diff --git a/internal/server/gin.go b/internal/server/gin.go index d1b6888..244e712 100644 --- a/internal/server/gin.go +++ b/internal/server/gin.go @@ -339,12 +339,13 @@ func intFromMeta(m map[string]any, key string) int { // radarLatestWindHandler queries Caiyun realtime wind for the latest query candidates // and provides per-cluster aggregated wind and basic coming/ETA analysis toward station. func radarLatestWindHandler(c *gin.Context) { - // Constants per user request + // 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 + // 常量：目标点（站点/雷达点）坐标 const ( stationLat = 23.097234 stationLon = 108.715433 ) - // Read latest metadata into struct + // 读取最新元数据 latestRoot := "./radar_data/latest" metaPath := latestRoot + "/metadata.json" b, err := os.ReadFile(metaPath) @@ -357,7 +358,8 @@ func radarLatestWindHandler(c *gin.Context) { c.JSON(http.StatusInternalServerError, gin.H{"error": "解析元数据失败"}) return } - // For each query candidate, call Caiyun + + // 输出结构保持兼容：仍提供 candidates，但每个cluster仅一个（质心） type Wind struct { Speed float64 `json:"speed_ms"` DirFrom float64 `json:"dir_from_deg"` @@ -373,29 +375,38 @@ func radarLatestWindHandler(c *gin.Context) { Wind *Wind `json:"wind,omitempty"` Error string `json:"error,omitempty"` } - outs := make([]CandOut, 0, len(meta.QueryCandidates)) - for _, q := range meta.QueryCandidates { - speed, dirFrom, tempC, rh, pPa, err := rf.FetchCaiyunRealtime(q.Lon, q.Lat) - co := CandOut{QueryCandidate: q} - if err != nil { - co.Error = err.Error() - } else { - dirTo := mathMod(dirFrom+180.0, 360.0) - u, v := windVectorUV(speed, dirTo) - // pressure in hPa for display - pHpa := pPa / 100.0 - co.Wind = &Wind{Speed: speed, DirFrom: dirFrom, DirTo: dirTo, U: u, V: v, TempC: tempC, RH: rh, PressureHpa: pHpa} + + outs := make([]CandOut, 0, len(meta.Clusters)) + + // 工具函数 + mPerDegLat := 111320.0 + mPerDegLon := func(lat float64) float64 { return 111320.0 * math.Cos(lat*math.Pi/180.0) } + // 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） + approachETA := func(lonC, latC, speedMS, dirToDeg, lonS, latS float64) (coming bool, etaMin float64, distanceKm float64, vrMS float64) { + wx := mPerDegLon(latC) + wy := mPerDegLat + dx := (lonS - lonC) * wx // 东向米 + dy := (latS - latC) * wy // 北向米 + D := math.Hypot(dx, dy) + if D == 0 { + return true, 0, 0, speedMS } - outs = append(outs, co) - } - // Aggregate by cluster id - agg := map[int][]Wind{} - for _, co := range outs { - if co.Wind == nil { - continue + // 云→站方位角（北=0，顺时针） + theta := math.Atan2(dx, dy) * 180 / math.Pi + if theta < 0 { + theta += 360 } - agg[co.ClusterID] = append(agg[co.ClusterID], *co.Wind) + beta := mathMod(dirToDeg, 360.0) + delta := (beta - theta) * math.Pi / 180.0 + vr := speedMS * math.Cos(delta) // 指向站点的径向速度 + if vr <= 0 { + return false, -1, D / 1000.0, vr + } + etaSec := D / vr + return true, etaSec / 60.0, D / 1000.0, vr } + + // 为每个云团质心取一次风，构造 candidates 与 per-cluster 分析 type