Vertex pool topology for geometry handled by wk.
Simple features throws away topology — every polygon stores its own coordinates, shared boundaries are duplicated, and expensive operations (GEOS) are needed to rediscover this structure which is then again discarded.
wkpool takes a different approach:
- Segments are atomic: Everything is edges (vertex pairs). Polygons, linestrings, meshes — all just segments with different grouping.
- Vertices live in a pool: Coordinates stored once, referenced by
integer ID (
.vx). - Observe, don’t correct:
establish_topology()represents the truth of your input. Snapping/fixing is a separate, explicit decision. - Topology is discoverable:
merge_coincident()finds shared vertices. Shared boundaries, neighbour relations — they emerge from the data. - Feature provenance: Segments track which feature they came from
(
.feature), enabling adjacency and boundary queries.
From CRAN use
install.packages("wkpool")For development version use
#install.packages("remotes")
remotes::install_github("hypertidy/wkpool")library(wkpool)
library(wk)
# Any wk-handleable geometry
#x <- wk::as_wkb(<wk-compatible>)
x <- wk::as_wkb(c(
paste0(
"MULTIPOLYGON (((0 0, 0 1, 0.75 1, 1 0.8, 0.5 0.7, ",
"0.8 0.6, 0.69 0, 0 0), (0.2 0.2, 0.5 0.2, ",
"0.5 0.4, 0.3 0.6, 0.2 0.4, 0.2 0.2)))"),
"MULTIPOLYGON (((0.69 0, 0.8 0.6, 1.1 0.63, 1.23 0.3, 0.69 0)))"
))
# Establish topology (no coordinate merging yet)
pool <- establish_topology(x)
# What do we have?
topology_report(pool)
#> $n_vertices_raw
#> [1] 19
#>
#> $n_vertices_unique
#> [1] 14
#>
#> $n_duplicate_vertices
#> [1] 5
#>
#> $n_near_miss_vertices
#> [1] 0
#>
#> $n_segments
#> [1] 16
#>
#> $n_shared_edges
#> [1] 1
#>
#> $n_features
#> [1] 2
# Merge coincident vertices (exact match)
merged <- merge_coincident(pool, tolerance = 0)
# Find shared boundaries
shared <- find_shared_edges(merged)
# Internal boundaries (edges shared by exactly 2 features)
internal <- find_internal_boundaries(merged)
# Neighbour relations
neighbours <- find_neighbours(merged, type = "edge") # share a boundary
neighbours_v <- find_neighbours(merged, type = "vertex") # share any vertex
# Access the raw structure
pool_vertices(merged) # data.frame: .vx, x, y
#> .vx x y
#> 1 1 0.00 0.00
#> 2 2 0.00 1.00
#> 3 3 0.75 1.00
#> 4 4 1.00 0.80
#> 5 5 0.50 0.70
#> 6 6 0.80 0.60
#> 7 7 0.69 0.00
#> 9 8 0.20 0.20
#> 10 9 0.50 0.20
#> 11 10 0.50 0.40
#> 12 11 0.30 0.60
#> 13 12 0.20 0.40
#> 17 13 1.10 0.63
#> 18 14 1.23 0.30
pool_segments(merged) # data.frame: .vx0, .vx1, .feature
#> .vx0 .vx1 .feature
#> 1 1 2 1
#> 2 2 3 1
#> 3 3 4 1
#> 4 4 5 1
#> 5 5 6 1
#> 6 6 7 1
#> 7 7 1 1
#> 8 8 9 1
#> 9 9 10 1
#> 10 10 11 1
#> 11 11 12 1
#> 12 12 8 1
#> 13 7 6 2
#> 14 6 13 2
#> 15 13 14 2
#> 16 14 7 2| Decision | Choice | Rationale |
|---|---|---|
| Pool scope | Per-vector, sidecar attribute | No wk core changes needed, n-geometry ready |
| Snapping | Observe don’t correct | Represent truth, fixing is separate |
| Vertex identity | Minted .vx integer |
Survives subset, lighter than UUID |
| Segment identity | Derived from vertex pair | No ID to track, tuple IS identity |
| Primary vctr | Segments | Geometry is what you subset, vertices follow |
| Foundation | vctrs | Principled combine/subset, tidyverse alignment |
-
wk_handle.wkpool()— round-trip back to wk geometry - Path reconstruction — derive linestrings/rings from segment connectivity
- Apply to production package (trip)
- Triangulation integration (decido) — indexed triangles from same pool
- Consider C++ once API is stable
Please note that the wkpool project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.