feat: 新增雷达图
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6bc0610c2d
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@ -339,12 +339,13 @@ func intFromMeta(m map[string]any, key string) int {
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// radarLatestWindHandler queries Caiyun realtime wind for the latest query candidates
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// and provides per-cluster aggregated wind and basic coming/ETA analysis toward station.
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func radarLatestWindHandler(c *gin.Context) {
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// Constants per user request
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// 使用极坐标法：对每个云团仅在质心取一次风，直接判定靠近与ETA
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// 常量：目标点（站点/雷达点）坐标
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const (
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stationLat = 23.097234
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stationLon = 108.715433
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)
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// Read latest metadata into struct
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// 读取最新元数据
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latestRoot := "./radar_data/latest"
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metaPath := latestRoot + "/metadata.json"
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b, err := os.ReadFile(metaPath)
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@ -357,7 +358,8 @@ func radarLatestWindHandler(c *gin.Context) {
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c.JSON(http.StatusInternalServerError, gin.H{"error": "解析元数据失败"})
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return
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}
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// For each query candidate, call Caiyun
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// 输出结构保持兼容：仍提供 candidates，但每个cluster仅一个（质心）
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type Wind struct {
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Speed float64 `json:"speed_ms"`
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DirFrom float64 `json:"dir_from_deg"`
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@ -373,29 +375,38 @@ func radarLatestWindHandler(c *gin.Context) {
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Wind *Wind `json:"wind,omitempty"`
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Error string `json:"error,omitempty"`
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}
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outs := make([]CandOut, 0, len(meta.QueryCandidates))
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for _, q := range meta.QueryCandidates {
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speed, dirFrom, tempC, rh, pPa, err := rf.FetchCaiyunRealtime(q.Lon, q.Lat)
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co := CandOut{QueryCandidate: q}
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if err != nil {
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co.Error = err.Error()
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} else {
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dirTo := mathMod(dirFrom+180.0, 360.0)
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u, v := windVectorUV(speed, dirTo)
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// pressure in hPa for display
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pHpa := pPa / 100.0
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co.Wind = &Wind{Speed: speed, DirFrom: dirFrom, DirTo: dirTo, U: u, V: v, TempC: tempC, RH: rh, PressureHpa: pHpa}
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outs := make([]CandOut, 0, len(meta.Clusters))
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// 工具函数
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mPerDegLat := 111320.0
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mPerDegLon := func(lat float64) float64 { return 111320.0 * math.Cos(lat*math.Pi/180.0) }
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// 计算极坐标ETA（到站点本身，不再使用侧向与半径作为命中条件）
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approachETA := func(lonC, latC, speedMS, dirToDeg, lonS, latS float64) (coming bool, etaMin float64, distanceKm float64, vrMS float64) {
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wx := mPerDegLon(latC)
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wy := mPerDegLat
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dx := (lonS - lonC) * wx // 东向米
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dy := (latS - latC) * wy // 北向米
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D := math.Hypot(dx, dy)
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if D == 0 {
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return true, 0, 0, speedMS
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}
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outs = append(outs, co)
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// 云→站方位角（北=0，顺时针）
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theta := math.Atan2(dx, dy) * 180 / math.Pi
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if theta < 0 {
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theta += 360
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}
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// Aggregate by cluster id
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agg := map[int][]Wind{}
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for _, co := range outs {
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if co.Wind == nil {
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continue
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beta := mathMod(dirToDeg, 360.0)
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delta := (beta - theta) * math.Pi / 180.0
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vr := speedMS * math.Cos(delta) // 指向站点的径向速度
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if vr <= 0 {
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return false, -1, D / 1000.0, vr
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}
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agg[co.ClusterID] = append(agg[co.ClusterID], *co.Wind)
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etaSec := D / vr
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return true, etaSec / 60.0, D / 1000.0, vr
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}
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// 为每个云团质心取一次风，构造 candidates 与 per-cluster 分析
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type ClusterAnal struct {
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ClusterID int `json:"cluster_id"`
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Lon float64 `json:"lon"`
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@ -411,77 +422,64 @@ func radarLatestWindHandler(c *gin.Context) {
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DistanceKm float64 `json:"distance_km"`
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LateralKm float64 `json:"lateral_km"`
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RCloudKm float64 `json:"r_cloud_km"`
