added adamw + minus one scaling flags

run.py

@@ -240,8 +240,10 @@ def train(data_parameters, training_parameters, network_parameters, misc_paramet
         return validation_loss
 
 
-    optimizer = torch.optim.Adam
-    # optimizer = torch.optim.AdamW
+    if training_parameters['adam_w_flag'] == True:
+        optimizer = torch.optim.AdamW
+    else:
+        optimizer = torch.optim.Adam
 
     loss_function = torch.nn.MSELoss()
     # loss_function=torch.nn.L1Loss()
@@ -334,6 +336,7 @@ def evaluate_mapping(mapping_evaluation_parameters):
     mean_subtraction_flag = mapping_evaluation_parameters['mean_subtraction_flag']
     scale_volumes_flag = mapping_evaluation_parameters['scale_volumes_flag']
     normalize_flag = mapping_evaluation_parameters['normalize_flag']
+    minus_one_scaling_flag = mapping_evaluation_parameters['minus_one_scaling_flag']
     negative_flag = mapping_evaluation_parameters['negative_flag']
     outlier_flag = mapping_evaluation_parameters['outlier_flag']
     shrinkage_flag = mapping_evaluation_parameters['shrinkage_flag']
@@ -354,6 +357,7 @@ def evaluate_mapping(mapping_evaluation_parameters):
                                  mean_subtraction_flag,
                                  scale_volumes_flag,
                                  normalize_flag,
+                                 minus_one_scaling_flag,
                                  negative_flag, 
                                  outlier_flag,
                                  shrinkage_flag,