You have observations of n + m
6-sided dice rolls with each face numbered from 1
to 6
. n
of the observations went missing, and you only have the observations of m
rolls. Fortunately, you have also calculated the average value of the n + m
rolls.
You are given an integer array rolls
of length m
where rolls[i]
is the value of the ith
observation. You are also given the two integers mean
and n
.
Return an array of length n
containing the missing observations such that the average value of the n + m
rolls is exactly mean
. If there are multiple valid answers, return any of them. If no such array exists, return an empty array.
The average value of a set of k
numbers is the sum of the numbers divided by k
.
Note that mean
is an integer, so the sum of the n + m
rolls should be divisible by n + m
.
Example 1:
Input: rolls = [3,2,4,3], mean = 4, n = 2 Output: [6,6] Explanation: The mean of all n + m rolls is (3 + 2 + 4 + 3 + 6 + 6) / 6 = 4.
Example 2:
Input: rolls = [1,5,6], mean = 3, n = 4 Output: [2,3,2,2] Explanation: The mean of all n + m rolls is (1 + 5 + 6 + 2 + 3 + 2 + 2) / 7 = 3.
Example 3:
Input: rolls = [1,2,3,4], mean = 6, n = 4 Output: [] Explanation: It is impossible for the mean to be 6 no matter what the 4 missing rolls are.
Example 4:
Input: rolls = [1], mean = 3, n = 1 Output: [5] Explanation: The mean of all n + m rolls is (1 + 5) / 2 = 3.
Constraints:
m == rolls.length
1 <= n, m <= 105
1 <= rolls[i], mean <= 6
Similar Questions:
// OJ: https://leetcode.com/problems/find-missing-observations/
// Author: github.com/lzl124631x
// Time: O(M + N)
// Space: O(1)
class Solution {
public:
vector<int> missingRolls(vector<int>& A, int mean, int n) {
int m = A.size(), sum = accumulate(begin(A), end(A), 0), goal = (n + m) * mean - sum;
if (goal < n || goal > 6 * n) return {};
vector<int> ans;
int d = goal / n, r = goal % n;
for (int i = 0; i < n; ++i) {
ans.push_back(d + (r > 0));
--r;
}
return ans;
}
};