reda
A mature recurrent-event toolkit in careful maintenance, shedding weight rather than adding surface.
Comparison · Analytics
mmconvert vs sdsfun
A side-by-side editorial comparison of mmconvert and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
mmconvert vs sdsfun: at a glance
What is mmconvert?
A single-purpose mouse map interpolator that solved its problem in 2023 and has coasted since
mmconvert does one thing: interpolate between GRCm39 physical positions and the revised Cox genetic map for mouse MUGA array markers. The substantive work all landed in a burst across 2021-2023 — the initial function, the GRCm39 annotation dataset, cross2_to_grcm39(), the recomputed Cox maps and their smoothed replacement. Everything since is upkeep: a warning-message fix in 0.12, and 0.14 is a test adjustment to silence a CRAN Note with no code change at all.
What is sdsfun?
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.
mmconvert vs sdsfun: editorial side-by-side
mmconvert
0.0ANALYTICS
A single-purpose mouse map interpolator that solved its problem in 2023 and has coasted since
◆ Current state
mmconvert does one thing: interpolate between GRCm39 physical positions and the revised Cox genetic map for mouse MUGA array markers. The substantive work all landed in a burst across 2021-2023 — the initial function, the GRCm39 annotation dataset, cross2_to_grcm39(), the recomputed Cox maps and their smoothed replacement. Everything since is upkeep: a warning-message fix in 0.12, and 0.14 is a test adjustment to silence a CRAN Note with no code change at all.
◆ Where it's heading
The package has reached the natural end state of a reference-data converter — the reference data stopped moving, so the package stopped moving. Releases now arrive roughly annually and exist to keep CRAN checks green. The 0.14 release shipped the same day as sibling qtl2convert 0.36, confirming these are batch maintenance passes across the maintainer's packages rather than independent development.
◆ Prediction
Without a new mouse genome build or a revised Cox map, the next release is likely another CRAN-check accommodation rather than new functionality.
sdsfun
0.0ANALYTICS
A spatial-statistics utility package exists to be depended on, and is built accordingly.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to mmconvert and sdsfun
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 mmconvert or sdsfun.
TidyDensity
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
cfbfastr
College football's open data client hit v2 — and now reports how many API calls you have left.
rnpn
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
GeneNMF
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
rempsyc
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
See all mmconvert alternatives → · See all sdsfun alternatives →
Recent activity from mmconvert and sdsfun
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agommconvertTest adjustment to clear a CRAN Note
- 10mo agosdsfunPackage load stops touching the RNG state
- 1y agommconvertFixes a malformed warning message in mmconvert()
- 1y agosdsfunUnified partial correlation testing and head/tails discretization
- 1y agosdsfunMissing-value handling added to linear trend removal
- 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
- 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
- 1y agosdsfunFast geodetector q-value estimator added
- 3y agommconvertOmits X chromosome positions for sex-averaged and male maps
- 3y agommconvertCRAN release adds chromosome lengths and smoothed Cox maps
- 3y agommconvertRecomputed Cox genetic maps and combined-array support
- 4y agommconvertRepoints data sources from master to main branches
Frequently asked questions
What is the difference between mmconvert and sdsfun?
Both compete on the same themes — r-package — within Analytics. mmconvert 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.
Is mmconvert better than sdsfun?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mmconvert 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.
What are the best alternatives to mmconvert?
Top mmconvert alternatives in Analytics are ranked by recent ship velocity. Browse the "mmconvert alternatives" section above for the current picks, or visit /alternatives/mmconvert for the full list with editorial commentary on each.
What are the best alternatives to sdsfun?
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.