1. [current: do_current.py] 增加了 hw_sensor_trq_feedback 曲线的采集

2. [current: current.py] 增加了 hw_sensor_trq_feedback 曲线数据的处理，以及修改了之前数据处理的逻辑
3. [current: clibs.py] 新增可手动修改连接 IP 地址的功能，存储在 assets/templates/ipaddr.txt 中，默认是 192.168.0.160

aio/README.md

@@ -630,3 +630,8 @@ v0.2.0.8(2024/08/20)
 
 v0.2.0.9(2024/10/09)
 1. [main: do_brake.py] 采集完成后，pending 3s，使速度完全将为 0
+
+v0.2.1.0(2024/12/05)
+1. [current: do_current.py] 增加了 hw_sensor_trq_feedback 曲线的采集
+2. [current: current.py] 增加了 hw_sensor_trq_feedback 曲线数据的处理，以及修改了之前数据处理的逻辑
+3. [current: clibs.py] 新增可手动修改连接 IP 地址的功能，存储在 assets/templates/ipaddr.txt 中，默认是 192.168.0.160

aio/assets/file_version_info.txt

@@ -6,8 +6,8 @@ VSVersionInfo(
   ffi=FixedFileInfo(
     # filevers and prodvers should be always a tuple with four items: (1, 2, 3, 4)
     # Set not needed items to zero 0.
-    filevers=(0, 2, 0, 9),
+    filevers=(0, 2, 1, 0),
-    prodvers=(0, 2, 0, 9),
+    prodvers=(0, 2, 1, 0),
     # Contains a bitmask that specifies the valid bits 'flags'r
     mask=0x3f,
     # Contains a bitmask that specifies the Boolean attributes of the file.
@@ -31,12 +31,12 @@ VSVersionInfo(
         '040904b0',
         [StringStruct('CompanyName', 'Rokae - https://www.rokae.com/'),
         StringStruct('FileDescription', 'All in one automatic toolbox'),
-        StringStruct('FileVersion', '0.2.0.9 (2024-10-09)'),
+        StringStruct('FileVersion', '0.2.1.0 (2024-12-05)'),
         StringStruct('InternalName', 'AIO.exe'),
         StringStruct('LegalCopyright', '© 2024-2024 Manford Fan'),
         StringStruct('OriginalFilename', 'AIO.exe'),
         StringStruct('ProductName', 'AIO'),
-        StringStruct('ProductVersion', '0.2.0.9 (2024-10-09)')])
+        StringStruct('ProductVersion', '0.2.1.0 (2024-12-05)')])
       ]),
     VarFileInfo([VarStruct('Translation', [1033, 1200])])
   ]

aio/assets/templates/heartbeat

@@ -1 +1 @@
-0
+1

aio/assets/templates/ipaddr.txt

@@ -0,0 +1 @@
+192.168.0.160

aio/assets/vers

@@ -1 +1 @@
-0.2.0.9 @ 10/09/2024
+0.2.1.0 @ 12/05/2024

aio/code/aio.py

@@ -96,7 +96,7 @@ class App(customtkinter.CTk):
         btns_func['log']['btn'].configure(command=lambda: self.thread_it(self.func_log_callback))
         btns_func['end']['btn'].configure(command=lambda: self.thread_it(self.func_end_callback))
         # 1.3 create version info
-        self.label_version = customtkinter.CTkLabel(self.frame_func, justify='left', text="Vers: 0.2.0.9\nDate: 10/09/2024", font=self.my_font, text_color="#4F4F4F")
+        self.label_version = customtkinter.CTkLabel(self.frame_func, justify='left', text="Vers: 0.2.1.0\nDate: 12/05/2024", font=self.my_font, text_color="#4F4F4F")
         self.frame_func.rowconfigure(6, weight=1)
         self.label_version.grid(row=6, column=0, padx=20, pady=20, sticky='s')
         # =====================================================================

aio/code/automatic_test/do_current.py

@@ -21,6 +21,12 @@ display_pdo_params = [
     {"name": "device_servo_trq_feedback", "channel": 3},
     {"name": "device_servo_trq_feedback", "channel": 4},
     {"name": "device_servo_trq_feedback", "channel": 5},
+    {"name": "hw_sensor_trq_feedback", "channel": 0},
+    {"name": "hw_sensor_trq_feedback", "channel": 1},
+    {"name": "hw_sensor_trq_feedback", "channel": 2},
+    {"name": "hw_sensor_trq_feedback", "channel": 3},
+    {"name": "hw_sensor_trq_feedback", "channel": 4},
+    {"name": "hw_sensor_trq_feedback", "channel": 5},
 ]
 
