prioritizr
Conservation planning absorbs the literature's target-setting rules as code.
A side-by-side editorial comparison of emuR and tf — release velocity, themes, recent moves, and the top alternatives to consider.
The R half of the EMU speech database system, fixing what was quietly broken.
emuR is the R interface to the EMU Speech Database Management System — loading annotated speech corpora, running hierarchical queries over annotation levels, extracting signal track data, and serving corpora to the EMU-webApp for browser-based annotation. It is at 2.6.0 on a slow cadence of roughly one release a year. Recent work has centred on the CRUD operations for annotation items and on widening what serve() can hand the web application.
tf gave functional data a second dimension: curves whose values are vectors.
tf supplies the vector classes underneath the tidyfun stack — tfd for raw functional observations, tfb for basis-represented ones, both built on vctrs so curves sit in a data frame column and behave like any other vector. Until July that codomain was scalar. The 0.5.0 release adds tfd_mv and tfb_mv, classes for functions whose values are vectors in R^d, and rebuilds the analysis verbs to match.
emuR is the R interface to the EMU Speech Database Management System — loading annotated speech corpora, running hierarchical queries over annotation levels, extracting signal track data, and serving corpora to the EMU-webApp for browser-based annotation. It is at 2.6.0 on a slow cadence of roughly one release a year. Recent work has centred on the CRUD operations for annotation items and on widening what serve() can hand the web application.
The releases read as a package being brought up to the standard its own API implied. delete_itemsInLevel() shipped in 2.1.1 as a first version, was described in 2.5.0 as heavily flawed and now usable, and the create/update/delete family is still called ongoing work. Alongside that, the query engine was rewritten onto CTEs and the signal-processing layer is being opened past the bundled wrassp, starting with Matlab. Speed work recurs — SQLite transactions, prepared statements, on-the-fly caching — consistent with corpora outgrowing the original design.
Two threads are explicitly unfinished: the CRUD documentation and behaviour, described as ongoing, and the add_signalVia family, described as a draft starting with Matlab. Expect the next release to advance one of them rather than open new ground.
tf supplies the vector classes underneath the tidyfun stack — tfd for raw functional observations, tfb for basis-represented ones, both built on vctrs so curves sit in a data frame column and behave like any other vector. Until July that codomain was scalar. The 0.5.0 release adds tfd_mv and tfb_mv, classes for functions whose values are vectors in R^d, and rebuilds the analysis verbs to match.
The package is widening what a functional observation can be, then porting the toolkit onto it. Registration arrived first in 0.4.0 for univariate curves and immediately gained an srvf_mv method for aligning components jointly, and tfb_mfpc() ports principal component analysis to the multivariate case with a single set of scores shared across components. Alongside that runs steady dependency shedding — mvtnorm and pracma both replaced by inlined samplers that reproduce prior draws bit-for-bit, glue dropped for cli in the previous release — and an unusually long tail of NA-handling and edge-case fixes, several caught in pre-release review of the new classes.
The new classes ship with FPCA, registration and shape alignment but the release notes describe tidyfun::tf_unnest() as the consumer of one new export, so the visible next step is the rest of the tidyfun stack catching up to vector-valued columns. Expect follow-up patches on the vctrs casting paths, which is where most of this release's late fixes clustered.
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 emuR or tf.
Conservation planning absorbs the literature's target-setting rules as code.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
An ecosystem model starts tracking carbon isotopes and land-use change.
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
Fitness-tracking analysis in slow maintenance, still absorbing upstream breakage.
State-panel tooling holding steady since its 2020 data and ergonomics release.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. emuR and tf 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. emuR and tf 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 emuR alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "emuR alternatives" section above for the current picks, or visit /alternatives/emur for the full list with editorial commentary on each.
Top tf alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "tf alternatives" section above for the current picks, or visit /alternatives/tf for the full list with editorial commentary on each.