December 2017
Intermediate to advanced
386 pages
10h 42m
English
Content preview from SciPy Recipes
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Computations on top of a sparse matrix
In order to understand how to perform computations on top of a sparse matrix and the resulting benefits thereof, we will be looking at an example and comparing the difference between having a sparse matrix and not having a sparse matrix.
Solving a system of equations
As discussed in the Solving linear systems using matrices recipe, a system of equations is solved using the solve function in scipy.linalg.
In order to compare the difference between sparse matrix computation and non-sparse matrix computation, we will perform the following tasks:
- Import relevant packages
- Initialize a 10,000 x 10,000 matrix named A
- Impute very few values with some random numbers
- Set the diagonal, so that the rank of matrix ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.