feat: 新增一个雨量融合的工具
This commit is contained in:
parent
cbeb623f20
commit
8797af23b5
@ -9,6 +9,7 @@ import (
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"log"
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"log"
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"math"
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"math"
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"os"
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"os"
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"sort"
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"strings"
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"strings"
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"time"
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"time"
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@ -25,6 +26,7 @@ const (
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var (
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var (
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defaultWeights = []float64{0.4, 0.3, 0.3}
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defaultWeights = []float64{0.4, 0.3, 0.3}
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asiaShanghai *time.Location
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asiaShanghai *time.Location
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debugEnabled bool
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)
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)
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func init() {
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func init() {
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@ -107,6 +109,8 @@ func main() {
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flag.IntVar(&minSources, "min_sources", 2, "最少参与融合的预报源个数(2或3)，不足则跳过")
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flag.IntVar(&minSources, "min_sources", 2, "最少参与融合的预报源个数(2或3)，不足则跳过")
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flag.StringVar(&maskHoursStr, "mask_hours", "1,1,1", "逐小时掩码开关(h+1,h+2,h+3)，如: 1,1,0")
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flag.StringVar(&maskHoursStr, "mask_hours", "1,1,1", "逐小时掩码开关(h+1,h+2,h+3)，如: 1,1,0")
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flag.Parse()
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flag.Parse()
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// 让库内辅助函数也能访问调试开关
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debugEnabled = debugLog
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if strings.TrimSpace(issuedRange) == "" {
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if strings.TrimSpace(issuedRange) == "" {
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log.Fatalln("必须提供 --issued_range")
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log.Fatalln("必须提供 --issued_range")
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@ -195,7 +199,7 @@ func main() {
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for _, job := range jobs {
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for _, job := range jobs {
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info := job.info
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info := job.info
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maskCtx, hasMaskCtx := buildMaskContext(info)
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maskCtx, hasMaskCtx := buildMaskContext(info)
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weights := append([]float64{}, defaultWeights...)
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stWeights := newWeightState(job.providers)
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for idx, issued := range job.issuedTimes {
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for idx, issued := range job.issuedTimes {
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matrix, err := loadProviderMatrix(db, info.ID, issued, job.providers)
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matrix, err := loadProviderMatrix(db, info.ID, issued, job.providers)
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@ -212,12 +216,54 @@ func main() {
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}
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}
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if debugLog {
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if debugLog {
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log.Printf("权重(使用前): station=%s issued=%s %s=%.2f %s=%.2f %s=%.2f",
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log.Printf("")
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info.ID, issued.Format("2006-01-02 15:04:05"),
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log.Printf("issue %s station=%s", issued.Format("2006-01-02 15:04:05"), info.ID)
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job.providers[0], weights[0], job.providers[1], weights[1], job.providers[2], weights[2])
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}
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}
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fused := fuseForecastsWith(matrix, effectiveWeights(weights, job.providers, matrix))
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// 学习先行：先得到学习前权重，再学习，再得到本轮使用权重
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effBefore, _ := stWeights.effectiveForMatrix(matrix)
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// 学习对齐：用刚结束的小时 [issued-1h, issued) 与 (issued-2h) 的 +1 预测
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learnStart := issued.Add(-time.Hour)
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learnEnd := issued
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actualRain, actualOK, err := fetchActualHourlyRain(db, info.ID, learnStart, learnEnd)
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if err != nil {
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log.Printf("站点 %s issued=%s 聚合实况失败: %v", info.ID, issued.Format(time.RFC3339), err)
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} else if actualOK {
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prevIssueBucket := issued.Add(-2 * time.Hour)
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preds := make([]float64, len(matrix))
