Physical Address
304 North Cardinal St.
Dorchester Center, MA 02124
You are given two positive 0-indexed integer arrays nums1
and nums2
, both of length n
.
The sum of squared difference of arrays nums1
and nums2
is defined as the sum of (nums1[i] - nums2[i])2
for each 0 <= i < n
.
You are also given two positive integers k1
and k2
. You can modify any of the elements of nums1
by +1
or -1
at most k1
times. Similarly, you can modify any of the elements of nums2
by +1
or -1
at most k2
times.
Return the minimum sum of squared difference after modifying array nums1
at most k1
times and modifying array nums2
at most k2
times.
Note: You are allowed to modify the array elements to become negative integers.
Example 1:
Input: nums1 = [1,2,3,4], nums2 = [2,10,20,19], k1 = 0, k2 = 0
Output: 579
Explanation: The elements in nums1 and nums2 cannot be modified because k1 = 0 and k2 = 0.
The sum of square difference will be: (1 - 2)2 + (2 - 10)2 + (3 - 20)2 + (4 - 19)2 = 579.
Example 2:
Input: nums1 = [1,4,10,12], nums2 = [5,8,6,9], k1 = 1, k2 = 1
Output: 43
Explanation: One way to obtain the minimum sum of square difference is:
- Increase nums1[0] once.
- Increase nums2[2] once.
The minimum of the sum of square difference will be:
(2 - 5)2 + (4 - 8)2 + (10 - 7)2 + (12 - 9)2 = 43.
Note that, there are other ways to obtain the minimum of the sum of square difference, but there is no way to obtain a sum smaller than 43.
Constraints:
n == nums1.length == nums2.length
1 <= n <= 105
0 <= nums1[i], nums2[i] <= 105
0 <= k1, k2 <= 109
class Solution {
public:
long long minSumSquareDiff(vector<int>& nums1, vector<int>& nums2, int k1, int k2) {
int n = nums1.size();
vector<int> diff(n);
for(int i = 0; i<n; ++i) {
diff[i] = abs(nums1[i] - nums2[i]);
}
int M = *max_element(diff.begin(), diff.end());
vector<int> bucket(M+1);
for(int i = 0 ; i<n; ++i) {
bucket[diff[i]]++;
}
int k = k1 + k2;
for(int i = M; i > 0; --i) {
if(bucket[i] > 0) {
int minus = min(bucket[i], k);
bucket[i] -= minus;
bucket[i-1] += minus;
k -= minus;
}
}
long long ans = 0;
for(long long i = M; i > 0; --i) {
ans += bucket[i]*i*i;
}
return ans;
}
};
class Solution {
public:
#define ll long long
long long minSumSquareDiff(vector<int>& nums1, vector<int>& nums2, int k1, int k2) {
int n = nums1.size();
unordered_map<ll, ll> mp;
for(int i = 0; i < n; ++i) {
mp[abs(nums1[i] - nums2[i])]++;
}
long long tot = k1 + k2;
priority_queue<array<ll, 2>> pq;
for(auto [x, y]: mp) {
if(x == 0) continue;
pq.push({x, y});
}
while(!pq.empty() and tot > 0) {
array<ll, 2> v = pq.top();
pq.pop();
if(pq.size() == 0) {
ll mn = min(tot, v[1]);
tot -= mn;
v[1] -= mn;
if(v[0] - 1 > 0) pq.push({v[0] - 1, mn});
if(v[1] > 0) pq.push(v);
} else {
ll mn = min(tot, v[1]);
tot -= mn;
v[1] -= mn;
if(v[1] > 0) pq.push(v);
if(pq.top()[0] == v[0] - 1) {
array<ll, 2> v1 = pq.top();
pq.pop();
v1[1] += mn;
pq.push(v1);
} else if(v[0] - 1 > 0) {
pq.push({v[0] - 1, mn});
}
}
}
ll ans = 0;
while(!pq.empty()) {
array<ll, 2> v = pq.top();
ans += v[0] * v[0] * v[1];
pq.pop();
}
return ans;
}
};
from heapq import heapify, heappush, heappop
class Solution:
def minSumSquareDiff(self, nums1: List[int], nums2: List[int], k1: int, k2: int) -> int:
heap = [ -abs(x-y) for x, y in zip(nums1, nums2)]
s = -sum(heap)
if k1+k2 >= s: return 0
delta = k1 + k2
heapify(heap)
n = len(nums1)
while delta > 0:
d = -heappop(heap)
gap = max(delta//n, 1) if heap else delta
d -= gap
heappush(heap, -d)
delta -= gap
return sum(pow(e,2) for e in heap)
In our experience, we suggest you solve this Minimum Sum of Squared Difference LeetCode Solution and gain some new skills from Professionals completely free and we assure you will be worth it.
If you are stuck anywhere between any coding problem, just visit Queslers to get the Minimum Sum of Squared Difference LeetCode Solution
I hope this Minimum Sum of Squared Difference LeetCode Solution would be useful for you to learn something new from this problem. If it helped you then don’t forget to bookmark our site for more Coding Solutions.
This Problem is intended for audiences of all experiences who are interested in learning about Data Science in a business context; there are no prerequisites.
Keep Learning!
More Coding Solutions >>