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

Non-standard ways to sort your data


Sorting is one of the basic operations commonly performed when processing data. In this recipe, we will explore several options for how you can perform sorting in non-standard cases. In particular, we will compare the performance of the various options that can be used for sorting.

Getting ready

In this recipe, we want to sort rows of an array of Float64 numbers by their norms. For our purposes, the norm of a list of values 

 is defined as 

, that is, the Euclidean norm (see http://mathworld.wolfram.com/MatrixNorm.html).

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.

Now open your favorite terminal to execute commands.

How to do it...

In order to compare different custom sorting strategies, we first create sample test data and then perform the sorting on it as follows:

  1. In this recipe, we will use the seed! function from the Random module and the norm function from...