no changes

main.py

@@ -5,7 +5,7 @@ from confusion_matrix import plot_confusion_matrix
 
 
 """
 """
 (c,b,e,o) will be read from the command line or a script
 (c,b,e,o) will be read from the command line or a script
-(c,b,e,o) corresponds to the combinations of the specific hyperparameters 
+(c,b,e,o) corresponds to the combinations of the specific hyperparameters
 to build the model
 to build the model
 c belongs to {0,1,2,3} and represents the layer architecture
 c belongs to {0,1,2,3} and represents the layer architecture
 b belongs to {0,1} and represents the batch size
 b belongs to {0,1} and represents the batch size
@@ -33,7 +33,7 @@ for params in combinations:
     if avg_auc > max_avg_auc:
     if avg_auc > max_avg_auc:
         max_avg_auc = avg_auc
         max_avg_auc = avg_auc
         max_params = params
         max_params = params
-        
+
 #%%
 #%%
 print("Best params:",max_params)
 print("Best params:",max_params)
 # once we have chosen the optimal parameters we can do the normal kfold
 # once we have chosen the optimal parameters we can do the normal kfold
@@ -43,15 +43,15 @@ acc, auc, cm, pr = cnn.run_kfold(input_, output_, max_params)
 
 
 #%%
 #%%
 labels = [
 labels = [
-    '[~R & ~E]', 
-    '[~R &  E]', 
-    '[ R & ~E]', 
+    '[~R & ~E]',
+    '[~R &  E]',
+    '[ R & ~E]',
     '[ R &  E]'
     '[ R &  E]'
     ]
     ]
 #this function saves the matrix image automatically
 #this function saves the matrix image automatically
-plot_confusion_matrix(cm, labels) 
+plot_confusion_matrix(cm, labels)
 
 
 f = open("out/acc_auc.txt", 'w+')
 f = open("out/acc_auc.txt", 'w+')
 f.write("Average accuracy: " + str(acc)+"\n")
 f.write("Average accuracy: " + str(acc)+"\n")
 f.write("Average area under the curve: " + str(auc))
 f.write("Average area under the curve: " + str(auc))
-f.close()
+f.close()
\ No newline at end of file