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Comparison · Infra & APIs

ggInterval vs sps

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

Shared themes:r-package

ggInterval vs sps: at a glance

FeatureggIntervalsps
SectorInfra & APIsInfra & APIs
Velocity score0.02.5
Sparks · 30d00
Top themessymbolic-data-analysis, interval-data, ggplot2, data-visualizationr-package, survey-sampling, sequential-poisson, performance
Last editorial update1h ago1d ago
WebsiteVisit →Visit →

What is ggInterval?

Interval-valued data plotting, spending 2026 making its function names and examples survive CRAN.

ggInterval visualizes symbolic interval-valued data — observations recorded as ranges rather than points — with a family of plot functions in the ggplot2 idiom. The plot catalogue grew most recently with interval correlation heatmaps and interval line plots compatible with time-series input. The three releases before that were corrections: seven plot functions renamed for consistency, examples switched from dontrun to donttest at CRAN's request, and a vignette rewritten to demonstrate every function in one place.

Read the full ggInterval trajectory →

What is sps?

sps keeps sanding down sequential Poisson sampling rather than adding to it.

The package implements sequential Poisson sampling for survey design, covering inclusion probabilities, proportional allocation, replicate weights, and take-all strata. Recent releases are small and tightly scoped: a divisor method helper, an iterator that draws a sample one unit at a time, automatic selection of the replicate-weight parameter, and repeated performance work on inclusion probability calculation.

Read the full sps trajectory →

ggInterval vs sps: editorial side-by-side

G
ggInterval
INFRA · APIS
0.0

Interval-valued data plotting, spending 2026 making its function names and examples survive CRAN.

◆ Current state

ggInterval visualizes symbolic interval-valued data — observations recorded as ranges rather than points — with a family of plot functions in the ggplot2 idiom. The plot catalogue grew most recently with interval correlation heatmaps and interval line plots compatible with time-series input. The three releases before that were corrections: seven plot functions renamed for consistency, examples switched from dontrun to donttest at CRAN's request, and a vignette rewritten to demonstrate every function in one place.

◆ Where it's heading

The package is consolidating an interface that had drifted. Renaming seven functions in a single release is the clearest signal — the naming was inconsistent enough to be worth breaking, and the vignette rewrite that followed suggests discoverability was the underlying complaint. Underneath that, the additions are steady and narrow: each release brings interval-aware versions of plot types that already exist for point data, which is the whole premise of the package.

◆ Prediction

The pattern of porting one more standard plot type into interval-aware form each release is the most likely continuation; the tsplot compatibility in the latest version hints that time-series interval data is the direction attracting attention.

S
sps
INFRA · APIS
2.5

sps keeps sanding down sequential Poisson sampling rather than adding to it.

◆ Current state

The package implements sequential Poisson sampling for survey design, covering inclusion probabilities, proportional allocation, replicate weights, and take-all strata. Recent releases are small and tightly scoped: a divisor method helper, an iterator that draws a sample one unit at a time, automatic selection of the replicate-weight parameter, and repeated performance work on inclusion probability calculation.

◆ Where it's heading

Development is consolidation rather than expansion. Most releases either speed up an existing routine or remove a decision the user previously had to make by hand, such as picking the smallest parameter that keeps replicate weights non-negative. Documentation and tooling get comparable attention to the algorithms, with a dedicated vignette on inclusion probabilities and a recent switch of test and documentation infrastructure. The API surface has been essentially stable across the window.

◆ Prediction

Expect continued small ergonomic and performance releases against the existing function set rather than new sampling designs, which is the pattern every release in this window follows.

Alternatives to ggInterval and sps

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 ggInterval or sps.

See all ggInterval alternatives → · See all sps alternatives →

Recent activity from ggInterval and sps

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

  1. 1mo agospsDocumentation polish; switches to tinytest and litedown
  2. 3mo agoggIntervalInterval correlation heatmaps and time-series-compatible line plots
  3. 6mo agoggIntervalExamples switched to donttest per CRAN review
  4. 6mo agoggIntervalVignette rewritten to cover every plot function
  5. 6mo agoggIntervalSeven plot functions renamed for consistency
  6. 9mo agospsFixes extra argument handling in sps_iterator()
  7. 0y agospsAdds divisor_method() and a one-unit-at-a-time sampling iterator
  8. 1y agospsAdds an inclusion-probability vignette and faster partial sorting
  9. 1y agospsAutomatic tau selection for replicate weights
  10. 2y agospsAdds becomes_ta() for take-all stratum sample sizes

Frequently asked questions

What is the difference between ggInterval and sps?

Both compete on the same themes — r-package — within Infra & APIs. sps 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 ggInterval better than sps?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. sps 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to ggInterval?

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

What are the best alternatives to sps?

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