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

First-class functions and closures


In this section, we will demonstrate the power and flexibility of functions (example code can be found in Chapter 3\first_class.jl). Firstly, functions have their own type:Function. Functions can also be assigned to a variable by their name:

julia> m = mult julia> m(6, 6) #> 36

 

 

This is useful when working with anonymous functions, such as c = x -> x + 2, or as follows:

julia> plustwo = function (x)                     x + 2                 end(anonymous function)julia> plustwo(3)5

Operatorsare just functions written with their arguments in an infix form; for example,x + y is equivalent to +(x, y). In fact, the first form is parsed to the second form when it is evaluated. We can confirm it in the REPL: +(3,4) returns 7 and typeof(+) returns Function.

A function can take a function (or multiple functions) as its argument, which calculates the numerical derivative of a functionf; as defined in the following function:

function numerical_derivative...