← Back to home
Comparison · Analytics

ggmapinset vs spEDM

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

ggmapinset vs spEDM: at a glance

FeatureggmapinsetspEDM
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, geospatial, inset-maps, extension-apicausal-inference, spatial-analysis, empirical-dynamic-modeling, r-package
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is ggmapinset?

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.

Read the full ggmapinset trajectory →

What is spEDM?

Spatial causal discovery in R, one exposed method per release

spEDM brings empirical dynamic modeling to spatial data — cross mapping, convergent cross mapping and pattern causality over spatial vector and raster inputs, with the numerics in C++ behind S4 generics. The recent releases have exposed geographical pattern causality and spatially convergent partial cross mapping at the R level with vignettes, and 1.12 turns to consolidating the API. It is part of the stscl family alongside the temporal-domain tEDM, with which it shares both its C++ core and its maintainer.

Read the full spEDM trajectory →

ggmapinset vs spEDM: editorial side-by-side

G
ggmapinset
ANALYTICS
0.0

A ggplot2 inset-map extension that is now infrastructure for other packages

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

S
spEDM
ANALYTICS
0.0

Spatial causal discovery in R, one exposed method per release

◆ Current state

spEDM brings empirical dynamic modeling to spatial data — cross mapping, convergent cross mapping and pattern causality over spatial vector and raster inputs, with the numerics in C++ behind S4 generics. The recent releases have exposed geographical pattern causality and spatially convergent partial cross mapping at the R level with vignettes, and 1.12 turns to consolidating the API. It is part of the stscl family alongside the temporal-domain tEDM, with which it shares both its C++ core and its maintainer.

◆ Where it's heading

The cadence is steady and predictable: each release surfaces one more EDM method as an R-level API with a vignette, then spends the rest of its notes on parameter-handling consistency across the generics. Breaking changes are frequent and deliberate — argument renames, parameter reordering, NA-handling defaults — which reads as a package still settling its interface while the method surface expands. Shared changes appear in tEDM within days, so interface churn lands on both packages at once.

◆ Prediction

Expect the next release to expose another causality variant at the R level with an accompanying vignette, and to continue renaming or reordering parameters toward consistency across the spatial and temporal packages.

Alternatives to ggmapinset and spEDM

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 spEDM.

See all ggmapinset alternatives → · See all spEDM alternatives →

Recent activity from ggmapinset and spEDM

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

  1. 4mo agospEDMData slicing for large-scale pattern causality, plus API breaks
  2. 4mo agoggmapinsetNew extension point for ggautomap; waiver() replaces NA
  3. 6mo agospEDMspEDM 1.11
  4. 6mo agospEDMSpatially convergent partial cross mapping reaches the R API
  5. 8mo agospEDMRaster cross mapping with anisotropic embedding
  6. 11mo agospEDMConfigurable distance metrics and multithreaded distance computation
  7. 1y agospEDMSpatial logistic map exposed at the R level
  8. 1y agoggmapinsetRectangular and arbitrary sf inset shapes
  9. 3y agoggmapinsetRebuilt on stat_sf_inset() with corrected coordinate limits

Frequently asked questions

What is the difference between ggmapinset and spEDM?

They serve adjacent needs but don't currently overlap on shipped themes. ggmapinset and spEDM 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 ggmapinset better than spEDM?

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

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.

What are the best alternatives to spEDM?

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