feat: remove fileClass parameter, always use xls/xlsx/csv

Qfunctions/loadData.py

@@ -3,11 +3,12 @@ import unicodedata
 import pandas as pd
 
 STATIC_PATH = './Static'
+DEFAULT_FILE_CLASSES = ('xlsx', 'xls', 'csv')
 
 
-# 从文件夹中读取所有xlsx文件，每个文件对应一个label
+# 从文件夹中读取所有数据文件，支持 xls/xlsx/csv
 # labelNames为label的名字，如果不提供则默认为文件名
-def load_data(folder, labelNames, fileClass='xlsx'):
+def load_data(folder, labelNames):
   # 检查folder参数
   if folder is None:
     raise ValueError("The 'folder' parameter is required.")
@@ -22,27 +23,28 @@ def load_data(folder, labelNames, fileClass='xlsx'):
   if not os.path.isdir(folder):
     raise ValueError(f"The folder '{folder}' does not exist.")
 
+  file_classes = DEFAULT_FILE_CLASSES
+
   # 自动检测数据组织方式
-  is_dir_mode = _detect_data_mode(folder=folder, labelNames=labelNames, fileClass=fileClass)
+  is_dir_mode = _detect_data_mode(folder=folder, labelNames=labelNames, fileClasses=file_classes)
   mode_name = 'multi-folder mode' if is_dir_mode else 'single-file mode'
   print(f"Auto detected data mode: {mode_name}")
 
   if not is_dir_mode:
-    data = load_from_file(folder=folder, labelNames=labelNames, fileClass=fileClass)
+    data = load_from_file(folder=folder, labelNames=labelNames, fileClasses=file_classes)
   else:
-    data = load_from_folder(folder=folder, labelNames=labelNames, fileClass=fileClass)
+    data = load_from_folder(folder=folder, labelNames=labelNames, fileClasses=file_classes)
 
   print(data)
   return data
 
 
-def load_from_folder(folder, labelNames, fileClass):
+def load_from_folder(folder, labelNames, fileClasses):
   all_features = []
-  fileClass = '.' + fileClass
   for labelName in labelNames:
-    subfolder = os.path.join(folder, labelName)
+    subfolder = os.path.join(folder, str(labelName))
     if os.path.exists(subfolder) and os.path.isdir(subfolder):
-      fileNames = [f for f in os.listdir(subfolder) if f.endswith(fileClass)]
+      fileNames = [f for f in os.listdir(subfolder) if _has_supported_extension(f, fileClasses)]
       max_row_length = get_max_row_len(subfolder, fileNames)
       features = []
       for fileName in fileNames:
@@ -55,17 +57,15 @@ def load_from_folder(folder, labelNames, fileClass):
   return pd.concat(all_features, ignore_index=True)
 
 
-def load_from_file(folder, labelNames, fileClass):
+def load_from_file(folder, labelNames, fileClasses):
   # 构建期望的文件名（label + .扩展名），并在目录中进行健壮匹配
   # （去除零宽字符、Unicode 规范化、大小写不敏感）
-  expected_names = [f"{labelName}.{fileClass}" for labelName in labelNames]
-
   actual_file_names = []
   missing = []
-  for expected in expected_names:
+  for labelName in labelNames:
-    match = _find_matching_file(folder, expected)
+    match = _find_matching_file_by_label(folder, labelName, fileClasses)
     if match is None:
-      missing.append(expected)
+      missing.append(f"{labelName}.<{'/'.join(fileClasses)}>")
     else:
       actual_file_names.append(match)
 
@@ -89,7 +89,7 @@ def load_from_file(folder, labelNames, fileClass):
 
 
 def load_xlsx(fileName, labelName, max_row_length=1000, fill_rule=None):
-  df = pd.read_excel(fileName)
+  df = _read_data_file(fileName)
 
   # 提取偶数列
   features = df.iloc[0:, 1::2]
@@ -128,11 +128,31 @@ def fill_to_len(row, length=1000, rule=None):
 def get_max_row_len(folder, filenames):
   max_len = 0
   for filename in filenames:
-    df = pd.read_excel(os.path.join(folder, filename))
+    df = _read_data_file(os.path.join(folder, filename))
     max_len = max(max_len, df.shape[0])
   return max_len
 
 
+def _read_data_file(file_path: str):
+  ext = os.path.splitext(file_path)[1].lower()
+  if ext == '.csv':
+    return pd.read_csv(file_path)
+  if ext in ('.xls', '.xlsx'):
+    return pd.read_excel(file_path)
+  raise ValueError(
+    f"Unsupported file format: {ext}. Only .xls, .xlsx, and .csv are supported. "
+    f"File: {file_path}"
+  )
+
+
+
+
+
+def _has_supported_extension(filename: str, fileClasses) -> bool:
+  ext = os.path.splitext(filename)[1].lower().lstrip('.')
+  return ext in fileClasses
+
+
 # ---------- 内部工具函数：处理包含零宽字符或不同 Unicode 形式的文件名匹配 ----------
 
 def _strip_zero_width(s: str) -> str:
@@ -189,28 +209,34 @@ def _find_matching_file(folder: str, expected_name: str):
   return None
 
 
-def _detect_data_mode(folder: str, labelNames, fileClass: str) -> bool:
+def _find_matching_file_by_label(folder: str, label_name, fileClasses):
+  for ext in fileClasses:
+    expected_name = f"{label_name}.{ext}"
+    match = _find_matching_file(folder, expected_name)
+    if match is not None:
+      return match
+  return None
+
+
+def _detect_data_mode(folder: str, labelNames, fileClasses) -> bool:
   """Auto detect data organization mode.
 
