There is a survey that consists of n
questions where each question's answer is either 0
(no) or 1
(yes).
The survey was given to m
students numbered from 0
to m - 1
and m
mentors numbered from 0
to m - 1
. The answers of the students are represented by a 2D integer array students
where students[i]
is an integer array that contains the answers of the ith
student (0-indexed). The answers of the mentors are represented by a 2D integer array mentors
where mentors[j]
is an integer array that contains the answers of the jth
mentor (0-indexed).
Each student will be assigned to one mentor, and each mentor will have one student assigned to them. The compatibility score of a student-mentor pair is the number of answers that are the same for both the student and the mentor.
- For example, if the student's answers were
[1, 0, 1]
and the mentor's answers were[0, 0, 1]
, then their compatibility score is 2 because only the second and the third answers are the same.
You are tasked with finding the optimal student-mentor pairings to maximize the sum of the compatibility scores.
Given students
and mentors
, return the maximum compatibility score sum that can be achieved.
Example 1:
Input: students = [[1,1,0],[1,0,1],[0,0,1]], mentors = [[1,0,0],[0,0,1],[1,1,0]] Output: 8 Explanation: We assign students to mentors in the following way: - student 0 to mentor 2 with a compatibility score of 3. - student 1 to mentor 0 with a compatibility score of 2. - student 2 to mentor 1 with a compatibility score of 3. The compatibility score sum is 3 + 2 + 3 = 8.
Example 2:
Input: students = [[0,0],[0,0],[0,0]], mentors = [[1,1],[1,1],[1,1]] Output: 0 Explanation: The compatibility score of any student-mentor pair is 0.
Constraints:
m == students.length == mentors.length
n == students[i].length == mentors[j].length
1 <= m, n <= 8
students[i][k]
is either0
or1
.mentors[j][k]
is either0
or1
.
class Solution:
def maxCompatibilitySum(self, students: List[List[int]], mentors: List[List[int]]) -> int:
def score(s, m):
res = 0
for i in range(len(s)):
res += 1 if s[i] == m[i] else 0
return res
m, n = len(students), len(students[0])
scores = [[0] * m for _ in range(m)]
for i in range(m):
for j in range(m):
scores[i][j] = score(students[i], mentors[j])
p = self.permute(list(range(m)))
mx = 0
for item in p:
t = 0
sidx = 0
for midx in item:
t += scores[sidx][midx]
sidx += 1
mx = max(mx, t)
return mx
def permute(self, nums):
def dfs(nums, i, res, path, used):
if i == len(nums):
res.append(copy.deepcopy(path))
return
for j in range(len(nums)):
if not used[j]:
path.append(nums[j])
used[j] = True
dfs(nums, i + 1, res, path, used)
used[j] = False
path.pop()
res, path = [], []
used = [False] * len(nums)
dfs(nums, 0, res, path, used)
return res
class Solution {
public int maxCompatibilitySum(int[][] students, int[][] mentors) {
int m = students.length, n = students[0].length;
int[][] scores = new int[m][m];
for (int i = 0; i < m; ++i) {
for (int j = 0; j < m; ++j) {
scores[i][j] = score(students[i], mentors[j]);
}
}
int[] idx = new int[m];
for (int i = 0; i < m; ++i) {
idx[i] = i;
}
int mx = 0;
List<List<Integer>> p = permute(idx);
for (List<Integer> item : p) {
int t = 0;
int sidx = 0;
for (int midx : item) {
t += scores[sidx][midx];
++sidx;
}
mx = Math.max(mx, t);
}
return mx;
}
private int score(int[] s, int[] m) {
int res = 0;
for (int i = 0; i < s.length; ++i) {
res += s[i] == m[i] ? 1 : 0;
}
return res;
}
private List<List<Integer>> permute(int[] nums) {
List<List<Integer>> res = new ArrayList<>();
permute(res, nums, 0);
return res;
}
private void permute(List<List<Integer>> res, int[] nums, int start) {
if (start == nums.length) {
List<Integer> t = new ArrayList<>();
for (int e : nums) {
t.add(e);
}
res.add(t);
return;
}
for (int i = start; i < nums.length; ++i) {
swap(nums, i, start);
permute(res, nums, start + 1);
swap(nums, i, start);
}
}
private void swap(int[] nums, int i, int j) {
int t = nums[i];
nums[i] = nums[j];
nums[j] = t;
}
}