1. Add CLI parser, 2. add python script for visualisation data

data/plot_flight_all.py

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+import matplotlib.pyplot as plt
+from  matplotlib import dates
+import pandas as pd
+from datetime import datetime
+import sys
+
+font = 10
+print_width = 20
+print_height = 12
+width = 1
+plot_windows = 1
+channels = [1, 1, 1, 1]
+
+path = '/home/danila/Danila/work/MVN/Soft/mvn_accomp_csv/data/'
+fname = [path + 'MVN_data_T1MVN.csv', 
+        path + 'MVN_data_T2MVN.csv', 
+        path + 'MVN_data_T3MVN.csv', 
+        path + 'MVN_data_T4MVN.csv'] 
+
+pict_name = path + "T1_4MVN" 
+ox_dtime_format = '%d.%m.%Y %H:%M'
+
+legend=['T1МВН', 'T2МВН', 'T3МВН', 'T4МВН']
+ch_names=['T1MVN', 'T2MVN', 'T3MVN', 'T4MVN']
+width=[1, 1, 1, 1]
+
+marker = ['-', '-', '-', '-'];
+width_arr = [1, 0.5, 0.2, 0.1]
+
+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),
+        pd.read_csv(fname[1], sep=';', parse_dates=['timestamp'], date_parser=dateparse),
+        pd.read_csv(fname[2], sep=';', parse_dates=['timestamp'], date_parser=dateparse),
+        pd.read_csv(fname[3], sep=';', parse_dates=['timestamp'], date_parser=dateparse)]
+
+# data_dict = {"temp": ch, "pow": ch, "time": []}
+# data_dict["time"] = data[0]['timestamp']
+# col=['ch1', 'ch2', 'ch3', 'ch4', 'ch5', 'ch6', 'ch7']
+
+# for j in range(2):
+#     for index, row, in data[j].iterrows():
+#         for i in range(6):
+#             ch[i].append(float(row[col[i]]))
+#     data_dict[ch_signs[j]] = ch
+#     ch= [[], [], [], [], [], []]
+
+if plot_windows == 1:
+    fig, ax = plt.subplots(figsize=(print_width, print_height), dpi=200)
+
+    i = 0
+    for elem in data:
+        if channels[i] == 1:
+            plt.plot(elem['timestamp'], elem[ch_names[i]], marker[i], linewidth=width[i], label=legend[i])
+        i += 1
+
+    # ax.axvline(x = data['timestamp'][300], color='r', linestyle='-.', label="power=100")
+    # ax.axvline(x = data['timestamp'][1500], color='b', linestyle='dotted', label="power=0")
+    ax.tick_params(axis="both", width=1, labelsize=font)
+    ax.grid(visible=True, linestyle = 'dotted')
+    ax.set_ylabel('Температура, $^\circ$C', fontsize=font)
+    ax.set_xlabel('Время', fontsize=font)
+    ax.legend(fontsize=font)
+
+    date_formatter = dates.DateFormatter(ox_dtime_format)
+    ax.xaxis.set_major_formatter(date_formatter)
+
+    plt.tight_layout()
+    fig.savefig(pict_name)
+    plt.show()
+
+sys.exit()
+# elif plot_windows == 2:
+
+#     fig = plt.figure(figsize=(print_width, print_height), dpi=200)
+#     ax1 = fig.add_subplot(2, 1, 1)
+#     ax2 = fig.add_subplot(2, 1, 2, sharex=ax1)
+
+#     i = 0
+#     for elem in data_dict['temp']:
+#         if channels[i] == 1:
+#             ax1.plot(data_dict['time'][begin:end], elem[begin:end], marker[i], linewidth=width[i], label=legend[i])
+#         i += 1
+    
+#     i = 0
+#     for elem in data_dict['pow']:
+#         if channels[i] == 1:
+#             ax2.plot(data_dict['time'][begin:end], elem[begin:end], marker[i], linewidth=width[i], label=legend[i])
+#         i += 1
+
+#     # ax1.axvline(x = data['timestamp'][300], color='r', linestyle='-.', label="power=100")
+#     # ax.axvline(x = data['timestamp'][1500], color='b', linestyle='dotted', label="power=0")
+#     ax1.tick_params(axis="both", width=1, labelsize=font)
+#     ax1.grid(visible=True, linestyle = 'dotted')
+#     ax1.set_ylabel('Температура, $^\circ$C', fontsize=font)
+#     ax1.set_xlabel('Время', fontsize=font)
+#     ax1.legend(fontsize=font)
+
+#     date_formatter = dates.DateFormatter('%d.%m.%Y %H')
+#     ax1.xaxis.set_major_formatter(date_formatter)
+
+#     ax2.tick_params(axis="both", width=1, labelsize=font)
+#     ax2.grid(visible=True, linestyle = 'dotted')
+#     ax2.set_ylabel('Мощность, %', fontsize=font)
+#     ax2.set_xlabel('Время', fontsize=font)
+#     ax2.legend(fontsize=font)
+
+#     date_formatter = dates.DateFormatter(ox_dtime_format)
+#     ax2.xaxis.set_major_formatter(date_formatter)
+
+#     plt.tight_layout()
+#     fig.savefig(pict_name)
+#     plt.show()
+