﻿ NumPy: Calculate the Frobenius norm and the condition number of a given array - w3resource # 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:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

What is the difficulty level of this exercise?

Test your Python skills with w3resource's quiz

﻿

## Python: Tips of the Day

Negative Indexing:

In Python you can use negative indexing. While positive index starts with 0, negative index starts with -1.

```name="Welcome"
print(name)
print(name[-1])
print(name[0:3])
print(name[-1:-4:-1])

```

Output:

```W
e
Wel
emo```