[modify]

v0.0.5(2024/05/23)
1. 完善了函数注释
2. 调整了阈值和步长
3. 删除了just_open函数，以及对应的win32com库（Thank GOD!终于可以不用这个库了）
4. 重写了获取开始点位的代码，直接使用speed来判断，而不用角度，所以find_row_start_dp以及copy_data_to_excel_file函数也被一并删除

rokae/brake/brake.py

@@ -2,25 +2,15 @@
 import os
 import sys
 import openpyxl
-from win32com.client import DispatchEx
 import time
 from threading import Thread
-import pythoncom
 import pandas
 
 
-def just_open(filename):
-    pythoncom.CoInitialize()
-    xlapp = DispatchEx("Excel.Application")
-    xlapp.Visible = False
-    xlbook = xlapp.Workbooks.Open(filename)
-    xlapp.DisplayAlerts = 0
-    xlbook.SaveAs(filename)
-    xlbook.Close()
-    xlapp.Quit()
-
-
 def traversal_files(path):
+    # 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 os.path.exists(path):
         msg = f'数据文件夹{path}不存在，请确认后重试......'
         warn_pause_exit(msg, 1, 11)
@@ -37,55 +27,57 @@ def traversal_files(path):
 
 
 def get_threshold_step(excel_file, AXIS):
+    # 功能：负载和速度100%，且是j2的时候，做特殊处理
+    # 参数：新生成的excel，轴号
+    # 返回值：速度差阈值，处理步长
     conditions = sorted(excel_file.split('\\')[-2].split('_'))
     # 只有负载和速度是100%时，才会启用更敏感的step
     flg = 1 if conditions[0][-3:] == '100' and conditions[2][-3:] == '100' else 0
     if flg == 1 and AXIS == 'j2':
-        threshold = 50
+        threshold = 30
-        step = 20
+        step = 5
     else:
-        threshold = 50
+        threshold = 10
-        step = 100
+        step = 5
 
     return threshold, step
 
 
 def find_row_start(excel_file, ws_data, conditions, AV, RR, AXIS):
+    # 功能：查找数据文件中有效数据的行号，也即最后一个速度下降的点位
+    # 参数：如上
+    # 返回值：速度下降点位，最后的数据点位
     ratio = float(conditions[1].removeprefix('speed'))/100
     speed_max = AV * ratio * RR / 6
-
+    row_max = row_start = ws_data.max_row
-    row_max = ws_data.max_row
-    row_start = row_max - 1000
 
     threshold, step = get_threshold_step(excel_file, AXIS)
-    while row_start > 0:
+    while row_start > step+1:
         speed = ws_data[f"A{row_start}"].value
         if speed is None or int(speed) < 1:
-            row_start -= step
+            row_start -= 50
             continue
-
+        _ = []
-        row_end = row_start - step
+        for i in range(row_start, row_start-step+1, -1):
-        if row_end < 2:
+            _.append(ws_data[f"A{i}"].value)
-            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......" \
+        speed_avg = abs(sum(_))/len(_)
-                  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"
+        if abs(speed_avg-speed_max) < threshold:
-            warn_pause_exit(msg, 1, 10)
+            row_start = row_start - 10
-        _a = ws_data[f"A{row_start}"].value
-        _b = ws_data[f"A{row_end}"].value
-        if abs(_a-speed_max) < threshold and abs(_b-speed_max) < threshold and abs(_a-_b) < threshold:
-            row_start -= (step + 200)
             break
         else:
             row_start -= step
     else:
         os.remove(excel_file)
-        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......"
+        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，也有可能是程序步长设定问题，请检查......"
         warn_pause_exit(msg, 1, 9)
 
     return row_max, row_start
 
 
 def find_result_sheet_name(conditions, count):
-    # 该函数比较简单，功能是获取结果文件准确的sheet页名称
+    # 功能：获取结果文件准确的sheet页名称
+    # 参数：臂展和速度的列表
+    # 返回值：结果文件对应的sheet name
     # 33%臂展_33%速度_正1
     reach = conditions[0].removeprefix('reach')
     speed = conditions[1].removeprefix('speed')
@@ -95,12 +87,17 @@ def find_result_sheet_name(conditions, count):
 
 
 def copy_data_to_result(ws_data, ws_result, row_max, row_start):
+    # 功能：将数据文件中有效数据拷贝至结果文件对应的 sheet
+    # 参数：如上
+    # 返回值：-
     # 结果文件数据清零
-    for row in ws_result.iter_rows(min_row=2, min_col=1, max_row=6000 - row_start + 2, max_col=2):
+    for row in ws_result.iter_rows(min_row=2, min_col=1, max_row=2000, max_col=2):
         for cell in row:
             cell.value = None
 
