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Comparison · Analytics
maplegend vs mlr3spatial
A side-by-side editorial comparison of maplegend and mlr3spatial — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:spatial
maplegend vs mlr3spatial: at a glance
What is maplegend?
The legend engine mapsf spun out, now covering legend types the parent map package can draw.
maplegend draws the legends for base-R thematic maps, extracted from mapsf so both packages could evolve the legend vocabulary independently. It has been catching up to the map types it has to serve: 0.6.0 added choro_point, choro_line, and choro_symb for choropleth legends rendered on circles, lines, and symbols, following the histogram legend type in 0.4.0. Considerable effort has gone into behaving correctly when the plot aspect ratio is not 1, which required refactoring most of the package in 0.4.0 and still produced a proportional-symbol segment sizing fix in 0.6.3.
What is mlr3spatial?
Raster prediction in mlr3 finally returns class probabilities, not just hard labels.
mlr3spatial connects mlr3 learners to raster and vector spatial data, handling chunked prediction over large rasters through DataBackendRaster. Development is slow and fix-heavy: most releases in the last two years were compatibility work against mlr3 and paradox rather than new capability. 0.7.0 is the exception.
maplegend vs mlr3spatial: editorial side-by-side
maplegend
0.0ANALYTICS
The legend engine mapsf spun out, now covering legend types the parent map package can draw.
◆ Current state
maplegend draws the legends for base-R thematic maps, extracted from mapsf so both packages could evolve the legend vocabulary independently. It has been catching up to the map types it has to serve: 0.6.0 added choro_point, choro_line, and choro_symb for choropleth legends rendered on circles, lines, and symbols, following the histogram legend type in 0.4.0. Considerable effort has gone into behaving correctly when the plot aspect ratio is not 1, which required refactoring most of the package in 0.4.0 and still produced a proportional-symbol segment sizing fix in 0.6.3.
◆ Where it's heading
This is a support library whose backlog is defined by its caller. Every legend type mapsf can produce needs a matching legend renderer, and the release notes are dominated by spacing, offset, and border details — box_cex for symbol spacing, NA box placement in horizontal choropleth legends, text overflow when no_data is set. The shared vocabulary with mapsf is being maintained deliberately, with val_rnd, val_big, and val_dec propagating through legend types release by release. Version numbering is not monotonic in this feed, with 0.4.0 published seconds after 0.5.0.
◆ Prediction
Expect the remaining combined map types to acquire matching legends and the val_* formatting arguments to reach the types that still lack them.
mlr3spatial
0.0ANALYTICS
Raster prediction in mlr3 finally returns class probabilities, not just hard labels.
◆ Current state
mlr3spatial connects mlr3 learners to raster and vector spatial data, handling chunked prediction over large rasters through DataBackendRaster. Development is slow and fix-heavy: most releases in the last two years were compatibility work against mlr3 and paradox rather than new capability. 0.7.0 is the exception.
◆ Where it's heading
The package tracks the mlr3 core rather than leading it — 0.5.0 and 0.6.1 exist to absorb upstream changes in paradox and mlr3. Against that background, 0.7.0 adding probability predictions to predict_spatial() is the first genuine capability increase in a while, arriving alongside two DataBackendRaster fixes for multi-band sources and similarly-named layers. Cadence is roughly one release per year.
◆ Prediction
Given the pattern, the next release is more likely to be compatibility work against a new mlr3 or terra version than another feature; further raster-backend edge cases around layer naming are the visible loose end.
Alternatives to maplegend and mlr3spatial
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 maplegend or mlr3spatial.
nanoparquet
nanoparquet is chasing byte-level agreement with the Java and Rust Parquet readers, not feature count.
poissonreg
poissonreg gave its models away to parsnip and kept the glue — now it just keeps glmnet honest.
S7
S7 has stopped adding surface and started proving it holds up against R itself.
torchvision
R's torchvision is porting PyTorch's vision stack one task at a time — instance segmentation just landed.
datefixR
The messy-date parser rewrote its core in Rust and came out 300x faster.
See all maplegend alternatives → · See all mlr3spatial alternatives →
Recent activity from maplegend and mlr3spatial
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agomlr3spatialpredict_spatial() gains probability predictions
- 2mo agomaplegendContinuous legend formatting and aspect-ratio segment fix
- 4mo agomaplegendChoropleth legends on points, lines and symbols
- 7mo agomaplegendPackage-wide refactor for non-unity aspect ratios, histogram legends
- 7mo agomaplegendSingle-modality legends allowed for typo, symb and prop_line
- 10mo agomlr3spatialCompatibility with mlr3 1.2.0
- 1y agomlr3spatialError on conflicting X/Y columns in sf objects
- 1y agomaplegendAlpha transparency and redraw on device resize
- 1y agomaplegendOffset and symbol sizing aligned with mapsf
- 2y agomlr3spatialCompatibility with paradox 1.0.0
- 3y agomlr3spatialUse terra::inMemory() instead of the @ptr slot
- 3y agomlr3spatialspatial_predict() accepts stars, sf and Raster* inputs
Frequently asked questions
What is the difference between maplegend and mlr3spatial?
Both compete on the same themes — spatial — within Analytics. maplegend and mlr3spatial 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 maplegend better than mlr3spatial?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. maplegend and mlr3spatial 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 maplegend?
Top maplegend alternatives in Analytics are ranked by recent ship velocity. Browse the "maplegend alternatives" section above for the current picks, or visit /alternatives/maplegend for the full list with editorial commentary on each.
What are the best alternatives to mlr3spatial?
Top mlr3spatial alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3spatial alternatives" section above for the current picks, or visit /alternatives/mlr3spatial for the full list with editorial commentary on each.