Book Image

Scientific Computing with Scala

By : Vytautas Jancauskas
Book Image

Scientific Computing with Scala

By: Vytautas Jancauskas

Overview of this book

Scala is a statically typed, Java Virtual Machine (JVM)-based language with strong support for functional programming. There exist libraries for Scala that cover a range of common scientific computing tasks – from linear algebra and numerical algorithms to convenient and safe parallelization to powerful plotting facilities. Learning to use these to perform common scientific tasks will allow you to write programs that are both fast and easy to write and maintain. We will start by discussing the advantages of using Scala over other scientific computing platforms. You will discover Scala packages that provide the functionality you have come to expect when writing scientific software. We will explore using Scala's Breeze library for linear algebra, optimization, and signal processing. We will then proceed to the Saddle library for data analysis. If you have experience in R or with Python's popular pandas library you will learn how to translate those skills to Saddle. If you are new to data analysis, you will learn basic concepts of Saddle as well. Well will explore the numerical computing environment called ScalaLab. It comes bundled with a lot of scientific software readily available. We will use it for interactive computing, data analysis, and visualization. In the following chapters, we will explore using Scala's powerful parallel collections for safe and convenient parallel programming. Topics such as the Akka concurrency framework will be covered. Finally, you will learn about multivariate data visualization and how to produce professional-looking plots in Scala easily. After reading the book, you should have more than enough information on how to start using Scala as your scientific computing platform
Table of Contents (16 chapters)
Scientific Computing with Scala
About the Author
About the Reviewer

Signal processing

Breeze has several methods to help you write digital signal processing code. These include functions for convolution, Fourier transforms, and several digital filters. These are useful when you are dealing with digital signals, such as sound and others. Anyone working with sound, speech, image processing, and other similar areas, such as pattern recognition, will find these useful. In this section, we will also use Breeze's plotting facilities to help us illustrate some concepts.

Fourier transforms

Fourier transforms are named after Joseph Fourier, who, in 1822, showed that some functions can be written as the (possibly) infinite sum of harmonics. Getting into the topic of Fourier analysis is out of the scope of this book. It will be assumed that the reader knows what they are and what they are useful for. We will simply show you how to do discrete Fourier transforms using Breeze. Here, we present a program that does a Fourier transform on a simple signal that consists of...