correct readme

README.markdown

@@ -12,6 +12,8 @@ The parser for converting data from the ASOTR MVN control channels into the CSV
 - **Output asotr_csv data files description**
 - **Contacts**
 
+**Note**: \<PATH_TO_ASOTR_CSV\> - path where is asotr_csv program is cloned from heagit
+
 ## Setup
 1. Install Rust compiler (if you don't have).
 Installation on Linux:
@@ -41,7 +43,7 @@ After running this commands you will get an execution file (asotr_csv) in the fo
 \<PATH_TO_ASOTR_CSV\>/target/release/
 
 ## Using
-### parsing ASOTR MVN data files in specified directory
+### Parsing ASOTR MVN data files in specified directory
 1. Donwload data from science data server to directory \<PATH_TO_ASOTR_DATA\>.  
 If you don't have MVN data, you might download it from server with science SRG data (IP: 193.232.11.95).   
 For questions about downloading science data contact Shtykovsky A. (a.shtykovsky@cosmos.ru) or Chelovekov I. (chelovekov@cosmos.ru)   
@@ -62,7 +64,7 @@ cd <PATH_TO_ASOTR_CSV>/target/release/
 csv data are ready to use in directory:  
 \<PATH_TO_ASOTR_CSV\>/target/release/  
 
-### parsing all ASOTR MVN data files in specified directory and subdirectories
+### Parsing all ASOTR MVN data files in specified directory and subdirectories
 1. Donwload data from science data server to directory \<PATH_TO_ASOTR_DATA\>.  
 If you don't have MVN data, you might download it from server with science SRG data (IP: 193.232.11.95).   
 For questions about downloading science data contact Shtykovsky A. (a.shtykovsky@cosmos.ru) or Chelovekov I. (chelovekov@cosmos.ru)
@@ -70,21 +72,36 @@ For questions about downloading science data contact Shtykovsky A. (a.shtykovsky
 2. Run linux bash script **asotr_all_unzip.sh** for directory with MVN data in order to unpack all **asotr.tar.gz** archives with ASOTR MVN data, for example:  
 ```
 cd <PATH_TO_ASOTR_CSV>  
-./asotr_all_unzip.sh <PATH_TO_ASOTR_DATA>   
+./asotr_all_unzip.sh <PATH_TO_ASOTR_DATA>/   
 ```
 
 **Note**: the script **asotr_all_unzip.sh** will not work on windows, you will need to unpack the each archive **\<PATH_TO_ASOTR_DATA\>/\<DIRECTORY_WITH_DATA\>/data/asotr.tar.gz** manually or write the corresponding Windows bat-file  
 
-3. Run program asotr_csv:  
+If you want to parse astor data in specified directory, run program asotr_csv directly:  
 ```
 cd <PATH_TO_ASOTR_CSV>/target/release/  
 ./asotr_csv -d <PATH_TO_ASOTR_DATA> 
 ```
-csv data are ready to use in directory:  
+Or if you want to parse all raw data from ASOTR into csv files and plot csv data you might use shell script:
-\<PATH_TO_ASOTR_CSV\>/target/release/  
+```
+cd <PATH_TO_ASOTR_CSV>  
+./asotr_all_unzip_auto.sh 
+```
+csv data will be in directory:  
+\<PATH_TO_ASOTR_CSV\>/data/  
 
 ### Plot csv data in Python
-If you want to plot csv data you might use \<PATH_TO_ASOTR_CSV\>/**asotr_all_unzip_auto.sh** shell script or use \<PATH_TO_ASOTR_CSV\>/data/**plot_flight_all.py** python-script directly for set different configurations.
+If you want to parse all raw data from astor into csv files and plot csv data you might use shell script:
+```
+cd <PATH_TO_ASOTR_CSV>  
+./asotr_all_unzip_auto.sh 
+```
+
+or if you already have csv files with ASOTR data, you might use plot script only:  
+```
+cd <PATH_TO_ASOTR_CSV>/data/
+python3 plot_flight_all.py
+```
 
