checkpoint: before files dir migrate

.gitignore

@@ -5,4 +5,7 @@
 # Include .gitignore itself
 !.gitignore
 # Recursively allow .py files in subdirectories
-!*/
+!*/
+
+dist
+build

backend.py

@@ -1,3 +1,4 @@
+from matplotlib import pyplot as plt
 import cosmic
 import tidi
 from utils import *
@@ -11,7 +12,10 @@ import sys
 import matplotlib.font_manager as fm
 
 app = Quart(__name__)
+app = cors(app, send_origin_wildcard=True, allow_origin="*")
 
+
+plt.switch_backend('agg')
 fm.fontManager.addfont("./SimHei.ttf")
 @app.before_request
 def auth():
@@ -34,14 +38,13 @@ app.register_blueprint(saber.saber_module, url_prefix="/saber")
 app.register_blueprint(tidi.tidi_module, url_prefix="/tidi")
 app.register_blueprint(cosmic.cosmic_module, url_prefix="/cosmic")
 # allow cors
-app = cors(app)
 
 
 if __name__ == '__main__':
     # get args '--prod'
     args = sys.argv
     if 'prod' in args:
-        
+        app.run("0.0.0.0", port=5000, debug=False)
         pass
     elif 'debug' in args:
         app.run("0.0.0.0",port=18200,debug=True)

cosmic/__init__.py

@@ -2,7 +2,9 @@ from io import BytesIO
 from quart import Blueprint, request, send_file
 from matplotlib import pyplot as plt
 
+from cosmic.single import SingleCosmicWavePlot
 from cosmic.temp_render import temp_render
+from quart.utils import run_sync
 
 
 cosmic_module = Blueprint("Cosmic", __name__)
@@ -14,9 +16,29 @@ def get_meta():
 @cosmic_module.route('/temp_render')
 async def render():
     T = request.args.get("T", 16)
-    temp_render(T=int(T))
+    await run_sync(temp_render)(T=int(T))
     buf = BytesIO()
     
     plt.savefig(buf, format="png")
     buf.seek(0)
+    return await send_file(buf, mimetype="image/png")
+
+@cosmic_module.route('/render/single')
+async def single_render():
+    year = request.args.get("year", 2008)
+    day = request.args.get("day", 1)
+    mode = request.args.get("mode", "mean_ktemp_Nz")
+    
+    p :SingleCosmicWavePlot = await run_sync(SingleCosmicWavePlot)(year=int(year), day=int(day))
+    if mode == "mean_ktemp_Nz":
+        await run_sync(p.plot_results_mean_ktemp_Nz)()
+    elif mode == "mean_ktemp_Ptz":
+        await run_sync(p.plot_results_mean_ktemp_Ptz)()
+    else :
+        raise ValueError("Invalid mode")
+        
+    buf = BytesIO()
+    plt.savefig(buf, format="png")
+    buf.seek(0)
+    
     return await send_file(buf, mimetype="image/png")

cosmic/multiple.py

@@ -15,7 +15,7 @@ plt.rcParams['axes.unicode_minus'] = False            # 正常显示负号
 
 def process_single_file(base_folder_path, i):
     # 构建当前文件夹的路径
-    folder_name = f"atmPrf_repro2021_2018_00{i}" if i < 10 else f"atmPrf_repro2021_2008_0{i}"
+    folder_name = f"atmPrf_repro2021_2008_00{i}" if i < 10 else f"atmPrf_repro2021_2008_0{i}"
     folder_path = os.path.join(base_folder_path, folder_name)
     # 检查文件夹是否存在
     if os.path.exists(folder_path):
@@ -269,7 +269,7 @@ def process_single_file(base_folder_path, i):
 
 
 # 主循环，处理1到3个文件
-base_folder_path = r"./cosmic/data/2018"
+base_folder_path = r"./cosmic/data/2008"
 all_mean_ktemp_Nz = []
 all_mean_ktemp_Ptz = []
 for file_index in range(1, 365):

cosmic/single.py

@@ -1,4 +1,5 @@
 import os
+import time
 import numpy as np
 import pandas as pd
 from scipy.interpolate import interp1d
@@ -22,7 +23,7 @@ def read_and_preprocess_data(base_folder_path, day_num):
     """
     dfs = []
     # 构建当前文件夹的路径
-    folder_name = f"atmPrf_repro2021_2018_00{day_num}" if day_num < 10 else f"atmPrf_repro2021_2018_0{day_num}"
+    folder_name = f"atmPrf_repro2021_2008_00{day_num}" if day_num < 10 else f"atmPrf_repro2021_2008_0{day_num}"
     folder_path = os.path.join(base_folder_path, folder_name)
     # 检查文件夹是否存在
     if os.path.exists(folder_path):
@@ -340,7 +341,7 @@ def calculate_potential_energy(background_temperatures, result, heights):
 # 模块7 绘制重力波势能和浮力频率日图
 
