Python Coding challenge - Day 415| What is the output of the following Python Code?

 

Code Explanation:

1. Importing the Library

import numpy as np

numpy is imported using the alias np, which is a standard convention.

NumPy provides powerful mathematical functions and operations for matrix manipulations.

2. Defining the Matrix

matrix = np.array([[2, -1], [-1, 2]])

Here, a 2x2 matrix is defined using np.array().

3. Calculating Eigenvalues and Eigenvectors

eigenvalues, eigenvectors = np.linalg.eig(matrix)

The np.linalg.eig() function from NumPy’s linear algebra module (linalg) is used to compute the eigenvalues and eigenvectors.

Eigenvectors are the corresponding vectors that satisfy this equation.

4. Printing the Eigenvalues

print(eigenvalues)

This prints the eigenvalues of the matrix.

For the given matrix, the characteristic polynomial is:

∣A−λI∣=0

Final Output:

[3, 1]

 [[3. 1.][]][3. 1[3. 1.][3. 1.][3. 1.][3. 1.].]