/**
 * @module tests/unit/graph/analyticsFallback
 * @description Direct unit tests for the pure-TS graph-analytics kernels
 * (`connectedComponents`, `stronglyConnectedComponents`, `pageRank`, `MinHeap`).
 * These cover the algorithmic edge cases — empty graphs, dangling PageRank mass,
 * nested SCCs, heap ordering — without the cost of a full Brainy instance. The
 * `brain.graph.*` surface is tested end-to-end in graph-analytics.test.ts.
 */

import { describe, it, expect } from 'vitest'
import {
  connectedComponents,
  stronglyConnectedComponents,
  pageRank,
  MinHeap
} from '../../../src/graph/analyticsFallback.js'

/** Group node indices that share a label into sorted sets for stable comparison. */
function groupsOf(labels: number[]): number[][] {
  const byLabel = new Map<number, number[]>()
  labels.forEach((label, i) => {
    const arr = byLabel.get(label)
    if (arr) arr.push(i)
    else byLabel.set(label, [i])
  })
  return [...byLabel.values()].map((g) => g.sort((a, b) => a - b)).sort((a, b) => a[0] - b[0])
}

describe('connectedComponents (weakly-connected, undirected projection)', () => {
  it('labels an empty graph with no components', () => {
    expect(connectedComponents([])).toEqual([])
  })

  it('treats every isolated node as its own component', () => {
    expect(groupsOf(connectedComponents([[], [], []]))).toEqual([[0], [1], [2]])
  })

  it('merges across edge direction (0→1, 2→1 ⇒ one group)', () => {
    // 0 → 1, 2 → 1, 3 isolated
    const labels = connectedComponents([[1], [], [1], []])
    expect(groupsOf(labels)).toEqual([[0, 1, 2], [3]])
  })

  it('keeps disjoint clusters separate', () => {
    // 0↔1 , 2↔3
    const labels = connectedComponents([[1], [0], [3], [2]])
    expect(groupsOf(labels)).toEqual([
      [0, 1],
      [2, 3]
    ])
  })
})

describe('stronglyConnectedComponents (directed, Tarjan)', () => {
  it('labels an empty graph with no components', () => {
    expect(stronglyConnectedComponents([])).toEqual([])
  })

  it('splits a directed chain into singletons (no mutual reachability)', () => {
    // 0 → 1 → 2
    expect(groupsOf(stronglyConnectedComponents([[1], [2], []]))).toEqual([[0], [1], [2]])
  })

  it('collapses a directed cycle into one SCC', () => {
    // 0 → 1 → 2 → 0
    expect(groupsOf(stronglyConnectedComponents([[1], [2], [0]]))).toEqual([[0, 1, 2]])
  })

  it('separates a cycle from the acyclic tail that feeds it', () => {
    // 3 → 0 → 1 → 2 → 0  : {0,1,2} is an SCC, 3 is its own SCC
    const labels = stronglyConnectedComponents([[1], [2], [0], [0]])
    expect(groupsOf(labels)).toEqual([[0, 1, 2], [3]])
  })

  it('handles two independent cycles', () => {
    // 0↔1 cycle, 2↔3 cycle
    const labels = stronglyConnectedComponents([
      [1],
      [0],
      [3],
      [2]
    ])
    expect(groupsOf(labels)).toEqual([
      [0, 1],
      [2, 3]
    ])
  })

  it('produces contiguous community indices', () => {
    const labels = stronglyConnectedComponents([[1], [2], [0], []])
    const distinct = new Set(labels)
    expect(Math.max(...labels)).toBe(distinct.size - 1)
  })
})

describe('pageRank', () => {
  it('returns an empty vector for an empty graph', () => {
    expect(pageRank([]).length).toBe(0)
  })

  it('is uniform on a symmetric cycle', () => {
    // 0 → 1 → 2 → 0 — every node identical by symmetry.
    const scores = pageRank([[1], [2], [0]])
    expect(scores[0]).toBeCloseTo(1 / 3, 6)
    expect(scores[1]).toBeCloseTo(1 / 3, 6)
    expect(scores[2]).toBeCloseTo(1 / 3, 6)
  })

  it('ranks a hub (high in-degree) above its sources', () => {
    // 0 → 3, 1 → 3, 2 → 3 : node 3 is the hub.
    const scores = pageRank([[3], [3], [3], []])
    expect(scores[3]).toBeGreaterThan(scores[0])
    expect(scores[3]).toBeGreaterThan(scores[1])
    expect(scores[3]).toBeGreaterThan(scores[2])
  })

  it('redistributes dangling mass so scores sum to 1', () => {
    // Node 3 is dangling (no out-edges) — its mass must not leak away.
    const scores = pageRank([[3], [3], [3], []])
    const total = scores.reduce((sum, s) => sum + s, 0)
    expect(total).toBeCloseTo(1, 6)
  })

  it('sums to 1 even when every node is dangling (no edges)', () => {
    const scores = pageRank([[], [], []])
    const total = scores.reduce((sum, s) => sum + s, 0)
    expect(total).toBeCloseTo(1, 6)
    expect(scores[0]).toBeCloseTo(1 / 3, 6)
  })
})

describe('MinHeap', () => {
  it('pops in ascending priority order', () => {
    const heap = new MinHeap<string>()
    heap.push('c', 3)
    heap.push('a', 1)
    heap.push('b', 2)
    heap.push('d', 4)
    expect([heap.pop(), heap.pop(), heap.pop(), heap.pop()]).toEqual(['a', 'b', 'c', 'd'])
  })

  it('returns undefined when empty and tracks size', () => {
    const heap = new MinHeap<number>()
    expect(heap.size).toBe(0)
    expect(heap.pop()).toBeUndefined()
    heap.push(42, 0.5)
    expect(heap.size).toBe(1)
    expect(heap.pop()).toBe(42)
    expect(heap.size).toBe(0)
  })

  it('handles interleaved push/pop correctly', () => {
    const heap = new MinHeap<number>()
    heap.push(5, 5)
    heap.push(1, 1)
    expect(heap.pop()).toBe(1)
    heap.push(3, 3)
    heap.push(2, 2)
    expect(heap.pop()).toBe(2)
    expect(heap.pop()).toBe(3)
    expect(heap.pop()).toBe(5)
  })
})
