DynACof.jl inputs

Templates for DynACof.jl input files.

Introduction

This repository contains the templates for the input parameter files needed for a DynACof.jl simulation, and was made to simplify the user experience. Those inputs come from Vezy et al. 2019.

Please make sure to use these files for the Julia version of DynACof, and not the ones for the R version

Download

Non-coders

If you don't have a GIT client installed, or if you don't even know what GIT is, you can download all the template files at once using this link.

Experienced users

To clone the repository, use this command:

git clone https://github.com/VEZY/DynACof.jl_inputs.git

Details

The values of the parameters in these files can be customized to fit new conditions. To do so, you'll have to download this repository, to open the files and identify the parameters you need to adapt, and to use these new input files for your simulation.

Examples

From Julia

Here is an example call to DynACof.jl using custom parameter files from the Julia REPL:

# Install the package if not already present in your library:
# Pkg.add("DynACof")

# Load the package
using DynACof

# Execute the model using your custom parameter files, located for the example in the folder "DynACof.jl_inputs":
Sim, Meteo, Parameters= dynacof()
dynacof(input_path = "DynACof.jl_inputs", file_name= (constants= "constants.jl",site="site.jl",meteo="meteorology.txt",soil="soil.jl", coffee="coffee.jl",tree="tree.jl"))

From R

The Julia version of DynACof (DynACof.jl) can be used from R using the R-version of DynACof. Here is an example usage from the R console.

All steps are made using R for simplicity in this example.

The first step is to download (or clone) this repository to get the data. For this example, we will download the repository into a temporary directory created from R.
- If you have GIT installed on your computer:

# install.packages("git2r")
dynacof_data= normalizePath(tempdir(), winslash = "/", mustWork = FALSE)
git2r::clone("https://github.com/VEZY/DynACof.jl_inputs.git",dynacof_data)

* or else, downloading the `ZIP` archive:

dynacof_data= normalizePath(tempdir(), winslash = "/", mustWork = FALSE)
data_dir_zip= normalizePath(file.path(dynacof_data,"master.zip"), winslash = "/", mustWork = FALSE)
download.file("https://github.com/VEZY/DynACof.jl_inputs/archive/master.zip", data_dir_zip)
unzip(data_dir_zip, exdir = dynacof_data)
unlink(data_dir_zip)
dynacof_data= normalizePath(list.dirs(dynacof_data)[2])

Then you have to download the DynACof package. To do so, you have to install the remotes package (or devtools):
- For remotes:
```
install.packages("remotes")
remotes::install_github("VEZY/DynACof")
```
- For devtools:
```
install.packages("remotes")
remotes::install_github("VEZY/DynACof")
```
The remotes package is lighter than devtools. But if you already are an R developer you should have devtools installed on your system.
Then, load the DynACof package and instantiate Julia:

library(DynACof)
DynACof::dynacof.jl_setup()

And finally, execute the model using your custom parameter files:

sim= dynacof.jl(Period = as.POSIXct(c("1979-01-01", "1980-12-31")),
                   Inpath = dynacof_data, Simulation_Name = "Test1",
                   FileName = list(Site = "site.jl", Meteo ="meteorology.txt",
                                   Soil = "soil.jl",Coffee = "coffee.jl", Tree = NULL))

And DynACof.jl should run the simulation from R.