A month of math software – January 2012
Welcome to the first MMS of 2012. This series has been going for a year now and I’m very pleased to say that it’s become quite popular. In the beginning I had to trawl the web for all of the news I featured here but a sizeable percentage of it gets sent to me these days. If you’ve got some news about mathematical sofware then contact me and tell me all about it.
General purpose mathematics
- Sage, the python based open source computational algebra system, has been updated to version 4.8. View the changelog to see what’s new. 94 people contributed to this release according to the changelog which is very impressive! I wonder how that compares to the number of developers on commercial systems such as Maple, Mathematica and MATLAB?
- After a long wait, we get not one but two new versions of the free Mathcad clone, Smath Studio in one month. Lots of great new features in versions 0.90 and 0.91 of this very nice multiplatform application.
- Verision 2.18-3 of Magma, the commercial computational algebra system, has been released.
- The new Mathematica StackExchange site has been launched so head over there for all of your Mathematica question and answer needs.
- The Mathworks have released an online community programing game for MATLABers called Cody. Problems start off incredibily easy and as you solve them, more difficult ones get unlocked. Your attempts are automatically scored by The Mathwork’s servers so feeback is instant and you can view other people’s solutions once you’ve solved a problem yourself. All in all, a great new way to sharpen your MATLAB programming skills.
Partial Differential Equations
- A new set of open-source software tools written in C++ for performing Partial Differential Equation (PDE) analysis and solving PDE constrained optimization problems has been released – Stanford University Unstructured (SU2)
- An article on smartphone apps for mathematics, written by Peter Rowlett, Hazel Lewis and I, has been published in the January 2012 edition of Mathematics Teaching. Ironically, none of the authors of the article have seen the finished product yet since we are not subscribers!
- Michael Carreno sent me news of the release of his graphical calculator app for iPhone, AbleMath. I haven’t had chance to try it yet since Mrs WalkingRandomly refuses anything mathematical on her iPhone and I am an Android man myself. However, the screenshots look very nice and, since it’s free, it’s a lot cheaper than those expensive, underpowered junkers that American schools seem to insist on teaching with.
- Version 3.0 of the NLEVP (Nonlinear Eigenvalue Problems) Toolbox for MATLAB was released in December 2011 but I found out about it too late for December’s edition of MMS. It contains problems from models of real-life applications as well as problems constructed specifically to have particular properties. The collection is fully documented in the Technical Report and user’s guide. This release contains 52 problems (up from 46 in version 2.0) and new functionality; it is also now compatible with GNU Octave.
- ViennaCL, a GPU-accelerated C++ open-source linear algebra library, was updated to version 1.2.0 on December 31st (just missing the deadline for December’s Month of Math Software). Roughly speaking, ViennaCL is a mixture of Boost.ublas (high-level interface) and MAGMA (GPU-support), yet based on OpenCL rather than CUDA.
- Version 0.95 of RStudio has been released. RStudio is an open-source integrated development environment (IDE) for the free statistical programming language, R. Check out the screencast detailing the new features.
From the blogs
- Happy 10*9*8+7+6-5+4*321
- Best Practices for Programming MATLAB
- Step-by-Step Differential Equation Solutions in Wolfram|Alpha
- PTC are preparing us for a new release of Mathcad Prime with several blog posts. Topics include performance enhancements, collapsible areas, and symbolic calculation.
- I should really be including this next one in February’s edition but it’s so interesting that I think I’ll share it now. Aurélien Garivier has written The Baum-Welch algorithm for hidden Markov Models: speed comparison between octave / python / R / scilab / matlab / C which gives you exactly what it says on the tin.