     # 将合适的数据复制到结果文件
+    row_max = row_start + 399 if row_max-row_start > 400 else row_max
+
     data = []
     for row in ws_data.iter_rows(min_row=row_start, min_col=1, max_row=row_max, max_col=2):
         for cell in row:
@@ -112,74 +109,16 @@ def copy_data_to_result(ws_data, ws_result, row_max, row_start):
             i = i + 1
 
 
-def copy_data_to_excel_file(wb_data, ws_result, row_max, row_start, excel_file, RC, RR):
-    try:
-        del wb_data['dp']
-        wb_data.create_sheet('dp')
-        ws_dp = wb_data['dp']
-    except Exception as Err:
-        wb_data.create_sheet('dp')
-        ws_dp = wb_data['dp']
-
-    data = []
-    for row in ws_result.iter_rows(min_row=1, min_col=1, max_row=row_max-row_start+2, max_col=5):
-        for cell in row:
-            data.append(cell.value)
-    i = 0
-    for row in ws_dp.iter_rows(min_row=1, min_col=1, max_row=row_max-row_start+2, max_col=5):
-        for cell in row:
-            cell.value = data[i]
-            i = i + 1
-
-    ws_dp.cell(row=5, column=7).value = RC
-    ws_dp.cell(row=6, column=7).value = RR
-
-    wb_data.save(excel_file)
-    wb_data.close()
-    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
-    wb_data = openpyxl.load_workbook(excel_file, data_only=True)
-    ws_dp = wb_data['dp']
-
-    return wb_data, ws_dp
-
-
-def find_row_start_dp(data_file, ws_dp, row_max, row_start, conditions, AV):
-    ratio = float(conditions[1].removeprefix('speed'))/100
-    av_max = AV * ratio
-    row_max_dp = row_max - row_start + 1 + 1  # title row
-    row_start_dp = row_max_dp - 5
-    while row_start_dp > 6:
-        # 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
-        angular = ws_dp.cell(row=row_start_dp, column=4).value
-        if angular is None or str(angular) == '0':
-            row_start_dp -= 50
-            continue
-        _a = float(ws_dp.cell(row=row_start_dp, column=4).value)
-        _b = float(ws_dp.cell(row=row_start_dp - 1, column=4).value)
-        _c = float(ws_dp.cell(row=row_start_dp - 2, column=4).value)
-        _d = float(ws_dp.cell(row=row_start_dp - 3, column=4).value)
-        _e = float(ws_dp.cell(row=row_start_dp - 4, column=4).value)
-        avg = (_a + _b + _c + _d + _e) / 5
-        if abs(avg - av_max) < 1:
-            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
-            break
-        else:
-            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
-    else:
-        msg = "数据有误，未找到平衡的点，请确认！"
-        warn_pause_exit(msg, 1, 1)
-
-    return row_start_dp
-
-
 def single_file_process(data_file, wb_result, count, AV, RR, RC, AXIS):
+    # 功能：完成单个数据文件的处理
+    # 参数：如上
+    # 返回值：-
     excel_file = data_file.replace('.data', '.xlsx')
     sheet_name = data_file.split('\\')[-1].removesuffix('.data')
     df = pandas.read_csv(data_file, sep='\t')
     df.to_excel(excel_file, sheet_name=sheet_name, index=False)
 
     conditions = sorted(data_file.split('\\')[-2].split('_')[1:])
-    # print(f"conditions = {conditions}")
     result_sheet_name = find_result_sheet_name(conditions, count)
     ws_result = wb_result[result_sheet_name]
 
@@ -188,16 +127,17 @@ def single_file_process(data_file, wb_result, count, AV, RR, RC, AXIS):
     row_max, row_start = find_row_start(excel_file, ws_data, conditions, AV, RR, AXIS)
 
     copy_data_to_result(ws_data, ws_result, row_max, row_start)
-    wb_data, ws_dp = copy_data_to_excel_file(wb_data, ws_result, row_max, row_start, excel_file, RC, RR)
+    ws_result["C2"] = int(2)
-    row_start_dp = find_row_start_dp(data_file, ws_dp, row_max, row_start, conditions, AV)
+    ws_result["G2"] = int(10+4)
-
-    ws_result["G2"] = int(row_start_dp)
 
     wb_data.save(excel_file)
     wb_data.close()
 
 
 def now_doing_msg(docs, flag):
+    # 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
+    # 返回值：-
     now = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))
     file_type = 'file' if os.path.isfile(docs) else 'dir'
     if flag == 'start' and file_type == 'dir':
@@ -211,6 +151,9 @@ def now_doing_msg(docs, flag):
 
