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- ggstats_add_xy_test<-function(table_stat, table, xcol=NULL, group, 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."]]
- if (is.null(xcol)){
- x<-colnames(table_stat)[1]
- }else{x<-xcol}
-
- if(!is.null(group)){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_agg %>% summarise(max=max(.data[[value.var]]))
- if(!is.na(exclude_group)){agg<-table_agg %>% group_by(.data[[exclude_group]]) %>% 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))
- colnames(agg)[1]<-x
- }else if (y == "mean+sd"){
- agg<-table %>% group_by(.data[[x]],.data[[group]]) %>% summarise(mean=mean(.data[[value.var]])+sd(.[[value.var]])) %>% spread(group, mean)
- agg<- data.frame(x=agg[,1], "max"=apply(agg[,2:ncol(agg)], 1, max, na.rm=T))
- colnames(agg)[1]<-x
- }else if (y == "mean+sem"){
- agg<-table %>% group_by(.data[[x]],.data[[group]]) %>% summarise(mean=mean(.data[[value.var]])+sem(.[[value.var]])) %>% spread(group, mean)
- agg<- data.frame(x=agg[,1], "max"=apply(agg[,2:ncol(agg)], 1, max, na.rm=T))
- colnames(agg)[1]<-x
- }
-
- group.list<-list()
- count<-1
- if(!is.null(group)){table_stat<-mutate(table_stat, {{x}}:=as.factor(.data[[x]]))}
-
- for (i in 1:nrow(table_stat)){
- group.list[[count]]<-c(table_stat %>% slice(i) %>% pull(group1),table_stat%>% slice(i) %>% pull(group2))
- count<-count+1
- }
- if(!is.null(group)){
- x.index<-sapply(table_stat %>% pull(x), function(y) which(levels(table_stat %>% pull(x)) == y))
- t<-tibble("y.position"=merge(table_stat, agg ,sort=F)[,"max"]+diff(range(table[value.var], na.rm = T))*bracket.offset,
- "groups"=group.list,
- "x.temp"=x.index,
- "xmin"=(match(table_stat %>% pull(x), levels(table[,x]))+0.75*((match(table_stat$group1, levels(table[,group]))-0.5)/length(levels(table[,group]))-0.5)),
- "xmax"=match(table_stat %>% pull(x), unique(table[,x]))+0.75*((match(table_stat$group2, levels(table[,group]))-0.5)/length(levels(table[,group]))-0.5)
- ) %>% rename("x"="x.temp")
- }else{
- t<-tibble("y.position"=merge(table_stat, agg ,sort=F)[,"max"]+diff(range(table[value.var], na.rm = T))*bracket.offset,
- "groups"=group.list,
- # "x.temp"=x.index,
- )# %>% rename("x"="x.temp")
- }
- if (!is.null(group)){
- 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)
- }
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