fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of dissmapr and tEDM — release velocity, themes, recent moves, and the top alternatives to consider.
dissmapr spent its first releases becoming citable rather than adding methods.
dissmapr provides an R workflow for compositional dissimilarity and turnover — occurrence data through spatial gridding and environmental linkage to order-wise dissimilarity and bioregional mapping. All three releases to date are infrastructure: a first citable archive in June 2026, then a maturity release aligning the package with the B-Cubed software development guide. The ten-function pipeline described in the notes has not changed across them.
The temporal half of the stscl EDM pair, tracking its spatial sibling
tEDM applies empirical dynamic modeling to time series — cross mapping, convergent cross mapping and the logistic map — as the temporal counterpart to spEDM, with which it shares a maintainer and a C++ core. The recent releases are consolidation rather than expansion: index handling in cross mapping corrected, generics taught to accept varying E, k and tau, and the associated paper now cited in the README. Only three releases are visible in the feed.
dissmapr provides an R workflow for compositional dissimilarity and turnover — occurrence data through spatial gridding and environmental linkage to order-wise dissimilarity and bioregional mapping. All three releases to date are infrastructure: a first citable archive in June 2026, then a maturity release aligning the package with the B-Cubed software development guide. The ten-function pipeline described in the notes has not changed across them.
The work is compliance-shaped rather than method-shaped: explicit @importFrom in place of whole-namespace imports, library() calls removed from package code, roughly 11 MB of development caches dropped, a runnable README quick-start, and Zenodo archival with CITATION.cff and codemeta.json. dissmapr moves in lockstep with its B-Cubed sibling invasimapr — both tagged 0.1.0 within three minutes of each other and 0.2.0 on the same day — so releases here reflect project-wide standards deadlines more than package-specific work. The stated roadmap of additional ecological distance metrics has not yet landed.
With standards work now signed off and R CMD check clean, the next release is the first real chance for the roadmap items — additional ecological distance metrics — to arrive.
tEDM applies empirical dynamic modeling to time series — cross mapping, convergent cross mapping and the logistic map — as the temporal counterpart to spEDM, with which it shares a maintainer and a C++ core. The recent releases are consolidation rather than expansion: index handling in cross mapping corrected, generics taught to accept varying E, k and tau, and the associated paper now cited in the README. Only three releases are visible in the feed.
tEDM moves in lockstep with spEDM. Configurable distance metrics, varying E/k/tau inputs, strict floating-point comparison and the S3 plotting font unification all appear in both packages within days or weeks, as does the maintainer surname correction. The recent balance has tilted toward correcting library and prediction index handling — the kind of repeated attention that suggests the indexing model was the weak point of the shared core.
Expect tEDM to keep inheriting the shared-core changes spEDM lands, with its own releases staying small and centred on cross-mapping parameter handling rather than new method surface.
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 dissmapr or tEDM.
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 dissmapr alternatives → · See all tEDM alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. dissmapr and tEDM 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. dissmapr and tEDM 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 dissmapr alternatives in Analytics are ranked by recent ship velocity. Browse the "dissmapr alternatives" section above for the current picks, or visit /alternatives/dissmapr for the full list with editorial commentary on each.
Top tEDM alternatives in Analytics are ranked by recent ship velocity. Browse the "tEDM alternatives" section above for the current picks, or visit /alternatives/tedm for the full list with editorial commentary on each.