gitea
de6d1d47c8
v0.0.4(2024/05/22) 1. 重新标定了get_threshold_step函数，让处理更加准确 2. 新定义了now_doing_msg函数，实时输出处理信息 3. 修改了find_row_start和find_row_start_dp函数，增加的部分相同，处理数据的时候，先判断是否是空值，或者是0，此时可以加快步进 4. 修改了just_open函数，不在做重试
369 lines
15 KiB
Python
369 lines
15 KiB
Python
# coding: utf-8
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import os
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import sys
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import openpyxl
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from win32com.client import DispatchEx
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import time
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from threading import Thread
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import pythoncom
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import pandas
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def just_open(filename):
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pythoncom.CoInitialize()
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xlapp = DispatchEx("Excel.Application")
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xlapp.Visible = False
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xlbook = xlapp.Workbooks.Open(filename)
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xlapp.DisplayAlerts = 0
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xlbook.SaveAs(filename)
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xlbook.Close()
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xlapp.Quit()
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def traversal_files(path):
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if not os.path.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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warn_pause_exit(msg, 1, 11)
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else:
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dirs = []
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files = []
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for item in os.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 get_threshold_step(excel_file, AXIS):
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conditions = sorted(excel_file.split('\\')[-2].split('_'))
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# 只有负载和速度是100%时，才会启用更敏感的step
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flg = 1 if conditions[0][-3:] == '100' and conditions[2][-3:] == '100' else 0
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if flg == 1 and AXIS == 'j2':
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threshold = 50
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step = 20
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else:
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threshold = 50
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step = 100
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return threshold, step
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def find_row_start(excel_file, ws_data, conditions, AV, RR, AXIS):
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ratio = float(conditions[1].removeprefix('speed'))/100
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speed_max = AV * ratio * RR / 6
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row_max = ws_data.max_row
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row_start = row_max - 1000
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threshold, step = get_threshold_step(excel_file, AXIS)
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while row_start > 0:
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speed = ws_data[f"A{row_start}"].value
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if speed is None or int(speed) < 1:
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row_start -= step
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continue
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row_end = row_start - step
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if row_end < 2:
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msg = f"可能是{excel_file.replace('xlsx', 'data')}, 这个文件数据采集有问题，也有可能是程序步长设定问题......" \
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f"建议重新采集，或者先删除该文件夹，重新运行程序，先手动处理"
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warn_pause_exit(msg, 1, 10)
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_a = ws_data[f"A{row_start}"].value
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_b = ws_data[f"A{row_end}"].value
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if abs(_a-speed_max) < threshold and abs(_b-speed_max) < threshold and abs(_a-_b) < threshold:
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row_start -= (step + 200)
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break
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else:
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row_start -= step
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else:
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os.remove(excel_file)
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msg = f"可能是{excel_file.replace('xlsx', 'data')},这个文件数据采集有问题，比如采集的时机不对，请检查......"
