Use post_process to zip files after evaluation

NAMESPACE

@@ -112,6 +112,7 @@ export(portal_ndvi_href)
 export(portal_project_href)
 export(portal_weather_href)
 export(portalcast)
+export(post_process)
 export(prefab_datasets)
 export(prefab_datasets_controls)
 export(prefab_models)

R/fill_dir.R

@@ -242,18 +242,12 @@ fill_forecasts <- function (main = ".") {
 
   messageq(paste0(" Located ", length(files), " forecast file(s) in resources to be moved to directory ..."), quiet = settings$quiet)
   messageq("  ... moving ... ", quiet = settings$quiet)
-
-  # zip the forecast files before copying them back
-  zip_unzip("zip", forecast_path = forecasts_path(main = main))
-
   copied <- file.copy(from      = files, 
                       to        = forecasts_path(main = main), 
                       recursive = TRUE)
 
   messageq(paste0("  ... ", sum(copied), " files moved. "), quiet = settings$quiet)
 
-  # zip the forecast zipped files
-  zip_unzip("zip", forecast_path = forecasts_path(main = main))
   invisible( )
 
 }
@@ -319,3 +313,13 @@ fill_models <- function (main               = ".",
 }
 
 
+#' After portalcast and evaluate_forecast run post_process to zip files
+#'
+#' @param main location of main directory with a forecast dir
+#'
+#' @export
+#'
+post_process <- function(main= ".") {
+  settings <- read_directory_settings(main = main)
+  zip_unzip("zip", forecasts_path(main = main))
+}

R/zip_unzip_forecasts.R

@@ -20,68 +20,73 @@ zip_unzip <- function(type = NULL,
     utils::zip(zipfile, files)
     unlink(files)
   }
-
+  
   messageq("Preparing forecasts files")
   proj_path <- forecast_path
   forecasts_metadata <- paste0(proj_path, "/forecasts_metadata.csv")
-
+  
   proj_path <- normalizePath(proj_path, mustWork = FALSE)
-  forecasts_metadata <- normalizePath(forecasts_metadata, mustWork = FALSE)
+  forecasts_metadata <-
+    normalizePath(forecasts_metadata, mustWork = FALSE)
   metadata <- read.csv(forecasts_metadata)
   unique_dates <- sort(unique(metadata$"forecast_date"))
-
+  
   if (type == "zip") {
     csv_file <- "_forecast_table.csv"
     yaml_file <- "_metadata.yaml"
     json_file <- "_model_forecast.json"
-
+    
     if (!is.null(date)) {
       unique_dates <- c(date)
       messageq(paste0("Zipping forecasts files for ", date))
     }
-
+    
     for (forecast_day in unique_dates) {
       id_date_files <- c()
-      zipfile <- paste0(proj_path, "/forecast_id_", forecast_day, ".zip")
-
+      zipfile <-
+        paste0(proj_path, "/forecast_id_", forecast_day, ".zip")
+
       # Get all the values of that particular day in a data frame
-      newdata <- subset(metadata,
+      newdata <- subset(
+        metadata,
         forecast_date == forecast_day,
         select = c("forecast_id", "forecast_date")
       )
-
+      
       # For each forecast_id get 3 files
       All_ids <- newdata$"forecast_id"
       for (id in All_ids) {
         csv_file_path <- paste0(proj_path, "/forecast_id_", id, csv_file)
         if (file.exists(csv_file_path)) {
           id_date_files <- c(id_date_files, csv_file_path)
         }
-        yaml_file_path <- paste0(proj_path, "/forecast_id_", id, yaml_file)
+        yaml_file_path <-
+          paste0(proj_path, "/forecast_id_", id, yaml_file)
         if (file.exists(yaml_file_path)) {
           id_date_files <- c(id_date_files, yaml_file_path)
         }
-        json_file_path <- paste0(proj_path, "/forecast_id_", id, json_file)
+        json_file_path <-
+          paste0(proj_path, "/forecast_id_", id, json_file)
         if (file.exists(json_file_path)) {
           id_date_files <- c(id_date_files, json_file_path)
         }
       }
-
+      
       if (length(id_date_files)) {
         # Zip forecast files for the current date
         zip_files(zipfile, id_date_files)
       }
     }
-
+    
     # Zip forecasts_evaluations.csv
     eval_file <- paste0(proj_path, "/forecasts_evaluations.csv")
     zipfile <- paste0(proj_path, "/forecasts_evaluations.zip")
     zip_files(zipfile, eval_file)
   }
-
+  
   if (type == "unzip") {
     messageq("Unzipping forecasts files")
-
+    
     # Unzip files based on unique_dates
     for (forecast_day in unique_dates) {
       zipfile <- paste0(proj_path, "/forecast_id_", forecast_day, ".zip")
@@ -91,7 +96,7 @@ zip_unzip <- function(type = NULL,
         unlink(zipfile)
       }
     }
-
+    
     # Unzip forecasts_evaluations.csv
     eval_zip <- paste0(proj_path, "/forecasts_evaluations.zip")
     eval_zip <- normalizePath(eval_zip, mustWork = FALSE)