Book Image

Julia 1.0 Programming - Second Edition

By : Ivo Balbaert
Book Image

Julia 1.0 Programming - Second Edition

By: Ivo Balbaert

Overview of this book

The release of Julia 1.0 is now ready to change the technical world by combining the high productivity and ease of use of Python and R with the lightning-fast speed of C++. Julia 1.0 programming gives you a head start in tackling your numerical and data problems. You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. With the help of practical examples, this book walks you through two important collection types: arrays and matrices. In addition to this, you will be taken through how type conversions and promotions work. In the course of the book, you will be introduced to the homo-iconicity and metaprogramming concepts in Julia. You will understand how Julia provides different ways to interact with an operating system, as well as other languages, and then you'll discover what macros are. Once you have grasped the basics, you’ll study what makes Julia suitable for numerical and scientific computing, and learn about the features provided by Julia. By the end of this book, you will also have learned how to run external programs. This book covers all you need to know about Julia in order to leverage its high speed and efficiency for your applications.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Ranges and arrays


Ranges come in handy when you have to work with an interval of numbers, for example, one up to thousand: 1:1000. The type of this object, typeof(1:1000), is UnitRange{Int64}. By default, the step is 1, but this can also be specified as the second number; 0:5:100 gives all multiples of 5 up to 100. You can iterate over a range, as follows:

# code from file chapter2\arrays.jl    
for i in 1:2:9 
    println(i) 
end 

This prints out 1, 3, 5, 7, 9 on consecutive lines.

In the previous section on Strings, we already encountered the array type when discussing the split function:

a = split("A,B,C,D",",")typeof(a) #> Array{SubString{String},1}show(a) #> SubString{String}["A","B","C","D"]

Julia's arrays are very efficient, powerful, and flexible. The general type format for an array is Array{Type, n}, with n number of dimensions (we will discuss multidimensional arrays or matrices in Chapter 6, More on Types, Methods, and Modules). As with the complex type, we can see that theArray...