simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of lavaanExtra and palettecore — release velocity, themes, recent moves, and the top alternatives to consider.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
lavaanExtra provides shorthand syntax and formatted output around lavaan structural equation models - write_lavaan() to build model strings, and nice_* functions for fit tables, plots, and modification indices. Three of the six visible releases exist only to satisfy CRAN resubmission: a unicode problem, a dependency version check, tests running without suggested packages. The substance sits in 0.1.5, 0.1.8, and 0.1.9.
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.
lavaanExtra provides shorthand syntax and formatted output around lavaan structural equation models - write_lavaan() to build model strings, and nice_* functions for fit tables, plots, and modification indices. Three of the six visible releases exist only to satisfy CRAN resubmission: a unicode problem, a dependency version check, tests running without suggested packages. The substance sits in 0.1.5, 0.1.8, and 0.1.9.
The package generalises its own vocabulary as it goes: lavaan_ind() became lavaan_defined() once it turned out to extract any user-defined parameter, and lavaan_cov() was split so lavaan_cor() covers actual correlations. Methodological positions are taken alongside the API - dropping the estimate argument from lavaan_reg() to force reporting both standardized and unstandardized values, and updating the RMSEA benchmark to Schreiber (2017). Rémi Thériault maintains it next to rempsyc, which formats output to match. Note that 0.1.5 restates the whole 0.1.4.x development series in one body.
The pattern points to another nice_* helper aimed at a reporting step that currently needs hand formatting, arriving with the usual CRAN resubmission behind it.
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.
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.
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.
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 lavaanExtra or palettecore.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
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.
From a bundled hospital dataset to a live CMS API client.
See all lavaanExtra alternatives → · See all palettecore alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
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.
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.
Top lavaanExtra alternatives in Analytics are ranked by recent ship velocity. Browse the "lavaanExtra alternatives" section above for the current picks, or visit /alternatives/lavaanextra for the full list with editorial commentary on each.
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.