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VrMS float64 `json:"vr_ms"`
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}
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analyses := []ClusterAnal{}
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// helpers
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mPerDegLat := 111320.0
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mPerDegLon := func(lat float64) float64 { return 111320.0 * math.Cos(lat*math.Pi/180.0) }
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cellDims := func(lat float64) (float64, float64) { // width (lon), height (lat) in meters per pixel
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// 等效云半径与侧向距离仅用于展示（不再作为判定条件）
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cellDims := func(lat float64) (float64, float64) { // 每像素米宽/米高
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return meta.ResDeg * mPerDegLon(lat), meta.ResDeg * mPerDegLat
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}
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const hitRadiusM = 5000.0
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for _, cl := range meta.Clusters {
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winds := agg[cl.ID]
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if len(winds) == 0 {
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// 取质心风
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speed, dirFrom, tempC, rh, pPa, err := rf.FetchCaiyunRealtime(cl.Lon, cl.Lat)
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q := rf.QueryCandidate{ClusterID: cl.ID, Role: "center", Lon: cl.Lon, Lat: cl.Lat}
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co := CandOut{QueryCandidate: q}
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if err != nil {
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co.Error = err.Error()
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outs = append(outs, co)
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// 即便取风失败，也继续下一个云团
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continue
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}
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// vector average in u,v (to-direction)
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sumU, sumV := 0.0, 0.0
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for _, wv := range winds {
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sumU += wv.U
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sumV += wv.V
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}
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u := sumU / float64(len(winds))
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v := sumV / float64(len(winds))
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speed := math.Hypot(u, v)
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dirTo := uvToDirTo(u, v)
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// project geometry
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dirTo := mathMod(dirFrom+180.0, 360.0)
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u, v := windVectorUV(speed, dirTo)
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pHpa := pPa / 100.0
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co.Wind = &Wind{Speed: speed, DirFrom: dirFrom, DirTo: dirTo, U: u, V: v, TempC: tempC, RH: rh, PressureHpa: pHpa}
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outs = append(outs, co)
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// 极坐标法靠近/ETA（到站点）
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coming, etaMin, distKm, vr := approachETA(cl.Lon, cl.Lat, speed, dirTo, stationLon, stationLat)
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// 展示参数：侧向距与等效半径
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// 侧向距 = 距离向量对速度方向单位向量的叉积绝对值
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wx, wy := mPerDegLon(cl.Lat), mPerDegLat
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// position of cluster and station in meters (local tangent plane)
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px := (cl.Lon - stationLon) * wx
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py := (cl.Lat - stationLat) * wy
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// vector from cluster to station
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dx := -px
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dy := -py
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d := math.Hypot(dx, dy)
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// radial component of velocity towards station
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if d == 0 {
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d = 1e-6
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}
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vr := (dx*u + dy*v) / d
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// cluster equivalent radius
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cw, ch := cellDims(cl.Lat)
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areaM2 := float64(cl.AreaPx) * cw * ch
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rCloud := math.Sqrt(areaM2 / math.Pi)
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// lateral offset (perpendicular distance from station line)
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px := (stationLon - cl.Lon) * wx
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py := (stationLat - cl.Lat) * wy
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vnorm := math.Hypot(u, v)
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lateral := 0.0
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if vnorm > 0 {
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// |d x vhat|
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vx, vy := u/vnorm, v/vnorm
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lateral = math.Abs(dx*vy - dy*vx)
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}
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coming := vr > 0 && lateral <= (rCloud+hitRadiusM)
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etaMin := 0.0
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if coming && vr > 0 {
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distToEdge := d - (rCloud + hitRadiusM)
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if distToEdge < 0 {
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distToEdge = 0
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}
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etaMin = distToEdge / vr / 60.0
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lateral = math.Abs(px*vy - py*vx)
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}
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cw, ch := cellDims(cl.Lat)
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areaM2 := float64(cl.AreaPx) * cw * ch
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rCloud := math.Sqrt(areaM2 / math.Pi)
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analyses = append(analyses, ClusterAnal{
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ClusterID: cl.ID,
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Lon: cl.Lon, Lat: cl.Lat,
