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."]]
  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_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))
    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
  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}
  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")

  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)
}