L1centrality
A graph-centrality package that spent 2026 making its existing measures usable at scale, then went quiet.
A side-by-side editorial comparison of eratosthenes and metR — release velocity, themes, recent moves, and the top alternatives to consider.
eratosthenes spends 0.1.0 hardening inputs rather than adding chronology methods.
eratosthenes does Bayesian estimation of archaeological chronologies from relative sequences, absolute constraints and artifact assemblages. The 0.0.9 line built out the inference diagnostics — traceplots, histograms, batch-means MCSE reporting, displacement estimation — and then consolidated artifact probability-density estimation into a single gibbs_ad_type(). The 0.1.0 tag turns outward instead, adding validators for every user-supplied structure and replacing seq_check() with a more informative seq_diag().
A meteorology ggplot2 extension where the netCDF reader became the main event
metR supplies meteorological and oceanographic tools for R: contour and streamline geoms, EOF decomposition, wave fitting, and ReadNetCDF() for getting gridded data in. Development has concentrated heavily on that reader. Version 0.18.0 added subsetting by dimension index, so the first or last ten timesteps can be read without knowing how many exist; 0.18.1 moved time parsing to the CFtime package; 0.18.2 added cdo operations through rcdo and reading across multiple files in parallel, and fixed a subsetting bug where nearest-gridpoint matching could return data outside the requested range entirely.
eratosthenes does Bayesian estimation of archaeological chronologies from relative sequences, absolute constraints and artifact assemblages. The 0.0.9 line built out the inference diagnostics — traceplots, histograms, batch-means MCSE reporting, displacement estimation — and then consolidated artifact probability-density estimation into a single gibbs_ad_type(). The 0.1.0 tag turns outward instead, adding validators for every user-supplied structure and replacing seq_check() with a more informative seq_diag().
The package is moving from research code to something a non-author can run. Consolidating estimation behind one function, then wrapping every input class in a validator, are the two steps that make failures legible instead of cryptic, and the diagnostics added earlier serve the same end for the sampler itself. Nothing in the window changes the underlying model; the work is all about making it usable and its output checkable.
With inputs validated and diagnostics in place, the next release is more likely to extend the constraint or assemblage modelling than to keep reworking the interface, though the feed's three sparse tags give little to read a cadence from.
metR supplies meteorological and oceanographic tools for R: contour and streamline geoms, EOF decomposition, wave fitting, and ReadNetCDF() for getting gridded data in. Development has concentrated heavily on that reader. Version 0.18.0 added subsetting by dimension index, so the first or last ten timesteps can be read without knowing how many exist; 0.18.1 moved time parsing to the CFtime package; 0.18.2 added cdo operations through rcdo and reading across multiple files in parallel, and fixed a subsetting bug where nearest-gridpoint matching could return data outside the requested range entirely.
Two threads run through the releases. The first is tracking ggplot2, absorbing the linewidth aesthetic, the trans to transform rename and guide compatibility as each landed upstream. The second is narrowing scope while deepening the data path: GetSMNData() was made defunct as too specific for a general package, raster and gdal dependencies were removed, and the udunits2 dependency was dropped when it was orphaned, initially replaced by a homebrewed date parser and eventually by CFtime. The result is a package steadily shedding its own code in favour of specialised upstream libraries.
Expect further ReadNetCDF() work, since it has received features in four of the last five releases and the rcdo integration opens a large surface of operations to expose.
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 eratosthenes or metR.
A graph-centrality package that spent 2026 making its existing measures usable at scale, then went quiet.
A test-theory package that grew into a graphical-model toolkit, now spending its releases paying down the API debt that growth created.
nuggets keeps compounding on the 2.0 rewrite — more pattern families, lighter install.
projoint spent a year on CRAN paperwork, then shipped a correctness fix it flagged itself.
dqcheckr adds drift analysis, then removes the YAML a user had to hand-write.
An actuarial mainstay spends its releases on CI plumbing, not on new mathematics.
See all eratosthenes alternatives → · See all metR alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. eratosthenes is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. eratosthenes is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top eratosthenes alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "eratosthenes alternatives" section above for the current picks, or visit /alternatives/eratosthenes for the full list with editorial commentary on each.
Top metR alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "metR alternatives" section above for the current picks, or visit /alternatives/metr for the full list with editorial commentary on each.