The animation package has two main purposes:
* 1. It provides functions for animations in statistics (mathematical, multivariate, non-parametric, computational), probability theory, sampling surveys, linear models, time series, and data mining.
* 2. It also provides functions to save animations to various formats including GIFs, HTML pages, PDFs, and videos.
* However, for GIFS and videos you need to download the third party software “ImageMagick” which is not very user friendly….
#install.packages("animation")
library(animation)#ani.options = argument for the animation parameters (nested within)
#interval = a positive number to set the time interval of the animation (unit in seconds); default is 1, which is very slow
#nmax = maximum number of steps in a loop (or iterations) to create animation frames. The actual number of frames can be less than nmax, depending on the animation. The default is 50
#ani.width & ani.height = width and height of the image frames (unit in pixels) typically for png, jpeg; default is 480; units might differ between exporting formats
#ani.pause = it will pause for a time interval (specified in ani.options('interval')) #2-faced coin with equal probability (0.5 or NULL).
#quartz()
flip.coin(faces = 2, prob = NULL, border = "white", grid = "white", col = 1:2,
type = "p", pch = 21, bg = "transparent", digits = 3) #2-faced coin with unequal probability (0.9/0.1).
flip.coin(faces = 2, prob = c(0.9, 0.1), border = "white", grid = "white", col = 1:2,
type = "p", pch = 21, bg = "transparent", digits = 3) #Coin with 3 potential outcomes
oopt = ani.options(interval = 0.3, nmax = ifelse(interactive(), #if else(interactive() meaning assumed human operator
50, 2))
## A simulation where a coin could either be heads, tails or "stand on a table"
flip.coin(faces = c("Head", "Stand", "Tail"), type = "n", prob = c(0.475, 0.05, 0.475), col = c(1, 2, 4))## Save as a HTML animation page (links to your working directory)
saveHTML({
ani.options(interval = 0.3, nmax = ifelse(interactive(), 50,
2))
par(mar = c(2, 3, 2, 1.5), mgp = c(1.5, 0.5, 0))
flip.coin(faces = c("Head", "Stand", "Tail"), type = "n",
prob = c(0.475, 0.05, 0.475), col = c(1, 2, 4))
}, img.name = "flip.coin", htmlfile = "flip.coin.html", ani.height = 500,
ani.width = 600, title = "Probability of flipping coins",
description = c("This animation has provided a simulation of flipping coins", "which might be helpful in understanding the concept of probability."))## HTML file created at: flip.coin.html#ani.options(oopt)# Suppose there are two plant species in a field: A and B.
# One of them will die at each time and a new plant will grow in the place where the old plant died.
# The species of the new plant depends on the proportions of two species: the larger the proportion is, the greater the probability for this species to come up will be
oopt = ani.options(nmax = ifelse(interactive(), 25, 2), interval = 0.3)
par(ann = FALSE, mar = rep(0, 4))
ecol.death.sim(nr = 10, nc = 10, num.sp = c(50, 50), col.sp = c(8, 2), pch.sp = c(20,17), col.die = 1, pch.die = 4, cex = 3)## Save as a HTML animation page (links to your working directory)
saveHTML({
ani.options(interval = 0.3, nmax = ifelse(interactive(), 25,
2))
par(ann = FALSE, mar = rep(0, 4))
ecol.death.sim(nr = 10, nc = 10, num.sp = c(50, 50), col.sp = c(8, 2), pch.sp = c(20,17), col.die = 1, pch.die = 4, cex = 3)
}, img.name = "ecol.death.sim", htmlfile = "ecol.death.sim.html", ani.height = 500,
ani.width = 600, title = "Ecological Death Simulation",
description = c("This animation shows the simulation of the death of two species with certain probabilities."))
#ani.options(oopt)
#Changing the proportion of species/probability of species replacing another: prob = 0.25/0.75
ecol.death.sim = function(
nr = 10, nc = 10, num.sp = c(50, 50), col.sp = c(1, 2), pch.sp = c(1, 2),
col.die = 1, pch.die = 4, cex = 3, ...
