Added dynamic graph.

Added dynamic graph to ControlModelM2.

models/ModelM2/ControlModelM2.py

@@ -71,6 +71,7 @@ class ControlModelM2(BaseBehaviour):
         super().step(now)
 
     def neutral_behaviour(self):
+        self.attrs['visible'] = False
 
         # Infected
         infected_neighbors = self.get_neighboring_agents(state_id=1)
@@ -85,9 +86,11 @@ class ControlModelM2(BaseBehaviour):
         for neighbor in neutral_neighbors:
             if random.random() < self.prob_infect:
                 neighbor.state['id'] = 1  # Infected
+        self.attrs['visible'] = False
 
     def cured_behaviour(self):
 
+        self.attrs['visible'] = True
         # Vaccinate
         neutral_neighbors = self.get_neighboring_agents(state_id=0)
         for neighbor in neutral_neighbors:
@@ -101,6 +104,7 @@ class ControlModelM2(BaseBehaviour):
                 neighbor.state['id'] = 2  # Cured
 
     def vaccinated_behaviour(self):
+        self.attrs['visible'] = True
 
         # Cure
         infected_neighbors = self.get_neighboring_agents(state_id=1)
@@ -121,12 +125,13 @@ class ControlModelM2(BaseBehaviour):
                 neighbor.state['id'] = 2  # Cured
 
     def beacon_off_behaviour(self):
+        self.attrs['visible'] = False
         infected_neighbors = self.get_neighboring_agents(state_id=1)
         if len(infected_neighbors) > 0:
             self.state['id'] == 5  # Beacon on
 
     def beacon_on_behaviour(self):
-
+        self.attrs['visible'] = False
         # Cure (M2 feature added)
         infected_neighbors = self.get_neighboring_agents(state_id=1)
         for neighbor in infected_neighbors:

settings.json

@@ -8,7 +8,7 @@
   },
 
   {
-    "agent": ["BaseBehaviour","SISaModel","ControlModelM2"],
+    "agent": ["SISaModel","ControlModelM2"],
 
 
     "bite_prob": 0.01,

soil.py

@@ -16,14 +16,32 @@ import json
 def visualization(graph_name):
 
     for x in range(0, settings.network_params["number_of_nodes"]):
+        attributes = {}
+        spells = []
         for attribute in models.networkStatus["agent_%s" % x]:
-            emotionStatusAux = []
-            for t_step in models.networkStatus["agent_%s" % x][attribute]:
-                prec = 2
-                output = math.floor(models.networkStatus["agent_%s" % x][attribute][t_step] * (10 ** prec)) / (10 ** prec)  # 2 decimals
-                emotionStatusAux.append((output, t_step, t_step + settings.network_params["timeout"]))
-            attributes = {}
-            attributes[attribute] = emotionStatusAux
+            if attribute == 'visible':
+                lastvisible = False
+                laststep = 0
+                for t_step in models.networkStatus["agent_%s" % x][attribute]:
+                    nowvisible = models.networkStatus["agent_%s" % x][attribute][t_step]
+                    if nowvisible and not lastvisible:
+                        laststep = t_step
+                    if not nowvisible and lastvisible:
+                        spells.append((laststep, t_step))
+
+                    lastvisible = nowvisible
+                if lastvisible:
+                    spells.append((laststep, None))
+            else:
+                emotionStatusAux = []
+                for t_step in models.networkStatus["agent_%s" % x][attribute]:
+                    prec = 2
+                    output = math.floor(models.networkStatus["agent_%s" % x][attribute][t_step] * (10 ** prec)) / (10 ** prec)  # 2 decimals
+                    emotionStatusAux.append((output, t_step, t_step + settings.network_params["timeout"]))
+                attributes[attribute] = emotionStatusAux
+        if spells:
+            G.add_node(x, attributes, spells=spells)
+        else:
             G.add_node(x, attributes)
 
     print("Done!")
@@ -101,7 +119,6 @@ if settings.network_params["network_type"] == 2:
     G = nx.margulis_gabber_galil_graph(settings.network_params["number_of_nodes"], None)
 # More types of networks can be added here
 
-
 ##############
 # Simulation #
 ##############
@@ -124,4 +141,4 @@ else:
                             num_trials=settings.network_params["num_trials"], logging_interval=1.0, **settings.environment_params)
     sim.run_simulation()
     results(str(agent))
-    visualization(str(agent))
+    visualization(str(agent))