Speed up plot() function for large dataset

Question

I am using plot() for over 1 mln data points and it turns out to be very slow.

Is there any way to improve the speed including programming and hardware

Answer 1

This question was asked at a time when the reticulate package to run Python commands from R didn't yet exist.

It's now possible to call the highly efficient matplotlib Python library to plot a large dataset.

matplotlib setup in R is described here.

Plotting 1 Million points with matplotlib takes around 1.5 seconds:

library(reticulate)
library(png)

mpl <- import("matplotlib")
mpl$use("Agg") # Stable non interactive back-end
plt <- import("matplotlib.pyplot")
mpl$rcParams['agg.path.chunksize'] = 0 # Disable error check on too many points

# generate points cloud
a <-rnorm(1E6,1,1)
b <-rnorm(1E6,1,1)

system.time({
  plt$figure()
  plt$plot(a,b,'.',markersize=1)
  # Save figure
  f <- tempfile(fileext='.png')
  plt$savefig(f)
  # Close figure
  plt$close(plt$gcf())
  # Show image
  img <- readPNG(f)
  grid::grid.raster(img)
  # Close temporary file
  unlink(f)
})

#>        User      System       Total 
#>        1.29        0.15        1.49

^{Created on 2020-07-26 by the reprex package (v0.3.0)}