| quincunx {animation} | R Documentation |
This function simulates the quincunx with “balls” (beans) falling through several layers (denoted by triangles) and the distribution of the final locations at which the balls hit is denoted by a histogram.
quincunx(balls = 200, layers = 15, pch.layers = 2, pch.balls = 19, col.balls = sample(colors(),
balls, TRUE), cex.balls = 2)
balls |
number of balls |
layers |
number of layers |
pch.layers |
point character of layers; triangles
( |
pch.balls,col.balls,cex.balls |
point character, colors and magnification of balls |
The bean machine, also known as the quincunx or Galton box, is a device invented by Sir Francis Galton to demonstrate the law of error and the normal distribution.
When a ball falls through a layer, it can either go to the right or left side with the probability 0.5. At last the location of all the balls will show us the bell-shaped distribution.
A named vector: the frequency table for the locations of the balls. Note the names of the vector are the locations: 1.5, 2.5, ..., layers - 0.5.
The maximum number of animation frames is controlled by
ani.options("nmax") as usual, but it is strongly
recommended that ani.options(nmax = balls + layers
-2), in which case all the balls will just fall through
all the layers and there will be no redundant animation
frames.
Yihui Xie <http://yihui.name>
http://vis.supstat.com/2013/04/bean-machine
set.seed(123)
oopt = ani.options(nmax = ifelse(interactive(), 200 + 15 - 2, 2), interval = 0.03)
freq = quincunx(balls = 200, col.balls = rainbow(200))
## frequency table
barplot(freq, space = 0)
## HTML animation page
saveHTML({
ani.options(nmax = ifelse(interactive(), 200 + 15 - 2, 2), interval = 0.03)
quincunx(balls = 200, col.balls = rainbow(200))
}, img.name = "quincunx", htmlfile = "quincunx.html", ani.height = 500, ani.width = 600,
single.opts = "'controls': ['first', 'previous', 'play', 'next', 'last', 'loop', 'speed'], 'delayMin': 0",
title = "Demonstration of the Galton Box", description = c("Balls", "falling through pins will show you the Normal",
"distribution."))
ani.options(oopt)