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warn_pause_exit(msg, 1, 9)
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return row_max, row_start
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def find_result_sheet_name(conditions, count):
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# 该函数比较简单，功能是获取结果文件准确的sheet页名称
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# 33%臂展_33%速度_正1
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reach = conditions[0].removeprefix('reach')
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speed = conditions[1].removeprefix('speed')
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result_sheet_name = f"{reach}%臂展_{speed}%速度_正{count}"
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return result_sheet_name
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def copy_data_to_result(ws_data, ws_result, row_max, row_start):
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# 结果文件数据清零
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for row in ws_result.iter_rows(min_row=2, min_col=1, max_row=6000 - row_start + 2, max_col=2):
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for cell in row:
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cell.value = None
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# 将合适的数据复制到结果文件
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data = []
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for row in ws_data.iter_rows(min_row=row_start, min_col=1, max_row=row_max, max_col=2):
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for cell in row:
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data.append(cell.value)
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i = 0
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for row in ws_result.iter_rows(min_row=2, min_col=1, max_row=row_max - row_start + 2, max_col=2):
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for cell in row:
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cell.value = data[i]
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i = i + 1
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def copy_data_to_excel_file(wb_data, ws_result, row_max, row_start, excel_file, RC, RR):
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try:
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del wb_data['dp']
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wb_data.create_sheet('dp')
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ws_dp = wb_data['dp']
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except Exception as Err:
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wb_data.create_sheet('dp')
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ws_dp = wb_data['dp']
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data = []
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for row in ws_result.iter_rows(min_row=1, min_col=1, max_row=row_max-row_start+2, max_col=5):
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for cell in row:
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data.append(cell.value)
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i = 0
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for row in ws_dp.iter_rows(min_row=1, min_col=1, max_row=row_max-row_start+2, max_col=5):
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for cell in row:
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cell.value = data[i]
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i = i + 1
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ws_dp.cell(row=5, column=7).value = RC
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ws_dp.cell(row=6, column=7).value = RR
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wb_data.save(excel_file)
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wb_data.close()
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just_open(excel_file) # 为了能读取到公式计算的数值，必须要用 win32com 打开关闭一次
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wb_data = openpyxl.load_workbook(excel_file, data_only=True)
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ws_dp = wb_data['dp']
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return wb_data, ws_dp
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def find_row_start_dp(data_file, ws_dp, row_max, row_start, conditions, AV):
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ratio = float(conditions[1].removeprefix('speed'))/100
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av_max = AV * ratio
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row_max_dp = row_max - row_start + 1 + 1 # title row
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row_start_dp = row_max_dp - 5
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while row_start_dp > 6:
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# 处理异常数据：当从数据文件中拷贝的有效数据超过5000时，会触发下面代码块
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angular = ws_dp.cell(row=row_start_dp, column=4).value
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if angular is None or str(angular) == '0':
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row_start_dp -= 50
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continue
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_a = float(ws_dp.cell(row=row_start_dp, column=4).value)
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_b = float(ws_dp.cell(row=row_start_dp - 1, column=4).value)
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_c = float(ws_dp.cell(row=row_start_dp - 2, column=4).value)
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_d = float(ws_dp.cell(row=row_start_dp - 3, column=4).value)
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_e = float(ws_dp.cell(row=row_start_dp - 4, column=4).value)
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avg = (_a + _b + _c + _d + _e) / 5
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if abs(avg - av_max) < 1:
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row_start_dp = row_start_dp + 10 - 5 # +10 是因为结果文件 C2 的值是 10，-5是做了保守处理，相当于再往前移动 5 个点位
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break
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else:
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row_start_dp -= 5 # 保守一点，每次移动 5 个点位，如果想要加快程序运行，可适当调整更大一些，建议不超过 15
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else:
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msg = "数据有误，未找到平衡的点，请确认！"
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warn_pause_exit(msg, 1, 1)
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return row_start_dp
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def single_file_process(data_file, wb_result, count, AV, RR, RC, AXIS):
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excel_file = data_file.replace('.data', '.xlsx')
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sheet_name = data_file.split('\\')[-1].removesuffix('.data')
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df = pandas.read_csv(data_file, sep='\t')
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df.to_excel(excel_file, sheet_name=sheet_name, index=False)
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conditions = sorted(data_file.split('\\')[-2].split('_')[1:])
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# print(f"conditions = {conditions}")
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result_sheet_name = find_result_sheet_name(conditions, count)
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ws_result = wb_result[result_sheet_name]
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wb_data = openpyxl.load_workbook(excel_file)
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ws_data = wb_data[sheet_name]
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row_max, row_start = find_row_start(excel_file, ws_data, conditions, AV, RR, AXIS)
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copy_data_to_result(ws_data, ws_result, row_max, row_start)
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wb_data, ws_dp = copy_data_to_excel_file(wb_data, ws_result, row_max, row_start, excel_file, RC, RR)
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row_start_dp = find_row_start_dp(data_file, ws_dp, row_max, row_start, conditions, AV)
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ws_result["G2"] = int(row_start_dp)
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wb_data.save(excel_file)
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wb_data.close()
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def now_doing_msg(docs, flag):
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now = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))
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file_type = 'file' if os.path.isfile(docs) else 'dir'
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if flag == 'start' and file_type == 'dir':
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print(f"[{now}] 正在处理目录【{docs}】中的数据......")
