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Python Data Visualization Cookbook (Second Edition)

You're reading from  Python Data Visualization Cookbook (Second Edition)

Product type Book
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Pages 302 pages
Edition 1st Edition
Languages

Table of Contents (16) Chapters

Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
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 the Right Plots to Understand Data 8. More on matplotlib Gems 9. Visualizations on the Clouds with Plot.ly Index

Animating with OpenGL


The motivation to use OpenGL stems from limitations of CPU processing power when we are faced with the task of visualizing millions of data points and doing 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 science-related visualizations.

Actually, there is at least one drawback of writing hardware-accelerated software that is hardware dependent. Modern graphics cards require proprietary drivers which are sometimes not available on the target platform/machine (the user's laptop, for example). Even when available, sometimes installing the 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 showstopper but you should bear this in mind, and measure the benefits and costs of introducing this complexity in...

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