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Mastering matplotlib

You're reading from  Mastering matplotlib

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781783987542
Pages 292 pages
Edition 1st Edition
Languages
Authors (2):
Duncan M. McGreggor Duncan M. McGreggor
Profile icon Duncan M. McGreggor
Duncan M McGreggor Duncan M McGreggor
Profile icon Duncan M McGreggor
View More author details

Table of Contents (16) Chapters

Mastering matplotlib
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Up to Speed 2. The matplotlib Architecture 3. matplotlib APIs and Integrations 4. Event Handling and Interactive Plots 5. High-level Plotting and Data Analysis 6. Customization and Configuration 7. Deploying matplotlib in Cloud Environments 8. matplotlib and Big Data 9. Clustering for matplotlib Index

Chapter 9. Clustering for matplotlib

In the final chapter of this book, we will address a topic that has been alluded to several times—clustering and parallel programming for matplotlib. Our motivation to discuss this is nearly identical to that which drove our investigation into working with large datasets. Although matplotlib lib itself isn't a library that makes direct use of large datasets or provides an API that can be used with clusters, advanced users of the library will very likely encounter situations where they may want to utilize matplotlib.

Not to put too fine a point on this, we live in a new world of computing. This was presented exceptionally well in the oft-quoted article, The Free Lunch Is Over, by Herb Sutter. With the drastic limitations faced by the semiconductor industry, yearly gains in computing power are no longer a result of faster chips. Instead, we get this benefit through the addition of cores in a single machine. Unfortunately, common practices in programming...

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