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#rayshader

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Using R to simulate the sky for the full day of July 30th, 2025 in Washington, DC

(hint at what's coming in the future for rayshader: give a lat, long, and time of day, and render an image with not only the exact sun orientation at that time, but a realistic simulation of the atmosphere as well🧑‍🍳 🤌)

Following up yesterday's post, I figured the #MadisonWI 3D data viz was worth a short blog post with code. #rayshader is very powerful, but also has a steep initial learning curve. I learned a lot from @tylermorganwall's and other people's documentation and blog posts, and so I figured I should contribute back myself. haraldkliems.netlify.app/posts

Harald KliemsHarald Kliems: A 3D map of downtown MadisonUsing digital surface model data and `rayshader` to create a detailed rendering

Okay, this is it for the evening. Will keep working on it but I need to think of something else to do to keep myself motivated. Here's Jiminy Peak Resort, Hancock, Massachusetts.

Thoughts/suggestions welcome!

#rayshader adventures, an #rstats tale

More #rayshader #rstats stuff: I wanted to try rendering at a higher number of samples and see if it looks significantly better and how long it'd take. At 256 samples (1920x1080), it does look very good, but rendering took forever, partly because R kept crashing every 50 or so frames. Each frame took about 2 minutes to render on a Macbook Pro M3 with 36 GB RAM. Currently I'm rendering a 64 sample version, which seems to take about 45 seconds/frame. I'll post for comparison once it's done.

#RayShader adventures continue. I'm happy enough with my base map elements that I started learning a bit about controlling the animation. Rendering hundreds of frames takes a long time, and so I needed to reduce the level of detail in order to be able to fine tune the various parameters. The turns are still a bit too jerky for my liking, but overall it's a big improvement over my earlier efforts.