Utiling geom_arc_bar for creation of geometric art

Geometry x Colors Experimentation

I’m still obsessing with Pentomino dataset that I have been using.

I love using the ggforce package for creating stunning visualizations. ggforce essentially allows you to extend the ggplot2 capabilities, i.e. ggplot2 on steroid. My go-to functions usually include geom_regon, geom_parallel_sets, and geom_circle. But recently, I realized there’s functions I haven’t fully explored, one of them being geom_arc_bar.

# Load required libraries
library(tidyverse)    # Data wrangling and general utilities
library(ggforce)      # Extra geoms for ggplot2 
library(cowplot)      # Additional plotting helpers
library(patchwork)    # Combine multiple ggplots effortlessly!

# Pentomino Solutions Dataset 
pento_sol <- read_csv("https://raw.githubusercontent.com/chichacha/pentomino/refs/heads/main/pentomino_solution.csv")

### Convert Solution to XY position data frame
pento_sol_df <- pento_sol |>
  mutate(solution_num = row_number()) |>
  mutate(sol_text = str_split(sol_text, " ")) |>
  unnest(sol_text) |>
  group_by(solution_num) |>
  mutate(y = row_number()) |>
  ungroup() |>
  mutate(sol_text = str_split(sol_text, "")) |>
  unnest(sol_text) |>
  group_by(solution_num, y) |>
  mutate(x = row_number()) |>
  ungroup()

pento_min <- pento_sol_df |>
  filter(sol_text != ".") |>  # exclude the "." cells
  select(x, y, sol_text, solution_num, dim) |>
  nest(.by = c(solution_num, dim))

# Just using my retro color palette
retro <-  c("#00A0B0", "#6A4A3C", "#CC333F", "#EB6841", "#EDC951")
retro12 <- colorRampPalette(retro)(12)
piece<-c("F","I","L","N","P","T","U","V","W","X","Y","Z")
names(retro12) <- piece

Quick Demo of Basic Use geom_arc_bar function

Here’s a demo showing the effects of different geom_arc_bar parameters like segment smoothness (n), expansion or contraction (expand), and rounding of corner (radius). I like that I can draw pie or donut chart without leaving cartesian coordinate.

# Sample data
data <- data.frame(
  x = c(0,0,0,0,0,0),
  y = c(0,0,0,0,0,0),
  r0=c(rep(0.5,times=4),0,0),
  r=c(rep(1,times=4),0.5,0.5),
  start = c(0, pi/2, pi, 3*pi/2,0,pi),
  end = c(pi/2, pi, 3*pi/2, 2*pi,pi,2*pi),
  group=c("A","B","C","D","E","F")
)

# Plot using geom_arc_bar
ggplot(data) +
  geom_arc_bar(aes(
    x0 = x, y0 = y, r0 = r0, r = r, 
    start = start, end = end, 
    fill = group
  ), color="#fffff3") +
  geom_arc_bar(aes(
    x0 = x+2, y0 = y, r0 = r0, r = r, 
    start = start, end = end, 
    fill = group
  ), color="#fffff3", n=4) + ## n to control the number of points used to draw a full circle.
  geom_arc_bar(aes(
    x0 = x+4, y0 = y, r0 = r0, r = r, 
    start = start, end = end, 
    fill = group
  ), color="#fffff3", expand=unit(-1,"mm")) + ## expand to control expansion, negative value is used to contract
  geom_arc_bar(aes(
    x0 = x+6, y0 = y, r0 = r0, r = r, 
    start = start, end = end, 
    fill = group
  ), color="#fffff3", radius=unit(3,"mm"), n=36) +
  theme_minimal_grid(font_family="Roboto Condensed") +
  labs(title = "Fun with geom_arc_bar", fill = "Group") +
  coord_fixed() +
  scale_fill_manual(values=c(retro,"#323433")) +
  scale_x_continuous(breaks=c(0,2,4,6)) +
  scale_y_continuous(breaks=c(-1,0,1))

