1399b38f16
fix: 🧠 修复智能编排日程接口边界与分配问题
* 修复少量边界用例下“排课时间是否充足”的误判问题，完善可用时间计算逻辑
* 修复周视图返回数据存在周次数量偏差的问题，确保周维度结果与实际排课数据一致
* 修复 `steady` 模式下编排不均匀问题
* 引入“逻辑空间映射”策略，将碎片时间段进行拼接后统一计算步长
* 优化分配算法，使 `steady` 模式下课程分布达到绝对平均状态
* 提升算法在高碎片时间场景下的稳定性与均衡性
411 lines
11 KiB
Go
411 lines
11 KiB
Go
package logic
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import (
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"github.com/LoveLosita/smartflow/backend/conv"
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"github.com/LoveLosita/smartflow/backend/model"
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"github.com/LoveLosita/smartflow/backend/respond"
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)
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type slotStatus int
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const (
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Free slotStatus = iota // 0: 纯空闲
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Occupied // 1: 已有课/任务，不可动
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Blocked // 2: 用户屏蔽时段
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Filler // 3: 水课，允许嵌入
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)
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type slotNode struct {
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Status slotStatus
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EventID uint // 🚀 关键：记录课程 ID，用于识别水课边界
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}
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type grid struct {
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data map[int]map[int][13]slotNode
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startWeek int
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startDay int
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endWeek int
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endDay int
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}
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// getNode 和 setNode 是对 grid 数据结构的封装，确保我们在访问时能正确处理默认值（Free）和边界情况
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func (g *grid) getNode(w, d, s int) slotNode {
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if dayMap, ok := g.data[w]; ok {
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return dayMap[d][s]
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}
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return slotNode{Status: Free, EventID: 0}
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}
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func (g *grid) setNode(w, d, s int, node slotNode) {
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if _, ok := g.data[w]; !ok {
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g.data[w] = make(map[int][13]slotNode)
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}
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dayData := g.data[w][d]
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dayData[s] = node
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g.data[w][d] = dayData
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}
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// 检查是否可用 (Free 或 Filler 且不在 Blocked 时段内)
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func (g *grid) isAvailable(w, d, s int) bool {
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node := g.getNode(w, d, s)
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return node.Status == Free || node.Status == Filler
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}
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// countAvailableSlots 统计指定周次范围内所有可用的原子节次总数
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func (g *grid) countAvailableSlots(currW, currD, currS int) int {
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count := 0
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if currW == 0 && currD == 0 && currS == 0 {
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currW, currD, currS = g.startWeek, g.startDay, 1
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}
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for w := currW; w <= g.endWeek; w++ {
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dayMap, hasData := g.data[w]
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for d := 1; d <= 7; d++ {
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// 🚀 头部裁剪：过滤开始日期前的天数
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if w == currW && d < currD {
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continue
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}
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// 🚀 尾部裁剪：过滤结束日期后的天数
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if w == g.endWeek && d > g.endDay {
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break
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}
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var dayData [13]slotNode
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if hasData {
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dayData = dayMap[d]
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}
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for s := 1; s <= 12; s++ {
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if w == currW && d == currD && s < currS {
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continue
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}
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if dayData[s].Status == Free || dayData[s].Status == Filler {
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count++
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}
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}
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}
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}
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return count
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}
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// FindNextAvailable 从当前时间点开始，按周、天、节次顺序查找下一个可用格子
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func (g *grid) FindNextAvailable(currW, currD, currS int) (int, int, int) {
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// 基础越界检查
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if currW > g.endWeek || (currW == g.endWeek && currD > g.endDay) {
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return -1, -1, -1
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}
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for w := currW; w <= g.endWeek; w++ {
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dayMap, hasData := g.data[w]
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for d := 1; d <= 7; d++ {
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if w == currW && d < currD {
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continue
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}
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if w == g.endWeek && d > g.endDay {
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break
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} // 🚀 守住结束天
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var dayData [13]slotNode
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if hasData {
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dayData = dayMap[d]
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}
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for s := 1; s <= 12; s++ {
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if w == currW && d == currD && s < currS {
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continue
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}
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if w == g.endWeek && d == g.endDay {
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break
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} // 🚀 守住结束节
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if dayData[s].Status == Free || dayData[s].Status == Filler {
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return w, d, s
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}
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}
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}
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}
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return -1, -1, -1
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}
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// 辅助函数：向后跳过指定数量的可用坑位
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func (g *grid) skipAvailableSlots(w, d, s, skipCount int) (int, int, int) {
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if skipCount <= 0 {
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// 即使 gap 为 0，也要至少移到下一节
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s++
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if s > 12 {
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s = 1
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d++
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if d > 7 {
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d = 1
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w++
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}
