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v0.1.4(2024/06/06)

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1. AV/RR支持小数
2. 可处理电机电流单轴以及多轴数据，可根据需要进行参数设定处理不同轴的数据
3. 界面初始位置修改，以及删除所有entry的长度设定，因为设定无效
4. 修改了layout.xlsx布局，增加了duration/trqH/STO字段，以及额外的RC行，整体扩展了区域
5. 更改label/entry/optionmenu等控件的生成方式，使用循环实现，更加简洁和容易维护（暂未实现）
6. 支持工业/协作两条产品线的电机电流数据处理，包括单轴，场景，max/avg计算
This commit is contained in:
gitea
2024-06-06 19:04:55 +08:00
parent 97ba8ffc51
commit a0404c0003
4 changed files with 172 additions and 76 deletions
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195
aio/current.py
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@ -2,11 +2,11 @@ from openpyxl import load_workbook
from os import scandir
from os.path import exists
from sys import argv
from pandas import read_csv
from pandas import read_csv, concat, set_option
from re import match
from threading import Thread
from time import sleep
from csv import reader
class GetThreadResult(Thread):
def __init__(self, func, args=()):
super(GetThreadResult, self).__init__()
@ -42,7 +42,7 @@ def traversal_files(path, w2t):
# 返回值：路径下的文件夹列表 路径下的文件列表
if not exists(path):
msg = f'数据文件夹{path}不存在，请确认后重试......'
w2t(msg, 0, 1)
w2t(msg, 0, 8)
else:
dirs = []
files = []
@ -64,16 +64,16 @@ def initialization(path, sub, w2t):
if sub != 'cycle':
if not (match('j[1-7].*\\.data', filename) or match('j[1-7].*\\.csv', filename)):
msg = f"所有文件必须以 jx_ 开头，以 .data/csv 结尾（x取值1-7），请检查后重新运行。"
w2t(msg, 0, 2)
w2t(msg, 0, 6)
else:
if filename.endswith('.xlsx'):
count += 1
elif not (match('j[1-7].*\\.data', filename) or match('j[1-7].*\\.csv', filename)):
msg = f"所有文件必须以 jx_ 开头，以 .data/csv 结尾（x取值1-7），请检查后重新运行。"
w2t(msg, 0, 3)
w2t(msg, 0, 7)
if sub == 'cycle' and count != 1:
w2t("未找到电机电流数据处理excel表格，确认后重新运行！", 0, 4)
w2t("未找到电机电流数据处理excel表格，确认后重新运行！", 0, 5)
return data_files
@ -125,7 +125,7 @@ def current_avg(data_files, rcs, trqh, w2t):
return current
def current_cycle(dur, data_files, rcs, vel, trq, trqh, w2t):
def current_cycle(dur, data_files, rcs, vel, trq, trqh, rpm, w2t):
result = None
hold = []
single = []
@ -162,9 +162,9 @@ def current_cycle(dur, data_files, rcs, vel, trq, trqh, w2t):
pass
if dur == 0:
p_single(wb, single, vel, trq, w2t)
p_single(wb, single, vel, trq, rpm, w2t)
else:
p_scenario()
p_scenario(wb, single, vel, trq, rpm, dur, w2t)
w2t(f"正在保存文件 {result}，需要 10s 左右", 1)
stop = 0
@ -180,94 +180,171 @@ def current_cycle(dur, data_files, rcs, vel, trq, trqh, w2t):
w2t("全部处理完毕")
def p_single(wb, single, vel, trq, w2t):
def find_point(flag, df, _row_s, _row_e, w2t, exitcode, threshold, step, end_point):
if flag == 'lt':
while _row_e > end_point:
speed_avg = df.iloc[_row_s:_row_e, 0].abs().mean()
if speed_avg < threshold:
_row_e -= step
_row_s -= step
continue
else:
return _row_s, _row_e
else:
w2t(f"数据有误，需要检查，无法找到第{exitcode}个有效点...", 0, exitcode)
elif flag == 'gt':
while _row_e > end_point:
speed_avg = df.iloc[_row_s:_row_e, 0].abs().mean()
if speed_avg > threshold:
_row_e -= step
_row_s -= step
continue
else:
return _row_s, _row_e
else:
w2t(f"数据有误，需要检查，无法找到有效起始点或结束点...", 0, exitcode)
def p_single(wb, single, vel, trq, rpm, w2t):
# 1. 先找到第一个速度为零的点，数据从后往前找，一开始就是零的情况不予考虑
# 2. 记录第一个点的位置，继续向前查找第二个速度为零的点，同理，一开始为零的点不予考虑
# 3. 记录第二个点的位置，并将其中的数据拷贝至对应位置
for data_file in single:
rpm = 1 if rpm == 0 else rpm
scale = 1000 if data_file.endswith('.csv') else 1
axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
shtname = f"J{axis}"
ws = wb[shtname]
set_option("display.precision", 2)
if data_file.endswith('.data'):
df = read_csv(data_file, sep='\t')
elif data_file.endswith('.csv'):
df = read_csv(data_file, sep=',', encoding='gbk', header=8)
csv_reader = reader(open(data_file))
i = 0
cycle = 0.001
for row in csv_reader:
i += 1
if i == 3:
cycle = float(row[0].split(':')[1].split('ms')[0]) / 1000
break
ws["H11"] = cycle
# 过滤尾部无效数据
col_names = list(df.columns)
df_1 = df[col_names[vel-1]].multiply(rpm)
df_2 = df[col_names[trq-1]].multiply(scale)
df = concat([df_1, df_2], axis=1)
_step = 5 if data_file.endswith('.csv') else 50
_end_point = 30 if data_file.endswith('.csv') else 200
