class TestSpaceNonToroidal(unittest.TestCase):
'''
Testing a toroidal continuous space.
'''
def setUp(self):
'''
Create a test space and populate with Mock Agents.
'''
self.space = ContinuousSpace(70, 20, False, -30, -30, 100, 100)
self.agents = []
for i, pos in enumerate(TEST_AGENTS):
a = MockAgent(i, None)
self.agents.append(a)
self.space.place_agent(a, pos)
def test_agent_positions(self):
'''
Ensure that the agents are all placed properly.
'''
for i, pos in enumerate(TEST_AGENTS):
a = self.agents[i]
assert a.pos == pos
def test_distance_calculations(self):
'''
Test toroidal distance calculations.
'''
pos_2 = (70, 20)
pos_3 = (-30, -20)
assert self.space.get_distance(pos_2, pos_3) == 107.70329614269008
def test_neighborhood_retrieval(self):
'''
Test neighborhood retrieval
'''
neighbors_1 = self.space.get_neighbors((-20, -20), 1)
assert len(neighbors_1) == 2
neighbors_2 = self.space.get_neighbors((40, -10), 10)
assert len(neighbors_2) == 0
neighbors_3 = self.space.get_neighbors((-30, -30), 10)
assert len(neighbors_3) == 0
def test_bounds(self):
'''
Test positions outside of boundary
'''
for i, pos in enumerate(OUTSIDE_POSITIONS):
a = MockAgent(len(self.agents) + i, None)
with self.assertRaises(Exception):
self.space.place_agent(a, pos)
a = self.agents[0]
for pos in OUTSIDE_POSITIONS:
assert self.space.out_of_bounds(pos)
with self.assertRaises(Exception):
self.space.move_agent(a, pos)
class TestSpaceToroidal(unittest.TestCase):
'''
Testing a toroidal continuous space.
'''
def setUp(self):
'''
Create a test space and populate with Mock Agents.
'''
self.space = ContinuousSpace(70, 20, True, -30, -30, 100, 100)
self.agents = []
for i, pos in enumerate(TEST_AGENTS):
a = MockAgent(i, None)
self.agents.append(a)
self.space.place_agent(a, pos)
def test_agent_positions(self):
'''
Ensure that the agents are all placed properly.
'''
for i, pos in enumerate(TEST_AGENTS):
a = self.agents[i]
assert a.pos == pos
def test_distance_calculations(self):
'''
Test toroidal distance calculations.
'''
pos_1 = (-30, -30)
pos_2 = (70, 20)
assert self.space.get_distance(pos_1, pos_2) == 0
pos_3 = (-30, -20)
assert self.space.get_distance(pos_1, pos_3) == 10
def test_neighborhood_retrieval(self):
'''
Test neighborhood retrieval
'''
neighbors_1 = self.space.get_neighbors((-20, -20), 1)
assert len(neighbors_1) == 2
neighbors_2 = self.space.get_neighbors((40, -10), 10)
assert len(neighbors_2) == 0
neighbors_3 = self.space.get_neighbors((-30, -30), 10)
assert len(neighbors_3) == 1
class TestSpaceToroidal(unittest.TestCase):
'''
Testing a toroidal continuous space.
'''
def setUp(self):
'''
Create a test space and populate with Mock Agents.
'''
self.space = ContinuousSpace(70, 20, True, -30, -30)
self.agents = []
for i, pos in enumerate(TEST_AGENTS):
a = MockAgent(i, None)
self.agents.append(a)
self.space.place_agent(a, pos)
def test_agent_positions(self):
'''
Ensure that the agents are all placed properly.
'''
for i, pos in enumerate(TEST_AGENTS):
a = self.agents[i]
assert a.pos == pos
def test_agent_matching(self):
'''
Ensure that the agents are all placed and indexed properly.
'''
for i, agent in self.space._index_to_agent.items():
assert agent.pos == tuple(self.space._agent_points[i, :])
assert i == self.space._agent_to_index[agent]
def test_distance_calculations(self):
'''
Test toroidal distance calculations.
