ue05

ue05/ga.R

@@ -0,0 +1,113 @@
+library(ggplot2)
+library(gganimate)
+library(grDevices)
+
+rand.pupulation <- function(n) {
+    return(matrix(runif(2*n), ncol=2)) 
+}
+
+alpha.fixed <- function(alpha) {
+    return(function() alpha)
+}
+
+alpha.runif <- function() {
+    return(function() runif(1))
+}
+
+recom.singlearithm <- function(alpha_gen) {
+
+    return(function(parents) {
+        alpha <- alpha_gen()
+        gene_index <- sample(1:ncol(parents), 1)
+
+        gene_p1 <- parents[1, gene_index]
+        gene_p2 <- parents[2, gene_index]
+
+        children <- parents
+
+        children[1,gene_index] <- alpha * gene_p2 + (1 - alpha) * gene_p1
+        children[2,gene_index] <- alpha * gene_p1 + (1 - alpha) * gene_p2
+
+        return(children)
+    })
+}
+
+recom.wholearithm <- function(alpha_gen) {
+    return(function(parents) {
+        alpha <- alpha_gen()
+
+        children <- parents
+
+        children[1,] <- alpha * children[1,] + (1 - alpha) * children[2,]
+        children[2,] <- alpha * children[2,] + (1 - alpha) * children[1,]
+
+        return(children)
+    })
+}
+
+next.population <- function(population, recom) {
+    next_population <- matrix(, nrow=0, ncol=2)
+
+    parent_pairs <- matrix(sample(1:nrow(population), nrow(population)), ncol=2)
+
+    for(i in 1:nrow(parent_pairs)) {
+        parents <- parent_pairs[i,]
+        next_population <- rbind(next_population, recom(population[parents,]))
+    }
+
+    return(next_population)
+}
+
+experiment <- function(population, gen, recom) {
+    df <- data.frame( x = population[,1]
+                     ,y = population[,2]
+                     ,generation = 0)
+
+    for(g in 1:gen) {
+        population <- next.population(population, recom)
+        
+        df <- rbind(df, data.frame( x = population[,1]
+                                   ,y = population[,2]
+                                   ,generation = g))
+    }
+
+    return(df)
+}
+
+plot.experiment <- function(df, filename) {
+    pdf(file=filename, onefile=TRUE)
+
+    for(g in unique(df$generation)) {
+        tmp_df <- df[df$generation == g,]
+
+        p <- ggplot(data=tmp_df, aes(x=x, y=y)) +
+            geom_point() +
+            labs(title=sprintf("generation: %d", g)) +
+            xlim(0, 1) +
+            ylim(0, 1)
+
+        hull <- chull(tmp_df$x, tmp_df$y)
+
+        p <- p + geom_polygon(data=tmp_df[hull,], alpha=0.25)
+
+        print(p)
+    }
+
+    dev.off()
+}
+
+all.experiments <- function() {
+    population <- rand.pupulation(20)
+    
+    df <- experiment(population, 10, recom.singlearithm(alpha.fixed(0.5)))
+    plot.experiment(df, "single_fixed_alpha.pdf")
+
+    df <- experiment(population, 10, recom.singlearithm(alpha.runif()))
+    plot.experiment(df, "single_rand_alpha.pdf")
+
+    df <- experiment(population, 10, recom.wholearithm(alpha.fixed(0.5)))
+    plot.experiment(df, "whole_fixed_alpha.pdf")
+
+    df <- experiment(population, 10, recom.wholearithm(alpha.runif()))
+    plot.experiment(df, "whole_rand_alpha.pdf")
+}