2670. Find the Distinct Difference Array

Description

You are given a 0-indexed array nums of length n.

The distinct difference array of nums is an array diff of length n such that diff[i] is equal to the number of distinct elements in the suffix nums[i + 1, ..., n - 1] subtracted from the number of distinct elements in the prefix nums[0, ..., i].

Return the distinct difference array of nums.

Note that nums[i, ..., j] denotes the subarray of nums starting at index i and ending at index j inclusive. Particularly, if i > j then nums[i, ..., j] denotes an empty subarray.

Example 1:

Input: nums = [1,2,3,4,5]
Output: [-3,-1,1,3,5]
Explanation: For index i = 0, there is 1 element in the prefix and 4 distinct elements in the suffix. Thus, diff[0] = 1 - 4 = -3.
For index i = 1, there are 2 distinct elements in the prefix and 3 distinct elements in the suffix. Thus, diff[1] = 2 - 3 = -1.
For index i = 2, there are 3 distinct elements in the prefix and 2 distinct elements in the suffix. Thus, diff[2] = 3 - 2 = 1.
For index i = 3, there are 4 distinct elements in the prefix and 1 distinct element in the suffix. Thus, diff[3] = 4 - 1 = 3.
For index i = 4, there are 5 distinct elements in the prefix and no elements in the suffix. Thus, diff[4] = 5 - 0 = 5.

Example 2:

Input: nums = [3,2,3,4,2]
Output: [-2,-1,0,2,3]
Explanation: For index i = 0, there is 1 element in the prefix and 3 distinct elements in the suffix. Thus, diff[0] = 1 - 3 = -2.
For index i = 1, there are 2 distinct elements in the prefix and 3 distinct elements in the suffix. Thus, diff[1] = 2 - 3 = -1.
For index i = 2, there are 2 distinct elements in the prefix and 2 distinct elements in the suffix. Thus, diff[2] = 2 - 2 = 0.
For index i = 3, there are 3 distinct elements in the prefix and 1 distinct element in the suffix. Thus, diff[3] = 3 - 1 = 2.
For index i = 4, there are 3 distinct elements in the prefix and no elements in the suffix. Thus, diff[4] = 3 - 0 = 3.

Constraints:

1 <= n == nums.length <= 50
1 <= nums[i] <= 50

Solutions

Solution 1: Hash Table + Preprocessed Suffix

We can preprocess a suffix array $suf$, where $suf[i]$ represents the number of distinct elements in the suffix $nums[i, ..., n - 1]$. During the preprocessing, we use a hash table $s$ to maintain the elements that have appeared in the suffix, so we can query the number of distinct elements in the suffix in $O(1)$ time.

After preprocessing the suffix array $suf$, we clear the hash table $s$, and then traverse the array $nums$ again, using the hash table $s$ to maintain the elements that have appeared in the prefix. The answer at position $i$ is the number of distinct elements in $s$ minus $suf[i + 1]$, that is, $s.size() - suf[i + 1]$.

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

Python3JavaC++GoTypeScriptRust

class Solution:
    def distinctDifferenceArray(self, nums: List[int]) -> List[int]:
        n = len(nums)
        suf = [0] * (n + 1)
        s = set()
        for i in range(n - 1, -1, -1):
            s.add(nums[i])
            suf[i] = len(s)
        s.clear()
        ans = [0] * n
        for i, x in enumerate(nums):
            s.add(x)
            ans[i] = len(s) - suf[i + 1]
        return ans

class Solution {
    public int[] distinctDifferenceArray(int[] nums) {
        int n = nums.length;
        int[] suf = new int[n + 1];
        Set<Integer> s = new HashSet<>();
        for (int i = n - 1; i >= 0; --i) {
            s.add(nums[i]);
            suf[i] = s.size();
        }
        s.clear();
        int[] ans = new int[n];
        for (int i = 0; i < n; ++i) {
            s.add(nums[i]);
            ans[i] = s.size() - suf[i + 1];
        }
        return ans;
    }
}

class Solution {
public:
    vector<int> distinctDifferenceArray(vector<int>& nums) {
        int n = nums.size();
        vector<int> suf(n + 1);
        unordered_set<int> s;
        for (int i = n - 1; i >= 0; --i) {
            s.insert(nums[i]);
            suf[i] = s.size();
        }
        s.clear();
        vector<int> ans(n);
        for (int i = 0; i < n; ++i) {
            s.insert(nums[i]);
            ans[i] = s.size() - suf[i + 1];
        }
        return ans;
    }
};

func distinctDifferenceArray(nums []int) []int {
    n := len(nums)
    suf := make([]int, n+1)
    s := map[int]bool{}
    for i := n - 1; i >= 0; i-- {
        s[nums[i]] = true
        suf[i] = len(s)
    }
    ans := make([]int, n)
    s = map[int]bool{}
    for i, x := range nums {
        s[x] = true
        ans[i] = len(s) - suf[i+1]
    }
    return ans
}

function distinctDifferenceArray(nums: number[]): number[] {
    const n = nums.length;
    const suf: number[] = Array(n + 1).fill(0);
    const s: Set<number> = new Set();
    for (let i = n - 1; i >= 0; --i) {
        s.add(nums[i]);
        suf[i] = s.size;
    }
    s.clear();
    const ans: number[] = Array(n).fill(0);
    for (let i = 0; i < n; ++i) {
        s.add(nums[i]);
        ans[i] = s.size - suf[i + 1];
    }
    return ans;
}

use std::collections::HashSet;

impl Solution {
    pub fn distinct_difference_array(nums: Vec<i32>) -> Vec<i32> {
        let n = nums.len();
        let mut suf = vec![0; n + 1];
        let mut s = HashSet::new();

        for i in (0..n).rev() {
            s.insert(nums[i]);
            suf[i] = s.len();
        }

        let mut ans = Vec::new();
        s.clear();
        for i in 0..n {
            s.insert(nums[i]);
            ans.push((s.len() - suf[i + 1]) as i32);
        }

        ans
    }
}

2670. Find the Distinct Difference Array

Description

Solutions

Solution 1: Hash Table + Preprocessed Suffix

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