Initial import

tasks/WeatherServer_GridBuilder_v2.md

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+# NavSea Weather Server
+Task: WeatherServer_GridBuilder_v2
+Architecture: NavSea V11
+Codex: codex6
+Status: TODO
+
+---
+
+# 1 任务目标
+
+升级 Grid Builder：
+
+grid_builder.py → GridBuilder v2
+
+目标：
+
+1 裁剪日本区域 grid  
+2 使用数组结构保存 grid  
+3 大幅减少 JSON 文件大小  
+
+---
+
+# 2 当前问题
+
+旧版 GridBuilder：
+
+生成全球 grid：
+
+1440 × 721  
+≈ 1,038,240 points
+
+JSON 文件：
+
+≈ 215MB
+
+这是不可接受的。
+
+Downloader 已经只下载：
+
+120E – 150E  
+20N – 50N
+
+GridBuilder 必须只输出这个区域。
+
+---
+
+# 3 区域范围
+
+REGION：
+
+lon_min = 120
+lon_max = 150
+
+lat_min = 20
+lat_max = 50
+
+理论 grid：
+
+(150-120)/0.25 = 120  
+(50-20)/0.25 = 120  
+
+≈ 14400 grid points
+
+---
+
+# 4 新 Grid 数据结构
+
+旧结构：
+
+points list
+
+{
+ "points":[
+  {lat,lon,...}
+ ]
+}
+
+新结构：
+
+grid arrays
+
+{
+ "time": "...",
+ "lat": [...],
+ "lon": [...],
+ "wind_speed": [...],
+ "wind_dir": [...],
+ "rain": [...],
+ "temp": [...],
+ "pressure": [...]
+}
+
+优点：
+
+1 文件更小  
+2 读取更快  
+3 tile generator 更容易  
+
+---
+
+# 5 创建文件
+
+weather_server/grid/grid_builder_v2.py
+
+---
+
+# 6 实现代码
+
+```python
+import os
+import json
+import numpy as np
+import xarray as xr
+
+INPUT_DIR = "data/grib"
+OUTPUT_DIR = "data/grid"
+
+os.makedirs(OUTPUT_DIR, exist_ok=True)
+
+REGION = {
+    "lon_min":120,
+    "lon_max":150,
+    "lat_min":20,
+    "lat_max":50
+}
+
+
+def compute_wind(u, v):
+
+    speed = np.sqrt(u**2 + v**2)
+
+    direction = (np.degrees(np.arctan2(u, v)) + 360) % 360
+
+    return speed, direction
+
+
+def process_file(path):
+
+    ds = xr.open_dataset(path, engine="cfgrib")
+
+    u = ds["u10"].values
+    v = ds["v10"].values
+    rain = ds["tp"].values
+    pressure = ds["msl"].values
+    temp = ds["t2m"].values
+
+    lat = ds.latitude.values
+    lon = ds.longitude.values
+
+    wind_speed, wind_dir = compute_wind(u, v)
+
+    lat_idx = np.where(
+        (lat >= REGION["lat_min"]) &
+        (lat <= REGION["lat_max"])
+    )[0]
+
+    lon_idx = np.where(
+        (lon >= REGION["lon_min"]) &
+        (lon <= REGION["lon_max"])
+    )[0]
+
+    lat_region = lat[lat_idx]
+    lon_region = lon[lon_idx]
+
+    wind_speed = wind_speed[np.ix_(lat_idx, lon_idx)]
+    wind_dir = wind_dir[np.ix_(lat_idx, lon_idx)]
+
+    rain = rain[np.ix_(lat_idx, lon_idx)]
+    temp = temp[np.ix_(lat_idx, lon_idx)]
+    pressure = pressure[np.ix_(lat_idx, lon_idx)]
+
+    return {
+        "lat": lat_region.tolist(),
+        "lon": lon_region.tolist(),
+        "wind_speed": wind_speed.tolist(),
+        "wind_dir": wind_dir.tolist(),
+        "rain": rain.tolist(),
+        "temp": temp.tolist(),
+        "pressure": pressure.tolist()
+    }
+
+
+def main():
+
+    for file in os.listdir(INPUT_DIR):
+
+        if not file.endswith(".grib2"):
+            continue
+
+        path = os.path.join(INPUT_DIR, file)
+
+        print("processing", file)
+
+        grid = process_file(path)
+
+        output = os.path.join(
+            OUTPUT_DIR,
+            f"grid_{file.replace('.grib2','')}.json"
+        )
+
+        data = {
+            "time": file.replace(".grib2",""),
+            "grid": grid
+        }
+
+        with open(output, "w") as f:
+
+            json.dump(data, f)
+
+        print("saved", output)
+
+
+if __name__ == "__main__":
+
+    main()