re-organize file storage structure, and add API related files, just framework
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186
aio/code/data_process/wavelogger.py
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186
aio/code/data_process/wavelogger.py
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import os
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import random
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from pandas import read_csv
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from csv import reader
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from sys import argv
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from os.path import exists
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from os import scandir, remove
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from openpyxl import Workbook
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from random import randint
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def traversal_files(path, w2t):
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# 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
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# 参数：路径
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# 返回值：路径下的文件夹列表 路径下的文件列表
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if not exists(path):
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msg = f'数据文件夹{path}不存在，请确认后重试......'
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w2t(msg, 0, 1, 'red')
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else:
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dirs = []
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files = []
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for item in scandir(path):
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if item.is_dir():
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dirs.append(item.path)
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elif item.is_file():
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files.append(item.path)
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return dirs, files
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def find_point(bof, step, pos, data_file, flag, df, row, w2t):
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# bof: backward or forward
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# pos: used for debug
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# flag: greater than or lower than
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if flag == 'gt':
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while 0 < row < df.index[-1]-100:
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_value = df.iloc[row, 2]
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if _value > 2:
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if bof == 'backward':
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row -= step
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elif bof == 'forward':
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row += step
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continue
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else:
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if bof == 'backward':
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row_target = row - step
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elif bof == 'forward':
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row_target = row + step
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break
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else:
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if bof == 'backward':
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w2t(f"[{pos}] 在 {data_file} 中，无法正确识别数据，需要确认...", 0, 2, 'red')
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elif bof == 'forward':
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row_target = row + 100
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elif flag == 'lt':
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while 0 < row < df.index[-1]-100:
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_value = df.iloc[row, 2]
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if _value < 2:
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if bof == 'backward':
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row -= step
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elif bof == 'forward':
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row += step
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continue
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else:
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if bof == 'backward':
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row_target = row - step
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elif bof == 'forward':
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row_target = row + step
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break
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else:
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if bof == 'backward':
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w2t(f"[{pos}] 在 {data_file} 中，无法正确识别数据，需要确认...", 0, 3, 'red')
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elif bof == 'forward':
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row_target = row + 100
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return row_target
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def get_cycle_info(data_file, df, row, step, w2t):
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# end -> middle: low
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# middle -> start: high
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# 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
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# 2. 从起始点，继续往前寻找，找到与之数值相反的中间点
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# 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
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if df.iloc[row, 2] < 2:
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row = find_point('backward', step, 'a1', data_file, 'lt', df, row, w2t)
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_row = find_point('backward', step, 'a2', data_file, 'gt', df, row, w2t)
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_row = find_point('backward', step, 'a3', data_file, 'lt', df, _row, w2t)
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row_end = find_point('backward', step, 'a4', data_file, 'gt', df, _row, w2t)
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row_middle = find_point('backward', step, 'a5', data_file, 'lt', df, row_end, w2t)
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row_start = find_point('backward', step, 'a6', data_file, 'gt', df, row_middle, w2t)
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return row_end-row_middle, row_middle-row_start, row_end-row_start
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def initialization(path, w2t):
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_, data_files = traversal_files(path, w2t)
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for data_file in data_files:
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if not data_file.lower().endswith('.csv'):
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w2t(f"{data_file} 文件后缀错误，只允许 .csv 文件，需要确认！", 0, 1, 'red')
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return data_files
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def preparation(data_file, wb, w2t):
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shtname = data_file.split('\\')[-1].split('.')[0]
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ws = wb.create_sheet(shtname)
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csv_reader = reader(open(data_file))
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i = 0
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begin = 70
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for row in csv_reader:
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i += 1
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if i == 1:
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begin = int(row[1])
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break
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df = read_csv(data_file, sep=',', encoding='gbk', skip_blank_lines=False, header=begin - 1, on_bad_lines='warn')
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low, high, cycle = get_cycle_info(data_file, df, df.index[-1]-110, 5, w2t)
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return ws, df, low, high, cycle
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def single_file_proc(ws, data_file, df, low, high, cycle, w2t):
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_row = _row_lt = _row_gt = count = 1
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_step = 5
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_data = {}
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row_max = df.index[-1]-100
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print(data_file)
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while _row < row_max:
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if count not in _data.keys():
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_data[count] = []
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_value = df.iloc[_row, 2]
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if _value < 2:
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_row_lt = find_point('forward', _step, 'c'+str(_row), data_file, 'lt', df, _row, w2t)
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_start = int(_row_gt + (_row_lt - _row_gt - 50) / 2)
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_end = _start + 50
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value = df.iloc[_start:_end, 2].mean() + df.iloc[_start:_end, 2].std()
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_data[count].append(value)
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else:
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_row_gt = find_point('forward', _step, 'c'+str(_row), data_file, 'gt', df, _row, w2t)
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if _row_gt - _row_lt > cycle * 2:
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count += 1
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_row = max(_row_gt, _row_lt)
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for i in range(2, 10):
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ws.cell(row=1, column=i).value = f"第{i-1}次测试"
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ws.cell(row=i, column=1).value = f"第{i-1}次精度变化"
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print(_data)
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for i in sorted(_data.keys()):
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_row = 2
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_column = i + 1
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for value in _data[i]:
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ws.cell(row=_row, column=_column).value = float(value)
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_row += 1
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def execution(data_files, w2t):
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wb = Workbook()
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for data_file in data_files:
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ws, df, low, high, cycle = preparation(data_file, wb, w2t)
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print(f"low = {low}")
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print(f"high = {high}")
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print(f"cycle = {cycle}")
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single_file_proc(ws, data_file, df, low, high, cycle, w2t)
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wd = data_files[0].split('\\')
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del wd[-1]
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wd = '\\'.join(wd)
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filename = wd + '\\result.xlsx'
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wb.save(filename)
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wb.close()
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w2t('----------------------------------------')
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w2t('所有文件均已处理完毕')
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def main(path, w2t):
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data_files = initialization(path, w2t)
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execution(data_files, w2t)
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if __name__ == '__main__':
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main(path=argv[1], w2t=argv[2])
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