更新 function.py

function.py

@@ -1,28 +1,3 @@
-import numpy as np
-
-"""
-实验说明:
-- 自行编写实现数据加载与预测病马死亡的对率回归算法。 
-
-注意事项:
-- 在 function.py 中实现对率回归算法。
-- 可以自行导入其他库，需要在 requirements.txt 添加依赖，若未在 requirements.txt 中添加使用到的依赖，则无法自动评测，成绩为零。
-- 自动评测脚本仅会加载 train_logreg、predict_logreg 和 load_data 函数，请勿修改函数名。
-
-测评环境:
-- CPU: Intel Xeon(R) CPU E3-1231 v3 @ 3.40GHz
-- OS: Ubuntu 22.04.4 LTS
-- Python: 3.10.12
-- numpy: 2.1.1
-"""
-
-"""
-请在这里填写学号和姓名，不填写即成绩无效。
-"""
-id = "202210423118"
-name = "刘国庆"
-
-
 def load_data(filepath):
     """
     从文件中加载数据，若不自行正确实现，则无法通过评测，不记录成绩。
@@ -34,19 +9,19 @@ def load_data(filepath):
     - np.array: 特征数据。
     - np.array: 标签数据。
     """
+    for delimiter in [',', ' ', '\t']:  # 尝试不同的分隔符：逗号、空格、制表符
         try:
-        # Load data with genfromtxt, filling missing values with NaN
+            # Load data, filling missing values with NaN
-        data = np.genfromtxt(filepath, delimiter=',', missing_values='?', filling_values=np.nan)
+            data = np.genfromtxt(filepath, delimiter=delimiter, missing_values='?', filling_values=np.nan)
             
             # Check if the data has been loaded correctly with at least two dimensions
-        if data.ndim < 2:
+            if data.ndim < 2 or data.size == 0:
-            print(f"Error: File '{filepath}' may be empty or improperly formatted.")
+                continue  # 尝试下一个分隔符
-            return None, None
 
             # Remove rows with NaN values
             data = data[~np.isnan(data).any(axis=1)]
             
-        # Ensure there's still data left after removing rows with NaN
+            # Ensure there's still data left after removing NaN
             if data.size == 0:
                 print(f"Error: No valid data after removing NaN rows in file '{filepath}'.")
                 return None, None
@@ -57,10 +32,13 @@ def load_data(filepath):
             
             return X, y
         except Exception as e:
-        print(f"Error loading data: {e}")
+            print(f"Error loading data with delimiter '{delimiter}': {e}")
+
+    print(f"Error: File '{filepath}' may be empty or improperly formatted.")
     return None, None
 
 
+
 def sigmoid(z):
     """
     Sigmoid activation function.