Matlab is a powerful programming language for scientific computing. The popularity of Matlab stems from the fact that it is a high level programming language focusing more on faster development and less on syntax. It also has many tool boxes that extend the functionality that is offered by basic Matlab on to other scientific and engineering domains. In spite of all these advantage, it comes with a price, the fact that we need to pay for purchasing, installing and maintaining it. Although the price we pay might be easily offset by the benefits, many Matlab like software are in existence and perform similar even if not the same set of functionality. In this blog, we will look at some of the alternatives. In all these alternatives, the program written to be run on Matlab can be run directly, within the constrains of functionality offered by that particular software.
FreeMat
FreeMat is a open source software released under GPL. It is available for most of the common OS like Windows, Linux and Mac. Installing the software on a Windows machine was a piece of cake. Its repertoire of functionality is large but does not have many of the toolboxes offered by Matlab.
Octave
Octave is another software available under GPL. The syntax of Octave commands are similar to Matlab (and not the same) and is also highly extensible using C, C++ and Fortran. Unlike FreeMat, Octave comes with many toolboxes for Image processing, Signal processing, Statistics etc. Installing the software on a Windows machine using cygwin is easy but installing from source on Linux machine requires expertise due to many dependencies.
Numpy and Scipy
Numpy and Scipy are Python modules that can be used to perform high level scientific computation like Matlab. Since these modules are based in python, their syntax is not similar to Matlab but due to its focus on high level programming, the syntax is generally simple. With installation of dependencies like python imaging library (PIL), we can perform image and signal processing. Scipy can also be used to perform optimization and statistics. Prebuilt binary packages are easy to install but installation from source is cumbersome due to its dependencies.
