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https://github.com/rte-antares-rpackage/antaresViz
ANTARES Visualizations
https://github.com/rte-antares-rpackage/antaresViz
adequacy bilan dygraphs electric energy leaflet linear-programming manipulatewidge monte-carlo-simulation optimization plotly previsionnel r renewable-energy rte shiny shiny-apps simulation stochastic-simulation-algorithm tyndp
Last synced: 3 months ago
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ANTARES Visualizations
- Host: GitHub
- URL: https://github.com/rte-antares-rpackage/antaresViz
- Owner: rte-antares-rpackage
- Created: 2016-11-15T16:47:23.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2024-01-09T23:01:50.000Z (10 months ago)
- Last Synced: 2024-05-22T13:16:57.709Z (6 months ago)
- Topics: adequacy, bilan, dygraphs, electric, energy, leaflet, linear-programming, manipulatewidge, monte-carlo-simulation, optimization, plotly, previsionnel, r, renewable-energy, rte, shiny, shiny-apps, simulation, stochastic-simulation-algorithm, tyndp
- Language: R
- Homepage: https://rte-antares-rpackage.github.io/antaresViz
- Size: 4.61 MB
- Stars: 20
- Watchers: 7
- Forks: 12
- Open Issues: 41
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- open-sustainable-technology - antaresViz - Visualize the results of Antares, an Open Source power system simulator meant to be used by anybody placing value in quantifying the adequacy or the economic performance of interconnected energy systems, at short or remote time horizons. (Energy Systems / Energy System Modeling Frameworks)
README
# antaresViz
> `antaresViz` is the package to visualize the results of your Antares simulations that you have imported in the R session with package `antaresRead`. It provides some functions that generate interactive visualisations. Moreover, by default, these functions launch a shiny widget that provides some controls to dynamically choose what data is displayed in the graphics.
[![R build status](https://github.com/rte-antares-rpackage/antaresViz/workflows/R-CMD-check/badge.svg)](https://github.com/rte-antares-rpackage/antaresViz/actions)
[![Codecov test coverage](https://codecov.io/gh/rte-antares-rpackage/antaresViz/branch/master/graph/badge.svg)](https://app.codecov.io/gh/rte-antares-rpackage/antaresViz?branch=master)
[![CRAN status](https://www.r-pkg.org/badges/version/antaresViz)](https://CRAN.R-project.org/package=antaresViz)
[![R-CMD-check](https://github.com/rte-antares-rpackage/antaresViz/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/rte-antares-rpackage/antaresViz/actions/workflows/R-CMD-check.yaml)## Installation
You can install stable version from CRAN with:
```r
install.packages("antaresViz")
```To install the last development version:
```r
devtools::install_github("rte-antares-rpackage/antaresViz")
```To display the help of the package and see all the functions it provides, use:
```r
help(package="antaresViz")
```## Basic plots
`antaresViz` provides a plot method for tables generated with `antaresRead`. This method is for visualizing a single variable in different formats (times series, barplot, monotone, distribution and cumulative distribution). For instance, the following code displays the distribution of marginal price in different areas.
```
mydata <- readAntares(areas = "all")
plot(mydata, variable = "MRG. PRICE")
```For more information, run:
```r
?plot.antaresDataTable
```## Stacks
Function `prodStack` generates a production stack for a set of areas. Different stacks have been defined. One can see their definition with command `productionStackAliases()`.
With function `exchangesStack`, one can visualize the evolution and origin/destination of imports and exports for a given area.
## Maps
The construction of maps first requires to associate geographic coordinates to the areas of a study. antaresViz provides function `mapLayout` to do interactively this association.
```r
# Get the coordinates of the areas as they have been placed in the antaresSoftware
layout <- readLayout()# Associate geographical coordinates
myMapLayout <- mapLayout(layout)# This mapping should be done once and the result be saved on disk.
save(myMapLayout, file = "myMapLayout.rda")```
Then map can be generated with function `plotMap`:
```r
myData <- readAntares(areas = "all", links = "all")
plotMap(myData, myMapLayout)
```You can use `spMaps` to set a map background or download some files at https://gadm.org/download_country_v3.html.
## Contributing:
Contributions to the library are welcome and can be submitted in the form of pull requests to this repository.
## ANTARES :
Antares is a powerful software developed by RTE to simulate and study electric power systems (more information about Antares here : ).
ANTARES is now an open-source project (since 2018), you can download the sources [here](https://github.com/AntaresSimulatorTeam/Antares_Simulator) if you want to use this package.## License Information:
Copyright 2015-2016 RTE (France)
* RTE: https://www.rte-france.com/
This Source Code is subject to the terms of the GNU General Public License, version 2 or any higher version. If a copy of the GPL-v2 was not distributed with this file, You can obtain one at https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html.