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AreaPx: cl.AreaPx, MaxDBZ: cl.MaxDBZ,
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SpeedMS: speed, DirToDeg: dirTo, U: u, V: v,
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Coming: coming, ETAMin: round2(etaMin),
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DistanceKm: round2(d / 1000.0), LateralKm: round2(lateral / 1000.0), RCloudKm: round2(rCloud / 1000.0),
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DistanceKm: round2(distKm), LateralKm: round2(lateral / 1000.0), RCloudKm: round2(rCloud / 1000.0),
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VrMS: round2(vr),
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})
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}
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c.JSON(http.StatusOK, gin.H{
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"station": gin.H{"lon": stationLon, "lat": stationLat},
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"params": meta.QueryParams,
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"params": meta.QueryParams, // 兼容保留
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"candidates": outs,
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"clusters": analyses,
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})
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@ -720,7 +720,7 @@
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window.RadarLatestGrid = data;
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renderPlotlyHeat(data);
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renderClustersPanel();
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renderWindQueryList();
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renderMethodNote();
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renderWindResults();
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}
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@ -838,11 +838,7 @@
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+ '质心: '+cl.lon.toFixed(4)+', '+cl.lat.toFixed(4)+'<br/>'
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+ 'dBZ: max '+cl.max_dbz.toFixed(1)+' / avg '+cl.avg_dbz.toFixed(1)
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+ '</div>';
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if (cl.samples && cl.samples.length) {
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html += '<div class="mt-1 text-xs text-gray-600">采样点: ' + cl.samples.map(function(s){
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return s.role+':('+s.lon.toFixed(3)+','+s.lat.toFixed(3)+')';
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}).join(' | ') + '</div>';
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}
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// 极坐标法：不再展示采样点列表（仅使用质心）
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html += '</div>';
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});
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html += '</div>';
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@ -850,11 +846,7 @@
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}).catch(function(){ /* ignore */ });
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}
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function renderWindQueryList(){
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fetch('/api/radar/latest').then(r=>r.json()).then(function(resp){
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var meta = resp.meta || {};
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var params = meta.query_params || {};
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var cands = meta.query_candidates || [];
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function renderMethodNote(){
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var containerId = 'radar-wind-query';
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var parent = document.getElementById(containerId);
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if (!parent) {
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@ -865,25 +857,9 @@
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root.appendChild(sec);
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parent = sec;
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}
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var html = '<div class="text-sm text-gray-700 mb-2">风场查询参数</div>';
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html += '<div class="text-xs text-gray-600 mb-2">'
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+ 'min_area_px='+ (params.min_area_px||9)
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+ '，strong_dbz_override=' + (params.strong_dbz_override||50)
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+ '，max_samples_per_cluster=' + (params.max_samples_per_cluster||5)
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+ '，max_candidates_total=' + (params.max_candidates_total||25)
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+ '</div>';
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if (!cands.length) {
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html += '<div class="text-xs text-gray-500">暂无需要查询的采样点</div>';
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} else {
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html += '<div class="text-sm text-gray-700 mb-1">需要查询的采样点（共 '+cands.length+' 个）</div>';
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html += '<ul class="list-disc pl-5 text-xs text-gray-700">';
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cands.forEach(function(p){
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html += '<li>cluster='+p.cluster_id+' | '+p.role+' | lon='+p.lon.toFixed(4)+', lat='+p.lat.toFixed(4)+'</li>';
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});
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html += '</ul>';
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}
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var html = '<div class="text-sm text-gray-700 mb-1">方法</div>';
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html += '<div class="text-xs text-gray-600">极坐标（质心单点）：使用云团质心处彩云风，计算与站点的径向分量与 ETA。</div>';
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parent.innerHTML = html;
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}).catch(function(){});
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}
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function renderWindResults(){
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@ -915,38 +891,51 @@
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});
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html += '</div>';
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}
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// candidate details
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if (cands.length) {
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html += '<div class="text-xs text-gray-700 mb-2">采样点明细：</div>';
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html += '<div class="overflow-x-auto"><table class="min-w-full text-xs text-gray-700"><thead><tr>'
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+ '<th class="px-2 py-1 border">cluster</th>'
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+ '<th class="px-2 py-1 border">role</th>'
