Last night I went to workshop called something like "Matter into Music" at ITP CAMP. It was a workshop about using Pure Data to create musical instruments (made of Arduino and sensors).

I think of Pure Data is the open-source (ie FREE) version of MaxMSP, a similiar looking platform(?) for artsy multimedia programming. Using graphical patches of blocks to get a computer to do something is a mode of progamming that intrigues me. It's different from what I do day to day and I figured it would a good change of pace.

At first I didn't really understand why non-programmer types would choose PD over something like Processing or OpenFrameworks. I suppose a visual representation of functions, outputs, inputs is more accessible than a wall of text.

I found myself a bit lost in the beginning. A couple of points for me:

• the documentation for PD is inconsistent and not really accessible, unlike the Ruby on Rail Guides and the documentation for Polymer.
• the names of blocks used in created patches (ie apps) are obscure. Like there is one object called "Message", which I thought would be like a console object. Nope! It's more like an input that sends configuration to the patch.

I wonder if memorizing the documentaiton of a new programming language would make learning it better? Like would knowing all the methods available for use would make the language easier to use?

Another reason why I got lost is that the workshop also dealt with synthesizing sound. Terms like osc, phasors got tossed around. We used things like multipliers to get the computer to bleep boop, and plugged blocks into something called dac (Digital audio control?). Unfamiliar territory for me.

I didn't really build anything during the workshop; I tinkered more than anything else, but I think Pure Data is something I'll definitely look into more in the future.

Something that intrigued me was the Satellite CCRMA. One thing I didn't like about musical intruments demo'd in the workshop, was that they were still connected to a clunky laptop. With Satellite, you can load the environment on a Raspberry Pi, connect your instrument and go.