Programming and writing about it.

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Tag: Research

2-cent tip: IEEE PDFeXpress compatible PDF file

This is a borrowed 2-cent tip from a source I now don’t recall. (Kindly comment if it was YOU). My apologies in advance for not remembering you.

To create IEEE PDF eXpress compatble PDF files from your LaTex sources: (on Linux)

  1. Create the .dvi file: $ latex  paper.tex
  2. DVI to PS: $  dvips -Ppdf -G0 -tletter paper.dvi
  3. PS to PDF:  ps2pdf -dCompatibilityLevel=1.4 -dPDFSETTINGS=/prepress paper.pdf

And you should be good to go.


Fedora Scientific: Open Source Scientific Computing

Hello Fedora People, this happens to be my first aggregated post on Planet Fedora! Great to be here. Onto real stuff.

Okay, this post comes at a time when December is already upon us, Fedora 16 has been released for a month now and that also means that Fedora Scientific has seen the light of the day for a month now. I felt this might be a good time to describe the current state of the project and my plans for the next release(s).

Software in Fedora Scientific (Fedora 16)

The current list of software available in Fedora Scientific is available here [1]. Briefly, they are:

Scientific Computing tools and environments: The numerical computing package GNU Octave, front-end wxMaxima, the Python scientific libraries SciPy, NumPy and Spyder (a Python environment for scientific computing) are some of the software included in this category. A development environment for R, the statistical computing environment, is also included, and so are the ROOT tools for analysing large amounts of data.

Generic libraries:    Software in this category includes the GNU C/C++ and FORTRAN compilers, the OpenJDK Java development tools, and the IDEs NetBeans and Eclipse. Also included are autotools, flex, bison, ddd and valgrind.

Parallel  and  distributed programming   tools / libraries: Software tools and libraries included in this category include the popular parallel programming libraries OpenMPI, PVM, and the shared-memory programming library OpenMP. Also included is the Torque resource manager to enable you to set up a batch-processing system.

Editing,  drawing  and  visualisation  tools: So you have simulated your grand experiments, and need to visualise the data, plot graphs, and create publication-quality articles and figures. The tools included to help you in this include LaTex compilers and the Texmaker and Kile editors, plotting and visualisation tools Gnuplot, xfig, MayaVi, Dia and Ggobi , and the vector
graphics tool Inkscape.

Version control, backup tools and document managers: Version control and back-up tools are
included to help you manage your data and documents better: Subversion, Git and Mercurial are available, along with the back-up tool backintime. Also included is a bibliography manager, BibTool.

Besides these four main categories, some of the other miscellaneous utilities include: hevea–the awesome LaTex-to-HTML converter, GNU Screen and IPython.

As you can see that the list of software is quite extensive, thanks to the awesome Fedora developers who have packaged this gamut of software.

Future Plans

The current release marks the beginning of a project very close to my heart. I feel that such a spin shall definitely be useful for the current Linux community members and future enthusiasts who use Linux for their computing needs. In the next release(s), I intend to explore the following directions for the spin:

  • A GNOME based spin in addition to the current KDE spin
  • Custom wallpapers
  • Work with the websites team to update the Spin website to include high quality images of scientific software and more content
  • Collect feedback from the community and act on it  :-)

Talk to Us, Contribute

Come, talk to us on the Fedora SciTech SIG mailing list [2]. Thanks to all the members of SciTech SIG for their useful discussions and comments.


Fedora Artwork and Fedora Websites team for help in the artwork for the spin,  Bill Nottingham for the initial comments on the idea and Christoph Wickert  for seeing the spin through for release. All the other people who contributed even with a single word of encouragement online and offline, please acknowledge my sincere thanks.



Parts of this blog post has been reproduced from my article on Fedora Scientific Spin  published in the December, 2011 issue for Linux For You.

Fedora Scientific: The Prologue

The Itch

When I wrote this [1] article a while back, the intention was to publicize the software tools that I was personally using at the point of time to help me in my research work- plotting graphs, analysing data, writing papers, running simulations, e.t.c. Those tools soon became indispensable for my research and hence I always installed them first after a fresh install of Linux. I longed for a Linux distro which would already have these tools installed and allow me to have a fully functional Linux workstation from the first boot.

The Scratching begins

I was getting wary of Ubuntu after their last release (April, 2011) and was looking for a new distribution to commit to – I thought I will give Fedora a shot (last time I tried Fedora was during the Fedora Core days) on one of my computers. Then, I started looking around for ways to create custom Fedora spins when I came across the tutorial for Fedora [2]. And that’s pretty much all I needed to get started working on a Linux for users in Science and Academia – Fedora Scientific

Discussions on Mailing lists

The most fruitful technical part of the discussion happened on the Canberra Linux User’s Group. [4] Thanks to all the folks who made suggestions for various packages and more importantly opined that the spin would be useful to the target audience.

