STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
nat.nblast vs sdsfun
A side-by-side editorial comparison of nat.nblast and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
nat.nblast vs sdsfun: at a glance
What is nat.nblast?
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.
What is sdsfun?
A spatial-statistics utility package exists to be depended on, and is built accordingly.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
nat.nblast vs sdsfun: editorial side-by-side
nat.nblast
0.0ANALYTICS
The NBLAST neuron-similarity engine is stable code on life support, shipping once every few years.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
Expect further releases only when CRAN check policy or a natverse dependency forces one. Nothing in these entries suggests algorithmic work is underway.
sdsfun
0.0ANALYTICS
A spatial-statistics utility package exists to be depended on, and is built accordingly.
◆ Current state
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
◆ Where it's heading
This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.
◆ Prediction
Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.
Alternatives to nat.nblast and sdsfun
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 nat.nblast or sdsfun.
ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
kde1d
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
gghighlight
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
rtrek
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all nat.nblast alternatives → · See all sdsfun alternatives →
Recent activity from nat.nblast and sdsfun
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10mo agosdsfunPackage load stops touching the RNG state
- 0y agonat.nblastCRAN cross-reference fixes and GitHub Actions setup
- 1y agosdsfunUnified partial correlation testing and head/tails discretization
- 1y agosdsfunMissing-value handling added to linear trend removal
- 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
- 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
- 1y agosdsfunFast geodetector q-value estimator added
- 5y agonat.nblastScale factor retained when normalising scores
- 7y agonat.nblastnhclust accepts score matrices directly
- 7y agonat.nblastR 3.3 compatibility fixes and first vignette
- 11y agonat.nblastPackage test fixes only
Frequently asked questions
What is the difference between nat.nblast and sdsfun?
Both compete on the same themes — r-package — within Analytics. nat.nblast and sdsfun 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.
Is nat.nblast better than sdsfun?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nat.nblast and sdsfun 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.
What are the best alternatives to nat.nblast?
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.
What are the best alternatives to sdsfun?
Top sdsfun alternatives in Analytics are ranked by recent ship velocity. Browse the "sdsfun alternatives" section above for the current picks, or visit /alternatives/sdsfun for the full list with editorial commentary on each.