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r2dii.analysis vs tulpa

A side-by-side editorial comparison of r2dii.analysis and tulpa — release velocity, themes, recent moves, and the top alternatives to consider.

r2dii.analysis vs tulpa: at a glance

Featurer2dii.analysistulpa
SectorAnalyticsAnalytics
Velocity score0.07.5
Sparks · 30d02
Top themesclimate-finance, portfolio-alignment, pacta, scenario-analysisbayesian-inference, cran-release, r-packages, spatial-modeling
Last editorial update3d ago10h ago
WebsiteVisit →Visit →

What is r2dii.analysis?

The climate-alignment maths behind PACTA, now stable and maintained rather than reshaped

r2dii.analysis computes the target-setting side of PACTA: market-share and sectoral decarbonisation targets that measure a loan book or portfolio against climate scenarios. It sits downstream of the matched company data the sibling packages produce. The 0.5.0 release declared it lifecycle-stable and handed maintenance to a new lead, and releases since have been narrow corrections rather than new methods.

Read the full r2dii.analysis trajectory →

What is tulpa?

The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.

tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.

Read the full tulpa trajectory →

r2dii.analysis vs tulpa: editorial side-by-side

R0.0

The climate-alignment maths behind PACTA, now stable and maintained rather than reshaped

◆ Current state

r2dii.analysis computes the target-setting side of PACTA: market-share and sectoral decarbonisation targets that measure a loan book or portfolio against climate scenarios. It sits downstream of the matched company data the sibling packages produce. The 0.5.0 release declared it lifecycle-stable and handed maintenance to a new lead, and releases since have been narrow corrections rather than new methods.

◆ Where it's heading

The history is a package converging. Early releases churn the output contract of target_market_share() and target_sda() — which sectors appear, which years, how missing production is treated — and each change alters the numbers users get. The ald-to-abcd rename runs across several releases before completing, and by 0.5.0 the churn has stopped, with three older summarise functions soft-deprecated and the package marked stable. What remains is edge-case correctness in target coverage.

◆ Prediction

With the package marked stable and the terminology migration finished, the soft-deprecated summarise functions are the obvious next thing to remove outright.

T
tulpa
ANALYTICS
7.5

The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.

◆ Current state

tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.

◆ Where it's heading

Two moves in nine days point at the same destination: the generics conversion made tulpa extensible by downstream packages, and CRAN admission makes it installable by them. The current cadence — several tags a week, some existing only to record a measurement that produced no code change — does not survive CRAN's submission overhead, so the release rhythm has to slow whether or not the project intends it. The correctness work still clusters on the joint nested-Laplace driver, and 0.1.0 extends the same diagnostics habit with .NL_AXIS_SD_REASONS, a closed vocabulary for an outer axis whose grid does not contain its own posterior mode.

◆ Prediction

Expect tulpaObs to follow tulpa onto CRAN, since it is the consumer whose registrations the engine has spent this window unblocking, and expect the version line to move in larger, less frequent steps now that each one carries a submission.

Alternatives to r2dii.analysis and tulpa

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 r2dii.analysis or tulpa.

See all r2dii.analysis alternatives → · See all tulpa alternatives →

Recent activity from r2dii.analysis and tulpa

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

  1. 20h agotulpaFirst CRAN release: engine surface unchanged from 0.0.198
  2. 4d agotulpatulpa_re_aghq() exposes the mode/theta cross-Hessian
  3. 8d agotulpaDense batched joint path could silently drop a grid cell
  4. 8d agotulpaCalibration and goodness-of-fit entry points become S3 generics
  5. 9d agotulpaCUDA backend had two definitions; link order decided if it ran
  6. 9d agotulpaHyperparameter bounds now flag when they leave the node range
  7. 7mo agor2dii.analysisLow-carbon technology targets filled in for partial company coverage
  8. 1y agor2dii.analysisColumn definitions filled into the data dictionary
  9. 1y agor2dii.analysisPackage declared stable, three summarise functions soft-deprecated
  10. 2y agor2dii.analysisald argument removed for good in favour of abcd
  11. 2y agor2dii.analysisCompany-level SDA converges on the scenario's final year
  12. 3y agor2dii.analysisRepository moved to the RMI-PACTA organisation

Frequently asked questions

What is the difference between r2dii.analysis and tulpa?

They serve adjacent needs but don't currently overlap on shipped themes. tulpa is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 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 r2dii.analysis better than tulpa?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. tulpa is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 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 r2dii.analysis?

Top r2dii.analysis alternatives in Analytics are ranked by recent ship velocity. Browse the "r2dii.analysis alternatives" section above for the current picks, or visit /alternatives/r2dii-analysis for the full list with editorial commentary on each.

What are the best alternatives to tulpa?

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