add exception processing into plot_flight_borders functional

.gitignore

@@ -5,6 +5,5 @@
 *.zip
 *.log
 *.txt
+*.report_*
 /__pycache__
-/data
-/reports

asotr.py

@@ -8,7 +8,16 @@ import json
 import pytz
 from matplotlib import dates
 
-fname_json_decode = '/home/danila/Danila/work/MVN/Soft/PID/python/decode_asotr_cmd.json'
+"""
+module asotr parses csv data from flight device ASOTR MVN
+
+Danila Gamkov []
+danila_gamkov@cosmos.ru
+# License: IKI RAN
+"""
+__author__ = 'Danila Gamkov'
+
+fname_json_decode = './decode_asotr_cmd.json'
 
 def get_utc_seconds(timestamp_str, timestamp_format):
     dt_obj = datetime.strptime(timestamp_str, timestamp_format)
@@ -115,8 +124,20 @@ def cmd_flight_parse(asotr_data):
 
     return (decode_list, temperature_list)
 
-# accuracy: minutes, hours
-def find_best_time_idx(time_arr, user_time, accuracy='minutes'):
+# accuracy: 'seconds', 'minutes', 'hours'
+def find_best_time_idx(time_arr, user_time, accuracy='minutes') -> int:
+    """
+    finds best time index according specified user_time in time_arr and with specified accuracy
+
+    Args:
+        time_arr(pandas.core.series.Series[datetime]): timestamp array
+        user_time(string): time value, which index required find in time_arr (string in the following format: d.m.Y HH:MM:SS)
+        accuracy(string): specify accuracy which time index required find in time_arr(type 'seconds', 'minutes' or 'hours')
+
+    Returns:
+        int: index that has been found in time_arr (or -1 if index has not been found)
+    """
+
     tstamp = datetime.strptime(user_time, "%d.%m.%Y %H:%M:%S")
     if accuracy == 'minutes':
         delta = timedelta(minutes=30)
@@ -166,15 +187,20 @@ def find_best_time_idx(time_arr, user_time, accuracy='minutes'):
                 return j
 
     return mid
-    # raise ValueError("data not found!")
 
 def find_time_idx(data_list, keys_list, timestamp, accuracy):
     out_dict = dict.fromkeys(keys_list, -1)
 
     for i, elem in enumerate(data_list):
-        out_dict[keys_list[i]] = find_best_time_idx(elem['timestamp'], timestamp, accuracy)
+        idx = find_best_time_idx(elem['timestamp'], timestamp, accuracy)
+        if idx != -1:
+            out_dict[keys_list[i]] = idx
+        else:
+            raise TimeIndexNotFound(f'index corresponding to time {timestamp} in times array not found!')
+
     return out_dict
 
+
 def get_cmd_data(fname):
     asotr_data = pd.read_csv(fname, delimiter=';')
     cmd_list, temperature_list = cmd_flight_parse(asotr_data)
@@ -191,9 +217,22 @@ def get_data(path, asotr_kit, start_date, end_date, time_accuracy):
 
     dateparse = lambda x: datetime.strptime(x, "%d.%m.%Y %H:%M:%S.%f")
 
-    data = [ pd.read_csv(fname[0], sep=";", parse_dates=["timestamp"], date_parser=dateparse),
+    try:
+        data = [ pd.read_csv(fname[0], sep=";", parse_dates=["timestamp"], date_parser=dateparse),
             pd.read_csv(fname[1], sep=";", parse_dates=["timestamp"], date_parser=dateparse),
             pd.read_csv(fname[2], sep=";", parse_dates=["timestamp"], date_parser=dateparse),]
+    except FileNotFoundError:
+        print(f'Error opening file: one (or all) file not found in directory: \n{fname}')
+        return
+    except pd.errors.EmptyDataError:
+        print(f'Error opening file: one (or all) file is empty or have incorrect format. \nLook at the files: {fname}')
+        return
+    except pd.errors.ParserError:
+        print(f'Error parsing file: file have incorrect structure. \nLook at the files: {fname}')
+        return
+    except Exception as e:
+        print(f'Error parsing file: {e}. \nLook at the files: {fname}')
+        return
 
     ch = [[], [], [], [], [], []]
     data_dict = {
@@ -208,8 +247,12 @@ def get_data(path, asotr_kit, start_date, end_date, time_accuracy):
     idxb = dict.fromkeys(ch_signs, -1)
     idxe = dict.fromkeys(ch_signs, -1)
 