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elif flag == 'start' and file_type == 'file':
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print(f"[{now}] 正在处理文件【{docs}】中的数据......")
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elif flag == 'done' and file_type == 'dir':
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print(f"[{now}] 目录【{docs}】数据文件已处理完毕......")
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elif flag == 'done' and file_type == 'file':
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print(f"[{now}] 文件【{docs}】数据文件已处理完毕......")
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def data_process(result_file, raw_data_dirs, AV, RR, RC, AXIS):
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prefix = result_file.split('\\')[-1].split('_')[0]
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wb_result = openpyxl.load_workbook(result_file) # 打开和关闭结果文件夹十分耗时间
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for raw_data_dir in raw_data_dirs:
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if raw_data_dir.split('\\')[-1].split('_')[0] == prefix:
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now_doing_msg(raw_data_dir, 'start')
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_, data_files = traversal_files(raw_data_dir)
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# 数据文件串行处理模式---------------------------------
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# count = 1
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# for data_file in data_files:
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# now_doing_msg(data_file, 'start')
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# single_file_process(data_file, wb_result, count, AV, RR, RC, AXIS)
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# count += 1
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# now_doing_msg(data_file, 'done')
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# ---------------------------------------------------
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# 数据文件并行处理模式---------------------------------
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threads = [Thread(target=single_file_process, args=(data_files[0], wb_result, 1, AV, RR, RC, AXIS)),
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Thread(target=single_file_process, args=(data_files[1], wb_result, 2, AV, RR, RC, AXIS)),
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Thread(target=single_file_process, args=(data_files[2], wb_result, 3, AV, RR, RC, AXIS))]
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[t.start() for t in threads]
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[t.join() for t in threads]
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now_doing_msg(raw_data_dir, 'done')
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# ---------------------------------------------------
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now_doing_msg(result_file, 'done')
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print(f"保存文件需要1-2min，请耐心等待......")
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wb_result.save(result_file)
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wb_result.close()
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def warn_pause_exit(msg, pause_num, exit_num):
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print(msg + '\n')
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for i in range(pause_num):
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_ = input("Press ENTER to continue......\n")
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sys.exit(exit_num)
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def check_files(raw_data_dirs, result_files):
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if len(result_files) != 3:
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msg = "结果文件数目错误，结果文件有且只有三个，请确认！"
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for result_file in result_files:
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print(result_file)
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warn_pause_exit(msg, 1, 3)
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prefix = []
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for result_file in result_files:
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prefix.append(result_file.split('\\')[-1].split('_')[0])
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if not sorted(prefix) == sorted(['load33', 'load66', 'load100']):
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wd = result_files[0].split('\\')
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del wd[-1]
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wd = '\\'.join(wd)
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msg = f"请关闭所有相关数据文件，并检查工作目录【{wd}】下，有且只允许有类似如下三个文件：\n" \
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f"1. load33_自研_制动性能测试.xlsx\n" \
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f"2. load66_自研_制动性能测试.xlsx\n" \
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f"3. load100_自研_制动性能测试.xlsx"
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warn_pause_exit(msg, 1, 8)
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for raw_data_dir in raw_data_dirs:
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components = raw_data_dir.split('\\')[-1].split('_')
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sorted(components)
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if components[0] not in ['load33', 'load66', 'load100'] or \
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components[1] not in ['speed33', 'speed66', 'speed100'] or \
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components[2] not in ['reach33', 'reach66', 'reach100']:
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msg = f"报错信息：数据目录【{raw_data_dir}】命名不合规，请参考如下形式\n" \
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f"命名规则：\n 1. loadAA_speedBB_reachCC\n 2. loadAA_reachBB_speedCC\n" \
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f"规则解释：AA/BB/CC 指的是负载/速度/臂展的比例\n" \
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f"load66_speed100_reach33：66% 负载，100% 速度以及 33% 臂展情况下的测试结果文件夹"
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warn_pause_exit(msg, 1, 7)
