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fastrg vs rnpn

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

Shared themes:r-package

fastrg vs rnpn: at a glance

Featurefastrgrnpn
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesrandom-graphs, stochastic-blockmodels, network-sampling, sparse-matricesphenology, api-client, ecological-data, data-cleaning
Last editorial update48m ago1h ago
WebsiteVisit →Visit →

What is fastrg?

A fast random-graph sampler that spent 0.3.1 fixing what its parameters actually mean.

fastRG samples from generalized random dot product graphs — stochastic blockmodels, degree-corrected and overlapping variants, directed and undirected — in time proportional to the number of edges rather than nodes squared, which is what makes large sparse networks tractable. Since 0.3.1 the model is constructed and parameterised in one object, with sampling methods taking that object rather than re-specifying edge distribution at sample time.

Read the full fastrg trajectory →

What is rnpn?

The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.

rnpn is the R client for the USA National Phenology Network, retrieving observation records, phenometrics and gridded model layers. Version 1.3.0 in March 2025 replaced nearly all of its infrastructure at once — sp and raster dropped, terra made optional, XML swapped for xml2, plyr for dplyr, httr and curl for httr2 — and changed what functions return, with tibbles in place of data.tables and empty tibbles in place of NULL on error. The two releases since have completed the missing-value handling and restored performance lost in the transition.

Read the full rnpn trajectory →

fastrg vs rnpn: editorial side-by-side

F
fastrg
ANALYTICS
0.0

A fast random-graph sampler that spent 0.3.1 fixing what its parameters actually mean.

◆ Current state

fastRG samples from generalized random dot product graphs — stochastic blockmodels, degree-corrected and overlapping variants, directed and undirected — in time proportional to the number of edges rather than nodes squared, which is what makes large sparse networks tractable. Since 0.3.1 the model is constructed and parameterised in one object, with sampling methods taking that object rather than re-specifying edge distribution at sample time.

◆ Where it's heading

The package's development has been about semantic correctness more than speed. The 0.3.1 release moved edge-distribution arguments to the constructors and reinterpreted the mixing matrix S under Bernoulli parameterisation; 0.3.2 then flipped the meaning of X and Y in directed blockmodels so outgoing and incoming factors match the edge convention, and made block sorting conditional rather than unconditional. Both are corrections to what returned values mean, not to how fast they arrive. The 2025 release is CRAN documentation linking only.

◆ Prediction

With parameterisation settled and only a documentation release since 2023, the package reads as feature-complete for its sampling families. Nothing in the entries points to additional model types being queued.

R
rnpn
ANALYTICS
0.0

The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.

◆ Current state

rnpn is the R client for the USA National Phenology Network, retrieving observation records, phenometrics and gridded model layers. Version 1.3.0 in March 2025 replaced nearly all of its infrastructure at once — sp and raster dropped, terra made optional, XML swapped for xml2, plyr for dplyr, httr and curl for httr2 — and changed what functions return, with tibbles in place of data.tables and empty tibbles in place of NULL on error. The two releases since have completed the missing-value handling and restored performance lost in the transition.

◆ Where it's heading

The package is being brought onto the current R stack and made honest about missing data, and those are the same project. Converting the -9999 sentinel to NA started in 1.3.0 for download functions and was extended to all columns in 1.4.1; the string "emptyvalue" got the same treatment. Beyond the migration, the feature additions are modest and specific to the domain, such as custom start and end dates for defining a phenometrics season.

◆ Prediction

With the dependency migration finished and sentinel handling now applied across all columns, the next releases most likely return to domain features and to fixes surfaced by the server side, which has already prompted work through migrations and backend moves. The removed progress indicator is an acknowledged regression that may come back.

Alternatives to fastrg and rnpn

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 fastrg or rnpn.

See all fastrg alternatives → · See all rnpn alternatives →

Recent activity from fastrg and rnpn

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

  1. 11mo agornpnSentinel -9999 now converted to NA across all columns
  2. 1y agofastrgDocumentation cross-linking fixes for CRAN
  3. 1y agornpnCustom season windows for phenometrics, and a speed regression fixed
  4. 1y agornpnDependency stack and return types replaced wholesale
  5. 1y agornpnBackfilled notes for seven earlier maintenance releases
  6. 2y agofastrgDirected blockmodel X and Y factors swapped to match edge direction
  7. 4y agofastrgfastRG 0.3.1

Frequently asked questions

What is the difference between fastrg and rnpn?

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

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

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

What are the best alternatives to rnpn?

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