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