Fix GH actions Rcmdcheck

DESCRIPTION

@@ -19,7 +19,6 @@ Depends:
     R (>= 2.10)
 Imports:
     dplyr,
-    fs,
     ggplot2,
     kwb.hydrus1d,
     kwb.utils,
@@ -38,24 +37,24 @@ Suggests:
     covr,
     DT,
     future.apply,
+    fs,
     knitr,
-    kwb.db,
     kwb.dwd,
+    kwb.pkgbuild,
     kwb.python,
-    plotly,
     openxlsx,
     reticulate,
     rmarkdown,
     soilDB
 VignetteBuilder: 
     knitr
 Remotes:
-    github::kwb-r/kwb.db,
     github::kwb-r/kwb.dwd@get-rid-of-rgdal,
     github::kwb-r/kwb.hydrus1d,
+    github::kwb-r/kwb.pkgbuild,
     github::kwb-r/kwb.python,
     github::kwb-r/kwb.utils
 Encoding: UTF-8
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2

NAMESPACE

@@ -6,6 +6,7 @@ export(aggregate_atmosphere)
 export(aggregate_solute)
 export(aggregate_tlevel)
 export(combine_dataframes)
+export(copy_column)
 export(create_monthly_atm)
 export(get_hydrologic_years)
 export(get_traveltimes)
@@ -66,6 +67,7 @@ importFrom(plotly,ggplotly)
 importFrom(rlang,.data)
 importFrom(scales,percent)
 importFrom(scales,percent_format)
+importFrom(stats,approx)
 importFrom(stats,setNames)
 importFrom(stringr,str_detect)
 importFrom(stringr,str_extract)

R/conservative_tracer-traveltime.R

@@ -6,6 +6,7 @@
 #' @return tibble with interpolated times for percentiles
 #' @export
 #' @importFrom dplyr distinct
+#' @importFrom stats approx
 interpolate_time <- function(
     solute,
     percentiles = c(0.01, 0.05, 0.1, 0.25,0.5, 0.75, 0.9, 0.95, 0.99)
@@ -23,10 +24,10 @@ interpolate_time <- function(
 
   tibble::tibble(
   percentiles = percentiles,
-  time_top = approx(solute_unique_top$sum_cv_top, solute_unique_top$time,
+  time_top = stats::approx(solute_unique_top$sum_cv_top, solute_unique_top$time,
                     xout = sum_cv_top_values,
                     method = "linear", rule = 1)$y,
-  time_bot = approx(solute_unique_bot$sum_cv_bot, solute_unique_bot$time,
+  time_bot = stats::approx(solute_unique_bot$sum_cv_bot, solute_unique_bot$time,
          xout = sum_cv_bot_values,
          method = "linear", rule = 1)$y,
   time_diff = time_bot - time_top
@@ -59,7 +60,7 @@ get_last_day_of_months <- function(ids,
 #' @param solute_files paths to solute files, with good naming convention for
 #' monthly solute exposition (e.g. 0110, solute1: first month, solute10: tenth
 #' month after simulation start)
-#' @param print debug messages (default: TRUE)
+#' @param dbg debug messages (default: TRUE)
 #' @return tibble with time of substance at top/bottom and diff time. Note that
 #' the percentile relate to the substance load
 #' @export

R/prepare_atmosphere.R

@@ -6,7 +6,7 @@
 #' @param number_of_new_columns  number of columns to be copied
 #'
 #' @return df with copied column names
-#' @keywords internal
+#' @export
 #' @examples
 #' # Beispiel-Tibble
 #' tb <- tibble::tibble(

R/recalculate_ctop_with_virtualstorage.R

@@ -6,14 +6,14 @@
 #' @export
 #'
 combine_dataframes <- function(df_list) {
-  # Überprüfen, ob die Liste nicht leer ist
+  # Ueberprüfen, ob die Liste nicht leer ist
   if (length(df_list) == 0) {
     stop("Die Liste der DataFrames ist leer")
   }
 
-  # Überprüfen, ob alle Elemente in der Liste DataFrames sind
+  # Ueberprüfen, ob alle Elemente in der Liste DataFrames sind
   if (!all(sapply(df_list, is.data.frame))) {
-    stop("Alle Elemente in der Liste müssen DataFrames sein")
+    stop("Alle Elemente in der Liste muessen DataFrames sein")
   }
 
   # Kombiniere die DataFrames mit left_join
@@ -65,7 +65,7 @@ vs_list <- lapply(seq_len(length(c_tops)), function(i) {
     dplyr::mutate(dplyr::across(tidyselect::starts_with("cT"), ~ . * Prec, .names = "Prec_{.col}"))
 
 
-  # Funktion zum Identifizieren zusammenhängender Gruppen
+  # Funktion zum Identifizieren zusammenhaengender Gruppen
   data_grouped <- data %>%
     dplyr::arrange(tAtm) %>%
     dplyr::mutate(group = cumsum(store != dplyr::lag(store, default = dplyr::first(store))))