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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%",
echo = FALSE
)
pkgload::load_all()
```
# airGRccia
<!-- badges: start -->
<!-- badges: end -->
airGRccia is an R package providing tools to facilitate Climate Change Impact and
Adaptation (CCIA) studies with the integrated hydrological model airGRiwrm.
The vignettes included in the package contain an example of the modeling of
the middle valley of the Herault River, France.
- Source: https://forgemia.inra.fr/umr-g-eau/airgrccia
- Documentation: https://umr-g-eau.pages.mia.inra.fr/airgrccia
## Installation
### Requirements
A recent version of R (>4.3.1) must be installed.
The use of the RStudio IDE is recommended.
MacOS and Linux users have to first install the GDAL library. Details of such
installation are available in the documentation of the
[sf package](https://r-spatial.github.io/sf/).
### Get source code
First, clone the source with GIT, or copy them as a ZIP file:
- GIT: https://forgemia.inra.fr/umr-g-eau/airgrccia.git
- ZIP: https://forgemia.inra.fr/umr-g-eau/airgrccia/-/archive/main/airgrccia-main.zip
And then, open the file `airgrccia.Rproj` with RStudio.
### Install dependencies
Type the following instruction in the R console
```r
install.packages("remotes") # If not already installed
remotes::install_deps(dep = TRUE)
```
## Get started
For using the functions contained in the package you can:
- Load the functions in the working environment with `pkgload::load_all()`
- Install the package on your computer with `devtools::install()`
The vignettes in this package contain a complete example of an integrated
semi-distributed hydrological model of the middle valley of the River Hérault:
```{r, results='asis'}
articles <- pkgdown:::data_articles()
l<- apply(articles, 1, function(r) {
cat(sprintf("- [%s](%s)\n", r$title, r$href))
}, simplify = FALSE)
```
The vignettes are using data stored on a cloud at the following URL:
`r loadConfig(userFile = NULL)$data$remote`
For each data file used in the vignettes, there is a call to the function
`getDataPath`.
This function automatically download and copy the file in a temporary folder.
If the data seems to be corrupted, one can reset the temporary folder by calling
`cleanDataCache()`.