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

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Scientific Computing with Scala
Vytautas Jancauskas
Apr, 2016 | 232 pages
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Table of Contents (16 chapters)
Scientific Computing with Scala
Scientific Computing with Scala
Credits
Credits
About the Author
About the Author
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Introducing Scientific Computing with Scala
Introducing Scientific Computing with Scala
Why Scala for scientific computing?
Numerical computing packages for Scala
Data analysis packages for Scala
Other scientific software
Alternatives for doing plotting
Using Emacs as the Scala IDE
Profiling Scala code
Debugging Scala code
Building, testing, and distributing your Scala software
Mixing Java and Scala code
Summary
2
Storing and Retrieving Data
Storing and Retrieving Data
Reading and writing CSV files
Reading and writing JSON files
Reading and writing XML files
Database access using JDBC
Database access using Slick
Reading and writing HDF5 files
Summary
3
Numerical Computing with Breeze
Numerical Computing with Breeze
Using Breeze in your project
Basic Breeze data structures
Statistical computing with Breeze
Optimization
Signal processing
Cheat sheet
Summary
4
Using Saddle for Data Analysis
Using Saddle for Data Analysis
Installing Saddle
Basic Saddle data structures
Data analysis with Saddle
Summary
5
Interactive Computing with ScalaLab
Interactive Computing with ScalaLab
Installing and running ScalaLab
Basic ScalaSci data structures
Data storage and retrieval
Plotting with ScalaLab
Other ScalaLab features
Summary
6
Parallel Programming in Scala
Parallel Programming in Scala
Programming with Scala threads
Using Scala's parallel collections
Agent-based concurrency with the Akka framework
Summary
7
Cluster Computing Using Scala
Cluster Computing Using Scala
Using MPJ Express for distributed computing
Using an Akka cluster for distributed computing
Summary
8
Scientific Plotting with Scala
Scientific Plotting with Scala
Plotting with JFreeChart
Plotting with scala-chart
Plotting with Wisp
Summary
9
Visualizing Multi-Dimensional Data in Scala
Visualizing Multi-Dimensional Data in Scala
Obtaining data to visualize
Andrews curve
Parallel coordinates
Scatter plot matrix
Sammon mapping
Improving the program
Summary
Index
Index

Using Breeze in your project

Adding Breeze to your project is simple. As elsewhere in this book, we will be using SBT to handle our builds. Make a new directory for your project. Then, create a new file called build.sbt and add the following lines to it. You may want to change the versions to whatever the newest or preferred versions of Breeze and Scala are. Otherwise, you can probably just leave it as is:

libraryDependencies  ++= Seq(
  "org.scalanlp" %% "breeze" % "0.11.2",
  "org.scalanlp" %% "breeze-natives" % "0.11.2",
  "org.scalanlp" %% "breeze-viz" % "0.11.2"
)

scalaVersion := "2.11.5"

To play around with Breeze data structures, we will generally not want to create full programs using it. What we want is to just experiment a bit without committing to start a new project. It would be ideal if we could go into a Scala REPL to try the simple things with the Breeze libraries already loaded. Luckily, using SBT, this is easy to do. Once you create the build.sbt file provided here, issue...

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