'''
pos_1 = (-30, -30)
pos_2 = (70, 20)
assert self.space.get_distance(pos_1, pos_2) == 0
pos_3 = (-30, -20)
assert self.space.get_distance(pos_1, pos_3) == 10
pos_4 = (20, -5)
pos_5 = (20, -15)
assert self.space.get_distance(pos_4, pos_5) == 10
pos_6 = (-30, -29)
pos_7 = (21, -5)
assert self.space.get_distance(pos_6, pos_7) == np.sqrt(49**2 + 24**2)
def test_heading(self):
pos_1 = (-30, -30)
pos_2 = (70, 20)
self.assertEqual((0, 0), self.space.get_heading(pos_1, pos_2))
pos_1 = (65, -25)
pos_2 = (-25, -25)
self.assertEqual((10, 0), self.space.get_heading(pos_1, pos_2))
def test_neighborhood_retrieval(self):
'''
Test neighborhood retrieval
'''
neighbors_1 = self.space.get_neighbors((-20, -20), 1)
assert len(neighbors_1) == 2
neighbors_2 = self.space.get_neighbors((40, -10), 10)
assert len(neighbors_2) == 0
neighbors_3 = self.space.get_neighbors((-30, -30), 10)
assert len(neighbors_3) == 1
def test_bounds(self):
'''
Test positions outside of boundary
'''
boundary_agents = []
for i, pos in enumerate(OUTSIDE_POSITIONS):
a = MockAgent(len(self.agents) + i, None)
boundary_agents.append(a)
self.space.place_agent(a, pos)
for a, pos in zip(boundary_agents, OUTSIDE_POSITIONS):
adj_pos = self.space.torus_adj(pos)
assert a.pos == adj_pos
a = self.agents[0]
for pos in OUTSIDE_POSITIONS:
assert self.space.out_of_bounds(pos)
self.space.move_agent(a, pos)
class TestSpaceNonToroidal(unittest.TestCase):
"""
Testing a toroidal continuous space.
"""
def setUp(self):
"""
Create a test space and populate with Mock Agents.
"""
self.space = ContinuousSpace(70, 20, False, -30, -30)
self.agents = []
for i, pos in enumerate(TEST_AGENTS):
a = MockAgent(i, None)
self.agents.append(a)
self.space.place_agent(a, pos)
def test_agent_positions(self):
"""
Ensure that the agents are all placed properly.
"""
for i, pos in enumerate(TEST_AGENTS):
a = self.agents[i]
assert a.pos == pos
def test_agent_matching(self):
"""
Ensure that the agents are all placed and indexed properly.
"""
for i, agent in self.space._index_to_agent.items():
assert agent.pos == tuple(self.space._agent_points[i, :])
assert i == self.space._agent_to_index[agent]
def test_distance_calculations(self):
"""
Test toroidal distance calculations.
"""
pos_2 = (70, 20)
pos_3 = (-30, -20)
assert self.space.get_distance(pos_2, pos_3) == 107.70329614269008
def test_heading(self):
pos_1 = (-30, -30)
pos_2 = (70, 20)
self.assertEqual((100, 50), self.space.get_heading(pos_1, pos_2))
pos_1 = (65, -25)
pos_2 = (-25, -25)
self.assertEqual((-90, 0), self.space.get_heading(pos_1, pos_2))
def test_neighborhood_retrieval(self):
"""
Test neighborhood retrieval
"""
neighbors_1 = self.space.get_neighbors((-20, -20), 1)
assert len(neighbors_1) == 2
neighbors_2 = self.space.get_neighbors((40, -10), 10)
assert len(neighbors_2) == 0
neighbors_3 = self.space.get_neighbors((-30, -30), 10)
assert len(neighbors_3) == 0
def test_bounds(self):
"""
Test positions outside of boundary
"""
for i, pos in enumerate(OUTSIDE_POSITIONS):
a = MockAgent(len(self.agents) + i, None)
with self.assertRaises(Exception):
self.space.place_agent(a, pos)
a = self.agents[0]
for pos in OUTSIDE_POSITIONS:
assert self.space.out_of_bounds(pos)
with self.assertRaises(Exception):
self.space.move_agent(a, pos)
class Covid(Model):
'''
Covid model class. Handles agent creation, placement and scheduling.
