WIP soil

* Pandas integration
* Improved environment
* Logging and data dumps
* Tests
* Added Finite State Machine models
* Rewritten ipython notebook and documentation

soil/agents/BigMarketModel.py

@@ -0,0 +1,102 @@
+import random
+from . import NetworkAgent
+
+
+class BigMarketModel(NetworkAgent):
+    """
+    Settings:
+        Names:
+            enterprises [Array]
+            
+            tweet_probability_enterprises [Array]
+        Users:
+            tweet_probability_users
+            
+            tweet_relevant_probability
+            
+            tweet_probability_about [Array]
+            
+            sentiment_about [Array]
+    """
+
+    def __init__(self, environment=None, agent_id=0, state=()):
+        super().__init__(environment=environment, agent_id=agent_id, state=state)
+        self.enterprises = environment.environment_params['enterprises']
+        self.type = ""
+        self.number_of_enterprises = len(environment.environment_params['enterprises'])
+
+        if self.id < self.number_of_enterprises:  # Enterprises
+            self.state['id'] = self.id
+            self.type = "Enterprise"
+            self.tweet_probability = environment.environment_params['tweet_probability_enterprises'][self.id]
+        else:  # normal users
+            self.state['id'] = self.number_of_enterprises
+            self.type = "User"
+            self.tweet_probability = environment.environment_params['tweet_probability_users']
+            self.tweet_relevant_probability = environment.environment_params['tweet_relevant_probability']
+            self.tweet_probability_about = environment.environment_params['tweet_probability_about']  # List
+            self.sentiment_about = environment.environment_params['sentiment_about']  # List
+
+    def step(self):
+
+        if self.id < self.number_of_enterprises:  # Enterprise
+            self.enterpriseBehaviour()
+        else:  # Usuario
+            self.userBehaviour()
+            for i in range(self.number_of_enterprises):  # So that it never is set to 0 if there are not changes (logs)
+                self.attrs['sentiment_enterprise_%s'% self.enterprises[i]] = self.sentiment_about[i]
+
+    def enterpriseBehaviour(self):
+
+        if random.random() < self.tweet_probability:  # Tweets
+            aware_neighbors = self.get_neighboring_agents(state_id=self.number_of_enterprises)  # Nodes neighbour users
+            for x in aware_neighbors:
+                if random.uniform(0,10) < 5:
+                    x.sentiment_about[self.id] += 0.1  # Increments for enterprise
+                else:
+                    x.sentiment_about[self.id] -= 0.1  # Decrements for enterprise
+
+                # Establecemos limites
+                if x.sentiment_about[self.id] > 1:
+                    x.sentiment_about[self.id] = 1
+                if x.sentiment_about[self.id]< -1:
+                    x.sentiment_about[self.id] = -1
+
+                x.attrs['sentiment_enterprise_%s'% self.enterprises[self.id]] = x.sentiment_about[self.id]
+
+    def userBehaviour(self):
+
+        if random.random() < self.tweet_probability:  # Tweets
+            if random.random() < self.tweet_relevant_probability:  # Tweets something relevant
+                # Tweet probability per enterprise
+                for i in range(self.number_of_enterprises):
+                    random_num = random.random()
+                    if random_num < self.tweet_probability_about[i]:
+                        # The condition is fulfilled, sentiments are evaluated towards that enterprise
+                        if self.sentiment_about[i] < 0:
+                            # NEGATIVO
+                            self.userTweets("negative",i)
+                        elif self.sentiment_about[i] == 0:
+                            # NEUTRO
+                            pass
+                        else:
+                            # POSITIVO
+                            self.userTweets("positive",i)
+
+    def userTweets(self,sentiment,enterprise):
+        aware_neighbors = self.get_neighboring_agents(state_id=self.number_of_enterprises)  # Nodes neighbours users
+        for x in aware_neighbors:
+            if sentiment == "positive":
+                x.sentiment_about[enterprise] +=0.003
+            elif sentiment == "negative":
+                x.sentiment_about[enterprise] -=0.003
+            else:
+                pass
+
+            # Establecemos limites
+            if x.sentiment_about[enterprise] > 1:
+                x.sentiment_about[enterprise] = 1
+            if x.sentiment_about[enterprise] < -1:
+                x.sentiment_about[enterprise] = -1
+
+            x.attrs['sentiment_enterprise_%s'% self.enterprises[enterprise]] = x.sentiment_about[enterprise]