59 lines
3.0 KiB
Org Mode
59 lines
3.0 KiB
Org Mode
#+BEGIN_HTML
|
|
<img width="200px" align="right" position="absolute" style="position: absolute; top: 0; right: 0; border: 0;" src="https://raw.githubusercontent.com/hollorol/RBBGCMuso/master/images/logo.jpg" alt="Fork me on GitHub">
|
|
#+END_HTML
|
|
|
|
* The RBBGCMuso Package
|
|
#+AUTHOR: Roland HOLLÓS, Dóra HIDY, Zoltán BARCZA
|
|
RBBGCMuso is an R package which helps you to use the [[http://agromo.agrar.mta.hu/bbgc/][Biome-BGCMuSo]] biogeochemical model in R environment. It also provides some additional tools for the model such as MuSo optimized Monte-Carlo simulation and global sensitivity analysis. If you want to use the framework, please read the following description.
|
|
|
|
** Installation
|
|
You can install the RBBGCMuso package in several ways depending on the operating system you use. Now, RBBGCMuso is tested only in Linux and Windows, so OS X compatibility cannot be granted yet. In Windows you can use install the package from binary or from source installer. In Linux you can only install from source.
|
|
|
|
*** Installation in Windows
|
|
You can allways install the latest RBBGCMuso by copy the following line into the R console
|
|
#+BEGIN_SRC R :eval no
|
|
source("https://raw.githubusercontent.com/hollorol/RBBGCMuso/master/installWin.R")
|
|
#+END_SRC
|
|
|
|
*** Installation in Linux or from Source
|
|
If you want to install the RBBGCMuso package in Linux, you have several ways.
|
|
1) Clone this repository, and build and run the package (further information here: [[http://kbroman.org/pkg_primer/pages/build.html][package build and install]])
|
|
2) Install devtools package and copy the following line into an R session
|
|
#+BEGIN_SRC R :eval no
|
|
devtools::install_github("hollorol/RBBGCMuso/RBBGCMuso")
|
|
#+END_SRC
|
|
|
|
Please note, that the last point also works in Windows after you installed the [[https://cran.r-project.org/web/packages/devtools/index.html][devtools]] package and [[https://cran.r-project.org/bin/windows/Rtools/][Rtools]].
|
|
|
|
** Quick usage
|
|
*** Preparation
|
|
In order to use the RBBGCMuso framework you have to set up the m environment, as you normally would if you use the modell without the framework. Please read the corresponding documentation at the [[http://agromo.agrar.mta.hu/bbgc/files/Manual_BBGC_MuSo_v5.pdf][Biome-BGCMuSo's actual userguide]]
|
|
*** Running the model
|
|
|
|
You can run the model in spinup, in normal, or in both phase. With calibMuso functcion, you are able to execute the the model in both or in a normal phase.
|
|
|
|
*** Visualization of the model output
|
|
*** Study the effect of ecophysiological parameters using parameterSweep
|
|
*** Monte-Carlo experiments
|
|
*** Sensitivity analysis
|
|
*** Perform Quick experiments
|
|
|
|
** Advanced usage
|
|
*** copyMusoExampleTo
|
|
*** setupMuso
|
|
*** musoData
|
|
*** musoMapping
|
|
*** musoMappingFind
|
|
*** spinupMuso
|
|
*** normalMuso
|
|
*** calibMuso
|
|
*** plotMuso
|
|
*** plotMusoWithData
|
|
*** musoQuckEffect
|
|
*** musoMonte
|
|
*** musoSensi
|
|
** Contact
|
|
** Acknowledgements
|
|
|
|
The research was funded by the Széchenyi 2020 programme, the European Regional Development Fund and the Hungarian Government (GINOP-2.3.2-15-2016-00028).
|