S3 plot dispatch for ModvegeSite, removed redundant "store_results" o…

…ption, bugfixes

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: growR
 Type: Package
-Version: 1.0.0.9008
+Version: 1.0.9.9000
 Date: 2023-09-27
 Authors@R: person(
     given = "Kevin",

NAMESPACE

@@ -2,6 +2,7 @@
 
 S3method("*",FunctionalGroup)
 S3method("+",FunctionalGroup)
+S3method(plot,ModvegeSite)
 export(FG_A)
 export(FG_B)
 export(FG_C)

NEWS.md

@@ -13,6 +13,9 @@
   concerns `ModvegeSite$plot()` and `analyze_parameter_scan()` as well as the 
   `compare.R` script.
 
+* S3 dispatch for plot method of `ModvegeSite` objects -> `plot(mvs)` is now 
+  possible if `mvs` is a `ModvegeSite` instance.
+
 ## Changed
 
 * Input data CSV files are now actual CSV files, instead of 
@@ -22,17 +25,23 @@
   `check_parameters` now only throws an error if any of the really  
   *required* parameters are missing.
 
+## Fixed
+
+* autocut: `get_annual_gross_yield` was incorrectly hardcoded to return 1.
+
 ## Removed
 
 * Removed superfluous weather inputs.
 
 * Removed automatic temperature *correction*.
 
+* Redundant argument *store_results* in `growR_run_loop`.
+
 # growR 1.0.0
 
 * Initial CRAN submission.
 
-# grower 0.0.1
+# growR 0.0.1
 
 * Renaming from `rmodvege` to `growR`.
 

R/management.R

@@ -85,7 +85,7 @@ ManagementData = R6Class(
         if (intensity %in% choices) {
           self$intensity = intensity
           logger(sprintf("[autocut]Setting management intensity to `%s`.", 
-                         intensity))
+                         intensity), level = INFO)
         } else {
           self$intensity = "high"
         }

R/modvegesite.R

@@ -467,12 +467,19 @@ ModvegeSite = R6Class(
       #'
       #' Creates a simple base R plot showing the BM with cutting events and,
       #' if applicable, target biomass, dBM, cBM and hvBM.
+      #' Can only be sensibly run *after* a simulation has been carried out, 
+      #' i.e. after this instance's `run()` method has been called.
       #'
       #' @param smooth_interval Int. Number of days over which the variable 
       #'   `dBM` is smoothened.
-      #' @return None Creates a plot of the result.
+      #' @param ... Further arguments are discarded.
+      #' @return NULL Creates a plot of the result in the active device.
       #'
-      plot = function(smooth_interval = 28) {
+      plot = function(smooth_interval = 28, ...) {
+        if (private$current_DOY == 1) {
+          warning("Cannot plot results because simulation has not yet been run.")
+          return()
+        }
         oldpar = par(no.readonly = TRUE)
         on.exit(par(oldpar))
         par(mfrow = c(2, 2))
@@ -490,7 +497,6 @@ ModvegeSite = R6Class(
         plot(self$cBM, type = "l", xlab = xlab, ylab = "cBM (kg / ha)")
         plot(self$hvBM, type = "l", xlab = xlab, ylab = "hvBM (kg / ha)")
       }
-
     )
   ), # End of public attributes
 
@@ -965,3 +971,20 @@ ModvegeSite = R6Class(
 
   ) # End of private attributes
 )
+
+## S3 dispatch methods
+
+#' Plot ModVege simulation result overview
+#'
+#' This wraps the `ModvegeSite` instance's `plot()` method.
+#'
+#' @param x A [ModvegeSite] instance.
+#' @param ... Arguments are passed on to [ModvegeSite]`$plot()`.
+#' @return NULL, but plots to the active device.
+#'
+#' @md
+#' @export
+plot.ModvegeSite = function(x, ...) {
+  x$plot(...)
+}
+

R/parameter_scan.R

@@ -90,10 +90,7 @@ run_parameter_scan = function(environment, param_values, force = FALSE,
            level = INFO
     )
     environment$parameters$set_parameters(parameter_sets[[i]])
-    mvs = growR_run_loop(c(environment), 
-                         output_dir = "",
-                         store_results = TRUE
-    )
+    mvs = growR_run_loop(c(environment), output_dir = "")
     results[[i]] = list(params = parameter_sets[[i]],
                         data = mvs[[1]])
   }

