Book Image

Julia 1.0 Programming Cookbook

By : Bogumił Kamiński, Przemysław Szufel
Book Image

Julia 1.0 Programming Cookbook

By: Bogumił Kamiński, Przemysław Szufel

Overview of this book

Julia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia. Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia. By the end of the book, you will have acquired the skills to work more effectively with your data
Table of Contents (18 chapters)
Title Page
Copyright and Credits
Dedication
About Packt
Contributors
Preface
Index

Defining primitive types


In Julia, you are able to define your own composite types, as explained in the previous recipe. However, you can also define your own raw-bytes type, like Float64 or UInt32.

Getting ready

ARGB (see https://en.wikipedia.org/wiki/RGBA_color_space#ARGB_(word-order)) is a method of encoding the color of a pixel, where A (

) stands for pixel opacity, and R (red), G (green), and B (blue) are the components of its color. Each component takes eight bits, making 32 bits in total. In this recipe, we will create a custom primitive type that facilitates working with ARGB-encoded data.

Note

In the GitHub repository for this recipe, you will find the commands.txt file that contains the presented sequence of shell and Julia commands. Additionally, in the argb.jl file you can find the definitions of the ARGB type and related methods used in this recipe.

Now open your favorite terminal to execute the commands.

How to do it...

Start by inspecting the contents of the argb.jl file. First, we...