Port DBSCAN and K-means clustering (#56)#92
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Adds FeatureCollection.dbscanClusters() and FeatureCollection.kmeansClusters() for point clustering. Sets cluster, dbscan/core/edge/noise, and centroid properties on each clustered point feature.
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Summary
Ported DBSCAN and K-means clustering from Turf.js.
Sources/GISTools/Algorithms/Clusters.swiftFeatureCollection.dbscanClusters(maxDistance:minPoints:mutate:)— DBSCAN density-based clusteringFeatureCollection.kmeansClusters(numberOfClusters:mutate:)— K-means partitioning clusteringBoth add properties to each point Feature:
cluster(Int) — cluster IDdbscan(String) — "core" / "edge" / "noise"centroid([Double]) — cluster centroid [lon, lat] (K-means only)Tests/ClustersTests.swift(6 tests)dbscanBasicdbscanNoisedbscanEmptykmeansBasickmeansEmptykmeansAutoKTest results
272 tests pass across 60 suites (+6 new).
Closes #56