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fix merge while merging from main

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gitea
2024-08-16 15:57:00 +08:00
parent addb123a8a 4925d899b4
commit 8f342832b2
53 changed files with 6134 additions and 1212 deletions
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1
aio/code/data_process/__init__.py
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@ -1 +0,0 @@
__all__ = ['brake', 'current', 'iso', 'wavelogger']

52
aio/code/data_process/brake.py
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@ -1,49 +1,12 @@
# coding: utf-8
from os import scandir
from os.path import isfile, exists
from os.path import isfile
from sys import argv
from openpyxl import load_workbook
from time import time, sleep, strftime, localtime
from threading import Thread
from pandas import read_csv
from commons import clibs
class GetThreadResult(Thread):
def __init__(self, func, args=()):
super(GetThreadResult, self).__init__()
self.func = func
self.args = args
self.result = 0
def run(self):
sleep(1)
self.result = self.func(*self.args)
def get_result(self):
Thread.join(self) # 等待线程执行完毕
try:
return self.result
except Exception as Err:
return None
def traversal_files(path, w2t):
# 功能：以列表的形式分别返回指定路径下的文件和文件夹，不包含子目录
# 参数：路径
# 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, 'red')
else:
dirs = []
files = []
for item in scandir(path):
if item.is_dir():
dirs.append(item.path)
elif item.is_file():
files.append(item.path)
return dirs, files
logger = clibs.log_prod
def check_files(path, raw_data_dirs, result_files, w2t):
@ -83,7 +46,7 @@ def check_files(path, raw_data_dirs, result_files, w2t):
规则解释：AA/BB/CC 指的是臂展/负载/速度的比例，例如reach66_load100_speed33：66%臂展，100%负载以及33%速度情况下的测试结果文件夹"""
w2t(msg, 0, 4, 'red')
_, raw_data_files = traversal_files(raw_data_dir, w2t)
_, raw_data_files = clibs.traversal_files(raw_data_dir, w2t)
if len(raw_data_files) != 3:
msg = f"数据目录 {raw_data_dir} 下数据文件个数错误，每个数据目录下有且只能有三个以 .data 为后缀的数据文件"
w2t(msg, 0, 5, 'red')
@ -109,6 +72,7 @@ def get_configs(configfile, w2t):
return av, rr
def now_doing_msg(docs, flag, w2t):
# 功能：输出正在处理的文件或目录
# 参数：文件或目录，start 或 done 标识
@ -228,7 +192,7 @@ def data_process(result_file, raw_data_dirs, av, rr, vel, trq, estop, w2t):
global stop
stop = 0
t_excel = GetThreadResult(load_workbook, args=(result_file, ))
t_excel = clibs.GetThreadResult(load_workbook, args=(result_file, ))
t_wait = Thread(target=w2t_local, args=('.', 1, w2t))
t_excel.start()
t_wait.start()
@ -242,7 +206,7 @@ def data_process(result_file, raw_data_dirs, av, rr, vel, trq, estop, w2t):
for raw_data_dir in raw_data_dirs:
if raw_data_dir.split('\\')[-1].split('_')[0] == prefix:
now_doing_msg(raw_data_dir, 'start', w2t)
_, data_files = traversal_files(raw_data_dir, w2t)
_, data_files = clibs.traversal_files(raw_data_dir, w2t)
# 数据文件串行处理模式---------------------------------
# count = 1
# for data_file in data_files:
@ -280,7 +244,7 @@ def main(path, vel, trq, estop, w2t):
# 参数：initialization函数的返回值
# 返回值：-
time_start = time()
raw_data_dirs, result_files = traversal_files(path, w2t)
raw_data_dirs, result_files = clibs.traversal_files(path, w2t)
try:
# threads = []

