comment magics and add pandas

trainingTstage.py

@@ -8,8 +8,8 @@
 # In[ ]:
 
 
-get_ipython().run_line_magic('reload_ext', 'autoreload')
-get_ipython().run_line_magic('autoreload', '2')
+# get_ipython().run_line_magic('reload_ext', 'autoreload')
+# get_ipython().run_line_magic('autoreload', '2')
 
 import os
 PATH = os.getcwd()
@@ -28,6 +28,7 @@ import sys
 import time
 
 import numpy as np
+import pandas as pd
 import matplotlib.pyplot as plt
 from sklearn.metrics import matthews_corrcoef as mcor, accuracy_score as acc, recall_score as recall, precision_score as precision, confusion_matrix
 import torch
@@ -80,7 +81,7 @@ settings = {
             'pretrained': '',
             }
 
-assert settings['split'] in ['valeries', '8020']
+assert settings['split'] in ['valieres', '8020']
 assert settings['pretrained'] in ['Med3D', 'branch-wise', 'T-stage', '']
 
 os.makedirs(f'{EXPERIMENT_DIR}/{EXPERIMENT_NAME}', exist_ok=False)
@@ -540,8 +541,6 @@ np.save(f'{EXPERIMENT_DIR}/{EXPERIMENT_NAME}/filenames_ts.npy', filenames_ts)
 
 # In[ ]:
 
-
-import pandas as pd
 metrics_out = pd.DataFrame((train_metrics, test_metrics), columns=['MCC', 'ACC', 'prec', 'rec'], index = ['train','test'])
 metrics_out.to_csv(f'{EXPERIMENT_DIR}/{EXPERIMENT_NAME}/metrics_out.csv', index=False)