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Comparison · Analytics
bittermelon vs spmodel
A side-by-side editorial comparison of bittermelon and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
bittermelon vs spmodel: 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 spmodel?
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
bittermelon vs spmodel: 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.
spmodel
0.0ANALYTICS
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
◆ Current state
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
◆ Where it's heading
Two threads run in parallel. The first is expanding what can be predicted — point predictions, then areal averages over a region via block kriging, then better accuracy and efficiency for that path as the block size default moved from 1000 to 4000 in 0.12.0. The second is numerical trustworthiness, and it is unusually prominent here: a range-constraint option for stability in 0.9.0, a corrected log determinant of the fixed effects in the restricted log likelihood in 0.11.0, a cloud semivariogram that had been doubling the semivariance fixed in 0.11.1, and now a tighter optimiser tolerance. Several of these silently changed results before they were caught.
◆ Prediction
Expect the maintainers to keep publishing explicit reproduction instructions alongside numerical default changes, as 0.13.0 does by documenting the `control = list(reltol = 1e-4)` escape hatch. The entries give no signal of expansion beyond the current model families.
Alternatives to bittermelon and spmodel
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 spmodel.
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 spmodel alternatives →
Recent activity from bittermelon and spmodel
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agospmodelTighter optimiser tolerance to avoid local maxima
- 4mo agobittermelonGreyscale font reading arrives; color glyphs no longer clamp silently
- 6mo agobittermelonBitmap extraction and a supported-format predicate
- 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
- 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
- 1y agospmodelBlock kriging for areal averages and their uncertainty ⚡
- 1y agospmodelRobust semivariogram and new covariance types for areal models
- 1y agobittermelonData frame coercion and an interactive pixel picker
- 1y agospmodelRange constraint option and redefined covariance type names
- 2y agobittermelonEmbedded monobit removed; broader format support now needs a manual install
- 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 spmodel?
Both compete on the same themes — r-package — within Analytics. bittermelon and spmodel 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 spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bittermelon and spmodel 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 spmodel?
Top spmodel alternatives in Analytics are ranked by recent ship velocity. Browse the "spmodel alternatives" section above for the current picks, or visit /alternatives/spmodel for the full list with editorial commentary on each.