'''
def __init__(self,
population=100,
width=100,
height=100,
mobility=6,
social_distance=2,
asymptomatic_percentage=50.0):
'''
Create a new Covid model.
Args:
population: Number of people (density) with one asymptomatic infected person.
asymptomatic_percentage: Percentage of infected people that are asymptomatic. Asymptomatic people transmit the virus for 42 time steps versus 15 time steps for those that are symptomatic.
social_distance: Distance at which neighboring susceptible agents can b ecome infected.
mobility: The maximum distance that an agent can travel.
'''
self.current_id = 0
self.population = population
self.mobility = mobility
self.social_distance = social_distance
self.asymptomatic_percentage = asymptomatic_percentage
self.state = "home"
self.schedule = RandomActivation(self)
self.space = ContinuousSpace(width, height, False)
self.image = Image.open(r"nmcounties.jpg")
self.num = {
'San Juan': 0,
'Rio Arriba': 0,
'Taos': 0,
'Colfax': 0,
'Union': 0,
'Los Alamos': 0,
'Mora': 0,
'Harding': 0,
'McKinley': 0,
'Sandoval': 0,
'Santa Fe': 0,
'San Miguel': 0,
'Quay': 0,
'Cibola': 0,
'Valencia': 0,
'Bernalillo': 0,
'Torrance': 0,
'Guadalupe': 0,
'Curry': 0,
'Catron': 0,
'Socorro': 0,
'Lincoln': 0,
'De Baca': 0,
'Roosevelt': 0,
'Sierra': 0,
'Chaves': 0,
'Hidalgo': 0,
'Grant': 0,
'Luna': 0,
'Doña Ana': 0,
'Otero': 0,
'Eddy': 0,
'Lea': 0,
}
self.pop = {
'San Juan': 0,
'Rio Arriba': 0,
'Taos': 0,
'Colfax': 0,
'Union': 0,
'Los Alamos': 0,
'Mora': 0,
'Harding': 0,
'McKinley': 0,
'Sandoval': 0,
'Santa Fe': 0,
'San Miguel': 0,
'Quay': 0,
'Cibola': 0,
'Valencia': 0,
'Bernalillo': 0,
'Torrance': 0,
'Guadalupe': 0,
'Curry': 0,
'Catron': 0,
'Socorro': 0,
'Lincoln': 0,
'De Baca': 0,
'Roosevelt': 0,
'Sierra': 0,
'Chaves': 0,
'Hidalgo': 0,
'Grant': 0,
'Luna': 0,
'Doña Ana': 0,
'Otero': 0,
'Eddy': 0,
'Lea': 0,
}
with open('counties.csv') as csvfile:
reader = csv.reader(csvfile, delimiter=',', quotechar='"')
for row in reader:
county = row[2].replace(' County', '')
if (county != '' and county != 'County'):
population = row[3].replace(',', '')
self.pop[county] = population
total = 0
for value in self.pop.values():
total += int(value)
for county, value in self.pop.items():
self.pop[county] = round(
int(self.population) * int(value) / int(total))
total = 0
for value in self.pop.values():
total += int(value)
if (self.population != total):
self.pop['Bernalillo'] += self.population - total
self.make_agents()
self.running = True
self.datacollector = DataCollector({
"Susceptible":
lambda m: self.count("Susceptible"),
"Infected":
lambda m: self.count("Infected"),
"Recovered":
lambda m: self.count("Recovered")
})
def counties(self, pixel):
if (pixel == (87, 127, 77)):
return 'San Juan'
elif (pixel == (168, 144, 178)):
return 'Rio Arriba'
elif (pixel == (131, 141, 91)):
return 'Taos'
elif (pixel == (189, 204, 119)):
return 'Colfax'
elif (pixel == (197, 112, 58)):
return 'Union'
elif (pixel == (211, 165, 80)):
return 'Los Alamos'
elif (pixel == (186, 81, 52)):
return 'Mora'
elif (pixel == (106, 97, 126)):
return 'Harding'
elif (pixel == (91, 124, 143)):
return 'McKinley'
elif (pixel == (92, 59, 40)):
return 'Sandoval'
elif (pixel == (75, 113, 116)):
return 'Santa Fe'
elif (pixel == (109, 103, 53)):
return 'San Miguel'
elif (pixel == (49, 73, 73)):
return 'Quay'
elif (pixel == (178, 62, 49)):
return 'Cibola'
elif (pixel == (138, 99, 84)):
return 'Valencia'
elif (pixel == (137, 184, 214)):
return 'Bernalillo'
elif (pixel == (106, 106, 104)):
return 'Torrance'
elif (pixel == (146, 117, 87)):
return 'Guadalupe'
elif (pixel == (156, 150, 88)):
return 'Curry'
elif (pixel == (67, 94, 149)):
return 'Catron'
