HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of metR and mize — 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.
A numerical optimization toolkit that has been feature-complete and quiet since 2017
mize provides a configurable interface to unconstrained numerical optimization methods - line searches, gradient descent variants, quasi-Newton updates - usable both as a one-shot call and as a stepwise iterator. Its functional surface has not changed since the initial CRAN release in July 2017. Every release since has been a patch: R-devel compatibility, line search edge cases, and in 2026's 0.2.5 the removal of LazyData from DESCRIPTION plus deletion of some flaky tests.
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.
mize provides a configurable interface to unconstrained numerical optimization methods - line searches, gradient descent variants, quasi-Newton updates - usable both as a one-shot call and as a stepwise iterator. Its functional surface has not changed since the initial CRAN release in July 2017. Every release since has been a patch: R-devel compatibility, line search edge cases, and in 2026's 0.2.5 the removal of LazyData from DESCRIPTION plus deletion of some flaky tests.
The pattern is a stable library rather than an abandoned one. Fixes address real reports - a bracket_step error when the Schmidt line search exhausts its function evaluation budget, an incorrect gradient count under backtracking with a specified step_down - and the maintainer used one release note to clarify that backtracking behaviour differs depending on whether step_down is supplied, which reads as answering a recurring question. The five and a half year gap between 0.2.4 and 0.2.5 is the clearest signal: the package is maintained on demand, not developed.
Expect nothing until an R or CRAN policy change forces another compliance patch, which is what triggered the most recent release.
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 mize.
France's national flood statistics, ported out of Fortran and into R.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
Fast design-based estimators for experiments, coasting on CRAN patches.
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. metR and mize 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. metR and mize 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 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 mize alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mize alternatives" section above for the current picks, or visit /alternatives/mize for the full list with editorial commentary on each.