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valids := make([]bool, len(matrix))
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for i, pm := range matrix {
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if v, ok := lead1RainAtIssued(db, info.ID, pm.Provider, prevIssueBucket); ok {
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preds[i] = v
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valids[i] = true
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}
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}
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if debugLog {
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log.Printf("在 [%s,%s) ，该小时本站实况雨量累计为:%.3f，预报源在 issue=%s 发布的 +1h %s-%s 预报值是 %s",
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learnStart.Format("15:04"), learnEnd.Format("15:04"), actualRain,
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prevIssueBucket.Format("15:04"), learnStart.Format("15:04"), learnEnd.Format("15:04"),
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formatWeights(preds, false))
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}
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stWeights.learnFromPreds(matrix, preds, valids, actualRain)
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}
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eff, _ := stWeights.effectiveForMatrix(matrix)
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if debugLog {
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// 以 provider=weight 的形式输出，顺序与 sources 一致
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toNamed := func(ws []float64) string {
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pairs := make([]string, 0, len(matrix))
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for i, pm := range matrix {
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pairs = append(pairs, fmt.Sprintf("%s=%.2f", pm.Provider, ws[i]))
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}
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return strings.Join(pairs, ", ")
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}
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log.Printf("学习前权重 %s ，本轮使用权重 %s", toNamed(effBefore), toNamed(eff))
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}
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fused := fuseForecastsWith(matrix, eff)
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// 记录掩码前的融合雨量
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var preMaskRain = []float64{fused[0].Rain, fused[1].Rain, fused[2].Rain}
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rainAllZero := isRainAllZero(fused)
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rainAllZero := isRainAllZero(fused)
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maskApplied := false
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maskApplied := false
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@ -242,11 +288,17 @@ func main() {
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}
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}
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}
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}
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if debugLog {
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if debugLog {
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log.Printf("掩码报告: station=%s issued=%s scanned=%v windOK=%v used=%s wind=%.2fm/s %.0f° tiles=%d hits=[%d,%d,%d] mask_hours=%v", info.ID, issued.Format("2006-01-02 15:04:05"), rep.Scanned, rep.WindOK, rep.UsedAlias, rep.WindSpeed, rep.WindDir, rep.Tiles, rep.HitsByHour[0], rep.HitsByHour[1], rep.HitsByHour[2], maskHours)
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log.Printf("mask t=%s wind=%.1fm/s %.0f° tiles=%d hits=[%d,%d,%d] applied=%v",
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issued.Format("2006-01-02 15:04:05"), rep.WindSpeed, rep.WindDir, rep.Tiles, rep.HitsByHour[0], rep.HitsByHour[1], rep.HitsByHour[2], maskApplied)
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}
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}
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}
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}
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}
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}
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if debugLog {
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// 展示预报与掩码后的融合雨量 [h+1,h+2,h+3]
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rp := []float64{fused[0].Rain, fused[1].Rain, fused[2].Rain}
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log.Printf("预报 %s , mask=%v , 融合的结果 %s", formatWeights(preMaskRain, false), maskApplied, formatWeights(rp, false))
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}
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for h := 1; h <= 3; h++ {
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for h := 1; h <= 3; h++ {
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results = append(results, fusedRecord{
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results = append(results, fusedRecord{
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StationID: info.ID,
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StationID: info.ID,
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@ -257,20 +309,7 @@ func main() {
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})
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})
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}
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}
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actualRain, actualOK, err := fetchActualHourlyRain(db, info.ID, issued, issued.Add(time.Hour))
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// 学习已在融合前完成
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if err != nil {
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log.Printf("站点 %s issued=%s 聚合实况失败: %v", info.ID, issued.Format(time.RFC3339), err)
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} else if actualOK {
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before := append([]float64{}, weights...)
