diff --git a/R/ggstats_add_xy.R b/R/ggstats_add_xy.R index ea4f7c0..97934fd 100644 --- a/R/ggstats_add_xy.R +++ b/R/ggstats_add_xy.R @@ -1,11 +1,11 @@ -ggstats_add_xy<-function(table_stat, table, group, xcol=NULL, y="max", bracket.offset=0.05, bracket.inspace=0.05, exclude_group=NULL){ +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} - table[,group]<-as.factor(table[,group]) + 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]]) @@ -14,6 +14,7 @@ ggstats_add_xy<-function(table_stat, table, group, xcol=NULL, y="max", bracket.o } 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)) @@ -30,33 +31,44 @@ ggstats_add_xy<-function(table_stat, table, group, xcol=NULL, y="max", bracket.o 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(group)){table_stat<-mutate(table_stat, {{x}}:=as.factor(.data[[x]]))} - 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) + 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) + }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) }