Fedora Spins SIG

The official word on whether the proposed spin would be found useful by the Fedora community in general and Linux community overall was decided by the Fedora Spins SIG  [5]. Thanks to their support and approval.

Where next

Fedora Scientific is officially on course for release with the Fedora 16 release in the next few days. The nightly builds are now available from [6]

Talk to Us, Contribute

Come, talk to us on the Fedora SciTech SIG mailing list [7]. Thanks to all the members of SciTech SIG for their useful discussions and comments.  This page explains the spin in more detail.

Current List of Packages

The current list of software made available in Fedora Scientific Spin are at [8].


Fedora Artwork and Fedora Websites team for help in the artwork for the spin,  Bill Nottingham for the initial comments on the idea and Christoph Wickert  for seeing the spin through for release. All the other people who contributed even with a single word of encouragement online and offline, please acknowledge my sincere thanks.



In the next post, which I intend to do soon after the official release, I shall talk about the applications and programs installed in Fedora Scientific.

And last, but by no means the least- Snowy, you make this world a better place for me.

Book Review: Essentials of Metaheuristics

Getting the book:

I picked up a copy of this book from the man himself, Sean Luke at the IEEE CEC 2011. I was “aware” of this book from a while back, so I thought it might be a good idea to pick a print copy for light readings during my travels post-conference. Here is a brief review of the book:


As the author states, the book is a compilation of undergraduate lectures notes on Metaheuristics. It focuses on the applications of Metaheuristics to optimization problems including Multi-objective optimization, Combinatorial optimization and Policy optimization. Depending on your experience with Metaheuristics, this book will serve a different purpose for you:

  1. If you are quite well versed with them, this book will be a nice light reading, with interesting bits and pieces throughout
  2. If you are starting with them, or want to start with Metaheuristics, this book gives a nice well rounded view of the state-of-the art


The book starts with an overview of gradient based optimization methods in Chapter 1 gradually moving to stochastic methods such as randomized hill-climbing, tabu search, simulated annealing in Chapter 2.

Chapter 3 introduces population methods — Evolution Strategies, Genetic Algorithms, Differential Evolution and Particle Swarm Optimization.

Over the last three chapters, the author introduces some fundamental concepts: the choice of representation of solutions, issues of exploration v$ exploitation and local optima traps.

Chapters 4-10 each discuss one specific topic. For example,  Chapter 4 is dedicated to representation of solutions — vectors, direct encoded graphs, program trees and rulesets.  Chapter 5 discussess parallel methods for metaheuristics and Chapter 7 talks about Multi-objective optimization. Chapter 8 and 10 talks about combinatorial optimization and policy optimization respectively. So, if you are looking for anything specific, you can directly jump to the relevant chapter (assuming, of course that you have the pre-requisite knowledge). As you can see in the ToC, most of the chapters from 4-10 depends on Chapters 3 & 4.

The book finally concludes with some descriptions of test problems and statistical tests that researchers often use to test their algorithms. The very important issue of selecting a proper random number generator is discussed in this chapter.


This book along with Evolutionary Computation: A Unified Approach (You may be interested in my review) is great for getting a holistic view of the Meta-heuristic methods, especially if you are more experienced with only one of them.

Getting the book:

IEEE CEC 2011: Post-conference Thoughts

I am currently sitting by the window of my 10th floor of my hotel room and New Orleans looks beautiful at this time of the night. The neon glows of the hotels and shops around and the lights of those huge wooden/steel bodies on the mighty Mississippi is quite a spectacle for my bespectacled eyes. The IEEE Congress on Evolutionary Computation 2011 concluded today.  Over three days of paper and poster presentations, plenary lectures, cruise dinner on the steamboat Natchez and the sumptuous banquet last night, it was an awesome conference. Thank you Dr. Alice Smith and congratulations on the wonderful conference, which must have given you a lot of sleepless nights.

Here are some rough notes/thoughts/rants on the conference:

Plenary lectures

Each of the three days of the conference began with a plenary lecture. Natalio Krasnagor delivered the lecture on the first day talking about his work at the confluence of Natural sciences and Evolutionary Algorithms. Holger Hoos delivered the lecture on the 2nd day  where he had a lot of interesting things to talk about his research and mostly on topics of automating software development, having more degrees of freedom in software and algorithm selecting algorithms. Hod Lipson delivered the last of the plenary lectures and demonstrated his work on Evolutionary robotics and his super work, Eureqa. A lot to take home from each of these lectures. Enlightening and inspiring.