R/run.R

@@ -10,27 +10,21 @@
 #' @param modvege_environments A list of [ModvegeEnvironment] instances.
 #' @param output_dir string; name of directory to which output files are to 
 #'   be written. If `output_dir == ""` (default), no files are written.
-#' @param store_results boolean; If TRUE, return a list of the [ModvegeSite] 
-#'   objects which were run.
 #'
-#' @return If `store_results == TRUE`, a list of the format 
-#'   `[[run]][[year]]` containing clones of the [ModvegeSite] instances that 
-#'   were run. Otherwise an empty list. Defaults to 
-#'   getOption("growR.output_dir").
+#' @return A list of the format `[[run]][[year]]` containing clones of 
+#'   the [ModvegeSite] instances that were run. Also write to files, if 
+#'   *output_dir* is nonempty.
 #'
 #' @examples
 #' env1 = create_example_environment(site = "posieux")
 #' env2 = create_example_environment(site = "sorens")
 #'
-#' growR_run_loop(c(env1, env2), output_dir = "", 
-#' store_results = TRUE)
+#' growR_run_loop(c(env1, env2), output_dir = "")
 #'
 #' @md
 #' @export
 #' 
-growR_run_loop = function(modvege_environments,
-                          output_dir = "",
-                          store_results = FALSE) {
+growR_run_loop = function(modvege_environments, output_dir = "") {
   # Parse output dir
   if (output_dir == "") {
     write_files = FALSE
@@ -62,19 +56,17 @@ growR_run_loop = function(modvege_environments,
       #-Write-output------------------------------------------------------------
 
       if (write_files) {
-        out_file = sprintf("%s%s%s_%s.dat",
-                           output_dir, 
+        out_file = sprintf("%s%s_%s.dat",
                            run_environment$site_name,
                            run_environment$run_name_in_filename,
                            this_year)
+        out_path = file.path(output_dir, out_file)
         logger("Entering `ModvegeSite$write_output`", level = TRACE)
-        modvege$write_output(out_file, force = TRUE)
+        modvege$write_output(out_path, force = TRUE)
       }
 
       #-Store-output------------------------------------------------------------
-      if (store_results) {
-        results[[run]][[i_year]] = modvege$clone(deep = TRUE)
-      }
+      results[[run]][[i_year]] = modvege$clone(deep = TRUE)
     } # End of loop over simulation years
   } # End of loop over runs
   logger("All runs completed.", level = INFO)

R/support_functions.R

@@ -299,11 +299,11 @@ fC.ST = function(x){1} # function(x){1 + .1*(x - 360)/(720 - 360)}
 #' @md
 #' @export
 get_annual_gross_yield = function(elevation, intensity = "high") {
-  #mask = yield_parameters$intensity == intensity
-  #a = yield_parameters[mask, ]$a
-  #b = yield_parameters[mask, ]$b
-  #return(a + b * max(elevation, 500))
-  return(1)
+  mask = yield_parameters$intensity == intensity
+  a = yield_parameters[mask, ]$a
+  b = yield_parameters[mask, ]$b
+  return(a + b * max(elevation, 500))
+#  return(1)
 }
 
 #' Get number of expected cuts

tests/testthat/test-run.R

@@ -7,7 +7,6 @@ test_that("growR_run_loop with example config", {
   for (env in envs) {
     env$years = env$years[[1]]
   }
-  expect_no_error(growR_run_loop(envs, 
-                                 store_results = FALSE))
+  expect_no_error(growR_run_loop(envs))
   unlink(.tmpdir(), recursive = TRUE)
 })

vignettes/growR.Rmd

@@ -138,8 +138,7 @@ information needed in order to run a ModVege simulation.
 We are now ready to do so:
 ```{r run_simulation}
 results = growR_run_loop(environments, 
-                         output_dir = file.path(working_dir, "output"), 
-                         store_results = TRUE)
+                         output_dir = file.path(working_dir, "output"))
 ```
 This will simulate grass growth for every year in every environment present 
 in `environments`. After some console output, we now have the results of 
@@ -230,7 +229,7 @@ new_envs = c(env0, env1, env2)
 
 And we're ready to run and inspect our next run of simulations:
 ```{r ni_screening}
-new_results = growR_run_loop(new_envs, store_results = TRUE)
+new_results = growR_run_loop(new_envs)
 # Plot all results
 for (run in new_results) {
   print(run[[1]]$parameters$NI)