elif (pixel == (55, 80, 50)):
return 'Socorro'
elif (pixel == (145, 186, 178)):
return 'Lincoln'
elif (pixel == (82, 33, 37)):
return 'De Baca'
elif (pixel == (195, 189, 189)):
return 'Roosevelt'
elif (pixel == (238, 219, 99)):
return 'Sierra'
elif (pixel == (243, 234, 129)):
return 'Chaves'
elif (pixel == (41, 30, 60)):
return 'Hidalgo'
elif (pixel == (116, 140, 106)):
return 'Grant'
elif (pixel == (11, 10, 8)):
return 'Luna'
elif (pixel == (157, 56, 74)):
return 'Doña Ana'
elif (pixel == (52, 53, 48)):
return 'Otero'
elif (pixel == (207, 144, 135)):
return 'Eddy'
elif (pixel == (138, 171, 80)):
return 'Lea'
else:
return ''
def make_agents(self):
'''
Create self.population agents, with random positions and starting headings.
'''
for i in range(self.population):
pos = self.inside()
person = Susceptible(self.next_id(), self, pos)
self.space.place_agent(person, pos)
self.schedule.add(person)
agent_key = random.randint(0, self.population - 1)
agent = self.schedule._agents[agent_key]
asymptomatic = True
person = Infected(self.next_id(), self, agent.pos, True)
person.set_imperial(agent.home, agent.work, agent.travel)
self.space.remove_agent(agent)
self.schedule.remove(agent)
self.space.place_agent(person, person.pos)
self.schedule.add(person)
def inside(self):
while (1):
x = self.random.random() * self.space.x_max
y = self.random.random() * self.space.y_max
if (y > 10.0 and y < self.space.y_max - 10.0 and x > 10.0
and x < self.space.x_max - 10.0):
coordinate = x, y
pixel = self.image.getpixel(coordinate)
if (pixel != (255, 255, 255)):
county = self.counties(pixel)
if (county != ''):
if (self.num[county] < self.pop[county]):
self.num[county] += 1
return np.array((x, y))
def step(self):
self.infect()
if self.state == "home":
self.state = "work"
elif self.state == "work":
self.state = "community"
elif self.state == "community":
self.state = "home"
self.schedule.step()
# collect data
self.datacollector.collect(self)
if self.count("Infected") == 0:
self.running = False
def infect(self):
agent_keys = list(self.schedule._agents.keys())
susceptible = []
for agent_key in agent_keys:
if self.schedule._agents[agent_key].name == "Susceptible":
susceptible.append(agent_key)
for agent_key in susceptible:
agent = self.schedule._agents[agent_key]
neighbors = self.space.get_neighbors(agent.pos,
self.social_distance)
for neighbor in neighbors:
if neighbor.name == "Infected":
asymptomatic = False
if (100.0 * self.random.random() <
self.asymptomatic_percentage):
asymptomatic = True
person = Infected(self.next_id(), self, agent.pos,
asymptomatic)
person.set_imperial(agent.home, agent.work, agent.travel)
self.space.remove_agent(agent)
self.schedule.remove(agent)
self.space.place_agent(person, person.pos)
self.schedule.add(person)
break
def count(self, type):
agent_keys = list(self.schedule._agents.keys())
num = 0
for agent_key in agent_keys:
if self.schedule._agents[agent_key].name == type:
num += 1
return num
class PredatorPreyModel(Model):
def __init__(self,
height=100,
width=100,
init_prey=100,
prey_reproduction=0.03,
init_predator=10,
predator_vision=1,
predator_reproduction=0.5,
predator_death=0.02,
local_offspring=False,
max_iters=500,
seed=None):
super().__init__()
self.height = height
self.width = width
self.init_prey = init_prey
self.prey_reproduction = prey_reproduction
self.init_predator = init_predator
self.predator_vision = predator_vision
self.predator_reproduction = predator_reproduction
self.predator_death = predator_death
self.local_offspring = local_offspring
self.iteration = 0
self.max_iters = max_iters
self.schedule = RandomActivation(self)
self.space = ContinuousSpace(height, width, torus=True)