-    idxb = find_time_idx(data, ch_signs, start_date, time_accuracy)
-    idxe = find_time_idx(data, ch_signs, end_date, time_accuracy)
+    try:
+        idxb = find_time_idx(data, ch_signs, start_date, time_accuracy)
+        idxe = find_time_idx(data, ch_signs, end_date, time_accuracy)
+    except Exception as e:
+        print(e)
+        return
 
     data_dict["time_temp"] = data[0]["timestamp"][idxb["temp"] : idxe["temp"]]
     data_dict["time_temp_set"] = data[1]["timestamp"][idxb["temp_set"] : idxe["temp_set"]]
@@ -324,8 +367,7 @@ def plot_signal_profile(time, data, pattern_t, pattern, method, shift_flag, peak
     plt.grid(True)
     plt.show()
 
-def insert_temp_data_from_flight_cmd(fname_cmd_temp):
-    dir_asotr = '/home/danila/Danila/work/MVN/Soft/asotr_csv/data/'
+def insert_temp_data_from_flight_cmd(fname_cmd_temp, dir_asotr):
     fname_asotr = [f'{dir_asotr}asotr01_data_T.csv', f'{dir_asotr}asotr02_data_T.csv']
 
     df_cmd = pd.read_csv(fname_cmd_temp, sep=';')
@@ -473,13 +515,11 @@ def plot_step_response_in_thermocycle(data_info, thermocycle_info, interp,
 
 
 def plot_imp_response(data, data_info, plot_info, thermocycle_info):
-
     title = f'{plot_info["title"]}, канал {data_info["channel"][2]} АСОТР КДИ СПИН-X, период опроса {data_info["period"]} ({thermocycle_info["date"]})'
 
     fig = plt.figure(figsize=(11, 6), dpi=200)
     fig.suptitle(title, fontsize=plot_info['font'])
     ax1 = fig.add_subplot(1,1,1)
-    
    
     date_formatter = dates.DateFormatter(plot_info['ox_dtime_format'])
     ax1.xaxis.set_major_formatter(date_formatter)
@@ -499,13 +539,12 @@ def plot_imp_response(data, data_info, plot_info, thermocycle_info):
 
 
 #timestamp as string format: dd:mm:YYYY HH:MM:SS 
-def insert_data_cyclo(base_time_str, fname):
-    path = '/home/danila/Danila/work/MVN/flight/experiments/'
+def insert_data_cyclo(base_time_str, fname, path):
     time_format = "%d.%m.%Y %H:%M:%S"
 
     cyclogram_file = path + fname
     df = pd.read_excel(cyclogram_file)
-    base_time = pd.to_datetime(base_time_str)
+    base_time = pd.to_datetime(base_time_str, format='%d.%m.%Y %H:%M:%S')
     df['timestamp'] = df.iloc[:, 0].apply(lambda x: base_time + timedelta(seconds=x))
     df.iloc[:, 0] = df['timestamp'].dt.strftime(time_format)
     df = df.drop(['timestamp'], axis=1)

decode_cmd_data.py

@@ -6,6 +6,7 @@ reload(asotr)
 import pandas as pd
 from datetime import datetime, timedelta
 
+path_data = '/home/danila/Danila/work/MVN/Soft/asotr_csv/data/'
 fname = '/home/danila/Danila/work/MVN/Soft/PID/data/flight/cmd_asotr/all_flight_cmd_asotr.csv'
 fname_cmd_temp = './data/flight_cmd_temp.csv'
 
@@ -23,8 +24,7 @@ with open(fname_cmd_temp, 'w') as file:
         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)
-
+df_asotr_ = asotr.insert_temp_data_from_flight_cmd(fname_cmd_temp, path_data)
 
 ## form timestamp file where minimum of temperatures were registered 
 end_date = ''
@@ -33,7 +33,6 @@ for i, data in enumerate(df_asotr_):
     data.to_csv(f'./data/asotr0{i+1}_data_T.csv', index=False, sep=';', 
             encoding='utf-8-sig', decimal='.')
 
