Improved docs

Fixed several bugs
Added convenience methods in soil.analysis

examples/custom-agents/UnnamedSimulation.dumped.yml

@@ -1,17 +0,0 @@
-default_state: {}
-environment_agents: []
-environment_params: {prob_neighbor_spread: 0.0, prob_tv_spread: 0.01}
-interval: 1
-max_time: 20
-name: Sim_prob_0
-network_agents:
-- agent_type: NewsSpread
-  state: {has_tv: false}
-  weight: 1
-- agent_type: NewsSpread
-  state: {has_tv: true}
-  weight: 2
-network_params: {generator: erdos_renyi_graph, n: 500, p: 0.1}
-num_trials: 1
-states:
-- {has_tv: true}

examples/custom-agents/agent.py

@@ -1,20 +0,0 @@
-import soil
-import random
-
-class NewsSpread(soil.agents.FSM):
-    @soil.agents.default_state
-    @soil.agents.state
-    def neutral(self):
-        r = random.random()
-        if self['has_tv'] and r < self.env['prob_tv_spread']:
-                return self.infected
-        return
-
-    @soil.agents.state
-    def infected(self):
-        prob_infect = self.env['prob_neighbor_spread']
-        for neighbor in self.get_neighboring_agents(state_id=self.neutral.id):
-            r = random.random()
-            if r < prob_infect:
-                neighbor.state['id'] = self.infected.id
-        return

examples/newsspread/NewsSpread.yml

@@ -0,0 +1,138 @@
+---
+default_state: {}
+load_module: newsspread
+environment_agents: []
+environment_params:
+  prob_neighbor_spread: 0.0
+  prob_tv_spread: 0.01
+interval: 1
+max_time: 30
+name: Sim_all_dumb
+network_agents:
+- agent_type: DumbViewer
+  state:
+    has_tv: false
+  weight: 1
+- agent_type: DumbViewer
+  state:
+    has_tv: true
+  weight: 1
+network_params:
+  generator: barabasi_albert_graph
+  n: 500
+  m: 5
+num_trials: 50
+---
+default_state: {}
+load_module: newsspread
+environment_agents: []
+environment_params:
+  prob_neighbor_spread: 0.0
+  prob_tv_spread: 0.01
+interval: 1
+max_time: 30
+name: Sim_half_herd
+network_agents:
+- agent_type: DumbViewer
+  state:
+    has_tv: false
+  weight: 1
+- agent_type: DumbViewer
+  state:
+    has_tv: true
+  weight: 1
+- agent_type: HerdViewer
+  state:
+    has_tv: false
+  weight: 1
+- agent_type: HerdViewer
+  state:
+    has_tv: true
+  weight: 1
+network_params:
+  generator: barabasi_albert_graph
+  n: 500
+  m: 5
+num_trials: 50
+---
+default_state: {}
+load_module: newsspread
+environment_agents: []
+environment_params:
+  prob_neighbor_spread: 0.0
+  prob_tv_spread: 0.01
+interval: 1
+max_time: 30
+name: Sim_all_herd
+network_agents:
+- agent_type: HerdViewer
+  state:
+    has_tv: true
+    id: infected
+  weight: 1
+- agent_type: HerdViewer
+  state:
+    has_tv: true
+    id: neutral
+  weight: 1
+network_params:
+  generator: barabasi_albert_graph
+  n: 500
+  m: 5
+num_trials: 50
+---
+default_state: {}
+load_module: newsspread
+environment_agents: []
+environment_params:
+  prob_neighbor_spread: 0.0
+  prob_tv_spread: 0.01
+  prob_neighbor_cure: 0.1
+interval: 1
+max_time: 30
+name: Sim_wise_herd
+network_agents:
+- agent_type: HerdViewer
+  state:
+    has_tv: true
+    id: infected
+  weight: 1
+- agent_type: WiseViewer
+  state:
+    has_tv: true
+  weight: 1
+network_params:
+  generator: barabasi_albert_graph
+  n: 500
+  m: 5
+num_trials: 50
+---
+default_state: {}
+load_module: newsspread
+environment_agents: []
+environment_params:
+  prob_neighbor_spread: 0.0
+  prob_tv_spread: 0.01
+  prob_neighbor_cure: 0.1
+interval: 1
+max_time: 30
+name: Sim_all_wise
+network_agents:
+- agent_type: WiseViewer
+  state:
+    has_tv: true
+    id: infected
+  weight: 1
+- agent_type: WiseViewer
+  state:
+    has_tv: true
+  weight: 1
+network_params:
+  generator: barabasi_albert_graph
+  n: 500
+  m: 5
+network_params:
+  generator: barabasi_albert_graph
+  n: 500
+  m: 5
+num_trials: 50