model_reporters = {
'Prey': lambda model: self.count('Prey'),
'Predator': lambda model: self.count('Predator'),
}
self.datacollector = DataCollector(model_reporters=model_reporters)
# Place prey
for i in range(self.init_prey):
x = self.random.uniform(0, self.width)
y = self.random.uniform(0, self.height)
# next_id() starts at 1
prey = Prey(self.next_id(), self, (x, y), self.prey_reproduction)
self.space.place_agent(prey, (x, y))
self.schedule.add(prey)
# Place predators
for i in range(self.init_predator):
x = self.random.uniform(0, self.width)
y = self.random.uniform(0, self.height)
predator = Predator(self.next_id(), self, (x, y),
self.predator_reproduction,
self.predator_death, self.predator_vision)
self.space.place_agent(predator, (x, y))
self.schedule.add(predator)
self.running = True
self.datacollector.collect(self)
def step(self):
"""
Advance the model by one step and collect data.
Returns
-------
None.
"""
self.schedule.step()
self.iteration += 1
self.datacollector.collect(self)
# Stop system if maximum of iterations is reached
if self.iteration > self.max_iters:
self.running = False
return None
def count(self, breed):
"""
Count agent by breed.
Parameters
----------
breed : string
Breed of agent Can be 'Prey' or 'Predator'.
Returns
-------
count : int
Number of agents of type breed.
"""
count = 0
for agent in self.schedule.agents:
if agent.breed == breed:
count += 1
if breed == 'Predator' and count == 0:
self.running = False
return count
def warm_up(self):
for agent in self.schedule.agents:
if agent.breed == 'Prey':
continue
neighbors = self.space.get_neighbors(agent.pos,
radius=agent.vision)
for prey in neighbors:
if prey.breed == 'Prey':
x = self.random.uniform(0, self.width)
y = self.random.uniform(0, self.height)
self.space.move_agent(prey, (x, y))
class BoidFlockers(Model):
"""
Flocker model class. Handles agent creation, placement and scheduling.
"""
def __init__(
self,
population=100,
width=100,
height=100,
speed=1,
vision=10,
separation=2,
rate = 10,
size_factor = 2,
sim_length = 1200,
angle_min = -180,
angle_max = 180):
"""
Create a new Flockers model.
Args:
width, height: Size of the space.
speed: How fast should the Boids move.
vision: How far around should each Boid look for its neighbors
separation: What's the minimum distance each Boid will attempt to
keep from any other
"""
self.population = population
self.unique_id = 1
self.vision = vision
self.speed = speed
self.separation = separation
self.schedule = RandomActivation(self)
self.space = ContinuousSpace(width, height, False)
self.size_factor = size_factor
self.angle_min = angle_min
self.angle_max = angle_max
self.running = True
self.rate = rate
self.kill_agents = []
self.queue = []
self.input_rate = 0
self.num_agents = 0
self.arrival = 0
self.departure = 0
self.n_confs = 0
self.n_intrusion = 0
self.dep_del = 0
self.enroute_del = 0
self.tot_del = self.dep_del + self.enroute_del
self.sim_length = sim_length
self.datacollector = DataCollector(
model_reporters= {"Occupancy": compute_N,
"Total flow": compute_flow,
"Effective flow": compute_eff_flow,
"Inpute rate": compute_inp,
"Output rate": compute_out,
'Effective speed': compute_eff_speed ,
'Speed': compute_speed,
'Queue length': compute_queue_len,
'size':'size_factor',
'inp_rate':'rate',
'vision':'vision',
'def_speed':'speed',
'sep':'separation',
'Departure Delay':'dep_del',
'Enroute Delay': 'enroute_del',
'Total Delay': 'tot_del',
'N Conflicts': 'n_confs',
'N Intrusions': 'n_intrusion',
'N Arrivals': 'arrival',
'N Departures': 'departure'
},
agent_reporters = {'id':'unique_id',
'prev_dist':'previos_distance',
'cur_dist':'current_distance',
