increased variance of a group for t2 and other minor plot changes

inst/fig2.R

@@ -2,10 +2,10 @@
 
 ## figure creation for 'ggrain' manuscript to Journal of Open Source Software
 
-## Use and pre-load to setwd() all documents in : "Workshop8 - Brain development day" 
+## Use and pre-load to setwd() all documents in : "Workshop8 - Brain development day"
 
 if (!require(pacman)) {install.packages("pacman")}
-pacman::p_load(patchwork, tidyverse, ggrain) 
+pacman::p_load(patchwork, tidyverse, ggrain)
 
 #################################################
 # first we will start by simulating some data! :)
@@ -24,34 +24,43 @@ df <- data.frame(score = c(groupa, groupb), group = c(rep("A", length(groupa)),
 
 ## simple figure
 
-p_simple <- ggplot(simdat, aes(x=group,y=score, fill = group, colour = group)) +
+p_simple <- ggplot(df, aes(x=group,y=score, fill = group)) +
   geom_rain(rain.side = "r",
-            boxplot.args = list(color = "black", outlier.color = NA)) + 
+            point.args = list(alpha = .8),
+            boxplot.args = list(color = "black", outlier.color = NA)) +
   scale_color_brewer(palette = "Dark2") + scale_fill_brewer(palette = "Dark2") +
-  theme_minimal(base_size = 26) 
+  labs(x = "") +
+  theme_minimal(base_size = 30)
 
 # making long data
 g_A1 <- rnorm(15, 6.5, 2)
 set.seed(22)
-g_A2 <- rnorm(15, 6.5, 2) + rnorm(15) + 1
+g_A2 <- rnorm(15, 6.5, 2) + rnorm(15, 1, 1) + 3
+
+g_A1 <- abs(g_A1) # zero cesoring
+
+g_B1 <- c(rnorm(14, 2, .8), 8.5)
+g_B1 <- abs(g_B1) # zero cesoring
 
-g_B1 <- c(rnorm(14, 2, 1), 8.1)
 set.seed(24)
-g_B2 <- c(rnorm(14, 2, 1), 8.9) + rnorm(15) + 1
+g_B2 <- c(rnorm(14, 2, 2), 8.9) + rnorm(15,1,1) + 3
 
-df2 <- data.frame(score = c(g_A1, g_A2, g_B1, g_B2), 
+df2 <- data.frame(score = c(g_A1, g_A2, g_B1, g_B2),
                   id = as.character(c(rep(1:15), rep(1:15), rep(16:30), rep(16:30))),
-                  time = c(rep("1", 15), rep("2", 15), rep("1", 15), rep("2", 15)),
+                  time = c(rep("pre", 15), rep("post", 15), rep("pre", 15), rep("post", 15)),
                   group = c(rep("A", 30), rep("B", 30)))
+df2$time <- factor(df2$time, levels = c("pre", "post"))
 
 # making a more complex long data fig
 
 p_complex <- ggplot(df2, aes(x = time, y = score, fill = group, color = group)) +
   geom_rain(id.long.var = "id", rain.side = "f2x2",
             boxplot.args = list(color = "black", outlier.color = NA),
-            violin.args = list(adjust = 1.5, trim = FALSE)) +
+            violin.args = list(adjust = 1.5, trim = FALSE, alpha = .5)) +
   scale_color_brewer(palette = "Dark2") + scale_fill_brewer(palette = "Dark2") +
-  theme_minimal(base_size = 26) 
+  labs(x = "") +
+  theme_minimal(base_size = 30)
+
 
 p_all <- p_simple / p_complex + plot_annotation(tag_levels = "a")