rcontroll 0.1.0.9004: merging and cleaning before CRAN fix

NEWS.md

@@ -1,3 +1,7 @@
+# rcontroll 0.1.0.9004
+
+- merging and cleaning before CRAN fix
+
 # rcontroll 0.1.0.9003
 
 - TROLL version 3.1.8 following discussion with IM, updating treefall time normalisation and carbon starvation to match TROLL4, a clean merge with main and dev will be needed

R/RcppExports.R

@@ -20,20 +20,17 @@
 #'
 #' @examples
 #' \dontrun{
-#' trollCpp(
-#'   global_file = "test/test_input_global.txt",
-#'   climate_file = "test/test_input_climate.txt",
-#'   species_file = "test/test_input_species.txt",
-#'   day_file = "test/test_input_daily.txt",
-#'   lidar_file = "",
-#'   forest_file = "",
-#'   output_file = "test"
-#' )
+#' trollCpp(global_file = "test/test_input_global.txt",
+#'          climate_file = "test/test_input_climate.txt",
+#'          species_file = "test/test_input_species.txt",
+#'          day_file = "test/test_input_daily.txt",
+#'          lidar_file = "",
+#'          forest_file = "",
+#'          output_file = "test")
 #' }
 #'
 #' @export
-trollCpp <- function(global_file, climate_file, species_file, #nolint
-                     day_file, lidar_file, forest_file, output_file) {
-  invisible(.Call(`_rcontroll_trollCpp`, global_file, climate_file,
-                  species_file, day_file, lidar_file, forest_file, output_file))
+trollCpp <- function(global_file, climate_file, species_file, day_file, lidar_file, forest_file, output_file) {
+    invisible(.Call(`_rcontroll_trollCpp`, global_file, climate_file, species_file, day_file, lidar_file, forest_file, output_file))
 }
+

R/autoplot.troll.R

@@ -120,8 +120,7 @@ setMethod("autoplot", "trollsim", function(object, # nolint
     }
     # prep table
     tab <- mutate(tab,
-      iter = as.numeric(iter /
-        object@parameters["iterperyear"])
+      iter = as.numeric(iter / object@parameters["iterperyear"])
     )
     if (!("simulation" %in% names(tab))) {
       tab$simulation <- "sim"

R/generate_climate.R

@@ -293,9 +293,8 @@ generate_climate <- function(x, y, tz,
       gather(variable, value) %>%
       group_by(variable) %>%
       do(decompose(ts(.$value, frequency = 24),
-        type = "additive"
-      )[c("seasonal", "trend", "random")] %>%
-        as.data.frame()) %>%
+                   type = "additive")[c("seasonal", "trend", "random")] %>%
+           as.data.frame()) %>%
       group_by(variable) %>%
       mutate(M = mean(trend, na.rm = TRUE)) %>%
       slice(1:24) %>%
@@ -380,9 +379,8 @@ generate_climate <- function(x, y, tz,
       gather(variable, value) %>%
       group_by(variable) %>%
       do(decompose(ts(.$value, frequency = 12),
-        type = "additive"
-      )[c("seasonal", "trend", "random")] %>%
-        as.data.frame()) %>%
+                   type = "additive")[c("seasonal", "trend", "random")] %>%
+           as.data.frame()) %>%
       mutate(value = (seasonal + mean(trend + random, na.rm = TRUE))) %>%
       slice(1:12) %>%
       select(-seasonal, -trend, -random) %>%

