save logistic_ex

R/logistic_ex.R

@@ -22,7 +22,7 @@ mod <- glm(chlamet ~ value + Turbidity, data = tomod, family = 'binomial')
 # get model prediction grid and predictions
 toprd <- expand_grid(
   value = seq(0, max(tomod$value), length.out = 100),
-  Turbidity = c( quantile(tomod$Turbidity, 0.95), mean(tomod$Turbidity) )
+  Turbidity = c( quantile(tomod$Turbidity, 0.99), mean(tomod$Turbidity) )
 )
 
 prds <- predict(mod, type = 'response', newdata = toprd, se.fit = T)
@@ -37,7 +37,7 @@ toplo <- toprd |>
 # get lines to show connection between hypothetical target and certainty of meeting threshold
 trgs <- expand_grid(
   value  = c(50), 
-  Turbidity = c( quantile(tomod$Turbidity, 0.95), mean(tomod$Turbidity) )
+  Turbidity = c( quantile(tomod$Turbidity, 0.99), mean(tomod$Turbidity) )
 )
 lnprds <- predict(mod, type = 'response', newdata = trgs, se.fit = T)
 tolns <- trgs |> 
@@ -52,21 +52,29 @@ tolns <- trgs |>
 p <- ggplot(toplo, aes(x = value, y = prd, group = Turbidity)) +
   geom_ribbon(aes(ymin = loval, ymax = hival, fill = Turbidity), alpha = 0.2) +
   geom_line(aes(color = Turbidity)) +
-  geom_segment(data = tolns, aes(color = Turbidity, x = value, xend = value, y = 0, yend = prd), linetype = 'dashed', inherit.aes = F) +
+  geom_segment(data = tolns, aes(x = value, xend = value, y = 0, yend = prd), linetype = 'dashed', inherit.aes = F) +
   geom_segment(data = tolns, aes(color = Turbidity, x = 0, xend = value, y = prd, yend = prd), linetype = 'dashed') +  
   # geom_segment(data = tolns, aes(x = 0, xend = value, y = hival, yend = hival), linetype = 'dashed') +
   scale_color_manual(values = c('tomato1', 'dodgerblue')) +
   scale_fill_manual(values = c('tomato1', 'dodgerblue')) +
-  coord_cartesian(xlim = c(0, 200)) +
+  coord_cartesian(xlim = c(0, 200), ylim = c(0, 1)) +
+  scale_y_continuous(expand = c(0, 0)) + 
+  scale_x_continuous(expand = c(0, 0)) +
   theme_minimal() +
-  theme(legend.position = 'top') +
+  theme(
+    legend.position = 'top',
+    panel.background = element_rect(fill = 'transparent', color = NA),
+    plot.background = element_rect(fill = 'transparent', color = NA),
+    legend.background = element_rect(fill = 'transparent', color = NA),
+    legend.box.background = element_rect(fill = 'transparent', color = NA)
+  ) +
   labs(
     x = 'Monthly nitrogen load', 
     fill = 'Climate condition', 
     color = 'Climate condition',
     y = 'Probability of meeting water quality goal'
   )
 
-png(here::here('figs/logisticex.png'), width = 5, height = 4, units = 'in', res = 300)
+png(here::here('figs/logisticex.png'), width = 4.5, height = 4, units = 'in', res = 300, bg = 'transparent')
 print(p)
 dev.off()