 
@@ -63,6 +69,7 @@ def data_proc_regular(path, filename, channel, scenario_time):
             lines = f_obj.readlines()
             _d2d_vel = {'hw_joint_vel_feedback': []}
             _d2d_trq = {'device_servo_trq_feedback': []}
+            _d2d_sensor = {'hw_sensor_trq_feedback': []}
             for line in lines[-500:]:  # 保留最后25s的数据
                 data = eval(line.strip())['data']
                 for item in data:
@@ -74,10 +81,13 @@ def data_proc_regular(path, filename, channel, scenario_time):
                         _d2d_vel['hw_joint_vel_feedback'].extend(item['value'])
                     elif item.get('channel', None) == channel and item.get('name', None) == 'device_servo_trq_feedback':
                         _d2d_trq['device_servo_trq_feedback'].extend(item['value'])
+                    elif item.get('channel', None) == channel and item.get('name', None) == 'hw_sensor_trq_feedback':
+                        _d2d_sensor['hw_sensor_trq_feedback'].extend(item['value'])
 
             df1 = DataFrame.from_dict(_d2d_vel)
             df2 = DataFrame.from_dict(_d2d_trq)
-            df = concat([df1, df2], axis=1)
+            df3 = DataFrame.from_dict(_d2d_sensor)
+            df = concat([df1, df2, df3], axis=1)
             _filename = f'{path}\\single\\j{channel+1}_single_{time()}.data'
             df.to_csv(_filename, sep='\t', index=False)
     elif channel in list(range(6, 9)):
@@ -85,16 +95,22 @@ def data_proc_regular(path, filename, channel, scenario_time):
             lines = f_obj.readlines()
             _d2d_vel_0 = {'hw_joint_vel_feedback': []}
             _d2d_trq_0 = {'device_servo_trq_feedback': []}
+            _d2d_sensor_0 = {'hw_sensor_trq_feedback': []}
             _d2d_vel_1 = {'hw_joint_vel_feedback': []}
             _d2d_trq_1 = {'device_servo_trq_feedback': []}
+            _d2d_sensor_1 = {'hw_sensor_trq_feedback': []}
             _d2d_vel_2 = {'hw_joint_vel_feedback': []}
             _d2d_trq_2 = {'device_servo_trq_feedback': []}
+            _d2d_sensor_2 = {'hw_sensor_trq_feedback': []}
             _d2d_vel_3 = {'hw_joint_vel_feedback': []}
             _d2d_trq_3 = {'device_servo_trq_feedback': []}
+            _d2d_sensor_3 = {'hw_sensor_trq_feedback': []}
             _d2d_vel_4 = {'hw_joint_vel_feedback': []}
             _d2d_trq_4 = {'device_servo_trq_feedback': []}
+            _d2d_sensor_4 = {'hw_sensor_trq_feedback': []}
             _d2d_vel_5 = {'hw_joint_vel_feedback': []}
             _d2d_trq_5 = {'device_servo_trq_feedback': []}
+            _d2d_sensor_5 = {'hw_sensor_trq_feedback': []}
             for line in lines:
                 data = eval(line.strip())['data']
                 for item in data:
@@ -106,60 +122,78 @@ def data_proc_regular(path, filename, channel, scenario_time):
                         _d2d_vel_0['hw_joint_vel_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 0 and item.get('name', None) == 'device_servo_trq_feedback':
                         _d2d_trq_0['device_servo_trq_feedback'].extend(item['value'])
+                    elif item.get('channel', None) == 0 and item.get('name', None) == 'hw_sensor_trq_feedback':
+                        _d2d_sensor_0['hw_sensor_trq_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 1 and item.get('name', None) == 'hw_joint_vel_feedback':
                         _d2d_vel_1['hw_joint_vel_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 1 and item.get('name', None) == 'device_servo_trq_feedback':
                         _d2d_trq_1['device_servo_trq_feedback'].extend(item['value'])
+                    elif item.get('channel', None) == 1 and item.get('name', None) == 'hw_sensor_trq_feedback':
+                        _d2d_sensor_1['hw_sensor_trq_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 2 and item.get('name', None) == 'hw_joint_vel_feedback':
                         _d2d_vel_2['hw_joint_vel_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 2 and item.get('name', None) == 'device_servo_trq_feedback':
                         _d2d_trq_2['device_servo_trq_feedback'].extend(item['value'])
+                    elif item.get('channel', None) == 3 and item.get('name', None) == 'hw_sensor_trq_feedback':
+                        _d2d_sensor_2['hw_sensor_trq_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 3 and item.get('name', None) == 'hw_joint_vel_feedback':
                         _d2d_vel_3['hw_joint_vel_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 3 and item.get('name', None) == 'device_servo_trq_feedback':
                         _d2d_trq_3['device_servo_trq_feedback'].extend(item['value'])
+                    elif item.get('channel', None) == 3 and item.get('name', None) == 'hw_sensor_trq_feedback':
+                        _d2d_sensor_3['hw_sensor_trq_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 4 and item.get('name', None) == 'hw_joint_vel_feedback':
                         _d2d_vel_4['hw_joint_vel_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 4 and item.get('name', None) == 'device_servo_trq_feedback':
                         _d2d_trq_4['device_servo_trq_feedback'].extend(item['value'])
+                    elif item.get('channel', None) == 4 and item.get('name', None) == 'hw_sensor_trq_feedback':
+                        _d2d_sensor_4['hw_sensor_trq_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 5 and item.get('name', None) == 'hw_joint_vel_feedback':
                         _d2d_vel_5['hw_joint_vel_feedback'].extend(item['value'])
                     elif item.get('channel', None) == 5 and item.get('name', None) == 'device_servo_trq_feedback':
                         _d2d_trq_5['device_servo_trq_feedback'].extend(item['value'])
+                    elif item.get('channel', None) == 5 and item.get('name', None) == 'hw_sensor_trq_feedback':
+                        _d2d_sensor_5['hw_sensor_trq_feedback'].extend(item['value'])
 