 
 def data_process(result_file, raw_data_dirs, AV, RR, RC, AXIS):
+    # 功能：完成一个结果文件的数据处理
+    # 参数：结果文件，数据目录，以及预读取的参数
+    # 返回值：-
     prefix = result_file.split('\\')[-1].split('_')[0]
     wb_result = openpyxl.load_workbook(result_file)  # 打开和关闭结果文件夹十分耗时间
     for raw_data_dir in raw_data_dirs:
@@ -220,12 +163,11 @@ def data_process(result_file, raw_data_dirs, AV, RR, RC, AXIS):
             # 数据文件串行处理模式---------------------------------
             # count = 1
             # for data_file in data_files:
-                # now_doing_msg(data_file, 'start')
+            #     now_doing_msg(data_file, 'start')
-                # single_file_process(data_file, wb_result, count, AV, RR, RC, AXIS)
+            #     single_file_process(data_file, wb_result, count, AV, RR, RC, AXIS)
-                # count += 1
+            #     count += 1
-                # now_doing_msg(data_file, 'done')
+            #     now_doing_msg(data_file, 'done')
             # ---------------------------------------------------
-
             # 数据文件并行处理模式---------------------------------
             threads = [Thread(target=single_file_process, args=(data_files[0], wb_result, 1, AV, RR, RC, AXIS)),
                        Thread(target=single_file_process, args=(data_files[1], wb_result, 2, AV, RR, RC, AXIS)),
@@ -242,6 +184,9 @@ def data_process(result_file, raw_data_dirs, AV, RR, RC, AXIS):
 
 
 def warn_pause_exit(msg, pause_num, exit_num):
+    # 功能：打印告警信息，并推出程序
+    # 参数：告警信息，暂停的次数，退出的值
+    # 返回值：-
     print(msg + '\n')
     for i in range(pause_num):
         _ = input("Press ENTER to continue......\n")
@@ -249,6 +194,9 @@ def warn_pause_exit(msg, pause_num, exit_num):
 
 
 def check_files(raw_data_dirs, result_files):
+    # 功能：检查数据文件以及结果文件的合规性
+    # 参数：数据文件夹，结果文件
+    # 返回值：-
     if len(result_files) != 3:
         msg = "结果文件数目错误，结果文件有且只有三个，请确认！"
         for result_file in result_files:
@@ -299,6 +247,9 @@ def check_files(raw_data_dirs, result_files):
 
 
 def delete_excel_files(raw_data_dirs):
+    # 功能：删除数据文件夹里的 .xlsx 文件
+    # 参数：数据文件夹
+    # 返回值：-
     for raw_data_dir in raw_data_dirs:
         _, raw_data_files = traversal_files(raw_data_dir)
         for raw_data_file in raw_data_files:
@@ -307,6 +258,9 @@ def delete_excel_files(raw_data_dirs):
 
 
 def initialization():
+    # 功能：初始化，记录开始时间，读取预定义参数
+    # 参数：-
+    # 返回值：结果文件，数据文件夹，以及预定义参数
     time_start = time.time()  # 记录开始时间
     try:
         # read init configurations from config file
@@ -331,6 +285,9 @@ def initialization():
 
 
 def execution(args):
+    # 功能：执行处理所有数据文件
+    # 参数：initialization函数的返回值
+    # 返回值：-
     raw_data_dirs, result_files, time_start, AV, RR, RC, AXIS = args
     prefix = []
     for raw_data_dir in raw_data_dirs:

rokae/brake/file_version_info.txt

@@ -6,8 +6,8 @@ VSVersionInfo(
   ffi=FixedFileInfo(
     # filevers and prodvers should be always a tuple with four items: (1, 2, 3, 4)
     # Set not needed items to zero 0.
-    filevers=(0, 0, 4, 0),
+    filevers=(0, 0, 5, 0),
-    prodvers=(0, 0, 4, 0),
+    prodvers=(0, 0, 5, 0),
     # Contains a bitmask that specifies the valid bits 'flags'r
     mask=0x3f,
     # Contains a bitmask that specifies the Boolean attributes of the file.
@@ -31,12 +31,12 @@ VSVersionInfo(
         '040904b0',
         [StringStruct('CompanyName', 'Rokae - https://www.rokae.com/'),
         StringStruct('FileDescription', 'All in one automatic operating tool'),
-        StringStruct('FileVersion', '0.0.4 (2024-05-20)'),
+        StringStruct('FileVersion', '0.0.5 (2024-05-20)'),
         StringStruct('InternalName', 'AIO.exe'),
         StringStruct('LegalCopyright', '© 2024-2024 Manford Fan'),
         StringStruct('OriginalFilename', 'AIO.exe'),
         StringStruct('ProductName', 'AIO'),
-        StringStruct('ProductVersion', '0.0.4 (2024-05-20)')])
+        StringStruct('ProductVersion', '0.0.5 (2024-05-20)')])
       ]), 
     VarFileInfo([VarStruct('Translation', [1033, 1200])])
   ]