project reorganization: 1. executable files in bin directory now. 2. add recursive_unpack_targz.py for recursive unpacking specified in this script archives tar.gz with MVN data. 3. add asotr_unzip_plot.sh bash file for unpacking MVN data, collect asotr data into csv files and plot asotr MVN data. 4. add brd_wheel_1Hz_parser.py for demonstrate how to work with brd telemetry data

bin/decode_cmd_data.py

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+import sys
+from importlib import reload
+sys.path.append('./')
+import asotr
+reload(asotr)
+import pandas as pd
+from datetime import datetime, timedelta
+
+path_data = '../data/asotr/'
+fname_cmd_flight = '../data/cmd_asotr/all_flight_cmd_asotr.csv'
+fname_cmd_temp = '../data/cmd_asotr/flight_cmd_temp.csv'
+fname_cmd_human = '../data/cmd_asotr/cmd_human.csv'
+timeformat = '%d.%m.%Y %H:%M:%S' 
+prev_days = 25
+
+## get flight commands file (generated by mvn_log_viewer) 
+## Translate to human-readeble format and take temperatures from flight commands file
+## save in cmd_human
+cmd_list, temperature_list = asotr.get_cmd_data(fname_cmd_flight)
+with open(fname_cmd_human, 'w') as file:
+    for elem in cmd_list:
+        file.write(f'{elem}\n')
+
+## temperatures from flight commands file save to file flight_cmd_temp
+with open(fname_cmd_temp, 'w') as file:
+    file.write(f'timestamp_sec;timestamp;asotr_kit;ch1;ch2;ch3;ch4;ch5;ch6\r\n')
+    for elem in temperature_list:
+        file.write(f'{elem}\n')
+
+## insert temperatures from flight commands file to main asotr temperatures data files
+df_asotr_ = asotr.insert_temp_data_from_flight_cmd(fname_cmd_temp, path_data)
+
+end_date = ''
+for i, data in enumerate(df_asotr_):
+    end_date = data['timestamp'].iloc[len(data) - 1][0:18]
+    data.to_csv(f'{path_data}asotr0{i+1}_data_T.csv', index=False, sep=';', 
+            encoding='utf-8-sig', decimal='.')
+
+delta_date = datetime.strptime(end_date, timeformat) - timedelta(days=prev_days)
+start_date = delta_date.strftime(timeformat)
+
+## form timestamp file where minimum of temperatures registered 
+for kit in range(1,3):
+    asotr_kit = f'0{kit}'
+    
+    _, data_dict = asotr.get_data(path_data, asotr_kit, start_date, end_date, 'minutes')
+
+    min_temp_ch = []
+    for channel in range(1,7):
+        ch = f'ch{channel}'
+        data1 = data_dict['temp'][ch]
+        time1 = data_dict['time_temp']
+
+        periods_t, periods, _ = asotr.find_periods(time1, data1, shift_flag=False, peaks='min')
+
+        min_temp_period = []
+        for elem in periods_t:
+            min_temp_period.append(elem.iloc[0].strftime('%d.%m.%Y %H:%M:%S.%f')[:-3])
+        
+        min_temp_ch.append(min_temp_period)
+
+    fname = f'{path_data}asotr{asotr_kit}_min_T.csv'
+
+    df = pd.DataFrame(min_temp_ch).transpose()
+    df.to_csv(fname, header=False, index=False, sep=';', 
+            encoding='utf-8-sig', decimal='.')
+    df1 = pd.read_csv(fname, sep=';', 
+            names=['ch1','ch2','ch3','ch4','ch5','ch6'])
+    df1.to_csv(fname, index=False, sep=';', 
+            encoding='utf-8-sig', decimal='.')
+
+
+ 
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