 
-def plot_results(mean_ktemp_Nz, mean_ktemp_Ptz, heights):
+def plot_results_mean_ktemp_Nz(mean_ktemp_Nz, heights):
     """
     绘制平均浮力频率和平均势能随高度变化的图像
 
@@ -350,44 +351,62 @@ def plot_results(mean_ktemp_Nz, mean_ktemp_Ptz, heights):
     heights (np.ndarray): 高度数据数组
     """
     # 绘制平均浮力频率（mean_ktemp_Nz）随高度变化的图像
+    plt.clf()
     plt.figure(figsize=(10, 6))
     plt.plot(mean_ktemp_Nz, heights / 1000)  # 高度单位换算为km，方便展示
     plt.xlabel('Average (N_z)')
     plt.ylabel('H(km)')
     # plt.gca().invert_yaxis()  # 使高度坐标轴从上到下递增，符合常规习惯
-    plt.show()
+    # plt.show()
+    
+def plot_results_mean_ktemp_Ptz(mean_ktemp_Ptz, heights):
+    """
 
     # 绘制平均势能（mean_ktemp_Ptz）随高度变化的图像
+    """
+    # clean the plot
+    plt.clf()
     plt.figure(figsize=(10, 6))
     plt.plot(mean_ktemp_Ptz, heights / 1000)  # 高度单位换算为km，方便展示
     plt.xlabel('Average (PT_z)')
     plt.ylabel('H (km)')
     # plt.gca().invert_yaxis()  # 使高度坐标轴从上到下递增，符合常规习惯
-    plt.show()
+    # plt.show()
 
 
-if __name__ == "__main__":
+class SingleCosmicWavePlot:
-    base_folder_path = r"./cosmic/data/2018"
+    
-    day_num = 1
+    def __init__(self, year, day):
-    # 模块1调用
+        
-    final_df = read_and_preprocess_data(base_folder_path, day_num)
+        base_folder_path = f"./cosmic/data/{year}"
-    # 模块2调用
+        day_num = day
-    latitude_filtered_df, altitude_temperature_mean = filter_and_grid_data(
+        # 模块1调用
-        final_df)
+        final_df = read_and_preprocess_data(base_folder_path, day_num)
-    # 模块3调用
+        # 模块2调用
-    merged_df = calculate_wn0_and_perturbation(
+        latitude_filtered_df, altitude_temperature_mean = filter_and_grid_data(
-        latitude_filtered_df, altitude_temperature_mean)
+            final_df)
-    # 模块4调用
+        # 模块3调用
-    fit_results, residuals, background_temperatures = wave_fitting_and_filtering(
+        merged_df = calculate_wn0_and_perturbation(
-        merged_df)
+            latitude_filtered_df, altitude_temperature_mean)
-    # 模块5调用
+        # 模块4调用
-    result = bandpass_filtering(residuals)
+        fit_results, residuals, background_temperatures = wave_fitting_and_filtering(
-    # 创建从1到80km的高度列表（按照代码中原本逻辑转换为对应单位的数组）
+            merged_df)
-    heights = np.linspace(0, 60000, 3000)
+        # 模块5调用
-    # 模块6调用，计算势能相关数据并获取平均浮力频率和平均势能
+        result = bandpass_filtering(residuals)
-    mean_ktemp_Nz, mean_ktemp_Ptz = calculate_potential_energy(
+        # 创建从1到80km的高度列表（按照代码中原本逻辑转换为对应单位的数组）
-        background_temperatures, result, heights)
+        heights = np.linspace(0, 60000, 3000)
-    print("平均浮力频率（mean_ktemp_Nz）:", mean_ktemp_Nz)
+        # 模块6调用，计算势能相关数据并获取平均浮力频率和平均势能
-    print("平均势能（mean_ktemp_Ptz）:", mean_ktemp_Ptz)
+        mean_ktemp_Nz, mean_ktemp_Ptz = calculate_potential_energy(
+            background_temperatures, result, heights)
+        # print("平均浮力频率（mean_ktemp_Nz）:", mean_ktemp_Nz)
+        # print("平均势能（mean_ktemp_Ptz）:", mean_ktemp_Ptz)
+        self.mean_ktemp_Nz = mean_ktemp_Nz
+        self.mean_ktemp_Ptz = mean_ktemp_Ptz
+        self.heights = heights
     # 调用绘图模块函数进行绘图
-    plot_results(mean_ktemp_Nz, mean_ktemp_Ptz, heights)
+    
+    def plot_results_mean_ktemp_Nz(self):
+        plot_results_mean_ktemp_Nz(self.mean_ktemp_Nz, self.heights)
+    
+    def plot_results_mean_ktemp_Ptz(self):
+        plot_results_mean_ktemp_Ptz(self.mean_ktemp_Ptz, self.heights)

