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Comparison · Analytics
bittermelon vs weird
A side-by-side editorial comparison of bittermelon and weird — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
bittermelon vs weird: at a glance
What is bittermelon?
bittermelon is growing from binary bitmaps toward greyscale and color glyphs
The package manipulates bitmap fonts and bitmaps in R, and the recent direction is widening what a glyph can be. v2.3.1 adds greyscale font support by reading the experimental yaff levels property into pixmap glyphs with alpha derived from the level fraction, and makes writing a multi-colored glyph an error rather than silently clamping it. Earlier releases built out the same surface: bm_extract(), an interactive pixel picker, data frame coercion, and format support for other packages' bitmap types.
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.
bittermelon vs weird: editorial side-by-side
bittermelon
0.0ANALYTICS
bittermelon is growing from binary bitmaps toward greyscale and color glyphs
◆ Current state
The package manipulates bitmap fonts and bitmaps in R, and the recent direction is widening what a glyph can be. v2.3.1 adds greyscale font support by reading the experimental yaff levels property into pixmap glyphs with alpha derived from the level fraction, and makes writing a multi-colored glyph an error rather than silently clamping it. Earlier releases built out the same surface: bm_extract(), an interactive pixel picker, data frame coercion, and format support for other packages' bitmap types.
◆ Where it's heading
Two things are converging. The representation is moving beyond one-bit glyphs — pixmaps, color, and now greyscale levels with transparency — while the API gets stricter about the boundary between them, refusing to quietly downcast a color glyph on write. Separately, the package has been shedding weight: the embedded monobit copy was removed once it outgrew CRAN size limits, pushing format breadth onto a user-installed dependency.
◆ Prediction
Expect further greyscale and color work now that levels parsing exists — most likely writing that format rather than only reading it, since the write path is where the current release chose to draw a hard error instead.
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 bittermelon 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 bittermelon or weird.
tidytransit
tidytransit tracks the GTFS spec as it grows, one reader and one router feature at a time.
oblicubes
A tiny grid renderer for oblique-projection cubes, complete since its first release.
biocro
BioCro swapped an unstable iteration for real root finders, changing what its crop models compute.
redist
redist keeps rewriting the sampler underneath a district-drawing API it has held stable since 4.0.
epiflows
epiflows has shipped four releases in eight years, none of which changed the code.
See all bittermelon alternatives → · See all weird alternatives →
Recent activity from bittermelon 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
- 4mo agobittermelonGreyscale font reading arrives; color glyphs no longer clamp silently
- 6mo agobittermelonBitmap extraction and a supported-format predicate
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 1y agobittermelonData frame coercion and an interactive pixel picker
- 2y agobittermelonEmbedded monobit removed; broader format support now needs a manual install
- 2y agoweirdWine reviews dataset replaced with a fetch function
- 2y agobittermelonCombining-character test fixed after a Unicode package change
- 3y agobittermelonHex fonts can be read selectively by code point
Frequently asked questions
What is the difference between bittermelon and weird?
Both compete on the same themes — r-package — within Analytics. bittermelon 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 bittermelon better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bittermelon 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 bittermelon?
Top bittermelon alternatives in Analytics are ranked by recent ship velocity. Browse the "bittermelon alternatives" section above for the current picks, or visit /alternatives/bittermelon-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.