rollupTree
The recursive-computation engine under massProps grows the accessors its consumer needed
A side-by-side editorial comparison of mpactr and smam — release velocity, themes, recent moves, and the top alternatives to consider.
mpactr spent two spring releases normalizing case in metadata after users kept tripping on it.
mpactr filters mass-spectrometry peak tables — removing contaminants, ion duplicates and low-reproducibility features before downstream metabolomics analysis — with a data.table and Rcpp core. Development is slow and the recent releases are small. The May pair both address the same friction: column names and imported table names arriving in inconsistent case and failing to match.
Animal-movement models in R, where new stochastic processes arrive years apart.
smam fits statistical models of animal movement, covering moving-resting processes with and without measurement error, moving-resting-handling, and moving-moving processes, with simulation, point estimation and variance estimation for each. The last three releases are pure upkeep: guarding Rf_error calls after an Rcpp update, a maintainer email change, and a compiler warning fix. The substantive work in this window is 0.7.0, which added estimate and vcov generics across all fit functions, and 0.6.0, which added the moving-moving process.
mpactr filters mass-spectrometry peak tables — removing contaminants, ion duplicates and low-reproducibility features before downstream metabolomics analysis — with a data.table and Rcpp core. Development is slow and the recent releases are small. The May pair both address the same friction: column names and imported table names arriving in inconsistent case and failing to match.
The package is stabilizing its input contract rather than growing its filtering methods. Metadata column names are now forced lowercase inside import_data() regardless of how the file was written, imported peak_tables names not present in the injection column are lowercased too, and get_meta_data() was renamed to get_metadata() in the same pass. Before that the work was infrastructural — Rcpp introduced to speed up filtering, data.table moved from Depends to Imports, and memory errors cleared so the package passes Valgrind and both sanitizers. Note the earliest entry compares against a v1.0.0 tag that precedes 0.1.0 in the repository, so version ordering in this feed is not reliable.
The case-normalization work has now touched both metadata columns and peak table names across two consecutive releases, which suggests the input-matching problem is not fully closed and a third pass is plausible. Nothing in these entries points to new filtering methods.
smam fits statistical models of animal movement, covering moving-resting processes with and without measurement error, moving-resting-handling, and moving-moving processes, with simulation, point estimation and variance estimation for each. The last three releases are pure upkeep: guarding Rf_error calls after an Rcpp update, a maintainer email change, and a compiler warning fix. The substantive work in this window is 0.7.0, which added estimate and vcov generics across all fit functions, and 0.6.0, which added the moving-moving process.
This package grows by adding process models, and it does so rarely. Between the moving-moving process in 2021 and now, the only interface-level change has been the 0.7.0 generics that gave every fit function a common way to retrieve estimates and their covariance, which is consolidation of an accumulated collection rather than expansion of it. The three releases since are entirely reactive to toolchain and CRAN pressure, and they arrive in step with the maintainer's other package coga, which received the same Rcpp guard within twenty minutes on the same day.
Expect further releases to be CRAN and Rcpp maintenance unless a new movement process is published, which is what has historically prompted a minor version here. The generics added in 0.7.0 give any future process model a ready-made interface to slot into.
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 mpactr or smam.
The recursive-computation engine under massProps grows the accessors its consumer needed
A mass-properties rollup spends a year on documentation and follows its sibling's API
Six months of releases and not one of them touched the scoring models
A cognitive-science sampling package ships once, then goes quiet for eighteen months
A Bayesian volatility sampler in its maintenance decade, paying for its own speed
A black-box interpreter reaches CRAN, then learns multi-class and survival responses
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. mpactr and smam 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. mpactr and smam 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 mpactr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mpactr alternatives" section above for the current picks, or visit /alternatives/mpactr for the full list with editorial commentary on each.
Top smam alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "smam alternatives" section above for the current picks, or visit /alternatives/smam for the full list with editorial commentary on each.