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Control model M2 implemented

This commit is contained in:
JesusMSM 2016-05-04 12:20:23 +02:00
parent 4c71949d44
commit 038d388afd
8 changed files with 67161 additions and 1408 deletions

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@ -56,6 +56,118 @@ class ComportamientoBase(BaseNetworkAgent):
final[a][stamp] = attrs[a]
return final
class ControlModelM2(ComportamientoBase):
#Init infected
init_states[random.randint(0,settings.number_of_nodes-1)] = {'id':1}
init_states[random.randint(0,settings.number_of_nodes-1)] = {'id':1}
# Init beacons
init_states[random.randint(0, settings.number_of_nodes-1)] = {'id': 4}
init_states[random.randint(0, settings.number_of_nodes-1)] = {'id': 4}
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(settings.prob_neutral_making_denier, settings.standard_variance)
self.prob_infect = np.random.normal(settings.prob_infect, settings.standard_variance)
self.prob_cured_healing_infected = np.random.normal(settings.prob_cured_healing_infected, settings.standard_variance)
self.prob_cured_vaccinate_neutral = np.random.normal(settings.prob_cured_vaccinate_neutral, settings.standard_variance)
self.prob_vaccinated_healing_infected = np.random.normal(settings.prob_vaccinated_healing_infected, settings.standard_variance)
self.prob_vaccinated_vaccinate_neutral = np.random.normal(settings.prob_vaccinated_vaccinate_neutral, settings.standard_variance)
self.prob_generate_anti_rumor = np.random.normal(settings.prob_generate_anti_rumor, settings.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()
elif self.state['id'] == 4: #Beacon-off
self.beacon_off_behaviour()
elif self.state['id'] == 5: #Beacon-on
self.beacon_on_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
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
def beacon_off_behaviour(self):
infected_neighbors = self.get_neighboring_agents(state_id=1)
if len(infected_neighbors) > 0:
self.state['id'] == 5 #Beacon on
def beacon_on_behaviour(self):
infected_neighbors = self.get_neighboring_agents(state_id=1)
for neighbor in infected_neighbors:
if random.random() < self.prob_generate_anti_rumor:
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
class SpreadModelM2(ComportamientoBase):
init_states[random.randint(0,settings.number_of_nodes)] = {'id':1}
init_states[random.randint(0,settings.number_of_nodes)] = {'id':1}

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@ -40,10 +40,10 @@ def init():
global prob_generate_anti_rumor
network_type=1
number_of_nodes=20
number_of_nodes=1000
max_time=50
num_trials=1
timeout=1
timeout=2
#Zombie model
bite_prob=0.01 # 0-1
@ -87,7 +87,7 @@ def init():
standard_variance = 0.055
#Spread Model M2
#Spread Model M2 and Control Model M2
prob_neutral_making_denier = 0.035
prob_infect = 0.075

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@ -79,7 +79,8 @@ neutral_line = plt.plot(x_values,neutral_values, label='Neutral')
cured_line = plt.plot(x_values,cured_values, label='Cured')
vaccinated_line = plt.plot(x_values,vaccinated_values, label='Vaccinated')
plt.legend()
plt.show()
plt.savefig('spread_model.png')
#plt.show()
#################

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