learn_theme_label {itol.toolkit}

Learn label

Description

learn label paramters as list

Usage

learn_theme_label(lines, sep)

Arguments

lines

a vector of character strings from template file.

sep

a character specifying the separator.

Value

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

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)