 ## Output asotr_csv data files description
 **description:**  

asotr_unzip.sh

@@ -7,5 +7,6 @@ then
 	echo "example 1: $0 ./20250120-000"
 else
 	path_=$1
-	tar -xvzf ${path_}/data/asotr.tar.gz -C ${path_}/data
+	tar -xzf ${path_}/data/asotr.tar.gz -C ${path_}/data
+	tar -xzf ${path_}/logs.tar.gz -C ${path_}
 fi

data/plot_flight_all.py

@@ -4,33 +4,49 @@ import pandas as pd
 from datetime import datetime
 import sys
 
-font = 10
+font = 4
-print_width = 20
+print_width = 6
-print_height = 12
+print_height = 4
 width = 1
 plot_windows = 2
-channels = [1, 1, 1, 1, 1, 1]
+channels = [0, 0, 1, 0, 0, 1]
+asotr_kit = '01'
 
 xborders=False
 begin=0;
 end=0;
 
-path = '/home/danila/Danila/work/MVN/Soft/asotr_csv/data/'
+path_B = './'
-fname = 'asotr01_data_T.csv'
+fname_B = 'beta_2025.xlsx'
-fname_pow = 'asotr01_data_P.csv'
+path = './'
-pict_name = path + "ASOTR1_flight_T_P_all" 
+fname = 'asotr' + asotr_kit + '_data_T.csv'
-ox_dtime_format = '%d.%m.%Y %H:%M'
+fname_pow = 'asotr' + asotr_kit + '_data_P.csv'
+pict_name = path + 'ASOTR' + asotr_kit + '_flight_T_P_all' 
+ox_dtime_format = '%d.%m %H:%M:%S'
 
-legend=['ch1', 'ch2', 'ch3', 'ch4', 'ch5', 'ch6', 'ch7']
+legend=['БРД1', 'БРД2', 'БРД3', 'БРД4', 'плита МУП МВН, датчик1', 'плита МУП МВН, датчик 2']
 width=[1, 1, 1, 1, 1, 1]
 
-marker = ['-', '-', '-', '-', '-', '-'];
+marker = ['-', '-', '-', '-', '--', '-'];
 width_arr = [1, 0.5, 0.2, 0.1, 1, 1]
 
 fname = [path + fname, path + fname_pow]
 
+fname_b = path_B + fname_B
+
 dateparse = lambda x: datetime.strptime(x, "%d.%m.%Y %H:%M:%S.%f")
 
+dparse_b = lambda x: datetime.strptime(x, '%Y-%m-%d %H:%M:%S')
+
+data_b = pd.read_excel(fname_b, 
+        sheet_name=0,
+        usecols=[0,1,2], 
+        header=4,
+        names=['turn_num', 'beta_angle', 'timestamp'],
+        parse_dates=['timestamp'],
+        date_parser=dparse_b)
+
+
 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)]
 
@@ -60,7 +76,7 @@ if plot_windows == 1:
     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])
+            ax.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")
@@ -90,6 +106,12 @@ elif plot_windows == 2:
             ax1.plot(data_dict['time'][begin:end], elem[begin:end], marker[i], linewidth=width[i], label=legend[i])
         i += 1
     
+    ax3 = ax1.twinx()
+    ax3.plot(data_b['timestamp'], data_b['beta_angle'], marker[4], color='r', linewidth=width[5], label='угол Бета')
+    ax3.set_ylabel('Угол Бета', fontsize=font)
+    ax3.tick_params(axis="y", width=1, labelsize=font)
+    ax3.legend(fontsize=font, loc='upper right')
+
     i = 0
     for elem in data_dict['pow']:
         if channels[i] == 1:
@@ -102,20 +124,21 @@ elif plot_windows == 2:
     ax1.grid(visible=True, linestyle = 'dotted')
     ax1.set_ylabel('Температура, $^\circ$C', fontsize=font)
     ax1.set_xlabel('Время', fontsize=font)
-    ax1.legend(fontsize=font)
+    ax1.legend(fontsize=font, loc='lower right')
 
-    date_formatter = dates.DateFormatter('%d.%m.%Y %H')
+    date_formatter = dates.DateFormatter(ox_dtime_format)
     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)
+    ax2.legend(fontsize=font, loc='lower right')
 
     date_formatter = dates.DateFormatter(ox_dtime_format)
     ax2.xaxis.set_major_formatter(date_formatter)
 
+    plt.title('АСОТР ' + asotr_kit, fontsize=font)
     plt.tight_layout()
     fig.savefig(pict_name)
     plt.show()

src/main.rs

@@ -125,6 +125,7 @@ pub mod asotr_data {
             }
 
             data.sort();
+            data.dedup();
 
             if disp { disp_data(&data, &patterns_disp[i])?; }