The imbalance number of a 0-indexed integer array arr
of length n
is defined as the number of indices in sarr = sorted(arr)
such that:
0 <= i < n - 1
, andsarr[i+1] - sarr[i] > 1
Here, sorted(arr)
is the function that returns the sorted version of arr
.
Given a 0-indexed integer array nums
, return the sum of imbalance numbers of all its subarrays.
A subarray is a contiguous non-empty sequence of elements within an array.
Example 1:
Input: nums = [2,3,1,4] Output: 3 Explanation: There are 3 subarrays with non-zero imbalance numbers: - Subarray [3, 1] with an imbalance number of 1. - Subarray [3, 1, 4] with an imbalance number of 1. - Subarray [1, 4] with an imbalance number of 1. The imbalance number of all other subarrays is 0. Hence, the sum of imbalance numbers of all the subarrays of nums is 3.
Example 2:
Input: nums = [1,3,3,3,5] Output: 8 Explanation: There are 7 subarrays with non-zero imbalance numbers: - Subarray [1, 3] with an imbalance number of 1. - Subarray [1, 3, 3] with an imbalance number of 1. - Subarray [1, 3, 3, 3] with an imbalance number of 1. - Subarray [1, 3, 3, 3, 5] with an imbalance number of 2. - Subarray [3, 3, 3, 5] with an imbalance number of 1. - Subarray [3, 3, 5] with an imbalance number of 1. - Subarray [3, 5] with an imbalance number of 1. The imbalance number of all other subarrays is 0. Hence, the sum of imbalance numbers of all the subarrays of nums is 8.
Constraints:
1 <= nums.length <= 1000
1 <= nums[i] <= nums.length
We can first enumerate the left endpoint
For each number
- If
$nums[k]$ exists, and the difference between$nums[k]$ and$nums[j]$ is more than$1$ , the unbalanced number increases by$1$ ; - If
$nums[h]$ exists, and the difference between$nums[j]$ and$nums[h]$ is more than$1$ , the unbalanced number increases by$1$ ; - If both
$nums[k]$ and$nums[h]$ exist, then inserting the element$nums[j]$ between$nums[h]$ and$nums[k]$ will reduce the unbalanced number by$1$ .
Then, we add the unbalanced number of the current subarray to the answer, and continue the iteration until we finish iterating over all subarrays.
The time complexity is
from sortedcontainers import SortedList
class Solution:
def sumImbalanceNumbers(self, nums: List[int]) -> int:
n = len(nums)
ans = 0
for i in range(n):
sl = SortedList()
cnt = 0
for j in range(i, n):
k = sl.bisect_left(nums[j])
h = k - 1
if h >= 0 and nums[j] - sl[h] > 1:
cnt += 1
if k < len(sl) and sl[k] - nums[j] > 1:
cnt += 1
if h >= 0 and k < len(sl) and sl[k] - sl[h] > 1:
cnt -= 1
sl.add(nums[j])
ans += cnt
return ans
class Solution {
public int sumImbalanceNumbers(int[] nums) {
int n = nums.length;
int ans = 0;
for (int i = 0; i < n; ++i) {
TreeMap<Integer, Integer> tm = new TreeMap<>();
int cnt = 0;
for (int j = i; j < n; ++j) {
Integer k = tm.ceilingKey(nums[j]);
if (k != null && k - nums[j] > 1) {
++cnt;
}
Integer h = tm.floorKey(nums[j]);
if (h != null && nums[j] - h > 1) {
++cnt;
}
if (h != null && k != null && k - h > 1) {
--cnt;
}
tm.merge(nums[j], 1, Integer::sum);
ans += cnt;
}
}
return ans;
}
}
class Solution {
public:
int sumImbalanceNumbers(vector<int>& nums) {
int n = nums.size();
int ans = 0;
for (int i = 0; i < n; ++i) {
multiset<int> s;
int cnt = 0;
for (int j = i; j < n; ++j) {
auto it = s.lower_bound(nums[j]);
if (it != s.end() && *it - nums[j] > 1) {
++cnt;
}
if (it != s.begin() && nums[j] - *prev(it) > 1) {
++cnt;
}
if (it != s.end() && it != s.begin() && *it - *prev(it) > 1) {
--cnt;
}
s.insert(nums[j]);
ans += cnt;
}
}
return ans;
}
};