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}
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return w, d, s
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}
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found := 0
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currW, currD, currS := w, d, s+1
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for currW <= g.endWeek {
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if currS > 12 {
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currS = 1
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currD++
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if currD > 7 {
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currD = 1
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currW++
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}
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continue
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}
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// 如果已经跳到了最后一天，不要再跳了，直接返回终点坐标
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if currW == g.endWeek && currD > g.endDay {
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return g.endWeek, g.endDay, 12
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}
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if g.isAvailable(currW, currD, currS) {
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found++
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if found > skipCount {
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return currW, currD, currS
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}
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}
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currS++
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}
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return currW, currD, currS
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}
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func SmartPlanningMainLogic(schedules []model.Schedule, taskClass *model.TaskClass) ([]model.UserWeekSchedule, error) {
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//1.先构建时间格子
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g := buildTimeGrid(schedules, taskClass)
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//2.根据时间格子和排课策略计算每个任务块的具体安排时间
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allocatedItems, err := computeAllocation(g, taskClass.Items, *taskClass.Strategy)
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if err != nil {
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return nil, err
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}
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//3.把这些时间通过DTO函数回填到涉及周的 UserWeekSchedule 结构中，供前端展示
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return conv.PlanningResultToUserWeekSchedules(schedules, allocatedItems), nil
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}
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// buildTimeGrid 构建一个时间格子，标记出哪些时间段被占用、哪些被屏蔽、哪些是水课
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func buildTimeGrid(schedules []model.Schedule, taskClass *model.TaskClass) *grid {
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// 🚀 核心修正：获取精确的起始坐标
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startW, startD, _ := conv.RealDateToRelativeDate(taskClass.StartDate.Format(conv.DateFormat))
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endW, endD, _ := conv.RealDateToRelativeDate(taskClass.EndDate.Format(conv.DateFormat))
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// 将信息初始化到 grid 结构中
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g := &grid{
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data: make(map[int]map[int][13]slotNode),
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startWeek: startW,
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startDay: startD,
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endWeek: endW,
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endDay: endD,
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}
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//标记屏蔽时段 (Blocked)
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for _, blockIdx := range taskClass.ExcludedSlots {
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sFrom, sTo := (blockIdx-1)*2+1, blockIdx*2
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for w := startW; w <= endW; w++ {
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for d := 1; d <= 7; d++ { //🚀 注意：这里的屏蔽是针对每天的，所以直接循环 1-7 天
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for s := sFrom; s <= sTo; s++ {
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g.setNode(w, d, s, slotNode{Status: Blocked})
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}
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}
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}
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}
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// 映射日程 (尊重 Blocked 且只处理范围内的数据)
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for _, s := range schedules {
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if s.Week >= startW && s.Week <= endW {
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if g.getNode(s.Week, s.DayOfWeek, s.Section).Status == Blocked {
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continue
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}
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status := Occupied
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// 只有当课程允许嵌入且当前事件支持嵌入时，才标记为 Filler
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if *taskClass.AllowFillerCourse && s.Event.CanBeEmbedded {
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status = Filler
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}
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g.setNode(s.Week, s.DayOfWeek, s.Section, slotNode{Status: status, EventID: uint(s.EventID)})
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}
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}
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return g
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}
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// computeAllocation 是核心函数，负责根据当前的时间格子状态和排课策略，计算出每个任务块的具体安排时间
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/*func computeAllocation(g *grid, items []model.TaskClassItem, strategy string) ([]model.TaskClassItem, error) {
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if len(items) == 0 {
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return items, nil
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}
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// 🚀 核心修正 1：获取真正的开始坐标（周、天、节）
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// 这里假设你已经通过 conv 把 StartDate 换成了 w1, d1, s1
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startW := g.startWeek
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startD := g.startDay // 建议从 conv 传入具体的 DayOfWeek
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startS := 1
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// 1. 获取可用资源总量
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totalAvailable := g.countAvailableSlots(0, 0, 0)
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// 假设每个任务块至少占用 2 个原子槽位
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totalRequired := len(items) * 2
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// 🚀 核心改进：容量预判
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if totalAvailable < totalRequired {
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// 如果连最基本的坑位都不够，直接报错，不进行任何编排
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return nil, respond.TimeNotEnoughForAutoScheduling
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}
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// 🚀 核心修正 2：步长改为“逻辑间隔”，不再是物理跳跃
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// gap 表示：每两个任务之间，我们要故意空出多少个“可用位”
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gap := 0
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if strategy == "steady" && totalAvailable > totalRequired {
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gap = (totalAvailable - totalRequired) / (len(items) + 1)
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}
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currW, currD, currS := startW, startD, startS
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lastPlacedIndex := -1
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for i := range items {
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w, d, s := g.FindNextAvailable(currW, currD, currS)
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if w == -1 || w > g.endWeek {
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break
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}
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node := g.getNode(w, d, s)
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slotLen := 2
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if node.Status == Filler {
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slotLen = 1
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currID := node.EventID
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for checkS := s + 1; checkS <= 12; checkS++ {
