Clusters phase A: community detection core (Louvain, seeded, structural)

sorokin.oleg.edu/learnharness

detectCommunities(nodes, edges) in src/core/clusters.ts (new dep
graphology-communities-louvain): Louvain modularity over the undirected,
unweighted follows+supports structure (user-decided 2026-09-13). The
random-walk traversal runs on an inlined seeded mulberry32 so the same
graph always yields the same partition; community indices are still
unstable across edits, which is exactly why labelings (phase B) key to
sorted MEMBER SETS. follows+supports between the same pair collapse to
one edge; self-loops and dangling edges are skipped defensively; no
min-size filter here (the >=3 render threshold is a presentation rule).

Tests: two-cliques-plus-bridge split, determinism, singleton/empty
graphs, pair collapse, defensive skips, member sorting. 363/363.

Real-data smoke over the current notes graph: 338 nodes / 211 edges ->
138 communities, modularity 0.95, and the big ones are exactly the
learn-session topics (databases, differential forms, sales, servers,
vim, copulas...). 32 communities clear the >=3 render threshold.

This commit is contained in:

amosblomqvist

2026-09-13 03:46:24 +03:00

parent b4245a209d

commit 95a4477283

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						"cmdk": "^1.1.1",

						"embla-carousel-react": "^8.6.0",

						"graphology": "^0.26.0",

						"graphology-communities-louvain": "^2.0.2",

						"graphology-layout-forceatlas2": "^0.10.1",

						"katex": "^0.16.47",

						"linkedom": "^0.18.13",