An occasional series in esoteric programming issues. As part of a larger analysis project I needed to implement a short program to determine the closest distance of two line segments in 3D space. This will be used to sort out which segments to compare… like I say, part of a bigger project. The best method to do this is to find the closest distance one segment is to the other when the other one is represented as an infinite line.

Top Trumps is a card game for children. The mind can wander when playing such games with kids… typically, I start thinking: what is the best strategy for this game? But also, as the game drags on: what is the quickest way to lose? Since Top Trumps is based on numerical values with simple outcomes, it seemed straightforward to analyse the cards and to simulate different scenarios to look at these questions.

2016 was the 400 year anniversary of William Shakespeare’s death. Stratford-upon-Avon Rotary Club held the Shakespeare Marathon on the same weekend. Runners had an option of half or full marathon. There were apparently 3.5 K runners. Only 700 of whom were doing the full marathon. The chip results were uploaded last night and can be found here. Similar to my post on the Coventry Half Marathon, I thought I’d quickly analyse the data.

Fans of probability love random processes. And lotteries are a great example of random number generation. The UK National Lottery ran in one format from 19/11/1994 until 7/10/2015. I was talking to somebody who had played the same set of numbers in all of these lottery draws and I wondered what the net gain or loss has been for them over this period.

The end of the month sees the Coventry Half Marathon. I looked at what constitutes a good time over this course, based on 2015 results. I thought I’d post this here in case any one is interested. The breakdown of runners by category for the 2015 event. Male Senior (MSEN) category has the most runners, constituting a wide age grouping. There were 3565 runners in total, 5 in an undetermined category and 9 DNFs.

I’ve previously written about analysing my iTunes library and about generating Smart Playlists in iTunes. This post takes things a bit further by generating a “perfect playlist” outside of iTunes… it is exclusively for nerds . How can you put together a perfect playlist? What are your favourite songs? How can you tell what they are?

I was searching for the excitation and emission spectra for mNeonGreen. I was able to find an image, but no values for the spectra.

I put a recent code snippet put up on the IgorExchange. It’s a simple procedure for averaging a set of 1D waves and putting the results in a new wave. The difference between this code and Average Waves.ipf (which ships with Igor) is that this function takes the average of all points in the wave and places this single value in a new wave. You can specify whether the mean or median is used for the average.

The transition for scientific journals from print to online has been slow and painful. And it is not yet complete. This week I got an RSS alert to a “new” paper in Oncogene.

An IgorPro tip this week. The default font for plots is Geneva. Most of our figures are assembled using Helvetica for labelling. The default font can be changed in Igor Graph Preferences, but Preferences need to be switched on in order to be implemented. Anyway, I always seem to end up with a mix of Geneva plots and Helevetica plots.