fix: can choose cosmic planetw day

.gitignore

@@ -19,6 +19,6 @@ dist
 notebooks
 passcode
 data
-
+*.7z
 res
 *.txt

backend.py

@@ -77,6 +77,6 @@ if __name__ == '__main__':
     env_port = os.getenv("Z_PORT")
     port = 5000 if env_port is None else int(env_port)
     if 'debug' in args:
-        app.run("0.0.0.0", port=18200, debug=True)
+        app.run("0.0.0.0", port=58620, debug=True)
     else:
         app.run("0.0.0.0", port=port, debug=False)

modules/cosmic/__init__.py

@@ -55,6 +55,7 @@ async def render_by_mode_single():
     T = request.args.get("T", 16)
     target_h = request.args.get("target_h", 40)
     target_latitude = request.args.get("target_lat", 30)
+    start_day = request.args.get("start_day", 0)
 
     # path: str = f"{DATA_BASEPATH.cosmic}/cosmic.txt"
     temp_df = await run_sync(cosmic_planet_daily_process)(
@@ -66,6 +67,7 @@ async def render_by_mode_single():
     await run_sync(cosmic_planetw_plot_perday)(
         temp_df,
         T=int(T),
+        start_day=int(start_day)
     )
     buf = BytesIO()
 

modules/cosmic/planetw_daily_process.py

@@ -106,7 +106,7 @@ def cosmic_planet_daily_process(
         return pd.read_parquet(cache_path)
 
     # 遍历文件夹序号1到365
-    for i in range(1, 165):
+    for i in range(1, 365):
         # 根据i的值调整文件夹名称
         if i < 10:
             folder_name = f"atmPrf_repro2021_2008_00{i}"  # 一位数，前面加两个0

modules/cosmic/planetw_perday.py

@@ -24,7 +24,7 @@ bounds = (
 def cosmic_planetw_plot_perday(
     df: pd.DataFrame,
     T=16,
-
+    start_day=0
 ):
 
     def u_func(x, *params, t):
@@ -45,41 +45,48 @@ def cosmic_planetw_plot_perday(
     min_data_points = 36
 
     # 进行多个时间窗口的拟合
-    for start_day in range(0, 365 - 3 * T):  # 最后一个窗口为[351, 366]
+    # for start_day in range(0, 365 - 3 * T):  # 最后一个窗口为[351, 366]
-        end_day = start_day + 3 * T  # 每个窗口的结束时间为 start_day + 3*T
+    end_day = start_day + 3 * T  # 每个窗口的结束时间为 start_day + 3*T
 
-        # 选择当前窗口的数据
+    # 选择当前窗口的数据
-        df_8 = df[(df['Time'] >= start_day) & (df['Time'] <= end_day)]
+    df_8 = df[(df['Time'] >= start_day) & (df['Time'] <= end_day)]
-
-        # 检查当前窗口的数据量
-        if len(df_8) < min_data_points:
-            print(f"数据量不足，无法拟合：{start_day} 到 {end_day}，数据点数量：{len(df_8)}")
-            continue  # 跳过当前时间窗口，继续下一个窗口
-
-        # 提取时间、经度、温度数据
-        t = np.array(df_8['Time'])  # 时间
-        x = np.array(df_8['Longitude_Radians'])  # 经度弧度制
-        temperature = np.array(df_8['Temperature'])  # 温度，因变量
-
-        # `tempeture` 为因变量，`x` 为自变量，`t` 为参数
-        # tempeture is possible to contain NaNs, so we need to drop them
-        mask = ~np.isnan(temperature)
-        x = x[mask]
-        temperature = temperature[mask]
-
-        # 用T进行拟合
-        popt, pcov = curve_fit(lambda x, *params: u_func(x, *params, t=t),
-                               x, temperature, p0=initial_guess, bounds=bounds, maxfev=50000)
-
-        # 绘制拟合曲线
-        t_fixed = (start_day + end_day) / 2  # 窗口的中间时间
-        x_fit = np.linspace(min(x), max(x), 100)  # 生成用于绘制拟合曲线的x值
-        y_fit = u_func(x_fit, *popt, t=t_fixed)  # 计算拟合曲线的y值
 
+    # 检查当前窗口的数据量
+    if len(df_8) < min_data_points:
+        print(f"数据量不足，无法拟合：{start_day} 到 {end_day}，数据点数量：{len(df_8)}")
         plt.figure(figsize=(10, 6))
-        plt.plot(x_fit, y_fit, label='拟合曲线', color='red', linewidth=2)
+        # write nothing but a title
-        plt.xlabel('经度（弧度制）')
-        plt.ylabel('温度')
         plt.title(f'时间窗口：{start_day} 到 {end_day}')
-        plt.legend()
         plt.grid(True)
+        # add a label, says unable to fit
+        plt.text(0.5, 0.5, "数据量不足，无法拟合", ha='center', va='center',
+                 transform=plt.gca().transAxes, fontsize=20)  # 跳过当前时间窗口，继续下一个窗口
+
+    # 提取时间、经度、温度数据
+    t = np.array(df_8['Time'])  # 时间
+    x = np.array(df_8['Longitude_Radians'])  # 经度弧度制
+    temperature = np.array(df_8['Temperature'])  # 温度，因变量
+
+    # `tempeture` 为因变量，`x` 为自变量，`t` 为参数
+    # tempeture is possible to contain NaNs, so we need to drop them
+    mask = ~np.isnan(temperature)
+    x = x[mask]
+    temperature = temperature[mask]
+    t = t[mask]
+
+    # 用T进行拟合
+    popt, pcov = curve_fit(lambda x, *params: u_func(x, *params, t=t),
+                           x, temperature, p0=initial_guess, bounds=bounds, maxfev=50000)
+
+    # 绘制拟合曲线
+    t_fixed = (start_day + end_day) / 2  # 窗口的中间时间
+    x_fit = np.linspace(min(x), max(x), 100)  # 生成用于绘制拟合曲线的x值
+    y_fit = u_func(x_fit, *popt, t=t_fixed)  # 计算拟合曲线的y值
+
+    plt.figure(figsize=(10, 6))
+    plt.plot(x_fit, y_fit, label='拟合曲线', color='red', linewidth=2)
+    plt.xlabel('经度（弧度制）')
+    plt.ylabel('温度')
+    plt.title(f'时间窗口：{start_day} 到 {end_day}')
+    plt.legend()
+    plt.grid(True)

run.sh

@@ -1,3 +1,10 @@
 #!/bin/bash
 
-./dist/backend/backend
+while true; do
+    # 运行你的程序
+    ./dist/backend/backend
+    
+    # 程序退出后等待5秒
+    echo "程序已退出，5秒后重新启动..."
+    sleep 5
+done