From bede2322ac002e463d7b3e70972a0721ebe12357 Mon Sep 17 00:00:00 2001
From: Danila Gamkov <danila.gamkov@mail.ru>
Date: Fri, 21 Feb 2025 20:14:54 +0300
Subject: [PATCH] remove consecutive repeated values in data

---
 data/plot_flight_all.py | 44 ++++++++++++++++++++++++++++++-----------
 src/main.rs             |  1 +
 2 files changed, 33 insertions(+), 12 deletions(-)

diff --git a/data/plot_flight_all.py b/data/plot_flight_all.py
index 2176b0b..c8f9634 100644
--- a/data/plot_flight_all.py
+++ b/data/plot_flight_all.py
@@ -4,9 +4,9 @@ import pandas as pd
 from datetime import datetime
 import sys
 
-font = 10
-print_width = 20
-print_height = 12
+font = 8
+print_width = 10
+print_height = 8
 width = 1
 plot_windows = 2
 channels = [1, 1, 1, 1, 1, 1]
@@ -15,22 +15,37 @@ xborders=False
 begin=0;
 end=0;
 
+path_B = '/home/danila/Danila/work/MVN/flight/beta_forecast/'
+fname_B = 'beta_2025.xlsx'
 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'
+fname = 'asotr02_data_T.csv'
+fname_pow = 'asotr02_data_P.csv'
+pict_name = path + "ASOTR2_flight_T_P_all" 
+ox_dtime_format = '%d %H:%M'
 
-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 +75,7 @@ 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 +105,11 @@ 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], linewidth=width[5], label='угол Бета')
+    ax3.set_ylabel('Угол Бета', fontsize=font)
+    ax3.legend(fontsize=font, loc='upper right')
+
     i = 0
     for elem in data_dict['pow']:
         if channels[i] == 1:
@@ -102,7 +122,7 @@ 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')
     ax1.xaxis.set_major_formatter(date_formatter)
@@ -111,7 +131,7 @@ elif plot_windows == 2:
     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)
diff --git a/src/main.rs b/src/main.rs
index b374cbe..d3ef644 100644
--- a/src/main.rs
+++ b/src/main.rs
@@ -125,6 +125,7 @@ pub mod asotr_data {
             }
 
             data.sort();
+            data.dedup();
 
             if disp { disp_data(&data, &patterns_disp[i])?; }