How to check if two scipy.sparse.csr_matrix() are equal?

In this tutorial, we will learn How to check if two scipy.sparse.csr_matrix() are equal in Python NumPy? By Pranit Sharma Last updated : May 05, 2023

The sparse matrix representation outputs the row-column tuple where the matrix contains non-zero values along with those values.

Suppose that we are given two scipy sparse matrices and we need to check if these matrices are equal or not.

Check if two scipy.sparse.csr_matrix() are equal

To check if two scipy.sparse.csr_matrix() are equal, you can use a hybrid approach of numpy and scipy, use numpy.array_equal() method which takes two arrays and returns True if the input arrays are equal; False, otherwise. Convert scipy matrix to dense matrix by using .todense() method so that these matrices can become input for array_equal().

Let us understand with the help of an example,

Python program to check if two scipy.sparse.csr_matrix() are equal

# Import numpy
import numpy as np

# Import scipy sparse
from scipy import sparse

# Creating two scipy sparse matrix
a = sparse.csr_matrix([[0,1],[1,0]])
b = sparse.csr_matrix([[0,1],[1,1]])

# Display original matrices
print("csr matrix 1:\n",a,"\n")
print("csr matrix 2:\n",b,"\n")

# Checking both matrices
res = np.array_equal(a.todense(), b.todense())

# Display result
print("Are both matrices equal?:\n",res,"\n")

Output

csr matrix 1:
   (0, 1)       1
  (1, 0)        1 

csr matrix 2:
   (0, 1)       1
  (1, 0)        1
  (1, 1)        1 

Are both matrices equal?:
 False