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The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of gtfstools and spatstat.geom — release velocity, themes, recent moves, and the top alternatives to consider.
gtfstools stopped guarding its own object model and started accepting everyone else's.
gtfstools reads, edits, filters and validates GTFS public transport feeds in R on a data.table backend. Since 1.3.0 it accepts GTFS objects produced by other packages such as gtfsio and tidytransit, converting them through an as_dt_gtfs() generic. Validation runs MobilityData's canonical validator, now supported through v6.0.0.
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.
gtfstools reads, edits, filters and validates GTFS public transport feeds in R on a data.table backend. Since 1.3.0 it accepts GTFS objects produced by other packages such as gtfsio and tidytransit, converting them through an as_dt_gtfs() generic. Validation runs MobilityData's canonical validator, now supported through v6.0.0.
The package built out a wide function surface first — filters, geometry conversion, speed and duration calculations — then turned outward. Delegating validation to MobilityData's validator and accepting other packages' objects both trade self-sufficiency for a position inside the wider GTFS ecosystem. Deprecations are handled slowly, with old behaviour left as the default for a release or more.
Expect continued validator version tracking and further completion of the deprecation cycle around filter_by_stop_id()'s full_trips behaviour.
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.
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.
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.
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 gtfstools or spatstat.geom.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
The R client for AusTraits spends its releases chasing the dataset it reads.
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
A fossil-record simulator that quietly grew a trait-evolution engine.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
See all gtfstools alternatives → · See all spatstat.geom alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
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.
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.
Top gtfstools alternatives in Analytics are ranked by recent ship velocity. Browse the "gtfstools alternatives" section above for the current picks, or visit /alternatives/gtfstools-r for the full list with editorial commentary on each.
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.