R/update_parameters.trollsim.R

@@ -38,12 +38,15 @@ setMethod("update_parameters", "trollsim", function(sim, ...) {
   V1 <- description <- newvalue <- oldvalue <- param <- value <- NULL # nolint
   sim@inputs$global %>%
     rename(oldvalue = value) %>%
-    left_join(list(...) %>%
-      as.data.frame() %>%
-      t() %>%
-      as.data.frame() %>%
-      rownames_to_column("param") %>%
-      rename(newvalue = V1), by = "param") %>%
+    left_join(
+      list(...) %>%
+        as.data.frame() %>%
+        t() %>%
+        as.data.frame() %>%
+        rownames_to_column("param") %>%
+        rename(newvalue = V1),
+      by = "param"
+    ) %>%
     mutate(value = ifelse(is.na(newvalue), oldvalue, newvalue)) %>%
     select(param, value, description)
 })

cran-comments.md

@@ -1,34 +1,7 @@
 ## Resubmission
 
-This is a resubmission. In this version I have:
-
-* Written software names single quotes
-* Omitted the redundant "Package for" at the start of the title
-* Extended the description of the package in the field description to one paragraph
-* Added \value to pipe.Rd, trollsim.Rd and trollstack.Rd
-* Replaced \dontrun by \donttest in troll.Rd
-
-I have not added a reference for the method because we are waiting for CRAN acceptance 
-before submitting it to Methods in Ecology and Evolution. 
-But I will add a reference as soon as a paper describing the method is accepted.
-
-I have included all the people concerned in the Authors@R field 
-and included everyone as authors. 
-Indeed, J. Chave, I. Maréchaux and F. Fischer developed the C++ code in src,
-and S. Schmitt and G. Salzet developed the R code.
-
-\dontrun is only used for the trollCpp, load_output, load_stack and autogif functions 
-due to the use of external files or additional software.
-But we have used \donttest in the troll and stack functions 
-which are executable in more than 5 seconds.
-
-The functions in the examples and vignettes do not write to the users' folders 
-but only to the temporary directories.
-The last chunk of the climate vignette uses the write_tsv function 
-but is not evaluated and is only an example for a user who would like to save the resulting climate data.
-
-All examples and vignettes used only one core 
-except for the stack function example, and the lidar and workflow vignettes which use no more than two cores.
+This is a resubmission. In this version I have avoided downloading gsl 
+at installation time following Tomas Kalibera pull request.
 
 ## Test environments 
 

inst/figures/lidr_fig.R

@@ -19,6 +19,8 @@ sim <- troll(
 fake <- readLAS("inst/figures/lidar/lidar_0.las")
 plot(fake, bg = "white", axis = TRUE, size = 1, legend = TRUE)
 nouragues <- readLAS("inst/figures/nouragues_clipped.las")
-plot(nouragues, bg = "white", axis = TRUE, size = 2,
-     legend = TRUE, backend = "rgl")
+plot(nouragues,
+  bg = "white", axis = TRUE, size = 2,
+  legend = TRUE, backend = "rgl"
+)
 # currently manual capture

vignettes/climate.Rmd

@@ -84,8 +84,7 @@ you can then convert the coordinates into the desired request format with `gsub`
 
 ```{r, eval=FALSE}
 (coords <- gsub(",", "/", getbb("French Guiana",
-  format_out = "string", limit = 1
-)))
+                                format_out = "string", limit = 1)))
 ```
 
 You need two types of product: (1) monthly averages by hour of day and (2) monthly averages at 00:00.
@@ -231,17 +230,16 @@ geo_lite_sf("Réserve naturelle des nouragues, 97301, Régina") %>%
   leaflet() %>%
   addTiles() %>%
   addPolygons(data = getbb("French Guiana",
-    format_out = "sf_polygon",
-    limit = 1
-  )$multipolygon) %>%
+                           format_out = "sf_polygon",
+                           limit = 1)$multipolygon) %>%
   addCircleMarkers(col = "red")
 ```
 
 You can extract corresponding coordinates using `st_coordinates` from `sf`:
 
 ```{r, eval=FALSE}
 (coords <- geo_lite_sf("Réserve naturelle des nouragues, 97301, Régina") %>%
-  st_coordinates())
+   st_coordinates())
 ```
 
 You will also need the corresponding time zone for time correction as ERA5-land is giving us time in UTC.