How to Compute the Condition Number in Python?

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The condition number is a measure of the sensitivity of a mathematical problem to changes in its input. In Python, you can compute the condition number of a matrix using the NumPy library. Here’s an example:

import numpy as np

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

# Compute the condition number
condition_number = np.linalg.cond(A)

print("Condition number:", condition_number)

In this example, the NumPy library is imported to work with arrays and linear algebra functions. The matrix A is defined as a NumPy array. The np.linalg.cond() function is then used to compute the condition number of the matrix A. The result is stored in the condition_number variable and printed.

Make sure to have NumPy installed (pip install numpy) before running this code. Additionally, note that the condition number is only defined for square matrices. If you have a non-square matrix, you may need to consider other approaches or matrix decompositions to assess its properties

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