Adds three intent-level graph reads to the `brain.graph` namespace, each
native-dispatched to the optional `@soulcraft/cor` 3.0 graph engine when present
and served from pure-TS kernels otherwise (identical public shapes, default
visibility filter respected on both paths):
- `rank(opts?)` → `{ id, score }[]` descending — importance / centrality.
TS fallback: PageRank power-iteration with dangling-mass redistribution.
- `communities(opts?)` → `{ groups, count }` — connected grouping. TS fallback:
union-find weakly-connected components, or iterative Tarjan SCC when
`{ directed: true }`.
- `path(from, to, opts?)` → `{ nodes, relationships, cost } | null` — best route.
TS fallback: BFS for fewest hops, Dijkstra (min-heap) for least summed edge
weight (`by: 'weight'`); on-demand frontier expansion so short paths terminate
early. `direction` / `type` / `maxDepth` filters apply.
These are intent contracts, not algorithm contracts — the question is the
promise, the algorithm is the engine's choice.
Pure kernels live in src/graph/analyticsFallback.ts (PageRank, connected
components, Tarjan SCC, MinHeap) — unit-tested in isolation. The full surface is
tested end-to-end through the TS fallback, and the native dispatch + int↔uuid
hydration paths are covered by a mock provider in graph-native-routing.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
163 lines
5.2 KiB
TypeScript
163 lines
5.2 KiB
TypeScript
/**
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* @module tests/unit/graph/analyticsFallback
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* @description Direct unit tests for the pure-TS graph-analytics kernels
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* (`connectedComponents`, `stronglyConnectedComponents`, `pageRank`, `MinHeap`).
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* These cover the algorithmic edge cases — empty graphs, dangling PageRank mass,
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* nested SCCs, heap ordering — without the cost of a full Brainy instance. The
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* `brain.graph.*` surface is tested end-to-end in graph-analytics.test.ts.
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*/
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import { describe, it, expect } from 'vitest'
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import {
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connectedComponents,
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stronglyConnectedComponents,
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pageRank,
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MinHeap
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} from '../../../src/graph/analyticsFallback.js'
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/** Group node indices that share a label into sorted sets for stable comparison. */
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function groupsOf(labels: number[]): number[][] {
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const byLabel = new Map<number, number[]>()
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labels.forEach((label, i) => {
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const arr = byLabel.get(label)
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if (arr) arr.push(i)
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else byLabel.set(label, [i])
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})
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return [...byLabel.values()].map((g) => g.sort((a, b) => a - b)).sort((a, b) => a[0] - b[0])
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}
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describe('connectedComponents (weakly-connected, undirected projection)', () => {
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it('labels an empty graph with no components', () => {
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expect(connectedComponents([])).toEqual([])
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})
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it('treats every isolated node as its own component', () => {
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expect(groupsOf(connectedComponents([[], [], []]))).toEqual([[0], [1], [2]])
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})
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it('merges across edge direction (0→1, 2→1 ⇒ one group)', () => {
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// 0 → 1, 2 → 1, 3 isolated
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const labels = connectedComponents([[1], [], [1], []])
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expect(groupsOf(labels)).toEqual([[0, 1, 2], [3]])
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})
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it('keeps disjoint clusters separate', () => {
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// 0↔1 , 2↔3
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const labels = connectedComponents([[1], [0], [3], [2]])
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expect(groupsOf(labels)).toEqual([
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[0, 1],
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[2, 3]
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])
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})
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})
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describe('stronglyConnectedComponents (directed, Tarjan)', () => {
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it('labels an empty graph with no components', () => {
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expect(stronglyConnectedComponents([])).toEqual([])
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})
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it('splits a directed chain into singletons (no mutual reachability)', () => {
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// 0 → 1 → 2
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expect(groupsOf(stronglyConnectedComponents([[1], [2], []]))).toEqual([[0], [1], [2]])
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})
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it('collapses a directed cycle into one SCC', () => {
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// 0 → 1 → 2 → 0
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expect(groupsOf(stronglyConnectedComponents([[1], [2], [0]]))).toEqual([[0, 1, 2]])
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})
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it('separates a cycle from the acyclic tail that feeds it', () => {
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// 3 → 0 → 1 → 2 → 0 : {0,1,2} is an SCC, 3 is its own SCC
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const labels = stronglyConnectedComponents([[1], [2], [0], [0]])
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expect(groupsOf(labels)).toEqual([[0, 1, 2], [3]])
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})
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it('handles two independent cycles', () => {
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// 0↔1 cycle, 2↔3 cycle
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const labels = stronglyConnectedComponents([
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[1],
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[0],
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[3],
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[2]
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])
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expect(groupsOf(labels)).toEqual([
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[0, 1],
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[2, 3]
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])
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})
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it('produces contiguous community indices', () => {
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const labels = stronglyConnectedComponents([[1], [2], [0], []])
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const distinct = new Set(labels)
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expect(Math.max(...labels)).toBe(distinct.size - 1)
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})
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})
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describe('pageRank', () => {
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it('returns an empty vector for an empty graph', () => {
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expect(pageRank([]).length).toBe(0)
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})
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it('is uniform on a symmetric cycle', () => {
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// 0 → 1 → 2 → 0 — every node identical by symmetry.
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const scores = pageRank([[1], [2], [0]])
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expect(scores[0]).toBeCloseTo(1 / 3, 6)
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expect(scores[1]).toBeCloseTo(1 / 3, 6)
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expect(scores[2]).toBeCloseTo(1 / 3, 6)
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})
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it('ranks a hub (high in-degree) above its sources', () => {
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// 0 → 3, 1 → 3, 2 → 3 : node 3 is the hub.
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const scores = pageRank([[3], [3], [3], []])
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expect(scores[3]).toBeGreaterThan(scores[0])
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expect(scores[3]).toBeGreaterThan(scores[1])
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expect(scores[3]).toBeGreaterThan(scores[2])
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})
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it('redistributes dangling mass so scores sum to 1', () => {
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// Node 3 is dangling (no out-edges) — its mass must not leak away.
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const scores = pageRank([[3], [3], [3], []])
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const total = scores.reduce((sum, s) => sum + s, 0)
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expect(total).toBeCloseTo(1, 6)
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})
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it('sums to 1 even when every node is dangling (no edges)', () => {
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const scores = pageRank([[], [], []])
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const total = scores.reduce((sum, s) => sum + s, 0)
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expect(total).toBeCloseTo(1, 6)
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expect(scores[0]).toBeCloseTo(1 / 3, 6)
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})
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})
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describe('MinHeap', () => {
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it('pops in ascending priority order', () => {
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const heap = new MinHeap<string>()
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heap.push('c', 3)
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heap.push('a', 1)
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heap.push('b', 2)
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heap.push('d', 4)
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expect([heap.pop(), heap.pop(), heap.pop(), heap.pop()]).toEqual(['a', 'b', 'c', 'd'])
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})
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it('returns undefined when empty and tracks size', () => {
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const heap = new MinHeap<number>()
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expect(heap.size).toBe(0)
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expect(heap.pop()).toBeUndefined()
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heap.push(42, 0.5)
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expect(heap.size).toBe(1)
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expect(heap.pop()).toBe(42)
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expect(heap.size).toBe(0)
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})
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it('handles interleaved push/pop correctly', () => {
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const heap = new MinHeap<number>()
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heap.push(5, 5)
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heap.push(1, 1)
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expect(heap.pop()).toBe(1)
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heap.push(3, 3)
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heap.push(2, 2)
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expect(heap.pop()).toBe(2)
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expect(heap.pop()).toBe(3)
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expect(heap.pop()).toBe(5)
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})
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})
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