Remove empty lines

R/SDMmodel2MaxEnt.R

@@ -9,9 +9,10 @@
 #' @export
 #' @importFrom dismo maxent
 #'
+#' @author Sergio Vignali
+#'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -35,10 +36,7 @@
 #' fc = "l")
 #'
 #' dismo_model <- SDMmodel2MaxEnt(model)
-#' dismo_model
-#' }
-#'
-#' @author Sergio Vignali
+#' dismo_model}
 SDMmodel2MaxEnt <- function(model) {
 
  if (!inherits(model@model, "Maxent"))

R/auc.R

@@ -63,11 +63,9 @@
 #' # Compute the testing AUC
 #' auc(model,
 #' test = test)
-#'
 #' \donttest{
 #' # Same example but using cross validation instead of training and testing
 #' # datasets
-#' # Create the folds
 #' folds <- randomFolds(data,
 #' k = 4,
 #' only_presence = TRUE)
@@ -86,8 +84,7 @@
 #'
 #' # Compute the AUC for the held apart testing dataset
 #' auc(model,
-#' test = test)
-#' }
+#' test = test)}
 auc <- function(model,
  test = NULL) {
 

R/doJk.R

@@ -24,8 +24,7 @@
 #' @author Sergio Vignali
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -94,8 +93,7 @@
 #'
 #' jk$results
 #' jk$models_without
-#' jk$models_withonly
-#' }
+#' jk$models_withonly}
 doJk <- function(model,
  metric,
  variables = NULL,

R/gridSearch.R

@@ -35,8 +35,7 @@
 #' @seealso \link{randomSearch} and \link{optimizeModel}.
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -89,8 +88,7 @@
 #' metric = "aicc",
 #' env = predictors,
 #' save_models = FALSE)
-#' output@results
-#' }
+#' output@results}
 gridSearch <- function(model,
  hypers,
  metric,

R/maxentTh.R

@@ -12,8 +12,7 @@
 #' @seealso \link{maxentVarImp}.
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -36,8 +35,7 @@
 #' data = data,
 #' fc = "l")
 #'
-#' maxentTh(model)
-#' }
+#' maxentTh(model)}
 maxentTh <- function(model) {
 
  if (!inherits(model@model, "Maxent"))

R/maxentVarImp.R

@@ -18,8 +18,7 @@
 #' @seealso \link{maxentTh}.
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -44,8 +43,7 @@
 #' data = data,
 #' fc = "l")
 #'
-#' maxentVarImp(model)
-#' }
+#' maxentVarImp(model)}
 maxentVarImp <- function(model) {
 
  if (.get_model_class(model) != "Maxent")

R/modelReport.R

@@ -28,9 +28,9 @@
 #' @author Sergio Vignali
 #'
 #' @examples
-#' \donttest{
-#' # If you run the following examples with the function example(), you may want
-#' # to set the argument ask like following: example("modelReport", ask = FALSE)
+#' \donttest{# If you run the following examples with the function example(),
+#' # you may want to set the argument ask like following: example("modelReport",
+#' # ask = FALSE)
 #' # Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
@@ -71,9 +71,7 @@
 #' only_presence = TRUE,
 #' jk = TRUE,
 #' env = predictors,
-#' permut = 2)
-#' }
-#' }
+#' permut = 2)}}
 modelReport <- function(model,
  folder,
  test = NULL,

R/optimizeModel.R

@@ -43,8 +43,7 @@
 #' @seealso \link{gridSearch} and \link{randomSearch}.
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -90,9 +89,7 @@
 #' seed = 798)
 #' output@results
 #' output@models
-#' output@models[[1]] # Best model
-#' }
-#' }
+#' output@models[[1]] # Best model}}
 optimizeModel <- function(model,
  hypers,
  metric,

R/plotCor.R

@@ -19,8 +19,7 @@
 #' @author Sergio Vignali
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -50,8 +49,7 @@
 #' plotCor(bg,
 #' method = "spearman",
 #' cor_th = 0.8,
-#' text_size = 4)
-#' }
+#' text_size = 4)}
 plotCor <- function(bg,
  method = "spearman",
  cor_th = NULL,

R/plotJk.R

@@ -17,8 +17,7 @@
 #' @author Sergio Vignali
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -62,8 +61,7 @@
 #' #' # Plot Jackknife test result for testing
 #' plotJk(jk,
 #' type = "test",
-#' ref = auc(model, test = test))
-#' }
+#' ref = auc(model, test = test))}
 plotJk <- function(jk,
  type = c("train", "test"),
  ref = NULL) {

