{ "_id": "6a1178eaacfb0bcc41cfa0a3", "Package": "triversity", "Title": "Diversity Measures on Multipartite Graphs", "Version": "2.0", "Authors@R": "person(\"Robin\", \"Lamarche-Perrin\", email = \"Robin.Lamarche-Perrin@lip6.fr\", role = c(\"aut\", \"cre\"))", "Author": "Robin Lamarche-Perrin [aut, cre]", "Maintainer": "Robin Lamarche-Perrin ", "Description": "Computing diversity measures on multipartite graphs. This\npackage first implements a parametrized family of such\ndiversity measures which apply on probability distributions.\nSometimes called \"True Diversity\", this family contains famous\nmeasures such as the richness, the Shannon entropy, the\nHerfindahl-Hirschman index, and the Berger-Parker index.\nSecond, the package allows to apply these measures on\nprobability distributions resulting from random walks between\nthe parts of multipartite graphs. By defining an initial\ndistribution on a given part of the graph and a path to follow\nbetween the different parts, the probability of the walker's\nposition within the final part is then computed, thus providing\na particular instance of diversity to measure.", "License": "GPL-3 | file LICENSE", "Encoding": "UTF-8", "RoxygenNote": "6.0.1", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://lamarche-perrin.r-universe.dev", "Date/Publication": "2018-03-06 10:15:22 UTC", "RemoteUrl": "https://github.com/lamarche-perrin/triversity", "RemoteRef": "HEAD", "RemoteSha": "554552e6fa5c326e1b261b30f15fc4d45479f23e", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-23 09:49:55 UTC", "User": "root" }, "MD5sum": "05876069cdf8c8870595bedbc98acf17", "_user": "lamarche-perrin", "_type": "src", "_file": "triversity_2.0.tar.gz", "_fileid": "2c7ddbb80d93d23f0694913a45d8bc5ffc98cf4396c4f73bc9d30780cba12d78", "_filesize": 146001, "_sha256": 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"get_diversity_from_path", "get_diversity_from_transition", "get_multipartite", "get_transition_from_path" ], "_datasets": [ { "name": "tripartite_example", "title": "An example of dataframe encoding a small tripartite graph.", "object": "tripartite_example", "file": "tripartite_example.csv.gz", "class": [ "data.frame" ], "fields": [ "V1", "V2", "V3", "V4" ], "rows": 11, "table": true, "tojson": true }, { "name": "tripartite_example_2", "title": "", "object": "tripartite_example_2", "file": "tripartite_example_2.csv.gz", "class": [ "data.frame" ], "fields": [ "u.t.u1.t1.i.i1" ], "rows": 10, "table": true, "tojson": true } ], "_help": [ { "page": "get_all_diversities", "title": "Compute all diversity flows associated to different random walks between the parts of a multipartite graph.", "topics": [ "get_all_diversities" ] }, { "page": "get_distribution_from_path", "title": "Compute the probability distribution associated to a random walk following a path between the parts of a multipartite graph.", "topics": [ "get_distribution_from_path" ] }, { "page": "get_diversity_from_distribution", "title": "Compute the diversity of a probability distribution.", "topics": [ "get_diversity_from_distribution" ] }, { "page": "get_diversity_from_path", "title": "Compute the diversity associated to a random walk following a path between the parts of a multipartite graph.", "topics": [ "get_diversity_from_path" ] }, { "page": "get_diversity_from_transition", "title": "Compute the diversity of a transition matrix, that is the individual diversities of its rows or their mean diversity.", "topics": [ "get_diversity_from_transition" ] }, { "page": "get_multipartite", "title": "Build a properly-structured multipartite graph from raw data.", "topics": [ "get_multipartite" ] }, { "page": "get_transition_from_path", "title": "Compute the transition matrix of a random walk following a path between the parts of a multipartite graph.", "topics": [ "get_transition_from_path" ] }, { 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