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Compute the condition number of a given matrix using NumPy

Last Updated : 29 Aug, 2020
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In this article, we will use the cond() function of the NumPy package to calculate the condition number of a given matrix. cond() is a function of linear algebra module in NumPy package.

Syntax: 

numpy.linalg.cond(x, p=None)

Example 1: Condition Number of 2X2 matrix

Python3 
# Importing library
import numpy as np

# Creating a 2X2 matrix
matrix = np.array([[4, 2], [3, 1]])

print("Original matrix:")
print(matrix)

# Output
result =  np.linalg.cond(matrix)

print("Condition number of the matrix:")
print(result)

Output:

Original matrix:
[[4 2]
 [3 1]]
Condition number of the matrix:
14.933034373659256

Example 2: Condition Number of 3X3 matrix

Python3 
# Importing library
import numpy as np

# Creating a 3X3 matrix
matrix = np.array([[4, 2, 0], [3, 1, 2], [1, 6, 4]])

print("Original matrix:")
print(matrix)

# Output
result =  np.linalg.cond(matrix)

print("Condition number of the matrix:")
print(result)

Output:

Original matrix:
[[4 2 0]
 [3 1 2]
 [1 6 4]]
Condition number of the matrix:
5.347703616656448

Example 3: Condition Number of 4X4 matrix

Python3 
# Importing library
import numpy as np

# Creating a 4X4 matrix
matrix = np.array([[4, 1, 4, 2], [3, 1, 2, 0], 
                   [3, 5, 7 ,1], [0, 6, 8, 4]])

print("Original matrix:")
print(matrix)

# Output
result =  np.linalg.cond(matrix)

print("Condition number of the matrix:")
print(result)

Output:

Original matrix:
[[4 1 4 2]
 [3 1 2 0]
 [3 5 7 1]
 [0 6 8 4]]
Condition number of the matrix:
57.34043866386226

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