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weights = adjustWeightsSubset(weights, job.providers, matrix, actualRain)
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if debugLog {
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log.Printf("权重调整: station=%s issued=%s actual=%.3f | 之前[%s=%.2f,%s=%.2f,%s=%.2f] 之后[%s=%.2f,%s=%.2f,%s=%.2f] 参与源=%d",
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info.ID, issued.Format("2006-01-02 15:04:05"), actualRain,
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job.providers[0], before[0], job.providers[1], before[1], job.providers[2], before[2],
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job.providers[0], weights[0], job.providers[1], weights[1], job.providers[2], weights[2],
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len(matrix))
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}
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}
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step++
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step++
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if progressFn != nil {
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if progressFn != nil {
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@ -554,6 +593,19 @@ func loadForecastSamples(db *sql.DB, stationID, provider string, issued time.Tim
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return list, nil
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return list, nil
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}
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}
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// lead1RainAtIssued 返回某站点、某provider在给定小时桶(J)内的发行的 +1 小时降雨预测（若存在）。
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func lead1RainAtIssued(db *sql.DB, stationID, provider string, bucketHour time.Time) (float64, bool) {
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issued, ok, err := resolveIssuedAtInBucket(db, stationID, provider, bucketHour)
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if err != nil || !ok {
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return 0, false
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}
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samples, err := loadForecastSamples(db, stationID, provider, issued)
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if err != nil || len(samples) < 1 {
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return 0, false
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}
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return samples[0].Rain, true
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}
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func fuseForecasts(matrix []providerMatrix, weights []float64) []forecastSample {
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func fuseForecasts(matrix []providerMatrix, weights []float64) []forecastSample {
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result := make([]forecastSample, 3)
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result := make([]forecastSample, 3)
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for h := 0; h < 3; h++ {
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for h := 0; h < 3; h++ {
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@ -646,36 +698,204 @@ func uniform(n int) []float64 {
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return w
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return w
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}
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}
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// effectiveWeights 将基础权重映射到参与融合的 providers（按 matrix 顺序），并在子集上归一化
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// weightState: 维护三源与各二源对的基础权重
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func effectiveWeights(base []float64, providersAll []string, matrix []providerMatrix) []float64 {
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type weightState struct {
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m := make(map[string]int)
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providersAll []string
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for i, p := range providersAll {
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baseTriad []float64 // [om, cy, im] 按 providersAll 对齐
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m[p] = i
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basePairs map[string][]float64 // 保留字段但不再使用成对权重
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}
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lastPresent map[string]bool // 上一次有效参与的provider集合
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eff := make([]float64, len(matrix))
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lastEff map[string]float64 // 上一次按provider的有效权重（仅在场时更新）
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sum := 0.0
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for i, pm := range matrix {
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if idx, ok := m[pm.Provider]; ok {
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eff[i] = base[idx]
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sum += eff[i]
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}
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}
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if sum <= 0 {
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return uniform(len(matrix))
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}
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for i := range eff {
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eff[i] /= sum
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}
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return eff
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}
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}
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// adjustWeightsSubset 仅对当前参与的 providers 调整权重，其它分量保持不变
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func newWeightState(providersAll []string) *weightState {
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func adjustWeightsSubset(base []float64, providersAll []string, matrix []providerMatrix, actual float64) []float64 {
