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Comparison · Infra & APIs

rgm vs SLmetrics

A side-by-side editorial comparison of rgm and SLmetrics — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

rgm vs SLmetrics: at a glance

FeaturergmSLmetrics
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesmicrobiome, graphical-models, bayesian-inference, cran-maintenancemachine-learning, model-evaluation, performance, cpp-backend
Last editorial update1h ago2d ago
WebsiteVisit →Visit →

What is rgm?

A microbiome network model that got itself un-archived by deleting the dependency that killed it.

rgm implements the random graphical model for microbiome interactions across related environments, published in JABES in 2026. The package was archived from CRAN in February 2026 because of its dependency on huge; the recovery release drops that dependency entirely, which cost it the graphical-lasso warm start that used to seed the initial graph — the default is now an empty graph, with warm starts left to the user. A post-processing function returning ggplot diagnostics arrived in the same release.

Read the full rgm trajectory →

What is SLmetrics?

A young ML metrics package rewrote its own backend twice in six months chasing speed.

SLmetrics provides supervised learning evaluation metrics for R — confusion matrices, classification and regression measures, ROC and precision-recall curves — with the computation pushed into C++. After a series of pre-releases it now runs on an Armadillo backend, supports OpenMP parallelism and LAPACK/BLAS, and reports 5-20x speedups over its earlier implementations. The API has been reshaped for extensibility, with an estimator argument replacing the fixed aggregation options.

Read the full SLmetrics trajectory →

rgm vs SLmetrics: editorial side-by-side

R
rgm
INFRA · APIS
0.0

A microbiome network model that got itself un-archived by deleting the dependency that killed it.

◆ Current state

rgm implements the random graphical model for microbiome interactions across related environments, published in JABES in 2026. The package was archived from CRAN in February 2026 because of its dependency on huge; the recovery release drops that dependency entirely, which cost it the graphical-lasso warm start that used to seed the initial graph — the default is now an empty graph, with warm starts left to the user. A post-processing function returning ggplot diagnostics arrived in the same release.

◆ Where it's heading

Three tags shipped inside two hours on one day, and the notes are candid about why: 1.1.0 held the actual work but was never released, 1.2.0 restated it under a higher version to signal the size of the change, and 1.2.1 answered CRAN pre-test feedback. Beyond the archival recovery, the visible work is housekeeping that had accumulated — a shadowed rmvnorm() definition, roxygen import tags that were silently emitting nothing, leftover C++ template scaffolding, and build artifacts under version control. The diagnostics function is the only genuinely new user-facing capability in the window.

◆ Prediction

The immediate task was restoring availability, and that is done; the open question the entries raise is whether losing the graphical-lasso warm start affects convergence in practice, which the new diagnostic plots are positioned to answer.

S
SLmetrics
INFRA · APIS
0.0

A young ML metrics package rewrote its own backend twice in six months chasing speed.

◆ Current state

SLmetrics provides supervised learning evaluation metrics for R — confusion matrices, classification and regression measures, ROC and precision-recall curves — with the computation pushed into C++. After a series of pre-releases it now runs on an Armadillo backend, supports OpenMP parallelism and LAPACK/BLAS, and reports 5-20x speedups over its earlier implementations. The API has been reshaped for extensibility, with an estimator argument replacing the fixed aggregation options.

◆ Where it's heading

Every release in this timeline is about making the same metrics compute faster or compose better. The backend moved from Rcpp to plain C++, gained OpenMP, then was ported wholesale from Eigen to Armadillo with heavy templating. In parallel the author has been widening the API's joints: generic S3 signatures, an extensible estimator argument, and function signatures loose enough that wrapping packages can rename arguments. Bundled datasets and embedded formulas in the docs point at teaching and benchmarking use. The package still labels itself pre-release, which is consistent with how freely it has broken argument names along the way.

◆ Prediction

A stable non-pre-release version is the natural next step now that the backend has settled on Armadillo, though the repeated willingness to rename arguments suggests more API churn may come first.

Alternatives to rgm and SLmetrics

Other Infra & APIs products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either rgm or SLmetrics.

See all rgm alternatives → · See all SLmetrics alternatives →

Recent activity from rgm and SLmetrics

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 3mo agorgmJournal DOI replaces the preprint; promotional wording removed
  2. 3mo agorgmBack on CRAN after dropping the dependency that caused archival
  3. 3mo agorgmUnreleased twin of the CRAN recovery release
  4. 1y agoSLmetricsArmadillo backend brings 5-20x speedups and an extensible metrics API
  5. 1y agoSLmetricsConsistent S3 signatures and three bundled datasets
  6. 1y agoSLmetricsRegression metrics 2-10x faster with reworked OpenMP controls
  7. 1y agoSLmetricsOpenMP parallelism and a soft-label entropy family
  8. 1y agoSLmetricsCross-entropy loss and relative RMSE with three normalisations
  9. 1y agoSLmetricsSample weights flow through the confusion matrix
  10. 2y agorgmFirst release: simulation, estimation and post-processing

Frequently asked questions

What is the difference between rgm and SLmetrics?

Both compete on the same themes — r-package — within Infra & APIs. rgm and SLmetrics are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is rgm better than SLmetrics?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rgm and SLmetrics are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.

What are the best alternatives to rgm?

Top rgm alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "rgm alternatives" section above for the current picks, or visit /alternatives/rgm for the full list with editorial commentary on each.

What are the best alternatives to SLmetrics?

Top SLmetrics alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "SLmetrics alternatives" section above for the current picks, or visit /alternatives/slmetrics for the full list with editorial commentary on each.