diff --git a/ue04/ev.R b/ue04/ev.R
new file mode 100644
index 0000000..0142163
--- /dev/null
+++ b/ue04/ev.R
@@ -0,0 +1,71 @@
+source("linear_scaling.R")
+library(ggplot2)
+library(RColorBrewer)
+
+fittrans.id <- function(popul) {
+    return(popul)
+}
+
+fittrans.linscale <- function(a, b) {
+    return(function(popul) {
+        popul[,2] = a * popul[,2] + b
+
+        return(popul)
+    })
+}
+
+select.fps <- function(popul) {
+    relfit <- linscale.relfitness(popul[,2])
+    
+    filtr <- sample(popul[,1], length(popul[,1]), prob=relfit, replace=TRUE)
+    return(popul[filtr,])
+}
+
+ev.run <- function(popul, gen, selection, fittrans=fittrans.id) {
+    npopul <- length(popul)
+
+    namedpopul <- matrix(c(1:npopul, popul), ncol=2)
+
+    df = data.frame( gen = 0
+                    ,fitness = namedpopul[,2]
+                    ,ancestor = namedpopul[,1]
+                    ,relfit = linscale.relfitness(namedpopul[,2]))
+
+    for(g in 1:gen) {
+        namedpopul <- selection(fittrans(namedpopul))
+
+        df = rbind(df, data.frame( gen = g
+                                  ,fitness = namedpopul[,2]
+                                  ,ancestor = namedpopul[,1]
+                                  ,relfit = linscale.relfitness(namedpopul[,2])))
+    }
+
+    return(df)
+}
+
+ev.plot <- function(df, filename) {
+    pdf(file=filename, onefile=TRUE)
+    
+
+    for(g in unique(df$gen)) {
+        p <- ggplot(data=df[df$gen == g,], aes(x="", y=relfit, fill=factor(ancestor))) +
+            geom_bar(stat="identity", width=1) +
+            coord_polar("y", start=0) +
+            labs(x=NULL, y=NULL, fill="ancestor", title=sprintf("generation: %i", g))
+
+        print(p)
+    }
+
+    dev.off()
+}
+
+ev.animate <- function(df, filename) {
+
+    anim <- ggplot(data=df, aes(x="", y=relfit, fill=factor(ancestor))) +
+        geom_bar(stat="identity", width=1) +
+        coord_polar("y", start=0) +
+        labs(x=NULL, y=NULL, fill="ancestor", title="generation: {closest_state}") +
+        transition_states(gen)
+
+    anim_save(filename, animation=anim)
+}
diff --git a/ue04/ev.gif b/ue04/ev.gif
new file mode 100644
index 0000000..6052d8f
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diff --git a/ue04/ev.pdf b/ue04/ev.pdf
new file mode 100644
index 0000000..345f549
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diff --git a/ue04/ev_with_trans.gif b/ue04/ev_with_trans.gif
new file mode 100644
index 0000000..df2e6fc
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diff --git a/ue04/ev_with_trans.pdf b/ue04/ev_with_trans.pdf
new file mode 100644
index 0000000..5fb7d13
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diff --git a/ue04/linear_scaling.R b/ue04/linear_scaling.R
index a744b86..2860cdd 100644
--- a/ue04/linear_scaling.R
+++ b/ue04/linear_scaling.R
@@ -1,6 +1,7 @@
 library(ggplot2)
 library(gganimate)
 
+
 linscale.initpopulation <- function(n) {
     return(runif(10))
 }
@@ -36,7 +37,7 @@ linscale.tracegens <- function(popul, a, b, n) {
     return(df)
 }
 
-linscale.experiment <- function(avals, bvals, n) {
+linscale.experiment <- function(avals, bvals, n, popul=c()) {
     df <- data.frame( generation = integer()
                      ,individual = integer()
                      ,fitness = double()
@@ -44,11 +45,13 @@ linscale.experiment <- function(avals, bvals, n) {
                      ,a = double()
                      ,b = double())
 
-    initpopul <- linscale.initpopulation(10)
+    if(length(popul) == 0) {
+        popul <- linscale.initpopulation(10)
+    }
 
     for(a in avals) {
         for(b in bvals) {
-            dftmp <- linscale.tracegens(initpopul, a, b, n)
+            dftmp <- linscale.tracegens(popul, a, b, n)
             dftmp["a"] <- a
             dftmp["b"] <- b
 
@@ -82,3 +85,5 @@ linscale.animate <- function(df) {
 
     anim_save("linescale.gif", animation=anim)
 }
+
+data.population <- linscale.initpopulation(10)
diff --git a/ue04/linescale.gif b/ue04/linescale.gif
index 19d279b..b4ffa1b 100644
Binary files a/ue04/linescale.gif and b/ue04/linescale.gif differ
diff --git a/ue04/linscale.pdf b/ue04/linscale.pdf
index 8ca4be8..f314381 100644
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