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gghighlight vs spEDM

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

Shared themes:r-package

gghighlight vs spEDM: at a glance

FeaturegghighlightspEDM
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, data-visualisation, ggplot-extension, upstream-compatcausal-inference, spatial-analysis, empirical-dynamic-modeling, r-package
Last editorial update1h ago4h ago
WebsiteVisit →Visit →

What is gghighlight?

A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.

gghighlight adds one verb to ggplot2: highlight the series matching a predicate and grey out the rest, with unhighlighted_params controlling how the shadowed layer renders and calculate_per_facet deciding whether the predicate evaluates within facets. The API settled at 0.2.0; the 0.5.0 release supports ggplot2 v4.0 including its ink and paper theme elements, and finally deletes gghighlight_point() and gghighlight_line().

Read the full gghighlight 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 →

gghighlight vs spEDM: editorial side-by-side

G
gghighlight
ANALYTICS
0.0

A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.

◆ Current state

gghighlight adds one verb to ggplot2: highlight the series matching a predicate and grey out the rest, with unhighlighted_params controlling how the shadowed layer renders and calculate_per_facet deciding whether the predicate evaluates within facets. The API settled at 0.2.0; the 0.5.0 release supports ggplot2 v4.0 including its ink and paper theme elements, and finally deletes gghighlight_point() and gghighlight_line().

◆ Where it's heading

Two threads run through the history. One is a slow deprecation, from soft-deprecating the geom-specific functions at 0.1.0, to defunct at 0.3.0, to removed at 0.5.0 — a five-year removal cycle. The other is compatibility work: purrr 1.0.0, dplyr's across() deprecation, ggplot2 3.4.0, then 4.0. Genuine feature additions are rare and small, with line_label_type at 0.4.0 the last one. Note that 0.3.2's notes restate 0.3.1's n() item, so adjacent tags here overlap rather than each describing distinct work.

◆ Prediction

The next release most likely absorbs further ggplot2 4.x changes, given that is what triggered the last three. Nothing in the entries points to a new highlighting capability.

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 gghighlight 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 gghighlight or spEDM.

See all gghighlight alternatives → · See all spEDM alternatives →

Recent activity from gghighlight 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. 6mo agospEDMspEDM 1.11
  3. 6mo agospEDMSpatially convergent partial cross mapping reaches the R API
  4. 8mo agospEDMRaster cross mapping with anisotropic embedding
  5. 11mo agospEDMConfigurable distance metrics and multithreaded distance computation
  6. 1y agospEDMSpatial logistic map exposed at the R level
  7. 1y agogghighlightggplot2 v4.0 support; geom-specific functions removed
  8. 2y agogghighlightTest expectations updated for upcoming ggplot2
  9. 3y agogghighlightline_label_type adds geomtextpath and second-axis labelling
  10. 4y agogghighlightDeprecated dplyr::across() usage removed
  11. 5y agogghighlightExplicit NULL in unhighlighted_params preserved; aesthetic name clash fixed
  12. 5y agogghighlightDiscrete-scale labels and n() predicates

Frequently asked questions

What is the difference between gghighlight and spEDM?

Both compete on the same themes — r-package — within Analytics. gghighlight 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 gghighlight better than spEDM?

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

Top gghighlight alternatives in Analytics are ranked by recent ship velocity. Browse the "gghighlight alternatives" section above for the current picks, or visit /alternatives/gghighlight 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.