ClusterAnal struct { ClusterID int `json:"cluster_id"` Lon float64 `json:"lon"` @@ -411,77 +422,64 @@ func radarLatestWindHandler(c *gin.Context) { DistanceKm float64 `json:"distance_km"` LateralKm float64 `json:"lateral_km"` RCloudKm float64 `json:"r_cloud_km"` + VrMS float64 `json:"vr_ms"` } analyses := []ClusterAnal{} - // helpers - mPerDegLat := 111320.0 - mPerDegLon := func(lat float64) float64 { return 111320.0 * math.Cos(lat*math.Pi/180.0) } - cellDims := func(lat float64) (float64, float64) { // width (lon), height (lat) in meters per pixel + + // 等效云半径与侧向距离仅用于展示（不再作为判定条件） + cellDims := func(lat float64) (float64, float64) { // 每像素米宽/米高 return meta.ResDeg * mPerDegLon(lat), meta.ResDeg * mPerDegLat } - const hitRadiusM = 5000.0 + for _, cl := range meta.Clusters { - winds := agg[cl.ID] - if len(winds) == 0 { + // 取质心风 + speed, dirFrom, tempC, rh, pPa, err := rf.FetchCaiyunRealtime(cl.Lon, cl.Lat) + q := rf.QueryCandidate{ClusterID: cl.ID, Role: "center", Lon: cl.Lon, Lat: cl.Lat} + co := CandOut{QueryCandidate: q} + if err != nil { + co.Error = err.Error() + outs = append(outs, co) + // 即便取风失败，也继续下一个云团 continue } - // vector average in u,v (to-direction) - sumU, sumV := 0.0, 0.0 - for _, wv := range winds { - sumU += wv.U - sumV += wv.V - } - u := sumU / float64(len(winds)) - v := sumV / float64(len(winds)) - speed := math.Hypot(u, v) - dirTo := uvToDirTo(u, v) - // project geometry + dirTo := mathMod(dirFrom+180.0, 360.0) + u, v := windVectorUV(speed, dirTo) + pHpa := pPa / 100.0 + co.Wind = &Wind{Speed: speed, DirFrom: dirFrom, DirTo: dirTo, U: u, V: v, TempC: tempC, RH: rh, PressureHpa: pHpa} + outs = append(outs, co) + + // 极坐标法靠近/ETA（到站点） + coming, etaMin, distKm, vr := approachETA(cl.Lon, cl.Lat, speed, dirTo, stationLon, stationLat) + + // 展示参数：侧向距与等效半径 + // 侧向距 = 距离向量对速度方向单位向量的叉积绝对值 wx, wy := mPerDegLon(cl.Lat), mPerDegLat - // position of cluster and station in meters (local tangent plane) - px := (cl.Lon - stationLon) * wx - py := (cl.Lat - stationLat) * wy - // vector from cluster to station - dx := -px - dy := -py - d := math.Hypot(dx, dy) - // radial component of velocity towards station - if d == 0 { - d = 1e-6 - } - vr := (dx*u + dy*v) / d - // cluster equivalent radius - cw, ch := cellDims(cl.Lat) - areaM2 := float64(cl.AreaPx) * cw * ch - rCloud := math.Sqrt(areaM2 / math.Pi) - // lateral offset (perpendicular distance from station line) + px := (stationLon - cl.Lon) * wx + py := (stationLat - cl.Lat) * wy vnorm := math.Hypot(u, v) lateral := 0.0 if vnorm > 0 { - // |d x vhat| vx, vy := u/vnorm, v/vnorm - lateral = math.Abs(dx*vy - dy*vx) - } - coming := vr > 0 && lateral <= (rCloud+hitRadiusM) - etaMin := 0.0 - if coming && vr > 0 { - distToEdge := d - (rCloud + hitRadiusM) - if distToEdge < 0 { - distToEdge = 0 - } - etaMin = distToEdge / vr / 60.0 + lateral = math.Abs(px*vy - py*vx) } + cw, ch := cellDims(cl.Lat) + areaM2 := float64(cl.AreaPx) * cw * ch + rCloud := math.Sqrt(areaM2 / math.Pi) + analyses = append(analyses, ClusterAnal{ ClusterID: cl.ID, Lon: cl.Lon, Lat: cl.Lat, AreaPx: cl.AreaPx, MaxDBZ: cl.MaxDBZ, SpeedMS: speed, DirToDeg: dirTo, U: u, V: v, Coming: coming, ETAMin: round2(etaMin), - DistanceKm: round2(d / 1000.0), LateralKm: round2(lateral / 1000.0), RCloudKm: round2(rCloud / 1000.0), + DistanceKm: round2(distKm), LateralKm: round2(lateral / 1000.0), RCloudKm: round2(rCloud / 1000.0), + VrMS: round2(vr), }) } + c.JSON(http.StatusOK, gin.H{ "station": gin.H{"lon": stationLon, "lat": stationLat}, - "params": meta.QueryParams, + "params": meta.QueryParams, // 兼容保留 "candidates": outs, "clusters": analyses, }) diff --git a/templates/index.html b/templates/index.html index e59e604..e3c6bf4 100644 --- a/templates/index.html +++ b/templates/index.html @@ -720,7 +720,7 @@ window.RadarLatestGrid = data; renderPlotlyHeat(data); renderClustersPanel(); - renderWindQueryList(); + renderMethodNote(); renderWindResults(); } @@ -838,11 +838,7 @@ + '质心: '+cl.lon.toFixed(4)+', '+cl.lat.toFixed(4)+'
' + 'dBZ: max '+cl.max_dbz.toFixed(1)+' / avg '+cl.avg_dbz.toFixed(1) + ''; - if (cl.samples && cl.samples.length) { - html += '
采样点: ' + cl.samples.map(function(s){ - return s.role+':('+s.lon.toFixed(3)+','+s.lat.toFixed(3)+')'; - }).join(' | ') + '
'; - } + // 极坐标法：不再展示采样点列表（仅使用质心） html += ''; }); html += ''; @@ -850,40 +846,20 @@ }).catch(function(){ /* ignore */ }); } - function renderWindQueryList(){ - fetch('/api/radar/latest').then(r=>r.json()).then(function(resp){ - var meta = resp.meta || {}; - var params = meta.query_params || {}; - var cands = meta.query_candidates || []; - var containerId = 'radar-wind-query'; - var parent = document.getElementById(containerId); - if (!parent) { - var sec = document.createElement('div'); - sec.id = containerId; - sec.className = 'mt-4'; - var root = document.getElementById('view-radar').querySelector('.radar-grid'); - root.appendChild(sec); - parent = sec; - } - var html = '
风场查询参数
'; - html += '
' - + 'min_area_px='+ (params.min_area_px||9) - + '，strong_dbz_override=' + (params.strong_dbz_override||50) - + '，max_samples_per_cluster=' + (params.max_samples_per_cluster||5) - + '，max_candidates_total=' + (params.max_candidates_total||25) - + '
'; - if (!cands.length) { - html += '
暂无需要查询的采样点
'; - } else { - html += '
需要查询的采样点（共 '+cands.length+' 个）
'; - html += ''; - } - parent.innerHTML = html; - }).catch(function(){}); +function renderMethodNote(){ + var containerId = 'radar-wind-query'; + var parent = document.getElementById(containerId); + if (!parent) { + var sec = document.createElement('div'); + sec.id = containerId; + sec.className = 'mt-4'; + var root = document.getElementById('view-radar').querySelector('.radar-grid'); + root.appendChild(sec); + parent = sec; + } + var html = '
方法
'; + html += '
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。
