fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of animovement and bayestools — release velocity, themes, recent moves, and the top alternatives to consider.
animovement stopped being a package and became a metapackage over seven focused ones.
animovement handles animal movement data — tracking output from pose-estimation and centroid trackers, cleaned into a standard form. Its 0.7.3 release, the first GitHub tag since November 2024, bundles the 0.5 through 0.7 development series and records a structural change: the codebase was split into aniframe, aniread, aniprocess, anicheck, animetric, anivis and anispace, which animovement now bundles and re-exports. The package has done this before at smaller scale, having renamed itself from trackballr in 0.2.0 to match a widened scope.
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
BayesTools provides the shared JAGS fitting, prior and summary infrastructure that the author's meta-analysis packages build on. The 0.2.x line filled in modeling primitives — prior_mixture() and mixed-posterior objects in 0.2.18, expression-valued priors and lme4-style uncorrelated random effects in 0.2.20, then a run of small diagnostic fixes for mixture and spike-and-slab priors. Version 0.3.0 in May 2026 adds automatic standardization of continuous predictors, default priors for unspecified factor and continuous terms, and functions to transform prior and posterior samples back to the original scale.
animovement handles animal movement data — tracking output from pose-estimation and centroid trackers, cleaned into a standard form. Its 0.7.3 release, the first GitHub tag since November 2024, bundles the 0.5 through 0.7 development series and records a structural change: the codebase was split into aniframe, aniread, aniprocess, anicheck, animetric, anivis and anispace, which animovement now bundles and re-exports. The package has done this before at smaller scale, having renamed itself from trackballr in 0.2.0 to match a widened scope.
Development has moved to the constituent packages, which release far more often than animovement itself — aniframe, aniread and aniprocess have each shipped multiple times in 2026 while animovement tagged once. That makes animovement a stable install surface rather than where the work happens, and the ani_df data class plus the frame-rate to sampling-rate terminology change are the contracts holding the suite together. Optional dependencies are handled through animovement_install_suggested() against r-universe and Bioconductor mirrors.
With the split done and the constituent packages iterating independently, animovement releases are likely to become periodic roll-ups of the suite rather than carriers of new functionality.
BayesTools provides the shared JAGS fitting, prior and summary infrastructure that the author's meta-analysis packages build on. The 0.2.x line filled in modeling primitives — prior_mixture() and mixed-posterior objects in 0.2.18, expression-valued priors and lme4-style uncorrelated random effects in 0.2.20, then a run of small diagnostic fixes for mixture and spike-and-slab priors. Version 0.3.0 in May 2026 adds automatic standardization of continuous predictors, default priors for unspecified factor and continuous terms, and functions to transform prior and posterior samples back to the original scale.
This package's releases are best read against what depends on them. The 0.2.x fixes track features appearing in RoBMA one version later, and 0.3.0 landed a single day before RoBMA 4.0.0 — the standardization and sample-transformation functions are the substrate that rewrite needed. The direction of the work is toward sensible defaults: default priors by predictor type, automatic standardization for sampling stability, and transformation back to interpretable scale so the convenience does not cost the user their units.
Given how tightly its releases track downstream needs, the next version is most likely driven by gaps surfacing in RoBMA 4.0.x rather than by independent feature work.
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 animovement or bayestools.
Pattern fills for ggplot2, hardened against the ways users write sizes
gcube's recent releases are all packaging metadata, not simulation code
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats keeps widening what a coefficient or Likert plot can be
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
State-space data simulation for R, filled in one function at a time
See all animovement alternatives → · See all bayestools alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. animovement and bayestools 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. animovement and bayestools 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 animovement alternatives in Analytics are ranked by recent ship velocity. Browse the "animovement alternatives" section above for the current picks, or visit /alternatives/animovement for the full list with editorial commentary on each.
Top bayestools alternatives in Analytics are ranked by recent ship velocity. Browse the "bayestools alternatives" section above for the current picks, or visit /alternatives/bayestools for the full list with editorial commentary on each.