update all (#530)

rdagent/components/coder/data_science/feature/eval_tests/feature_test.txt

@@ -8,6 +8,7 @@ Please make sure the stdout is rich enough to support informative feedback
 """
 
 import pickle
+from copy import deepcopy
 
 import numpy as np
 import pandas as pd
@@ -19,17 +20,44 @@ print(f"X.shape: {X.shape}")
 print(f"y.shape: {y.shape}" if not isinstance(y, list) else f"y(list)'s length: {len(y)}")
 print(f"X_test.shape: {X_test.shape}")
 print(f"test_ids length: {len(test_ids)}")
+X_loaded = deepcopy(X)
+y_loaded = deepcopy(y)
+X_test_loaded = deepcopy(X_test)
 X, y, X_test = feat_eng(X, y, X_test)
 
 
 def get_length(data):
     return len(data) if isinstance(data, list) else data.shape[0]
 
-assert get_length(X_test) == get_length(test_ids), (
-    f"Mismatch in length of test images and test IDs: X_test ({get_length(X_test)}) and test_ids ({get_length(test_ids)})"
-)
-assert get_length(X) == get_length(y), (
-    f"Mismatch in length of training images and labels: X ({get_length(X)}) and y ({get_length(y)})"
-)
 
-print("Feature Engineering test passed successfully. Length of test images matches length of test IDs.")
+def get_width(data):
+    return 1 if isinstance(data, list) else data.shape[1:]
+
+
+def get_column_list(data):
+    return data.columns.tolist() if isinstance(data, pd.DataFrame) else None
+
+
+assert get_length(X_test) == get_length(
+    test_ids
+), f"Mismatch in length of test images and test IDs: X_test ({get_length(X_test)}) and test_ids ({get_length(test_ids)})"
+assert get_length(X) == get_length(
+    y
+), f"Mismatch in length of training images and labels: X ({get_length(X)}) and y ({get_length(y)})"
+
+assert get_length(X) != 0, f"Training data is empty."
+assert get_length(y) != 0, f"Training labels are empty."
+assert get_length(X_test) != 0, f"Test data is empty."
+
+assert get_width(X) == get_width(
+    X_test
+), "Mismatch in width of training and test data. Width means the number of features."
+
+if isinstance(X, pd.DataFrame) and isinstance(X_test, pd.DataFrame):
+    assert get_column_list(X) == get_column_list(X_test), "Mismatch in column names of training and test data."
+
+assert sorted(X.dtypes.unique().tolist()) == sorted(
+    X_loaded.dtypes.unique().tolist()
+), f"feature engineering has produced new data types which is not allowed, data loader data types are {X_loaded.dtypes.unique().tolist()} and feature engineering data types are {X.dtypes.unique().tolist()}"
+
+print("Feature Engineering test passed successfully. All checks including length, width, and data types have been validated.")