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A side-by-side editorial comparison of epiworldR and ggcorrplot — release velocity, themes, recent moves, and the top alternatives to consider.
epiworldR is a thin R shell whose releases track the C++ simulator underneath it
Almost every release here is a version bump of the underlying epiworld C++ library, wrapped and pushed to CRAN. The substantive R-side work is narrow and consistent: exposing simulation outputs that were already computed but not reachable from R — outbreak size, active cases, hospitalizations and their savers. The newest release addresses an AddressSanitizer finding, which is the kind of thing CRAN checks surface on a compiled package.
ggcorrplot came back after four years and found its significance markers had been lying
ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.
Almost every release here is a version bump of the underlying epiworld C++ library, wrapped and pushed to CRAN. The substantive R-side work is narrow and consistent: exposing simulation outputs that were already computed but not reachable from R — outbreak size, active cases, hospitalizations and their savers. The newest release addresses an AddressSanitizer finding, which is the kind of thing CRAN checks surface on a compiled package.
The R package's job is staying current with the simulator and satisfying CRAN, not evolving its own interface. What direction it has shows in which model outputs get exposed next, and in a steady tidy-up of the build — the custom configure script was dropped in favour of R's built-in C++17 and OpenMP settings, and test coverage has been filled in across several releases with automated assistance.
Expect the next release to track another epiworld version bump, with any R-side addition most likely being one more exposed metric or saver, following the pattern of get_hospitalizations and get_outbreak_size.
ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.
Both releases chase the same target: parity with the older corrplot package inside a ggplot2 object. Significance stars appended to coefficient labels, circle scaling, decimal control, then boxed cells and glyphs sized by absolute correlation — these are corrplot's visual vocabulary reimplemented where they can be composed with other ggplot2 layers. The bug fixes point the other way, at foundations: p-values matched to cells by name rather than row position, clustering computed on the unrounded matrix, tl.col actually applied.
With the corrplot look largely reproduced and the correctness backlog cleared, the remaining gap is the mixed upper/lower display corrplot supports; that is the natural next argument if the current release pace holds.
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 epiworldR or ggcorrplot.
Chord's assistant can now write to the team's knowledge base, not just read from it.
tidytransit tracks the GTFS spec as it grows, one reader and one router feature at a time.
A tiny grid renderer for oblique-projection cubes, complete since its first release.
BioCro swapped an unstable iteration for real root finders, changing what its crop models compute.
redist keeps rewriting the sampler underneath a district-drawing API it has held stable since 4.0.
epiflows has shipped four releases in eight years, none of which changed the code.
See all epiworldR alternatives → · See all ggcorrplot alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ggcorrplot 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggcorrplot 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 Analytics products to evaluate alongside.
Top epiworldR alternatives in Analytics are ranked by recent ship velocity. Browse the "epiworldR alternatives" section above for the current picks, or visit /alternatives/epiworldr for the full list with editorial commentary on each.
Top ggcorrplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggcorrplot alternatives" section above for the current picks, or visit /alternatives/ggcorrplot for the full list with editorial commentary on each.