class Simulation:
def __init__(self, nodes):
self.nodes = nodes
self.node_manager = NodeManager()
for node in self.nodes:
self.node_manager.add_node(node)
self.node_manager.update_node(node)
self.node_manager.commit(time.time())
self.steps = 0
def step(self, action):
self.steps += 1
for index, node in enumerate(self.nodes):
new_energy_value = node.update(action)
if (new_energy_value is not None):
self.node_manager.update_node(node)
self.node_manager.commit(time.time())
new_state = self.get_state()
reward = self.calculate_reward(new_state, action)
done = self.isDone()
return new_state, reward, done
def calculate_reward(self, energy_values, action):
nulls = energy_values.isnull().sum(axis=1).iloc[0]
# energy_too_low = self.get_state().mean(axis=1).iloc[0] < 1.8
for value in energy_values:
if energy_values[value].iloc[0] < 1.8:
return -100
if (nulls > 0):
reward = -100
elif (action is Action.CHARGE):
reward = -1
elif (action is Action.GATHER):
reward = 1
else:
reward = 0
return reward
def get_state(self):
return self.node_manager.get_most_recent_state().fillna(value=0)
def isDone(self):
energy_too_low = (self.get_state().mean(axis=1).iloc[0] < 1.8)
return energy_too_low or (self.steps > 10000)
# nodes = []
# nodes.append(Node(1, 5))
# nodes.append(Node(2, 5))
# nodes.append(Node(3, 5))
# sim = Simulation(nodes)
# actions = [Action.CHARGE, Action.GATHER, Action.GATHER]
# new_state, reward, done = sim.step(actions)