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 (11 chapters)
10
Index

Reading and writing CSV files


We will examine reading and writing CSV files here. CSV stands for Comma Separated Values. These files are just records arranged in rows with a row consisting of multiple values separated by commas (and sometimes other separator symbols, such as spaces or tabs). Instead of relying on ready-made libraries to do this, we will write our own small, extensible class for reading and writing data in CSV format.

The reason for this is that the file format is so simple it requires little more effort than reading a text file line by line. Therefore, the resulting code is simple, short, and will save you an extra dependency. Also, there does not seem to be a de facto standard for CSV access in Scala. It will serve us as an introduction to file access in Scala, which may come in handy if you need to read other weird file formats. Here is an example of a CSV file containing a part of the famous IRIS dataset. It is very commonly used to sanity test pattern recognition and...