             df_01 = DataFrame.from_dict(_d2d_vel_0)
             df_02 = DataFrame.from_dict(_d2d_trq_0)
-            df = concat([df_01, df_02], axis=1)
+            df_03 = DataFrame.from_dict(_d2d_sensor_0)
+            df = concat([df_01, df_02, df_03], axis=1)
             _filename = f'{path}\\s_{channel-5}\\j1_s_{channel-5}_{scenario_time}_{time()}.data'
             df.to_csv(_filename, sep='\t', index=False)
 
             df_01 = DataFrame.from_dict(_d2d_vel_1)
             df_02 = DataFrame.from_dict(_d2d_trq_1)
-            df = concat([df_01, df_02], axis=1)
+            df_03 = DataFrame.from_dict(_d2d_sensor_1)
+            df = concat([df_01, df_02, df_03], axis=1)
             _filename = f'{path}\\s_{channel-5}\\j2_s_{channel-5}_{scenario_time}_{time()}.data'
             df.to_csv(_filename, sep='\t', index=False)
 
             df_01 = DataFrame.from_dict(_d2d_vel_2)
             df_02 = DataFrame.from_dict(_d2d_trq_2)
-            df = concat([df_01, df_02], axis=1)
+            df_03 = DataFrame.from_dict(_d2d_sensor_2)
+            df = concat([df_01, df_02, df_03], axis=1)
             _filename = f'{path}\\s_{channel-5}\\j3_s_{channel-5}_{scenario_time}_{time()}.data'
             df.to_csv(_filename, sep='\t', index=False)
 
             df_01 = DataFrame.from_dict(_d2d_vel_3)
             df_02 = DataFrame.from_dict(_d2d_trq_3)
-            df = concat([df_01, df_02], axis=1)
+            df_03 = DataFrame.from_dict(_d2d_sensor_3)
+            df = concat([df_01, df_02, df_03], axis=1)
             _filename = f'{path}\\s_{channel-5}\\j4_s_{channel-5}_{scenario_time}_{time()}.data'
             df.to_csv(_filename, sep='\t', index=False)
 
             df_01 = DataFrame.from_dict(_d2d_vel_4)
             df_02 = DataFrame.from_dict(_d2d_trq_4)
-            df = concat([df_01, df_02], axis=1)
+            df_03 = DataFrame.from_dict(_d2d_sensor_4)
+            df = concat([df_01, df_02, df_03], axis=1)
             _filename = f'{path}\\s_{channel-5}\\j5_s_{channel-5}_{scenario_time}_{time()}.data'
             df.to_csv(_filename, sep='\t', index=False)
 
