Package: motifr
Title: Motif Analysis in Multi-Level Networks
Version: 1.0.0
Date: 2020-12-01
Authors@R: 
    c(person(given = "Mario",
             family = "Angst",
             role = c("aut", "cre"),
             email = "mario.angst@gmail.com",
             comment = c(ORCID = "0000-0002-8297-9827")),
      person(given = "Tim",
             family = "Seppelt",
             role = "aut",
             email = "seppelt@cs.rwth-aachen.de",
             comment = c(ORCID = "0000-0002-6447-0568")))
Description: 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.
License: MIT + file LICENSE
URL: https://marioangst.github.io/motifr/
BugReports: https://github.com/marioangst/motifr/issues
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)
VignetteBuilder: knitr
Config/reticulate: list( packages = list( list(package = "sma", pip =
        TRUE), list(package = "networkx", pip = TRUE) ) )
Encoding: UTF-8
Language: en-GB
LazyData: true
RoxygenNote: 7.1.1
SystemRequirements: Python (>= 3.0.0), numpy, pandas
NeedsCompilation: no
Packaged: 2020-12-09 10:45:48 UTC; Mario
Author: Mario Angst [aut, cre] (<https://orcid.org/0000-0002-8297-9827>),
  Tim Seppelt [aut] (<https://orcid.org/0000-0002-6447-0568>)
Maintainer: Mario Angst <mario.angst@gmail.com>
Repository: CRAN
Date/Publication: 2020-12-10 15:40:02 UTC
Built: R 4.6.0; ; 2026-04-25 13:47:01 UTC; unix
