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) }