r2rtf
The clinical-report table engine learned Chinese, then learned to leave RTF entirely
Comparison · Analytics
forestly vs xplainfi
A side-by-side editorial comparison of forestly and xplainfi — release velocity, themes, recent moves, and the top alternatives to consider.
forestly vs xplainfi: at a glance
What is forestly?
forestly built an interactive safety review tool, then taught it to produce submission-ready RTF.
forestly renders adverse-event forest plots as interactive reactable widgets — filterable by AE category, with sliders for incidence thresholds and a toggle for the risk-difference column. Version 0.1.3 added `rtf_static_forestly()` for static RTF output, and 0.1.4 has been about giving the display owner control over what reviewers see: the CSV download button, the AE filter label, and the diff toggle can each be switched off.
What is xplainfi?
xplainfi treats feature importance as an estimate with error bars, not a number.
xplainfi implements feature importance methods for mlr3 — perturbation-based PFI, CFI and RFI, refit-based LOCO and WVIM, and SAGE. Its defining choice is that importance scores come with inference attached: several confidence-interval methods, including the Nadeau-Bengio correction and a distribution-free option added in 1.1.0. It declared itself released at 1.0.0 in January 2026.
forestly vs xplainfi: editorial side-by-side
forestly
0.0ANALYTICS
forestly built an interactive safety review tool, then taught it to produce submission-ready RTF.
◆ Current state
forestly renders adverse-event forest plots as interactive reactable widgets — filterable by AE category, with sliders for incidence thresholds and a toggle for the risk-difference column. Version 0.1.3 added `rtf_static_forestly()` for static RTF output, and 0.1.4 has been about giving the display owner control over what reviewers see: the CSV download button, the AE filter label, and the diff toggle can each be switched off.
◆ Where it's heading
The arc runs from a fixed interactive widget toward a configurable one with two output modes. Nearly every new argument in the last two releases exists to remove something from the display or relabel it, which suggests the users driving development are producing outputs for others to review under conventions they do not control. The x-axis range, column header, figure header and slider range arguments point the same way — this is a tool being fitted into standardised reporting rather than used ad hoc.
◆ Prediction
Given that the last two releases have consisted almost entirely of display-control arguments, the next is likely more of the same, applied to whichever parts of the interactive layout are still fixed.
xplainfi
2.5ANALYTICS
xplainfi treats feature importance as an estimate with error bars, not a number.
◆ Current state
xplainfi implements feature importance methods for mlr3 — perturbation-based PFI, CFI and RFI, refit-based LOCO and WVIM, and SAGE. Its defining choice is that importance scores come with inference attached: several confidence-interval methods, including the Nadeau-Bengio correction and a distribution-free option added in 1.1.0. It declared itself released at 1.0.0 in January 2026.
◆ Where it's heading
Two lines of work run in parallel. The statistical side keeps adding inference options — variance corrections, conditional predictive impact, and the Lei et al. observation-wise loss-difference test — while the computational side attacks the cost of refit-based methods, most recently with a batch_size argument that parallelises refits and a default of one refit per resampling iteration. Support for pre-trained learners in 1.1.0 removes the refit requirement entirely in some workflows.
◆ Prediction
The stated reasoning that budget is better spent on resampling iterations than repeated refits suggests n_repeats may be removed from WVIM and LOCO outright, as the release notes hint.
Alternatives to forestly and xplainfi
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 forestly or xplainfi.
DoseFinding
New stewardship at openpharma, then two releases adding the methods MCP-Mod was missing
webmockr
The stubbing library added httr2 support, then spent a year cutting itself free of everything else
crul
crul took mocking back from webmockr and made it a property of the client itself
dendroNetwork
Six releases, six identical bodies — the feed carries the package abstract instead of release notes
chattr
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
See all forestly alternatives → · See all xplainfi alternatives →
Recent activity from forestly and xplainfi
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 21d agoxplainfiRefits parallelise; repeated refits deprioritised in favour of resampling
- 5mo agoxplainfiPre-trained learners supported; distribution-free inference added
- 5mo agoforestlyDownload button, AE filter label and diff toggle become optional
- 6mo agoxplainfiVersion bumped to mark the package as released
- 9mo agoxplainfiConfidence intervals arrive for feature importance scores
- 11mo agoforestlyStatic RTF forest plots join the interactive output ⚡
- 1y agoforestlyreactR 0.6.0 rendering fix and slider label control
- 2y agoforestlyTreatment group selection and rough-edge fixes
- 3y agoforestlyFirst release on GitHub and CRAN
Frequently asked questions
What is the difference between forestly and xplainfi?
They serve adjacent needs but don't currently overlap on shipped themes. xplainfi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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 forestly better than xplainfi?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. xplainfi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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 forestly?
Top forestly alternatives in Analytics are ranked by recent ship velocity. Browse the "forestly alternatives" section above for the current picks, or visit /alternatives/forestly for the full list with editorial commentary on each.
What are the best alternatives to xplainfi?
Top xplainfi alternatives in Analytics are ranked by recent ship velocity. Browse the "xplainfi alternatives" section above for the current picks, or visit /alternatives/xplainfi for the full list with editorial commentary on each.