             df_01 = DataFrame.from_dict(_d2d_vel_5)
             df_02 = DataFrame.from_dict(_d2d_trq_5)
-            df = concat([df_01, df_02], axis=1)
+            df_03 = DataFrame.from_dict(_d2d_sensor_5)
+            df = concat([df_01, df_02, df_03], axis=1)
             _filename = f'{path}\\s_{channel-5}\\j6_s_{channel-5}_{scenario_time}_{time()}.data'
             df.to_csv(_filename, sep='\t', index=False)
     elif channel in list(range(9, 15)):
@@ -167,6 +201,7 @@ def data_proc_regular(path, filename, channel, scenario_time):
             lines = f_obj.readlines()
             _d2d_vel = {'hw_joint_vel_feedback': []}
             _d2d_trq = {'device_servo_trq_feedback': []}
+            _d2d_sensor = {'hw_sensor_trq_feedback': []}
             for line in lines[-300:]:  # 保留最后15s的数据
                 data = eval(line.strip())['data']
                 for item in data:
@@ -178,10 +213,13 @@ def data_proc_regular(path, filename, channel, scenario_time):
                         _d2d_vel['hw_joint_vel_feedback'].extend(item['value'])
                     elif item.get('channel', None) == channel-9 and item.get('name', None) == 'device_servo_trq_feedback':
                         _d2d_trq['device_servo_trq_feedback'].extend(item['value'])
+                    elif item.get('channel', None) == channel-9 and item.get('name', None) == 'hw_sensor_trq_feedback':
+                        _d2d_sensor['hw_sensor_trq_feedback'].extend(item['value'])
 
             df1 = DataFrame.from_dict(_d2d_vel)
             df2 = DataFrame.from_dict(_d2d_trq)
-            df = concat([df1, df2], axis=1)
+            df3 = DataFrame.from_dict(_d2d_sensor)
+            df = concat([df1, df2, df3], axis=1)
             _filename = f'{path}\\single\\j{channel-8}_hold_{time()}.data'
             df.to_csv(_filename, sep='\t', index=False)
 
@@ -191,6 +229,7 @@ def data_proc_inertia(path, filename, channel):
         lines = f_obj.readlines()
         _d2d_vel = {'hw_joint_vel_feedback': []}
         _d2d_trq = {'device_servo_trq_feedback': []}
+        _d2d_sensor = {'hw_sensor_trq_feedback': []}
         for line in lines:
             data = eval(line.strip())['data']
             for item in data:
@@ -202,10 +241,13 @@ def data_proc_inertia(path, filename, channel):
                     _d2d_vel['hw_joint_vel_feedback'].extend(item['value'])
                 elif item.get('channel', None) == channel+3 and item.get('name', None) == 'device_servo_trq_feedback':
                     _d2d_trq['device_servo_trq_feedback'].extend(item['value'])
+                elif item.get('channel', None) == channel+3 and item.get('name', None) == 'hw_sensor_trq_feedback':
+                    _d2d_trq['hw_sensor_trq_feedback'].extend(item['value'])
 
         df1 = DataFrame.from_dict(_d2d_vel)
         df2 = DataFrame.from_dict(_d2d_trq)
-        df = concat([df1, df2], axis=1)
+        df3 = DataFrame.from_dict(_d2d_sensor)
+        df = concat([df1, df2, df3], axis=1)
         _filename = f'{path}\\inertia\\j{channel+4}_inertia_{time()}.data'
         df.to_csv(_filename, sep='\t', index=False)
 

aio/code/commons/clibs.py

@@ -8,16 +8,15 @@ from logging import getLogger
 from logging.config import dictConfig
 import concurrent_log_handler
 
-ip_addr = '192.168.0.160'  # for product
-# ip_addr = '192.168.84.129'  # for test
 RADIAN = 57.3  # 180 / 3.1415926
 MAX_FRAME_SIZE = 1024
 TIMEOUT = 5
 setdefaulttimeout(TIMEOUT)
 tab_names = {'dp': 'Data Process', 'at': 'Automatic Test', 'da': 'Duration Action', 'op': 'openapi'}
 # PREFIX = ''  # for pyinstaller packaging
-PREFIX = '../assets/'  # for source code debug
+PREFIX = '../assets/'  # for source code testing and debug
 app_icon = f'{PREFIX}templates/icon.ico'
+ip_file = f'{PREFIX}templates/ipaddr.txt'
 log_path = f'{PREFIX}templates/logs/'
 log_data_hmi = f'{PREFIX}templates/logs/c_msg.log'
 log_data_debug = f'{PREFIX}templates/logs/debug.log'
@@ -42,6 +41,14 @@ durable_data_current_max = {
     'axis5': [0 for _ in range(18)],
     'axis6': [0 for _ in range(18)],
 }
+try:
+    with open(ip_file, mode="r", encoding="utf-8") as f_ipaddr:
+        ip_addr = f_ipaddr.read().strip()
+except:
+    ip_addr = '192.168.0.160'
+
+# ip_addr = '192.168.0.160'  # for product
+# ip_addr = '192.168.84.129'  # for test
 
