Leetcode #2946: Matrix Similarity After Cyclic Shifts
In this guide, we solve Leetcode #2946 Matrix Similarity After Cyclic Shifts in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
You are given an m x n integer matrix mat and an integer k. The matrix rows are 0-indexed.
Quick Facts
- Difficulty: Easy
- Premium: No
- Tags: Array, Math, Matrix, Simulation
Intuition
There is a mathematical invariant or formula that directly leads to the result.
Using math avoids unnecessary loops and reduces complexity.
Approach
Derive the formula or update rule, then compute the answer directly.
Handle edge cases like overflow or zero carefully.
Steps:
- Identify the math relationship.
- Compute the result with a loop or formula.
- Handle edge cases.
Python Solution
class Solution:
def areSimilar(self, mat: List[List[int]], k: int) -> bool:
n = len(mat[0])
for i, row in enumerate(mat):
for j, x in enumerate(row):
if i % 2 == 1 and x != mat[i][(j + k) % n]:
return False
if i % 2 == 0 and x != mat[i][(j - k + n) % n]:
return False
return True
Complexity
The time complexity is O(n) or O(1). The space complexity is O(1).
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.