library(tidyverse)
library(tibble)
library(ggforce)
library(deldir)
library(ggthemes)
library(tictoc)
library(ambient)
library(purrr)
library(tidyr)
library(stringr)
library(sf)Midnight Stargazing
# generating random variables using various distributions
w <- rpois(300, 70)
x <- rgamma(300, 3)
y <- rnorm(300, 50, 200)
z <- rbinom(300, 200, 0.7)
a <- sample(c('a', 'b', 'c'), replace = T, size = 300)
data <- cbind(w, x, y, z, a) # combining into df
# create gradient color pallete
pal <- colorRampPalette(c("lightgoldenrod1","azure3", "slateblue"))
art_colors <- pal(n_distinct(w))
#plot
ggplot(data, aes(x = y, y = z)) +
geom_point(aes(shape = a, color = w), show.legend = F, alpha = 0.9) + #add points
geom_line(aes(group = w, color = w), linetype = 3, show.legend = F, alpha = 0.3)+ # connect points
scale_shape_manual(values = c("a" = 20, "b" = 8, "c" = 21)) + # change shapes of points
scale_color_manual(values = art_colors) + # change colors
coord_radial() + #circle
theme_void() + #remove everything
theme(panel.background = element_rect(fill = "midnightblue", color = "midnightblue")) # background color
Description
Gazing at the midnight stars, your eyes drift between the celestial bodies. The stars seem to be randomly scattered across the sky…..
Code choices
By adding coord_radial(), the art piece now has a circular shape. Setting the background fill and color gives the same midnight blue color as the backdrop of the piece. Adjusting the alpha in the geoms adjusts the opacity of the shapes on the plot. scale_color_manual allows me to choose a palette and scale_shape_manual allows me to choose the shapes the points will be. Lastly, using theme_void removes all titles, axis lines, etc. to give the appearance of art.
Central Coast Spring
# defining palette that I want
my_pal <- c("#4A5d23", "#708238", "#568203","#8A9A5B", "#6B8E23", "#A0522D", "#8B4513", "#7e481c", "goldenrod1")
# function to randomly select row from danielle
choose_rectangle <- function(blocks) {
sample(nrow(blocks), 1, prob = blocks$area)
}
# function to randomly set rectangle breaks from danielle
choose_break <- function(lower, upper) {
round((upper - lower) * runif(1))
}
# function to create tibble of rectangles from danielle
create_rectangles <- function(left, right, bottom, top, value) {
tibble(
left = left,
right = right,
bottom = bottom,
top = top,
width = right - left,
height = top - bottom,
area = width * height,
value = value
)
}
# danielle function to split rectangle horizontally
split_rectangle_x <- function(rectangle, new_value) {
with(rectangle, {
split <- choose_break(left, right)
new_left <- c(left, left + split)
new_right <- c(left + split, right)
new_value <- c(value, new_value)
create_rectangles(new_left, new_right, bottom, top, new_value)
})
}
# danielle function to split rectangle vertically
split_rectangle_y <- function(rectangle, new_value) {
with(rectangle, {
split <- choose_break(bottom, top)
new_bottom <- c(bottom, bottom + split)
new_top <- c(bottom + split, top)
new_value <- c(value, new_value)
create_rectangles(left, right, new_bottom, new_top, new_value)
})
}
# danielle function combining the two split functions
split_rectangle <- function(rectangle, value) {
if(runif(1) < .5) {
return(split_rectangle_x(rectangle, value))
}
split_rectangle_y(rectangle, value)
}
# danielle function to randomly split rectangle
split_block <- function(blocks, value) {
old <- choose_rectangle(blocks)
new <- split_rectangle(blocks[old, ], value)
bind_rows(blocks[-old, ], new)
}
# danielle function to repeatedly divide rectangles
subdivision <- function(ncol = 1000,
nrow = 1000,
nsplits = 50,
seed = NULL) {
if(!is.null(seed)) set.seed(seed)
blocks <- create_rectangles(
left = 1,
right = ncol,
bottom = 1,
top = nrow,
value = 0
)
reduce(1:nsplits, split_block, .init = blocks)
}
# danielle function to fracture/ fill square basicall the start of the mosaic
fill_rectangle <- function(left, right, bottom, top, width,
height, area, value, nshades = 100) {
set.seed(value)
fractals <- list(billow, fbm, ridged)
generators <- list(gen_simplex, gen_perlin, gen_worley)
expand_grid(
x = left:right,
y = bottom:top,
) |>
mutate(
fill = 10 * value + fracture(
x = x * sample(-3:3, 1),
y = y * sample(-3:3, 1),
noise = sample(generators, 1)[[1]],
fractal = sample(fractals, 1)[[1]],
octaves = sample(10, 1),
frequency = sample(10, 1) / 20,
value = "distance2"
) |>
normalise(to = c(1, nshades)) |>
round()
)
}
# danielle function to plot squares
draw_mosaic <- function(dat, palette) {
background <- sample(palette[1:5], 1) #edited
dat |>
ggplot(aes(x, y, fill = fill)) +
geom_tile(show.legend = FALSE, colour = background, size = .2) +
scale_size_identity() +
scale_colour_gradientn(colours = palette) +
scale_fill_gradientn(colours = palette) +
scale_x_continuous(expand = expansion(add = 5)) +
scale_y_continuous(expand = expansion(add = 5)) +
coord_equal() +
theme_void() +
theme(plot.background = element_rect(fill = background))
}
# danielle function bringing it all together - edited palette
mosaica <- function(ncol = 60,
nrow = 60,
nsplits = 30,
seed = NULL) {
subdivision(ncol, nrow, nsplits, seed) |>
pmap_dfr(fill_rectangle) |>
slice_sample(prop = .995) |>
filter(!is.na(fill)) |>
draw_mosaic(palette = my_pal) #added my palette here for more control
}
mosaica(ncol = 200, nrow = 150, nsplits = 3000, seed = 541)
Description
Spring has arrived in the central coast of California. Green grass spreads across the hills dotted with yellow blooms.
Code Choices
I decided to choose my own palette instead of allowing for a random palette as the shapes reminded me of fields. This was also more fun for me. I also edited the background call in the draw_mosaic function to select a green from the palette rather than the browns or yellow. In the function call to mosaica, ncol is set to 200, meaning the art will be 200 “pixels” wide, and nrow is set to 150, meaning the art will be 150 “pixels” tall. The nsplits argument is set to 3000, meaning the art will be divided into 300 “rectangles”, though the nature of the mosaic allows for the shapes to be non-rectangular (or at least not perfectly rectangular). This is a large number of splits and allows for more “detail” in the drawing