simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of effectplots and nat.nblast — release velocity, themes, recent moves, and the top alternatives to consider.
A young ALE and PDP plotting package that rebuilt its numeric core after a data-corrupting bug.
effectplots computes and plots partial dependence, ALE, and observed-versus-predicted effect curves for fitted models. It reached CRAN in November 2024 and shipped three releases in the four months after. The 0.2.0 release is the pivot: an outlier-clipping routine that silently modified the caller's data frame was fixed, the numeric path was rewritten for speed and memory, and the plotting and category-collapsing defaults were reset.
The NBLAST neuron-similarity engine is stable code on life support, shipping once every few years.
nat.nblast implements NBLAST, the pairwise neuron-morphology similarity algorithm used across the natverse for matching and clustering traced neurons — nblast(), nhclust() and the scoring-matrix machinery around them. The algorithm and its interface have not changed in a decade of releases; recent work is CRAN compliance and build infrastructure.
effectplots computes and plots partial dependence, ALE, and observed-versus-predicted effect curves for fitted models. It reached CRAN in November 2024 and shipped three releases in the four months after. The 0.2.0 release is the pivot: an outlier-clipping routine that silently modified the caller's data frame was fixed, the numeric path was rewritten for speed and memory, and the plotting and category-collapsing defaults were reset.
After 0.2.0 the work turns to the awkward cases - missing values on the x axis, explicit and empty factor levels, discrete grid detection. The package is also widening past a single modelling ecosystem: h2o support and tidymodels examples arrived with 0.2.0, and fcut() was exported as a fast replacement for cut(). Release notes are issue-numbered throughout, so the roadmap is effectively the issue tracker.
Expect continued default tuning around collapse_m and discrete_m plus more model-backend coverage; the cadence points to another batch of issue fixes rather than a new plot type.
nat.nblast implements NBLAST, the pairwise neuron-morphology similarity algorithm used across the natverse for matching and clustering traced neurons — nblast(), nhclust() and the scoring-matrix machinery around them. The algorithm and its interface have not changed in a decade of releases; recent work is CRAN compliance and build infrastructure.
The four-year gap between 1.6.6 and 1.6.8 says most of it: this is finished code being kept on CRAN rather than a package under development. The 1.6.8 release fixes Rd cross-references and moves continuous integration to GitHub Actions, with no user-facing change at all. The last release that altered numerical output was 1.6.6 in 2021.
Expect further releases only when CRAN check policy or a natverse dependency forces one. Nothing in these entries suggests algorithmic work is underway.
Other Analytics 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 effectplots or nat.nblast.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
See all effectplots alternatives → · See all nat.nblast alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. effectplots and nat.nblast 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. effectplots and nat.nblast 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 Analytics products to evaluate alongside.
Top effectplots alternatives in Analytics are ranked by recent ship velocity. Browse the "effectplots alternatives" section above for the current picks, or visit /alternatives/effectplots for the full list with editorial commentary on each.
Top nat.nblast alternatives in Analytics are ranked by recent ship velocity. Browse the "nat.nblast alternatives" section above for the current picks, or visit /alternatives/nat-nblast for the full list with editorial commentary on each.