the multiprocessing library in python

As part of a course on computational methods, I am simulating molecular dynamics using the velocity verlet algorithm. Simply put, given an initial distribution of particle position & momenta and an interaction potential, we can use the momenta to update the position and the forces, derived from the potential, to update the momenta. Depending on which is updated first, the position or the momentum, we call them the verlet or the velocity verlet. One of the major hurdles here, given a large system size is to measure forces on all particles, the x and y components, simultaneously. Note that one cannot measure the force for a particle, update it's position and momentum and then move to the next particle! That's wrongedy wrong wrong! One needs to measure the forces on each particle given the current positions/configuration and then update the momentum, followed by an update to the positions. And then the cycle repeats. Like i was saying, one of the time-taking things is to measure the forces on each particle and I was vexed having to wait. I tried making the code lean but i couldn't go beyond a point conventionally. Then it struck me that one could parallelize computing the forces. I started looking for examples of multiprocessing in python and came across this excellent introduction. And voila! 4 lines of code and i reduced the time it took to compute forces by half! maybe if i try a bit more i can bring it down further. And all it took was 4 lines of code -

import multiprocessing as mp
pool = mp.Pool(processes=4)
results = [pool.apply_async(local_force(i), args=(i,)) for i in range(399)]
output = [p.get() for p in results]

* - local _force(i) is a function that i had defined earlier that measures the force on a given particle i

Animation using GNUPlot

Animation using GNUPlotI've been trying to create an animation depicting a quasar spectrum moving across the 5 SDSS pass bands with respect to redshift. It is important to visualise what emission lines are moving in and out of bands to be able to understand the color-redshift plots and the changes in it.
I've tried doing this using the animate function in matplotlib, python but i wasn't able to make it work - meaning i worked on it for a couple of days and then i gave up, not having found solutions for my problems on the internet.
And then i came across this site, where the gunn-peterson trough and the lyman alpha forest have been depicted - in a beautiful manner. And this got me interested in using js and d3 to do the animations and make it dynamic - using sliders etc.
In the meanwhile, i thought i'd look up and see if there was a way to create animations in gnuplot and whoopdedoo, what do i find but nirvana!

In the image, you see 5 static curves and one dynam…

on MOOCs.

For those of you who don't know, MOOC stands for Massively Open Online Course.

The internet is an awesome thing. It's making education free for all. Well, mostly free. But it's surprising at the width and depth of courses being offered online. And it looks like they are also having an impact on students, especially those from universities that are not top ranked. Students in all parts of the world can now get a first class education experience, thanks to courses offered by Stanford, MIT, Caltech, etc.

I'm talking about MOOCs because one of my new year resolutions is to take online courses, atleast 2 per semester (6 months). And I've chosen the following two courses on edX - Analyzing Big Data with Microsoft R Server and Data Science Essentials for now. I looked at courses on Coursera but I couldn't find any which was worthy and free. There are a lot more MOOC providers out there but let's start here. And I feel like the two courses are relevant to where I …

On programmers.

I just watched this brilliant keynote today. It's a commentary on Programmers and the software development industry/ecosystem as a whole.

I am not going to give you a tl;dr version of the talk because it is a talk that I believe everyone should watch, that everyone should learn from. Instead, I am going to give my own parallel-ish views on programmers and programming.
As pointed out in the talk, there are mythical creatures in the software development industry who are revered as gods. Guido Van Rossum, the creator of Python, was given the title Benevolent Dictator For Life (BDFL). People flock around the creators of popular languages or libraries. They are god-like to most programmers and are treated like gods. By which, I mean to say, we assume they don't have flaws. That they are infallible. That they are perfect.
And alongside this belief in the infallibility of these Gods, we believe that they were born programmers. That programming is something that people are born wit…