fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of ggmapinset and semmcci — release velocity, themes, recent moves, and the top alternatives to consider.
A ggplot2 inset-map extension that is now infrastructure for other packages
ggmapinset adds magnified inset panels to ggplot2 sf maps, handling the coordinate transformation, the inset frame and the sf-related stat layers that have to follow it. The 0.5.0 release is aimed less at end users than at extension authors: coerce_centre() is a new extension point required by sibling package ggautomap, and the inset parameter drops NA in favour of waiver() as its default. It comes from cidm-ph, alongside nswgeo.
Monte Carlo confidence intervals for SEM, now mostly reacting to upstream deprecations
semmcci generates Monte Carlo confidence intervals for structural equation model parameters, working alongside lavaan. Its four-year release history is a run of patch versions from the jeksterslab account, each adding a function or adjusting method detail. The recent ones are quieter still: the latest addresses a lavaan::getCov() deprecation in tests, and the one before it is described only as minor method edits.
ggmapinset adds magnified inset panels to ggplot2 sf maps, handling the coordinate transformation, the inset frame and the sf-related stat layers that have to follow it. The 0.5.0 release is aimed less at end users than at extension authors: coerce_centre() is a new extension point required by sibling package ggautomap, and the inset parameter drops NA in favour of waiver() as its default. It comes from cidm-ph, alongside nswgeo.
The package has moved steadily from feature to foundation. 0.3.0 replaced confusing parameter names and rebuilt everything on stat_sf_inset() so coordinate limits stayed correct, then exposed transform_to_inset() explicitly for extension developers. 0.4.0 generalised inset shapes beyond circles to rectangles and arbitrary sf geometries. 0.5.0 continues in that direction, changing defaults in ways that require downstream extensions to adapt — the cost of being depended upon.
Expect further extension points driven by what ggautomap and the other cidm-ph mapping packages need, with the user-facing inset API staying largely settled after the shape generalisation.
semmcci generates Monte Carlo confidence intervals for structural equation model parameters, working alongside lavaan. Its four-year release history is a run of patch versions from the jeksterslab account, each adding a function or adjusting method detail. The recent ones are quieter still: the latest addresses a lavaan::getCov() deprecation in tests, and the one before it is described only as minor method edits.
The functional build-out finished some time ago. MCGeneric() in 1.1.3 and Func()/MCFunc() in 1.1.4 opened the package to user-defined functions of parameters, which is the natural end point for a Monte Carlo interval tool — once arbitrary functions are supported, there is little left to add. Since then releases have tracked lavaan's changes rather than semmcci's own direction, and the gap between them has stretched from months to over a year.
Expect the next release to be triggered by another lavaan deprecation rather than by new capability.
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 ggmapinset or semmcci.
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 ggmapinset alternatives → · See all semmcci alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ggmapinset and semmcci 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. ggmapinset and semmcci 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 ggmapinset alternatives in Analytics are ranked by recent ship velocity. Browse the "ggmapinset alternatives" section above for the current picks, or visit /alternatives/ggmapinset for the full list with editorial commentary on each.
Top semmcci alternatives in Analytics are ranked by recent ship velocity. Browse the "semmcci alternatives" section above for the current picks, or visit /alternatives/semmcci for the full list with editorial commentary on each.