Processing: Creative Coding and Computational Art

the time to play at whatever level you are at. This is a really important approach that
teachers are sometimes lousy at implementing. It is easy to get caught up in teaching the
pursuit of mastery, focusing on achievement goals for students and checking off the requisite
material covered. The school system reinforces this approach with standardized testing,
creating crammers and compartmentalizers who separate work and play, craft from
art. Is it any wonder that many of us (especially creative types) felt bored and frustrated in
the traditional classroom, especially in subjects that required methodical drilling or rote
memorization (like math)? Sadly, as we get older, we eventually label these subjects as the
problem, not the non-integrated teaching approaches. My experience in the classroom has
been that I find most people receptive to learning anything when it’s taught effectively.
And my vision of effective teaching always involves finding a way of integrating aspects of
play and work into the learning process. Before I launch into yet another whiny soliloquy,
I’ll sum it up with the following: real code art (whatever the heck that means) can be
made at any level—by a newbie coder learning the basics or a seventh-degree Java black
belt—and happy coding mistakes help us see the expressive possibilities at whatever level
we are at.
Before I end this chapter, I think it might be helpful to illustrate this point with a short
example of how I approach happy coding mistakes in my own process.
Algorithmic tree
I used to paint a lot of trees. Originally, I painted the entire landscape, but gradually over
time, I found myself zooming in closer on the trees, until one summer, I painted an entire
series of large paintings based on part of one tree. It is interesting watching your neighbors’
reactions as you spend more and more time standing in your backyard, staring up at
the same tree.
So in honor of my favorite tree, I thought I’d illustrate some creative coding by generating
a tree with code. Let me also preface this by saying that you shouldn’t try to follow this
code unless you already know how to program; it may seem totally overwhelming. My
main point here is to reveal my creative process, not to teach the code; the rest of the
book is for that. Feel free to run this sketch and make changes to the code to see what
happens. If you get any really cool results, I hope you’ll e-mail me some screenshots.
In considering the problem, I decided to think about trees some and to break the problem
down into simple parts. In a moment of brilliant clarity, I concluded that trees have a
trunk, branches, and leaves. OK, I know I can probably make a trunk (think straight vertical
line). Branches could be a little harder, and leaves, well, probably too hard (actually too
much work). Branches, I concluded, could be simplified as a thin trunk, splitting off to
another series of thinner trunks, splitting off to another series of thinner trunks, and so on.
Thus, it seemed branches could be made from a single branch machine, in a fractal progression
(huh?). By fractal progression, I mean the branches are self-similar and repeat.
Each branch’s ending point is a starting point for more branches, with a decreasing scale.
Thus, the tree thickness decreases from trunk to branch—which seemed pretty consistent
with real trees. I decided to put the leaves on hold for now. I was ready for a little sketch
of my branch plan (see Figure 2-2).
CREATIVE CODING
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