Motif Analysis in Multi-Level Networks
Compare motif occurence in empirical network to occurence in a baselin...
Count multi-level motifs
List critical dyads
List edge contribution
Returns an example for a motif found in a given network
Explore the motif zoo interactively in a shiny app
List gaps
Returns subgraph induced by one level of the network
Checks whether the given network is directed
Lists motifs of a given class or all motifs with a given signature
Two-level network example (wetlands management)
Summary for motif counts and Erdős-Rényi distribution
Compute statistical properties (expectation and variance) of the distr...
Plot critical dyads in network visualisation
Plot gaps in network visualisation
Helper function for plotting gaps and critical edges
Visualize a multi-level network (using ggraph)
Plots an example for a motif with given motif identifier string taken ...
Simulate a baseline baseline model
Lists all supported motif classes for a given signature
Lists all supported signatures
Translate multi-level statnet or igraph network object to Python netwo...
Checks for updates for motifr's Python core, the sma package
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.