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Python Data Visualization Cookbook

You're reading from  Python Data Visualization Cookbook

Product type Book
Published in Nov 2013
Publisher Packt
ISBN-13 9781782163367
Pages 280 pages
Edition 1st Edition
Languages
Author (1):
Igor Milovanovic Igor Milovanovic
Profile icon Igor Milovanovic

Table of Contents (15) Chapters

Python Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Preparing Your Working Environment 2. Knowing Your Data 3. Drawing Your First Plots and Customizing Them 4. More Plots and Customizations 5. Making 3D Visualizations 6. Plotting Charts with Images and Maps 7. Using Right Plots to Understand Data 8. More on matplotlib Gems Index

Animating with OpenGL


The motivation to use OpenGL comes from the limitations of CPU processing power when we face a task to visualize millions of data points and do it fast (sometimes even in real time).

Modern computers have powerful GPUs that are made for fast visualization related computations (such as games), and there is no reason why they can't be used for scientific-related visualizations.

Actually, there is at least one drawback of writing the hardware accelerated software. As far as hardware dependency is concerned, modern graphic cards require proprietary drivers, sometimes not available on the target platform/machine (for example, user laptop); even when available, sometimes installing required dependencies on site is not what you want to spend your time on, while all you want is to present your findings and demonstrate your research results. This is not a show stopper but have this in mind, and measure benefits and costs of introducing this complexity in your project.

With caveats...

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