← Back to home
Comparison · Analytics

dissmapr vs sdsfun

A side-by-side editorial comparison of dissmapr and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.

dissmapr vs sdsfun: at a glance

Featuredissmaprsdsfun
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesbiodiversity, dissimilarity, bioregions, research softwarespatial-statistics, geodetector, spatial-clustering, rcpp
Last editorial update6h ago45m ago
WebsiteVisit →Visit →

What is dissmapr?

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.

Read the full dissmapr trajectory →

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.

Read the full sdsfun trajectory →

dissmapr vs sdsfun: editorial side-by-side

D
dissmapr
ANALYTICS
0.0

dissmapr spent its first releases becoming citable rather than adding methods.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

S
sdsfun
ANALYTICS
0.0

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 dissmapr 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 dissmapr or sdsfun.

See all dissmapr alternatives → · See all sdsfun alternatives →

Recent activity from dissmapr and sdsfun

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agodissmaprVersion bump; notes identical to 0.2.0
  2. 1mo agodissmaprB-Cubed standards alignment, docs overhaul and a citable DOI
  3. 1mo agodissmaprdissmapr v0.1.0: First citable release
  4. 10mo agosdsfunPackage load stops touching the RNG state
  5. 1y agosdsfunUnified partial correlation testing and head/tails discretization
  6. 1y agosdsfunMissing-value handling added to linear trend removal
  7. 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
  8. 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
  9. 1y agosdsfunFast geodetector q-value estimator added

Frequently asked questions

What is the difference between dissmapr and sdsfun?

They serve adjacent needs but don't currently overlap on shipped themes. dissmapr 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 dissmapr better than sdsfun?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dissmapr 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 dissmapr?

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.

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.