-path_data = '/home/danila/Danila/work/MVN/Soft/asotr_csv/data/'
 timeformat = '%d.%m.%Y %H:%M:%S' 
 prev_days = 14
 

plot_flight_borders.py

@@ -3,7 +3,7 @@ from matplotlib import dates
 import argparse
 import sys
 from importlib import reload
-sys.path.append('/home/danila/Danila/work/MVN/Soft/PID/python/')
+sys.path.append('./')
 import asotr
 reload(asotr)
 import pandas as pd
@@ -16,18 +16,16 @@ def convert_to_str(lst):
         res += f"_{idx + 1}"
     return res
 
-def plot_asotr_borders(ch, asotr_kit, begin, end, font=14, cmd=0):
+def plot_asotr_borders(path_with_data, ch, asotr_kit, begin, end, font=14, cmd=0, show_flag=False):
     print_width = 20
     print_height = 12
     width = 1
     plot_windows = 2
 
     channels = list(map(int, ch))
-
     pict_name = (f'./reports/ASOTR{asotr_kit}_flight_T_P_{convert_to_str(channels)}_{begin[0:5].replace(".", "")}_{end[0:5].replace(".", "")}_{end[6:]}.png')
 
     plot_task = {"temp": 1, "temp_set": 1, "pow": 1}
-
     ox_dtime_format = "%d.%m.%Y"
 
     legend = [
@@ -46,10 +44,12 @@ def plot_asotr_borders(ch, asotr_kit, begin, end, font=14, cmd=0):
     width_arr = [1, 0.5, 0.2, 0.1, 1, 1]
 
     # get from files and prepare data
-    path = "/home/danila/Danila/work/MVN/Soft/asotr_csv/data/"
-    start_date = begin + " 00:00:00"  # Начальная граница
-    end_date = end + " 23:59:59"  # Конечная граница
-    data, data_dict = asotr.get_data(path, asotr_kit, start_date, end_date, 'minutes')
+    start_date = begin + " 00:00:00"  
+    end_date = end + " 23:59:59"  
+    try:
+        data, data_dict = asotr.get_data(path_with_data, asotr_kit, start_date, end_date, 'minutes')
+    except Exception as e:
+        return
     
     if plot_windows == 1:
         fig, ax = plt.subplots(figsize=(print_width, print_height), dpi=200)
@@ -82,10 +82,14 @@ def plot_asotr_borders(ch, asotr_kit, begin, end, font=14, cmd=0):
         ax1 = fig.add_subplot(2, 1, 1)
         ax2 = fig.add_subplot(2, 1, 2, sharex=ax1)
 
-
         if cmd == '1':
-            cmd_human = pd.read_csv('./flight_cmd_human.txt', 
+            fname = './flight_cmd_human.txt'
+            try:
+                cmd_human = pd.read_csv('./flight_cmd_human.txt', 
                     delimiter=';', names=['timestamp', 'cmd'])
+            except Exception as e:
+                print(f'Error parsing file: {e}')
+                return
             
             for i, row in cmd_human.iterrows():
                 if i > 20:
@@ -97,7 +101,7 @@ def plot_asotr_borders(ch, asotr_kit, begin, end, font=14, cmd=0):
                                 linestyle='-.')
                         ax1.text(data_dict['time_temp'][idx], 30, row['cmd'], 
                                 rotation=45, va='bottom', fontsize=font)
-         
+        
         if plot_task["temp"] == 1:
             for i in range(len(channels)):
                 if channels[i] == 1:
@@ -149,11 +153,14 @@ def plot_asotr_borders(ch, asotr_kit, begin, end, font=14, cmd=0):
         fig.suptitle(title, fontsize=font)
         plt.tight_layout()
         fig.savefig(pict_name)
-        plt.show()
+        if show_flag == True:
+            plt.show()
 
 if __name__ == '__main__':
     argparser = argparse.ArgumentParser("plot_flight_borders.py")
 
+    argparser.add_argument('-s', '--source', required=True,
+            help='type path with asotr csv data')
     argparser.add_argument('-c', '--channel', required=True, 
             help='type channel (example: 000011)')
     argparser.add_argument('-a', '--asotr', required=True, 
@@ -166,7 +173,9 @@ if __name__ == '__main__':
             help='type font size (from 1 to 30)')
     argparser.add_argument('-d', '--cmd', required=False, 
             help='type display commands flag (0/1)')
+    argparser.add_argument('-p', '--plot', required=False, 
+            help='display data in plot flag (0/1)')
     args = argparser.parse_args()
 
