Skip to main content

The week that wasn't (written about)

To be exact, it's been almost 10 days since I last wrote. It's not that I don't have anything to say anymore, I've been talking about menial, day-to-day, conventionally boring stuff all along, it's just that I lost interest in telling people how (conventionally) boring my days were. I can say that I needed a break from writing. I can say that I was busy with work. I can say that I was not interested in writing anymore but I guess none of them are the true reason. I guess I just stopped caring. I don't really have much of a reason as to why I stopped writing and why I am starting again.

It's been a productive week I guess, compared to the same week last year that is. I got tired of having to solve the same problem over and over again so I decided to latex my solutions. I was also getting frustrated/irritated because I wasn't finding practice problems at my level. And because most textbooks don't have a solution sets. One long term goal that I've decided upon this week is to take up a common textbook for which solutions aren't already available online, work them out and put them up online. People like me need reassurance that what they're doing is correct and in fact gives the right answer so I thought it'd be good. Also, I tend to forget a lot so latexing everything will help me down the line, I'm sure. Here is a small hint at what's cooking in this regard. Actually, that's all there is, I just wanted to start a sentence with 'Here is a small hint of ...'.

I'm working on a couple of other small projects, as I have been over the last couple of months. I'll write about them when they reach an acceptable level of completion. I still haven't been able to find time or help to work on the tougher (i.e one that take longer) ideas. Sigh...

Popular posts from this blog

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…

Pandas download statistics, PyPI and Google BigQuery - Daily downloads and downloads by latest version

Inspired by this blog post :, I wanted to play around with Google BigQuery myself. And the blog post is pretty awesome because it has sample queries. I mix and matched the examples mentioned on the blog post, intent on answering two questions - 
1. How many people download the Pandas library on a daily basis? Actually, if you think about it, it's more of a question of how many times was the pandas library downloaded in a single day, because the same person could've downloaded multiple times. Or a bot could've.
This was just a fun first query/question.
2. What is the adoption rate of different versions of the Pandas library? You might have come across similar graphs which show the adoption rate of various versions of Windows.
Answering this question is actually important because the developers should have an idea of what the most popular versions are, see whether or not users are adopting new features/changes they provide…

Adaptive step size Runge-Kutta method

I am still trying to implement an adaptive step size RK routine. So far, I've been able to implement the step-halving method but not the RK-Fehlberg. I am not able to figure out how to increase the step size after reducing it initially.

To give some background on the topic, Runge-Kutta methods are used to solve ordinary differential equations, of any order. For example, in a first order differential equation, it uses the derivative of the function to predict what the function value at the next step should be. Euler's method is a rudimentary implementation of RK. Adaptive step size RK is changing the step size depending on how fastly or slowly the function is changing. If a function is rapidly rising or falling, it is in a region that we should sample carefully and therefore, we reduce the step size and if the rate of change of the function is small, we can increase the step size. I've been able to implement a way to reduce the step size depending on the rate of change of …