[mask])
        cnt[mask]++
    }
    return
}

function beautifulSubarrays(nums: number[]): number {
    const cnt = new Map();
    cnt.set(0, 1);
    let ans = 0;
    let mask = 0;
    for (const x of nums) {
        mask ^= x;
        ans += cnt.get(mask) || 0;
        cnt.set(mask, (cnt.get(mask) || 0) + 1);
    }
    return ans;
}

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