test

models/SpreadModelM2/SpreadModelM2.py

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+import settings
+import random
+import numpy as np
+from models.BaseBehaviour import *
+from models import init_states
+
+
+class SpreadModelM2(BaseBehaviour):
+    """
+    Settings:
+        prob_neutral_making_denier
+
+        prob_infect
+
+        prob_cured_healing_infected
+
+        prob_cured_vaccinate_neutral
+
+        prob_vaccinated_healing_infected
+
+        prob_vaccinated_vaccinate_neutral
+
+        prob_generate_anti_rumor
+    """
+    for x in range(settings.environment_params['source']):
+        init_states[random.randint(0, settings.network_params["number_of_nodes"])] = {'id': 1}
+
+    def __init__(self, environment=None, agent_id=0, state=()):
+        super().__init__(environment=environment, agent_id=agent_id, state=state)
+
+        self.prob_neutral_making_denier = np.random.normal(environment.environment_params['prob_neutral_making_denier']/settings.environment_params['source'],
+                                                           environment.environment_params['standard_variance'])
+
+        self.prob_infect = np.random.normal(environment.environment_params['prob_infect'],
+                                            environment.environment_params['standard_variance'])
+
+        self.prob_cured_healing_infected = np.random.normal(environment.environment_params['prob_cured_healing_infected'],
+                                                            environment.environment_params['standard_variance'])
+        self.prob_cured_vaccinate_neutral = np.random.normal(environment.environment_params['prob_cured_vaccinate_neutral'],
+                                                             environment.environment_params['standard_variance'])
+
+        self.prob_vaccinated_healing_infected = np.random.normal(environment.environment_params['prob_vaccinated_healing_infected'],
+                                                                 environment.environment_params['standard_variance'])
+        self.prob_vaccinated_vaccinate_neutral = np.random.normal(environment.environment_params['prob_vaccinated_vaccinate_neutral'],
+                                                                  environment.environment_params['standard_variance'])
+        self.prob_generate_anti_rumor = np.random.normal(environment.environment_params['prob_generate_anti_rumor'],
+                                                         environment.environment_params['standard_variance'])
+
+
+    def step(self, now):
+
+        if self.state['id'] == 0:  # Neutral
+            self.neutral_behaviour()
+        elif self.state['id'] == 1:  # Infected
+            self.infected_behaviour()
+        # elif self.state['id'] == 2:  # Cured
+        #     self.cured_behaviour()
+        # elif self.state['id'] == 3:  # Vaccinated
+            # self.vaccinated_behaviour()
+
+        self.attrs['status'] = self.state['id']
+        super().step(now)
+
+    def neutral_behaviour(self):
+
+        # Infected
+        infected_neighbors = self.get_neighboring_agents(state_id=1)
+        if len(infected_neighbors) > 0:
+            if random.random() < self.prob_neutral_making_denier:
+                self.state['id'] = 3   # Vaccinated making denier
+
+        # Generate anti-rumor
+        infected_neighbors_2 = self.get_neighboring_agents(state_id=1)
+        for neighbor in infected_neighbors_2:
+            if random.random() < self.prob_generate_anti_rumor:
+                neighbor.state['id'] = 2  # Cured
+
+    def infected_behaviour(self):
+
+        # Neutral
+        neutral_neighbors = self.get_neighboring_agents(state_id=0)
+        for neighbor in neutral_neighbors:
+            if random.random() < self.prob_infect:
+                neighbor.state['id'] = 1  # Infected
+
+    def cured_behaviour(self):
+
+        # Vaccinate
+        # neutral_neighbors = self.get_neighboring_agents(state_id=0)
+        # for neighbor in neutral_neighbors:
+        #     if random.random() < self.prob_cured_vaccinate_neutral:
+        #         neighbor.state['id'] = 3  # Vaccinated
+
+        # Cure
+        infected_neighbors = self.get_neighboring_agents(state_id=1)
+        for neighbor in infected_neighbors:
+            if random.random() < self.prob_cured_healing_infected:
+                neighbor.state['id'] = 2  # Cured
+
+    def vaccinated_behaviour(self):
+
+        # Cure
+        infected_neighbors = self.get_neighboring_agents(state_id=1)
+        for neighbor in infected_neighbors:
+            if random.random() < self.prob_cured_healing_infected:
+                neighbor.state['id'] = 2  # Cured
+
+        # Vaccinate
+        neutral_neighbors = self.get_neighboring_agents(state_id=0)
+        for neighbor in neutral_neighbors:
+            if random.random() < self.prob_cured_vaccinate_neutral:
+                neighbor.state['id'] = 3  # Vaccinated
+
+        # Generate anti-rumor
+        infected_neighbors_2 = self.get_neighboring_agents(state_id=1)
+        for neighbor in infected_neighbors_2:
+            if random.random() < self.prob_generate_anti_rumor:
+                neighbor.state['id'] = 2  # Cured

models/SpreadModelM2/__init__.py

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+from .SpreadModelM2 import SpreadModelM2