The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

chessboard

• Overview
• Features
• Installation
• Get started
• Long-form documentations
• Citation
• Contributing
• Acknowledgments
• References

Overview

The package chessboard provides functions to work with directed (asymmetric) and undirected (symmetric) spatial (or non-spatial) networks. It implements different methods to detect neighbors, all based on the chess game (it goes beyond the rook and the queen) to create complex connectivity scenarios.

chessboard can handle spatial networks, but it does not explicitly use geographical coordinates to find neighbors (it is not based on spatial distance). Instead, it identifies neighbors according to node labels (i.e. the node position on a two-dimension chessboard) and a specific method (pawn, fool, rook, bishop, knight, queen, wizard, etc.).

It implements the following rules to detect neighbors and create edges:

the degree of neighborhood: the number of adjacent nodes that will be used to create direct edges.
the orientation of neighborhood: can neighbors be detected horizontally, vertically and/or diagonally?
the direction of neighborhood: does the sampling has a main direction? This can be particularly relevant for directed networks (e.g. rivers).

Features

The main purpose of chessboard is to create various network objects, including:

node list
edge list
connectivity matrix

chessboard also provides different plotting functions (all based on the ggplot2 package):

gg_matrix() plots a (connectivity) matrix
gg_chessboard() plots the sampling as a chessboard

Read the Visualization tools vignette for further details.

Finally, the package can also produce objects that will be used later in Moran’s Eigenvector Maps (MEM, Dray et al. 2006) and Asymetric Eigenvector Maps (AEM, Blanchet et al. 2008), methods available in the package adespatial (Dray et al. 2023):

edges weights matrix
spatial weights matrix
nodes by edges matrix
edges weights vector

Installation

The package is not yet published on the CRAN but you can install the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("frbcesab/chessboard")

Then you can attach the package chessboard:

library("chessboard")

Get started

For an overview of the main features of chessboard, please read the Get started vignette.

Long-form documentations

chessboard provides three vignettes to learn more about the package:

the Get started vignette describes the core features of the package
the Chess pieces vignette details the different methods implemented in chessboard to detect neighbors
the Visualization tools vignette describes the plotting functions available in chessboard

Citation

Please cite chessboard as:

Casajus N, Rievrs Borges E, Tabacchi E, Fried G & Mouquet N (2023) chessboard: An R package for creating network connections based on chess moves. Journal of Open Source Software, 8, 5753. https://doi.org/10.21105/joss.05753.

Contributing

All types of contributions are encouraged and valued. For more information, check out our Contributor Guidelines.

Please note that the chessboard project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Acknowledgments

This package has been developed for the FRB-CESAB working group Bridge that aims to better understand the role of local and regional environmental factors in shaping the taxonomic and functional diversity of plant communities established along river corridors, roadside corridors and cultivated field margins.

References

Blanchet FG, Legendre P & Borcard D (2008) Modelling directional spatial processes in ecological data. Ecological Modelling, 215, 325-336. doi: 10.1016/j.ecolmodel.2008.04.001.

Csardi G & Nepusz T (2006) The igraph software package for complex network research. InterJournal, Complex Systems, 1695, 1-9. https://igraph.org/.

Dray S, Bauman D, Blanchet G et al. (2023) adespatial: Multivariate Multiscale Spatial Analysis. R package version 0.3-21, https://CRAN.R-project.org/package=adespatial.

Dray S, Legendre P & Peres-Neto PR (2006) Spatial modeling: a comprehensive framework for principal coordinate analysis of neighbor matrices (PCNM). Ecological Modelling, 196: 483–93. doi: 10.1016/j.ecolmodel.2006.02.015.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.