examples/newsspread/newsspread.py

@@ -0,0 +1,79 @@
+from soil.agents import BaseAgent,FSM, state, default_state
+import random
+import logging
+
+
+class DumbViewer(FSM):
+    '''
+    A viewer that gets infected via TV (if it has one) and tries to infect
+    its neighbors once it's infected.
+    '''
+    defaults = {
+        'prob_neighbor_spread': 0.5,
+        'prob_neighbor_cure': 0.25,
+    }
+
+    @default_state
+    @state
+    def neutral(self):
+        r = random.random()
+        if self['has_tv'] and r < self.env['prob_tv_spread']:
+            self.infect()
+        return
+
+    @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)
+                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:
+            self.set_state(self.infected.id)
+
+class WiseViewer(HerdViewer):
+    '''
+    A viewer that can change its mind.
+    '''
+    @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:
+                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()

examples/rabbits/rabbit_agents.py

@@ -1,4 +1,4 @@
-from soil.agents import NetworkAgent, FSM, state, default_state, BaseAgent
+from soil.agents import FSM, state, default_state, BaseAgent
 from enum import Enum
 from random import random, choice
 from itertools import islice
@@ -11,7 +11,7 @@ class Genders(Enum):
     female = 'female'
 
 
-class RabbitModel(NetworkAgent, FSM):
+class RabbitModel(FSM):
 
     level = logging.INFO
 
@@ -26,7 +26,7 @@ class RabbitModel(NetworkAgent, FSM):
     life_expectancy = 365 * 3
     gestation = 33
     pregnancy = -1
-    max_females = 2
+    max_females = 5
 
     @default_state
     @state
@@ -71,6 +71,7 @@ class RabbitModel(NetworkAgent, FSM):
         self.debug('Pregnancy: {}'.format(self['pregnancy']))
         if self['pregnancy'] >= self.gestation:
             number_of_babies = int(8+4*random())
+            self.info('Having {} babies'.format(number_of_babies))
             for i in range(number_of_babies):
                 state = {}
                 state['gender'] = choice(list(Genders)).value
@@ -79,13 +80,13 @@ class RabbitModel(NetworkAgent, FSM):
                 self.env.add_edge(self['mate'], child.id)
                 # self.add_edge()
                 self.debug('A BABY IS COMING TO LIFE')
-                self.env['rabbits_alive'] = self.env.get('rabbits_alive', 0)+1
+                self.env['rabbits_alive'] = self.env.get('rabbits_alive', self.global_topology.number_of_nodes())+1
                 self.debug('Rabbits alive: {}'.format(self.env['rabbits_alive']))
                 self['offspring'] += 1
                 self.env.get_agent(self['mate'])['offspring'] += 1
-                del self['mate']
-                self['pregnancy'] = -1
-                return self.fertile
+            del self['mate']
+            self['pregnancy'] = -1
+            return self.fertile
 
     @state
     def dead(self):
@@ -98,12 +99,12 @@ class RabbitModel(NetworkAgent, FSM):
 
 class RandomAccident(BaseAgent):
 
-    level = logging.INFO
+    level = logging.DEBUG
 
     def step(self):
         rabbits_total = self.global_topology.number_of_nodes()
         rabbits_alive = self.env.get('rabbits_alive', rabbits_total)
-        prob_death = self.env.get('prob_death', 1e-100)*math.log(max(1, rabbits_alive))
+        prob_death = self.env.get('prob_death', 1e-100)*math.floor(math.log10(max(1, rabbits_alive)))
         self.debug('Killing some rabbits with prob={}!'.format(prob_death))
         for i in self.env.network_agents:
             if i.state['id'] == i.dead.id:

examples/rabbits/rabbits.yml

@@ -1,14 +1,14 @@
 ---
 load_module: rabbit_agents
 name: rabbits_example
-max_time: 1500
+max_time: 1200
 interval: 1
 seed: MySeed
 agent_type: RabbitModel
 environment_agents:
     - agent_type: RandomAccident
 environment_params:
-  prob_death: 0.0001
+  prob_death: 0.001
 default_state:
   mating_prob: 0.01
 topology: