After last weeks return to posting, I thought it was time to do something vaguely useful (and actually talk about it) so I’m tidying up a few meetup sessions I’ve presented at into a series of Basic Data Science (with Python) posts. This is the first one and covers my Python environment, the Jupyter notebook environments I use for analysis, and some on the Plot.ly graphs and RISE / Reveal.js methods I use to turn those notebooks into presentations. ...
Quick one more as a reminder to me than anything else. As part of my PhD work I’m building different behaviours for virtual submarines. I’ll be explaining some parts of my work in a separate post, but basically, I needed to random walk. Random walk in 2 dimensions is easy; pick two random numbers, go that way. Unfortunately doesn’t work that way on a spherical surface So to make things easier, I stole this StackOverflow answer from dmckee and tidied it up a bit for my purposes. (Assuming everyone else is like me and does import numpy as np) ...
About 6 months ago now, I had the pleasure of getting Phil Herron to talk at the Farset Labs PyBelfast group about his work in GCC/Cython fron end optimisation work, which was simultaneously waaaaay over my head and really interesting. I’ve been a ‘Python Primary’ software engineer now for about 5 years, in web-dev, infrastructure monitoring, data analysis, and scientific computing, with some esoteric stuff involving small-vector linear algebra optimisation on GPU CUDA, Matlab bridging with Octave / Oct2Py, and distributed state systems. But somehow, I’ve managed to dodge hardcore Cython. ...