qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of constants and lpjmlkit — release velocity, themes, recent moves, and the top alternatives to consider.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
constants exposes the CODATA recommended values of the physical constants to R, as a data frame plus symbol lists that carry units, uncertainties, or both. The package reached 1.0.0 on the 2018 CODATA release and has shipped once since, purely to track a units package update. Its surface is small and its release cadence is bound to CODATA, which revises every few years.
The LPJmL toolkit finally reads NetCDF, closing a gap against the format its field uses.
lpjmlkit is the R toolkit for running the LPJmL dynamic global vegetation model and reading its output. The 1.8.0 release adds direct NetCDF reading, either straight or via .nc.json metafiles, alongside the package's own binary formats. Before that, 1.7.3 sped up read_io(), reworked the LPJmLGridData implementation and added reservoir input support. Releases are infrequent, roughly one every 12 to 18 months.
constants exposes the CODATA recommended values of the physical constants to R, as a data frame plus symbol lists that carry units, uncertainties, or both. The package reached 1.0.0 on the 2018 CODATA release and has shipped once since, purely to track a units package update. Its surface is small and its release cadence is bound to CODATA, which revises every few years.
The direction set at 1.0.0 was to stop being a curated convenience wrapper and become a mechanical mirror of NIST. Hand-crafted symbol names were replaced with NIST's own ASCII symbols, categories adopted NIST's, and uncertainty switched from relative to absolute — all framed by the maintainer as necessary to make future CODATA updates routine. On top of that the package gained a correlation matrix and optional integration with the quantities package, moving it from a lookup table toward something that can propagate uncertainty.
Having rebuilt the symbol table specifically so CODATA revisions become mechanical, the next substantive release most likely tracks a new CODATA dataset rather than adding API. The experimental correlated-value support, disabled by default at 1.0.0, is the one part these entries flag as unfinished.
lpjmlkit is the R toolkit for running the LPJmL dynamic global vegetation model and reading its output. The 1.8.0 release adds direct NetCDF reading, either straight or via .nc.json metafiles, alongside the package's own binary formats. Before that, 1.7.3 sped up read_io(), reworked the LPJmLGridData implementation and added reservoir input support. Releases are infrequent, roughly one every 12 to 18 months.
The work concentrates on the I/O layer rather than the modeling interface, and it is moving toward the formats the wider earth-system community already exchanges. The gap between 1.7.3 and 1.8.0 is over a year, so this is a research-group package released when the science requires it, not on a schedule. The changelog itself is thin — several entries are merge-commit text or CRAN resubmissions.
Further I/O breadth is the likeliest direction now that NetCDF is supported, though the entries give no schedule; the release cadence has not been regular enough to predict timing.
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 constants or lpjmlkit.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
The R client for AusTraits spends its releases chasing the dataset it reads.
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
A fossil-record simulator that quietly grew a trait-evolution engine.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
See all constants alternatives → · See all lpjmlkit alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. constants and lpjmlkit 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. constants and lpjmlkit 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 constants alternatives in Analytics are ranked by recent ship velocity. Browse the "constants alternatives" section above for the current picks, or visit /alternatives/constants-r for the full list with editorial commentary on each.
Top lpjmlkit alternatives in Analytics are ranked by recent ship velocity. Browse the "lpjmlkit alternatives" section above for the current picks, or visit /alternatives/lpjmlkit-r for the full list with editorial commentary on each.