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Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
kde1d vs palettecore
A side-by-side editorial comparison of kde1d and palettecore — release velocity, themes, recent moves, and the top alternatives to consider.
kde1d vs palettecore: at a glance
What is kde1d?
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.
What is palettecore?
Accessible palettes generated from one seed, with every audit number computed on the hex you actually get
palettecore generates sequential, diverging and categorical colour palettes from a single seed using CIEDE2000 arc-length spacing in OKLCH, and audits each one for colour-vision-deficiency separation, greyscale survival, gamut and WCAG contrast. It exists as a numpy-only Python core and an R mirror validated hex-exact against shared parity fixtures, plus a CLI the project describes as its agent-friendly entry point. Four releases landed inside 24 hours in late July.
kde1d vs palettecore: editorial side-by-side
kde1d
0.0ANALYTICS
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
palettecore
6.3ANALYTICS
Accessible palettes generated from one seed, with every audit number computed on the hex you actually get
◆ Current state
palettecore generates sequential, diverging and categorical colour palettes from a single seed using CIEDE2000 arc-length spacing in OKLCH, and audits each one for colour-vision-deficiency separation, greyscale survival, gamut and WCAG contrast. It exists as a numpy-only Python core and an R mirror validated hex-exact against shared parity fixtures, plus a CLI the project describes as its agent-friendly entry point. Four releases landed inside 24 hours in late July.
◆ Where it's heading
The arc is about making the audit honest rather than making the palettes prettier. The 0.2.2 release, prompted by an external review, moved every diagnostic to compute on the 8-bit quantised hex codes actually returned rather than on internal floats — a change that flips results near thresholds and had been quietly overstating one deuteranopia score. The 0.4.0 helix kind and the vividness control extend the generator, but the same release also tightens its own claims, reframing helix as checked rather than assumed CVD-safe.
◆ Prediction
Given the pattern of auditing its own assertions, expect the next release to extend the cvd_luminance_monotonic diagnostic beyond helix to the other palette kinds.
Alternatives to kde1d and palettecore
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 kde1d or palettecore.
ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
gghighlight
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
rtrek
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
eiaapi
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
See all kde1d alternatives → · See all palettecore alternatives →
Recent activity from kde1d and palettecore
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 24d agopalettecorepalettecore 0.4.0
- 24d agopalettecorepalettecore 0.2.2
- 25d agopalettecorepalettecore 0.2.1
- 25d agopalettecorepalettecore 0.2.0 ⚡
- 1y agokde1dkde1d 1.1.1
- 1y agokde1dZero-inflated mixtures and a new standalone C++ API ⚡
- 4y agokde1dBit-wise Boolean operations removed
- 5y agokde1ddkde1d() invisible output fixed
- 5y agokde1dValgrind false positive silenced
- 6y agokde1dqrng dependency dropped; undefined behaviour fixed
Frequently asked questions
What is the difference between kde1d and palettecore?
They serve adjacent needs but don't currently overlap on shipped themes. palettecore is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is kde1d better than palettecore?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. palettecore is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to kde1d?
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.
What are the best alternatives to palettecore?
Top palettecore alternatives in Analytics are ranked by recent ship velocity. Browse the "palettecore alternatives" section above for the current picks, or visit /alternatives/palettecore for the full list with editorial commentary on each.