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ws := &weightState{providersAll: providersAll}
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preds := extractProviderRainAt(matrix, 0)
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ws.baseTriad = append([]float64{}, defaultWeights...)
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if len(preds) == 0 {
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ws.basePairs = map[string][]float64{}
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return base
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ws.lastPresent = map[string]bool{}
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ws.lastEff = map[string]float64{}
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return ws
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}
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func (ws *weightState) idx(p string) int {
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for i, v := range ws.providersAll {
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if v == p {
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return i
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}
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}
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// 找最优和最差（绝对误差）
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}
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return 0
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}
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func pairKey(a, b string) string {
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if a < b {
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return a + "|" + b
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}
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return b + "|" + a
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}
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// providersList: 用于debug展示参与源
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func providersList(matrix []providerMatrix) string {
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names := make([]string, len(matrix))
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for i, pm := range matrix {
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names[i] = pm.Provider
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}
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return fmt.Sprintf("%v", names)
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}
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// formatWeights 将权重格式化为字符串，如 "[0.70,0.10,0.20]"
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// 若 quantizeTenths=true，则先按 0.1 就近取整再输出两位小数
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func formatWeights(ws []float64, quantizeTenths bool) string {
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if len(ws) == 0 {
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return "[]"
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}
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var parts []string
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for _, v := range ws {
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if quantizeTenths {
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v = math.Round(v*10.0) / 10.0
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}
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parts = append(parts, fmt.Sprintf("%.2f", v))
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}
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return "[" + strings.Join(parts, ",") + "]"
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}
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// effectiveForMatrix: 返回与 matrix 顺序对齐的有效权重（两源/三源），在子集上归一化
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func (ws *weightState) effectiveForMatrix(matrix []providerMatrix) ([]float64, bool) {
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// 根据当前在场provider集合，对 triad 进行“缺失转移/新增分配”并输出有效权重。
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n := len(matrix)
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eff := make([]float64, n)
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if n == 0 {
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return eff, false
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}
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// 建立当前在场集合
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present := make(map[string]bool, n)
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for _, pm := range matrix {
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present[pm.Provider] = true
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}
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// 识别缺失与新增
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var missing []string
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var added []string
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if len(ws.lastPresent) == 0 {
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// 首次：按照 providersAll 判断缺失（需要立即应用缺失转移）
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for _, p := range ws.providersAll {
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if !present[p] {
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missing = append(missing, p)
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}
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}
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} else {
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for p := range ws.lastPresent {
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if !present[p] {
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missing = append(missing, p)
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}
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}
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for p := range present {
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if !ws.lastPresent[p] {
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added = append(added, p)
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}