Slightly Abstract Pentomino Solutions

What happens when a classic Pentomino puzzle collides with geometric abstraction? These visuals are still valid solutions to the Pentomino problem, but now they blur the line between puzzles and art. By experimenting with shapes, colors, these solutions have transformed into something entirely new: playful geometric art with a hint of order and chaos 🪄🐰🎩

abstract_plot <- function(i){
  pento_min$data[[i]] |>
    arrange(sol_text) |>
    group_by(sol_text) |>
    mutate(idx=row_number(),
           diff_x=x-lag(x,default=1),
           diff_y=y-lag(y,default=1)) |>
    ungroup() |>
    ggplot() +
    geom_tile(aes(x=x,y=y), fill="#fffff3") +
    geom_arc_bar(aes(x0=x+0.5,y0=y+0.5,r0=0, r=sqrt(1), start=3*pi/2, end=pi, 
                     fill=sol_text), color="transparent",
                 data = . %>% filter(idx==1)) +
    geom_arc_bar(aes(x0=x-0.5,y0=y-0.5,r0=0, r=sqrt(1), start=0, end=pi/2, 
                     fill=sol_text), color="transparent",
                 data = . %>% filter(idx==2)) +
    geom_arc_bar(aes(x0=x+0.5,y0=y-0.5,r0=0, r=sqrt(1), start=0, end=-pi/2, 
                     fill=sol_text), color="transparent",
                 data = . %>% filter(idx==3)) +
    geom_circle(aes(x0=x,y0=y, r=sqrt(0.25),
                    fill=sol_text), 
                data = . %>% filter(idx==5),
                color="transparent") +
    geom_arc_bar(aes(x0=x+0.5,y0=y+0.5,r0=0, r=sqrt(1), start=3*pi/2, end=pi, 
                     fill=sol_text), color="transparent",
                 data = . %>% filter(idx==4)) +
    coord_fixed() +
    scale_fill_manual(values=retro12) +
    #scale_color_manual(values=retro12) +
    theme_nothing()
  
}

pento_min |> filter(dim=="8×8a") |> 
  pull(solution_num) |>
  sample(size=6) |>
  map(abstract_plot) |>
  wrap_plots() 

library(TSP)

abstract_plot2 <- function(i) {
  my_tsp <-pento_min$data[[i]] |>
    mutate(sol_text=as.numeric(fct_reorder(sol_text,x*y,sum))*100) |>
    dist("manhattan") |>
    TSP::as.TSP()
  
  ### available TSP Method without installing extra
  methods <- c("identity", "random", "nearest_insertion",
               "cheapest_insertion", "farthest_insertion", "arbitrary_insertion",
               "nn", "repetitive_nn", "two_opt")
  
  my_tsp_path <- solve_TSP(my_tsp, method=methods[3]) ## nearest insertion 
  
  pento_min$data[[i]][as.integer(my_tsp_path),] |>
    mutate(idx=row_number()) |>
    ggplot() +
    geom_arc_bar(aes(x0=x+0.5,y0=y+0.5,r0=0, r=sqrt(1), start=3*pi/2, end=pi, 
                     fill=sol_text), color="transparent",
                 data = . %>% filter(idx%%8==1)) +
    geom_arc_bar(aes(x0=x-0.5,y0=y-0.5,r0=0, r=sqrt(1), start=0, end=pi/2, 
                     fill=sol_text), color="transparent",
                 data = . %>% filter(idx%%8==2)) +
    geom_arc_bar(aes(x0=x+0.5,y0=y-0.5,r0=0, r=sqrt(1), start=0, end=-pi/2, 
                     fill=sol_text), color="transparent",
                 data = . %>% filter(idx%%8==3)) +
    geom_circle(aes(x0=x,y0=y, r=sqrt(0.25),
                    fill=sol_text), 
                data = . %>% filter(idx%%8==4),
                color="transparent") +
    geom_arc_bar(aes(x0=x+0.5,y0=y+0.5,r0=0, r=sqrt(1), start=3*pi/2, end=pi, 
                     fill=sol_text), color="transparent",
                 data = . %>% filter(idx%%8==5)) +
    geom_regon(aes(x0=x,y0=y,r=sqrt(0.5),sides=4, fill=sol_text,angle=0), 
               color="transparent",
               data = . %>% filter(idx%%8==6)) +
    geom_regon(aes(x0=x,y0=y,r=sqrt(0.5),sides=4, fill=sol_text,angle=0), 
               color="transparent",
               data = . %>% filter(idx%%8==7)) +
    geom_regon(aes(x0=x,y0=y,r=sqrt(0.5),sides=4, fill=sol_text,angle=0), 
               color="transparent",
               data = . %>% filter(idx%%8==0)) +
    # geom_text(aes(x=x,y=y, label=idx), color="#fffff330",
    #           family="Futura") +
    coord_fixed() +
    scale_fill_manual(values=retro12) +
    theme_nothing()
  
}

pento_min |> filter(dim=="8×8d") |> 
  pull(solution_num) |>
  sample(size=6) |>
  map(abstract_plot2) |>
  wrap_plots()