rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
units vs weird
A side-by-side editorial comparison of units and weird — release velocity, themes, recent moves, and the top alternatives to consider.
units vs weird: at a glance
What is units?
units reaches 1.0 by rewriting its parser and accepting the breakage that comes with it.
units attaches physical units to R vectors on top of the udunits2 library, covering arithmetic, conversion and ggplot2 scales. Version 1.0-0 replaced the unit-expression tokenizer so numbers are consistently treated as prefixes, and expressions like ml/min/1.73m^2 now parse the way physiologists write them. Printing follows NIST conventions, and 1.0-1 is a fix pass over memory handling and parser edge cases.
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.
units vs weird: editorial side-by-side
units
0.0ANALYTICS
units reaches 1.0 by rewriting its parser and accepting the breakage that comes with it.
◆ Current state
units attaches physical units to R vectors on top of the udunits2 library, covering arithmetic, conversion and ggplot2 scales. Version 1.0-0 replaced the unit-expression tokenizer so numbers are consistently treated as prefixes, and expressions like ml/min/1.73m^2 now parse the way physiologists write them. Printing follows NIST conventions, and 1.0-1 is a fix pass over memory handling and parser edge cases.
◆ Where it's heading
The long 0.8-x run was accretion — ggplot2 scales absorbed from ggforce, ud_convert(), matrix methods, steady performance work — while known parsing defects stayed in place. The 1.0 release finally traded backwards compatibility for correct parsing, and 1.0-1's pointer-wrapping and exception-propagation work suggests the C++ glue is being hardened behind it. Fixes cluster at the udunits2 boundary, which remains the main source of surprises.
◆ Prediction
Expect continued patch releases against udunits2 quirks and the new tokenizer's fallout rather than new surface area, with the ggplot2 integration and conversion helpers already in place.
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 units 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 units or weird.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
Recent activity from units 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
- 5mo agounitsMemory-leak and udunits2 parsing fixes after 1.0
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 10mo agounitsNew tokenizer parses compound units correctly ⚡
- 1y agounitsCopy semantics fix in ud_convert(); C++17 for old R
- 1y agounitscbind/rbind methods, ud_convert() and broad fixes
- 1y agounitsSilences a CRAN compiler warning
- 2y agoweirdWine reviews dataset replaced with a fetch function
- 2y agounitsRestores simplify=FALSE for identical units
Frequently asked questions
What is the difference between units and weird?
They serve adjacent needs but don't currently overlap on shipped themes. units 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 units better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. units 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 units?
Top units alternatives in Analytics are ranked by recent ship velocity. Browse the "units alternatives" section above for the current picks, or visit /alternatives/units-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.