Reshape the Matrix Python Solution with Tests

Tested Python solution for LeetCode 566 with 20 pytest cases. Generate a practice environment with lcpy.

LeetCode 566, Easy. Topics: Array, Matrix, Simulation. View on LeetCode.

Generate this problem as a practice environment: tested reference solution, 20 parametrized pytest cases, and a playground notebook:

lcpy gen -n 566   # by problem number
lcpy gen -s reshape_the_matrix   # by problem name

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Problem

In MATLAB, there is a handy function called reshape which can reshape an m x n matrix into a new one with a different size r x c keeping its original data.

You are given an m x n matrix mat and two integers r and c representing the number of rows and the number of columns of the wanted reshaped matrix.

The reshaped matrix should be filled with all the elements of the original matrix in the same row-traversing order as they were.

If the reshape operation with given parameters is possible and legal, output the new reshaped matrix; Otherwise, output the original matrix.

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Examples

Input: mat = [[1,2],[3,4]], r = 1, c = 4
Output: [[1,2,3,4]]

Input: mat = [[1,2],[3,4]], r = 2, c = 4
Output: [[1,2],[3,4]]

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Constraints

• m == mat.length
• n == mat[i].length
• 1 <= m, n <= 100
• -1000 <= mat[i][j] <= 1000
• 1 <= r, c <= 300

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Solution

Reference implementation from solution.py on GitHub, full suite in test_solution.py:

class Solution:
    # Time: O(m * n)
    # Space: O(r * c) for the output matrix
    def matrix_reshape(self, mat: list[list[int]], r: int, c: int) -> list[list[int]]:
        m, n = len(mat), len(mat[0])
        if m * n != r * c:
            return mat
        result: list[list[int]] = []
        row: list[int] = []
        for values in mat:
            for value in values:
                row.append(value)
                if len(row) == c:
                    result.append(row)
                    row = []
        return result

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Complexity

Time	Space
O(m * n)	O(r * c) for the output matrix

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