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Mastering Julia

Mastering Julia

By : Malcolm Sherrington
4.4 (7)
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Mastering Julia

Mastering Julia

4.4 (7)
By: Malcolm Sherrington

Overview of this book

Julia is a well-constructed programming language with fast execution speed, eliminating the classic problem of performing analysis in one language and translating it for performance into a second. This book will help you develop and enhance your programming skills in Julia to solve real-world automation challenges. This book starts off with a refresher on installing and running Julia on different platforms. Next, you will compare the different ways of working with Julia and explore Julia's key features in-depth by looking at design and build. You will see how data works using simple statistics and analytics, and discover Julia's speed, its real strength, which makes it particularly useful in highly intensive computing tasks and observe how Julia can cooperate with external processes in order to enhance graphics and data visualization. Finally, you will look into meta-programming and learn how it adds great power to the language and establish networking and distributed computing with Julia.
Table of Contents (12 chapters)
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11
Index

Graphic engines


Native graphics are constructed by developing the plots in Julia and using wrapper calls to libraries such as cairo, pango, and tk.

In this section, we will consider creating graphics by means of an external tasks (programs) rather than shared libraries. Clearly, this means that the program must be installed on the specific computer and not all operating systems are equivalent with respect to the various packages on offer.

PyPlot

PyPlot is a part of the work of Steven Johnson of MIT, which arose from the previous development of the PyCall module. Together with Winston and Gadfly, it is the third part in the Julia graphics triumvirate.

It provides an interface to the matplotlib plotting library from Python and in particular to matplotlib.pyplot. The API of matplotlib can be used as the basis for a comprehensive reference source to the various function calls: matplotlib.org/api.

Therefore in order to use PyPlot, the installation of Python and matplotlib is necessary. If this is...

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Mastering Julia
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