.Rprofile

+source("renv/activate.R")

Model scripts/plotter.R

-library(rgdal)
 library(sp)
 library(khroma)
 

README.md

@@ -16,15 +16,6 @@ git clone https://git.wur.nl/glowpa/glowpa-model.git
 git checkout mapping-tool
 ```
 
-dependencies for model:
-```R
-install.packages("raster","sf","sp","rgdal","logger","dplyr","tictoc","parallel","khroma")
-```
-additional dependencies for api:
-```R
-install.packages("jsonlite","plumber","rnaturalearth","rnaturalearthdata")
-```
-
 The mapping tool branch comes with the following submodules:
 * pathogenflows R package (https://git.wur.nl/glowpa/pathogenflows.git forked from https://github.com/mverbyla/pathogenflows)
 
@@ -36,7 +27,27 @@ git submodule update
 ```
 The git repository of the submodule is now cloned in the submodule directory. Now open the GloWPa.Rproj file R studio.
 
-Install the folowing R packages from the R console: `devtools::install_local('./libs/pathogenflows')`
+We use `renv` to install the project dependencies. The required packages to run the model will be downloaded and installed from CRAN. The only exception is the pathogenflows package which will be installed from the ./libs/pathogenflows path. Make sure you have followed the previous instructions regarding the git submodules. The renv lockfile does not contain dependencies to run the plumber API. 
+
+```R
+renv::restore()
+```
+Note that the raster package is deprecated since October 2023, but can be installed in R 4.3.3 on Windows systems.
+
+In case you want to install the required packages without using renv. First install the following required packages from CRAN:
+
+```R
+install.packages("raster","sf","sp","logger","dplyr","tictoc","parallel","khroma","jsonlite")
+```
+Finally, install the pathogenflows package from the source code in the `libs/pathogenflows` directory:
+```R
+install.packages("./libs/pathogenflows", repos = NULL, type = "source")
+```
+
+Additional dependencies to run the Plumber API:
+```R
+install.packages("jsonlite","plumber","rnaturalearth","rnaturalearthdata")
+```
 
 ##  Updating code in submodules
 In case anything needs to be changed in the submodule code make sure you make changes in the repository of the submodule. So:
@@ -62,11 +73,12 @@ In case anything needs to be changed in the submodule code make sure you make ch
     1. Commit code.
     2. Push code.
 3. Go to GloWPa git 
-4. Update submodule: `git submodule update`
-5. Update the R library locally. `devtools::install_local("libs/pathogenflows/", force = T)` 
-6. Test if everything works
-7. Now the submodule reference code has been updated and needs to be committed to the GloWPa repository: `git commit -a -m "Updated submodule"`
-8. Push to origin. `git push`
+4. Go to libs/pathogenflows
+5. Run `git pull`.
+6. Update the R library locally. `devtools::install_local("libs/pathogenflows/", force = T)` 
+7. Test if everything works
+8. Now the submodule reference code has been updated and needs to be committed to the GloWPa repository: `git commit -a -m "Updated submodule"`
+9. Push to origin. `git push`
 
 ## Running the model
 Set enviroment variables in local_env.R

pathogenflows @ 9c9cc9da

-Subproject commit bb6bf662eff9bd4fa909412462cebeddbdeea66c
+Subproject commit 9c9cc9da1bfa829e3c138e7f47ca1d9087db5236

local_env.R

 # SET LOCAL SETTINGS
-model_dir <- "/home/nauta/Data/Software/GloWPa/"
-model_input_dir <- "/home/nauta/Data/Projects/2020/K2P/02_Experiment/02_Runs/Run0/Input/kla_online/"
-model_output_dir <- "/home/nauta/Data/Projects/2020/K2P/02_Experiment/02_Runs/Run0/Output/"
+model_dir <- "C:/Users/nauta008/Data/Software/glowpa_fix/glowpa-model"
+model_input_dir <- "C:/Users/nauta008/Data/Data/glowpa/mapping_tool_fix"
+model_output_dir <- "C:/Users/nauta008/Data/Data/glowpa/mapping_tool_fix/output"
 csv_sep <- ";"
 # ----
 

