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You're reading from  Mastering matplotlib

Product typeBook
Published inJun 2015
Reading LevelIntermediate
Publisher
ISBN-139781783987542
Edition1st Edition
Languages
Python
Tools
Matplotlib
Concepts
Data Visualization
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Authors (2):
Duncan M. McGreggor
Duncan M. McGreggor
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Duncan M. McGreggor

Duncan M. McGreggor, having programmed with GOTOs in the 1980s, has made up for that through community service by making open source contributions for more than 20 years. He has spent a major part of the past 10 years dealing with distributed and scientific computing (in languages ranging from Python, Common Lisp, and Julia to Clojure and Lisp Flavored Erlang). In the 1990s, after serving as a linguist in the US Army, he spent considerable time working on projects related to MATLAB and Mathematica, which was a part of his physics and maths studies at the university. Since the mid 2000s, matplotlib and NumPy have figured prominently in many of the interesting problems that he has solved for his customers. With the most recent addition of the IPython Notebook, matplotlib and the suite of the Python scientific computing libraries remain some of his most important professional tools.
Read more about Duncan M. McGreggor

Duncan M McGreggor
Duncan M McGreggor
author image
Duncan M McGreggor

Duncan M. McGreggor, having programmed with GOTOs in the 1980s, has made up for that through community service by making open source contributions for more than 20 years. He has spent a major part of the past 10 years dealing with distributed and scientific computing (in languages ranging from Python, Common Lisp, and Julia to Clojure and Lisp Flavored Erlang). In the 1990s, after serving as a linguist in the US Army, he spent considerable time working on projects related to MATLAB and Mathematica, which was a part of his physics and maths studies at the university. Since the mid 2000s, matplotlib and NumPy have figured prominently in many of the interesting problems that he has solved for his customers. With the most recent addition of the IPython Notebook, matplotlib and the suite of the Python scientific computing libraries remain some of his most important professional tools.
Read more about Duncan M McGreggor

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The supporting components of the matplotlib stack

In addition to the three major components of the matplotlib stack, there are supporting components. These include the following:

  • Configuration support

  • Utility modules and functions

  • C extensions

  • External libraries upon which matplotlib depends

We will touch on these in the coming chapters. They are related to the given topics at hand, but they do not impact the structure or nature of matplotlib's overall architecture.

Combining the details uncovered in the previous sections, the following diagram portrays a logical architecture for matplotlib that glosses over the finer details:

To make this more of a living reality, we will follow this high-level description with some more detailed examinations, which consist of the following:

  • Learning about matplotlib modules and associated namespaces

  • Creating a sample import graph

  • Following the execution of the pyplot functions through the matplotlib stack

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Mastering matplotlib
Published in: Jun 2015Publisher: ISBN-13: 9781783987542
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Authors (2)

author image
Duncan M. McGreggor

Duncan M. McGreggor, having programmed with GOTOs in the 1980s, has made up for that through community service by making open source contributions for more than 20 years. He has spent a major part of the past 10 years dealing with distributed and scientific computing (in languages ranging from Python, Common Lisp, and Julia to Clojure and Lisp Flavored Erlang). In the 1990s, after serving as a linguist in the US Army, he spent considerable time working on projects related to MATLAB and Mathematica, which was a part of his physics and maths studies at the university. Since the mid 2000s, matplotlib and NumPy have figured prominently in many of the interesting problems that he has solved for his customers. With the most recent addition of the IPython Notebook, matplotlib and the suite of the Python scientific computing libraries remain some of his most important professional tools.
Read more about Duncan M. McGreggor

author image
Duncan M McGreggor

Duncan M. McGreggor, having programmed with GOTOs in the 1980s, has made up for that through community service by making open source contributions for more than 20 years. He has spent a major part of the past 10 years dealing with distributed and scientific computing (in languages ranging from Python, Common Lisp, and Julia to Clojure and Lisp Flavored Erlang). In the 1990s, after serving as a linguist in the US Army, he spent considerable time working on projects related to MATLAB and Mathematica, which was a part of his physics and maths studies at the university. Since the mid 2000s, matplotlib and NumPy have figured prominently in many of the interesting problems that he has solved for his customers. With the most recent addition of the IPython Notebook, matplotlib and the suite of the Python scientific computing libraries remain some of his most important professional tools.
Read more about Duncan M McGreggor

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