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- library(ggplot2)
- library(gganimate)
-
-
- linscale.initpopulation <- function(n) {
- return(runif(10))
- }
-
- linscale.scale <- function(population, a, b) {
- return(a * population + b)
- }
-
- linscale.relfitness <- function(population) {
- return(population / sum(population))
- }
-
- linscale.tracegens <- function(popul, a, b, n) {
- lenpopul <- length(popul)
-
- df <- data.frame( generation = 0
- ,individual = 1:lenpopul
- ,fitness = popul
- ,relfitness = linscale.relfitness(popul)
- )
-
-
-
- for(i in 1:n) {
- popul <- linscale.scale(popul, a, b)
-
- df <- rbind(df, data.frame( generation = i
- ,individual = 1:lenpopul
- ,fitness = popul
- ,relfitness = linscale.relfitness(popul)))
- }
-
- return(df)
- }
-
- linscale.experiment <- function(avals, bvals, n, popul=c()) {
- df <- data.frame( generation = integer()
- ,individual = integer()
- ,fitness = double()
- ,relfitness = double()
- ,a = double()
- ,b = double())
-
- if(length(popul) == 0) {
- popul <- linscale.initpopulation(10)
- }
-
- for(a in avals) {
- for(b in bvals) {
- dftmp <- linscale.tracegens(popul, a, b, n)
- dftmp["a"] <- a
- dftmp["b"] <- b
-
- df <- rbind(df, dftmp)
- }
- }
-
- return(df)
- }
-
- linscale.plot <- function(df) {
- pdf(file="linscale.pdf", onefile=TRUE)
-
- for(g in unique(df$generation)) {
- p <- ggplot(data=df[df$generation == g, ]) +
- geom_col(aes(x=individual, y=relfitness)) +
- facet_grid(b ~ a, labeller = label_both) +
- labs(title=sprintf("generation: %i", g))
- print(p)
- }
-
- dev.off()
- }
-
- linscale.animate <- function(df) {
- anim <- ggplot(data=df) +
- geom_col(aes(x=individual, y=relfitness)) +
- facet_grid(b ~ a, labeller = label_both) +
- labs(title="generation: {closest_state}") +
- transition_states(generation)
-
- anim_save("linescale.gif", animation=anim)
- }
-
- data.population <- linscale.initpopulation(10)
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