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v0.1.6.3(2024/06/18)

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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
This commit is contained in:
gitea 2024-06-18 20:42:48 +08:00
parent 4ba8af842c
commit c3dbb2cff0
5 changed files with 19 additions and 10 deletions
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5
aio/README.md
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@ -229,3 +229,8 @@ v0.1.6.1(2024/06/16)
v0.1.6.2(2024/06/16)
1. [current.py] 修改了max/avg相关功能中对于返回值的处理逻辑，并在输出框以行的形式打印出来
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

8
aio/assets/file_version_info.txt
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@ -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, 1, 6, 2),
prodvers=(0, 1, 6, 2),
filevers=(0, 1, 6, 3),
prodvers=(0, 1, 6, 3),
# 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', '0.1.6.2 (2024-06-16)'),
StringStruct('FileVersion', '0.1.6.3 (2024-06-18)'),
StringStruct('InternalName', 'AIO.exe'),
StringStruct('LegalCopyright', '© 2024-2024 Manford Fan'),
StringStruct('OriginalFilename', 'AIO.exe'),
StringStruct('ProductName', 'AIO'),
StringStruct('ProductVersion', '0.1.6.2 (2024-06-16)')])
StringStruct('ProductVersion', '0.1.6.3 (2024-06-18)')])
]),
VarFileInfo([VarStruct('Translation', [1033, 1200])])
]

2
aio/assets/vers
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@ -1 +1 @@
0.1.6.2 @ 06/16/2024
0.1.6.3 @ 06/18/2024

2
aio/code/aio.py
View File

@ -72,7 +72,7 @@ class App(customtkinter.CTk):
btns['log']['btn'].configure(command=lambda: self.thread_it(self.func_log_callback))
btns['end']['btn'].configure(command=lambda: self.thread_it(self.func_end_callback))
# create version info
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")
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")
self.frame_func.rowconfigure(6, weight=1)
self.label_version.grid(row=6, column=0, padx=20, pady=20, sticky='s')
# =====================================================================

12
aio/code/current.py
View File

@ -232,10 +232,12 @@ def p_single(wb, single, vel, trq, rpm, w2t):
axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
shtname = f"J{axis}"
ws = wb[shtname]
addition = 1
set_option("display.precision", 2)
if data_file.endswith('.data'):
df = read_csv(data_file, sep='\t')
rr = float(wb['统计'].cell(row=2, column=axis+1).value)
addition = 180 / 3.1415926 * 60 / 360 * rr
elif data_file.endswith('.csv'):
df = read_csv(data_file, sep=',', encoding='gbk', header=8)
csv_reader = reader(open(data_file))
@ -249,7 +251,7 @@ def p_single(wb, single, vel, trq, rpm, w2t):
ws["H11"] = cycle
col_names = list(df.columns)
df_1 = df[col_names[vel-1]].multiply(rpm)
df_1 = df[col_names[vel-1]].multiply(rpm*addition)
df_2 = df[col_names[trq-1]].multiply(scale)
df = concat([df_1, df_2], axis=1)
@ -309,10 +311,12 @@ def p_scenario(wb, single, vel, trq, rpm, dur, w2t):
axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
shtname = f"J{axis}"
ws = wb[shtname]
addition = 1
set_option("display.precision", 2)
if data_file.endswith('.data'):
df = read_csv(data_file, sep='\t')
rr = float(wb['统计'].cell(row=2, column=axis+1).value)
addition = 180 / 3.1415926 * 60 / 360 * rr
elif data_file.endswith('.csv'):
df = read_csv(data_file, sep=',', encoding='gbk', header=8)
csv_reader = reader(open(data_file))
@ -326,7 +330,7 @@ def p_scenario(wb, single, vel, trq, rpm, dur, w2t):
ws["H11"] = cycle
col_names = list(df.columns)
df_1 = df[col_names[vel-1]].multiply(rpm)
df_1 = df[col_names[vel-1]].multiply(rpm*addition)
df_2 = df[col_names[trq-1]].multiply(scale)
df = concat([df_1, df_2], axis=1)