Compute the condition number of a given matrix using NumPy
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 libraryimport numpy as np # Creating a 2X2 matrixmatrix = np.array([[4, 2], [3, 1]]) print("Original matrix:")print(matrix) # Outputresult = 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 libraryimport numpy as np # Creating a 3X3 matrixmatrix = np.array([[4, 2, 0], [3, 1, 2], [1, 6, 4]]) print("Original matrix:")print(matrix) # Outputresult = 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 libraryimport numpy as np # Creating a 4X4 matrixmatrix = np.array([[4, 1, 4, 2], [3, 1, 2, 0], [3, 5, 7 ,1], [0, 6, 8, 4]]) print("Original matrix:")print(matrix) # Outputresult = 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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