2028. Find Missing Observations
Difficulty: Medium
Topics: Array, Math, Simulation
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 + mrolls 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.
Constraints:
- m == rolls.length
- 1 5
- 1
Hint:
- What should the sum of the n rolls be?
- Could you generate an array of size n such that each element is between 1 and 6?
Solution:
We need to determine an array of missing rolls such that the average of all n + m dice rolls is exactly equal to mean. Here's the step-by-step breakdown of the solution:
Steps to Approach:
Calculate the total sum for n + m rolls:
Given that the average value of n + m rolls is mean, the total sum of all the rolls should be total_sum = (n + m) * mean.Determine the missing sum:
The sum of the m rolls is already known. Thus, the sum of the missing n rolls should be:
missing_sum = total_sum - ∑(rolls)
where ∑(rolls) is the sum of the elements in the rolls array.
- Check for feasibility: Each roll is a 6-sided die, so the missing values must be between 1 and 6 (inclusive). Therefore, the sum of the missing n rolls must be between:
min_sum = n X 1 = n
and
max_sum = n X 6 = 6n
If the missing_sum is outside this range, it's impossible to form valid missing observations, and we should return an empty array.
- Distribute the missing sum: If missing_sum is valid, we distribute it across the n rolls by initially filling each element with 1 (the minimum possible value). Then, we increment elements from 1 to 6 until we reach the required missing_sum.
Let's implement this solution in PHP: 2028. Find Missing Observations
<?php /** * @param Integer[] $rolls * @param Integer $mean * @param Integer $n * @return Integer[] */ function missingRolls($rolls, $mean, $n) { ... ... ... /** * go to ./solution.php */ } // Example 1 $rolls = [3, 2, 4, 3]; $mean = 4; $n = 2; print_r(missingRolls($rolls, $mean, $n)); // Example 2 $rolls = [1, 5, 6]; $mean = 3; $n = 4; print_r(missingRolls($rolls, $mean, $n)); // Example 3 $rolls = [1, 2, 3, 4]; $mean = 6; $n = 4; print_r(missingRolls($rolls, $mean, $n)); ?>
Explanation:
-
Input:
- rolls = [3, 2, 4, 3]
- mean = 4
- n = 2
-
Steps:
- The total number of rolls is n + m = 6.
- The total sum needed is 6 * 4 = 24.
- The sum of the given rolls is 3 + 2 + 4 + 3 = 12.
- The sum required for the missing rolls is 24 - 12 = 12.
We need two missing rolls that sum up to 12, and the only possibility is [6, 6].
-
Result:
- For example 1: The output is [6, 6].
- For example 2: The output is [2, 3, 2, 2].
- For example 3: No valid solution, so the output is [].
Time Complexity:
- Calculating the sum of rolls takes O(m), and distributing the missing_sum takes O(n). Hence, the overall time complexity is O(n + m), which is efficient for the input constraints.
This solution ensures that we either find valid missing rolls or return an empty array when no solution exists.
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