'; + parent.innerHTML = html; } function renderWindResults(){ @@ -915,38 +891,51 @@ }); html += ''; } - // candidate details - if (cands.length) { - html += '
采样点明细：
'; - html += '
' - + '' - + '' - + '' - + '' - + '' - + '' - + '' - + '' - + '' - + '' - + ''; - cands.forEach(function(p){ - var w = p.wind || {}; - html += '' - + '' - + '' - + '' - + '' - + '' - + '' - + '' - + '' - + '' - + '' - + ''; + // 朝向云团：极坐标计算明细列表 + var candByCluster = {}; + (cands||[]).forEach(function(co){ candByCluster[co.cluster_id] = co; }); + var comings = (clusters||[]).filter(function(cl){ return cl.coming; }); + if (comings.length) { + html += '
朝向云团（极坐标计算明细）
'; + comings.forEach(function(cl){ + var co = candByCluster[cl.cluster_id] || {}; + var w = co.wind || {}; + var speed = (w.speed_ms!=null)? w.speed_ms : (cl.speed_ms||0); + var dirFrom = (w.dir_from_deg!=null)? w.dir_from_deg : null; + var dirTo = (w.dir_to_deg!=null)? w.dir_to_deg : (cl.dir_to_deg||0); + // 计算几何与极坐标过程（前端复算，便于展示公式与数值） + var mPerDegLat = 111320.0; + var mPerDegLon = 111320.0 * Math.cos((cl.lat||0) * Math.PI/180.0); + var dx = ((station.lon||0) - (cl.lon||0)) * mPerDegLon; // 东向 + var dy = ((station.lat||0) - (cl.lat||0)) * mPerDegLat; // 北向 + var D = Math.hypot(dx, dy); // m + var theta = Math.atan2(dx, dy) * 180/Math.PI; // 北=0, 顺时针 + if (theta < 0) theta += 360; + var delta = dirTo - theta; // deg + // wrap 到 [-180,180] + delta = ((delta + 540) % 360) - 180; + var vr = speed * Math.cos(delta * Math.PI/180.0); // m/s（指向站点为正） + var etaMin = (vr>0) ? (D/vr/60.0) : null; + var code = '' + + 'station = ('+(station.lon||0).toFixed(6)+', '+(station.lat||0).toFixed(6)+')\n' + + 'centroid = ('+(cl.lon||0).toFixed(6)+', '+(cl.lat||0).toFixed(6)+')\n' + + 'speed = '+speed.toFixed(2)+' m/s\n' + + (dirFrom!=null?('dir_from = '+dirFrom.toFixed(0)+'°\n'):'') + + 'dir_to = '+dirTo.toFixed(0)+'°\n' + + 'dx = (lonS-lonC) * 111320*cos(latC) = '+dx.toFixed(1)+' m\n' + + 'dy = (latS-latC) * 111320 = '+dy.toFixed(1)+' m\n' + + 'D = hypot(dx,dy) = '+(D/1000.0).toFixed(2)+' km\n' + + 'theta = atan2(dx,dy) = '+theta.toFixed(1)+'°\n' + + 'delta = dir_to - theta = '+delta.toFixed(1)+'°\n' + + 'vr = speed * cos(delta) = '+vr.toFixed(2)+' m/s\n' + + (etaMin!=null?('ETA = D/vr = '+etaMin.toFixed(1)+' min\n'):'ETA = N/A (vr<=0)\n'); + html += '
' + + '
ID '+cl.cluster_id+' | 质心: '+cl.lon.toFixed(4)+', '+cl.lat.toFixed(4)+'
' + + '
'+code.replace(/'
+                                 + '
'; }); - html += '
clusterrolelonlatspd(m/s)dir_from(°)T(°C)RHP(hPa)err
'+p.cluster_id+''+p.role+''+p.lon.toFixed(4)+''+p.lat.toFixed(4)+''+(w.speed_ms!=null?w.speed_ms.toFixed(1):'')+''+(w.dir_from_deg!=null?w.dir_from_deg.toFixed(0):'')+''+(w.temp_c!=null?w.temp_c.toFixed(1):'')+''+(w.rh!=null?(w.rh*100).toFixed(0)+'%':'')+''+(w.pressure_hpa!=null?w.pressure_hpa.toFixed(1):'')+''+(p.error||'')+'
'; } + // 极坐标法：省略采样点明细表，仅保留汇总与朝向明细 parent.innerHTML = html; }).catch(function(){}); }