Summer is finally here in Zurich, and that means the BRG (BBQ Research Group) is back in action. With a brand new grill, beautiful weather and Alps in the background, we witnessed the dream run of Wales in the 2016 European Championship come to an end. Now we must sit through another 90 minutes (or 120 minutes…) of Portuguese football and haircuts…
Including Python code in LaTeX papers is very simple and convenient with the “listings” package. Documentation of the package is part of the (awesome) LaTeX wikibook…
Sublime Text is great, but using it properly is not as transparent as what most of us are used to. I will try to list here some of the things i had to figure out to start working efficiently.
By using the hidden/undocumented command ‘TestMooCow,’ you can synchronize two viewports in Rhino. It will link/unlink two viewports to pan/zoom/rotate in sync.
Python Triangle is a python wrapper around Jonathan Richard Shewchuk’s two-dimensional quality mesh generator and delaunay triangulator library. According to the Python Triangle docs, installation is straightforward. However, at least on my system, it didn’t work right out of the box. Luckily, the fix is quite simple.
At present it is quite easy in LaTeX to fit an image proportionally to a frame of fixed width and height. However, to fill a frame with that same image is not straightforward…
For our holiday card this year, we explored bringing 3D reciprocal diagrams into virtual reality! On the front of our holiday card, are planar projections of 3D reciprocal snowflakes. Using the “BRG XCard 2015” app, you will be able to see the holographic projections of the 3D reciprocal snowflakes in real-time! If you understand the frame-like snowflake as the structure (under given external loads, or equivalent self-stress), the forces within the bars of that structure are proportional to the areas of the corresponding, perpendicular faces of the solidlike snowflake.
Previously, in our post “The force density method”, we described how to use the force density method to compute an equilibrium shape of the provided network data. In this post we will show how to apply SciPy’s nonlinear solvers to the same problem.