You are given an array of integers nums and an integer target.
Return the number of non-empty subsequences of nums such that the sum of the minimum and maximum element on it is less or equal to target. Since the answer may be too large, return it modulo109 + 7.
Example 1:
Input: nums = [3,5,6,7], target = 9
Output: 4
Explanation: There are 4 subsequences that satisfy the condition.
[3] -> Min value + max value <= target (3 + 3 <= 9)
[3,5] -> (3 + 5 <= 9)
[3,5,6] -> (3 + 6 <= 9)
[3,6] -> (3 + 6 <= 9)
Example 2:
Input: nums = [3,3,6,8], target = 10
Output: 6
Explanation: There are 6 subsequences that satisfy the condition. (nums can have repeated numbers).
[3] , [3] , [3,3], [3,6] , [3,6] , [3,3,6]
Example 3:
Input: nums = [2,3,3,4,6,7], target = 12
Output: 61
Explanation: There are 63 non-empty subsequences, two of them do not satisfy the condition ([6,7], [7]).
Number of valid subsequences (63 - 2 = 61).
Constraints:
1 <= nums.length <= 105
1 <= nums[i] <= 106
1 <= target <= 106
Solutions
Solution 1: Sorting + Binary Search
Since the problem is about subsequences and involves the sum of the minimum and maximum elements, we can first sort the array \(\textit{nums}\).
Then we enumerate the minimum element \(\textit{nums}[i]\). For each \(\textit{nums}[i]\), we can find the maximum element \(\textit{nums}[j]\) in \(\textit{nums}[i + 1]\) to \(\textit{nums}[n - 1]\) such that \(\textit{nums}[i] + \textit{nums}[j] \leq \textit{target}\). The number of valid subsequences in this case is \(2^{j - i}\), where \(2^{j - i}\) represents all possible subsequences from \(\textit{nums}[i + 1]\) to \(\textit{nums}[j]\). We sum up the counts of all such subsequences.
The time complexity is \(O(n \times \log n)\), and the space complexity is \(O(n)\), where \(n\) is the length of the array \(\textit{nums}\).