-    plot_asotr_borders(args.channel, args.asotr, args.begin, args.end, 
-            args.font, args.cmd)
+    plot_asotr_borders(args.source, args.channel, args.asotr, args.begin, args.end, 
+            args.font, args.cmd, args.plot)

plot_flight_borders.sh

@@ -1,19 +1,23 @@
 #! /bin/bash
 
-if [ $# != 2 ]
+if [ $# != 5 ]
 then
 	echo "erorr use $0. Right use this script: "
-	echo "$0 25.02.2025 10.03.2025"
+	echo "$0 path_to_csv_astor_data/ 25.02.2025 10.03.2025 14 0"
 else
-	begin=$1
-	end=$2
-	python3 plot_flight_borders.py -c 111100 -a 01 -b ${begin} -e ${end}
-	python3 plot_flight_borders.py -c 001000 -a 01 -b ${begin} -e ${end}
-	python3 plot_flight_borders.py -c 000011 -a 01 -b ${begin} -e ${end}
-	python3 plot_flight_borders.py -c 111100 -a 02 -b ${begin} -e ${end}
-	python3 plot_flight_borders.py -c 010100 -a 02 -b ${begin} -e ${end}
-	python3 plot_flight_borders.py -c 010000 -a 02 -b ${begin} -e ${end}
-	python3 plot_flight_borders.py -c 000100 -a 02 -b ${begin} -e ${end}
-	python3 plot_flight_borders.py -c 000011 -a 02 -b ${begin} -e ${end}
+	path_csv_data=$1
+	begin=$2
+	end=$3
+	font=$4
+	cmd_flag=$5
+
+	python3 plot_flight_borders.py -s ${path_csv_data} -c 111100 -a 01 -b ${begin} -e ${end} -f ${font} --cmd ${cmd_flag}
+	python3 plot_flight_borders.py -s ${path_csv_data} -c 001000 -a 01 -b ${begin} -e ${end} -f ${font} --cmd ${cmd_flag}
+	python3 plot_flight_borders.py -s ${path_csv_data} -c 000011 -a 01 -b ${begin} -e ${end} -f ${font} --cmd ${cmd_flag}
+	python3 plot_flight_borders.py -s ${path_csv_data} -c 111100 -a 02 -b ${begin} -e ${end} -f ${font} --cmd ${cmd_flag}
+	python3 plot_flight_borders.py -s ${path_csv_data} -c 010100 -a 02 -b ${begin} -e ${end} -f ${font} --cmd ${cmd_flag}
+	python3 plot_flight_borders.py -s ${path_csv_data} -c 010000 -a 02 -b ${begin} -e ${end} -f ${font} --cmd ${cmd_flag}
+	python3 plot_flight_borders.py -s ${path_csv_data} -c 000100 -a 02 -b ${begin} -e ${end} -f ${font} --cmd ${cmd_flag}
+	python3 plot_flight_borders.py -s ${path_csv_data} -c 000011 -a 02 -b ${begin} -e ${end} -f ${font} --cmd ${cmd_flag}
 fi
 

prepare_flight_cyclo.py

@@ -1,17 +1,19 @@
 import sys
 from importlib import reload
-sys.path.append('/home/danila/Danila/work/MVN/Soft/PID/python/')
+sys.path.append('./')
 import asotr
 reload(asotr)
 import pandas as pd
 from datetime import datetime, timedelta
 
-timestamp = '25.04.2025 01:18:00'
+path = './data/experiments/'
+
+timestamp = '03.05.2025 01:27:00'
 cyclogram_file = 'cyclogram_step_ident_ch1.xls'
-asotr.insert_data_cyclo(timestamp, cyclogram_file)
+asotr.insert_data_cyclo(timestamp, cyclogram_file, path)
 
-timestamp = '25.04.2025 04:24:00'
+timestamp = '03.05.2025 04:33:00'
 cyclogram_file = 'cyclogram_imp_ident_ch1.xls'
-asotr.insert_data_cyclo(timestamp, cyclogram_file)
+asotr.insert_data_cyclo(timestamp, cyclogram_file, path)
 
 

temp_peaks_forecast.py

@@ -12,7 +12,7 @@ from datetime import timedelta
 path = '/home/danila/Danila/work/MVN/Soft/asotr_csv/data/'
 channel = 'ch1'
 asotr_kit = '01'
-start_date = '20.04.2025 00:00:00'
+start_date = '23.04.2025 00:00:00'
 forecast_days = 20
 # end_date = '26.03.2025 01:20:00'