def test_zero_q_function_should_return_vector(self):
# Given
q_function = ZeroQFunction()
state = State([])
two_actions = Actions("Do Nothing", "Do Something")
three_actions = Actions("Do Nothing", "Do Something",
"Do Something else")
# When
two_q_values = q_function.evaluate(state, two_actions)
three_q_values = q_function.evaluate(state, three_actions)
# Check
assert len(two_q_values) == 2
assert len(three_q_values) == 3
def test_Actions_should_supports_indexing(self):
# Given
actions = Actions("Hello", "World")
# Check
assert actions[0] == "Hello"
assert actions[1] == "World"
def test_agent_should_return_decision(self):
# Given
agent = Agent()
# When
actions = Actions("do nothing")
decision = agent.choose_best_action(actions)
# Assert
assert decision == "do nothing"
def test_empty_action_set_should_be_empty(self):
# Given
actions = Actions()
# Check
assert actions.is_empty()
def test_non_empty_action_set_shouldnt_be_empty(self):
# Given
actions = Actions("Hello")
# Check
assert not actions.is_empty()
def state_to_actions(state):
_, speed = state
if speed > 0:
return Actions(*[0.1 * i for i in range(11)])
else:
return Actions()
def state_to_empty_actions(state):
return Actions()