HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of ggdist and PESTO — release velocity, themes, recent moves, and the top alternatives to consider.
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.
A calibration toolkit that found its core PEST++ bridge had never actually run
PESTO wraps PEST++ inversion for APSIM crop models from R. Version 0.10.0 rebuilt the PEST++ invocation layer after the maintainer found the shell-out had never executed: control variables were passed as /h :name=value, a syntax PEST++ has never accepted. Fifteen defects were present since the initial April 2026 release and shipped in every version after it. 0.10.1 followed with APSIM binary discovery via APSIM_EXE_PATH and a benchmark battery against real PEST 18, pestpp-ies 5.2.16 and native APSIM that reproduced the prior baseline at 0.0% deviation on every accuracy metric.
ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.
Two threads run in parallel and keep converging. One is statistical: pluggable density estimators arrived first, then became the default, then gained weights and quantile histograms. The other is compositional: sub-geometries acquired their own guides, then their own scales, so a slab's thickness axis is now a first-class annotated dimension. Cadence has stretched from twice-yearly to roughly annual, with the recent work tightening existing surface rather than opening new.
Subguides gained subscales a release later, so the remaining asymmetry is in the sub-geometry system rather than the statistics; expect the next release to continue that fill-in work.
PESTO wraps PEST++ inversion for APSIM crop models from R. Version 0.10.0 rebuilt the PEST++ invocation layer after the maintainer found the shell-out had never executed: control variables were passed as /h :name=value, a syntax PEST++ has never accepted. Fifteen defects were present since the initial April 2026 release and shipped in every version after it. 0.10.1 followed with APSIM binary discovery via APSIM_EXE_PATH and a benchmark battery against real PEST 18, pestpp-ies 5.2.16 and native APSIM that reproduced the prior baseline at 0.0% deviation on every accuracy metric.
The arc runs from packaging discipline toward working software, and the ordering is unusual. Releases 0.4.0 and 0.4.1 were governance and metadata passes: citation files, code of conduct, canonical URL migration to AAGI. 0.7.0 broadened the forward-model templates to ODE, crop-growth and SEIR forms and promoted the observation schema to public API. Only at 0.10.0 did the project ground itself against the actual USGS sources and a real pestpp binary, which is precisely when the defects surfaced.
Expect the next releases to widen the real-engine test matrix - more PEST++ variants and pinned APSIM versions exercised in CI - rather than add new forward-model families, since verification is now the stated priority in every release note.
Other Infra & APIs 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 ggdist or PESTO.
France's national flood statistics, ported out of Fortran and into R.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
Fast design-based estimators for experiments, coasting on CRAN patches.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
See all ggdist alternatives → · See all PESTO alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. ggdist and PESTO 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggdist and PESTO 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 Infra & APIs products to evaluate alongside.
Top ggdist alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggdist alternatives" section above for the current picks, or visit /alternatives/ggdist for the full list with editorial commentary on each.
Top PESTO alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "PESTO alternatives" section above for the current picks, or visit /alternatives/pesto for the full list with editorial commentary on each.