R/plotPA.R

@@ -24,10 +24,9 @@
 #' @seealso \link{plotPred}.
 #'
 #' @examples
-#' \donttest{
-#' map <- terra::rast(matrix(runif(400, 0, 1),
-#' nrow = 20,
-#' ncol = 20))
+#' \donttest{map <- terra::rast(matrix(runif(400, 0, 1),
+#' nrow = 20,
+#' ncol = 20))
 #' plotPA(map,
 #' th = 0.8)
 #'
@@ -36,15 +35,12 @@
 #' th = 0.5,
 #' colors = c("#d8b365", "#018571"))
 #'
-#' # Save the file
 #' \dontrun{
-#' # The following command will save the map in the working directory. Note that
-#' # the filename must include the extension
+#' # Save the file. The following command will save the map in the working
+#' # directory. Note that `filename` must include the extension.
 #' plotPA(map,
 #' th = 0.7,
-#' filename = "my_map.tif")
-#' }
-#' }
+#' filename = "my_map.tif")}}
 plotPA <- function(map,
  th,
  colors = NULL,

R/plotPred.R

@@ -18,19 +18,17 @@
 #' @seealso \link{plotPA}.
 #'
 #' @examples
-#' \donttest{
-#' map <- terra::rast(matrix(runif(400, 0, 1),
-#' nrow = 20,
-#' ncol= 20))
+#' \donttest{map <- terra::rast(matrix(runif(400, 0, 1),
+#' nrow = 20,
+#' ncol= 20))
 #'
 #' plotPred(map,
 #' lt = "Habitat suitability \ncloglog")
 #'
 #' # Custom colors
 #' plotPred(map,
 #' lt = "Habitat suitability",
-#' colorramp = c("#2c7bb6", "#ffffbf", "#d7191c"))
-#' }
+#' colorramp = c("#2c7bb6", "#ffffbf", "#d7191c"))}
 plotPred <- function(map,
  lt = "",
  colorramp = NULL,

R/plotROC.R

@@ -10,6 +10,8 @@
 #' @importFrom rlang .data
 #' @importFrom ggplot2 ggplot aes
 #'
+#' @author Sergio Vignali
+#'
 #' @examples
 #' # Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
@@ -47,8 +49,6 @@
 #' # Plot the training and testing ROC curves
 #' plotROC(model,
 #' test = test)
-#'
-#' @author Sergio Vignali
 plotROC <- function(model,
  test = NULL) {
 

R/predict-SDMmodel.R

@@ -101,8 +101,7 @@ setGeneric("predict", function(object, ...)
 #' predict(model,
 #' data = predictors,
 #' type = "logistic",
-#' filename = "my_map.tif")
-#' }
+#' filename = "my_map.tif")}
 setMethod(
  f = "predict",
  signature = "SDMmodel",

R/predict-SDMmodelCV.R

@@ -59,8 +59,7 @@
 #' values from a lambdas file.
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -97,10 +96,10 @@
 #'
 #' # Make cloglog prediction for the whole study area, get the average, standard
 #' # deviation, and maximum values of the k models, and save the output in three
-#' # files
-#' \dontrun{
+#' # files.
 #' # The following commands save the output in the working directory. Note that
-#' # the filename must include the extension
+#' # the `filename` must include the extension
+#' \dontrun{
 #' maps <- predict(model,
 #' data = predictors,
 #' fun = c("mean", "sd", "max"),
@@ -119,9 +118,7 @@
 #' data = predictors,
 #' fun = "sd",
 #' type = "logistic",
-#' filename = "my_map.tif")
-#' }
-#' }
+#' filename = "my_map.tif")}}
 setMethod(
  f = "predict",
  signature = "SDMmodelCV",

R/randomSearch.R

@@ -32,8 +32,7 @@
 #' @author Sergio Vignali
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -78,8 +77,7 @@
 #' output@models
 #'
 #' # Order results by highest test AUC
-#' output@results[order(-output@results$test_AUC), ]
-#' }
+#' output@results[order(-output@results$test_AUC), ]}
 randomSearch <- function(model,
  hypers,
  metric,

R/reduceVar.R

@@ -34,8 +34,7 @@
 #' @author Sergio Vignali
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -101,9 +100,7 @@
 #' th = 2,
 #' metric = "auc",
 #' test = test,
-#' use_pc = TRUE)
-#' }
-#' }
+#' use_pc = TRUE)}}
 reduceVar <- function(model,
  th,
  metric,

R/swd2csv.R

@@ -20,8 +20,7 @@
 #' @author Sergio Vignali
 #'
 #' @examples
-#' \donttest{
-#' # Acquire environmental variables
+#' \donttest{# Acquire environmental variables
 #' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
 #' pattern = "grd",
 #' full.names = TRUE)
@@ -46,9 +45,7 @@
 #'
 #' # Save the SWD object in two separate csv files
 #' swd2csv(data,
-#' file_name = c("presence.csv", "absence.csv"))
-#' }
-#' }
+#' file_name = c("presence.csv", "absence.csv"))}}
 swd2csv <- function(swd,
  file_name) {