The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

glow

A package for making glow-y plots

The glow package is a framework for creating plots with glowing points as an alternative way of plotting large point clouds.

Installation

remotes::install_github("traversc/glow")

Some advantages over traditional techniques

Usage

Creating a glow plot is done through the GlowMapper or GlowMapper4 classes, which utilize the R6 class framework.

The class function $map creates a raster that can be plotted with ggplot’s geom_raster or output directly using the EBImage library.

See the help files and inst/examples/notes.txt for more information on each example.

ggplot example using the diamonds dataset

library(glow)
library(ggplot2)
library(viridisLite) # Magma color scale

# Number of threads
nt <- 4

data(diamonds)
gm <- GlowMapper$new(xdim=800, ydim = 640, blend_mode = "screen", nthreads=nt)

# relx(0.002) makes point size relative to x-axis, e.g. each point radius is 0.2% of the y-axis
gm$map(x=diamonds$carat, y=diamonds$price, intensity=1, radius = rely(0.002))
pd <- gm$output_dataframe(saturation = 1)

# Dark color theme
ggplot() + 
  geom_raster(data = pd, aes(x = pd$x, y = pd$y, fill = pd$value), show.legend = FALSE) +
  scale_fill_gradientn(colors = additive_alpha(magma(12))) +
  coord_fixed(gm$aspect(), xlim = gm$xlim(), ylim = gm$ylim()) + 
  labs(x = "carat", y = "price") + 
  theme_night(bgcolor = magma(12)[1])

# light "heat" color theme
light_colors <- light_heat_colors(144)
ggplot() + 
  geom_raster(data = pd, aes(x = pd$x, y = pd$y, fill = pd$value), show.legend = FALSE) +
  scale_fill_gradientn(colors = additive_alpha(light_colors)) +
  coord_fixed(gm$aspect(), xlim = gm$xlim(), ylim = gm$ylim()) + 
  labs(x = "carat", y = "price") + 
  theme_bw(base_size = 14)

# light "cool" color theme
light_colors <- light_cool_colors(144)
ggplot() + 
  geom_raster(data = pd, aes(x = pd$x, y = pd$y, fill = pd$value), show.legend = FALSE) +
  scale_fill_gradientn(colors = additive_alpha(light_colors)) +
  coord_fixed(gm$aspect(), xlim = gm$xlim(), ylim = gm$ylim()) + 
  labs(x = "carat", y = "price") + 
  theme_bw(base_size = 14)

Writing a raster image directly

Instead of using ggplot, you can also output a raster image directly using the EBImage Bioconductor library.

library(EBImage)

# Generate data
cliff_points <- clifford_attractor(1e6, 1.886,-2.357,-0.328, 0.918, 0.1, 0)
color_pal <- circular_palette(n=144, pal_function=rainbow)
cliff_points$color <- map_colors(color_pal, cliff_points$angle, min_limit=-pi, max_limit=pi)

# Create raster
gm <- GlowMapper4$new(xdim=480, ydim = 270, blend_mode = "additive", nthreads=4)
gm$map(x=cliff_points$x, y=cliff_points$y, radius=1e-3, color=cliff_points$color)
pd <- gm$output_raw(saturation = 1)

# Output raster with EBImage
image_array <- array(1, dim=c(480, 270, 3))
image_array[,,1] <- pd[[1]]*pd[[4]]
image_array[,,2] <- pd[[2]]*pd[[4]]
image_array[,,3] <- pd[[3]]*pd[[4]]
img <- EBImage::Image(image_array, colormode='Color')
plot(img)
writeImage(img, "plots/clifford_vignette.png")

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.