diff --git a/internal/server/gin.go b/internal/server/gin.go
index 244e712..d1b6888 100644
--- a/internal/server/gin.go
+++ b/internal/server/gin.go
@@ -339,13 +339,12 @@ 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) {
- // 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
+ // Constants per user request
const (
stationLat = 23.097234
stationLon = 108.715433
)
- // 读取最新元数据
+ // Read latest metadata into struct
latestRoot := "./radar_data/latest"
metaPath := latestRoot + "/metadata.json"
b, err := os.ReadFile(metaPath)
@@ -358,8 +357,7 @@ func radarLatestWindHandler(c *gin.Context) {
c.JSON(http.StatusInternalServerError, gin.H{"error": "解析元数据失败"})
return
}
-
- // 输出结构保持兼容：仍提供 candidates，但每个cluster仅一个（质心）
+ // For each query candidate, call Caiyun
type Wind struct {
Speed float64 `json:"speed_ms"`
DirFrom float64 `json:"dir_from_deg"`
@@ -375,38 +373,29 @@ func radarLatestWindHandler(c *gin.Context) {
Wind *Wind `json:"wind,omitempty"`
Error string `json:"error,omitempty"`
}
-
- 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 := 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}
}
- // 云→站方位角（北=0，顺时针）
- theta := math.Atan2(dx, dy) * 180 / math.Pi
- if theta < 0 {
- theta += 360
- }
- 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
+ outs = append(outs, co)
+ }
+ // Aggregate by cluster id
+ agg := map[int][]Wind{}
+ for _, co := range outs {
+ if co.Wind == nil {
+ continue
+ }
+ agg[co.ClusterID] = append(agg[co.ClusterID], *co.Wind)
}
-
- // 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"`
@@ -422,64 +411,77 @@ 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{}
-
- // 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
+ // 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
return meta.ResDeg * mPerDegLon(lat), meta.ResDeg * mPerDegLat
}
-
+ const hitRadiusM = 5000.0
for _, cl := range meta.Clusters {
- // 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
+ winds := agg[cl.ID]
+ if len(winds) == 0 {
continue
}
- 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
- px := (stationLon - cl.Lon) * wx
- py := (stationLat - cl.Lat) * wy
- vnorm := math.Hypot(u, v)
- lateral := 0.0
- if vnorm > 0 {
- vx, vy := u/vnorm, v/vnorm
- lateral = math.Abs(px*vy - py*vx)
+ // 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
+ 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)
+ 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
+ }
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(distKm), LateralKm: round2(lateral / 1000.0), RCloudKm: round2(rCloud / 1000.0),
- VrMS: round2(vr),
+ DistanceKm: round2(d / 1000.0), LateralKm: round2(lateral / 1000.0), RCloudKm: round2(rCloud / 1000.0),
})
}
-
c.JSON(http.StatusOK, gin.H{
"station": gin.H{"lon": stationLon, "lat": stationLat},
- "params": meta.QueryParams, // 兼容保留
+ "params": meta.QueryParams,
"candidates": outs,
"clusters": analyses,
})
diff --git a/templates/index.html b/templates/index.html
index e3c6bf4..e59e604 100644
--- a/templates/index.html
+++ b/templates/index.html
@@ -720,7 +720,7 @@
window.RadarLatestGrid = data;
renderPlotlyHeat(data);
renderClustersPanel();
- renderMethodNote();
+ renderWindQueryList();
renderWindResults();
}
@@ -838,7 +838,11 @@
+ '质心: '+cl.lon.toFixed(4)+', '+cl.lat.toFixed(4)+'
'
+ 'dBZ: max '+cl.max_dbz.toFixed(1)+' / avg '+cl.avg_dbz.toFixed(1)
+ '';
- // 极坐标法：不再展示采样点列表（仅使用质心）
+ 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(' | ') + '
';
+ }
html += '';
});
html += '';
@@ -846,20 +850,40 @@
}).catch(function(){ /* ignore */ });
}
-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 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 += '';
+ cands.forEach(function(p){
+ html += '- cluster='+p.cluster_id+' | '+p.role+' | lon='+p.lon.toFixed(4)+', lat='+p.lat.toFixed(4)+'
';
+ });
+ html += '
';
+ }
+ parent.innerHTML = html;
+ }).catch(function(){});
}
function renderWindResults(){
@@ -891,51 +915,38 @@ function renderMethodNote(){
});
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(/'
- + '
采样点明细：
';
+ html += ''
+ + '| cluster | '
+ + 'role | '
+ + 'lon | '
+ + 'lat | '
+ + 'spd(m/s) | '
+ + 'dir_from(°) | '
+ + 'T(°C) | '
+ + 'RH | '
+ + 'P(hPa) | '
+ + 'err | '
+ + '
';
+ cands.forEach(function(p){
+ var w = p.wind || {};
+ html += ''
+ + '| '+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||'')+' | '
+ + '
';
});
+ html += '