v0.1.6.3(2024/06/18)
1. [current.py] 适配电机电流中速度使用hw_joint_vel_feedback的数据,取消对device_servo_vel_feedback的支持,后续所有涉及到速度相关的数据均已前者为准,现已完成对单轴和场景的适配 > !!WARNING:目前版本的电机电流程序还支持DriverMaster采集的数据处理,等明确后,将不再支持,也即所有的电机电流数据(工业+协作),都是用诊断曲线来采集
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@ -72,7 +72,7 @@ class App(customtkinter.CTk):
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btns['log']['btn'].configure(command=lambda: self.thread_it(self.func_log_callback))
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btns['end']['btn'].configure(command=lambda: self.thread_it(self.func_end_callback))
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# create version info
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self.label_version = customtkinter.CTkLabel(self.frame_func, justify='left', text="Vers: 0.1.6.2\nDate: 06/16/2024", font=self.my_font, text_color="#4F4F4F")
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self.label_version = customtkinter.CTkLabel(self.frame_func, justify='left', text="Vers: 0.1.6.3\nDate: 06/18/2024", font=self.my_font, text_color="#4F4F4F")
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self.frame_func.rowconfigure(6, weight=1)
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self.label_version.grid(row=6, column=0, padx=20, pady=20, sticky='s')
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# =====================================================================
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@ -232,10 +232,12 @@ def p_single(wb, single, vel, trq, rpm, w2t):
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axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
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shtname = f"J{axis}"
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ws = wb[shtname]
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addition = 1
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set_option("display.precision", 2)
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if data_file.endswith('.data'):
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df = read_csv(data_file, sep='\t')
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rr = float(wb['统计'].cell(row=2, column=axis+1).value)
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addition = 180 / 3.1415926 * 60 / 360 * rr
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elif data_file.endswith('.csv'):
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df = read_csv(data_file, sep=',', encoding='gbk', header=8)
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csv_reader = reader(open(data_file))
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@ -249,7 +251,7 @@ def p_single(wb, single, vel, trq, rpm, w2t):
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ws["H11"] = cycle
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col_names = list(df.columns)
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df_1 = df[col_names[vel-1]].multiply(rpm)
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df_1 = df[col_names[vel-1]].multiply(rpm*addition)
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df_2 = df[col_names[trq-1]].multiply(scale)
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df = concat([df_1, df_2], axis=1)
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@ -309,10 +311,12 @@ def p_scenario(wb, single, vel, trq, rpm, dur, w2t):
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axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
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shtname = f"J{axis}"
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ws = wb[shtname]
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addition = 1
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set_option("display.precision", 2)
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if data_file.endswith('.data'):
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df = read_csv(data_file, sep='\t')
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rr = float(wb['统计'].cell(row=2, column=axis+1).value)
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addition = 180 / 3.1415926 * 60 / 360 * rr
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elif data_file.endswith('.csv'):
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df = read_csv(data_file, sep=',', encoding='gbk', header=8)
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csv_reader = reader(open(data_file))
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@ -326,7 +330,7 @@ def p_scenario(wb, single, vel, trq, rpm, dur, w2t):
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ws["H11"] = cycle
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col_names = list(df.columns)
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df_1 = df[col_names[vel-1]].multiply(rpm)
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df_1 = df[col_names[vel-1]].multiply(rpm*addition)
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df_2 = df[col_names[trq-1]].multiply(scale)
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df = concat([df_1, df_2], axis=1)
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