diff --git a/__pycache__/agent.cpython-36.pyc b/__pycache__/agent.cpython-36.pyc
new file mode 100644
index 0000000..4a51564
Binary files /dev/null and b/__pycache__/agent.cpython-36.pyc differ
diff --git a/__pycache__/simulation.cpython-36.pyc b/__pycache__/simulation.cpython-36.pyc
new file mode 100644
index 0000000..3d76c3d
Binary files /dev/null and b/__pycache__/simulation.cpython-36.pyc differ
diff --git a/main.py b/main.py
index 87240ab..eca66ba 100644
--- a/main.py
+++ b/main.py
@@ -9,8 +9,8 @@ def main():
     average_degree = 8          # Average degree of social network
     num_episode = 2             # Number of total episode in a single simulation for taking ensemble average
     network_type = "lattice"    # topology of social network
-
-    simulation = Simulation(population, average_degree, network_type)
+    display_transparency = 0.7
+    simulation = Simulation(population, average_degree, network_type,display_transparency)
 
     for episode in range(num_episode):
         random.seed()
diff --git a/simulation.py b/simulation.py
index 6221391..c8d05b2 100644
--- a/simulation.py
+++ b/simulation.py
@@ -7,7 +7,7 @@
 
 class Simulation:
     
-    def __init__(self, population, average_degree, network_type):
+    def __init__(self, population, average_degree, network_type,display_transparency):
         """
         network_type has several options, give following network type as string;
             1. lattice
@@ -22,7 +22,7 @@ def __init__(self, population, average_degree, network_type):
         self.network = None
         self.agents = self.__generate_agents(population, average_degree)
         self.initial_cooperators = self.__choose_initial_cooperators()
-
+        self.display_transparency = display_transparency
     def __generate_agents(self, population, average_degree):
         if self.network_type == "lattice":
             self.network = self.__generate_lattice(population)
@@ -245,12 +245,15 @@ def color(i):
             else:
                 pos = nx.spring_layout(self.network)
                 
-        nx.draw_networkx_edges(self.network, pos)
-        nx.draw_networkx_nodes(self.network, pos, node_color = list(color.values()), node_size = 10)
+        nx.draw_networkx_edges(self.network, pos,alpha=self.display_transparency)
+        nx.draw_networkx_nodes(self.network, pos, node_color = list(color.values()), node_size = 10,alpha=self.display_transparency)
         plt.title('t={}'.format(timestep), fontsize=20)
         plt.xticks([])
         plt.yticks([])
-        plt.savefig(f"snapshot_t={timestep}.png")
+        if self.display_transparency==1:
+            plt.savefig(f"snapshot_t={timestep}.png",transparent=False)
+        else:
+            plt.savefig(f"snapshot_t={timestep}.png",transparent=True)
         plt.close()
 
     def one_episode(self, episode):
@@ -264,5 +267,5 @@ def one_episode(self, episode):
                 fc_converged = self.__play_game(episode, Dg, Dr)
                 new_result = pd.DataFrame([[format(Dg, '.1f'), format(Dr, '.1f'), fc_converged]], columns = ['Dg', 'Dr', 'Fc'])
                 result = result.append(new_result)
-        
+        self.__take_snapshot(1)
         result.to_csv(f"phase_diagram{episode}.csv")
\ No newline at end of file