macOS
Homebrewverified · 100%
brew install gibbsldalocal Homebrew formula metadata
MacPortsverified · 94%
sudo port install gibbsldaMacPorts ports tree · math/gibbslda/Portfile · source: api.github.com
brew / rank 19099
Install gibbslda with Homebrew, MacPorts
Library wrapping imlib2's context API. Version 0.2 via Homebrew; verified from local package data. Also installable with macports: sudo port install gibbslda.
install
Additional install commands
overview
Package summary
Library wrapping imlib2's context API
Project links
Commands and aliases
- lda
history
Project history and usage
GibbsLDA++ is a C/C++ implementation of Latent Dirichlet Allocation using Gibbs sampling for parameter estimation and inference. It belongs to the late-2000s generation of compact research toolkits for topic modeling.
Project history
The official SourceForge project identifies GibbsLDA++ as a beta C/C++ Gibbs-sampling LDA implementation by pxhieu. The project was registered in July 2007, and its file area shows the manual, case-study material, and 0.2 source distribution published in July and August 2007.
Adoption history
GibbsLDA++ was useful because LDA had become a common model for hidden topic structures while many researchers still wanted a small command-line implementation. The supplied package metadata shows it carried by Homebrew and MacPorts, reflecting a preservation-style package footprint for older scientific workflows.
How it is used
Practitioners use the `lda` executable to estimate LDA models and infer topic distributions from text corpora. The official project description emphasizes large-scale text data collections, Gibbs sampling, and console/terminal use.
Why package nerds care
For package maintainers, GibbsLDA++ is a small legacy scientific CLI whose main value is reproducibility. Keeping it packaged lets old scripts and papers continue to depend on a stable `lda` executable rather than a broad machine-learning framework.
Timeline
- 2007: SourceForge project registered.
- 2007: Documents published on SourceForge.
- 2007: GibbsLDA++ 0.2 source and case-study files published.
- 2013: SourceForge project page records a later project update.
Related projects
- GibbsLDA++ is related to JGibbLDA from the same topic-modeling lineage, LDA research implementations, and other C/C++, Java, Matlab, and Python topic-modeling packages.
Sources
security posture
Risk level: green
library-like package without higher-risk signals.
Risk classifier
green risk · low confidence · appliance
Why
- library-like package without higher-risk signals
Signals
- metadata:library-like
Install behavior
- No Homebrew bottle metadata was recorded.
Recommended review
Before unattended agent use, check whether the tool reads plaintext credentials, writes remote state, publishes artifacts, or shells out to plugins.
executables
Installed executables
| Command | Kind | Exposure | Note |
|---|---|---|---|
lda | executable | indexed executable | Discovered from the local executable index. |
freshness
Version and freshness
These signals separate page generation age, package-manager activity, and upstream release comparison. Version lag is warned only when an evidence URL and comparable versions are present.
page generated2026-08-03
manager version0.2
manager updated
local dataunknown
upstreamnot available
latest detectednot detected
- okNo freshness warnings were generated.
install metadata
Package metadata
| Package key | brew:gibbslda |
|---|---|
| Version | 0.2 |
| Package manager | Homebrew |
| Homepage | https://gibbslda.sourceforge.net/ |
| Bottle | not recorded |
| Service | none declared |
source database matches
Other package-manager records
Matches are pulled from external package-manager indexes and kept separate from local Automic Vault package links.
MacPorts95%
gibbslda
sudo port install gibbslda- normalized package name match
- Matched by: Gibbslda
source trail
Generated from repository data
This page is generated by av-web from the private package SQLite artifact built by scripts/generate-pkg-sqlite.py.
Combined YAML source
View the package source record on GitHub.
Used sources
- Geiger risk classifier
- cross-ecosystem install command graph
- curated package history
- external package-manager database matches
- pkg.so package database
- pkgdb category and tag curation