[OLD SEMESTER] 15-104 • Introduction to Computing for Creative Practice
Professor Tom Cortina • Fall 2021 • Introduction to Computing for Creative Practice
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I really enjoyed this work by Patrick Gunderson. The visual complexity created by the ramdomly generated splotches of colour pattern is really visually pleasing. I really enjoy the complementing and in some cases contrasting colour patterns that are created randomly. It many arts it almost looks as if the art is capturing the motion of a specific object. He tries to incorporate imperfections into algorithmic systems the strikes the tension in between order and natural flow.
This project, by Tyler Hobbs, is a generative piece that uses a custom algorithm to generate this distinct visual “painting.” I admire it firstly because it’s simply beautiful and mesmerizing to look at. Also, the artists’ website says that he strives to create work that strikes a balance between “the cold, hard structures that computers excel at, and the messy, organizing chaos we observe in the natural world around us.” Likewise, this piece in particular is obviously a digital artwork, but also looks strikingly like waves of an ocean or like some organic surface with hills, valleys, shadows, twists and turns– making it neither completely inorganic or organic, neither completely machine nor natural. I wasn’t able to find much information on the exact random algorithms, but with the specification of the piece having 16 iterations, it seems that the algorithm makes this “Blue Literal” image randomly, just with the bounds and specifications of Hobbs’ code, so that every time, it creates this image of these small, short lines of different shades of blue traveling in different but slowly changing directions, with the shades of blue also changing in relation to the lines around it, creating this gradient/wave effect. Again, the specificity of the aesthetic with the combination of a random generation makes it both distinctly computer-generated and simultaneously distinctly Hobbs’ art.
As a part of my quarantine boredom, I have picked up the game Minecraft again in a serious way, and a good deal of my time in Minecraft is simply spent wandering around the game’s randomly generated terrain. Minecraft has over 60 different types of terrain, each including their own terms of generation (i.e.: a snowy tundra will look very different from a fringe jungle biome). The only uniform constraint is the height limit, y=256, and bedrock y=0. I admire the sheer variety of terrains in Minecraft, and how much work goes into creating them. They are all instantly recognizable and yet always unique. Before 15-104, I had never considered the effects of randomness on terrain, but now I can see just how deep it goes. The caves underneath are random, as is the surface land, the nether connected to the overworld, the generated structures, the ores, the trees, the mobs… the list goes on. I think that that’s the beauty of Minecraft: it is an entirely different experience every time, due to the randomness deeply embedded in the game.
Minecraft (released Nov.18, 2011)
https://www.minecraft.net/en-us
Hello! For this weeks looking outward I wrote on John Cage’s Fontana Mix. Fontana Mix is a musical composition Cage composed based on dictation from randomly generated drawings. The sheet music is a combination of traditional sheet music and transparencies with randomly generated points, grids, and lines. Stacking these transparencies allows the player to create an image that can be algorithmically turned into a piece of playable music. This is done by noting the intersections between the lines and the grid, and connecting points in and out of the grid. These intersections are associated with instructions telling the player how to play the piece. The outcome is note only an uneasy and fascinating piece of music, but a beautiful image associated with the music. The viewer will have a hard time relating the image to what they hear, but both share the property of being seemingly random while simultaneously beautiful and reasonable.
For this weeks blog, I chose to analyze Bogdan Soban’s artwork, which is generated through random generative processes. Each art pieces, although follows a similar workflow, look very unique and different compared to each other. His overall art style can be seen as a common theme in all his work but the way he depicts this theme is differed by elements like color palette and level of abstraction. Soban uses complex mathematical formulas to develop these highly abstract and complicated pieces. He also uses a programming language called Visual Basic for most of his abstract work and then uses a random number generator to calculate the seed start time for the generative process. On his website, you can see some of the programs he has used to create these art pieces.
