HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
Comparison · Infra & APIs
fdacluster vs ggdist
A side-by-side editorial comparison of fdacluster and ggdist — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
fdacluster vs ggdist: at a glance
What is fdacluster?
Functional data clustering grew from one algorithm into a comparable suite
fdacluster clusters functional data while separating amplitude from phase variation, aligning curves as part of the clustering rather than before it. The algorithm set covers k-means, hierarchical clustering and DBSCAN, all producing a common caps result object so runs can be compared directly. Version 0.4.0 tightened the interface with is_domain_interval and transformation arguments describing the input data, added compatibility checking between incompatible option combinations, and split the L2 and normalized L2 distances into separate C++ classes to enforce that plain L2 cannot be combined with dilation or affine warping it is not invariant to.
What is ggdist?
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.
fdacluster vs ggdist: editorial side-by-side
fdacluster
0.0INFRA · APIS
Functional data clustering grew from one algorithm into a comparable suite
◆ Current state
fdacluster clusters functional data while separating amplitude from phase variation, aligning curves as part of the clustering rather than before it. The algorithm set covers k-means, hierarchical clustering and DBSCAN, all producing a common caps result object so runs can be compared directly. Version 0.4.0 tightened the interface with is_domain_interval and transformation arguments describing the input data, added compatibility checking between incompatible option combinations, and split the L2 and normalized L2 distances into separate C++ classes to enforce that plain L2 cannot be combined with dilation or affine warping it is not invariant to.
◆ Where it's heading
The trajectory runs from method implementation toward guardrails and portability. Early releases added capability; recent ones prevent misuse and reduce weight - dplyr, forcats, tidyr and purrr removed in 0.4.0, furrr swapped for future.apply - while 0.4.2 is entirely C++ correctness, replacing Armadillo's whole-object finiteness check with scalar std::isfinite and fixing an integer overflow in linear index computation that broke large datasets. Cadence is roughly one release a year.
◆ Prediction
Given that the last two releases were dependency reduction and numerical correctness rather than method work, expect the next to continue in that vein unless a new clustering algorithm is contributed.
ggdist
0.0INFRA · APIS
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to fdacluster and ggdist
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 fdacluster or ggdist.
bsvarSIGNs
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
estimatr
Fast design-based estimators for experiments, coasting on CRAN patches.
ipaddress
IP address vectors for R that hit 1.0 and then went quiet.
ltertools
A column-key toolkit for stitching decades of ecological field data into one table.
finnts
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
See all fdacluster alternatives → · See all ggdist alternatives →
Recent activity from fdacluster and ggdist
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 7mo agofdaclusterInteger overflow fixed for large datasets, C++ finiteness checks corrected
- 1y agoggdistPer-geometry thickness subscales and settable defaults
- 1y agofdaclusterParallel worker setup and an acronym correction
- 1y agofdaclusterInput description arguments and enforced distance-warping compatibility
- 2y agoggdistBlurred dotplots draw Monte Carlo error; weights reach every estimator ⚡
- 2y agoggdistC++ dotplot binning and safer bandwidth fallbacks
- 3y agofdaclusterMedian centroids and centroids defined on unioned grids
- 3y agofdaclusterNamespace notation and optional dependency guards
- 3y agofdaclusterHierarchical clustering, DBSCAN and a shared result class arrive together ⚡
- 3y agoggdistBounded density becomes the default; existing charts change ⚡
- 3y agoggdistCategorical distributions, hex layouts, pluggable density estimators
- 4y agoggdistComputed variables shared across sub-geometries
Frequently asked questions
What is the difference between fdacluster and ggdist?
Both compete on the same themes — r-package — within Infra & APIs. fdacluster and ggdist 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 fdacluster better than ggdist?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fdacluster and ggdist 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.
What are the best alternatives to fdacluster?
Top fdacluster alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "fdacluster alternatives" section above for the current picks, or visit /alternatives/fdacluster for the full list with editorial commentary on each.
What are the best alternatives to ggdist?
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.