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}
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}
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if debugEnabled && (len(missing) > 0 || len(added) > 0) {
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// 稳定顺序：按 providersAll 顺序输出 present/added/removed
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presList := make([]string, 0, len(present))
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for _, p := range ws.providersAll {
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if present[p] {
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presList = append(presList, p)
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}
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}
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// added/missing 也按 providersAll 顺序
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orderIdx := func(p string) int { return ws.idx(p) }
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sort.Slice(added, func(i, j int) bool { return orderIdx(added[i]) < orderIdx(added[j]) })
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sort.Slice(missing, func(i, j int) bool { return orderIdx(missing[i]) < orderIdx(missing[j]) })
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log.Printf("sources %v added=%v removed=%v", presList, added, missing)
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}
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// 缺失：将缺失源的权重转移给当前在场中权重最大的源，缺失源置0
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if len(missing) > 0 && len(present) > 0 {
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// 找当前在场的最大权重源
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maxP := ""
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maxW := -1.0
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for p := range present {
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w := ws.baseTriad[ws.idx(p)]
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if w > maxW {
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maxW, maxP = w, p
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}
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}
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gain := 0.0
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for _, m := range missing {
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w := ws.baseTriad[ws.idx(m)]
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if w > 0 {
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gain += w
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ws.baseTriad[ws.idx(m)] = 0
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}
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}
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if maxP != "" && gain > 0 {
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ws.baseTriad[ws.idx(maxP)] += gain
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if debugEnabled {
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tri := []float64{ws.baseTriad[ws.idx(providerOpenMeteo)], ws.baseTriad[ws.idx(providerCaiyun)], ws.baseTriad[ws.idx(providerImdroid)]}
|
||||||
|
log.Printf("removed %v -> %s +%.2f triad %s",
|
||||||
|
missing, maxP, gain, formatWeights(tri, true))
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
// 新增：从当前最大源挪出0.2给新加入的源（每个新增一次性处理）
|
||||||
|
for _, a := range added {
|
||||||
|
// 仅在此前为0时进行分配，避免重复分配
|
||||||
|
if ws.baseTriad[ws.idx(a)] <= 0 {
|
||||||
|
// 找在场的最大源（不包含自身）
|
||||||
|
maxP := ""
|
||||||
|
maxW := -1.0
|
||||||
|
for p := range present {
|
||||||
|
if p == a {
|
||||||
|
continue
|
||||||
|
}
|
||||||
|
w := ws.baseTriad[ws.idx(p)]
|
||||||
|
if w > maxW {
|
||||||
|
maxW, maxP = w, p
|
||||||
|
}
|
||||||
|
}
|
||||||
|
if maxP != "" && maxW > 0 {
|
||||||
|
delta := 0.2
|
||||||
|
if maxW < delta {
|
||||||
|
delta = maxW
|
||||||
|
}
|
||||||
|
ws.baseTriad[ws.idx(maxP)] -= delta
|
||||||
|
ws.baseTriad[ws.idx(a)] += delta
|
||||||
|
if debugEnabled {
|
||||||
|
tri := []float64{ws.baseTriad[ws.idx(providerOpenMeteo)], ws.baseTriad[ws.idx(providerCaiyun)], ws.baseTriad[ws.idx(providerImdroid)]}
|
||||||
|
log.Printf("added %s from %s %.2f triad %s",
|
||||||
|
a, maxP, delta, formatWeights(tri, true))
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
// 更新 lastPresent 为当前集合
|
||||||
|
ws.lastPresent = present
|
||||||
|
|
||||||
|
// 组装有效权重，按 matrix 顺序输出。此时 triad 在场分量应合计为1。
|
||||||
|
for i, pm := range matrix {
|
||||||
|
eff[i] = ws.baseTriad[ws.idx(pm.Provider)]
|
||||||
|
}
|
||||||
|
// 不在此处打印权重对比，由主循环根据“学习前/后”输出
|
||||||
|
// 更新上一次有效权重
|
||||||
|
for i, pm := range matrix {
|
||||||
|
ws.lastEff[pm.Provider] = eff[i]
|
||||||
|
}
|
||||||
|
return eff, false
|
||||||
|
}
|
||||||
|
|
||||||
|
// learn: 只在本集合中做 +0.1/-0.1，学习后在该集合内归一化，并写回对应的基础权重集
|
||||||
|
func (ws *weightState) learn(matrix []providerMatrix, actual float64) {
|
||||||
|
n := len(matrix)
|
||||||
|
if n <= 1 {
|
||||||
|
return
|
||||||
|
}
|
||||||
|
preds := extractProviderRainAt(matrix, 0)
|
||||||
|
if len(preds) != n {
|
||||||
|
return
|
||||||
|
}
|
||||||
|
// 找出当前在场集合中的最优与最差
|
||||||
best, worst := 0, 0
|
best, worst := 0, 0
|
||||||
for i := range preds {
|
for i := range preds {
|
||||||
if math.Abs(preds[i]-actual) < math.Abs(preds[best]-actual) {
|
if math.Abs(preds[i]-actual) < math.Abs(preds[best]-actual) {
|
||||||
@ -685,35 +905,87 @@ func adjustWeightsSubset(base []float64, providersAll []string, matrix []provide
|
|||||||
worst = i
|
worst = i
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
// provider 名到 base 索引
|
|
||||||
m := make(map[string]int)
|
alpha := 0.1
|
||||||
for i, p := range providersAll {
|
pBest := matrix[best].Provider
|
||||||
m[p] = i
|
pWorst := matrix[worst].Provider
|
||||||
|
|
||||||
|
// 仅在在场集合中调整，第三方可能为0（绝对不可信）且不参与两源学习
|
||||||
|
decCap := ws.baseTriad[ws.idx(pWorst)]
|
||||||
|
delta := alpha
|
||||||
|
if decCap < delta {
|
||||||
|
delta = decCap
|
||||||
}
|
}
|
||||||
out := append([]float64{}, base...)
|
if delta <= 0 {
|
||||||
// 应用 ±0.1 调整
|
return
|
||||||
if bi, ok := m[matrix[best].Provider]; ok {
|
|
||||||
out[bi] += 0.1
|
|
||||||
}
|
}
|
||||||
if wi, ok := m[matrix[worst].Provider]; ok {
|
prev := append([]float64{}, ws.baseTriad...)