Link to his website – http://www.soban-art.com/index-ang.asp
This map of the US was created by Jasper Johns, and my grandmother has a version of it on her wall. Since I see it whenever I come to visit, I immediately thought of it for this week’s LO assignment. The randomness of the work comes from how the states’ borders are not clearly defined and paint is all over the place. Johns found a way to use 3 different colors together by blending them but also contrasting them. I admire the chaos of this piece, and wonder if there is any underlying message about the US. Although not particularly useful as a map, this is an incredibly cool painting.
Jasper Johns – Map – 1961
https://www.moma.org/collection/works/79372
This work is inspired by “A Million Times”, though it tells time in a very different way. I created an array of small, one-arm clocks to tell seconds, minutes, and hours, based on their columns and rows. This effectively creates a vector field that tells time with its coefficients. While each time in the day looks distinct and often disjointed, the array becomes spontaneously synchronized every now and again and blurs the viewer’s ability to tell the time. I understand if you don’t want to put this on your wrist but I hope you enjoy it on your computer screen for a little bit 🙂
var d = 18;
function setup() {
createCanvas(480, 240);
background(240);
}
function drawClock(x,y,theta) {
push();
translate(x,y);
stroke(220);
strokeWeight(1);
circle(0, 0, 40);
stroke(0);
strokeWeight(2);
line(0, 0, d*cos(radians(theta)), d*sin(radians(theta)));
pop();
}
function draw() {
for (var j = 0; j < 6; j++) {
for (var i = 0; i < 4; i++) {
sMap = map(second(), 0, 59, 0, 360);
drawClock(40*i+20, 40*j+20, sMap+10*i-10*j);
}
for (var i = 0; i < 4; i++) {
push();
translate(160,0);
mMap = map(minute(), 0, 59, 0, 360);
drawClock(40*i+20, 40*j+20, mMap+10*i-10*j);
pop();
}
for (var i = 0; i < 4; i++) {
push();
translate(320,0);
hMap = map(hour(), 0, 59, 0, 360);
drawClock(40*i+20, 40*j+20, hMap+10*i-10*j);
pop();
}
}
}
While looking for examples of random art on google, something that came up was “Scott Pakin’s Random Art Generator.” In this webpage, the user is able to toggle a few settings in order to create a randomly generated image. They have the ability to adjust the canvas size, the complexity, the color model, and whether they equalize color or not. By adjusting these, the computer then generates a unique image of random color, lines, and shapes. The outcome of the graphics mostly stick to being a similar style, as seen below, but they do change with the inputs you give them. I admire that the engineer of this website is able to create an algorithm that can produce these unique images. I think the algorithm they use is similar to the one that we use in class where colors are generated within a specific random set and so are graphics/canvas size.
Name: Scott Pakin’s Random Art Generator
Link: https://www.pakin.org/random-art/
The project I am looking at this week is called “Random Walk with Pi #1” It is created by Cristian Vasile and was uploaded February 26th, 2014.
I really like this artist’s work overall because he uses random functions and manipulates them with these complex algorithms to make these amazing and methodical pieces.
In this piece specifically he utilized random walk (just like the one we learned in class) on pi’s first 10,000 digits which he then converted it to a geographic coordinate on earth’s surface. Clearly, he had to use very sophisticated formulas to take these random walk paths and then proportion them to coordinates on a geographical map.
What I really like about this piece is comparing it with other pieces from the same artist. He also used random walk with “E” and the golden ration. It is very cool to see how the 3 pieces are different, but also very similar in randomness because they all used random walk.
Overall, I think it is a really cool and artistic way to use random walk and complex algorithms. I never thought random walk and math would look so pretty.
Link: https://fineartamerica.com/featured/random-walk-with-pi-1-cristian-vasile.html
Emilio Bustamante
Randomness in architecture
During my career I have never seen randomness in architecture. A group of fourth year students created a project which uses randomness in their design process. By combining controls and randomness they are able to create forms which have a lot of variations but still have a logical composition. The script does something similar to what we are learning in p5js. They created parameters which the random values needed to follow like how far away can an object be from its origin. Multiple random boxes were stacked to create different megastructures and analyze different compositions. This allowed for fast form making and manipulation.
https://www.sciencedirect.com/science/article/abs/pii/S0142694X14000039?via%3Dihub