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if next := g.getNode(w, d, checkS); next.Status == Filler && next.EventID == currID {
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slotLen++
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} else {
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break
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}
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}
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}
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endS := s + slotLen - 1
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items[i].EmbeddedTime = &model.TargetTime{
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SectionFrom: s, SectionTo: endS,
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Week: w, DayOfWeek: d,
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}
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for sec := s; sec <= endS; sec++ {
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g.setNode(w, d, sec, slotNode{Status: Occupied})
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}
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// 🚀 核心修正 3：基于“可用位”推进指针，而非物理索引
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// 我们要在 grid 中向后数出 gap 个可用位置，作为下一个任务的起点
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currW, currD, currS = g.skipAvailableSlots(w, d, endS, gap)
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lastPlacedIndex = i // 记录最后一个成功安放的任务索引
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}
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// 🚀 核心改进：结果完整性校验
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if lastPlacedIndex < len(items)-1 {
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return nil, fmt.Errorf("排程中断：由于时间片碎片化，仅成功安排了 %d/%d 个任务块，请尝试扩充时间范围或删减屏蔽位", lastPlacedIndex+1, len(items))
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return nil, respond.TimeNotEnoughForAutoScheduling
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}
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return items, nil
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}*/
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type slotCoord struct {
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w, d, s int
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}
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// getAllAvailable 获取窗口内所有可用的原子节次坐标（逻辑一维化）
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func (g *grid) getAllAvailable() []slotCoord {
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var coords []slotCoord
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for w := g.startWeek; w <= g.endWeek; w++ {
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dayMap, hasData := g.data[w]
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for d := 1; d <= 7; d++ {
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// 边界裁剪逻辑
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if w == g.startWeek && d < g.startDay {
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continue
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}
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if w == g.endWeek && d > g.endDay {
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break
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}
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var dayData [13]slotNode
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if hasData {
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dayData = dayMap[d]
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}
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for s := 1; s <= 12; s++ {
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// 顺着你的逻辑，不限开始节次，但需注意状态判定
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if dayData[s].Status == Free || dayData[s].Status == Filler {
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coords = append(coords, slotCoord{w, d, s})
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}
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}
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}
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}
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return coords
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}
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func computeAllocation(g *grid, items []model.TaskClassItem, strategy string) ([]model.TaskClassItem, error) {
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if len(items) == 0 {
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return items, nil
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}
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// 1. 预处理：提取所有可用坑位
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coords := g.getAllAvailable()
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totalAvailable := len(coords)
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totalRequired := len(items) * 2 // 基础需求：每个任务 2 节
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if totalAvailable < totalRequired {
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return nil, respond.TimeNotEnoughForAutoScheduling
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}
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// 2. 计算精准步长
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gap := 0
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if strategy == "steady" {
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gap = (totalAvailable - totalRequired) / (len(items) + 1)
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}
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// 3. 线性映射分配
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// cursor 是我们在逻辑切片中的“指针”
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cursor := gap
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lastPlacedIndex := -1
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for i := range items {
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if cursor >= totalAvailable {
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break
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}
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// 获取当前逻辑位置对应的物理坐标
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startLoc := coords[cursor]
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w, d, s := startLoc.w, startLoc.d, startLoc.s
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// 4. 容器长度探测 (顺着你的逻辑)
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node := g.getNode(w, d, s)
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slotLen := 2
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if node.Status == Filler {
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slotLen = 1
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currID := node.EventID
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for checkS := s + 1; checkS <= 12; checkS++ {
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if next := g.getNode(w, d, checkS); next.Status == Filler && next.EventID == currID {
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slotLen++
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} else {
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break
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}
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}
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} else if s == 12 || !g.isAvailable(w, d, s+1) {
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// 如果是 Free 区域，但下一节不可用，则被迫设为 1 节
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slotLen = 1
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}
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// 回填时间
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endS := s + slotLen - 1
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items[i].EmbeddedTime = &model.TargetTime{
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SectionFrom: s, SectionTo: endS,
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Week: w, DayOfWeek: d,
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}
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// 标记占用 (物理网格)
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for sec := s; sec <= endS; sec++ {
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g.setNode(w, d, sec, slotNode{Status: Occupied})
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}
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// 🚀 核心进步：逻辑跳跃
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// 既然任务占用了 slotLen 节，我们在逻辑切片中也向后推 slotLen 个位置，再加 gap
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cursor += slotLen + gap
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lastPlacedIndex = i
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}
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if lastPlacedIndex < len(items)-1 {
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return nil, respond.TimeNotEnoughForAutoScheduling
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}
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return items, nil
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}
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