model_run.R

-#' This script can be used to run the model in an R or Rstudio environment using the overall_inputs file to startup the model
-#'
-
-rm(list = ls())
-# SET your local settings in local_env.R
-source("./Model scripts/readers.R")
-source("./Model scripts/GloWPa.R")
-
-scenarios <- read.csv(file.path(model_input_dir,"overall_inputs.csv"),sep = ENV$csv_sep, stringsAsFactors = F)
-browser()
-for(i in 1:dim(scenarios)[1]){
-  scenario <- scenarios[i,]
-  # set loadings_module to 1; human_emissions if not specified
-  if(!"loadings_module" %in% colnames(scenario)){
-    scenario$loadings_module <- 2
-  }
-  if(!"model_input" %in% colnames(scenario)){
-    scenario$model_input <- model_input_dir
-  }
-  if(!"model_output" %in% colnames(scenario)){
-    scenario$model_output <- model_output_dir
-  }
-  human_data_fname <- sprintf("%s.csv",scenario$HumanData_filename)
-  human_data <- read.csv(file.path(model_input_dir,human_data_fname), sep= ENV$csv_sep, stringsAsFactors = F)
-  human_data <- human_data[order(human_data$iso),]
-  popurban_grid <- readers.read.raster(file.path(scenario$model_input,scenario$population_urban_filename))
-  poprural_grid <- readers.read.raster(file.path(scenario$model_input,scenario$population_rural_filename))
-  isoraster <- readers.read.raster(file.path(scenario$model_input,scenario$isoraster_filename))
-  if(!is.na(scenario$WWTPData_filename)){
-    wwtp_inputs <- readers.read.wwtp(file.path(scenario$model_input,scenario$WWTPData_filename))
-  }
-  output <- glowpa.run(scenario,human_data,isoraster,popurban_grid,poprural_grid,wwtp_inputs)
-}
+#' This script can be used to run the model in an R or Rstudio environment using the overall_inputs file to startup the model
+#'
+
+rm(list = ls())
+# SET your local settings in local_env.R
+source("./Model scripts/readers.R")
+source("./Model scripts/GloWPa.R")
+
+scenarios <- read.csv(file.path(model_input_dir,"overall_inputs.csv"),sep = ENV$csv_sep, stringsAsFactors = F)
+browser()
+for(i in 1:dim(scenarios)[1]){
+  scenario <- scenarios[i,]
+  # set loadings_module to 1; human_emissions if not specified
+  if(!"loadings_module" %in% colnames(scenario)){
+    scenario$loadings_module <- 2
+  }
+  if(!"model_input" %in% colnames(scenario)){
+    scenario$model_input <- model_input_dir
+  }
+  if(!"model_output" %in% colnames(scenario)){
+    scenario$model_output <- model_output_dir
+  }
+  human_data_fname <- sprintf("%s.csv",scenario$HumanData_filename)
+  human_data <- read.csv(file.path(model_input_dir,human_data_fname), sep= ENV$csv_sep, stringsAsFactors = F)
+  human_data <- human_data[order(human_data$iso),]
+  popurban_grid <- readers.read.raster(file.path(scenario$model_input,scenario$population_urban_filename))
+  poprural_grid <- readers.read.raster(file.path(scenario$model_input,scenario$population_rural_filename))
+  isoraster <- readers.read.raster(file.path(scenario$model_input,scenario$isoraster_filename))
+  if(!is.na(scenario$WWTPData_filename)){
+    wwtp_inputs <- readers.read.wwtp(file.path(scenario$model_input,scenario$WWTPData_filename))
+  }
+  output <- glowpa.run(scenario,human_data,isoraster,popurban_grid,poprural_grid,wwtp_inputs)
+}

renv.lock

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+}

renv/.gitignore

+library/
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+sandbox/
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renv/settings.json

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