NHSRwaitinglist
Queuing theory packaged for NHS waiting-list managers, one year into a community-built first release.
A side-by-side editorial comparison of antaresread and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
The R reader for Antares Simulator studies, pinned to whatever the simulator ships next
antaresRead loads Antares Simulator studies from disk or the Antares Web API into R. Its release history maps one-to-one onto simulator versions: 2.9.2 for Antares 9.2, 2.9.3 for 9.3, and the 3.0.x line for the study-format changes that followed. The recurring work is the converted study version format (9.0 becoming 900) which has now been fixed or re-fixed in three consecutive releases, and 3.1.0 turns that churn into a declared breaking change as Antares Web 2.33.0 introduces yet another numbering scheme.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
antaresRead loads Antares Simulator studies from disk or the Antares Web API into R. Its release history maps one-to-one onto simulator versions: 2.9.2 for Antares 9.2, 2.9.3 for 9.3, and the 3.0.x line for the study-format changes that followed. The recurring work is the converted study version format (9.0 becoming 900) which has now been fixed or re-fixed in three consecutive releases, and 3.1.0 turns that churn into a declared breaking change as Antares Web 2.33.0 introduces yet another numbering scheme.
The package is a compatibility layer whose roadmap is set entirely upstream, and version identity is where it keeps getting cut. The same .getSimOptionsAPI() version-format fix appears in 3.0.0, 3.0.1 and again in 3.1.0 — three passes at one problem, which suggests the API and disk representations of a study version have not converged. Alongside that, API-mode work is displacing disk-mode work: dedicated endpoints for output listing, district definitions, per-area output handling.
The next release will most likely track the following Antares Simulator or Antares Web version, and given the 3.1.0 breaking change, a follow-up correcting the new numbering scheme is a reasonable expectation.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.
Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.
Other Analytics 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 antaresread or sdsfun.
Queuing theory packaged for NHS waiting-list managers, one year into a community-built first release.
The plotting companion to simmer, shipping only when the simulator or a graphics dependency moves.
A fast random-graph sampler that spent 0.3.1 fixing what its parameters actually mean.
A young Mathematics Genealogy client spending its first four releases satisfying CRAN.
The natverse package that taught neuron data to remember which brain space it lives in.
The NBLAST neuron-similarity engine is stable code on life support, shipping once every few years.
See all antaresread alternatives → · See all sdsfun alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. antaresread and sdsfun 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. antaresread and sdsfun 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 Analytics products to evaluate alongside.
Top antaresread alternatives in Analytics are ranked by recent ship velocity. Browse the "antaresread alternatives" section above for the current picks, or visit /alternatives/antaresread for the full list with editorial commentary on each.
Top sdsfun alternatives in Analytics are ranked by recent ship velocity. Browse the "sdsfun alternatives" section above for the current picks, or visit /alternatives/sdsfun for the full list with editorial commentary on each.