 if not exists(log_path):
     mkdir(log_path)

aio/code/commons/openapi.py

@@ -19,7 +19,7 @@ class ModbusRequest(object):
         self.host = clibs.ip_addr
         self.port = 502
         self.interval = 0.3
-        self.c = ModbusTcpClient(self.host, self.port)
+        self.c = ModbusTcpClient(host=self.host, port=self.port)
         self.c.connect()
 
     def motor_off(self):

aio/code/data_process/current.py

@@ -33,7 +33,8 @@ def initialization(path, sub, w2t):
         else:
             if not (match('j[1-7].*\\.data', filename) or match('j[1-7].*\\.csv', filename)):
                 msg = f"不合规 {data_file}\n"
-                msg += f"所有数据文件必须以 jx_ 开头，以 .data/csv 结尾（x取值1-7），配置文件需要命名为\"configs.xlsx\"，结果文件需要命名为\"T_电机电流.xlsx\"，请检查后重新运行。"
+                msg += f"所有数据文件必须以 jx_ 开头，以 .data/csv 结尾（x取值1-7），配置文件需要命名为\"configs.xlsx\"，结果文件需要命名为\"T_电机电流.xlsx\"，请检查后重新运行。\n"
+                msg += "使用max/avg功能时，需要有配置文件表格\"configs.xlsx\"；使用cycle功能时，需要有电机电流数据处理\"T_电机电流.xlsx\"和配置文件\"configs.xlsx\"两个表格，确认后重新运行！"
                 w2t(msg, 0, 6, 'red')
 
     if not ((sub == 'cycle' and count == 2) or (sub != 'cycle' and count == 1)):
@@ -186,7 +187,6 @@ def find_point(data_file, pos, flag, df, _row_s, _row_e, w2t, exitcode, threshol
             else:
                 return _row_s, _row_e
         else:
-            # w2t(f"[{pos}] {data_file}数据有误，需要检查，无法找到第{exitcode}个有效点...", 0, exitcode, 'red')
             w2t(f"[{pos}] {data_file}数据有误，需要检查，无法找到第{exitcode}个有效点...", 0, 0, 'red')
     elif flag == 'gt':
         while _row_e > end_point:
@@ -198,7 +198,6 @@ def find_point(data_file, pos, flag, df, _row_s, _row_e, w2t, exitcode, threshol
             else:
                 return _row_s, _row_e
         else:
-            # w2t(f"[{pos}] {data_file}数据有误，需要检查，无法找到有效起始点或结束点...", 0, exitcode, 'red')
             w2t(f"[{pos}] {data_file}数据有误，需要检查，无法找到有效起始点或结束点...", 0, 0, 'red')
 
 
@@ -234,6 +233,7 @@ def p_single(wb, single, vel, trq, rpms, rrs, w2t):
         df_1 = df[col_names[vel-1]].multiply(rpm*addition)
         df_2 = df[col_names[trq-1]].multiply(scale)
         # print(df_1.abs().max())
+        df_origin = df
         df = concat([df_1, df_2], axis=1)
 
         _step = 5 if data_file.endswith('.csv') else 50
@@ -270,11 +270,12 @@ def p_single(wb, single, vel, trq, rpms, rrs, w2t):
         row_start = _row_s + _adjust
         data = []
         for row in range(row_start, row_end):
-            data.append(df.iloc[row, 0])
+            data.append(df_origin.iloc[row, 0])
-            data.append(df.iloc[row, 1])
+            data.append(df_origin.iloc[row, 1])
+            data.append(df_origin.iloc[row, 2])
 
         i = 0
-        for row in ws.iter_rows(min_row=2, min_col=2, max_row=150000, max_col=3):
+        for row in ws.iter_rows(min_row=2, min_col=2, max_row=150000, max_col=4):
             for cell in row:
                 try:
                     _ = f"{data[i]:.2f}"