'phys_speed':'physic_speed',
'vision':'vision',
'def_speed':'speed',
'sep':'separation',
'x': lambda x: x.pos[0],
'y': lambda x: x.pos[1]}
)
def make_od(self):
x = self.space.x_max/2 + np.random.uniform(-1,1)\
* self.space.x_max/2/self.size_factor
y = self.space.y_max/2 + np.random.uniform(-1,1)\
* self.space.y_max/2/self.size_factor
pos = np.array((x, y))
x_dest = self.space.x_max/2 + np.random.uniform(-1,1) \
* self.space.x_max/2/self.size_factor
y_dest = self.space.y_max/2 + np.random.uniform(-1,1) \
* self.space.y_max/2/self.size_factor
dest = np.array((x_dest, y_dest))
return pos,dest
def make_od2(self):
valid = False
while valid == False:
x = self.space.x_max/2 + np.random.uniform(-1,1)\
* self.space.x_max/2/self.size_factor
y = self.space.y_max/2 + np.random.uniform(-1,1)\
* self.space.y_max/2/self.size_factor
pos = np.array((x, y))
x_dest = self.space.x_max/2 + np.random.uniform(-1,1) \
* self.space.x_max/2/self.size_factor
y_dest = self.space.y_max/2 + np.random.uniform(-1,1) \
* self.space.y_max/2/self.size_factor
dest = np.array((x_dest, y_dest))
vector = (dest - pos)/np.linalg.norm((dest - pos))
angle = np.arctan2(vector[0],vector[1]) * 180 / np.pi
if angle >= self.angle_min and angle <= self.angle_max:
valid =True
else: continue
return pos, dest
def make_agents(self, od, init_time):
pos = od[0]
dest = od[1]
velocity = np.random.random(2) * 2 - 1
boid = Boid(
unique_id=self.unique_id,
model=self,
pos=pos,
speed = self.speed,
velocity=velocity,
destination = dest,
vision=self.vision,
separation=self.separation,
init_time = init_time
)
return boid
def place_boid(self, boid):
self.space.place_agent(boid, boid.pos)
self.schedule.add(boid)
def agent_maker(self):
per_step = self.rate/60
fractional = per_step % 1
integer = int(per_step - round(fractional))
num_frac = np.random.binomial(size=1, n=1, p= fractional)
self.input_rate = int(integer+num_frac)
#create agents
for i in range(self.input_rate):
od = self.make_od2()
agent = self.make_agents(od, init_time = self.schedule.time)
agent.od_dist = agent.distance()
self.unique_id += 1
if self.num_agents >= 1:
neighbors = self.space.get_neighbors(od[0], self.separation, False)
if len(neighbors) == 0:
agent.entry_time = self.schedule.time
self.place_boid(agent)
self.arrival += 1
self.num_agents += 1
#print('first attempt!')
else:
self.queue.append(agent)
if self.num_agents == 0:
agent.entry_time = self.schedule.time
self.place_boid(agent)
self.arrival += 1
self.num_agents += 1
def queue_clearer(self, time):
for index, agent in enumerate(self.queue):
od = agent.pos
# print(od)
neighbors = self.space.get_neighbors(od[0], self.separation, False)
if len(neighbors) == 0:
agent.entry_time = time
# agent.dep_del = max(agent.entry_time - agent.init_time,0)
# print('second attempt!',agent.unique_id,agent.init_time, agent.entry_time, agent.dep_del)
self.dep_del += agent.entry_time - agent.init_time
self.place_boid(agent)
self.arrival += 1
self.num_agents += 1
del self.queue[index]
else:
pass
def step(self):
"""
Create agents here
"""
#collect data
# try:
self.n_confs = 0
self.n_intrusion = 0
#compute input rate for step
if self.schedule.time <self.sim_length:
self.agent_maker()
else: pass
self.queue_clearer(time= self.schedule.time)
self.kill_agents = []
#make 1 step
self.schedule.step()
#remove agents that arrived at their destinations
self.departure += len(self.kill_agents)
for i in self.kill_agents:
self.enroute_del += i.enroute_del
self.schedule.remove(i)
self.num_agents -= 1
self.space.remove_agent(i)
try:
self.datacollector.collect(self)
except:
pass
class Covid(Model):
'''
Covid model class. Handles agent creation, placement and scheduling.
