def __init__(self, params, observer):
self.rng = np.random.RandomState(params.seed)
self.area_width = params.area_size[0]
self.area_height = params.area_size[1]
env = dworp.NullEnvironment()
time = dworp.BasicTime(params.steps)
scheduler = dworp.BasicScheduler()
self.space = Space2d(self.area_width, self.area_height)
boids = [self.create_boid(params) for x in range(params.pop)]
for boid in boids:
self.space.add(boid, boid.point)
super().__init__(boids, env, time, scheduler, observer)
def __init__(self, params, observer):
self.rng = np.random.RandomState(params.seed)
env = SugarscapeEnvironment(self.rng)
# construct our agents
agents = [self.create_agent() for _ in range(params.pop)]
# assign them locations & add them to the environment
for agent in agents:
empty_locations = env.empty_locations()
# note: can't just do self.rng.choice(empty_locations), because numpy thinks a list of tuples is
# multi-dimensional, and rng.choice only works with 1-d arrays.
env.move(
agent,
empty_locations[self.rng.choice(range(len(empty_locations)))])
super().__init__(agents, env, dworp.InfiniteTime(),
dworp.BasicScheduler(), observer,
SugarscapeTerminator())
def __init__(self, params, observer):
self.params = params
self.rng = np.random.RandomState(params.seed)
time = dworp.InfiniteTime()
scheduler = dworp.BasicScheduler()
terminator = BirthTerminator()
# start out with an equal number of red and blue people
num_people = params.capacity // 2
red = [
Person('red', params.red_fertility, self.rng)
for x in range(num_people)
]
blue = [
Person('blue', params.blue_fertility, self.rng)
for x in range(num_people)
]
people = red + blue
env = BirthEnvironment({'red': len(red), 'blue': len(blue)})
super().__init__(people, env, time, scheduler, observer, terminator)
self.state.fill(0)
def step(self, new_time, agents):
self.state[self.TEMP] = np.random.randint(self.MIN_TEMP, self.MAX_TEMP)
self.logger.info("Temperature is now {}".format(self.state[self.TEMP]))
@property
def temp(self):
return self.state[self.TEMP]
class ShortsObserver(dworp.Observer):
def step(self, time, agents, env):
count = sum([agent.wearing_shorts for agent in agents])
print("{}: Temp {} - Shorts {}".format(time, env.temp, count))
def done(self, agents, env):
print("Simulation over")
logging.basicConfig(level=logging.WARN)
g = igraph.Graph.Erdos_Renyi(n=100, p=0.05, directed=False)
agents = [CollegeStudent(v) for v in g.vs]
env = WeatherEnvironment(g)
time = dworp.BasicTime(10)
scheduler = dworp.BasicScheduler()
observer = ShortsObserver()
sim = dworp.TwoStageSimulation(agents, env, time, scheduler, observer)
sim.run()