273 lines
8.0 KiB
Go
273 lines
8.0 KiB
Go
package main
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import (
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"fmt"
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"os"
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_ "github.com/go-sql-driver/mysql"
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"gorm.io/driver/mysql"
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"gorm.io/gorm"
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)
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type LivestreamPrize struct {
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ID int64 `gorm:"column:id"`
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Name string `gorm:"column:name"`
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Weight int32 `gorm:"column:weight"`
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Level int32 `gorm:"column:level"`
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}
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type LivestreamDrawLog struct {
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ID int64 `gorm:"column:id"`
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ActivityID int64 `gorm:"column:activity_id"`
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PrizeID int64 `gorm:"column:prize_id"`
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PrizeName string `gorm:"column:prize_name"`
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Level int32 `gorm:"column:level"`
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WeightsTotal int64 `gorm:"column:weights_total"`
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RandValue int64 `gorm:"column:rand_value"`
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}
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func main() {
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// 从环境变量读取数据库连接信息
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dsn := os.Getenv("DB_DSN")
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if dsn == "" {
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fmt.Println("请设置环境变量 DB_DSN，例如：")
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fmt.Println("export DB_DSN='user:password@tcp(host:port)/dev_game?charset=utf8mb4&parseTime=True&loc=Local'")
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fmt.Println("\n或者直接运行：")
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fmt.Println("DB_DSN='user:password@tcp(host:port)/dev_game?charset=utf8mb4&parseTime=True&loc=Local' go run main.go")
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return
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}
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db, err := gorm.Open(mysql.Open(dsn), &gorm.Config{})
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if err != nil {
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fmt.Printf("连接数据库失败: %v\n", err)
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return
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}
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fmt.Println("========== 直播间抽奖概率分析工具 ==========\n")
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// 1. 查询最近的活动
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fmt.Println("【最近的直播间活动】")
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var activities []struct {
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ID int64 `gorm:"column:id"`
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Name string `gorm:"column:name"`
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}
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if err := db.Table("livestream_activities").
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Order("id DESC").
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Limit(10).
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Find(&activities).Error; err != nil {
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fmt.Printf("查询活动失败: %v\n", err)
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return
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}
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if len(activities) == 0 {
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fmt.Println("没有找到直播间活动")
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return
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}
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for i, act := range activities {
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fmt.Printf("%d. ID: %d, 名称: %s\n", i+1, act.ID, act.Name)
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}
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// 选择第一个活动进行分析
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activityID := activities[0].ID
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fmt.Printf("\n分析活动ID: %d (%s)\n\n", activityID, activities[0].Name)
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// 2. 查询奖品配置
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fmt.Println("【奖品权重配置】")
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var prizes []LivestreamPrize
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if err := db.Table("livestream_prizes").
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Where("activity_id = ?", activityID).
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Order("weight ASC").
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Find(&prizes).Error; err != nil {
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fmt.Printf("查询奖品失败: %v\n", err)
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return
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}
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if len(prizes) == 0 {
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fmt.Println("该活动没有配置奖品")
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return
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}
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var totalWeight int64
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for _, p := range prizes {
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totalWeight += int64(p.Weight)
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}
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fmt.Printf("总权重: %d\n\n", totalWeight)
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fmt.Printf("%-5s %-30s %-10s %-10s %-10s\n", "ID", "名称", "权重", "概率", "期望")
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fmt.Println("------------------------------------------------------------------------------------")
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for _, p := range prizes {
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prob := float64(p.Weight) / float64(totalWeight) * 100
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expected := int(float64(totalWeight) / float64(p.Weight))
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fmt.Printf("%-5d %-30s %-10d %-10.3f%% 1/%-10d\n",
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p.ID, p.Name, p.Weight, prob, expected)
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}
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// 3. 查询中奖记录
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fmt.Println("\n【中奖统计】")
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var drawLogs []LivestreamDrawLog
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if err := db.Table("livestream_draw_logs").
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Where("activity_id = ?", activityID).
