NextEdu/src/modules/textbooks/graph-layout.ts

/**
 * 知识图谱布局纯函数。
 *
 * 从 knowledge-graph.tsx 抽离，便于单元测试。
 */

import type { KnowledgePoint } from "./types"

export interface GraphNode extends KnowledgePoint {
  x: number
  y: number
}

export interface GraphEdge {
  id: string
  x1: number
  y1: number
  x2: number
  y2: number
}

export interface GraphLayout {
  nodes: GraphNode[]
  edges: GraphEdge[]
  width: number
  height: number
}

/** 节点尺寸常量 */
export const NODE_WIDTH = 160
export const NODE_HEIGHT = 52
export const GAP_X = 40
export const GAP_Y = 90

/**
 * 计算知识图谱的分层布局。
 *
 * 算法：
 * 1. 根据 parentId 构建父子关系
 * 2. BFS 计算每个节点的层级（level）
 * 3. 同层节点按出现顺序水平排列
 * 4. 生成节点坐标和边坐标
 *
 * @param knowledgePoints 知识点列表
 * @returns 图布局（节点带坐标、边、总宽高）
 */
export function computeGraphLayout(
  knowledgePoints: KnowledgePoint[]
): GraphLayout {
  if (knowledgePoints.length === 0) {
    return { nodes: [], edges: [], width: 0, height: 0 }
  }

  const byId = new Map<string, KnowledgePoint>()
  for (const kp of knowledgePoints) byId.set(kp.id, kp)

  const children = new Map<string, string[]>()
  const roots: string[] = []

  for (const kp of knowledgePoints) {
    if (kp.parentId && byId.has(kp.parentId)) {
      const arr = children.get(kp.parentId) ?? []
      arr.push(kp.id)
      children.set(kp.parentId, arr)
    } else {
      roots.push(kp.id)
    }
  }

  const levelMap = new Map<string, number>()
  const levels: string[][] = []
  const queue = [...roots].map((id) => ({ id, level: 0 }))

  // 容错：如果没有任何根节点（全部循环引用），把所有节点放第 0 层
  if (queue.length === 0) {
    for (const kp of knowledgePoints) queue.push({ id: kp.id, level: 0 })
  }

  while (queue.length > 0) {
    const item = queue.shift()
    if (!item) continue
    if (levelMap.has(item.id)) continue
    levelMap.set(item.id, item.level)
    if (!levels[item.level]) levels[item.level] = []
    levels[item.level].push(item.id)
    const kids = children.get(item.id) ?? []
    for (const kid of kids) {
      if (!levelMap.has(kid)) queue.push({ id: kid, level: item.level + 1 })
    }
  }

  // 容错：处理孤立节点（未在 BFS 中访问到）
  for (const kp of knowledgePoints) {
    if (!levelMap.has(kp.id)) {
      const level = levels.length
      levelMap.set(kp.id, level)
      if (!levels[level]) levels[level] = []
      levels[level].push(kp.id)
    }
  }

  const maxCount = Math.max(...levels.map((l) => l.length), 1)
  const width = maxCount * (NODE_WIDTH + GAP_X) + GAP_X
  const height = levels.length * (NODE_HEIGHT + GAP_Y) + GAP_Y

  const positions = new Map<string, { x: number; y: number }>()
  levels.forEach((ids, level) => {
    ids.forEach((id, index) => {
      const x = GAP_X + index * (NODE_WIDTH + GAP_X)
      const y = GAP_Y + level * (NODE_HEIGHT + GAP_Y)
      positions.set(id, { x, y })
    })
  })

  const nodes = knowledgePoints.map((kp) => {
    const pos = positions.get(kp.id) ?? { x: GAP_X, y: GAP_Y }
    return { ...kp, x: pos.x, y: pos.y }
  })

  const edges = knowledgePoints
    .filter((kp) => kp.parentId && positions.has(kp.parentId))
    .map((kp) => {
      const parentId = kp.parentId as string
      const parentPos = positions.get(parentId)
      const childPos = positions.get(kp.id)
      // 类型守卫：两个位置都必须存在（已在 filter 中保证，但 TS 需要 narrowing）
      if (!parentPos || !childPos) {
        return null
      }
      return {
        id: `${parentId}-${kp.id}`,
        x1: parentPos.x + NODE_WIDTH / 2,
        y1: parentPos.y + NODE_HEIGHT,
        x2: childPos.x + NODE_WIDTH / 2,
        y2: childPos.y,
      }
    })
    .filter((e): e is GraphEdge => e !== null)

  return { nodes, edges, width, height }
}