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NumPy: Calculate the Frobenius norm and the condition number of a given array

NumPy: Linear Algebra Exercise-19 with Solution

Write a NumPy program to calculate the Frobenius norm and the condition number of a given array.

Sample Solution:

Python Code :

import numpy as np
a = np.arange(1, 10).reshape((3, 3))
print("Original array:")
print(a)
print("Frobenius norm and the condition number:")
print(np.linalg.norm(a, 'fro'))
print(np.linalg.cond(a, 'fro'))

Sample Output:

Original array:
[[1 2 3]
 [4 5 6]
 [7 8 9]]
Frobenius norm and the condition number:
16.8819430161
4.56177073661e+17

Python Code Editor:


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Python: Tips of the Day

Getting the last element of a list:

some_list[-1] is the shortest and most Pythonic.

In fact, you can do much more with this syntax. The some_list[-n] syntax gets the nth-to-last element. So some_list[-1] gets the last element, some_list[-2] gets the second to last, etc, all the way down to some_list[-len(some_list)], which gives you the first element.

You can also set list elements in this way. For instance:

>>> some_list = [1, 2, 3]
>>> some_list[-1] = 5 # Set the last element
>>> some_list[-2] = 3 # Set the second to last element
>>> some_list
[1, 3, 5]

Note that getting a list item by index will raise an IndexError if the expected item doesn't exist. This means that some_list[-1] will raise an exception if some_list is empty, because an empty list can't have a last element.

Ref: https://bit.ly/3d8TfFP