64 lines
3.2 KiB
Org Mode
64 lines
3.2 KiB
Org Mode
#+BEGIN_HTML
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<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">
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#+END_HTML
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* The RBBGCMuso Package
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#+AUTHOR: Roland HOLLÓS, Dóra HIDY, Zoltán BARCZA
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RBBGCMuso is an R package which supports the easy but powerful application of 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 Bione-BGCMuSo optimized Monte-Carlo simulation and global sensitivity analysis. If you would like to use the framework, please read the following description.
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** Installation
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You can install the RBBGCMuso package in several ways depending on the operating system you use. Up to now RBBGCMuso was tested only in Linux and Windows environment, so Mac OS X compatibility cannot be granted yet. In MS Windows you can install the package from binary or from source installer. In Linux you can only install the software from source.
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*** Installation in Windows
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You can always install the latest RBBGCMuso by copying the following line into the R console (using R or R Studio):
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#+BEGIN_SRC R :eval no
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source("https://raw.githubusercontent.com/hollorol/RBBGCMuso/master/installWin.R")
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#+END_SRC
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*** Installation in Linux or from Source in Linux or Windows
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If you would like to install the RBBGCMuso package in Linux environment, you have two options.
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a) Clone this repository, then build and run the package (further information is available here: [[http://kbroman.org/pkg_primer/pages/build.html][package build and install]])
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OR
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b) Install the devtools package firts:
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#+BEGIN_SRC R :eval no
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install.packages("devtools")
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#+END_SRC
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Then copy the following line into the R session and execute it:
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#+BEGIN_SRC R :eval no
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devtools::install_github("hollorol/RBBGCMuso/RBBGCMuso")
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#+END_SRC
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Please note that the last point also works in Windows after you have installed the [[https://cran.r-project.org/bin/windows/Rtools/][Rtools]] Windows software.
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** Quick usage
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*** Preparation
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In order to use the RBBGCMuso framework, you have to set up the environment, as you would normally do if you use the model without the RBBGCMuso framework. Please read the corresponding documentation at the [[http://agromo.agrar.mta.hu/bbgc/files/Manual_BBGC_MuSo_v5.pdf][Biome-BGCMuSo's actual user's guide]]
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*** Running the model
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You can run the model in spinup, in normal, or in both phase (including the so-called transient run). Using the so-called calibMuso functcion you will be able to execute the the model in both spinup or normal phase.
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*** Visualization of the model output
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*** Study the effect of ecophysiological parameters using parameterSweep
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*** Monte-Carlo experiments
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*** Sensitivity analysis
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*** Perform Quick experiments
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** Advanced usage
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*** copyMusoExampleTo
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*** setupMuso
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*** musoData
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*** musoMapping
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*** musoMappingFind
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*** spinupMuso
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*** normalMuso
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*** calibMuso
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*** plotMuso
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*** plotMusoWithData
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*** musoQuckEffect
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*** musoMonte
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*** musoSensi
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** Contact
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** Acknowledgements
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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).
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