# Learn label learn label paramters as list ```r learn_theme_label(lines, sep) ``` ## Arguments - `lines`: a vector of character strings from template file. - `sep`: a character specifying the separator. ## Returns a list of label parameters containing - **display**: 1/0 specifying display or hide the text labels above each field column - **size**: a number specifying the size factor for the text labels - **top**: 1/0 specifying the labels position. If 0, label text which does not fit into the shape will be hidden - **below**: 1/0 specifying the labels position. By default, internal labels will be placed above the branches. If 1, labels will be below the branches - **rotation**: a number specifying text label rotation angle - **straight**: 1/0 specifying tree rotation. If set to 1, tree rotation will not influence the individual label rotation - **vertical**: a number specifying the label vertical shift. Shift internal labels vertically by this amount of pixels (positive or negative) - **shift**: a number specifying the label shift. text label shift in pixels (positive or negative) - **external_shift**: 1/0 specifying label external shift that add extra horizontal shift to the external labels. Useful in unrooted display mode to shift text labels further away from the node labels. ## Examples ```r library(dplyr) tree <- system.file("extdata", "tree_of_itol_templates.tree", package = "itol.toolkit") tab_tmp <- data.table::fread(system.file("extdata", "parameter_groups.txt", package = "itol.toolkit")) tab_id_group <- tab_tmp[,c(1,2)] tab_tmp <- tab_tmp[,-c(1,2)] tab_tmp_01 <- convert_01(object = tab_tmp) tab_tmp_01 <- cbind(tab_id_group,tab_tmp_01) order <- c("type","separator","profile","field","common themes", "specific themes","data") tab_tmp_01_long <- tab_tmp_01 %>% tidyr::gather(key = "variable", value = "value", c(-parameter,-group)) template_start_group <- tab_tmp_01_long %>% group_by(group,variable) %>% summarise(sublen = sum(value)) %>% tidyr::spread(key=variable, value=sublen) template_start_group$group <- factor(template_start_group$group, levels = order) template_start_group <- template_start_group %>% arrange(group) start_group <- data.frame(Var1 = template_start_group$group, Freq = apply(template_start_group[,-1], 1, max)) start_group$start <- 0 for (i in 2:nrow(start_group)) { start_group$start[i] <- sum(start_group$Freq[1:(i-1)]) } template_start_group[template_start_group == 0] <- NA template_end_group <- template_start_group[,2:(ncol(template_start_group)-1)] + start_group$start template_end_group <- data.frame(group = order,template_end_group) template_end_group_long <- template_end_group %>% tidyr::gather(key = "variable", value = "value", -group) names(template_end_group_long)[3] <- "end" template_end_group_long$start <- rep(start_group$start, length(unique(template_end_group_long$variable))) template_end_group_long <- template_end_group_long %>% na.omit() template_end_group_long$length <- sum(start_group$Freq) template_end_group_long <- template_end_group_long[,c(2,5,4,3,1)] template_end_group_long$group <- factor(template_end_group_long$group,levels = order) unit <- create_unit(data = template_end_group_long, key = "Quickstart", type = "DATASET_DOMAINS", tree = tree) file <- tempfile() write_unit(unit,file) lines <- line_clean(file=file) sep = learn_separator(file = file) learn_theme_label(lines,sep) ```

learn_theme_label function