rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
Comparison · Analytics
oblicubes vs weird
A side-by-side editorial comparison of oblicubes and weird — release velocity, themes, recent moves, and the top alternatives to consider.
oblicubes vs weird: at a glance
What is oblicubes?
A tiny grid renderer for oblique-projection cubes, complete since its first release.
oblicubes draws 3D cubes and cuboids in oblique projection as grid grobs, with ggplot2 geom wrappers and a height-matrix helper for turning elevation data into coordinates. The entire feature set arrived in the initial 0.1.2 release, adapted from coolbutuseless's isocubes and cj-holmes's isocuboids. The two releases since have widened compatibility rather than added anything.
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.
oblicubes vs weird: editorial side-by-side
oblicubes
0.0ANALYTICS
A tiny grid renderer for oblique-projection cubes, complete since its first release.
◆ Current state
oblicubes draws 3D cubes and cuboids in oblique projection as grid grobs, with ggplot2 geom wrappers and a height-matrix helper for turning elevation data into coordinates. The entire feature set arrived in the initial 0.1.2 release, adapted from coolbutuseless's isocubes and cj-holmes's isocuboids. The two releases since have widened compatibility rather than added anything.
◆ Where it's heading
The package is finished and its maintainer is treating it that way. 1.0.0 removed the R 4.1 native pipe from examples specifically so earlier R versions could use it — reaching backward, not forward — and added image alt text. The only change since is swapping a deprecated dplyr call in examples.
◆ Prediction
Expect nothing beyond occasional dependency deprecation fixes; the release pattern shows a small, deliberately complete package being kept installable.
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 oblicubes 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 oblicubes or weird.
epikit
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
SimInf
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
mutagen
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
broman
A statistician's personal toolbox, growing one plotting utility at a time
qtl
R/qtl is in pure custodial mode: every recent release answers a compiler, not a user
See all oblicubes alternatives → · See all weird alternatives →
Recent activity from oblicubes and weird
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoweirdOutlier maps, biplot projections, and Gaussian mixtures as distributional objects
- 3mo agoweirdsurprisals() reaches glm objects; lookout dependency dropped
- 6mo agooblicubesExamples updated to dplyr::reframe()
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 1y agooblicubesR 4.1 pipe removed from examples; image alt text added
- 2y agoweirdWine reviews dataset replaced with a fetch function
- 3y agooblicubesInitial release: oblique-projection cube and cuboid grobs
Frequently asked questions
What is the difference between oblicubes and weird?
They serve adjacent needs but don't currently overlap on shipped themes. oblicubes 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 oblicubes better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. oblicubes 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 oblicubes?
Top oblicubes alternatives in Analytics are ranked by recent ship velocity. Browse the "oblicubes alternatives" section above for the current picks, or visit /alternatives/oblicubes-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.