some fix

modules/cosmic/__init__.py

@@ -20,7 +20,8 @@ def get_meta():
 @cosmic_module.route('/temp_render')
 async def render():
     T = request.args.get("T", 16)
-    await run_sync(cosmic_planetw_daily_plot)(T=int(T))
+    k = request.args.get("k", 1)
+    await run_sync(cosmic_planetw_daily_plot)(T=int(T), k=int(k))
     buf = BytesIO()
 
     plt.savefig(buf, format="png")
@@ -61,7 +62,7 @@ async def multiday_render():
                                                                  day_range=(start_day, end_day))
     if mode == "布伦特-维萨拉频率分布":
         await run_sync(p.plot_heatmap_tempNz)()
-    elif mode == "位温分布":
+    elif mode == "不同高度下的逐日统计分析":
         await run_sync(p.plot_heatmap_tempPtz)()
     elif mode == "每月浮力频率变化趋势":
         await run_sync(p.plot_floatage_trend)()

modules/cosmic/planetw_daily.py

@@ -17,7 +17,11 @@ matplotlib.rcParams['axes.unicode_minus'] = False  # 正常显示负号
 # 读取一年的数据文件
 
 
-def cosmic_planetw_daily_plot(path: str = f"{DATA_BASEPATH.cosmic}/cosmic.txt", T=16):
+def cosmic_planetw_daily_plot(
+        path: str = f"{DATA_BASEPATH.cosmic}/cosmic.txt",
+        T=16,
+        k=0
+):
     def u_func(x, *params):
         a1, b1, a2, b2, a3, b3, a4, b4, a5, b5, a6, b6, a7, b7, a8, b8, a9, b9 = params
         return (
@@ -100,23 +104,22 @@ def cosmic_planetw_daily_plot(path: str = f"{DATA_BASEPATH.cosmic}/cosmic.txt",
     x_values = fit_df.index.to_numpy()
 
     # 对每一列生成独立的图
-    for k, col in k_to_a.items():
-        plt.figure(figsize=(8, 6))  # 创建新的图形
-        plt.plot(x_values, fit_df[col].values)
-        plt.title(f'{k} 振幅图')
-        plt.xlabel('Day')
-        plt.ylabel('振幅')
+    # for k, col in k_to_a.items():
+    col = k_to_a[f'k={k}']
+    plt.figure(figsize=(8, 6))  # 创建新的图形
+    plt.plot(x_values, fit_df[col].values)
+    plt.title(f'k={k} 振幅图')
+    plt.xlabel('Day')
+    plt.ylabel('振幅')
 
-        # 设置横坐标的动态调整
-        adjusted_x_values = x_values + (3 * T + 1) / 2
-        if len(adjusted_x_values) > 50:
-            step = 30
-            tick_positions = adjusted_x_values[::step]  # 选择每30个点
-            tick_labels = [f'{int(val)}' for val in tick_positions]
-        else:
-            tick_positions = adjusted_x_values
-            tick_labels = [f'{int(val)}' for val in tick_positions]
+    # 设置横坐标的动态调整
+    adjusted_x_values = x_values + (3 * T + 1) / 2
+    if len(adjusted_x_values) > 50:
+        step = 30
+        tick_positions = adjusted_x_values[::step]  # 选择每30个点
+        tick_labels = [f'{int(val)}' for val in tick_positions]
+    else:
+        tick_positions = adjusted_x_values
+        tick_labels = [f'{int(val)}' for val in tick_positions]
 
-        plt.xticks(ticks=tick_positions, labels=tick_labels)
-
-        plt.show()  # 显示图形
+    plt.xticks(ticks=tick_positions, labels=tick_labels)

modules/saber/__init__.py

@@ -146,10 +146,13 @@ async def do_year_power_wave_plot():
 async def do_gravity_year():
     year = request.args.get("year")
     T = request.args.get("T")
+    k = request.args.get("k")
+    H = request.args.get("H")
+    lat_range = request.args.get("lat_range")
     year = int(year)
     T = int(T)
     if T not in [5, 10, 16]:
         raise ValueError("T must be in [5, 10, 16]")
     data = await run_sync(saber_planetw_process)(year)
-    await run_sync(saber_planetw_plot)(data, T)
+    await run_sync(saber_planetw_plot)(data, T, k=int(k))
     return await extract_payload()

modules/saber/planetw_plot.py

@@ -27,7 +27,11 @@ bounds = (
      np.inf, np.inf, np.inf])  # 上界
 
 
-def saber_planetw_plot(df: pd.DataFrame, T=16):
+def saber_planetw_plot(
+        df: pd.DataFrame,
+        T=16,
+        k=0
+):
     # 定义拟合函数
     def u_func(x, *params):
         a1, b1, a2, b2, a3, b3, a4, b4, a5, b5, a6, b6, a7, b7, a8, b8, a9, b9 = params
@@ -96,27 +100,26 @@ def saber_planetw_plot(df: pd.DataFrame, T=16):
     x_values = fit_df.index.to_numpy()
 
     # 创建一个包含多个子图的图形
-    fig, axs = plt.subplots(len(k_to_a), 1, figsize=(10, 2 * len(k_to_a)))
 
     # 对每一列生成独立的子图
-    for ax, (k, col) in zip(axs, k_to_a.items()):
-        ax.plot(x_values, fit_df[col].values)
-        ax.set_title(f'{k} 振幅图')
-        ax.set_xlabel('Day')
-        ax.set_ylabel('振幅')
+    col = k_to_a[f'k={k}']
+    plt.plot(x_values, fit_df[col].values)
+    plt.set_title(f'k = {k} 振幅图')
+    plt.set_xlabel('Day')
+    plt.set_ylabel('振幅')
 
-        # 设置横坐标的动态调整
-        adjusted_x_values = x_values + (3 * T + 1) / 2
-        if len(adjusted_x_values) > 50:
-            step = 30
-            tick_positions = adjusted_x_values[::step]  # 选择每30个点
-            tick_labels = [f'{int(val)}' for val in tick_positions]
-        else:
-            tick_positions = adjusted_x_values
-            tick_labels = [f'{int(val)}' for val in tick_positions]
+    # 设置横坐标的动态调整
+    adjusted_x_values = x_values + (3 * T + 1) / 2
+    if len(adjusted_x_values) > 50:
+        step = 30
+        tick_positions = adjusted_x_values[::step]  # 选择每30个点
+        tick_labels = [f'{int(val)}' for val in tick_positions]
+    else:
+        tick_positions = adjusted_x_values
+        tick_labels = [f'{int(val)}' for val in tick_positions]
 
-        ax.set_xticks(tick_positions)
-        ax.set_xticklabels(tick_labels)
+    plt.set_xticks(tick_positions)
+    plt.set_xticklabels(tick_labels)
 
     plt.tight_layout()
     # plt.show()