Adaptado para incluir Facets.

R/ggstats_add_xy.R

@@ -1,11 +1,19 @@
-ggstats_add_xy<-function(table_stat, table, group, y="max", bracket.offset=0.05, bracket.inspace=0.05){
+ggstats_add_xy<-function(table_stat, table, group, xcol=NULL, y="max", bracket.offset=0.05, bracket.inspace=0.05, exclude_group=NULL){
   ## Adapted version to fit rstatix output
   value.var<-table_stat[[1,".y."]]
-  x<-colnames(table_stat)[1]
+  if (is.null(xcol)){
+    x<-colnames(table_stat)[1]
+  }else{x<-xcol}
+
   table[,group]<-as.factor(table[,group])
   table[,x]<-as.factor(table[,x])
+  if (is.null(exclude_group)){
+    table_agg<-table %>% group_by(.data[[x]])
+  }else{
+    table_agg<-table %>% group_by(.data[[x]], .data[[exclude_group]])
+  }
   if (y == "max"){
-    agg<-table %>% group_by(.data[[x]]) %>% summarise(max=max(.data[[value.var]]))
+    agg<-table_agg %>% summarise(max=max(.data[[value.var]]))
   }else if (y == "mean"){
     agg<-table %>% group_by(.data[[x]],.data[[group]]) %>% summarise(mean=mean(.data[[value.var]])) %>% spread(group, mean)
     agg<- data.frame(x=agg[,1], "max"=apply(agg[,2:ncol(agg)], 1, max, na.rm=T))
@@ -32,10 +40,22 @@ ggstats_add_xy<-function(table_stat, table, group, y="max", bracket.offset=0.05,
             "xmax"=match(table_stat %>% pull(x), unique(table[,x]))+0.75*((match(table_stat$group2, levels(table[,group]))-0.5)/length(levels(table[,group]))-0.5)
   ) %>% rename("x"="x.temp")
 
-  for (dia in unique(pull(table_stat,1))){
-    t[table_stat[,x] == dia,"y.position"]<-seq(t[table_stat[,x] == dia,"y.position"][[1,1]],
-                                               t[table_stat[,x] == dia,"y.position"][[1,1]]+diff(range(table[,value.var], na.rm = T))*bracket.inspace*(nrow(table_stat[table_stat[,x] == dia,])-1),
-                                               by=diff(range(table[,value.var], na.rm = T))*bracket.inspace)
+  if (!is.null(exclude_group)){
+    for (j in unique(pull(table_stat, all_of(exclude_group)))){
+      for (dia in unique(pull(table_stat,all_of(xcol)))){
+        if (stat.test %>% filter(p < 0.05) %>% filter(.data[[x]] == dia & .data[[exclude_group]] == j) %>% nrow() > 0){
+          t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"]<-seq(t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"][[1,1]],
+                                                                                       t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"][[1,1]]+diff(range(table[,value.var], na.rm = T))*bracket.inspace*(nrow(table_stat[table_stat[,x] == dia & table_stat[,exclude_group] == j,])-1),
+                                                                                       by=diff(range(table[,value.var], na.rm = T))*bracket.inspace)
+        }
+      }
+    }
+  }else{
+    for (dia in unique(pull(table_stat,all_of(xcol)))){
+      t[table_stat[,x] == dia,"y.position"]<-seq(t[table_stat[,x] == dia,"y.position"][[1,1]],
+                                                 t[table_stat[,x] == dia,"y.position"][[1,1]]+diff(range(table[,value.var], na.rm = T))*bracket.inspace*(nrow(table_stat[table_stat[,x] == dia,])-1),
+                                                 by=diff(range(table[,value.var], na.rm = T))*bracket.inspace)
+    }
   }
 
   return(cbind(table_stat,t) %>% as_tibble)