In ctesta01/ggtriangles: Implements geom_triangles

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 8,
  fig.height = 6
)

`datasets::sleep` Example

This plot shows the data from datasets::sleep.

In particular, it shows off a few features of ggtriangles, such as: - using negative heights with ggtriangles, - using the legend_y_offset argument to geom_triangles - manually specifying the legend key height and width so the triangles fit in the legend

library(ggtriangles)

sleep_effect_max <- max(datasets::sleep$extra)
sleep_effect_min <- min(datasets::sleep$extra)
triangle_height_range <- c(sleep_effect_min, sleep_effect_max)

plt <- ggplot(datasets::sleep,
       aes(
         x = as.numeric(ID),
         y = as.numeric(group),
         triangle_height = extra
       )) +
  geom_triangles(alpha = 0.85, legend_y_offset = 0.5) +
  scale_y_continuous(breaks = c(1, 2)) +
  expand_limits(y = c(0.5, 2.5)) +
  xlab("Individual") +
  ylab("Drug Given") +
  scale_triangle_height(
    breaks = c(sleep_effect_min, 0, sleep_effect_max),
    range = c(.75, .75) * (triangle_height_range)/max(triangle_height_range),
    limits = triangle_height_range
  ) +
  ggtitle("Data show the effects of two soporific drugs administered to a group of 10 people") +
  labs(caption = "Data from datasets::sleep",
       triangle_height = "Observed change\nin sleep hours") +
  theme(
    legend.position = 'bottom',
    legend.key.height = unit(1.75, 'cm'),
    legend.key.width = unit(.75, 'cm')
  )

print(plt)

`iris` Dataset Example

plt <- ggplot(iris,
  aes(
    x = Sepal.Length,
    y = Sepal.Width,
    triangle_height = Petal.Length,
    fill = Petal.Length,
    color = Petal.Length,
    triangle_width = Petal.Width
  )
) +
geom_triangles(alpha = .7) +
scale_fill_viridis_c(option = 'A', end = .8) +
scale_color_viridis_c(option = 'A', end = .8) +
scale_triangle_width(range = c(0.1, 1), n.breaks = 3, breaks = c(1.5, 2, 2.5)) +
scale_triangle_height(range = c(0.1, 1), n.breaks = 3) +
  guides(color = guide_colourbar(order = 1, reverse = TRUE),
         fill = guide_colourbar(order = 1, reverse = TRUE),
        triangle_height = guide_legend(order = 2),
        triangle_width = guide_legend(order = 3)) + 
ggtitle(
  "Sepal length and width and petal length and width of iris flowers",
  "Petal length and width are shown by the height and width of each triangle"
) +
theme_bw() +
theme(legend.position = 'right')

print(plt)


# if you want to combine the triangle aesthetics (like height or width) with the 
# color or fill aesthetics in the legend, you can do that using the override.aes
# argument to the guide_*() functions that are passed to guides().

plt <- ggplot(iris,
  aes(
    x = Sepal.Length,
    y = Sepal.Width,
    triangle_height = Petal.Length,
    fill = Petal.Length,
    color = Petal.Length,
    triangle_width = Petal.Width
  )
) +
geom_triangles(alpha = .7) +
scale_fill_viridis_c(option = 'A', end = .8) +
scale_color_viridis_c(option = 'A', end = .8) +
scale_triangle_width(range = c(0.1, 1), n.breaks = 3, breaks = c(.25, 1.25, 2.5)) +
scale_triangle_height(range = c(0.1, 1), n.breaks = 6) +
  guides(color = 'none',
         fill = 'none',
         triangle_height = guide_legend(
           order = 1,
           nrow = 1,
           override.aes = list(
           color = viridis::viridis(6, end = .8, option = 'A'),
           fill = viridis::viridis(6, end = .8, option = 'A')
           ),
           keywidth = unit(.5, 'cm')
           ),
           triangle_width = guide_legend(order = 2, keywidth = unit(.9, 'cm'))) + 
ggtitle(
  "Sepal length and width and petal length and width of iris flowers",
  "Petal length and width are shown by the height and width of each triangle"
) +
theme_bw() +
theme(legend.position = 'bottom')

print(plt)

`mtcars` Dataset Example

library(dplyr)
library(tibble)
library(ggrepel)

# create our original plot using mtcars 
#
# this shows each car as a triangle where 
#   (x, y, z (height), width, fill) = 
#     (mpg, engine displacement, cylinders, weight, miles per gallon).
# 
# we use a geom_point layer to help make the visualization 
# more intuitively precise as to where on the x and y axes 
# each car is located.
# 
# the geom_text_repel layer helps the reader of the plot learn 
# what the car names are associated with each car based on the
# measures shown
# 
# font size is slightly reduced in the title and subtitle 
# to fit on a roughly 7in x 8.5in (wide) layout.
# 

plt <- mtcars %>%
  tibble::rownames_to_column('name') %>%
  ggplot(aes(x = mpg, y = disp, triangle_height = cyl, triangle_width = wt, color = hp, fill = hp, label = name)) +
  geom_triangles(alpha = .7) +
  geom_point(color = 'black', size = 1) +
  ggrepel::geom_text_repel(color = 'black', size = 2, nudge_y = -10) +
  scale_fill_viridis_c(end = .6) +
  scale_color_viridis_c(end = .6) +
  scale_triangle_height(range = c(0.1, 0.75), breaks = c(2, 4, 8), n.breaks = 3, limits = c(0,8)) +
  scale_triangle_width(range = c(0.3, 1)) + 
  expand_limits(y = range(mtcars$disp) + c(0, 25)) + # expand limits so triangles don't go off page
  xlab("miles per gallon") +
  ylab("engine displacement (cu. in.)") +
  labs(fill = 'horsepower', color = 'horsepower', triangle_height = 'cylinders', triangle_width = 'weight\n(1000 lbs)') +
  ggtitle("MPG, Engine Displacement, # of Cylinders, Weight, and Horsepower of Cars from the 1974 Motor Trends Magazine",
  "Cylinders shown in height, weight in width, horsepower in color") +
  theme_bw() +
  theme(plot.title = element_text(size = 10), plot.subtitle = element_text(size = 8), legend.title = element_text(size = 10))

print(plt)

an archimedian spiral example

a <- 2
b <- .5
theta <- seq(0, 10*pi, length=200)
rr <- a+b*theta
# change to cartesian
xx <- rr*sin(theta)
yy <- rr*cos(theta)

data.frame(x = xx, y = yy) %>%
  mutate(row_number = row_number()) %>% 
  ggplot(aes(x = xx, y = yy, triangle_height = row_number, angle = atan2(yy, xx) * 180 / (pi), fill = row_number, color = row_number)) +
  geom_triangles(alpha = 0.5) +
  scale_fill_viridis_c(direction = -1) + 
  scale_color_viridis_c(direction = -1) + 
  theme_void() + 
  theme(plot.background = element_rect(fill = 'black'), legend.position = 'none')