randomwalk
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
Comparison · Analytics
fillpattern vs spEDM
A side-by-side editorial comparison of fillpattern and spEDM — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
fillpattern vs spEDM: at a glance
What is fillpattern?
Pattern fills for ggplot2, hardened against the ways users write sizes
fillpattern provides pattern fills — stripes, bricks, dots — for ggplot2 and base R graphics, aimed at figures that must stay legible in greyscale or to colour-blind readers. The 1.0.3 release is mostly defensive: size modifier strings ending in a colon no longer swap width for height, modify_size() reports invalid units instead of crashing and understands in, inches and cm, and a background colour bug in scale_fill_pattern() is fixed. The minimum R version rises to 4.2.0 for recent graphics engine features.
What is spEDM?
Spatial causal discovery in R, one exposed method per release
spEDM brings empirical dynamic modeling to spatial data — cross mapping, convergent cross mapping and pattern causality over spatial vector and raster inputs, with the numerics in C++ behind S4 generics. The recent releases have exposed geographical pattern causality and spatially convergent partial cross mapping at the R level with vignettes, and 1.12 turns to consolidating the API. It is part of the stscl family alongside the temporal-domain tEDM, with which it shares both its C++ core and its maintainer.
fillpattern vs spEDM: editorial side-by-side
fillpattern
0.0ANALYTICS
Pattern fills for ggplot2, hardened against the ways users write sizes
◆ Current state
fillpattern provides pattern fills — stripes, bricks, dots — for ggplot2 and base R graphics, aimed at figures that must stay legible in greyscale or to colour-blind readers. The 1.0.3 release is mostly defensive: size modifier strings ending in a colon no longer swap width for height, modify_size() reports invalid units instead of crashing and understands in, inches and cm, and a background colour bug in scale_fill_pattern() is fixed. The minimum R version rises to 4.2.0 for recent graphics engine features.
◆ Where it's heading
Development is slow and entirely reactive to how the string-based size interface fails. The pattern across releases is the same: a user hits an edge — very small fill areas in 1.0.2, malformed unit strings in 1.0.3 — and the fix is either a graceful fallback or a clearer error. Leaning on R's newer graphics engine rather than reimplementing pattern rendering keeps the package small at the cost of raising its version floor.
◆ Prediction
Expect further releases to stay in the same register: parsing and validation fixes for the size and unit interface, with the pattern set itself unlikely to change.
spEDM
0.0ANALYTICS
Spatial causal discovery in R, one exposed method per release
◆ Current state
spEDM brings empirical dynamic modeling to spatial data — cross mapping, convergent cross mapping and pattern causality over spatial vector and raster inputs, with the numerics in C++ behind S4 generics. The recent releases have exposed geographical pattern causality and spatially convergent partial cross mapping at the R level with vignettes, and 1.12 turns to consolidating the API. It is part of the stscl family alongside the temporal-domain tEDM, with which it shares both its C++ core and its maintainer.
◆ Where it's heading
The cadence is steady and predictable: each release surfaces one more EDM method as an R-level API with a vignette, then spends the rest of its notes on parameter-handling consistency across the generics. Breaking changes are frequent and deliberate — argument renames, parameter reordering, NA-handling defaults — which reads as a package still settling its interface while the method surface expands. Shared changes appear in tEDM within days, so interface churn lands on both packages at once.
◆ Prediction
Expect the next release to expose another causality variant at the R level with an accompanying vignette, and to continue renaming or reordering parameters toward consistency across the spatial and temporal packages.
Alternatives to fillpattern and spEDM
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 fillpattern or spEDM.
fastml
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
abclass
abclass built out angle-based classifiers in 2022, then went quiet except for CRAN upkeep.
churon
churon is spending its entire release history getting a Rust ONNX binding through CRAN.
firatheme
firatheme woke up after four years and started fixing what ggplot2 changed underneath it.
bagyo
bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.
See all fillpattern alternatives → · See all spEDM alternatives →
Recent activity from fillpattern and spEDM
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agospEDMData slicing for large-scale pattern causality, plus API breaks
- 6mo agofillpatternSize string parsing fixed; invalid units now report instead of crash
- 6mo agospEDMspEDM 1.11
- 6mo agospEDMSpatially convergent partial cross mapping reaches the R API
- 8mo agospEDMRaster cross mapping with anisotropic embedding
- 11mo agospEDMConfigurable distance metrics and multithreaded distance computation
- 1y agospEDMSpatial logistic map exposed at the R level
- 2y agofillpatternSmall fill areas no longer crash; min_size falls back to solid
- 2y agofillpatternfillpattern 1.0.1
Frequently asked questions
What is the difference between fillpattern and spEDM?
Both compete on the same themes — r-package — within Analytics. fillpattern and spEDM 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 fillpattern better than spEDM?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fillpattern and spEDM 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 fillpattern?
Top fillpattern alternatives in Analytics are ranked by recent ship velocity. Browse the "fillpattern alternatives" section above for the current picks, or visit /alternatives/fillpattern for the full list with editorial commentary on each.
What are the best alternatives to spEDM?
Top spEDM alternatives in Analytics are ranked by recent ship velocity. Browse the "spEDM alternatives" section above for the current picks, or visit /alternatives/spedm for the full list with editorial commentary on each.