class ClassifierController(Controller):
NAME = "Classifier Controller"
def __init__(self, pendulum_length, pendulum_mass, cart_mass):
Controller.__init__(self, pendulum_length, pendulum_mass, cart_mass)
self.decisionTree = tree.DecisionTreeClassifier()
self.dataset_generator = DatasetGenerator(pendulum_mass, cart_mass,
pendulum_length)
def learn(self, number):
dataset = self.dataset_generator.generateRandomDataset(number)
self.decisionTree = self.decisionTree.fit(dataset.data, dataset.target)
with open("test.dot", 'w') as f:
f = tree.export_graphviz(self.decisionTree, out_file=f)
def calculate_force(self, angular_position, angular_velocity,
cart_position, cart_velocity):
force = self.decisionTree.predict(
[angular_position, angular_velocity, cart_position,
cart_velocity])[0]
return force
def __init__(self, pendulum_length, pendulum_mass, cart_mass):
Controller.__init__(self, pendulum_length, pendulum_mass, cart_mass)
self.decisionTree = tree.DecisionTreeClassifier()
self.dataset_generator = DatasetGenerator(pendulum_mass, cart_mass,
pendulum_length)
