STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of simmer.plot and TidyDensity — release velocity, themes, recent moves, and the top alternatives to consider.
The plotting companion to simmer, shipping only when the simulator or a graphics dependency moves.
simmer.plot renders discrete-event simulation output — S3 plot() methods over get_mon_arrivals(), get_mon_attributes() and get_mon_resources(), plus trajectory diagrams drawn through DiagrammeR. Since 0.1.12 the methods attach to the monitoring data itself rather than the simulation environment, and 0.1.18 finished that migration by deleting the deprecated environment-level methods.
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.
simmer.plot renders discrete-event simulation output — S3 plot() methods over get_mon_arrivals(), get_mon_attributes() and get_mon_resources(), plus trajectory diagrams drawn through DiagrammeR. Since 0.1.12 the methods attach to the monitoring data itself rather than the simulation environment, and 0.1.18 finished that migration by deleting the deprecated environment-level methods.
This package moves when something it depends on moves. Its history is a sequence of parser fixes for new simmer trajectory formats, DiagrammeR and tidyr and dplyr version bumps, and ggplot2 workarounds. The one clear internal decision — plotting monitor output instead of the environment — was made in 2017 and completed six years later. The 2025 release fixes documentation cross-references and nothing else.
The next release most likely follows a simmer trajectory-format change or a CRAN documentation policy, matching every recent entry. There is no visible feature work in the pipeline.
TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.
The package is filling out a matrix rather than changing shape — every new distribution gets the same four or five companion functions, so the surface grows predictably and the design does not. What variation exists comes from utilities that work across distributions: MCMC sampling, bootstrap helpers, time series conversion, distribution comparison. The two genuine breaking changes in this window were both internal reworks, moving generation onto data.table and rewriting quantile normalization for speed.
The established pattern of adding a distribution with its full helper set is the most likely continuation. Recent releases have been small, suggesting the catalogue is approaching the distributions its author considers worth covering.
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 simmer.plot or TidyDensity.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all simmer.plot alternatives → · See all TidyDensity alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. simmer.plot and TidyDensity 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. simmer.plot and TidyDensity 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.
Top simmer.plot alternatives in Analytics are ranked by recent ship velocity. Browse the "simmer.plot alternatives" section above for the current picks, or visit /alternatives/simmer-plot for the full list with editorial commentary on each.
Top TidyDensity alternatives in Analytics are ranked by recent ship velocity. Browse the "TidyDensity alternatives" section above for the current picks, or visit /alternatives/tidydensity for the full list with editorial commentary on each.