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# 直接删掉 excel 文件
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_, raw_data_files = traversal_files(raw_data_dir)
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for raw_data_file in raw_data_files:
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if raw_data_file.endswith(".xlsx"):
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os.remove(raw_data_file)
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_, raw_data_files = traversal_files(raw_data_dir)
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if len(raw_data_files) != 3:
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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"
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warn_pause_exit(msg, 1, 6)
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for raw_data_file in raw_data_files:
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if not raw_data_file.split('\\')[-1].endswith('.data'):
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msg = f"数据文件【{raw_data_file}】后缀错误，每个数据目录下有且只能有三个以 .data 为后缀的数据文件"
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warn_pause_exit(msg, 1, 5)
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print("数据目录合规性检查结束，未发现问题......")
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def delete_excel_files(raw_data_dirs):
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for raw_data_dir in raw_data_dirs:
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_, raw_data_files = traversal_files(raw_data_dir)
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for raw_data_file in raw_data_files:
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if raw_data_file.endswith('.xlsx'):
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os.remove(raw_data_file)
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def initialization():
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time_start = time.time() # 记录开始时间
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try:
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# read init configurations from config file
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wb_conf = openpyxl.load_workbook('./configs.xlsx', read_only=True)
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ws_conf = wb_conf['brake']
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DATA_DIR = ws_conf.cell(row=2, column=2).value
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AV = int(ws_conf.cell(row=3, column=2).value)
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RR = int(ws_conf.cell(row=4, column=2).value)
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RC = float(ws_conf.cell(row=5, column=2).value)
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AXIS = ws_conf.cell(row=6, column=2).value
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wb_conf.close()
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except Exception as Err:
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msg = "无法在当前路径下找到或打开【configs.xlsx】文件，请确认！"
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warn_pause_exit(msg, 1, 2)
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raw_data_dirs, result_files = traversal_files(DATA_DIR)
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delete_excel_files(raw_data_dirs)
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check_files(raw_data_dirs, result_files)
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return raw_data_dirs, result_files, time_start, AV, RR, RC, AXIS
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def execution(args):
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raw_data_dirs, result_files, time_start, AV, RR, RC, AXIS = args
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prefix = []
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for raw_data_dir in raw_data_dirs:
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prefix.append(raw_data_dir.split('\\')[-1].split("_")[0])
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try:
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# threads = []
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for result_file in result_files:
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if result_file.split('\\')[-1].split('_')[0] not in set(prefix):
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continue
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else:
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now_doing_msg(result_file, 'start')
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data_process(result_file, raw_data_dirs, AV, RR, RC, AXIS)
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# threads.append(Thread(target=data_process, args=(result_file, raw_data_dirs, AV, RR, RC, AXIS)))
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# [t.start() for t in threads]
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# [t.join() for t in threads]
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print("#---------------------------------------------------------")
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print("全部处理完毕")
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delete_excel_files(raw_data_dirs)
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except Exception as Err:
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print("程序运行错误，请检查配置文件是否准确设定，以及数据文件组织是否正确！")
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delete_excel_files(raw_data_dirs) # 运行结束之后，删除中间临时文件
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time_end = time.time() # 记录结束时间
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time_total = time_end - time_start # 计算的时间差为程序的执行时间，单位为秒/s
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msg = f"数据处理时间：{time_total//3600:02} h {time_total % 3600/60:05.2f} min"
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warn_pause_exit(msg, 1, 0)
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def main():
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execution(initialization())
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if __name__ == "__main__":
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main()
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