Creative Coding

Make generative art with R

R is a programming language used widely for data analysis, but in this workshop, we will explore ways to make art!

Prerequisite

Please note that you are expected to be proficient in R and some knowledge of tidyverse or ggplot2 as we do not have time to cover the basics in this workshop. Participants are expected also to bring their own laptops with R installed.

If you need a refresher for using ggplot2, check out this online chapter here.

We will use the following materials for inspiration:

Sharing your artwork

Please upload your artwork (and optionally your code to generate the artwork) here. Your name (based on your input) will be included in the display.

Alternatively, if you are proficient in Git/GitHub and Quarto, then you are welcomed to do a pull request directly to the repo that hosts this website.

Please note that the link expires at 30th Nov 2023. Beyond this date or there are other matters, please get in touch with Emi Tanaka (emi.tanaka@anu.edu.au) to display your artwork.

aRt

By Elle Saber

Code 
library(tidyverse)
theme_set(theme_void() + theme(legend.position = "none"))
set.seed(1)

n <- 100

segments.dat <- tibble(
  x0 = rnorm(n, 50, 20),
  y0 = rt(n, df = 10),
  x1 = x0 + runif(n, min = 0, max = 10),
  y1 = y0 + runif(n, min = 0, max = 1),
  shade = runif(n), 
  size = runif(n)
)

curly.dat <- tibble(x = seq(1, 120, by=.2),
                    ysin = sin(x))


middle.dat <- tibble(x = runif(100, 1, 100), 
                     y = rnorm(100))

ggplot() + 
  geom_segment(data = middle.dat, aes(x,y, xend=0, yend =0), colour = "deepskyblue3", alpha=.5, size = 5)+
  geom_segment(data = segments.dat, aes(x = x0, y = y0,
                                        xend = x1, yend = y1,
                                        colour = shade, size = size )) + 
  scale_color_viridis_c(option = "magma") + 
  geom_polygon(data = curly.dat, aes(x, ysin), fill = "violetred", alpha=.5) + 
  coord_polar()

By Erin Walsh

Code 
########################## Rtist workshop 30/10/2023 ##########################
## Playing with Truchet tiles exercise
## erin.walsh@anu.edu.au

library(ggplot2)
library(gridExtra)

gconst <- factor(rep(1:2, each = 4))
poss_seqs <- sample(c(0,1), size = 8, replace = TRUE)

rand_tile <- function(seed=1,num=1){set.seed(seed)
  data.frame(x = sample(c(0,1), size = 8, replace = TRUE),
         y = sample(c(0,1), size = 8, replace = TRUE),
         g = factor(rep(1:2, each = 4)),
         title = paste0("tile",num))}


theme_set(theme_void() + theme(legend.position = "none"))

plot_tile <- function(dat){
  ggplot(dat, aes(x, y)) +
    geom_polygon(aes(group = paste(title, g), fill = g), 
                 color = sample(c("#9B5DE5","#F15BB5","#FEE440","#00BBF9","#00F5D4"),1), 
                 linewidth = 1) + 
    coord_equal() + 
    ## sample two colors randomly
    #scale_fill_manual(values = sample(colors(), 2))
    scale_fill_manual(values = sample(c("#9B5DE5","#F15BB5","#FEE440","#00BBF9","#00F5D4"),2))
}



many_rows <- 8
many_cols <- 8

accum <- list()
for(i in 1:(many_rows*many_cols)){accum[[i]] <- plot_tile(rand_tile(i,i))}

do.call(grid.arrange, accum)