Package: motifr 1.0.0

motifr: Motif Analysis in Multi-Level Networks

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.

Authors:Mario Angst [aut, cre], Tim Seppelt [aut]

motifr_1.0.0.tar.gz
motifr_1.0.0.zip(r-4.7)motifr_1.0.0.zip(r-4.6)motifr_1.0.0.zip(r-4.5)
motifr_1.0.0.tgz(r-4.6-any)motifr_1.0.0.tgz(r-4.5-any)
motifr_1.0.0.tar.gz(r-4.7-any)motifr_1.0.0.tar.gz(r-4.6-any)
motifr_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
motifr/json (API)

# Install 'motifr' in R:
install.packages('motifr', repos = c('https://marioangst.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/marioangst/motifr/issues

Pkgdown/docs site:https://marioangst.github.io

Datasets:

On CRAN:

Conda:

5.46 score 16 stars 18 scripts 283 downloads 21 exports 78 dependencies

Last updated from:5c7b65acfc. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK192
source / vignettesOK220
linux-release-x86_64OK188
macos-release-arm64OK176
macos-oldrel-arm64OK109
windows-develOK148
windows-releaseOK165
windows-oldrelOK163
wasm-releaseOK150

Exports:compare_to_baselinecount_motifscritical_dyadsedge_contributionexemplify_motifexplore_motifsidentify_gapsinduced_level_subgraphis.directedlist_motifsmotif_summarymotifs_distributionplot_critical_dyadsplot_gapsplot_mnetshow_motifsimulate_baselinesupported_classessupported_signaturesto_py_graphupdate_motifr

Dependencies:base64encbslibcachemclicodacommonmarkcpp11digestdplyrfarverfastmapfontawesomefsgenericsggforceggplot2ggraphggrepelgluegraphlayoutsgridExtragtableherehtmltoolshttpuvigraphintergraphisobandjquerylibjsonlitelabelinglaterlatticelifecyclemagrittrMASSMatrixmemoisemimenetworkotelpillarpkgconfigplyrpngpolyclippromisespurrrR6rappdirsRColorBrewerRcppRcppArmadilloRcppTOMLreshape2reticulaterlangrprojrootS7sassscalesshinysourcetoolsstatnet.commonstringistringrsystemfontstibbletidygraphtidyrtidyselecttweenrutf8vctrsviridisviridisLitewithrxtable

Baseline model comparisons
Baseline models | Motifs in networks simulated based on a baseline model | Motif distributions without simulation | Difference between Erdős-Rényi and Fixed Densities | Level selection in Actor's Choice Model | Exponential Random Graph Models (ERGM) | Workflow for Partial ERGM
Rendered fromrandom_baselines.Rmdusingknitr::rmarkdown

Last update: 2020-11-30
Started: 2020-04-27

The motif zoo
Motif classification – how to label motifs in the wild | A word of caution on counting: Position matching
Rendered frommotif_zoo.Rmdusingknitr::rmarkdown

Last update: 2020-11-30
Started: 2020-04-27

Readme and manuals

Help Manual

Help pageTopics
Compare motif occurence in empirical network to occurence in a baseline modelcompare_to_baseline
Count multi-level motifscount_motifs
List critical dyadscritical_dyads
Two-level directed network dummy exampledirected_dummy_net
Three-level network dummy exampledummy_net
List edge contributionedge_contribution
Returns an example for a motif found in a given networkexemplify_motif
Explore the motif zoo interactively in a shiny appexplore_motifs
List gapsidentify_gaps
Returns subgraph induced by one level of the networkinduced_level_subgraph
Checks whether the given network is directedis.directed
Large two-level directed network dummy examplelarge_directed_dummy_net
Lists motifs of a given class or all motifs with a given signaturelist_motifs
Two-level network example (wetlands management)ml_net
Summary for motif counts and Erdős-Rényi distributionmotif_summary
Compute statistical properties (expectation and variance) of the distribution of motifs in a baseline modelmotifs_distribution
Plot critical dyads in network visualisationplot_critical_dyads
Plot gaps in network visualisationplot_gaps
Helper function for plotting gaps and critical edgesplot_gaps_or_critical_dyads
Visualize a multi-level network (using ggraph)plot_mnet
Plots an example for a motif with given motif identifier string taken from the given graph.show_motif
Simulate a baseline baseline modelsimulate_baseline
Lists all supported motif classes for a given signaturesupported_classes
Lists all supported signaturessupported_signatures
Two-level tidygraph network exampletidygraph_dummy_net
Translate multi-level statnet or igraph network object to Python networkx objectto_py_graph
Checks for updates for motifr's Python core, the sma packageupdate_motifr