Refactor: 1. add print into console data, 2. rewrite CLI parsing, 4. the output format csv has been reworked. 5. Add information to README. For addition create python code for plot csv 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 = 2
+channels = [1, 1, 1, 1, 1, 1]
+
+xborders=False
+begin=0;
+end=0;
+
+path = '/home/danila/Danila/work/MVN/Soft/asotr_csv/data/'
+fname = 'asotr01_data_T.csv'
+fname_pow = 'asotr01_data_P.csv'
+pict_name = path + "ASOTR1_flight_T_P_all" 
+ox_dtime_format = '%d.%m.%Y %H:%M'
+
+legend=['ch1', 'ch2', 'ch3', 'ch4', 'ch5', 'ch6', 'ch7']
+width=[1, 1, 1, 1, 1, 1]
+
+marker = ['-', '-', '-', '-', '-', '-'];
+width_arr = [1, 0.5, 0.2, 0.1, 1, 1]
+
+fname = [path + fname, path + fname_pow]
+
+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)]
+
+ch= [[], [], [], [], [], []]
+ch_signs = ["temp", "pow"]
+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= [[], [], [], [], [], []]
+
+len_data = [len(data_dict['temp'][0]), len(data_dict['pow'][0])]
+len_ = min(len_data)
+
+if xborders == False:
+    begin = 0
+    end = len_ - 1
+
+if plot_windows == 1:
+    fig, ax = plt.subplots(figsize=(print_width, print_height), dpi=200)
+
+    i = 0
+    for elem in data_dict['temp']:
+        if channels[i] == 1:
+            plt.plot(data_dict['time'][begin:end], elem[begin:end], 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()
+
+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()
+