Add a lintr configuration file and apply it to the package

.Rbuildignore

@@ -3,3 +3,4 @@
 LICENSE.md
 _pkgdown.yml
 ^\.github$
+.lintr

.lintr

@@ -0,0 +1,7 @@
+linters: linters_with_defaults(
+    line_length_linter(250),
+    commented_code_linter = NULL,
+    trailing_whitespace_linter(allow_empty_lines = TRUE),
+    object_name_linter = NULL
+  )
+encoding: "UTF-8"

R/build_Lifemap.R

@@ -4,7 +4,7 @@
 #' The dataframe can contain any number of additional columns defining traits/characters/values associated to
 #' each taxid.
 #' @param basemap The chosen basemap for Lifemap ("fr", "ncbi", "base" or "virus").
-#' @param verbose If TRUE (the default), the function will print detailed information to the console. 
+#' @param verbose If TRUE (the default), the function will print detailed information to the console.
 #' If FALSE, it will run silently.
 #'
 #' @return A list of class lifemap_obj containing:
@@ -16,7 +16,7 @@
 #'   - A list of its ascendants (ascend)
 #'   - Its type ("requested" or "ancestor")
 #'   - Its direct ancestor
-#'   - Its type (type), i.e. whether the taxid was 
+#'   - Its type (type), i.e. whether the taxid was
 #' requested by the user ("requested") or if it is the anecestor of a requested taxid ("ancestor")
 #' - basemap : the basemap used to get taxa's details
 #'
@@ -34,16 +34,16 @@
 #' LM <- build_Lifemap(eukaryotes_80, "fr")
 #' }
 build_Lifemap <- function(df, basemap = c("ncbi", "base", "fr", "virus"), verbose = TRUE) {
-  
+
   basemap <- match.arg(arg = basemap, choices = basemap)
   if (is.null(df$taxid)) {
     stop('The dataframe must at least contain a "taxid" column')
   }
   # create a new "environment" to store the full data
-  if (!exists("lifemap_basemap_envir", where = .GlobalEnv)) { 
+  if (!exists("lifemap_basemap_envir", where = .GlobalEnv)) {
     lifemap_basemap_envir <- new.env()
   }
-  
+
   ## SET DATASETS ASDRESSES
   # getting the right URL depending on the basemap wanted
   if (basemap == "ncbi") {
@@ -59,7 +59,7 @@ build_Lifemap <- function(df, basemap = c("ncbi", "base", "fr", "virus"), verbos
   else {
     stop(sprintf('%s is not a working basemap, try c("base", "fr", "ncbi" or "virus")', basemap))
   }
-  
+
   y <- tryCatch({
     load(url(basemap_url), envir = lifemap_basemap_envir)
   },
@@ -72,61 +72,61 @@ build_Lifemap <- function(df, basemap = c("ncbi", "base", "fr", "virus"), verbos
     return(NA)
   }
   )
-  
+
   if (!is.na(y)) {
     # download full data for chosen basemap
     if (verbose) {
       cat("Downloading basemap coordinates...\n")
     }
     load(url(basemap_url), envir = lifemap_basemap_envir)
-    
+
     # add LUCA
     LUCA <- data.frame("taxid" = 0, "lon" = 0, "lat" = -4.226497, "sci_name" = "Luca", "zoom" = 5)
     lifemap_basemap_envir$DF <- dplyr::bind_rows(lifemap_basemap_envir$DF, LUCA)
-    
+
     # get info for unique taxids (then we work with df_distinct, not df anymore)
     df_distinct <- dplyr::distinct(df, .data$taxid, .keep_all = TRUE)
     if (nrow(df_distinct) != nrow(df)) {
-        warning(sprintf("%s duplicated TaxIDs were removed \n", nrow(df) - nrow(df_distinct)))
+      warning(sprintf("%s duplicated TaxIDs were removed \n", nrow(df) - nrow(df_distinct)))
     }
-    
+
     # get data
     if (verbose) {
       cat("Getting info for requested taxids...\n")
     }
-    
+
     # get index of requested taxids
     indexes <- fastmatch::fmatch(df_distinct$taxid, lifemap_basemap_envir$DF$taxid)
     if (sum(is.na(indexes)) > 0) {
-        warning(sprintf("%s TaxID(s) could not be found: %s \n",
-                        sum(is.na(indexes)), 
-                        paste(df_distinct$taxid[is.na(indexes)], sep = ",")))
+      warning(sprintf("%s TaxID(s) could not be found: %s \n",
+                      sum(is.na(indexes)),
+                      paste(df_distinct$taxid[is.na(indexes)], sep = ",")))
     }
-    
+
     # create new df with only existing taxids
     df_exists <- df_distinct[!is.na(indexes), ]
     DATA0 <- lifemap_basemap_envir$DF[indexes[!is.na(indexes)], ]
-    
+
     # get ancestors
     unique_ancestors <- unique(unlist(DATA0$ascend))
     real_ancestors <- setdiff(unique_ancestors, df_exists$taxid)
     ANCESTORS <- lifemap_basemap_envir$DF[fastmatch::fmatch(real_ancestors, lifemap_basemap_envir$DF$taxid), ]
-    
+
     # add type
     DATA0$type <- "requested"
     ANCESTORS$type <- "ancestor"
     # bind all
     DATA1 <- rbind(DATA0, ANCESTORS)
-    
-    # merge 
+
+    # merge
     DATA2 <- merge(DATA1, df_exists, by = "taxid", all = TRUE)
-    
+
     # replace the column 'ascend' by simply the direct ancestor
     DATA2$ancestor <- unlist(lapply(DATA2$ascend, function(x) ifelse(!is.null(x), x[1], NA)))
-    
+
     lm_obj <- list(df = DATA2, basemap = basemap)
     class(lm_obj) <- c("lifemap_obj", "list")
-    
+
     return(lm_obj)
   } else {
     return(NA)

