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Julia 1.0 Programming Cookbook

You're reading from   Julia 1.0 Programming Cookbook Over 100 numerical and distributed computing recipes for your daily data science work?ow

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788998369
Length 460 pages
Edition 1st Edition
Languages
Tools
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Authors (2):
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Przemysław Szufel Przemysław Szufel
Author Profile Icon Przemysław Szufel
Przemysław Szufel
Bogumił Kamiński Bogumił Kamiński
Author Profile Icon Bogumił Kamiński
Bogumił Kamiński
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Toc

Table of Contents (12) Chapters Close

Preface 1. Installing and Setting Up Julia 2. Data Structures and Algorithms FREE CHAPTER 3. Data Engineering in Julia 4. Numerical Computing with Julia 5. Variables, Types, and Functions 6. Metaprogramming and Advanced Typing 7. Handling Analytical Data 8. Julia Workflow 9. Data Science 10. Distributed Computing 11. Other Books You May Enjoy

Traversing matrices efficiently


Matrices are a basic building block of any numerical computing workflow. In this introductory recipe, we show how to work with them using loops.

The important point to consider here is that in order to traverse a matrix efficiently in Julia you should traverse it column-wise, as this is the memory layout used internally. Other languages that use column-major order are Fortran, MATLAB, and R.

Getting ready

Make sure that you have the BenchmarkTools.jl package installed. If it is missing then run the following command: using Pkg; Pkg.add("BenchmarkTools").

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 and the sums.jl file that contains definitions of functions used in this recipe.

Now open your favorite terminal to execute the commands.

How to do it...

First, we define two ways we could implement a function that takes the sum of all elements of an array. After this...

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