def __init__(self):
super().__init__()
self.end_condition = end_condition
self.trackers["agent_count"] = analysis.AgentTypeCountTracker()
io_file_name = "bacteria_intelligent.qlearning.pkl"
self.bacteria_decision = decision.QLearningDecision(
perception=bacteria_perception,
loss=bacteria_loss,
simulation=self,
input_file_name=io_file_name,
output_file_name=io_file_name,
nonconformity_probability=0)
self.trackers["qlearning"] = analysis.QLearningHistoryTracker(
self.bacteria_decision)
# create bacteria agents
for i in range(5):
for j in range(5):
self.agents.add(
Bacteria(np.array([10 * i, 10 * j], dtype=np.float),
self.bacteria_decision))
# create yogurt agents
for i in range(20):
for j in range(20):
self.agents.add(
Yogurt(np.array([5 * i, 5 * j + 50], dtype=np.float)))
def test_exponential_agent_type_count():
from adjsim import core, analysis, decision
from matplotlib import pyplot
def increment_agents(env, source):
env.agents.add(TestAgent())
class TestAgent(core.Agent):
def __init__(self):
super().__init__()
self.actions["increment"] = increment_agents
self.decision = decision.RandomSingleCastDecision()
test_sim = core.Simulation()
test_sim.agents.add(TestAgent())
test_sim.trackers["count"] = analysis.AgentTypeCountTracker()
common.step_simulate_interpolation(test_sim)
assert test_sim.trackers["count"].data[TestAgent] == [
2**i for i in range(common.INTERPOLATION_NUM_TIMESTEP + 1)
]
test_sim.trackers["count"].plot(block=False)
pyplot.close()
def __init__(self):
super().__init__()
self.end_condition = end_condition
self.trackers["agent_count"] = analysis.AgentTypeCountTracker()
self.bacteria_decision = decision.RandomRepeatedCastDecision()
# create bacteria agents
for i in range(5):
for j in range(5):
self.agents.add(
Bacteria(np.array([10 * i, 10 * j], dtype=np.float),
self.bacteria_decision))
# create yogurt agents
for i in range(20):
for j in range(20):
self.agents.add(
Yogurt(np.array([5 * i, 5 * j + 50], dtype=np.float)))
def test_agent_add():
from adjsim import core, analysis, decision
def addition_callback(agent):
addition_callback.count += 1
addition_callback.count = 0
def increment_agents(env, source):
env.agents.add(TestAgent())
class TestAgent(core.Agent):
def __init__(self):
super().__init__()
self.actions["increment"] = increment_agents
self.decision = decision.RandomSingleCastDecision()
test_sim = core.Simulation()
test_sim.callbacks.agent_added.register(addition_callback)
test_sim.agents.add(TestAgent())
test_sim.trackers["count"] = analysis.AgentTypeCountTracker()
common.step_simulate_interpolation(test_sim)
assert addition_callback.count == 2**common.INTERPOLATION_NUM_TIMESTEP