R/create_matrix.R

@@ -15,10 +15,10 @@
 #'
 #' create_matrix(LM_eukaryotes$df, c("GC.", "Genes"))
 create_matrix <- function(df, cols) {
-  a <- sapply(1:nrow(df), 
-              function(x,y) {
+  a <- sapply(seq_len(nrow(df)),
+              function(x, y) {
                 cbind(y$taxid[x], c(y$taxid[x], y$ascend[x][[1]]))
-              }, 
+              },
               y = df)
   a <- a[-length(a)]
   B <- do.call(rbind, a)
@@ -30,7 +30,7 @@ create_matrix <- function(df, cols) {
       new_df <- dplyr::full_join(new_df, df[, c("taxid", var)], by = dplyr::join_by("descendant" == "taxid"))
     }
   }
-  return (new_df)
+  return(new_df)
 }
 
 #' Infer numerical values to nodes.
@@ -49,9 +49,10 @@ create_matrix <- function(df, cols) {
 #'
 #' inferred_values <- pass_infos(M = infos, FUN = mean, value = "GC.")
 pass_infos <- function(M, FUN, value) {
-  inferred_values <- tapply(M[[value]], M$ancestor, function(x) {
+  iv <- tapply(M[[value]], M$ancestor, function(x) {
     x <- x[!is.na(x)]
     FUN(x)})
+  return(iv)
 }
 
 
@@ -74,15 +75,15 @@ pass_infos <- function(M, FUN, value) {
 #'
 #' inferred_values <- pass_infos_discret(M = infos, value = "Status")
 pass_infos_discret <- function(M, value) {
-  bind_values <- M |> 
+  bind_values <- M |>
     dplyr::select(.data$ancestor, dplyr::all_of(value)) |>
     stats::na.omit() |>
     dplyr::group_by(.data[[value]], .data$ancestor) |>
-    dplyr::count() |> 
+    dplyr::count() |>
     tidyr::pivot_wider(names_from = dplyr::all_of(value), values_from = .data$n, values_fill = 0) |>
     as.data.frame() |>
-    dplyr::rename("taxid" = "ancestor") |> 
+    dplyr::rename("taxid" = "ancestor") |>
     dplyr::arrange(.data$taxid)
-  
+
   return(bind_values)
 }

R/display_map.R

@@ -19,17 +19,16 @@
 #' display_map()
 display_map <- function(df = NULL, basemap = c("fr", "ncbi", "base", "virus")) {
   basemap <- match.arg(basemap)
-  if (basemap == "fr"){
+  if (basemap == "fr") {
     display <- "http://lifemap-fr.univ-lyon1.fr/osm_tiles/{z}/{x}/{y}.png"
-  } else if (basemap == "ncbi"){
+  } else if (basemap == "ncbi") {
     display <- "http://lifemap-ncbi.univ-lyon1.fr/osm_tiles/{z}/{x}/{y}.png"
-  } else if (basemap == "base"){
+  } else if (basemap == "base") {
     display <- "http://lifemap.univ-lyon1.fr/osm_tiles/{z}/{x}/{y}.png"
-  } else if (basemap == "virus"){
+  } else if (basemap == "virus") {
     display <- "https://virusmap.univ-lyon1.fr/osm_tiles/{z}/{x}/{y}.png"
   }
-  url2check <- strsplit(display, "osm_tiles")[[1]][1]
-
+
   m <- tryCatch({
     leaflet::leaflet(df) |>
       leaflet::addTiles(display, options = leaflet::providerTileOptions(minZoom = 5, maxZoom = 50))
@@ -43,7 +42,7 @@ display_map <- function(df = NULL, basemap = c("fr", "ncbi", "base", "virus")) {
     return(NA)
   }
   )
-  
+
   if (!all(is.na(m))) {
     return(m)
   } else {