92
aio/code/data_process/current.py
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@ -1,31 +1,13 @@
from openpyxl import load_workbook
from os import scandir
from os.path import exists
from sys import argv
from pandas import read_csv, concat, set_option
from re import match
from threading import Thread
from time import sleep
from csv import reader, writer
from commons import clibs
class GetThreadResult(Thread):
def __init__(self, func, args=()):
super(GetThreadResult, self).__init__()
self.func = func
self.args = args
self.result = 0
def run(self):
sleep(1)
self.result = self.func(*self.args)
def get_result(self):
Thread.join(self) # 等待线程执行完毕
try:
return self.result
except Exception as Err:
return None
logger = clibs.log_prod
def w2t_local(msg, wait, w2t):
@ -38,27 +20,8 @@ def w2t_local(msg, wait, w2t):
break
def traversal_files(path, w2t):
# 功能：以列表的形式分别返回指定路径下的文件和文件夹，不包含子目录
# 参数：路径
# 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, 8, 'red')
else:
dirs = []
files = []
for item in scandir(path):
if item.is_dir():
dirs.append(item.path)
elif item.is_file():
files.append(item.path)
return dirs, files
def initialization(path, sub, w2t):
_, data_files = traversal_files(path, w2t)
_, data_files = clibs.traversal_files(path, w2t)
count = 0
for data_file in data_files:
@ -69,8 +32,8 @@ def initialization(path, sub, w2t):
count += 1
else:
if not (match('j[1-7].*\\.data', filename) or match('j[1-7].*\\.csv', filename)):
print(f"不合规 {data_file}")
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。"
msg = f"不合规 {data_file}\n"
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, 6, 'red')
if not ((sub == 'cycle' and count == 2) or (sub != 'cycle' and count == 1)):
@ -79,7 +42,7 @@ def initialization(path, sub, w2t):
return data_files
def current_max(data_files, rcs, trqh, w2t):
def current_max(data_files, rcs, trq, w2t):
current = {1: [], 2: [], 3: [], 4: [], 5: [], 6: [], 7: []}
for data_file in data_files:
if data_file.endswith('.data'):
@ -93,8 +56,8 @@ def current_max(data_files, rcs, trqh, w2t):
axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
rca = rcs[axis-1]
col = df.columns.values[trqh-1]
c_max = df[col].max()
col = df.columns.values[trq-1]
c_max = df[col].abs().max()
scale = 1 if data_file.endswith('.csv') else 1000
_ = abs(c_max/scale*rca)
@ -118,7 +81,7 @@ def current_max(data_files, rcs, trqh, w2t):
return current
def current_avg(data_files, rcs, trqh, w2t):
def current_avg(data_files, rcs, trq, w2t):
current = {1: [], 2: [], 3: [], 4: [], 5: [], 6: [], 7: []}
for data_file in data_files:
if data_file.endswith('.data'):
@ -132,7 +95,7 @@ def current_avg(data_files, rcs, trqh, w2t):
axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
rca = rcs[axis-1]
col = df.columns.values[trqh - 1]
col = df.columns.values[trq-1]
c_std = df[col].std()
c_avg = df[col].mean()
@ -158,7 +121,7 @@ def current_avg(data_files, rcs, trqh, w2t):
return current
def current_cycle(dur, data_files, rcs, vel, trq, trqh, rpms, w2t):
def current_cycle(dur, data_files, rcs, rrs, vel, trq, trqh, rpms, w2t):
result = None
hold = []
single = []
@ -174,7 +137,7 @@ def current_cycle(dur, data_files, rcs, vel, trq, trqh, rpms, w2t):
w2t(f"正在打开文件 {result}，需要 10s 左右", 1, 0, 'orange')
global stop
stop = 0
t_excel = GetThreadResult(load_workbook, args=(result, ))
t_excel = clibs.GetThreadResult(load_workbook, args=(result, ))
t_wait = Thread(target=w2t_local, args=('.', 1, w2t))
t_excel.start()
t_wait.start()
@ -189,14 +152,14 @@ def current_cycle(dur, data_files, rcs, vel, trq, trqh, rpms, w2t):
for axis, cur_value in avg.items():
try:
shtname = f"J{axis}"
wb[shtname]["J4"].value = float(cur_value)
wb[shtname]["J4"].value = float(cur_value[0])
except:
pass
if dur == 0:
p_single(wb, single, vel, trq, rpms, w2t)
p_single(wb, single, vel, trq, rpms, rrs, w2t)
else:
p_scenario(wb, single, vel, trq, rpms, dur, w2t)
p_scenario(wb, single, vel, trq, rpms, rrs, dur, w2t)
w2t(f"正在保存文件 {result}，需要 10s 左右", 1, 0, 'orange')
stop = 0
@ -239,7 +202,7 @@ def find_point(data_file, pos, flag, df, _row_s, _row_e, w2t, exitcode, threshol
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')
def p_single(wb, single, vel, trq, rpms, w2t):
def p_single(wb, single, vel, trq, rpms, rrs, 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
@ -253,7 +216,7 @@ def p_single(wb, single, vel, trq, rpms, w2t):
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)
rr = rrs[axis-1]
addition = 180 / 3.1415926 * 60 / 360 * rr
elif data_file.endswith('.csv'):
df = read_csv(data_file, sep=',', encoding='gbk', header=8)
@ -270,6 +233,7 @@ def p_single(wb, single, vel, trq, rpms, w2t):
col_names = list(df.columns)
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 = concat([df_1, df_2], axis=1)
_step = 5 if data_file.endswith('.csv') else 50
@ -320,7 +284,7 @@ def p_single(wb, single, vel, trq, rpms, w2t):
cell.value = None
def p_scenario(wb, single, vel, trq, rpms, dur, w2t):
def p_scenario(wb, single, vel, trq, rpms, rrs, dur, w2t):
for data_file in single:
cycle = 0.001
axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
@ -332,7 +296,7 @@ def p_scenario(wb, single, vel, trq, rpms, dur, w2t):
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)
rr = rrs[axis-1]
addition = 180 / 3.1415926 * 60 / 360 * rr
elif data_file.endswith('.csv'):
df = read_csv(data_file, sep=',', encoding='gbk', header=8)
@ -376,6 +340,7 @@ def get_configs(configfile, w2t):
_wb = load_workbook(configfile, read_only=True)
_ws = _wb['Target']
rcs = []
rrs = []
rpms = []
for i in range(2, 9):
try:
@ -388,18 +353,23 @@ def get_configs(configfile, w2t):
except:
rcs.append(0.0)
return rpms, rcs
try:
rrs.append(float(_ws.cell(row=2, column=i).value))
except:
rrs.append(0.0)
return rpms, rcs, rrs
def main(path, sub, dur, vel, trq, trqh, w2t):
data_files = initialization(path, sub, w2t)
rpms, rcs = get_configs(path + '\\configs.xlsx', w2t)
rpms, rcs, rrs = get_configs(path + '\\configs.xlsx', w2t)
if sub == 'max':
current_max(data_files, rcs, trqh, w2t)
current_max(data_files, rcs, trq, w2t)
elif sub == 'avg':
current_avg(data_files, rcs, trqh, w2t)
current_avg(data_files, rcs, trq, w2t)
elif sub == 'cycle':
current_cycle(dur, data_files, rcs, vel, trq, trqh, rpms, w2t)
current_cycle(dur, data_files, rcs, rrs, vel, trq, trqh, rpms, w2t)
else:
pass

