Check if two given matrices are identical - Python

Last Updated : 15 Jan, 2025

In Python, we often need to check whether two given matrices are identical. Two matrices are considered identical if they have the same number of rows and columns and the corresponding elements in each matrix are equal. Let's explore various methods to compare two matrices and check if they are identical.

Using equality operator (==)

equality operator can be used to directly compare two matrices. Python lists support element-wise comparison, so this method is simple and efficient.

Python

# Input matrices m1 = [[1, 2, 3], [4, 5, 6]] m2 = [[1, 2, 3], [4, 5, 6]]  # Check if matrices are identical res = m1 == m2 print(res)

Output

True

Explanation:

The equality operator compares the two matrices element by element.
If all corresponding elements in both matrices are equal, it returns True.
This method is simple and efficient for smaller matrices.

Let's explore some more methods and see how we can check if two given matrices are identical.

Table of Content

Using zip()

zip() function can be used to pair up the rows of both matrices and then compare each pair.

Python

m1 = [[1, 2, 3], [4, 5, 6]] m2 = [[1, 2, 3], [4, 5, 6]]  # Check if matrices are identical using zip res = all(r1 == r2 for r1, r2 in zip(m1, m2)) print(res)

Output

True

Explanation:

zip() function pairs up the corresponding rows from both matrices.
all() function checks if all the pairs of rows are equal.
This method uses Python's built-in functions for clean and efficient code.

Using for loop

We can also compare two matrices manually using nested loops. This method iterates over each element and checks if they are equal.

Python

m1 = [[1, 2, 3], [4, 5, 6]] m2 = [[1, 2, 3], [4, 5, 6]]  # Initialize result as True res = True  # Check if matrices have the same dimensions and elements for i in range(len(m1)):     for j in range(len(m1[i])):         if m1[i][j] != m2[i][j]:             res = False             break     if not res:         break print(res)

Output

True

Explanation:

We use nested loops to iterate through each element in both matrices.
If any element does not match, the result is set to False.
This method allows for a manual check of matrix equality and is useful when we need more control over the comparison process.

Using numpy for large matrices

When working with large matrices, the numpy library offers a very efficient way to compare matrices using the numpy.array_equal() function.

Python

import numpy as np  # Input matrices m1 = np.array([[1, 2, 3], [4, 5, 6]]) m2 = np.array([[1, 2, 3], [4, 5, 6]])  # Check if matrices are identical res = np.array_equal(m1, m2) print(res)

Output

True

Explanation:

We convert the matrices to numpy arrays and use the array_equal() function to check if they are identical.
This method works well for large matrices, as numpy optimizes such operations.