bittermelon
bittermelon is growing from binary bitmaps toward greyscale and color glyphs
Comparison · Analytics
gridpattern vs weird
A side-by-side editorial comparison of gridpattern and weird — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:data-visualization
gridpattern vs weird: at a glance
What is gridpattern?
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
An R package supplying pattern fills for grid graphics — stripes, weaves, polygon tilings, images and placeholders. Releases are infrequent and irregular, roughly one or two a year with an eighteen-month gap before the most recent. The work divides between adding pattern types and making the existing ones behave consistently, particularly around units and how spacing parameters are interpreted.
What is weird?
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
gridpattern vs weird: editorial side-by-side
gridpattern
0.0ANALYTICS
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
◆ Current state
An R package supplying pattern fills for grid graphics — stripes, weaves, polygon tilings, images and placeholders. Releases are infrequent and irregular, roughly one or two a year with an eighteen-month gap before the most recent. The work divides between adding pattern types and making the existing ones behave consistently, particularly around units and how spacing parameters are interpreted.
◆ Where it's heading
Two long-running efforts are visible. The first is unit consistency: v1.2.1 gave the geometry patterns a units parameter, v1.2.2 extended it to weave and fixed polygon tiling to respect it — the slow propagation of one design decision through a family of functions. The second is integration with R's own graphics capabilities, which reaches its clearest expression in v1.4.2's line pattern: rather than filling bands with solid colour as stripe does, it draws stroked lines through the device, so every built-in linetype including dotdash, twodash and custom hex specifications works. The package is also visibly maintaining its external dependencies, having rotated placeholder image services as hosts disappeared.
◆ Prediction
Expect further pattern types and continued propagation of the units parameter to any function still missing it; the entries give no indication of a change in the package's scope beyond pattern fills.
weird
0.0ANALYTICS
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
◆ Current state
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
◆ Where it's heading
The refactor onto a shared distribution representation is the decision everything else follows from. It let 2.1.0 add hdr() and parameters() methods for kde objects rather than bespoke accessors, and it let 3.0.0 bring in dist_mclust() to turn a Gaussian mixture model into the same object type — so a mixture, a kernel density estimate and a fitted distribution all flow through one interface. The 3.0.0 additions lean visual and multivariate: outlier maps plotting score distance against orthogonal distance, biplot projections with variable axes overlaid, and an augment() method for robust PCA objects. Dependencies have been shed steadily along the way — lookout, interpolation — while mvscale() moved out and then back in.
◆ Prediction
Expect surprisals() coverage to keep extending to further model classes, and the multivariate and robust-PCA diagnostics introduced in 3.0.0 to gain the same distributional-object treatment as the univariate side.
Alternatives to gridpattern and weird
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 gridpattern or weird.
epiworldR
epiworldR is a thin R shell whose releases track the C++ simulator underneath it
watina
A groundwater database client that has started doing the domain analysis too
inbospatial
A thin R wrapper over Flemish geospatial services, adding one standard at a time
Fluent Bit
Fluent Bit keeps two lines alive while the 5.x branch quietly opens 5.1.
OpenCTI
OpenCTI is rebuilding its connector layer into a marketplace and wiring the platform to XTM Hub
See all gridpattern alternatives → · See all weird alternatives →
Recent activity from gridpattern and weird
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoweirdOutlier maps, biplot projections, and Gaussian mixtures as distributional objects
- 1mo agogridpatternHatch and line patterns added; wave gains ten new types
- 3mo agoweirdsurprisals() reaches glm objects; lookout dependency dropped
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 1y agogridpatternaRtsy generative patterns available as fills
- 2y agogridpatternunits parameter reaches weave; polygon tiling honours it
- 2y agogridpatternpatternFill() returns a grid pattern object; patterns can nest
- 2y agoweirdWine reviews dataset replaced with a fetch function
- 2y agogridpatternText pattern example skipped on devices lacking the glyphs
- 2y agogridpatternreset_image_cache() added; R 4.1 feature detection offered standalone
Frequently asked questions
What is the difference between gridpattern and weird?
Both compete on the same themes — data-visualization — within Analytics. gridpattern and weird 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 gridpattern better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gridpattern and weird 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 gridpattern?
Top gridpattern alternatives in Analytics are ranked by recent ship velocity. Browse the "gridpattern alternatives" section above for the current picks, or visit /alternatives/gridpattern-r for the full list with editorial commentary on each.
What are the best alternatives to weird?
Top weird alternatives in Analytics are ranked by recent ship velocity. Browse the "weird alternatives" section above for the current picks, or visit /alternatives/weird-r for the full list with editorial commentary on each.