simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of ggquiver and kde1d — release velocity, themes, recent moves, and the top alternatives to consider.
ggquiver returned after four years to make arrows respect ggplot's own scales.
A small ggplot2 extension for quiver and vector-field plots. The 0.3.x line in late 2021 was about making arrows behave correctly outside plain Cartesian coordinates — non-Cartesian coordinate systems, ggmap backgrounds, arrow sizing and angles. Then nothing for over four years, until 0.4.0 made arrows honour scale transformations on the x and y aesthetics and exposed grid::arrow()'s appearance options.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.
A small ggplot2 extension for quiver and vector-field plots. The 0.3.x line in late 2021 was about making arrows behave correctly outside plain Cartesian coordinates — non-Cartesian coordinate systems, ggmap backgrounds, arrow sizing and angles. Then nothing for over four years, until 0.4.0 made arrows honour scale transformations on the x and y aesthetics and exposed grid::arrow()'s appearance options.
The consistent theme across both eras is deferring to ggplot2 rather than drawing on top of it: coordinate systems first, then scale transformations, then arrow styling handed to grid. Development is episodic — years pass, then a release that closes the gap between what the geom does and what a user expects from any other layer. The changelog is entirely correctness and integration work; there is no sign of the package growing new plot types.
The entries only support a narrow read: further releases will likely keep closing ggplot2 integration gaps as they are reported, but the four-year gap means cadence is not predictable from this feed.
kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.
The package has alternated between performance work and widening the class of data it accepts. The 1.0.0 release was the performance milestone — FFT-based estimation, a better integration algorithm for the p, q and r functions, deterministic jittering replacing randomness, and standalone C++ headers. The 1.1.0 release is the scope milestone, adding a third data type to the two it already handled. Releases come from the same maintainer as svines and cluster on shared dates, so changes in the underlying C++ surface across the vine and density stack tend to ship together.
With the C++ API deliberately reworked for standalone use at 1.1.0, further work most plausibly consolidates that interface rather than adding data types. What 1.1.1 actually changed is not readable from its body.
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 ggquiver or kde1d.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
See all ggquiver alternatives → · See all kde1d alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ggquiver and kde1d 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. ggquiver and kde1d 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.
Top ggquiver alternatives in Analytics are ranked by recent ship velocity. Browse the "ggquiver alternatives" section above for the current picks, or visit /alternatives/ggquiver for the full list with editorial commentary on each.
Top kde1d alternatives in Analytics are ranked by recent ship velocity. Browse the "kde1d alternatives" section above for the current picks, or visit /alternatives/kde1d for the full list with editorial commentary on each.