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71 lines
1.9 KiB
71 lines
1.9 KiB
source("linear_scaling.R")
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library(ggplot2)
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library(RColorBrewer)
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fittrans.id <- function(popul) {
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return(popul)
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}
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fittrans.linscale <- function(a, b) {
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return(function(popul) {
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popul[,2] = a * popul[,2] + b
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return(popul)
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})
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}
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select.fps <- function(popul) {
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relfit <- linscale.relfitness(popul[,2])
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filtr <- sample(popul[,1], length(popul[,1]), prob=relfit, replace=TRUE)
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return(popul[filtr,])
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}
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ev.run <- function(popul, gen, selection, fittrans=fittrans.id) {
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npopul <- length(popul)
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namedpopul <- matrix(c(1:npopul, popul), ncol=2)
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df = data.frame( gen = 0
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,fitness = namedpopul[,2]
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,ancestor = namedpopul[,1]
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,relfit = linscale.relfitness(namedpopul[,2]))
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for(g in 1:gen) {
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namedpopul <- selection(fittrans(namedpopul))
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df = rbind(df, data.frame( gen = g
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,fitness = namedpopul[,2]
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,ancestor = namedpopul[,1]
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,relfit = linscale.relfitness(namedpopul[,2])))
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}
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return(df)
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}
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ev.plot <- function(df, filename) {
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pdf(file=filename, onefile=TRUE)
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for(g in unique(df$gen)) {
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p <- ggplot(data=df[df$gen == g,], aes(x="", y=relfit, fill=factor(ancestor))) +
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geom_bar(stat="identity", width=1) +
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coord_polar("y", start=0) +
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labs(x=NULL, y=NULL, fill="ancestor", title=sprintf("generation: %i", g))
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print(p)
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}
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dev.off()
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}
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ev.animate <- function(df, filename) {
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anim <- ggplot(data=df, aes(x="", y=relfit, fill=factor(ancestor))) +
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geom_bar(stat="identity", width=1) +
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coord_polar("y", start=0) +
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labs(x=NULL, y=NULL, fill="ancestor", title="generation: {closest_state}") +
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transition_states(gen)
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anim_save(filename, animation=anim)
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}
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