Tools for motif analysis in multi-level networks. Multi-level networks combine multiple networks in one, e.g. social-ecological networks. Motifs are small configurations of nodes and edges (subgraphs) occurring in networks. 'motifr' can visualize multi-level networks, count multi-level network motifs and compare motif occurrences to baseline models. It also identifies contributions of existing or potential edges to motifs to find critical or missing edges. The package is in many parts an R wrapper for the excellent 'SESMotifAnalyser' 'Python' package written by Tim Seppelt.
Version: 1.0.0 Depends: R (≥ 3.5.0) Imports: dplyr, ggplot2 (≥ 2.1.0), ggraph, igraph, intergraph, network, purrr, RColorBrewer, reshape2, reticulate, rlang, scales, tibble, tidygraph Suggests: ergm, knitr, pkgdown, rmarkdown, shiny, testthat (≥ 2.1.0) Published: 2020-12-10 DOI: 10.32614/CRAN.package.motifr Author: Mario Angst [aut, cre], Tim Seppelt [aut] Maintainer: Mario Angst <mario.angst at gmail.com> BugReports: https://github.com/marioangst/motifr/issues License: MIT + file LICENSE URL: https://marioangst.github.io/motifr/ NeedsCompilation: no SystemRequirements: Python (>= 3.0.0), numpy, pandas Language: en-GB Materials: README NEWS CRAN checks: motifr results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=motifr to link to this page.
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