25
aio/code/data_process/iso.py
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@ -1,27 +1,10 @@
# _*_ encoding：utf-8 _*_
import pdfplumber
from openpyxl import load_workbook
from os import scandir, remove
from os.path import exists
from os import remove
from sys import argv
from commons import clibs
def traversal_files(path, w2t):
# 功能：以列表的形式分别返回指定路径下的文件和文件夹，不包含子目录
# 参数：路径
# 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, 'red')
else:
dirs = files = []
for item in scandir(path):
if item.is_dir():
dirs.append(item.path)
elif item.is_file():
files.append(item.path)
return dirs, files
logger = clibs.log_prod
def p_iso(file, p_files, ws, tmpfile):
@ -153,7 +136,7 @@ def p_iso_1000(file, p_files, ws, tmpfile):
def main(path, w2t):
dirs, files = traversal_files(path, 1)
dirs, files = clibs.traversal_files(path, 1)
try:
wb = load_workbook(path + "/iso-results.xlsx")

37
aio/code/data_process/wavelogger.py
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@ -1,31 +1,10 @@
import os
import random
from pandas import read_csv
from csv import reader
from sys import argv
from os.path import exists
from os import scandir, remove
from openpyxl import Workbook
from random import randint
from commons import clibs
def traversal_files(path, w2t):
# 功能：以列表的形式分别返回指定路径下的文件和文件夹，不包含子目录
# 参数：路径
# 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, 'red')
else:
dirs = []
files = []
for item in scandir(path):
if item.is_dir():
dirs.append(item.path)
elif item.is_file():
files.append(item.path)
return dirs, files
logger = clibs.log_prod
def find_point(bof, step, pos, data_file, flag, df, row, w2t):
@ -95,7 +74,7 @@ def get_cycle_info(data_file, df, row, step, w2t):
def initialization(path, w2t):
_, data_files = traversal_files(path, w2t)
_, data_files = clibs.traversal_files(path, w2t)
for data_file in data_files:
if not data_file.lower().endswith('.csv'):
@ -126,7 +105,7 @@ def single_file_proc(ws, data_file, df, low, high, cycle, w2t):
_step = 5
_data = {}
row_max = df.index[-1]-100
print(data_file)
# print(data_file)
while _row < row_max:
if count not in _data.keys():
_data[count] = []
@ -149,7 +128,7 @@ def single_file_proc(ws, data_file, df, low, high, cycle, w2t):
ws.cell(row=1, column=i).value = f"第{i-1}次测试"
ws.cell(row=i, column=1).value = f"第{i-1}次精度变化"
print(_data)
# print(_data)
for i in sorted(_data.keys()):
_row = 2
_column = i + 1
@ -162,9 +141,9 @@ def execution(data_files, w2t):
wb = Workbook()
for data_file in data_files:
ws, df, low, high, cycle = preparation(data_file, wb, w2t)
print(f"low = {low}")
print(f"high = {high}")
print(f"cycle = {cycle}")
# print(f"low = {low}")
# print(f"high = {high}")
# print(f"cycle = {cycle}")
single_file_proc(ws, data_file, df, low, high, cycle, w2t)
wd = data_files[0].split('\\')