last changes

backend/dqn.py

@@ -21,7 +21,7 @@ def train(space, activities):
         os.makedirs(logdir)
 
     # model = PPO('MultiInputPolicy', env, verbose=1, tensorboard_log=logdir)
-    model = DQN('MultiInputPolicy', env, buffer_size = 50000000 ,verbose=1, exploration_fraction = 0.8, gamma=0.1, learning_starts = 10000, tensorboard_log=logdir)
+    model = DQN('MultiInputPolicy', env, verbose=1, exploration_fraction = 0.8, gamma=0.1, learning_starts = 10000, tensorboard_log=logdir)
 
     TIMESTEPS = 1250000
     iters = 0
@@ -32,7 +32,7 @@ def train(space, activities):
 
 
 def deploy(state):
-    model = DQN.load(r"models\other\1000000.zip")
+    model = DQN.load(r"models\1687531146\1250000.zip")
     action, _ = model.predict(state, deterministic=True)
 
     return action

backend/eventlog.py

@@ -311,7 +311,8 @@ def show_active_cases(name):
 def main():
     # generate_event_log(10000)
     # print(get_state(5, "eventlog.xes"))
-    print(format_check("eventlog.xes"))
+    # print(format_check("eventlog.xes"))
+    print(show_active_cases("eventlog.csv"))
 
 
 if __name__ == "__main__":

backend/petrinet.py

@@ -68,9 +68,10 @@ def decorate_petri_net(case, rec, name):
 
 
     pm4py.view_petri_net(net, initial_marking, final_marking, decorations = decoration)
+    pm4py.save_vis_petri_net(net, initial_marking, final_marking, r"Frontend\export\net.png")
 
 
-decorate_petri_net(5, 15, "optis")
+decorate_petri_net(646, 7, "eventlog.csv")
 
 
 

backend/test.py

@@ -13,4 +13,6 @@ def test_agent():
     state['process'] = np.asarray(process)
     print(state)
 
-    print(dqn.deploy(state))
\ No newline at end of file
+    print(dqn.deploy(state))
+
+test_agent()
\ No newline at end of file