   Returns:
     True: multi-folder mode (folder/label/*.ext)
     False: single-file mode (folder/label.ext)
   """
-  ext = f'.{fileClass}'
-
   # 判断是否满足多文件夹模式：每个 label 对应一个子目录，且至少有一个目标后缀文件
   has_all_label_subfolders = True
   for label in labelNames:
     subfolder = os.path.join(folder, str(label))
-    if not (os.path.isdir(subfolder) and any(f.endswith(ext) for f in os.listdir(subfolder))):
+    if not (os.path.isdir(subfolder) and any(_has_supported_extension(f, fileClasses) for f in os.listdir(subfolder))):
       has_all_label_subfolders = False
       break
 
   # 判断是否满足单文件模式：每个 label 能匹配到对应文件
   has_all_label_files = True
   for label in labelNames:
-    expected_name = f"{label}.{fileClass}"
+    if _find_matching_file_by_label(folder, label, fileClasses) is None:
-    if _find_matching_file(folder, expected_name) is None:
       has_all_label_files = False
       break
 

README.md

@@ -3,7 +3,7 @@
 ## 1. 项目约定
 
 ### 1.1 输入数据格式
-每一类数据建议保存为 `xlsx/xls`。读取时默认取偶数列（索引 1,3,5...）作为特征，奇数列内容可忽略。
+每一类数据支持 `xls/xlsx/csv`。读取时默认取偶数列（索引 1,3,5...）作为特征，奇数列内容可忽略。
 
 示意：
 
@@ -148,10 +148,11 @@ from Qfunctions.saveToXlsx import save_to_xlsx
 projet_name = '20241009MaterialDiv'
 label_names = ['Acrlic', 'Ecoflex', 'PDMS', 'PLA', 'Wood']
 
-# 自动识别数据模式
+# 自动识別数据模式
-# - folder/label.xlsx => 单文件模式
+# 支持 .xls 、.xlsx 、.csv 三种格式（可混合使用）
-# - folder/label/*.xlsx => 多子特征模式
+# - folder/label.xlsx 或 folder/label.xls 或 folder/label.csv => 单文件模式
-data = load_data(projet_name, label_names, fileClass='xlsx')
+# - folder/label/*.(xlsx|xls|csv) => 多子特征模式
+data = load_data(projet_name, label_names)
 
 # 划分训练/测试集
 X_train, X_test, y_train, y_test, encoder = divSet(
@@ -191,19 +192,17 @@ save_to_xlsx(project_name=projet_name, file_name='acc_and_loss', data=epoch_data
 |---|---|---|---|
 | folder | str | 必填 | `Static/` 下的数据目录名 |
 | labelNames | list | 必填 | 类别名称列表，用于读取和排序标签 |
-| fileClass | str | xlsx | 数据文件后缀 |
 
 自动识别规则：
 
-- 若每个 `label` 都对应 `folder/label/*.xlsx`，识别为多子特征模式。
+- 若每个 `label` 都对应 `folder/label/*.(xlsx|xls|csv)`，识别为多子特征模式。
-- 若每个 `label` 都对应 `folder/label.xlsx`，识别为单文件模式。
+- 若每个 `label` 都对应 `folder/label.(xlsx|xls|csv)`，识别为单文件模式。- 超出需法的文件格式（只许 xls/xlsx/csv），汽转时报错。- 若两种都成立（同名文件和同名子目录同时存在），会报错并提示只保留一种目录结构。
-- 若两种都成立（同名文件和同名子目录同时存在），会报错并提示只保留一种目录结构。
 - 若两种都不成立，会报错并提示检查目录结构或 `label_names`。
 
 读取路径规则：
 
-- 单文件模式：`./Static/folder/labelNames[i].xlsx`
+- 单文件模式：`./Static/folder/labelNames[i].(xlsx|xls|csv)`
-- 多子特征模式：`./Static/folder/labelNames[i]/*.xlsx`
+- 多子特征模式：`./Static/folder/labelNames[i]/*.(xlsx|xls|csv)`
 
 ## 5. 常见问题
 
@@ -211,4 +210,4 @@ save_to_xlsx(project_name=projet_name, file_name='acc_and_loss', data=epoch_data
 优先检查：
 
 - `label_names` 与文件/文件夹是否同名
-- 文件后缀是否与 `fileClass` 一致
+- 文件后缀是否为 `.xls`、`.xlsx` 或 `.csv`（其他格式将报错）

main.py

@@ -9,7 +9,7 @@ def main():
   # label_names 是一个列表里面按顺序包含了小写的‘a'到‘z’
   label_names = list(range(10))
   print(label_names)
-  data = load_data(projet_name, label_names, fileClass='xlsx')
+  data = load_data(projet_name, label_names)
   
   model = Qmlp(
     data=data,