|
||||||
out[wi] -= 0.1
|
ws.baseTriad[ws.idx(pWorst)] -= delta
|
||||||
|
ws.baseTriad[ws.idx(pBest)] += delta
|
||||||
|
if debugEnabled {
|
||||||
|
before := []float64{prev[ws.idx(providerOpenMeteo)], prev[ws.idx(providerCaiyun)], prev[ws.idx(providerImdroid)]}
|
||||||
|
after := []float64{ws.baseTriad[ws.idx(providerOpenMeteo)], ws.baseTriad[ws.idx(providerCaiyun)], ws.baseTriad[ws.idx(providerImdroid)]}
|
||||||
|
log.Printf("rain=%.3f best=%s worst=%s weights %s -> %s",
|
||||||
|
actual, pBest, pWorst, formatWeights(before, true), formatWeights(after, true))
|
||||||
}
|
}
|
||||||
// 夹紧并归一化
|
}
|
||||||
sum := 0.0
|
|
||||||
for i := range out {
|
// learnFromPreds: 使用外部提供的预测值（与 matrix 顺序对齐）进行学习。
|
||||||
if out[i] < 0 {
|
func (ws *weightState) learnFromPreds(matrix []providerMatrix, preds []float64, valids []bool, actual float64) {
|
||||||
out[i] = 0
|
n := len(matrix)
|
||||||
|
if n == 0 || len(preds) != n || len(valids) != n {
|
||||||
|
return
|
||||||
}
|
}
|
||||||
sum += out[i]
|
// 仅在有效的、且当前权重>0 的来源中选择最优/最差
|
||||||
|
idxs := make([]int, 0, n)
|
||||||
|
for i := 0; i < n; i++ {
|
||||||
|
if !valids[i] {
|
||||||
|
continue
|
||||||
}
|
}
|
||||||
if sum == 0 {
|
idxs = append(idxs, i)
|
||||||
// 回到默认
|
|
||||||
return append([]float64{}, defaultWeights...)
|
|
||||||
}
|
}
|
||||||
for i := range out {
|
if len(idxs) < 2 {
|
||||||
out[i] /= sum
|
return
|
||||||
|
}
|
||||||
|
best, worst := idxs[0], idxs[0]
|
||||||
|
for _, i := range idxs {
|
||||||
|
if math.Abs(preds[i]-actual) < math.Abs(preds[best]-actual) {
|
||||||
|
best = i
|
||||||
|
}
|
||||||
|
if math.Abs(preds[i]-actual) > math.Abs(preds[worst]-actual) {
|
||||||
|
worst = i
|
||||||
|
}
|
||||||
|
}
|
||||||
|
alpha := 0.1
|
||||||
|
pBest := matrix[best].Provider
|
||||||
|
pWorst := matrix[worst].Provider
|
||||||
|
decCap := ws.baseTriad[ws.idx(pWorst)]
|
||||||
|
delta := alpha
|
||||||
|
if decCap < delta {
|
||||||
|
delta = decCap
|
||||||
|
}
|
||||||
|
if delta <= 0 {
|
||||||
|
return
|
||||||
|
}
|
||||||
|
// 日志：绝对误差详情（OM/CY/IM）和最优/最差
|
||||||
|
if debugEnabled {
|
||||||
|
name := func(p string) string { return p }
|
||||||
|
// 组装当前在场源的误差摘要
|
||||||
|
parts := make([]string, 0, len(matrix))
|
||||||
|
for i, pm := range matrix {
|
||||||
|
if !valids[i] || ws.baseTriad[ws.idx(pm.Provider)] <= 0 {
|
||||||
|
continue
|
||||||
|
}
|
||||||
|
parts = append(parts, fmt.Sprintf("%s |%.2f-%.3f|=%.3f", name(pm.Provider), preds[i], actual, math.Abs(preds[i]-actual)))
|
||||||
|
}
|
||||||
|
log.Printf("绝对误差：%s → best=%s，worst=%s。", strings.Join(parts, "，"), name(pBest), name(pWorst))
|
||||||
|
}
|
||||||
|
ws.baseTriad[ws.idx(pWorst)] -= delta
|
||||||
|
ws.baseTriad[ws.idx(pBest)] += delta
|
||||||
|
if debugEnabled {
|
||||||
|
after := []float64{ws.baseTriad[ws.idx(providerOpenMeteo)], ws.baseTriad[ws.idx(providerCaiyun)], ws.baseTriad[ws.idx(providerImdroid)]}
|
||||||
|
log.Printf("按规则：best +0.1，worst −0.1 → 权重在下一轮将为 %s", formatWeights(after, true))
|
||||||
}
|
}
|
||||||
return out
|
|
||||||
}
|
}
|
||||||
|
|
||||||
// probeProviderAtBucket: 调试辅助，打印该小时桶内每个provider的issued与是否有+1/+2/+3样本
|
// probeProviderAtBucket: 调试辅助，打印该小时桶内每个provider的issued与是否有+1/+2/+3样本
|
||||||
|
|||||||
Loading…
x
Reference in New Issue
Block a user