
Number of Subsequences That Satisfy the Given Sum Condition
6 May, 2023
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Problem Statement:-
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 modulo 10
9
+ 7
.
Problem Explanation with examples:-
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 <= 10
5
1 <= nums[i] <= 10
6
1 <= target <= 10
6
Intuition:-
- As we only need the min and max values of the subsequence, we can sort the array because the order doesn't matter.
- Now we can use two pointer approach to find the subsequence with a sum less than or equal to the target.
- Now we can use the formula 2**(r-l+1) to find the number of subsequences possible within the range of l and r.
- We can use a mod to avoid overflow. Return the result.
Solution:-
- Sort the array.
- Create two pointers l and r and initialize them to 0 and len(nums)-1 respectively.
- Run a loop until l <= r.
- If nums[l] + nums[r] > target, decrement r.
- Else increment l and add (2**(r-l+1))%mod to res.
- Return res%mod.
Code:-
JAVA Solution
class Solution {
public int numSubseq(int[] nums, int target) {
int mod = (int)Math.pow(10, 9) + 7;
int l = 0;
int r = nums.length - 1;
Arrays.sort(nums);
int res = 0;
while (l <= r) {
if (nums[l] + nums[r] > target) {
r--;
} else {
l++;
res += (int)(Math.pow(2, r - l) % mod);
}
}
return res % mod;
}
}
Python Solution
class Solution:
def numSubseq(self, nums: List[int], target: int) -> int:
mod = 10**9 + 7
l = 0
r = len(nums)-1
nums.sort()
res = 0
while l <= ra:
if nums[l] + nums[r] > target:
r -= 1
else:
l += 1
res += (2**(r-l))%mod
return res%mod
Complexity Analysis:-
TIME:-
The time complexity is O(nlogn) + O(n) = O(nlogn) where n is the length of nums. O(nlogn) for sorting and O(n) for two pointer approach.
SPACE:-
The space complexity is O(1) as we use constant extra space.
References:-
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