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+ '<th class="px-2 py-1 border">lon</th>'
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+ '<th class="px-2 py-1 border">lat</th>'
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+ '<th class="px-2 py-1 border">spd(m/s)</th>'
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+ '<th class="px-2 py-1 border">dir_from(°)</th>'
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+ '<th class="px-2 py-1 border">T(°C)</th>'
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+ '<th class="px-2 py-1 border">RH</th>'
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+ '<th class="px-2 py-1 border">P(hPa)</th>'
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+ '<th class="px-2 py-1 border">err</th>'
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+ '</tr></thead><tbody>';
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cands.forEach(function(p){
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var w = p.wind || {};
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html += '<tr>'
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+ '<td class="px-2 py-1 border">'+p.cluster_id+'</td>'
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+ '<td class="px-2 py-1 border">'+p.role+'</td>'
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+ '<td class="px-2 py-1 border">'+p.lon.toFixed(4)+'</td>'
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+ '<td class="px-2 py-1 border">'+p.lat.toFixed(4)+'</td>'
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+ '<td class="px-2 py-1 border">'+(w.speed_ms!=null?w.speed_ms.toFixed(1):'')+'</td>'
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+ '<td class="px-2 py-1 border">'+(w.dir_from_deg!=null?w.dir_from_deg.toFixed(0):'')+'</td>'
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+ '<td class="px-2 py-1 border">'+(w.temp_c!=null?w.temp_c.toFixed(1):'')+'</td>'
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+ '<td class="px-2 py-1 border">'+(w.rh!=null?(w.rh*100).toFixed(0)+'%':'')+'</td>'
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+ '<td class="px-2 py-1 border">'+(w.pressure_hpa!=null?w.pressure_hpa.toFixed(1):'')+'</td>'
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+ '<td class="px-2 py-1 border">'+(p.error||'')+'</td>'
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+ '</tr>';
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// 朝向云团：极坐标计算明细列表
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var candByCluster = {};
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(cands||[]).forEach(function(co){ candByCluster[co.cluster_id] = co; });
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var comings = (clusters||[]).filter(function(cl){ return cl.coming; });
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if (comings.length) {
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html += '<div class="text-xs text-gray-700 mb-2">朝向云团（极坐标计算明细）</div>';
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comings.forEach(function(cl){
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var co = candByCluster[cl.cluster_id] || {};
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var w = co.wind || {};
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var speed = (w.speed_ms!=null)? w.speed_ms : (cl.speed_ms||0);
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var dirFrom = (w.dir_from_deg!=null)? w.dir_from_deg : null;
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var dirTo = (w.dir_to_deg!=null)? w.dir_to_deg : (cl.dir_to_deg||0);
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// 计算几何与极坐标过程（前端复算，便于展示公式与数值）
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var mPerDegLat = 111320.0;
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var mPerDegLon = 111320.0 * Math.cos((cl.lat||0) * Math.PI/180.0);
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var dx = ((station.lon||0) - (cl.lon||0)) * mPerDegLon; // 东向
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var dy = ((station.lat||0) - (cl.lat||0)) * mPerDegLat; // 北向
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var D = Math.hypot(dx, dy); // m
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var theta = Math.atan2(dx, dy) * 180/Math.PI; // 北=0, 顺时针
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if (theta < 0) theta += 360;
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var delta = dirTo - theta; // deg
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// wrap 到 [-180,180]
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delta = ((delta + 540) % 360) - 180;
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var vr = speed * Math.cos(delta * Math.PI/180.0); // m/s（指向站点为正）
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var etaMin = (vr>0) ? (D/vr/60.0) : null;
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var code = ''
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+ 'station = ('+(station.lon||0).toFixed(6)+', '+(station.lat||0).toFixed(6)+')\n'
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+ 'centroid = ('+(cl.lon||0).toFixed(6)+', '+(cl.lat||0).toFixed(6)+')\n'
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+ 'speed = '+speed.toFixed(2)+' m/s\n'
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+ (dirFrom!=null?('dir_from = '+dirFrom.toFixed(0)+'°\n'):'')
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+ 'dir_to = '+dirTo.toFixed(0)+'°\n'
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+ 'dx = (lonS-lonC) * 111320*cos(latC) = '+dx.toFixed(1)+' m\n'
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+ 'dy = (latS-latC) * 111320 = '+dy.toFixed(1)+' m\n'
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+ 'D = hypot(dx,dy) = '+(D/1000.0).toFixed(2)+' km\n'
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+ 'theta = atan2(dx,dy) = '+theta.toFixed(1)+'°\n'
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+ 'delta = dir_to - theta = '+delta.toFixed(1)+'°\n'
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+ 'vr = speed * cos(delta) = '+vr.toFixed(2)+' m/s\n'
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+ (etaMin!=null?('ETA = D/vr = '+etaMin.toFixed(1)+' min\n'):'ETA = N/A (vr<=0)\n');
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html += '<div class="mb-3 border border-green-200 rounded p-2 bg-green-50">'
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+ '<div class="text-xs text-green-800">ID '+cl.cluster_id+' | 质心: '+cl.lon.toFixed(4)+', '+cl.lat.toFixed(4)+'</div>'
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+ '<pre class="mt-1 text-[11px] leading-4 text-gray-800 overflow-x-auto">'+code.replace(/</g,'<')+'</pre>'
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+ '</div>';
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});
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html += '</tbody></table></div>';
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}
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// 极坐标法：省略采样点明细表，仅保留汇总与朝向明细
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parent.innerHTML = html;
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}).catch(function(){});
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}
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