Does Proportional Tournament Selection Work?

Shep.Herd Evolutionary Model Analysis

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Visualize Basic Trait Patterns

`summarise()` has grouped output by 'file', 'Wave.Number', 'tournament'. You
can override using the `.groups` argument.

Speed

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Turn Rate

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Change in the Turn.Rate.Trait value over time.

Personal Space

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Change in the Slime.Distance.Trait value over time.

Tower Avoidance

`geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Change in the Tower.Distance.Trait value over time.

Visualize Basic Type Patterns

Main Slime Type

`summarise()` has grouped output by 'Wave.Number', 'Main.Type', 'file',
'tournament'. You can override using the `.groups` argument.

Change in the frequency of Main Type over time.

Secondary Slime Type

`summarise()` has grouped output by 'Wave.Number', 'Secondary.Type', 'file',
'tournament'. You can override using the `.groups` argument.

Change in the frequency of Secondary Type over time.

Fitness Analysis

Raw Fitness

Log Fitness

fitness <- ggplot(fit_ranked%>% filter(Wave.Number < max(Wave.Number)), aes(x = Sheep.Distance.Fitness, y = offspring_count))+ geom_point(aes(color = Speed.Trait))+ geom_smooth(method = “lm”)+ facet_grid(Wave.Number~file)

ggsave(fitness, file = “fitness.png”, height = 12, width =4)

fitnessrank <- ggplot(fit_ranked%>% filter(Wave.Number < max(Wave.Number)), aes(x = fitrank, y = offspring_count))+ geom_point(aes(color = Speed.Trait))+ geom_smooth(method = “lm”)+ facet_grid(Wave.Number~file)

ggsave(fitnessrank, file = “fitnessrank.png”, height = 12, width =4)

speed <- ggplot(fit_ranked%>% filter(Wave.Number < max(Wave.Number)), aes(x = Speed.Trait, y = offspring_count))+ geom_point(aes(color = Main.Type))+ geom_smooth(method = “lm”)+ facet_grid(Wave.Number~file)

ggsave(speed, file = “speed.png”, height = 12, width =4)

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stat_bin() using bins = 30. Pick better value with binwidth.

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stat_bin() using bins = 30. Pick better value with binwidth.

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stat_bin() using bins = 30. Pick better value with binwidth. ```

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