) {
x = rep(1:nc, nr)
y = rep(1:nr, each = nc)
p = factor(sample(c(rep(1, 25), rep(2,75))), levels = 1:2)
nmax = ani.options('nmax')
for (i in 1:nmax) {
dev.hold() #this gives a way to hold/flush output on certain on-screen devices
plot(1:nc, 1:nr, type = 'n', xlim = c(0.5, nc + 0.5), ylim = c(0.5, nr + 0.5), ...)
abline(h = 1:nr, v = 1:nc, col = 'lightgray', lty = 3)
points(x, y, col = col.sp[p], pch = pch.sp[p], cex = cex)
ani.pause()
idx = sample(nr * nc, 1)
points(x[idx], y[idx], pch = pch.die, col = col.die, cex = cex, lwd = 3)
tbl = as.vector(table(p))
tbl = tbl + if (as.integer(p[idx]) > 1) c(0, -1) else c(-1, 0)
p[idx] = sample(1:2, 1, prob = tbl)
ani.pause()
}
invisible(p)
}
ecol.death.sim()oopt = ani.options(interval = 1.5)
saveHTML({
for (i in 1:5) {
plot(runif(10), ylim = c(0, 1))
ani.pause()
}
}, htmlfile = "simple.plot.html", img.name = "simple.plot")## HTML file created at: simple.plot.htmlani.options(oopt)
#This could be useful especially if you have different replicates of the same graph!
#What graphs do we have replicates of where it might be useful to look at an animation of all of the plots... The RanWalk function! RanWalk <- function(times=100,
n1=50,
lambda=1.001,
noiseSD=10) {
n <- rep(NA, times)
n[1] <- n1
noise <- rnorm(n=times, mean=0, sd=noiseSD)
for (i in 1:(times-1)) {
n[i + 1] <- lambda*n[i] + noise[i] #would write in a manusript as n(t+1) = lambda(nt) + e
if(n[i + 1] <= 0){
n[i+ 1] <- NA
cat("Population extinction at time",
i-1, "\n")
#tkbell()
break} #end of conditional statement
} #end of for loop
return(n)
} #end of function
head(RanWalk())## [1] 50.00000 30.91826 40.90250 43.67661 39.89196 36.55936saveHTML({
for (i in 1:10) {
plot(RanWalk(), type="o")
ani.pause()
}
}, htmlfile = "RanWalk.html", img.name = "RanWalk.plot", description = "Animation of stochastic random walks (model population growth)")## Population extinction at time 74## Population extinction at time 78## Population extinction at time 10## Population extinction at time 4## Population extinction at time 23## Population extinction at time 19## Population extinction at time 24## Population extinction at time 83## HTML file created at: RanWalk.html#For this example expand your plot window!
#This animation plots the density functions of 150 draws of 100 values from a normally distributed random variable
#Set delay between frames when replaying
ani.options(interval=.05)
# Set up a vector of colors for use below
col.range <- heat.colors(15)
# Begin animation loop
saveHTML({
layout(matrix(c(1, rep(2, 5)), 6, 1))
par(mar=c(3,3,1,1) + 0.1)
for (i in 1:150) { # Begin the loop that creates the 150 individual graphs
chunk <- rnorm(100)+sqrt(abs((i)-51)) # Pull 100 observations from a normal distribution
# and add a constant based on the iteration to move the distribution
par(fg=1) # Reset the color of the top chart every time (so that it doesn’t change as the
# bottom chart changes)
# Set up the top chart that keeps track of the current frame/iteration
plot(-5, xlim = c(1,150), ylim = c(0, .3), axes = F, xlab = "", ylab = "", main = "Iteration")
abline(v=i, lwd=5, col = rgb(0, 0, 255, 255, maxColorValue=255))
abline(v=i-1, lwd=5, col = rgb(0, 0, 255, 50, maxColorValue=255))
abline(v=i-2, lwd=5, col = rgb(0, 0, 255, 25, maxColorValue=255))
# Bring back the X axis
axis(1)
# Set the color of the bottom chart based on the distance of the distribution’s mean from 0
par(fg = col.range[mean(chunk)+3])
# Set up the bottom chart
plot(density(chunk), xlab = "x-value", xlim = c(-5, 15), ylim = c(0, .6))
# Add a line that indicates the mean of the distribution. Add additional lines to track
# previous means
abline(v=mean(chunk), col = rgb(255, 0, 0, 255, maxColorValue=255))
if (exists("lastmean")) {abline(v=lastmean, col = rgb(255, 0, 0, 50, maxColorValue=255)); prevlastmean <- lastmean;}
#Fix last mean calculation
lastmean <- mean(chunk)
}
}, img.name = "density_normal_dist", htmlfile = "normal.dist.html", ani.height = 500,
ani.width = 600, title = "Normal Distribution",
description = c("This animation plots the density functions of 150 draws of 100 values from a normally distributed random variable.") )## HTML file created at: normal.dist.html