'''
def __init__(self,
population=100,
width=100,
height=100,
mobility=6,
social_distance=2,
asymptomatic_percentage=50.0,
imperial=True):
'''
Create a new Covid model.
Args:
population: Number of people (density) with one asymptomatic infected person.
imperial: Agent rotates between home, work and community. For home the agent returns to a random point near a fixed home position. Community has the agent randomly placed in the space. Work has 90% like home but with a fixed work position and 10% random like community. This is patterned after the Imperial College model. Turning off imperial iterates with each agent traveling a random direction and distance from the current position.
asymptomatic_percentage: Percentage of infected people that are asymptomatic. Asymptomatic people transmit the virus for 42 time steps versus 15 time steps for those that are symptomatic.
social_distance: Distance at which neighboring susceptible agents can b ecome infected.
mobility: The maximum distance that an agent can travel.
'''
self.current_id = 0
self.population = population
self.mobility = mobility
self.social_distance = social_distance
self.asymptomatic_percentage = asymptomatic_percentage
self.imperial = imperial
if imperial:
self.state = "home"
else:
self.state = "diffusion"
self.schedule = RandomActivation(self)
self.space = ContinuousSpace(width, height, True)
self.make_agents()
self.running = True
self.datacollector = DataCollector({
"Susceptible":
lambda m: self.count("Susceptible"),
"Infected":
lambda m: self.count("Infected"),
"Recovered":
lambda m: self.count("Recovered")
})
def make_agents(self):
'''
Create self.population agents, with random positions and starting headings.
'''
for i in range(0, 1):
x = self.random.random() * self.space.x_max
y = self.random.random() * self.space.y_max
pos = np.array((x, y))
asymptomatic = True
person = Infected(self.next_id(), self, pos, asymptomatic)
self.space.place_agent(person, pos)
self.schedule.add(person)
for i in range(self.population - 1):
x = self.random.random() * self.space.x_max
y = self.random.random() * self.space.y_max
pos = np.array((x, y))
person = Susceptible(self.next_id(), self, pos)
self.space.place_agent(person, pos)
self.schedule.add(person)
def step(self):
self.infect()
if self.state == "home":
self.state = "work"
elif self.state == "work":
self.state = "community"
elif self.state == "community":
self.state = "home"
self.schedule.step()
# collect data
self.datacollector.collect(self)
if self.count("Infected") == 0:
self.running = False
def infect(self):
agent_keys = list(self.schedule._agents.keys())
susceptible = []
for agent_key in agent_keys:
if self.schedule._agents[agent_key].name == "Susceptible":
susceptible.append(agent_key)
for agent_key in susceptible:
agent = self.schedule._agents[agent_key]
neighbors = self.space.get_neighbors(agent.pos,
self.social_distance)
for neighbor in neighbors:
if neighbor.name == "Infected":
asymptomatic = False
if (100.0 * self.random.random() <
self.asymptomatic_percentage):
asymptomatic = True
person = Infected(self.next_id(), self, agent.pos,
asymptomatic)
if self.imperial:
person.set_imperial(agent.home, agent.work,
agent.travel)
self.space.remove_agent(agent)
self.schedule.remove(agent)
self.space.place_agent(person, person.pos)
self.schedule.add(person)
break
def count(self, type):
agent_keys = list(self.schedule._agents.keys())
num = 0
for agent_key in agent_keys:
if self.schedule._agents[agent_key].name == type:
num += 1
return num
class TestSpaceToroidal(unittest.TestCase):
'''
Testing a toroidal continuous space.
'''
def setUp(self):
'''
Create a test space and populate with Mock Agents.
'''
self.space = ContinuousSpace(70, 20, True, -30, -30, 100, 100)
self.agents = []
for i, pos in enumerate(TEST_AGENTS):
a = MockAgent(i, None)
self.agents.append(a)
self.space.place_agent(a, pos)
def test_agent_positions(self):
'''
Ensure that the agents are all placed properly.
