A playground for University of Bologna Students and a 6-days seminar about digital tools.

Digital generative tools are a very important part of architectural education. Andrew Kudless during his conference at SimAE was telling about chinese traditional woodcraftsmen: they spend their first two years of apprentice in making their own tools. Today, we have a large pool of digital ready made tools, built to respond to more or less specific problems or tasks, while keeping a level of flexibility and personalization. The majority of these tools have hidden capabilities, which can only be accessed bypassing the conventional interface and getting close to the machine logic of programming or building parametric components which generate shapes. Thus, seriality, differentiation, complexity can be implemented in architectural projects through code, in order to exploit the power of algorithmic based complex systems which are the basis of biological systems.

But, before going through such complexity, we must start with simple tasks and simple rules. Before playing seriously we need practice. This is the playground where a bunch of students will start to practice, a pool where they will share their results and questions. Maybe the stuff here that will be posted will seem obvious or naive to the navigated code-monkey, but, as I mentioned before, we all start from the basics and this is intended as a place to start. However, any comment and contribution is appreciated.

Playground is open, let's play! _ Alessio


Interpolation function

In a discussion on the Grasshopper Google Group, David Rutten (btw... whenever you read, hear or pronounce this name please join hands as in prayer and say "Thank you, Zen master!"), as I said, David Rutten (repeat) has posted a useful and easy to implement function for interpolation. Here's the text extracted from the discussion:

there's a good function that always works when interpolating linearly between two tensors (be they numbers, vectors, points... any kind of data that can be blended).

If you have 2 values (A & B) and you want to interpolate between them at f (a blending factor), the function is always:

R = A + f * (B-A)

For example, let's fill in a few numbers and see what happens... Let's assume we want to find the value one quarter along the way between 15 and 19:

R = 15 + 0.25 * (19-15)
R = 16

Or, let's go twice beyond two points {10, 10, 0} and {12, 15, 4}

R = {10, 10, 0} + 2.0 * ({12, 15, 4} - {10, 10, 0})
R = {10, 10, 0} + 2.0 * ({2, 5, 4}) <---- if you subtract two points you get the vector going from A to B R = {10, 10, 0} + {4, 10, 8} R = {14, 20, 8}

This function is handy because it works without division (no division by zero errors), it works well when A is larger than B and it works for every value of f (i.e. you can also use it to extrapolate).

Well, nothing really new to those of you guys who followed the seminar, we talked and applied a lot of interpolations as a basic task of implementing gradients at different levels of discretization, but I think Rutten explains it very straightforward so it might be useful to have it as a reminder. Now go and apply it to any attractor/repellor/blend case you might undergo from now on.

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