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You don’t need a framework to start evaluating model output. A spreadsheet-sized rubric and twenty lines of Python get you surprisingly far.
A quick tour of R’s built-in airquality data with dplyr-free base R and ggplot2, plus a branded theme you can reuse.
How flow fields work, built up step by step in NumPy and matplotlib: the field, one particle, thousands of particles, smoother noise and a few variations.
Most decisions are two-way doors. Treat them that way and your team moves faster, and learns more.
Quarto notebooks, frozen results, GitHub Actions and Netlify. The whole pipeline in one picture.
A scrapbook of generative experiments with particle simulations and d3-force: dunes, trees, hairballs and falling particles.
Notes from six PyMCon 2020 talks on Bayesian modelling with PyMC: Pokémon GO rates, the Bayesian zig-zag, COVID-19 workflows, election models, Prophet-style time series and Bayesian ML.
Re-parameterising Antonio Sánchez Chinchón’s Physarum model in R and pairing it with Vans Design colour palettes.
Simple, elegant gradient images made with polar coordinates in ggplot2 and stitched together with magick.
Recreating hexbinned 3D elevation renders in R with elevatr, hexbin and rayshader, tried out on the Lake District, Peak District and Cairngorms.
Turning Environment Agency lidar data into ray-traced cityscapes with R for preparation and Blender for rendering.