nothing

DDPG.py

@@ -43,7 +43,7 @@ if __name__ == '__main__':
         # args.save_network=False
         # args.test_network=False
         # args.save_test_data=False
-        # args.compare_with_pyomo=False
+        # args.compare_with_gurobi=False
 
         if args.train:
             collect_data = True
@@ -97,8 +97,8 @@ if __name__ == '__main__':
         with open(test_data_save_path, 'wb') as tf:
             pickle.dump(record, tf)
 
-    '''compare with pyomo data and results'''
-    if args.compare_with_pyomo:
+    '''compare with gurobi data and results'''
+    if args.compare_with_gurobi:
         month = record['init_info'][0][0]
         day = record['init_info'][0][1]
         initial_soc = record['init_info'][0][3]
@@ -112,7 +112,7 @@ if __name__ == '__main__':
         plot_dir = make_dir(args.cwd, plot_args.feature_change)
         plot_optimization_result(base_result, plot_dir)
         plot_evaluation_information(args.cwd + '/' + 'test_data.pkl', plot_dir)
-    '''compare the different cost get from pyomo and DDPG'''
+    '''compare the different cost get from gurobi and DDPG'''
     ration = sum(eval_data['operation_cost']) / sum(base_result['step_cost'])
     print('operation_cost_sum:', sum(eval_data['operation_cost']))
     print('step_cost_sum:', sum(base_result['step_cost']))

PPO.py

@@ -261,7 +261,7 @@ class Arguments:
         self.save_network = True
         self.test_network = True
         self.save_test_data = True
-        self.compare_with_pyomo = True
+        self.compare_with_gurobi = True
         self.plot_on = True
 
     def init_before_training(self, if_main):
@@ -336,7 +336,7 @@ if __name__ == '__main__':
         # args.save_network=False
         # args.test_network=False
         # args.save_test_data=False
-        # args.compare_with_pyomo=False
+        # args.compare_with_gurobi=False
         if args.train:
             for i_episode in range(num_episode):
                 with torch.no_grad():
@@ -379,8 +379,8 @@ if __name__ == '__main__':
         with open(test_data_save_path, 'wb') as tf:
             pickle.dump(record, tf)
 
-    '''compare with pyomo data and results'''
-    if args.compare_with_pyomo:
+    '''compare with gurobi data and results'''
+    if args.compare_with_gurobi:
         month = record['init_info'][0][0]
         day = record['init_info'][0][1]
         initial_soc = record['init_info'][0][3]
@@ -394,7 +394,7 @@ if __name__ == '__main__':
         plot_dir = make_dir(args.cwd, plot_args.feature_change)
         plot_optimization_result(base_result, plot_dir)
         plot_evaluation_information(args.cwd + '/' + 'test_data.pkl', plot_dir)
-    '''compare the different cost get from pyomo and PPO'''
+    '''compare the different cost get from gurobi and PPO'''
     ration = sum(eval_data['operation_cost']) / sum(base_result['step_cost'])
     print('operation_cost_sum:', sum(eval_data['operation_cost']))
     print('step_cost_sum:', sum(base_result['step_cost']))

SAC.py

@@ -46,7 +46,7 @@ if __name__ == '__main__':
         # args.save_network=False
         # args.test_network=False
         # args.save_test_data=False
-        # args.compare_with_pyomo=False
+        # args.compare_with_gurobi=False
         #
         if args.train:
             collect_data = True
@@ -102,8 +102,8 @@ if __name__ == '__main__':
         with open(test_data_save_path, 'wb') as tf:
             pickle.dump(record, tf)
 
-    '''compare with pyomo data and results'''
-    if args.compare_with_pyomo:
+    '''compare with gurobi data and results'''
+    if args.compare_with_gurobi:
         month = record['init_info'][0][0]
         day = record['init_info'][0][1]
         initial_soc = record['init_info'][0][3]
@@ -117,7 +117,7 @@ if __name__ == '__main__':
         plot_dir = make_dir(args.cwd, plot_args.feature_change)
         plot_optimization_result(base_result, plot_dir)
         plot_evaluation_information(args.cwd + '/' + 'test_data.pkl', plot_dir)
-    '''compare the different cost get from pyomo and SAC'''
+    '''compare the different cost get from gurobi and SAC'''
     ration = sum(eval_data['operation_cost']) / sum(base_result['step_cost'])
     print('operation_cost_sum:', sum(eval_data['operation_cost']))
     print('step_cost_sum:', sum(base_result['step_cost']))

TD3.py

@@ -43,7 +43,7 @@ if __name__ == '__main__':
         # args.save_network=False
         # args.test_network=False
         # args.save_test_data=False
-        # args.compare_with_pyomo=False
+        # args.compare_with_gurobi=False
 
         if args.train:
             collect_data = True
@@ -98,8 +98,8 @@ if __name__ == '__main__':
         with open(test_data_save_path, 'wb') as tf:
             pickle.dump(record, tf)
 
-    '''compare with pyomo data and results'''
-    if args.compare_with_pyomo:
+    '''compare with gurobi data and results'''
+    if args.compare_with_gurobi:
         month = record['init_info'][0][0]
         day = record['init_info'][0][1]
         initial_soc = record['init_info'][0][3]
@@ -113,7 +113,7 @@ if __name__ == '__main__':
         plot_dir = make_dir(args.cwd, plot_args.feature_change)
         plot_optimization_result(base_result, plot_dir)
         plot_evaluation_information(args.cwd + '/' + 'test_data.pkl', plot_dir)
-    '''compare the different cost get from pyomo and TD3'''
+    '''compare the different cost get from gurobi and TD3'''
     ration = sum(eval_data['operation_cost']) / sum(base_result['step_cost'])
     print('operation_cost_sum:', sum(eval_data['operation_cost']))
     print('step_cost_sum:', sum(base_result['step_cost']))

tools.py

@@ -152,7 +152,7 @@ class Arguments:
         self.save_network = True
         self.test_network = True
         self.save_test_data = True
-        self.compare_with_pyomo = True
+        self.compare_with_gurobi = True
         self.plot_on = True
 
     def init_before_training(self, if_main):