DatabionicSwarm

2.0.0

Swarm Intelligence for Self-Organized Clustering

4packages depend

4.7Kdownloads / year

–test coverage

11/13checks pass

Overview

About

Maintained by Michael ThrunFirst published 2017-08-2014 releasesCRAN page ↗GitHub ↗

Algorithms implementing populations of agents that interact with one another and sense their environment may exhibit emergent behavior such as self-organization and swarm intelligence. Here, a swarm system called Databionic swarm (DBS) is introduced which was published in Thrun, M.C., Ultsch A.: "Swarm Intelligence for Self-Organized Clustering" (2020), Artificial Intelligence, DOI:10.1016/j.artint.2020.103237. DBS is able to adapt itself to structures of high-dimensional data such as natural clusters characterized by distance and/or density based structures in the data space. The first module is the parameter-free projection method called Pswarm (Pswarm()), which exploits the concepts of self-organization and emergence, game theory, swarm intelligence and symmetry considerations. The second module is the parameter-free high-dimensional data visualization technique, which generates projected points on the topographic map with hypsometric tints defined by the generalized U-matrix (GeneratePswarmVisualization()). The third module is the clustering method itself with non-critical parameters (DBSclustering()). Clustering can be verified by the visualization and vice versa. The term DBS refers to the method as a whole. It enables even a non-professional in the field of data mining to apply its algorithms for visualization and/or clustering to data sets with completely different structures drawn from diverse research fields. The comparison to common projection methods can be found in the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) DOI:10.1007/978-3-658-20540-9.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("DatabionicSwarm", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("Mthrun/DatabionicSwarm")

Development version from Mthrun/DatabionicSwarm. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-databionicswarm

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-DatabionicSwarm

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-DatabionicSwarm

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

2NOTE11OK

Failing flavors

NOTE r-devel-linux-x86_64-debian-clang
NOTE r-devel-linux-x86_64-debian-gcc

Slowest check: 6.2 min · r-oldrel-windows-x86_64

Code health

None

Tests · ratio 0.00

not tracked

Coverage

100%

Documentation · exports

Dependencies · direct

Check history

NOTE2026-07-11
12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-04-25
12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-04-22
11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
ERROR2026-04-18
10 OK · 3 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
NOTE2026-03-10
11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 100%
Return-value docs: 100%
References docs: 87%

Downloads

4.7K

CRAN downloads in the past year

Rank #8,519 · ~13/day · ~394/mo

Releases R versions

Daily download trend is not available in this view yet.

44130 days

1.3K90 days

4.7K1 year

Compare downloads with other packages →

Also on450 r2u35 autocran28 c2d4u

Repository

GitHub ↗ mthrun/databionicswarm

12Stars

2Forks

1Open issues

0Open PRs

2Releases

96Commits

2Contributors

96 commits · Last activity 2024-05-15

Stars over time

2024-04-17 · 112026-07-07 · 12

Repository practices

Upstream repositoryBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/mthrun/databionicswarm on 2026-07-19.

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

22 external dependencies (excludes base and recommended)

Depends (1)

R >= 3.0

Imports (6)

Rcpp RcppParallel deldir GeneralizedUmatrix ABCanalysis ggplot2

LinkingTo (3)

Rcpp RcppArmadillo RcppParallel

Suggests (14)

DataVisualizations knitr rmarkdown plotrix geometry sp spdepparallelrgl png ProjectionBasedClustering parallelDist pracma dendextend

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

4direct

0indirect

DRquality PDEnaiveBayes FCPS ProjectionBasedClustering

Code & Tests

Code Composition

R 2,517 (39%)C++ 1,917 (30%)Rd 1,732 (27%)Vignettes 255 (4%)C 9 (0%)

Code characteristics

Cyclomatic complexity: 3.0 median / 37 max
System requirements: 3 external

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

86 13 exported

Complexity

7 avg / 37 max

Call network

86 nodes / 53 edges

Call graph

Open call graph →

Loading call graph…

Lowest coverage

Per-function coverage is not measured for this package yet.

Datasets

Bundled datasets · 1

Name	Class	Rows × Cols	Also ships in
DefaultColorSequence	vector	–	in 4 packages

People & History

People (2)

Maintainer (1)

Michael Thrun

Author, Maintainer, Copyright holder

Authors (2)

Michael Thrun

Author, Maintainer, Copyright holder

Quirin Stier

Author, Reviewer · added in 1.2.0

Michael Thrun

Author, Maintainer, Copyright holder

Reviewers (1)

Quirin Stier

Author, Reviewer · added in 1.2.0

Package Timeline

14 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
2.0.0Latest
2024-06-20 · current release · diff ↗
R
R 4.4.0 released · 2024-04-24
1.2.1
2023-10-13 · diff ↗
1.2.0
2023-05-30 · diff ↗
R
R 4.3.0 released · 2023-04-21
1.1.6
2022-11-29 · diff ↗
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
1.1.5
2021-01-12 · diff ↗
R
R 4.0.0 released · 2020-04-24
1.1.3
2020-02-03 · diff ↗
1.1.2
2019-12-11 · diff ↗
R
R 3.6.0 released · 2019-04-26
1.1.1
2019-01-27 · diff ↗

Show 8 earlier events

1.1.0
2018-07-03 · diff ↗
1.0.3
2018-05-06 · diff ↗
R
R 3.5.0 released · 2018-04-23
1.0.1
2018-03-07 · diff ↗
1.0.0
2018-01-31 · diff ↗
0.9.8
2017-09-28 · diff ↗
0.9.7
2017-08-20
R
R 3.4.0 released · 2017-04-21

Package metadata

First published: 2017-08-20
Total releases: 14 / 9 yrs
License: GPL-3 OSI
Minimum R: ≥ 3.0
Bundled data: 18 KB / 3 files
Download size: 1.0 MB
Installed size: not tracked yet
With dependencies: not tracked yet

Appears in task views

Cluster Analysis & Finite Mixture Models

Report a problem with this page →