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collapse vs spatstat.geom

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

Shared themes:r-package

collapse vs spatstat.geom: at a glance

Featurecollapsespatstat.geom
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticsspatial-statistics, computational-geometry, r-package, three-dimensional
Last editorial update1h ago5h ago
WebsiteVisit →Visit →

What is collapse?

collapse got a JSS paper and a 7x fmean speedup in the same release.

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

Read the full collapse trajectory →

What is spatstat.geom?

The geometry layer under spatstat, steadily absorbing 3D patterns and missing-data semantics

spatstat.geom holds the spatial data structures and geometric operations the rest of the spatstat family builds on — windows, tessellations, images, point patterns and the operations that move between them. Recent releases split their attention between extending those structures to three dimensions and hardening the discretisation code where polygonal geometry meets a pixel grid. 3.8-2 adds more capabilities for three-dimensional point patterns.

Read the full spatstat.geom trajectory →

collapse vs spatstat.geom: editorial side-by-side

C
collapse
ANALYTICS
0.0

collapse got a JSS paper and a 7x fmean speedup in the same release.

◆ Current state

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

◆ Where it's heading

The package is consolidating institutionally as much as technically. The repository moved to the fastverse organization with multiple people granted access, the Journal of Statistical Software paper landed as the primary citation, and documentation now includes an AI-generated interactive layer. Technically the focus is the hashing and grouping core — the decision to treat -0 and 0 as equal across funique(), group(), fmatch(), fmode() and their derivatives was made in sync with an equivalent change in Rcpp, and accepted a measured 3% cost to get it. The last release with breaking changes sits outside this six-entry window.

◆ Prediction

Expect further targeted performance work on the grouped statistical functions and continued small correctness fixes; the governance move to fastverse suggests contribution volume rather than direction is what the maintainer is managing.

S
spatstat.geom
ANALYTICS
2.5

The geometry layer under spatstat, steadily absorbing 3D patterns and missing-data semantics

◆ Current state

spatstat.geom holds the spatial data structures and geometric operations the rest of the spatstat family builds on — windows, tessellations, images, point patterns and the operations that move between them. Recent releases split their attention between extending those structures to three dimensions and hardening the discretisation code where polygonal geometry meets a pixel grid. 3.8-2 adds more capabilities for three-dimensional point patterns.

◆ Where it's heading

Two threads run through this window. The first is a family-wide push into 3D that originated in the simulation package and has now reached the geometry layer. The second is a slower semantic change: 3.5-0 introduced missing or unavailable (NA) spatial objects, and 3.6-0 followed with more facilities for handling them, meaning an absent window or image became a representable value rather than an error. Around both, the plotting and discretisation code accretes steadily — nonlinear colour maps, plot backgrounds, transparency control, signed distance transforms, and repeated attention to boundary pixels.

◆ Prediction

Expect the 3D surface here to keep filling in behind the simulation package rather than leading it, given that 3.8-2 follows the 3D simulation release by two months. The entries give no indication that the NA work is finished, since it has already spanned two releases.

Alternatives to collapse and spatstat.geom

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 collapse or spatstat.geom.

See all collapse alternatives → · See all spatstat.geom alternatives →

Recent activity from collapse and spatstat.geom

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

  1. 20d agospatstat.geomMore three-dimensional point pattern capabilities
  2. 2mo agospatstat.geomBetter boundary pixel handling when discretising windows
  3. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  4. 6mo agospatstat.geomAnalytic level sets and signed distance transforms
  5. 7mo agocollapseNegative zero now hashes equal to zero across the package
  6. 8mo agocollapsecollap() no longer double-aggregates external weights
  7. 9mo agocollapseCustom unlist() preserves attributes
  8. 10mo agospatstat.geomNA object handling extended; clickpoly gains grid snapping
  9. 0y agocollapseAssorted bug fixes
  10. 1y agospatstat.geomNA spatial objects, hole removal and connected components
  11. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
  12. 1y agospatstat.geomNonlinear colour and symbol maps; half-open quadrat tiles

Frequently asked questions

What is the difference between collapse and spatstat.geom?

Both compete on the same themes — r-package — within Analytics. spatstat.geom is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is collapse better than spatstat.geom?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. spatstat.geom is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to collapse?

Top collapse alternatives in Analytics are ranked by recent ship velocity. Browse the "collapse alternatives" section above for the current picks, or visit /alternatives/collapse-r for the full list with editorial commentary on each.

What are the best alternatives to spatstat.geom?

Top spatstat.geom alternatives in Analytics are ranked by recent ship velocity. Browse the "spatstat.geom alternatives" section above for the current picks, or visit /alternatives/spatstat-geom for the full list with editorial commentary on each.