1632. Rank Transform of a Matrix
Description
Given an m x n
matrix
, return a new matrix answer
where answer[row][col]
is the rank of matrix[row][col]
.
The rank is an integer that represents how large an element is compared to other elements. It is calculated using the following rules:
- The rank is an integer starting from
1
. - If two elements
p
andq
are in the same row or column, then:- If
p < q
thenrank(p) < rank(q)
- If
p == q
thenrank(p) == rank(q)
- If
p > q
thenrank(p) > rank(q)
- If
- The rank should be as small as possible.
The test cases are generated so that answer
is unique under the given rules.
Example 1:
Input: matrix = [[1,2],[3,4]] Output: [[1,2],[2,3]] Explanation: The rank of matrix[0][0] is 1 because it is the smallest integer in its row and column. The rank of matrix[0][1] is 2 because matrix[0][1] > matrix[0][0] and matrix[0][0] is rank 1. The rank of matrix[1][0] is 2 because matrix[1][0] > matrix[0][0] and matrix[0][0] is rank 1. The rank of matrix[1][1] is 3 because matrix[1][1] > matrix[0][1], matrix[1][1] > matrix[1][0], and both matrix[0][1] and matrix[1][0] are rank 2.
Example 2:
Input: matrix = [[7,7],[7,7]] Output: [[1,1],[1,1]]
Example 3:
Input: matrix = [[20,-21,14],[-19,4,19],[22,-47,24],[-19,4,19]] Output: [[4,2,3],[1,3,4],[5,1,6],[1,3,4]]
Constraints:
m == matrix.length
n == matrix[i].length
1 <= m, n <= 500
-109 <= matrix[row][col] <= 109
Solution
rank-transform-of-a-matrix.py
class DSU:
def __init__(self, graph):
self.p = {i:i for i in graph}
def find(self, x):
if self.p[x] != x:
self.p[x] = self.find(self.p[x])
return self.p[x]
def union(self, x, y):
self.p[self.find(x)] = self.find(y)
def groups(self):
ans = defaultdict(list)
for el in self.p.keys():
ans[self.find(el)].append(el)
return ans
class Solution:
def matrixRankTransform(self, M):
n, m = len(M), len(M[0])
rank = [0] * (m + n)
d = defaultdict(list)
for i, j in product(range(n), range(m)):
d[M[i][j]].append([i, j])
for a in sorted(d):
graph = [i for i, j in d[a]] + [j + n for i, j in d[a]]
dsu = DSU(graph)
for i, j in d[a]: dsu.union(i, j + n)
for group in dsu.groups().values():
mx = max(rank[i] for i in group)
for i in group: rank[i] = mx + 1
for i, j in d[a]: M[i][j] = rank[i]
return M