Martin-Jung / MadingleyR

The MadingleyR R package streamlines the installation procedure and supports all major operating systems. MadingleyR enables users to combine multiple consecutive simulation runs, making case study specific modifications to MadingleyR objects along the way.

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MadingleyR Installation

The MadingleyR package can be directly installed from R using the devtools or remotes R package. The following command installs the package using the remotes R package:

# Load the remotes package
library('remotes') # or use library('devtools')

# Install the MadingleyR package
install_github('MadingleyR/MadingleyR', subdir='Package', build_vignettes = TRUE)

# Load MadingleyR package 
library('MadingleyR')

# Get version MadingleyR and C++ source code
madingley_version( )

# View the MadingleyR tutorial vignette
vignette('MadingleyR')

In addition to installing the MadingleyR dependencies (rgdal, sp, data.table and raster), the installation process also downloads the precompiled C++ executable (no compilation needed), default spatio-temporal input layers and all other default input parameters and includes them in the installation folder.

Repository content

Package maintainer

Selwyn Hoeks

Updates

  • 01 Jun 2022 - MadingleyR v1.0.5 (C++ source code v2.02): madingley_run() cohort and stock definition input bugs fixed
  • 11 Feb 2022 - MadingleyR v1.0.4 (C++ source code v2.02): plotting functions adapted to allow for functional groups going extinct
  • 19 Jan 2022 - MadingleyR v1.0.3 (C++ source code v2.02): unit fixes for biomass of vegetation in plotting functions, fix to trophic pyramid
  • 23 Nov 2021 - MadingleyR v1.0.2 (C++ source code v2.02): add control over spatial HANPP (see HANPP example)
  • 05 Sept 2021 - MadingleyR v1.0.0 (C++ source code v2.00): windows output folder fix

Troubleshooting

Please note that if the installation via Github fails, the MadingleyR package can be installed locally using the latest static release. Follow this link for the installation guide, select the latest release to make sure all updates are included.

MadingleyR workflow

Fig1
Overview of the MadingleyR workflow.


About

The MadingleyR R package streamlines the installation procedure and supports all major operating systems. MadingleyR enables users to combine multiple consecutive simulation runs, making case study specific modifications to MadingleyR objects along the way.


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