Cleaned code

config.ini

@@ -1,24 +1,20 @@
 [PARAMETERS]
-no_of_transactions = 2500
-lambda = 25
+no_of_transactions = 300
+lambda = 50
 no_of_agents = 2
-alpha = 1
+alpha = 0.005
 latency = 1
-distance = 500
+distance = 5000
 tip_selection_algo = weighted
 agent_choice = [1.0,0.0]
 printing = True
 
 
 [EVENT1]
-step = 1000
+step = 200
 agent_choice = [0.7,0.3]
 
 
 [EVENT2]
-step = 1500
+step = 250
 distance = 1
-
-
-[EVENT3]
-step = 2500

core.py

@@ -6,7 +6,7 @@
 
 from simulation.helpers import update_progress, csv_export
 from simulation.plotting import print_graph, print_tips_over_time, \
-print_tips_over_time_multiple_agents, print_tips_over_time_multiple_agents_with_tangle
+print_tips_over_time_multiple_agents, print_tips_over_time_multiple_agents_with_tangle, print_attachment_probabilities
 from simulation.simulation import Single_Agent_Simulation
 from simulation.simulation_multi_agent import Multi_Agent_Simulation
 
@@ -47,7 +47,7 @@
 
 for i in range(runs):
 
- simu2 = Multi_Agent_Simulation(50, 3, 2, 0.005, 1, "weighted", _agent_choice=[0.7,0.3], _printing=True)
+ simu2 = Multi_Agent_Simulation(100, 3, 2, 0.005, 1, "weighted", _agent_choice=[0.7,0.3], _printing=True)
  simu2.setup()
  simu2.run()
 
@@ -85,6 +85,7 @@
 # print_tips_over_time(simu2)
 # print_tips_over_time_multiple_agents(simu2, simu2.no_of_transactions)
 # print_tips_over_time_multiple_agents_with_tangle(simu2, simu2.no_of_transactions)
+#print_attachment_probabilities(simu2)
 
 
 #Plotting the partitioning values for multiple simulations, cumulative mean and 95% confidence interval
@@ -109,10 +110,9 @@
 # # plt.plot(np.unique(simu2.arrival_times), np.poly1d(np.polyfit(simu2.arrival_times, simu2.record_desc, 1))(np.unique(simu2.arrival_times)), label="Best Fit Line", linestyle='--')
 # plt.xlabel("Time (s)")
 # plt.ylabel("Descendants of incoming transaction / total current transactions in Tangle")
-# # plt.plot(partitioning_values)
-# # plt.plot(average_partitioning_across_simus)
-# # lower_bound_95_confidence_interval = st.t.interval(0.80, len(partitioning_values)-1, loc=np.mean(partitioning_values), scale=st.sem(partitioning_values))[0]
-# # upper_bound_95_confidence_interval = st.t.interval(0.80, len(partitioning_values)-1, loc=np.mean(partitioning_values), scale=st.sem(partitioning_values))[1]
-# # plt.axhline(y=lower_bound_95_confidence_interval, color='r', linestyle='-')
-# # plt.axhline(y=upper_bound_95_confidence_interval, color='r', linestyle='-')
+# plt.plot(simu2.record_attachment_probabilities)
+# lower_bound_95_confidence_interval = st.t.interval(0.80, len(partitioning_values)-1, loc=np.mean(partitioning_values), scale=st.sem(partitioning_values))[0]
+# upper_bound_95_confidence_interval = st.t.interval(0.80, len(partitioning_values)-1, loc=np.mean(partitioning_values), scale=st.sem(partitioning_values))[1]
+# plt.axhline(y=lower_bound_95_confidence_interval, color='r', linestyle='-')
+# plt.axhline(y=upper_bound_95_confidence_interval, color='r', linestyle='-')
 # plt.show()

simulation/plotting.py

@@ -248,3 +248,41 @@ def print_tips_over_time_multiple_agents(self, no_current_transactions):
 
 
  plt.show()
+
+
+
+def print_attachment_probabilities(self):
+
+ plt.figure(figsize=(14, 8))
+ print(self.record_attachment_probabilities)
+
+ x = np.squeeze([i[0] for i in self.record_attachment_probabilities])
+ y = np.squeeze([i[1] for i in self.record_attachment_probabilities])
+ # print(x,y)
+
+ plt.plot(x,y)
+ plt.plot(np.unique(x), np.poly1d(np.polyfit(x, y, 1))(np.unique(x)),\
+ label="Best Fit", linestyle='--')
+
+ x_mean = [i for i in x]
+ y_mean = [np.mean(y) for i in y]
+ print(np.mean(y))
+ plt.plot(x_mean, y_mean,\
+ label="Average", linestyle='-')
+
+ # lower_bound_95_confidence_interval = st.t.interval(0.80, len(partitioning_values)-1, loc=np.mean(partitioning_values), scale=st.sem(partitioning_values))[0]
+ # upper_bound_95_confidence_interval = st.t.interval(0.80, len(partitioning_values)-1, loc=np.mean(partitioning_values), scale=st.sem(partitioning_values))[1]
+ # plt.axhline(y=lower_bound_95_confidence_interval, color='r', linestyle='-')
+ # plt.axhline(y=upper_bound_95_confidence_interval, color='r', linestyle='-')
+
+ title = "Transactions = " + str(self.no_of_transactions) + \
+ ", " + r'$\lambda$' + " = " + str(self.lam) + \
+ ", " + r'$d$' + " = " + str(self.distances[1][0])
+ if (self.tip_selection_algo == "weighted"):
+ title += ", " + r'$\alpha$' + " = " + str(self.alpha)
+ plt.xlabel("Transactions (time)")
+ # plt.xticks([])
+ plt.ylabel("Probability to attach to sub-Tangle")
+ plt.legend(loc='upper left')
+ plt.title(title)
+ plt.show()