Interesting ideas/papers presented

  • A lot of work is being done on Genetic Programming, mainly as tools — in varied domains, from edge detection to blog network modeling. Once the IEEE CEC proceedings are indexed by IEEExplore, it would be very interesting to go through these papers. Available here.
  • Multi-view classification
  • Representation plays a key role in EAs and Daniel Ashlock‘s tutorial on this topic was (or supposed to be) quite enlightening, but I think I was busy doing something else. However, I intend to go through the slides he used and get an idea of the variety of representation schemes for different applications.


I usually tend to set high standards for myself and more often than not fail to achieve them, which ofcourse doesn’t deter me in setting them in the first place. Seeing a lot of “well known” people in this field presenting trivial works at a premier conference was quite disheartening. One good thing it does is that it makes me feel that may be I should be a little gentle to myself.

I wanted to change the world, but they lied to us

I don’t know about you, but I almost always think myself to be the cover page of the major world news papers or its nearest domain equivalent, whenever I do something cool/nice/interesting (according to myself, ofcourse). I thought writing up a paper titled “How does the good old GA perform at Real World Optimization?” would irk a lot of people and elicit reactions out of them. I guess nothing really matters. Sigh.

Well, anyway I am taking back a lot from this conference at the Big Easy. Good bye Poboy’s and Gumbo!

2-cent tip: Use them cores on MATLAB

Optimisation using Evolutionary Algorithms is a stochastic process. This makes it a fundamental requirement to “test” your algorithm using a number of different initial random seeds. Thus, several runs ranging from 10-30 of an algorithm are made to make a proper inference about its performance. Essentially this looks like:

"your algorithm"

This is essentially a sequential process and is a time consuming one. Even if you don’t have a cluster of nodes, but have a multi-core CPU at your disposal, you can easily make these runs run simultaneously on the multiple-cores using a couple of simple MATLAB constructs: matlabpool and parfor

First declare the number of worker labs using matlabpool open 3 . For example, if you have a quad-core box, you might want to set it to 3.  Then replace the FOR in above loop, by a parfor. Now you will see that there will be three MATLAB processes and three of your runs going on simultaneously.

Article: Getting Started with Inotify

Update: The PDF is now available.

It’s always fun to peek into one of the umpteen features of Linux. In the April, 2011 issue of Linux For You I take a hands-on look at Inotify.

The source code for this article is available at


2-cent tip: BibTex to bibitem format

I learnt this tip from:

Just putting it up here on my space, so as to replicate this awesomely useful tip so that I can quickly refer here when I need it and also for Google-fu to find it so that it may save some time for you, reader:


Create a refs.bib file with all the BibTex entries, which are easily available from Google Scholar or similar

Create a “dummy” .tex file with the following entries:


Now, do the following:

$ latex dummy
$ bibtex dummy
$ bibtex dummy
$ latex dummy

You will see a dummy.bbl file containing all your BibTex entries in \bibitem format.

Prof. Deb’s podcast on Science Watch

Hear Prof. Kalyanmoy Deb speak about his research on Multi-objective Optimization, Evolutionary Algorithms, Innovisation, Multi-modal Optimization in this ScienceWatch podcast:

Kalyanmoy Deb\’s podcast


SEAL 2010 Papers I liked reading

SEAL 2010 is happening at IIT Kanpur, India from the 1st to 4th December, 2010. As someone who was a part of the initial arrangements and was part of the lab hosting it, it is surely going to be legendary what with people like Narendra Karmarkar delivering keynote lectures. Needless to say, it would have been great to be present.

The papers are up on the Springer website and here are some papers I liked reading:

  • Improving Differential Evolution by Altering Steps in EC: This is a very approachable paper where the authors describe their experiments by modifying a standard DE algorithm my incorporating relevant ideas from another EA, G3-PCX. The bigger picture is to move towards unified approach to Evolutionary Computing
  • Bayesian Reliability Analysis under Incomplete Information Using Evolutionary Algorithms
  • Metamodels for Fast Multi-objective Optimization: Trading off Global Exploration and Local Exploitation
  • Generating Sequential Space-Filling Designs Using Genetic Algorithms and Monte Carlo Methods
  • And a paper which I would have surely liked, had I udnerstood the paper fully would be Beyond Convexity: New Perspectives in Computational Optimization

The papers are available online at