opticskxi
1.2.2OPTICS K-Xi Density-Based Clustering
Overview
Density-based clustering methods are well adapted to the clustering of high-dimensional data and enable the discovery of core groups of various shapes despite large amounts of noise. This package provides a novel density-based cluster extraction method, OPTICS k-Xi, and a framework to compare k-Xi models using distance-based metrics to investigate datasets with unknown number of clusters. The vignette first introduces density-based algorithms with simulated datasets, then presents and evaluates the k-Xi cluster extraction method. Finally, the models comparison framework is described and experimented on 2 genetic datasets to identify groups and their discriminating features. The k-Xi algorithm is a novel OPTICS cluster extraction method that specifies directly the number of clusters and does not require fine-tuning of the steepness parameter as the OPTICS Xi method. Combined with a framework that compares models with varying parameters, the OPTICS k-Xi method can identify groups in noisy datasets with unknown number of clusters. Results on summarized genetic data of 1,200 patients are in Charlon T. (2019) doi:10.13097/archive-ouverte/unige:161795. A short video tutorial can be found at https://www.youtube.com/watch?v=P2XAjqI5Lc4/.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-07-1112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-1513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-1012 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 95%
- Return-value docs
- 95%
- References docs
- 0%
Downloads
Repository
Repository practices
Repository gitlab.com/thomaschln/opticskxi is linked, but repository-practices checks have not run for it yet. Checks are GitHub-only for now.
Dependencies
Code & Tests
- Cyclomatic complexity
- 2.0 median / 10 max
- Test cases
- 13 / 0.22 per code line
Test coverage
Line coverage
93%
Expression
91.1%
Tests / Examples
93.1% / 73% ex
Functions
41 21 exported
Complexity
2.6 avg / 10 max
Call network
41 nodes / 28 edges
Call graph
Open call graph →Lowest coverage
41 functions| Function | Cyclo | Coverage |
|---|---|---|
| norm_inprod exp | 1 | 0% |
| stddev_mean exp | 2 | 0% |
| inprod | 2 | 0% |
| dist_matrix exp | 2 | 75% |
| get_best_kxi exp | 4 | 75% |
| normalize exp | 4 | 80% |
Datasets
| Name | Class | Rows × Cols | Also ships in |
|---|---|---|---|
| crohn | data.frame | 387 × 212 | in 3 packages |
| hla | data.frame | 271 × 8 | in 2 packages |
| multishapes | data.frame | 1,100 × 3 | in 2 packages |
People & History
5 releases. Pick two to compare their code metrics. R releases are shown for context.
- 1.2.2Latest
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 1.2.12025-03-09 · diff ↗
- 1.2.02025-02-26 · diff ↗
- 1.1.02024-12-09 · diff ↗
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 0.12019-07-19
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2019-07-19
- Total releases
- 5 / 7 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 661 KB / 4 files
- Download size
- 2.5 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet