218 lines
6.4 KiB
Go
218 lines
6.4 KiB
Go
package livestream
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import (
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"encoding/json"
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"testing"
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"bindbox-game/internal/repository/mysql/model"
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)
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// TestDiscreteRandomDistribution 测试随机离散分布的均匀性
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func TestDiscreteRandomDistribution(t *testing.T) {
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// 模拟实际奖品配置
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jsonData := `[{"id":58,"name":"Nu高达","weight":100},{"id":59,"name":"NT高达","weight":100},{"id":60,"name":"魔礼青","weight":100},{"id":61,"name":"维达尔","weight":100},{"id":62,"name":"玉衡星6号","weight":400},{"id":63,"name":"马克兔","weight":600},{"id":64,"name":"00高达","weight":700},{"id":65,"name":"SD随机款","weight":1100},{"id":66,"name":"兰博基尼","weight":3000},{"id":67,"name":"高达徽章","weight":28000},{"id":68,"name":"冰箱贴","weight":65800}]`
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var prizes []*model.LivestreamPrizes
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if err := json.Unmarshal([]byte(jsonData), &prizes); err != nil {
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t.Fatalf("解析奖品数据失败: %v", err)
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}
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// 计算总权重
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var totalWeight int32
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for _, p := range prizes {
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totalWeight += p.Weight
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}
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t.Logf("总权重: %d", totalWeight)
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// 生成随机离散位置
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state, err := GenerateDiscretePositions(1, prizes)
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if err != nil {
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t.Fatalf("生成随机离散位置失败: %v", err)
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}
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// 模拟10000次抽奖
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simulateCount := 10000
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results := make(map[int64]int)
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for i := 0; i < simulateCount; i++ {
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// 模拟随机值
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randValue := int32(i % int(totalWeight)) // 简化为顺序遍历，实际用crypto/rand
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// 查找对应的奖品
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for prizeID, positions := range state.PrizePosMap {
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for _, pos := range positions {
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if pos == randValue {
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results[prizeID]++
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break
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}
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}
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}
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}
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// 创建奖品ID到名称的映射
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prizeMap := make(map[int64]string)
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for _, p := range prizes {
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prizeMap[p.ID] = p.Name
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}
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// 输出统计结果
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t.Log("\n========== 随机离散分布测试结果 ==========")
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for _, p := range prizes {
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count := results[p.ID]
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theoryProb := float64(p.Weight) / float64(totalWeight) * 100
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actualProb := float64(count) / float64(simulateCount) * 100
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diff := actualProb - theoryProb
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t.Logf("%-20s 权重:%6d 理论:%6.2f%% 实际:%6.2f%% 偏差:%+6.2f%% 次数:%5d",
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p.Name, p.Weight, theoryProb, actualProb, diff, count)
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}
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}
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// TestContinuousVsDiscrete 对比连续区间和随机离散
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func TestContinuousVsDiscrete(t *testing.T) {
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// 简化奖品配置
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prizes := []*model.LivestreamPrizes{
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{ID: 1, Name: "大奖", Weight: 100},
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{ID: 2, Name: "小奖A", Weight: 3000},
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{ID: 3, Name: "小奖B", Weight: 3000},
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{ID: 4, Name: "冰箱贴", Weight: 65800},
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}
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totalWeight := int32(100 + 3000 + 3000 + 65800)
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t.Logf("\n========== 连续区间 vs 随机离散对比 ==========")
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t.Logf("总权重: %d", totalWeight)
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t.Log("")
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// 连续区间模拟
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t.Log("【连续区间方法】")
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t.Log("大奖区间: [0, 99] (0.1%)")
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t.Log("小奖A区间: [100, 3099] (3%)")
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t.Log("小奖B区间: [3100, 6099] (3%)")
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t.Log("冰箱贴区间: [6100, 71899] (65.8%)")
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t.Log("")
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// 随机离散模拟
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state, err := GenerateDiscretePositions(1, prizes)
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if err != nil {
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t.Fatalf("生成随机离散位置失败: %v", err)
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}
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t.Log("【随机离散方法】")
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t.Logf("大奖的随机位置数: %d", len(state.PrizePosMap[1]))
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t.Logf("小奖A的随机位置数: %d", len(state.PrizePosMap[2]))
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t.Logf("小奖B的随机位置数: %d", len(state.PrizePosMap[3]))
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t.Logf("冰箱贴的随机位置数: %d", len(state.PrizePosMap[4]))
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// 验证位置分布
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t.Log("\n位置分布示例（前10个）:")
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if positions, ok := state.PrizePosMap[1]; ok && len(positions) > 0 {
