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Comparison · Infra & APIs

ggpointless vs inlabru

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

ggpointless vs inlabru: at a glance

Featureggpointlessinlabru
SectorInfra & APIsInfra & APIs
Velocity score0.02.5
Sparks · 30d00
Top themesggplot2-extensions, data-visualization, pictogram-charts, alpha-gradientsbayesian-modelling, spatial-statistics, r-package, api-consolidation
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is ggpointless?

ggpointless keeps adding the ggplot2 layers nobody else bothered to write.

ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.

Read the full ggpointless trajectory →

What is inlabru?

A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time

inlabru wraps INLA for spatial, point-process and latent-Gaussian models in R. It is mid-modernisation: since 2.12.0 cut the sp stack, each release has renamed part of the public surface, standardised how external packages attach custom mappers, or replaced internal machinery. 2.15.0 is the latest step, pairing a new predictor evaluation and linearisation implementation with broom's tidy(), glance() and augment() methods and four non-zero-truncated observation families.

Read the full inlabru trajectory →

ggpointless vs inlabru: editorial side-by-side

G
ggpointless
INFRA · APIS
0.0

ggpointless keeps adding the ggplot2 layers nobody else bothered to write.

◆ Current state

ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.

◆ Where it's heading

Two patterns are visible. Ideas get generalized rather than left as one-offs: geom_area_fade() in the previous release established alpha gradients via grid::linearGradient(), and the recent release spreads that treatment across paths, lines, steps, segments, curves and the three reference-line geoms, each with the same fade_direction and alpha_fade_to arguments. And each new geom is expected to survive real plots — the unit charts work under coord_equal, coord_polar, coord_radial, coord_flip and faceting, and geom_gridline reads positions from trained scales and inherits styling from the theme's panel grid. The package also tracks ggplot2 closely, requiring 4.0.0 and using make_constructor() and gg_par() internally, and it dropped its bundled datasets outright rather than maintain stale copies.

◆ Prediction

The fade treatment now covers most path-like geoms but not the area and ribbon family beyond geom_area_fade(), which is where the pattern has room left to run. The unit-cell charts arrive with a label helper and no fill or grouping variants, so those are the plausible next additions.

I
inlabru
INFRA · APIS
2.5

A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time

◆ Current state

inlabru wraps INLA for spatial, point-process and latent-Gaussian models in R. It is mid-modernisation: since 2.12.0 cut the sp stack, each release has renamed part of the public surface, standardised how external packages attach custom mappers, or replaced internal machinery. 2.15.0 is the latest step, pairing a new predictor evaluation and linearisation implementation with broom's tidy(), glance() and augment() methods and four non-zero-truncated observation families.

◆ Where it's heading

The arc is consolidation of the extension surface rather than expansion of the model catalogue. Every release adds mappers or families with one hand and removes a dependency, a re-export or a deprecated path with the other — plyr in 2.15.0, fmesher's Depends entry in 2.14.1, sp and ggmap in 2.12.0. The compatibility flag bru_compat_pre_2_14_enable and the temporary fm_int/fm_pixels re-exports show a maintainer sequencing breaks across releases instead of landing them together.

◆ Prediction

The 2.14 compatibility flag is still defaulting to TRUE and the fmesher re-exports are described in the entries as temporary, so the next obvious move is a release that flips bru_compat_pre_2_14_enable off and drops those re-exports.

Alternatives to ggpointless and inlabru

Other Infra & APIs 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 ggpointless or inlabru.

See all ggpointless alternatives → · See all inlabru alternatives →

Recent activity from ggpointless and inlabru

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

  1. 23d agoinlabruPredictor linearisation rewritten; broom tidiers, truncated families
  2. 3mo agoggpointlessPictogram unit charts, gridline layers and a family of fading geoms
  3. 3mo agoinlabruBugfix release: factor contrasts, raster extraction, error classes
  4. 5mo agoinlabruNew mappers, standardised cgeneric support, bru_obs storage refactor
  5. 5mo agoggpointlessFourier and arch geoms, area fades and glowing points
  6. 1y agoinlabruMapper classes shortened to bm_*, experimental predictor aggregation
  7. 1y agoinlabruDrops sp and ggmap for an sf-native spatial stack
  8. 2y agoggpointlessgeom_catenary() draws a hanging chain
  9. 3y agoggpointlessgeom_chaikin() adds corner-cutting path smoothing
  10. 4y agoggpointlessgeom_lexis() and the female_leaders dataset

Frequently asked questions

What is the difference between ggpointless and inlabru?

They serve adjacent needs but don't currently overlap on shipped themes. inlabru 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 ggpointless better than inlabru?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. inlabru 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to ggpointless?

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

What are the best alternatives to inlabru?

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