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Find(&drawLogs).Error; err != nil {
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fmt.Printf("查询中奖记录失败: %v\n", err)
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return
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}
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if len(drawLogs) == 0 {
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fmt.Println("该活动还没有中奖记录")
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return
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}
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fmt.Printf("总抽奖次数: %d\n\n", len(drawLogs))
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// 统计每个奖品的中奖次数
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prizeStats := make(map[int64]int)
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for _, log := range drawLogs {
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prizeStats[log.PrizeID]++
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}
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// 创建奖品ID到奖品的映射
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prizeMap := make(map[int64]LivestreamPrize)
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for _, p := range prizes {
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prizeMap[p.ID] = p
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}
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// 分析每个奖品的实际中奖率
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fmt.Println("【实际中奖率分析】")
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fmt.Printf("%-5s %-30s %-10s %-10s %-10s %-10s %-10s\n",
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"ID", "名称", "权重", "理论概率", "实际次数", "实际概率", "偏差")
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fmt.Println("------------------------------------------------------------------------------------")
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type PrizeStat struct {
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Prize LivestreamPrize
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Count int
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TheoryProb float64
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ActualProb float64
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Diff float64
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}
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var stats []PrizeStat
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for _, p := range prizes {
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count := prizeStats[p.ID]
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theoryProb := float64(p.Weight) / float64(totalWeight) * 100
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actualProb := float64(count) / float64(len(drawLogs)) * 100
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diff := actualProb - theoryProb
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stats = append(stats, PrizeStat{
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Prize: p,
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Count: count,
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TheoryProb: theoryProb,
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ActualProb: actualProb,
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Diff: diff,
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})
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fmt.Printf("%-5d %-30s %-10d %-10.3f%% %-10d %-10.3f%% %+10.3f%%\n",
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p.ID, p.Name, p.Weight, theoryProb, count, actualProb, diff)
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}
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// 4. 分析大奖出现频率
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fmt.Println("\n【大奖分析】")
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var bigPrizeCount int
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var bigPrizeWeight int64
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var bigPrizeNames []string
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// 假设权重 <= 1000 的是大奖
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for _, stat := range stats {
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if stat.Prize.Weight <= 1000 {
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bigPrizeCount += stat.Count
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bigPrizeWeight += int64(stat.Prize.Weight)
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if stat.Count > 0 {
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bigPrizeNames = append(bigPrizeNames, fmt.Sprintf("%s(%d次)", stat.Prize.Name, stat.Count))
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}
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}
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}
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if bigPrizeWeight > 0 {
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bigPrizeTheory := float64(bigPrizeWeight) / float64(totalWeight) * 100
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bigPrizeActual := float64(bigPrizeCount) / float64(len(drawLogs)) * 100
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fmt.Printf("大奖定义: 权重 <= 1000\n")
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fmt.Printf("大奖总权重: %d\n", bigPrizeWeight)
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fmt.Printf("大奖理论概率: %.3f%% (1/%d)\n", bigPrizeTheory, int(float64(totalWeight)/float64(bigPrizeWeight)))
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fmt.Printf("大奖实际概率: %.3f%%\n", bigPrizeActual)
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fmt.Printf("大奖出现次数: %d / %d\n", bigPrizeCount, len(drawLogs))
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fmt.Printf("偏差: %+.3f%%\n", bigPrizeActual-bigPrizeTheory)
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if len(bigPrizeNames) > 0 {
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fmt.Printf("\n中奖明细: %v\n", bigPrizeNames)
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}
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// 判断是否异常
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fmt.Println()
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if bigPrizeActual > bigPrizeTheory*3 {
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fmt.Println("🔴 严重警告：大奖实际概率是理论概率的 3 倍以上！")
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fmt.Println(" 可能原因：")
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fmt.Println(" 1. 权重配置错误")
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fmt.Println(" 2. 随机数生成有问题")
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fmt.Println(" 3. 缓存未更新（修改权重后未重新生成随机位置）")
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} else if bigPrizeActual > bigPrizeTheory*2 {
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fmt.Println("🟠 警告：大奖实际概率是理论概率的 2 倍以上！")
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fmt.Println(" 建议检查权重配置和随机位置生成")
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} else if bigPrizeActual > bigPrizeTheory*1.5 {
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fmt.Println("🟡 注意：大奖实际概率偏高")
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fmt.Println(" 可能是统计波动，建议继续观察")
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} else {
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fmt.Println("✅ 大奖概率在正常范围内")
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}
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}
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// 5. 查询最近的中奖记录
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fmt.Println("\n【最近 20 次中奖记录】")
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var recentLogs []LivestreamDrawLog
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if err := db.Table("livestream_draw_logs").
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Where("activity_id = ?", activityID).
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Order("id DESC").
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Limit(20).
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Find(&recentLogs).Error; err != nil {
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fmt.Printf("查询中奖记录失败: %v\n", err)
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return
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}
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for _, log := range recentLogs {
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prize, ok := prizeMap[log.PrizeID]
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isBigPrize := ""
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if ok && prize.Weight <= 1000 {
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isBigPrize = " [大奖]"
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}
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fmt.Printf("ID: %d, 奖品: %s, 随机值: %d/%d%s\n",
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log.ID, log.PrizeName, log.RandValue, log.WeightsTotal, isBigPrize)
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}
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// 6. 随机值分布分析
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fmt.Println("\n【随机值分布分析】")
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if len(drawLogs) > 0 {
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// 检查随机值是否均匀分布
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bucketCount := 10
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buckets := make([]int, bucketCount)
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bucketSize := totalWeight / int64(bucketCount)
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for _, log := range drawLogs {
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if log.WeightsTotal > 0 {
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bucket := int(log.RandValue / bucketSize)
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if bucket >= bucketCount {
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bucket = bucketCount - 1
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}
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buckets[bucket]++
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}
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}
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fmt.Printf("将随机值范围 [0, %d) 分为 %d 个区间：\n", totalWeight, bucketCount)
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expectedPerBucket := float64(len(drawLogs)) / float64(bucketCount)
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for i, count := range buckets {
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start := int64(i) * bucketSize
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end := start + bucketSize
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if i == bucketCount-1 {
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end = totalWeight
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}
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deviation := (float64(count) - expectedPerBucket) / expectedPerBucket * 100
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fmt.Printf("区间 [%6d, %6d): %4d 次 (期望: %.1f, 偏差: %+.1f%%)\n",
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start, end, count, expectedPerBucket, deviation)
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}
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}
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}
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