saber/__init__.py

@@ -5,6 +5,7 @@ from matplotlib import pyplot as plt
 from saber.process import DataProcessor
 from saber.render import Renderer
 from saber.utils import *
+from quart.utils import run_sync
 
 
 saber_module = Blueprint('saber', __name__)
@@ -74,8 +75,8 @@ async def do_plot_wave_day_fitting():
 
     ncfile = data_nc_load(path)
     processor = get_processer()
-    data = processor.process_day(ncfile, int(day))
+    data = await run_sync(processor.process_day)(ncfile, int(day))
-    renderer.plot_wave_fitting(data, int(height))
+    await run_sync(renderer.plot_wave_fitting)(data, int(height))
     return await  extract_payload()
 
 
@@ -87,8 +88,9 @@ async def do_day_fft_ifft_plot():
 
     ncfile = data_nc_load(path)
     processor = get_processer()
-    data = processor.process_day(ncfile, int(day))
+    data = await run_sync(processor.process_day)(ncfile, int(day))
-    renderer.day_fft_ifft_plot(wave_data=data, cycle_no=int(cycle_no))
+    # 高度滤波处理
+    await run_sync(renderer.day_fft_ifft_plot)(wave_data=data, cycle_no=int(cycle_no))
     return await  extract_payload()
 
 
@@ -100,8 +102,8 @@ async def do_day_cycle_power_wave_plot():
 
     ncfile = data_nc_load(path)
     processor = get_processer()
-    data = processor.process_day(ncfile, int(day))
+    data = await run_sync(processor.process_day)(ncfile, int(day))
-    renderer.day_cycle_power_wave_plot(wave_data=data, cycle_no=int(cycle_no))
+    await run_sync(renderer.day_cycle_power_wave_plot)(wave_data=data, cycle_no=int(cycle_no))
     return await extract_payload()
 
 
@@ -112,8 +114,8 @@ async def do_month_power_wave_plot():
 
     ncfile = data_nc_load(path)
     processor = get_processer()
-    data = processor.process_month(ncfile)
+    data =await run_sync(processor.process_month)(ncfile)
-    renderer.month_power_wave_plot(wave_data=data, date_time=ncfile.date_time)
+    await run_sync(renderer.month_power_wave_plot)(wave_data=data, date_time=ncfile.date_time)
     return await  extract_payload()
 
 
@@ -121,8 +123,8 @@ async def do_month_power_wave_plot():
 async def do_year_power_wave_plot():
     year = request.args.get("year")
     processor = get_processer()
-    data = processor.process_year([
+    data = await run_sync(processor.process_year)([
         data_nc_load(path) for path in glob.glob(f"./saber/data/{year}/*.nc")
     ])
-    renderer.year_power_wave_plot(year_wave=data)
+    await run_sync(renderer.year_power_wave_plot)(year_wave=data)
     return await extract_payload()

tidi/__init__.py

@@ -1,6 +1,7 @@
 import glob
 from io import BytesIO
 from quart import Blueprint, request, send_file
+from quart.utils import run_sync
 from matplotlib import pyplot as plt
 
 from tidi.plot import TidiPlotv2
@@ -28,7 +29,7 @@ async def render_wave():
     k = int(k)
     T = int(T)
     
-    tidi_render(mode, year, k, T)
+    await run_sync(tidi_render)(mode, year, k, T)
     buffer = BytesIO()
     plt.savefig(buffer, format="png")
     buffer.seek(0)
@@ -40,8 +41,8 @@ async def render_stats_v1():
     year = request.args.get('year')
     year = int(year)
     
-    plotter = TidiPlotv2(year)
+    plotter = await run_sync(TidiPlotv2)(year)
-    plotter.plot_v1()
+    await run_sync(plotter.plot_v1)()
     buffer = BytesIO()
     plt.savefig(buffer, format="png")
     buffer.seek(0)
@@ -52,8 +53,8 @@ async def render_stats_v2():
     year = request.args.get('year')
     year = int(year)
     
-    plotter = TidiPlotv2(year)
+    plotter = await run_sync(TidiPlotv2)(year)
-    plotter.plot_month()
+    await run_sync(plotter.plot_month)()
     buffer = BytesIO()
     plt.savefig(buffer, format="png")
     buffer.seek(0)

tidi/staged/plot.py

@@ -1,3 +1,5 @@
+# 行星波
+
 #此代码是对数据处理后的txt数据进行行星波参数提取绘图
 #2006_TIDI_V_Meridional_data.txt也可以做同样处理，一个是经向风提取的行星波，一个是纬向风的