pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
A side-by-side editorial comparison of ggpointless and TrendLSW — release velocity, themes, recent moves, and the top alternatives to consider.
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.
Wavelet trend estimation tightens the defaults it shipped with.
TrendLSW estimates trend and evolutionary wavelet spectrum for locally stationary time series through a single TLSW() entry point. Its history since the first CRAN appearance is short and centres on defaults and plotting around that function, plus one dataset addition. The latest entry carries both the 1.0.4 and 1.0.3 notes in one body.
ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.
Two patterns are visible. Ideas get generalized rather than left as one-offs: geom_area_fade() in the previous release established alpha gradients via grid::linearGradient(), and the recent release spreads that treatment across paths, lines, steps, segments, curves and the three reference-line geoms, each with the same fade_direction and alpha_fade_to arguments. And each new geom is expected to survive real plots — the unit charts work under coord_equal, coord_polar, coord_radial, coord_flip and faceting, and geom_gridline reads positions from trained scales and inherits styling from the theme's panel grid. The package also tracks ggplot2 closely, requiring 4.0.0 and using make_constructor() and gg_par() internally, and it dropped its bundled datasets outright rather than maintain stale copies.
The fade treatment now covers most path-like geoms but not the area and ribbon family beyond geom_area_fade(), which is where the pattern has room left to run. The unit-cell charts arrive with a label helper and no fill or grouping variants, so those are the plausible next additions.
TrendLSW estimates trend and evolutionary wavelet spectrum for locally stationary time series through a single TLSW() entry point. Its history since the first CRAN appearance is short and centres on defaults and plotting around that function, plus one dataset addition. The latest entry carries both the 1.0.4 and 1.0.3 notes in one body.
The package has moved from getting onto CRAN to correcting the choices it launched with: the spectrum filter defaults were swapped to their trend counterparts, the plot.CI switch was removed in favour of inferring it from what was actually computed, and an example was shrunk to fit check timings. This is consolidation around a stable API rather than expansion.
Further releases most likely continue tuning TLSW() defaults and plot behaviour; the entries show no work toward new estimators.
Other Infra & APIs 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 ggpointless or TrendLSW.
The protist reference database keeps widening past the rRNA gene it was built on.
Composable aligned layouts, rebuilt on S7 while ggplot2 4.0 lands underneath.
Conservation planning absorbs the literature's target-setting rules as code.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
An ecosystem model starts tracking carbon isotopes and land-use change.
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
See all ggpointless alternatives → · See all TrendLSW alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ggpointless and TrendLSW 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggpointless and TrendLSW 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 Infra & APIs products to evaluate alongside.
Top ggpointless alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggpointless alternatives" section above for the current picks, or visit /alternatives/ggpointless for the full list with editorial commentary on each.
Top TrendLSW alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "TrendLSW alternatives" section above for the current picks, or visit /alternatives/trendlsw for the full list with editorial commentary on each.