NumPy: Get the lower-triangular L in the Cholesky decomposition of a given array
NumPy: Linear Algebra Exercise-16 with Solution
Write a NumPy program to get the lower-triangular L in the Cholesky decomposition of a given array.
Python Code :
import numpy as np a = np.array([[4, 12, -16], [12, 37, -53], [-16, -53, 98]], dtype=np.int32) print("Original array:") print(a) L = np.linalg.cholesky(a) print("Lower-trianglular L in the Cholesky decomposition of the said array:") print(L)
Original array: [[ 4 12 -16] [ 12 37 -53] [-16 -53 98]] Lower-triangular L in the Cholesky decomposition of the said array: [[ 2. 0. 0.] [ 6. 1. 0.] [-8. -5. 3.]]
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
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.
- New Content published on w3resource:
- Scala Programming Exercises, Practice, Solution
- Python Itertools exercises
- Python Numpy exercises
- Python GeoPy Package exercises
- Python Pandas exercises
- Python nltk exercises
- Python BeautifulSoup exercises
- Form Template
- Composer - PHP Package Manager
- PHPUnit - PHP Testing
- Laravel - PHP Framework