Python Audio Visualizer

I wrote a simple python program with the Processing IDE/library to visualize audio by drawing small lines in a 3D plane for every sample in a given audio buffer, where the height (y-axis) of each line corresponds to the sound value of that sample as the audio plays. The depth (z-axis) of the side bands and width (x-axis) of the rear band correspond to the size of the audio buffer. The left band’s input is the left channel of the audio, the right band is the right channel, and the rear band is a mix of the two channels.

Beehive Hexbugs

Using different audio samples taken from inside a Colorado Top Bar beehive, my group of peers Amanda Kriss, Leo Liu, Bianca Garcia and I were able to create generative pieces of physical artwork. The hive sounds were fed into a Max patch, whose purpose was to translate hive sound data into data that could be partitioned into “left”, “right”, “forward”, and “backward” directions. This was done by creating amplitude thresholds for forward/backward controls, and frequency thresholds for left/right controls. These would eventually reach a Hexbug with markers on its legs, drawing as it walks around the canvas. This way, the Hexbug would act differently based on different sound inputs; i.e., different stages in the beehive’s formation (see final pieces).

Here is the code for the MAX Patch.

Screen Shot 2016-05-28 at 3.27.42 PM.png — The Patch

The Max patch communicates with code written by Chip Audette we ran on our Arduino hardware, designed to output left, right, up, and down controls. The leads connecting to the arduino were soldered to the Hexbug remote control board in order to take over control of the Hexbugs.

IMG_4477 (1).JPG

Short videos of the bots in action:

Finished Pieces:

Using sounds from a cold hive:

Hexbug1

Using sounds from a hive just upon formation, drawing with the crab bot:

Hexbug3

Using sounds from a hive just upon formation, drawing with the spider bot:

Hexbug2

F-111 Simulation Game

Here I created a game/simulation reflecting the terrain-following radar system on an F-111 military plane.

I wrote the game in the Processing IDE with Java’s Processing library. Here is my code for the game.

The purpose of the game is to present a simple display of how the terrain-following radar (TFR) works, and why it’s helpful to a pilot. The controls are simply TFR ON/OFF, RESET, UP, and DOWN. When the TFR button is not pressed, the plane must be guided by the user over the oncoming hills, but not too high, similar to the classic helicopter arcade game. You get more points the lower into the hills you go. Every 10 seconds, the display of the plane and hills will go black as it turns to night time, where it will stay black for 10 more seconds before turning back to day. This is why the TFR button is especially important; once it is turned on while within the blue “TFR” safe zone, the plane will guide itself over the hills, something imperative in night flights. This radar system was originally developed in the 1960’s for this very purpose; low-level night missions, and general low-visibility situations.

I created a simple housing for the game using a MaKey MaKey board, where I programmed the buttons to correspond to the physical buttons I made out of spoons and a screw. The triangular piece of metal on the left of the housing is a ground for the user to place their hand on, because the system has to be grounded for signals to carry through.

Monty Hall Simulation

The Monty Hall Problem is a probability puzzle, made famous by the 1970’s TV show ‘Let’s Make a Deal’. The problem arises when the guest is given 3 doors to choose from, behind only one of which hides a prize. Once a guess is made, the presenter, Monty Hall, opens the door which the guest did NOT guess, but which also does NOT have the prize behind it, asking then if the guest would like to change door guesses based on this new information.

Despite the seeming 50-50 chance of guessing correctly now, the guest now has a 33.3% chance of guessing correctly if they do not change their guess, and a 66.6% of guessing correctly if they do switch their guess. This seems unbelievable, but it’s due to the fact that when the original guess was made, the guest knew nothing about the doors, and there was a 66.6% chance the prize was behind one of the two doors not chosen. But now that the guest has new information saying the prize is definitely NOT behind one of those two doors, the 66.6% probability becomes concentrated on the only remaining door not originally guessed.

This is a practice in Bayesian reasoning, where the new probability of guessing the correct door is a condition of the new information given when Monty Hall shows you it’s not behind one of the doors.

I wrote a program which replicates this situation for any number of simulations, showing the probability of winning when switching door guesses and when remaining with the original door guess:

Skyline in Processing

Animated Seattle skyline made with only solid shapes and fills. UFO pans across the screen, and the city lights flicker.

This too was written in Java/Processing.

Processing Portfolio

Here I created a portfolio of all of my work in Processing for my Coding in Emergent Digital Practices (EDPX 2100) course at DU.

It was written in Java/Processing, along with the other pieces. The interface is broken down into weeks, then by lessons. Clicking on a week brings up the lesson options, and clicking on a lesson brings up the sketch I created for that lesson, whether animation, practice, or finished piece, in the top left of the window.

Mola

Created in Adobe Illustrator.

Image Play

I manipulated this vector image by Michael McMillan to create the following piece. I then sent it to a vinyl cutter and made it into vinyls decals.

Text Portrait: Casey Reas

Casey Reas is an artist working mainly in the digital realm, using and writing software. He’s well known especially for his co-creation of the Processing platform and libraries, which are now used openly and commonly by digital artists. Several of my projects have also been created in Processing. Much of his work can be found on his website, reas.com.

The text used in this piece comes from defining keywords about the artist, and the background and shirt text is made up of code I’ve written in Casey’s software, Processing.

Self Portrait

This design embodies a self-absorbed satirical persona, representing an entirely for-fun club baseball team as a group of famous athletes on the cover of the hypothetical magazine “The Pioneer”.

Franceschi_Project7_SelfPortrait_1