Parallelism and granular exporting options

* Graphs are not saved by default (not backwards compatible)
* Modified newsspread examples
* More granular options to save results (exporting to CSV and GEXF are now
optional)
* Updated tutorial to include exporting options
* Removed references from environment to simulation
* Added parallelism to simulations (can be turned off with a flag or argument).

examples/newsspread/NewsSpread.yml

@@ -68,7 +68,7 @@ network_agents:
 - agent_type: HerdViewer
   state:
     has_tv: true
-    id: infected
+    id: neutral
   weight: 1
 - agent_type: HerdViewer
   state:
@@ -95,7 +95,7 @@ network_agents:
 - agent_type: HerdViewer
   state:
     has_tv: true
-    id: infected
+    id: neutral
   weight: 1
 - agent_type: WiseViewer
   state:
@@ -121,7 +121,7 @@ network_agents:
 - agent_type: WiseViewer
   state:
     has_tv: true
-    id: infected
+    id: neutral
   weight: 1
 - agent_type: WiseViewer
   state:

examples/newsspread/newsspread.py

@@ -1,5 +1,4 @@
-from soil.agents import BaseAgent,FSM, state, default_state
-import random
+from soil.agents import FSM, state, default_state, prob
 import logging
 
 
@@ -10,70 +9,73 @@ class DumbViewer(FSM):
     '''
     defaults = {
         'prob_neighbor_spread': 0.5,
-        'prob_neighbor_cure': 0.25,
+        'prob_tv_spread': 0.1,
     }
 
     @default_state
     @state
     def neutral(self):
-        r = random.random()
-        if self['has_tv'] and r < self.env['prob_tv_spread']:
-            self.infect()
-        return
+        if self['has_tv']:
+            if prob(self.env['prob_tv_spread']):
+                self.set_state(self.infected)
 
     @state
     def infected(self):
         for neighbor in self.get_neighboring_agents(state_id=self.neutral.id):
-            prob_infect = self.env['prob_neighbor_spread']
-            r = random.random()
-            if r < prob_infect:
-                self.set_state(self.infected.id)
+            if prob(self.env['prob_neighbor_spread']):
                 neighbor.infect()
-        return
 
     def infect(self):
         self.set_state(self.infected)
 
+
 class HerdViewer(DumbViewer):
     '''
     A viewer whose probability of infection depends on the state of its neighbors.
     '''
 
     level = logging.DEBUG
- 
+
     def infect(self):
         infected = self.count_neighboring_agents(state_id=self.infected.id)
         total = self.count_neighboring_agents()
         prob_infect = self.env['prob_neighbor_spread'] * infected/total
         self.debug('prob_infect', prob_infect)
-        r = random.random()
-        if r < prob_infect:
+        if prob(prob_infect):
             self.set_state(self.infected.id)
 
+
 class WiseViewer(HerdViewer):
     '''
     A viewer that can change its mind.
     '''
+
+    defaults = {
+        'prob_neighbor_spread': 0.5,
+        'prob_neighbor_cure': 0.25,
+        'prob_tv_spread': 0.1,
+    }
+
     @state
     def cured(self):
         prob_cure = self.env['prob_neighbor_cure']
         for neighbor in self.get_neighboring_agents(state_id=self.infected.id):
-            r = random.random()
-            if r < prob_cure:
+            if prob(prob_cure):
                 try:
                     neighbor.cure()
                 except AttributeError:
                     self.debug('Viewer {} cannot be cured'.format(neighbor.id))
-        return
 
     def cure(self):
         self.set_state(self.cured.id)
 
     @state
     def infected(self):
-        prob_cure = self.env['prob_neighbor_cure']
-        r = random.random()
-        if r < prob_cure:
-            self.cure()
-            return
-        return super().infected()
+        cured = max(self.count_neighboring_agents(self.cured.id),
+                    1.0)
+        infected = max(self.count_neighboring_agents(self.infected.id),
+                       1.0)
+        prob_cure = self.env['prob_neighbor_cure'] * (cured/infected)
+        if prob(prob_cure):
+            return self.cure()
+        return self.set_state(super().infected)