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sampleSize := 10
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if len(positions) < sampleSize {
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sampleSize = len(positions)
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}
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t.Logf("大奖位置: %v", positions[:sampleSize])
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}
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if positions, ok := state.PrizePosMap[4]; ok && len(positions) > 0 {
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sampleSize := 10
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if len(positions) < sampleSize {
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sampleSize = len(positions)
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}
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t.Logf("冰箱贴位置: %v", positions[:sampleSize])
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}
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}
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// TestEdgeCases 测试边界情况
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func TestEdgeCases(t *testing.T) {
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t.Run("空奖品列表", func(t *testing.T) {
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_, err := GenerateDiscretePositions(1, []*model.LivestreamPrizes{})
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if err == nil {
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t.Error("应该返回错误")
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}
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})
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t.Run("零权重", func(t *testing.T) {
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prizes := []*model.LivestreamPrizes{
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{ID: 1, Name: "奖品", Weight: 0},
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}
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_, err := GenerateDiscretePositions(1, prizes)
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if err == nil {
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t.Error("应该返回错误")
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}
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})
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t.Run("单个奖品", func(t *testing.T) {
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prizes := []*model.LivestreamPrizes{
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{ID: 1, Name: "唯一奖品", Weight: 1000},
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}
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state, err := GenerateDiscretePositions(1, prizes)
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if err != nil {
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t.Fatalf("不应该出错: %v", err)
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}
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if len(state.PrizePosMap[1]) != 1000 {
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t.Errorf("位置数量错误，期望1000，实际%d", len(state.PrizePosMap[1]))
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}
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})
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}
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// TestPositionUniqueness 测试位置的唯一性
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func TestPositionUniqueness(t *testing.T) {
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prizes := []*model.LivestreamPrizes{
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{ID: 1, Name: "大奖", Weight: 100},
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{ID: 2, Name: "小奖", Weight: 3000},
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{ID: 3, Name: "冰箱贴", Weight: 65800},
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}
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state, err := GenerateDiscretePositions(1, prizes)
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if err != nil {
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t.Fatalf("生成失败: %v", err)
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}
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// 收集所有位置
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allPositions := make(map[int32]int64)
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for prizeID, positions := range state.PrizePosMap {
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for _, pos := range positions {
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if existingPrizeID, exists := allPositions[pos]; exists {
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t.Errorf("位置 %d 被多个奖品占用: 奖品%d 和 奖品%d", pos, existingPrizeID, prizeID)
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}
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allPositions[pos] = prizeID
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}
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}
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expectedCount := 100 + 3000 + 65800
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if len(allPositions) != expectedCount {
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t.Errorf("位置总数错误，期望%d，实际%d", expectedCount, len(allPositions))
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}
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t.Logf("位置唯一性验证通过: %d 个唯一位置", len(allPositions))
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}
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// BenchmarkDiscreteVsContinuous 性能对比测试
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func BenchmarkDiscreteGeneration(b *testing.B) {
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prizes := []*model.LivestreamPrizes{
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{ID: 1, Name: "大奖", Weight: 100},
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{ID: 2, Name: "小奖A", Weight: 3000},
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{ID: 3, Name: "小奖B", Weight: 3000},
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{ID: 4, Name: "冰箱贴", Weight: 65800},
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}
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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_, err := GenerateDiscretePositions(int64(i), prizes)
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if err != nil {
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b.Fatal(err)
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}
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}
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}
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// 打印结果辅助函数
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func printResults(t *testing.T, results map[int64]int, prizes []*model.LivestreamPrizes, simulateCount int) {
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t.Log("\n========== 测试结果 ==========")
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for _, p := range prizes {
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count := results[p.ID]
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t.Logf("%-20s 中奖次数: %d (%.2f%%)", p.Name, count, float64(count)/float64(simulateCount)*100)
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}
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}
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