fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of ecodive and invasimapr — release velocity, themes, recent moves, and the top alternatives to consider.
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
ecodive computes alpha and beta diversity metrics for ecological and microbiome count data, including phylogenetic measures like Faith's PD and the UniFrac family. The 2.0.0 rewrite expanded it from a handful of metrics to roughly fourteen alpha and thirty beta measures while flipping the expected input orientation to samples-as-rows. Subsequent releases have been spent settling the normalisation interface that expansion exposed.
invasimapr halved its install size and became citable; the science stayed put.
invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.
ecodive computes alpha and beta diversity metrics for ecological and microbiome count data, including phylogenetic measures like Faith's PD and the UniFrac family. The 2.0.0 rewrite expanded it from a handful of metrics to roughly fourteen alpha and thirty beta measures while flipping the expected input orientation to samples-as-rows. Subsequent releases have been spent settling the normalisation interface that expansion exposed.
This is a package that made its breaking changes deliberately and in a cluster. After 2.0.0 reoriented input and removed the weighted parameter, 2.1.0 superseded rescale with norm, and 2.2.6 changed norm's default from percent to none and removed it from some beta functions entirely. That last one matters more than it reads: normalisation defaults silently change the numbers a metric returns, and the direction is toward making the user state their choice rather than inheriting one.
With the metric surface broad and the normalisation interface now explicit, expect the next releases to stabilise — documentation and edge-case handling around CLR and rarefaction rather than another interface break.
invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.
The pressure is toward being installable and auditable rather than more capable — install slimmed from roughly 100 MB to 56 MB, R CMD check warnings and notes resolved, sp moved to Suggests, a Darwin Core-aligned data dictionary added, and a Zenodo concept DOI with CITATION.cff, codemeta.json and .zenodo.json. The package moves in lockstep with its B-Cubed sibling dissmapr, tagged within minutes of each other at both 0.1.0 and 0.2.1, which points at project-level standards deadlines rather than independent release decisions. Trait dispersion metrics and scenario exploration remain on the roadmap.
Standards compliance is now complete and the roadmap names functional trait dispersion metrics and scenario exploration tools, so the next release is the first that can plausibly be about invasion ecology rather than packaging.
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 ecodive or invasimapr.
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
State-space data simulation for R, filled in one function at a time
rollama turns a local-LLM wrapper into an instrument for reproducible annotation
See all ecodive alternatives → · See all invasimapr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ecodive and invasimapr 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. ecodive and invasimapr 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 ecodive alternatives in Analytics are ranked by recent ship velocity. Browse the "ecodive alternatives" section above for the current picks, or visit /alternatives/ecodive for the full list with editorial commentary on each.
Top invasimapr alternatives in Analytics are ranked by recent ship velocity. Browse the "invasimapr alternatives" section above for the current picks, or visit /alternatives/invasimapr for the full list with editorial commentary on each.