def single_experiment(x, y, mode):
N = 1
inputs = []
start_time = time.time()
model = Model(N, 7, 7, x, y, mode)
i = 0
while True:
print("step : " + str(i))
show_grid(model, 2)
model.step()
running_time = time.time() - start_time
i += 1
agent_perc = model.datacollector.get_agent_vars_dataframe()
if (running_time >= 20 or agent_perc['Position'][-1] == (3, 6)):
break
running_time = time.time() - start_time
print("runningtime : " + str(running_time))
#inputs.append(IF.Inputs_Function(agent_perc))
#print(agent_perc[['View','Position', 'Behaviour', 'Light Perception','Sound Perception']][0:100])
figure = plt.figure(3)
_ = plt.title('Sound Perception during steps')
steps = agent_perc['Iterations'].tolist()
_ = plt.axis([steps[0], steps[-1], 0.4, 1.])
_ = plt.plot(steps, agent_perc['Sound Perception'].tolist())
figure = plt.figure(4)
_ = plt.title('Light Perception during steps')
_ = plt.axis([steps[0], steps[-1], 0., 60.])
_ = plt.plot(steps, agent_perc['Light Perception'].tolist())
agent_perc.head()
plt.show()
def __init__(self,
model,
pos,
direction,
speed=1,
active=True,
trace=None):
"""
Initializes an Agent
:param model: The model that the agent lives in.
:param pos: The initial position in (x, y)
:param direction: The initial agent direction as a Direction-object
:param speed: The initial speed.
:param active: Whether or not the agent is not eliminated.
:param trace: A list of positions that the agent occupied during the last step (just for pre-initialization)
"""
if model is None:
# use an empty model if an agent is used to play against an online game
model = Model()
super().__init__(None, model)
else:
super().__init__(model.next_id(), model)
self.pos = pos
self.direction = direction
self.speed = speed
self.active = active
self.deadline = None
# Holds all cells that were visited in the last step
if trace is None:
self.trace = []
else:
self.trace = trace
self.action = None
self.elimination_step = -1 # Saves the step that the agent was eliminated in (-1 if still active)
def __init__(self):
Model.__init__(self)
self.discussion_post = 0
self.discussion_social_post = 0
self.total_chat = 0
self.total_social_chat = 0
# counters for current period
self.chat_count = 0
self.chat_social_count = 0
self.step_count = 0
for i, x in enumerate(espacio.grid):
for j, y in enumerate(x):
n_individuos_en_celda = len(y)
cuenta[i][j] = n_individuos_en_celda
total += n_individuos_en_celda
saturacion = total / espacio.height*espacio.width
##Luego se muestra una representación
plt.figure(figsize = figsize)
plt.imshow(cuenta, vmin = 0, vmax = saturacion)
plt.colorbar()
plt.show()
if __name__=='__main__':
import networkx as nx
modelo = Model()
modelo.num_ind = 10
class Individuo(Agent):
def __init__(self, unique_id, model, edad, sexo):
super().__init__(unique_id, model)
self.model = model
self.edad = edad
self.sexo = sexo
ciudad = Ciudad(modelo, Individuo)
ciudad.generarindividuos()
#Se crean las casas distribuyendo los individuos
ciudad.crear_hogares()
#Se agrega una tienda a la ciudad y se conecta con todas las casas
ciudad.crear_nodo('aurrera', tipo='tienda', tamano=10)
def __init__(self, x, y, agent_type):
self.x = x
self.y = y
self.type = agent_type
def step(self, model):
neighbors = model.grid.get_neighbors(self.x, self.y, moore=True)
similar = 0
for neighbor in neighbors:
if neighbor.type == self.type:
similar += 1
# If unhappy, move:
if similar < model.homophily:
new_x, new_y = random.choice(mode.get_empty())
grid[self.y][self.x] = None
grid[new_y][new_x] = self
else:
model.happy += 1
if __name__ == "__main__":
model = Model(10, 10, 0.8, 0.2, 3)
while model.happy < model.model.schedule.get_agent_count():
model.go()
PMSM = random.uniform(.02,.05)
MSMandHIV = 0.001917
NotMSMandHIV = 0.001509
MSMacquire = 26200/(321039839*PMSM*(1-MSMandHIV/PMSM))
NotMSMacquire = 8800/(321039839*(1-PMSM))
PHIV=[MSMandHIV/PMSM,NotMSMandHIV/(1-PMSM)]
AcHIV=[MSMacquire/365,NotMSMacquire/365]
if ExcludeMSM:
Eligibility= .38/(1-PMSM)
else:
Eligibility= .38 + PMSM*(1-PHIV[0])
a=time.time()
Model = MoneyModel(agentnum)
print('Running Model')
for i in tqdm(range(365)):
Model.step()
data = Model.datacollector.get_model_vars_dataframe()
b=time.time()
print(str((b-a)/60)+' Minutes Elapsed')
Date= str(random.randint(1,9999999))
file_Name = Date+'HIVDetected'+'.pickle'
fileObject = open(file_Name,'wb')
pickle.dump([a.HIVDetected for a in Model.schedule.agents],fileObject, protocol=2)
fileObject.close()
file_Name = Date+'HIVDonations'+'.pickle'
fileObject = open(file_Name,'wb')
pickle.dump([a.HIVDonation for a in Model.schedule.agents],fileObject, protocol=2)
fileObject.close()
file_Name = Date+'HIV'+'.pickle'
def setUp(self):
self.original_games_path = os.path.abspath(
"../..") + "/res/originalGames/"
self.test_games = os.listdir(self.original_games_path)
self.model = Model()
self.maxDiff = None