'''
for i, pos in enumerate(TEST_AGENTS):
a = self.agents[i]
assert a.pos == pos
def test_distance_calculations(self):
'''
Test toroidal distance calculations.
'''
pos_1 = (-30, -30)
pos_2 = (70, 20)
assert self.space.get_distance(pos_1, pos_2) == 0
pos_3 = (-30, -20)
assert self.space.get_distance(pos_1, pos_3) == 10
def test_heading(self):
pos_1 = (-30, -30)
pos_2 = (70, 20)
self.assertEqual((0, 0), self.space.get_heading(pos_1, pos_2))
pos_1 = (65, -25)
pos_2 = (-25, -25)
self.assertEqual((10, 0), self.space.get_heading(pos_1, pos_2))
def test_neighborhood_retrieval(self):
'''
Test neighborhood retrieval
'''
neighbors_1 = self.space.get_neighbors((-20, -20), 1)
assert len(neighbors_1) == 2
neighbors_2 = self.space.get_neighbors((40, -10), 10)
assert len(neighbors_2) == 0
neighbors_3 = self.space.get_neighbors((-30, -30), 10)
assert len(neighbors_3) == 1
def test_bounds(self):
'''
Test positions outside of boundary
'''
boundary_agents = []
for i, pos in enumerate(OUTSIDE_POSITIONS):
a = MockAgent(len(self.agents) + i, None)
boundary_agents.append(a)
self.space.place_agent(a, pos)
for a, pos in zip(boundary_agents, OUTSIDE_POSITIONS):
adj_pos = self.space.torus_adj(pos)
assert a.pos == adj_pos
a = self.agents[0]
for pos in OUTSIDE_POSITIONS:
assert self.space.out_of_bounds(pos)
self.space.move_agent(a, pos)
class TestSpaceNonToroidal(unittest.TestCase):
'''
Testing a toroidal continuous space.
'''
def setUp(self):
'''
Create a test space and populate with Mock Agents.
'''
self.space = ContinuousSpace(70, 20, False, -30, -30)
self.agents = []
for i, pos in enumerate(TEST_AGENTS):
a = MockAgent(i, None)
self.agents.append(a)
self.space.place_agent(a, pos)
def test_agent_positions(self):
'''
Ensure that the agents are all placed properly.
'''
for i, pos in enumerate(TEST_AGENTS):
a = self.agents[i]
assert a.pos == pos
def test_agent_matching(self):
'''
Ensure that the agents are all placed and indexed properly.
'''
for i, agent in self.space._index_to_agent.items():
assert agent.pos == tuple(self.space._agent_points[i, :])
assert i == self.space._agent_to_index[agent]
def test_distance_calculations(self):
'''
Test toroidal distance calculations.
'''
pos_2 = (70, 20)
pos_3 = (-30, -20)
assert self.space.get_distance(pos_2, pos_3) == 107.70329614269008
def test_heading(self):
pos_1 = (-30, -30)
pos_2 = (70, 20)
self.assertEqual((100, 50), self.space.get_heading(pos_1, pos_2))
pos_1 = (65, -25)
pos_2 = (-25, -25)
self.assertEqual((-90, 0), self.space.get_heading(pos_1, pos_2))
def test_neighborhood_retrieval(self):
'''
Test neighborhood retrieval
'''
neighbors_1 = self.space.get_neighbors((-20, -20), 1)
assert len(neighbors_1) == 2
neighbors_2 = self.space.get_neighbors((40, -10), 10)
assert len(neighbors_2) == 0
neighbors_3 = self.space.get_neighbors((-30, -30), 10)
assert len(neighbors_3) == 0
def test_bounds(self):
'''
Test positions outside of boundary
'''
for i, pos in enumerate(OUTSIDE_POSITIONS):
a = MockAgent(len(self.agents) + i, None)
with self.assertRaises(Exception):
self.space.place_agent(a, pos)
a = self.agents[0]
for pos in OUTSIDE_POSITIONS:
assert self.space.out_of_bounds(pos)
with self.assertRaises(Exception):
self.space.move_agent(a, pos)
