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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
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
def find_point(bof, step, pos, data_file, flag, df, row, w2t):
# bof: backward or forward
# pos: used for debug
# flag: greater than or lower than
if flag == 'gt':
while 0 < row < df.index[-1]-100:
_value = df.iloc[row, 2]
if _value > 2:
if bof == 'backward':
row -= step
elif bof == 'forward':
row += step
continue
else:
if bof == 'backward':
row_target = row - step
elif bof == 'forward':
row_target = row + step
break
else:
if bof == 'backward':
w2t(f"[{pos}] 在 {data_file} 中,无法正确识别数据,需要确认...", 0, 2, 'red')
elif bof == 'forward':
row_target = row + 100
elif flag == 'lt':
while 0 < row < df.index[-1]-100:
_value = df.iloc[row, 2]
if _value < 2:
if bof == 'backward':
row -= step
elif bof == 'forward':
row += step
continue
else:
if bof == 'backward':
row_target = row - step
elif bof == 'forward':
row_target = row + step
break
else:
if bof == 'backward':
w2t(f"[{pos}] 在 {data_file} 中,无法正确识别数据,需要确认...", 0, 3, 'red')
elif bof == 'forward':
row_target = row + 100
return row_target
def get_cycle_info(data_file, df, row, step, w2t):
# end -> middle: low
# middle -> start: high
# 1. 从最后读取数据无论是大于1还是小于1都舍弃找到相反的值的起始点
# 2. 从起始点,继续往前寻找,找到与之数值相反的中间点
# 3. 从中间点,继续往前寻找,找到与之数值相反的结束点,至此,得到了高低数值的时间区间以及一轮的周期时间
if df.iloc[row, 2] < 2:
row = find_point('backward', step, 'a1', data_file, 'lt', df, row, w2t)
_row = find_point('backward', step, 'a2', data_file, 'gt', df, row, w2t)
_row = find_point('backward', step, 'a3', data_file, 'lt', df, _row, w2t)
row_end = find_point('backward', step, 'a4', data_file, 'gt', df, _row, w2t)
row_middle = find_point('backward', step, 'a5', data_file, 'lt', df, row_end, w2t)
row_start = find_point('backward', step, 'a6', data_file, 'gt', df, row_middle, w2t)
return row_end-row_middle, row_middle-row_start, row_end-row_start
def initialization(path, w2t):
_, data_files = traversal_files(path, w2t)
for data_file in data_files:
if not data_file.lower().endswith('.csv'):
w2t(f"{data_file} 文件后缀错误,只允许 .csv 文件,需要确认!", 0, 1, 'red')
return data_files
def preparation(data_file, wb, w2t):
shtname = data_file.split('\\')[-1].split('.')[0]
ws = wb.create_sheet(shtname)
csv_reader = reader(open(data_file))
i = 0
begin = 70
for row in csv_reader:
i += 1
if i == 1:
begin = int(row[1])
break
df = read_csv(data_file, sep=',', encoding='gbk', skip_blank_lines=False, header=begin - 1, on_bad_lines='warn')
low, high, cycle = get_cycle_info(data_file, df, df.index[-1]-110, 5, w2t)
return ws, df, low, high, cycle
def single_file_proc(ws, data_file, df, low, high, cycle, w2t):
_row = _row_lt = _row_gt = count = 1
_step = 5
_data = {}
row_max = df.index[-1]-100
print(data_file)
while _row < row_max:
if count not in _data.keys():
_data[count] = []
_value = df.iloc[_row, 2]
if _value < 2:
_row_lt = find_point('forward', _step, 'c'+str(_row), data_file, 'lt', df, _row, w2t)
_start = int(_row_gt + (_row_lt - _row_gt - 50) / 2)
_end = _start + 50
value = df.iloc[_start:_end, 2].mean() + df.iloc[_start:_end, 2].std()
_data[count].append(value)
else:
_row_gt = find_point('forward', _step, 'c'+str(_row), data_file, 'gt', df, _row, w2t)
if _row_gt - _row_lt > cycle * 2:
count += 1
_row = max(_row_gt, _row_lt)
for i in range(2, 10):
ws.cell(row=1, column=i).value = f"{i-1}次测试"
ws.cell(row=i, column=1).value = f"{i-1}次精度变化"
print(_data)
for i in sorted(_data.keys()):
_row = 2
_column = i + 1
for value in _data[i]:
ws.cell(row=_row, column=_column).value = float(value)
_row += 1
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}")
single_file_proc(ws, data_file, df, low, high, cycle, w2t)
wd = data_files[0].split('\\')
del wd[-1]
wd = '\\'.join(wd)
filename = wd + '\\result.xlsx'
wb.save(filename)
wb.close()
w2t('----------------------------------------')
w2t('所有文件均已处理完毕')
def main(path, w2t):
data_files = initialization(path, w2t)
execution(data_files, w2t)
if __name__ == '__main__':
main(path=argv[1], w2t=argv[2])