ScalaLab is a free and open-source utility that aims to provide an efficient scientific programming environment for the Java Virtual Machine.
The scripting language is based on the Scala programming language enhanced with high level scientific operators and with an integrated environment that provides a Matlab-like working style.
In addition, all the huge libraries of Java scientific code can be easily accessible. The main potential of the ScalaLab is speed and flexibility.
Furthermore, ScalaLab includes the ScalaSci scripting engine, based on the new Scala programming language, that obtains scripting speed by resolving method calls at compile time ("statically typed").
The code for scripting is really fast, close to Java (sometimes slower, sometimes faster), and usually faster from equivalent Matlab .m scripts.
ScalaLab is cross-platform and it works on Mac OS X, Windows and Linux.
Detailed instructions on how to install and use the ScalaLab utility on your Mac are available HERE.
· Java 1.7 or later
What's New in This Release: [ read full changelog ]
· ScalaSci classes are better organized, Embedded Systems Construction is simplified, concerns ScalaLab211 (17 June)
· Framework for developing stand alone applications with ScalaLab 211 (June 15), see EmbeddedApplicationsWithScalaLab.pdf document, at downloads
· Better support for Band Matrices, see new version of ScalaLab User guide
· ScalaLab based on Scala 2.10.2 (12-June)
· Improvements in integrated Complex number and ComplexMatrix support
· Minor user interface improvements (04-June)
· Multidimensional integration support
· Improved .pdf documentation
· Scala 2.11 M3 based version
· MATLAB-like :: operator, see WhatsNew wiki page
· Adaptive Functional Plotting (May22)
· Numerical Recipes based FFT is used by default (May 21)
· Improvement in the conformance to the scalaSciMatrix interface
· Convenient factory constructors for matrices
· Plot popup menu option (May 15) - see WhatIsNew wiki page Improved code completion with F4 based on Java reflection (May 13)
· Improved support for JBLAS fast native routines...