In celebration of pi-day, let’s look at a method of computing pi using random numbers that is often presented in probability, statistics or other classes, as an elementary example of using random sampling and / or simulation.
In my case, the first time I remember seeing / hearing about this example was in a probability class, however we didn’t actually write any code to try it, we just looked at the idea.
Aviso: eso ha sido un trozo de texto que escribí para practicar mí español, no tiene nada que ver con FarSounder oficialmente.
Introducción En mi empresa, se llama FarSounder, hacemos un sistema de Sónar para los buques y los yates. El objetivo principal de este sistema es buscar cosas que sean peligrosas delante de la nave y bajo el agua. Hay un sensor que se pone en la proa, que está dirigido hacia delante, por supuesto.
We’ve all got a little more time on our hands lately due to social distancing and COVID-19 (unless you have young children). I’ve been partly entertaining myself by learning new programming languages and frameworks, and also with some programming puzzles on sites like HackerRank.
I found one problem I ran into recently particularly interesting, and I enjoyed figuring it out (read: drove me crazy for a bit). This post is a write up of the problem and the solution that I ended up with.
It’s been about a year or so since we officially upgraded all of our tooling at my job at FarSounder from Python 2.7 to Python 3 (3.6 at the moment). Aside from the syntactic changes, there have been a handful of updates in Python 3 that I’ve found to really increase the readability of our scripts. One of those updates (from back in Python 3.4) has been the introduction of the pathlib module.