Merge remote-tracking branch 'origin/main' into fix/752-embed-absolute-paths

Author: carlos-alm

.github/workflows/codegraph-impact.yml

@@ -1,5 +1,10 @@
 name: Codegraph Impact Analysis
 on: [pull_request]
+
+concurrency:
+  group: codegraph-impact-${{ github.ref }}
+  cancel-in-progress: true
+
 jobs:
   impact:
     runs-on: ubuntu-latest

src/graph/algorithms/leiden/optimiser.ts

@@ -437,79 +437,6 @@ function boltzmannSelectCandidate(
  * (approaches greedy), higher = more exploratory. Determinism is preserved
  * via the seeded PRNG — same seed produces the same assignments.
  */
-/**
- * Collect eligible candidate communities for node `v` during refinement.
- * A candidate must: (a) be in the same macro-community, (b) respect the size
- * limit, and (c) produce a positive quality gain above GAIN_EPSILON.
- * Returns the number of collected candidates written into `scratch`.
- */
-function collectRefinementCandidates(
-  p: Partition,
-  g: GraphAdapter,
-  v: number,
-  touchedCount: number,
-  macroV: number,
-  commMacro: Int32Array,
-  maxSize: number,
-  opts: NormalizedOptions,
-  scratch: RefinementScratch,
-): number {
-  let candLen: number = 0;
-  for (let t = 0; t < touchedCount; t++) {
-    const c: number = p.getCandidateCommunityAt(t);
-    if (c === p.nodeCommunity[v]!) continue;
-    if (commMacro[c]! !== macroV) continue;
-    if (maxSize < Infinity) {
-      const nextSize: number = p.getCommunityTotalSize(c) + g.size[v]!;
-      if (nextSize > maxSize) continue;
-    }
-    const gain: number = computeQualityGain(p, v, c, opts);
-    if (gain > GAIN_EPSILON) {
-      scratch.candC[candLen] = c;
-      scratch.candGain[candLen] = gain;
-      candLen++;
-    }
-  }
-  return candLen;
-}
-
-/**
- * Boltzmann probabilistic selection from collected candidates (Algorithm 3).
- * Returns the chosen community ID, or -1 if the node should stay as singleton.
- *
- * p(v, C) is proportional to exp(deltaH / theta), with the "stay as singleton"
- * option (deltaH = 0) included. For numerical stability, the max gain is
- * subtracted before exponentiation.
- */
-function boltzmannSelectCandidate(
-  candLen: number,
-  theta: number,
-  rng: () => number,
-  scratch: RefinementScratch,
-): number {
-  let maxGain: number = 0;
-  for (let i = 0; i < candLen; i++) {
-    if (scratch.candGain[i]! > maxGain) maxGain = scratch.candGain[i]!;
-  }
-  // "Stay as singleton" weight: exp((0 - maxGain) / theta)
-  const stayWeight: number = Math.exp((0 - maxGain) / theta);
-  let totalWeight: number = stayWeight;
-  for (let i = 0; i < candLen; i++) {
-    scratch.candWeight[i] = Math.exp((scratch.candGain[i]! - maxGain) / theta);
-    totalWeight += scratch.candWeight[i]!;
-  }
-
-  const r: number = rng() * totalWeight;
-  if (r < stayWeight) return -1; // node stays as singleton
-
-  let cumulative: number = stayWeight;
-  for (let i = 0; i < candLen; i++) {
-    cumulative += scratch.candWeight[i]!;
-    if (r < cumulative) return scratch.candC[i]!;
-  }
-  return scratch.candC[candLen - 1]!; // fallback
-}
-
 function refineWithinCoarseCommunities(
   g: GraphAdapter,
   basePart: Partition,