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ggguides vs tulpaRatio

A side-by-side editorial comparison of ggguides and tulpaRatio — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

ggguides vs tulpaRatio: at a glance

FeatureggguidestulpaRatio
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, legends, r-package, bugfix-trainbayesian-inference, hmc-nuts, spatial-statistics, performance
Last editorial update1h ago24m ago
WebsiteVisit →Visit →

What is ggguides?

Three releases in one day to make legend positioning finally do what the docs said.

ggguides is a helper layer over ggplot2's guide system, exposing legend placement and styling through small named functions instead of raw theme() calls. On 23 April 2026 it shipped 1.1.7, 1.1.8 and 1.1.9 within thirteen hours, each fixing a different path by which the justification argument silently did nothing. The common root cause is that ggplot2 3.5 split legend.justification into side-specific theme elements, and ggguides was still writing to the generic fallback.

Read the full ggguides trajectory →

What is tulpaRatio?

A Bayesian ratio-modelling package that threw out its Stan dependency and wrote its own sampler

ratiod models ratios, rates and proportions hierarchically, with the stated position that a ratio is a derived quantity and inference should run on the latent numerator and denominator processes rather than their quotient. The 1.0.0 release shipped a native HMC/NUTS backend, removing the Stan dependency that packages in this space normally take as given. Everything since has been sampler optimisation, benchmarked against the Stan implementations it replaced.

Read the full tulpaRatio trajectory →

ggguides vs tulpaRatio: editorial side-by-side

G
ggguides
ANALYTICS
0.0

Three releases in one day to make legend positioning finally do what the docs said.

◆ Current state

ggguides is a helper layer over ggplot2's guide system, exposing legend placement and styling through small named functions instead of raw theme() calls. On 23 April 2026 it shipped 1.1.7, 1.1.8 and 1.1.9 within thirteen hours, each fixing a different path by which the justification argument silently did nothing. The common root cause is that ggplot2 3.5 split legend.justification into side-specific theme elements, and ggguides was still writing to the generic fallback.

◆ Where it's heading

The package is in the phase where a wrapper meets the reality of the API it wraps. All three same-day releases are the same bug found in successive entry points: legend_inside(), then the four side functions, then legend_style(by = ). Along the way the fix work produced a real feature, a justification argument on the side legend functions. The pattern of a single reporter driving three consecutive releases suggests the surface is being audited rather than randomly patched.

◆ Prediction

Expect a consolidation release that audits the remaining theme elements ggguides writes to against ggplot2 3.5 semantics, rather than another single-path fix.

T
tulpaRatio
ANALYTICS
0.0

A Bayesian ratio-modelling package that threw out its Stan dependency and wrote its own sampler

◆ Current state

ratiod models ratios, rates and proportions hierarchically, with the stated position that a ratio is a derived quantity and inference should run on the latent numerator and denominator processes rather than their quotient. The 1.0.0 release shipped a native HMC/NUTS backend, removing the Stan dependency that packages in this space normally take as given. Everything since has been sampler optimisation, benchmarked against the Stan implementations it replaced.

◆ Where it's heading

The feed reads as one architectural bet followed by the work to justify it. After the native backend landed, the releases are a steady march of gradient and adaptation work — hand-coded gradients for more model families, L-BFGS mass matrix adaptation, an O2 build — each measured as a speed multiple against Stan. Coverage is tracked openly as a fraction (48 of 60 hand-coded configs), and unresolved problems are named rather than buried, including a deferred GP spatial bug.

◆ Prediction

The hand-coded gradient coverage count is the visible backlog, so the next releases most likely close the remaining configs and resolve the GP spatial issue that the benchmark release explicitly deferred.

Alternatives to ggguides and tulpaRatio

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 ggguides or tulpaRatio.

See all ggguides alternatives → · See all tulpaRatio alternatives →

Recent activity from ggguides and tulpaRatio

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 3mo agoggguideslegend_style(by=) justification now reaches the whole-plot theme
  2. 3mo agoggguidesSide legend functions gain justification and target the right theme element
  3. 3mo agoggguideslegend_inside() justification now moves the legend as documented
  4. 6mo agotulpaRatioHand-coded gradients reach binomial zero-inflated and hurdle models
  5. 6mo agotulpaRatioGaussian process sampling reaches roughly 4x Stan
  6. 7mo agotulpaRatioL-BFGS mass matrix adaptation for MSGP models
  7. 7mo agotulpaRatioBenchmarks published for 35 of 40 model configurations
  8. 7mo agotulpaRatioFirst stable release ships a native HMC/NUTS backend, no Stan required
  9. 8mo agoggguidesLegend reordering, key overrides and colorbar styling added

Frequently asked questions

What is the difference between ggguides and tulpaRatio?

Both compete on the same themes — r-package — within Analytics. ggguides and tulpaRatio 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 ggguides better than tulpaRatio?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggguides and tulpaRatio 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 ggguides?

Top ggguides alternatives in Analytics are ranked by recent ship velocity. Browse the "ggguides alternatives" section above for the current picks, or visit /alternatives/ggguides for the full list with editorial commentary on each.

What are the best alternatives to tulpaRatio?

Top tulpaRatio alternatives in Analytics are ranked by recent ship velocity. Browse the "tulpaRatio alternatives" section above for the current picks, or visit /alternatives/tulparatio for the full list with editorial commentary on each.