driveR
A cancer driver prioritization package that ships rarely and mostly to stay installable
A side-by-side editorial comparison of metR and simDAG — release velocity, themes, recent moves, and the top alternatives to consider.
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.
simDAG grew a second simulation engine, then spent two releases surviving upstream breakage.
simDAG generates data from directed acyclic graphs, with a library of node types covering Gaussian, binomial, Poisson, negative binomial, zero-inflated, ordered regression, Cox, and Aalen models. The 1.0.0 milestone opened node_cox() to arbitrary baseline hazard functions, which lets continuous time-dependent hazards drive discrete-event simulations. The two most recent releases exist only to keep the package on CRAN through breakage in lme4 and simr.
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.
simDAG generates data from directed acyclic graphs, with a library of node types covering Gaussian, binomial, Poisson, negative binomial, zero-inflated, ordered regression, Cox, and Aalen models. The 1.0.0 milestone opened node_cox() to arbitrary baseline hazard functions, which lets continuous time-dependent hazards drive discrete-event simulations. The two most recent releases exist only to keep the package on CRAN through breakage in lme4 and simr.
The package has been widening what a simulation can represent rather than deepening any one node. Networks arrived in 0.4.0 so individuals could depend on each other, discrete-event simulation in continuous time arrived in 0.5.0 as an alternative to the discrete-time engine, and 1.0.0 connected the two by letting continuous hazards feed the event-driven path. Alongside that, node types keep accumulating for outcome families the framework could not previously generate.
Expect the node library to keep expanding into outcome types the discrete-event engine can now support, though the recent releases suggest upstream dependency churn will keep consuming release slots.
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 metR or simDAG.
A cancer driver prioritization package that ships rarely and mostly to stay installable
An isotope geolocation package still recovering from the r-spatial retirement
Functional data clustering grew from one algorithm into a comparable suite
A forecast combination package that spun its profiler out into its own project
A survival curve package spending release after release correcting its own estimates
A numerical optimization toolkit that has been feature-complete and quiet since 2017
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. simDAG 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. simDAG 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 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.
Top simDAG alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "simDAG alternatives" section above for the current picks, or visit /alternatives/simdag for the full list with editorial commentary on each.