_adjust = 0 if data_file.endswith('.csv') else 150
_row_e = df.index[-1]
_row_s = _row_e - 200
while _row_e > 200:
speed_avg = df.iloc[_row_s:_row_e, vel-1].abs().mean()
if speed_avg > 2:
_row_e -= 50
_row_s -= 50
continue
else:
break
else:
w2t("数据有误，需要检查，无法找到第一个有效起始点...", 0, 1)
_row_s = _row_e - _end_point
speed_avg = df.iloc[_row_s:_row_e, 0].abs().mean()
if speed_avg < 2:
# 过滤尾部为零无效数据
_row_s, _row_e = find_point('lt', df, _row_s, _row_e, w2t, 1, threshold=2, step=_step, end_point=_end_point)
# 找到第一个起始点 row_end，继续找到有数据的部分，后面有一段有效数据区
row_end = _row_e - _adjust
_row_e -= _end_point
_row_s -= _end_point
_row_s, _row_e = find_point('gt', df, _row_s, _row_e, w2t, 3, threshold=2, step=_step, end_point=_end_point)
# 速度已经快要降为零了，继续寻找下一个速度上升点
_row_e -= _end_point
_row_s -= _end_point
_row_s, _row_e = find_point('lt', df, _row_s, _row_e, w2t, 3, threshold=2, step=_step, end_point=_end_point)
elif speed_avg > 2:
# 过滤尾部非零无效数据
_row_s, _row_e = find_point('gt', df, _row_s, _row_e, w2t, 2, threshold=2, step=_step, end_point=_end_point)
# 找到第一个起始点 row_end，继续找到有数据的部分，后面有一段零数据区
row_end = _row_e - _adjust
_row_e -= _end_point
_row_s -= _end_point
_row_s, _row_e = find_point('lt', df, _row_s, _row_e, w2t, 4, threshold=2, step=_step, end_point=_end_point)
#目前已经有一点的速度值了，继续往前搜寻下一个速度为零的点
_row_e -= _end_point
_row_s -= _end_point
_row_s, _row_e = find_point('gt', df, _row_s, _row_e, w2t, 4, threshold=2, step=_step, end_point=_end_point)
# 找到第一个起始点 row_end，继续找到有数据的部分
row_end = _row_e - 100
_row_e -= 200
_row_s -= 200
while _row_e > 200:
speed_avg = df.iloc[_row_s:_row_e, vel-1].abs().mean()
if speed_avg < 2:
_row_e -= 50
_row_s -= 50
continue
else:
break
else:
w2t("数据有误，需要检查，无法找到第二个有效起始点...", 0, 2)
# 目前已经有一点的速度值了，继续往前搜寻下一个速度为零的点
_row_e -= 200
_row_s -= 200
while _row_e > 200:
speed_avg = df.iloc[_row_s:_row_e, vel-1].abs().mean()
if speed_avg > 2:
_row_e -= 50
_row_s -= 50
continue
else:
break
else:
w2t("数据有误，需要检查，无法找到第三个有效起始点...", 0, 3)
row_start = _row_s + 180
row_start = _row_s + _adjust
data = []
for row in range(row_start, row_end):
data.append(df.iloc[row, vel-1])
data.append(df.iloc[row, trq-1])
data.append(df.iloc[row, 0])
data.append(df.iloc[row, 1])
i = 0
for row in ws.iter_rows(min_row=2, min_col=2, max_row=15000, max_col=3):
for cell in row:
try:
cell.value = data[i]
_ = f"{data[i]:.2f}"
cell.value = float(_)
i += 1
except:
cell.value = None
def p_scenario():
pass
def p_scenario(wb, single, vel, trq, rpm, dur, w2t):
for data_file in single:
cycle = 0.001
rpm = 1 if rpm == 0 else rpm
scale = 1000 if data_file.endswith('.csv') else 1
axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
shtname = f"J{axis}"
ws = wb[shtname]
set_option("display.precision", 2)
if data_file.endswith('.data'):
df = read_csv(data_file, sep='\t')
elif data_file.endswith('.csv'):
df = read_csv(data_file, sep=',', encoding='gbk', header=8)
csv_reader = reader(open(data_file))
i = 0
for row in csv_reader:
i += 1
if i == 3:
cycle = float(row[0].split(':')[1].split('ms')[0]) / 1000
break
ws["H11"] = cycle
col_names = list(df.columns)
df_1 = df[col_names[vel-1]].multiply(rpm)
df_2 = df[col_names[trq-1]].multiply(scale)
df = concat([df_1, df_2], axis=1)
row_start = 300
row_end = row_start + int(dur/cycle)
if row_end > df.index[-1]:
w2t(f"位置超限：{data_file} 共有 {df.index[-1]} 条数据，无法取到第 {row_end} 条数据...", 0, 9)
data = []
for row in range(row_start, row_end):
data.append(df.iloc[row, 0])
data.append(df.iloc[row, 1])
i = 0
for row in ws.iter_rows(min_row=2, min_col=2, max_row=15000, max_col=3):
for cell in row:
try:
_ = f"{data[i]:.2f}"
cell.value = float(_)
i += 1
except:
cell.value = None
# =======================================
def main(path, sub, rcs, vel, trq, trqh, dur, w2t):
def main(path, sub, rcs, vel, trq, trqh, dur, rpm, w2t):
data_files = initialization(path, sub, w2t)
if sub == 'max':
current_max(data_files, rcs, trqh, w2t)
elif sub == 'avg':
current_avg(data_files, rcs, trqh, w2t)
elif sub == 'cycle':
current_cycle(dur, data_files, rcs, vel, trq, trqh, w2t)
current_cycle(dur, data_files, rcs, vel, trq, trqh, rpm, w2t)
else:
pass