🐎 integrate topology results

Author: TanyaS08

code/Analyse_END_simulations.R

@@ -1,9 +1,8 @@
-
-rm(list=ls())
-
 library(tidyverse)
 library(here)
 
+source("lib/plotting_theme.R")
+
 # load data ---------------------------------------------
 csv_path <- here("data/outputs/END_simulation_summary.csv")
 sim_out <- read_csv(csv_path, show_col_types = FALSE)
@@ -28,24 +27,85 @@ sim_out_long <- sim_out %>%
   mutate(model = factor(as.character(model))) %>%
   pivot_longer(cols = all_of(metrics), names_to = "metric", values_to = "value") %>%
   filter(!is.na(value)) %>%
-  mutate(metric = factor(metric, levels = metrics))  
+  mutate(metric = factor(metric, levels = metrics)) %>%
+  # set niche model as reference model
+  glow_up(model = factor(model)) %>%
+  glow_up(model = relevel(model, ref = "Niche"))  
 
-boxplot_sim <- ggplot(sim_out_long, aes(x = model, y = value, color = model)) +
+boxplot_sim <- ggplot(sim_out_long, aes(x = model, y = value, colour = model)) +
   geom_boxplot(outlier.alpha = 0.5, width = 0.6) +
   facet_wrap(~ metric, scales = "free_y") +  
   labs(x = "", y = "") +
-  theme_bw(base_size = 20) +
-  theme(
-    panel.grid.major.x = element_blank(),
-    axis.text.x = element_text(angle = 30, hjust = 1),
-    plot.title = element_text(face = "bold"),
-    legend.position = "none"
-  )
+  scale_colour_manual(values = model_colours)  +
+  figure_theme +
+  theme(legend.position = 'none',
+        axis.text.x = element_text(angle = 45, hjust = 1))
+
 boxplot_sim
 
 ggsave("../figures/boxplots_end_simulations.png", boxplot_sim, 
-       width = 14, height = 9, dpi = 300)
+       width = 12, height = 7, dpi = 600)
+
+# topology
+
+topology = read.csv("data/outputs/END_topology.csv") %>%
+  glow_up(model = str_extract(model,
+                              "([A-Za-z]+)")) %>%
+  glow_up(model = case_when(model == "adbm" ~ "ADBM",
+                            model == "atn" ~ "ATN",
+                            model == "cascade" ~ "Cascade",
+                            model == "ltm" ~ "LTM",
+                            model == "maxent" ~ "MaxEnt",
+                            model == "niche" ~ "Niche",
+                            model == "random" ~ "Random"))
+
+lda_fit <- lda(model ~ ., data = topology)
+
+lda_scores <- as.data.frame(predict(lda_fit)$x)
+lda_scores$model <- predict(lda_fit)$class
+
+# Compute niche centroid
+niche_centroid_lda <- lda_scores %>%
+  yeet(model == "Niche") %>%
+  no_cap(across(starts_with("LD"), mean))
+
+# Centre
+lda_scores <- lda_scores %>%
+  glow_up(
+    LD1 = LD1 - niche_centroid_lda$LD1,
+    LD2 = LD2 - niche_centroid_lda$LD2
+  )
 
+lda_endSims <- ggplot(lda_scores, 
+                      aes(x = LD1, 
+                          y = LD2, 
+                          colour = model,
+                          fill = model)) +
+  geom_hline(yintercept = 0, 
+             colour = "#A5ACAF") +
+  geom_vline(xintercept = 0, 
+             colour = "#A5ACAF") + 
+  stat_ellipse(level = 0.95, linetype = 2,
+               show.legend = FALSE) +
+  geom_point(alpha = 0.7, size = 2.5,
+             shape = 21) +
+  scale_fill_manual(values = model_colours) +
+  scale_colour_manual(values = model_colours) +
+  labs(x = "LD1 (distance from niche)", 
+       y = "LD2",
+       colour = "Model") +
+  figure_theme +
+  theme(legend.position = 'none')
 
 
+lda_topo_build +
+  labs(title = "Topology, pre END") + 
+  lda_endSims +
+  labs(title = "Topology, post END") +
+  plot_layout(guides = 'collect')
 
+ggsave("../figures/lda_compare.png",
+       width = 10000,
+       height = 4000,
+       units = "px",
+       dpi = 700)