paleobuddy
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
Comparison · Analytics
dipsaus vs SimInf
A side-by-side editorial comparison of dipsaus and SimInf — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
dipsaus vs SimInf: at a glance
What is dipsaus?
dipsaus sheds five dependencies and rebuilds its native layer on Rcpp
dipsaus is a utility toolbox for R and Shiny developers — parallel helpers, fast map and queue wrappers, RStudio integrations, and custom Shiny inputs — and the foundation layer under the RAVE neuroimaging stack. The 0.3.x line dropped magrittr, remotes, glue, base64url and startup, moved off RcppParallel and TBB, and switched to Rcpp specifically to stop calling R's internal ENCLOS and CLOSENV interfaces. On the user-facing side it added fancyDirectoryInput, a Shiny widget for uploading whole directories with streaming and a progress bar.
What is SimInf?
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
SimInf simulates stochastic disease spread over networks of nodes, with a model parser that compiles user-specified transitions to C. Version 10.0.0 was a deliberate major break: the SimInf_pfilter S4 class and the bootstrap filtering interface were redesigned, a replicates slot was added to SimInf_model, a multi-particle variant of the split-step solver arrived, and the package gained Particle Markov Chain Monte Carlo fitting against observed time series. The follow-up 10.1.0 is a single zero-length memcpy fix found by CRAN's M1 checks.
dipsaus vs SimInf: editorial side-by-side
dipsaus
0.0ANALYTICS
dipsaus sheds five dependencies and rebuilds its native layer on Rcpp
◆ Current state
dipsaus is a utility toolbox for R and Shiny developers — parallel helpers, fast map and queue wrappers, RStudio integrations, and custom Shiny inputs — and the foundation layer under the RAVE neuroimaging stack. The 0.3.x line dropped magrittr, remotes, glue, base64url and startup, moved off RcppParallel and TBB, and switched to Rcpp specifically to stop calling R's internal ENCLOS and CLOSENV interfaces. On the user-facing side it added fancyDirectoryInput, a Shiny widget for uploading whole directories with streaming and a progress bar.
◆ Where it's heading
Two long-running threads run through every release: cut dependencies, and make asynchronous work in R less fragile. The package has been removing packages it once required — synchronicity, qs, RcppRedis, htmltools, stringr, now five more — while successively replacing its own async machinery (make_async_evaluator, then async_workers, then lapply_callr and lapply_async with automatic global handling). The Rcpp move adds a third pressure: staying inside R's supported C interfaces as the non-API surface is closed off.
◆ Prediction
The dependency-shedding pattern points at the remaining soft-deprecated pieces — dipsaus_lock/unlock and PersistContainer have both been marked for removal for several releases and are the obvious next things to go.
SimInf
0.0ANALYTICS
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
◆ Current state
SimInf simulates stochastic disease spread over networks of nodes, with a model parser that compiles user-specified transitions to C. Version 10.0.0 was a deliberate major break: the SimInf_pfilter S4 class and the bootstrap filtering interface were redesigned, a replicates slot was added to SimInf_model, a multi-particle variant of the split-step solver arrived, and the package gained Particle Markov Chain Monte Carlo fitting against observed time series. The follow-up 10.1.0 is a single zero-length memcpy fix found by CRAN's M1 checks.
◆ Where it's heading
The package has been moving from simulation toward inference for several releases. The 9.x line built the input side — utilities for cleaning raw individual event data, variables and enumeration constants in the model parser — and 10.0.0 closed the loop by making the simulator fittable to data through PMCMC. The version number was incremented precisely because that required breaking the particle filter interface.
◆ Prediction
Fitting machinery this new usually needs a second pass on usability, so the next releases most likely focus on diagnostics and documentation around PMCMC rather than on the simulation core, which has been stable across the whole 9.x and 10.x history.
Alternatives to dipsaus and SimInf
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 dipsaus or SimInf.
geodist
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
errors
errors keeps making uncertainty print the way each scientific field expects.
CMAQ
CMAQ went global in v5.5, and has been patching that surface ever since.
enpls
enpls has not changed its statistics since 2016 — only its website, twice.
grex
grex is a lookup table with a version number — it ships when the annotation moves.
See all dipsaus alternatives → · See all SimInf alternatives →
Recent activity from dipsaus and SimInf
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 7mo agodipsausDirectory upload widget lands; native layer moves to Rcpp ⚡
- 9mo agoSimInfAvoid memcpy on zero-length continuous state vector
- 9mo agoSimInfPMCMC fitting arrives; particle filter interface redesigned ⚡
- 2y agoSimInfDocumentation link anchors; parser dependency fix
- 2y agoSimInfModel parser gains variables and enumeration constants
- 2y agoSimInfindividual_events() added for raw event data cleaning
- 3y agoSimInfConfigure script uses R to locate the compiler
- 4y agodipsausrs_edit_file, constrained %OF% operator, nested rs_exec
- 4y agodipsausget_credential added; synchronicity dependency dropped
- 4y agodipsauslapply_callr replaces async_workers; qs and RcppRedis removed
- 5y agodipsausBackground job scheduling and parallel covariance helpers
- 6y agodipsausRStudio-aware helpers with console fallbacks
Frequently asked questions
What is the difference between dipsaus and SimInf?
Both compete on the same themes — r-package — within Analytics. dipsaus and SimInf 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 dipsaus better than SimInf?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dipsaus and SimInf 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 dipsaus?
Top dipsaus alternatives in Analytics are ranked by recent ship velocity. Browse the "dipsaus alternatives" section above for the current picks, or visit /alternatives/dipsaus-r for the full list with editorial commentary on each.
What are the best alternatives to SimInf?
Top SimInf alternatives in Analytics are ranked by recent ship velocity. Browse the "SimInf alternatives" section above for the current picks, or visit /alternatives/siminf-r for the full list with editorial commentary on each.