def test_agent_n_dimensions_setter():
try:
new_agent = agent.Agent(n_variables=5, n_dimensions=0.0)
except:
new_agent = agent.Agent(n_variables=5, n_dimensions=4)
try:
new_agent = agent.Agent(n_variables=5, n_dimensions=0)
except:
new_agent = agent.Agent(n_variables=5, n_dimensions=4)
assert new_agent.n_dimensions == 4
def test_agent_n_dimensions_setter():
try:
new_agent = agent.Agent(1, 0.0, 0, 1)
except:
new_agent = agent.Agent(1, 1, 0, 1)
try:
new_agent = agent.Agent(1, 0, 0, 1)
except:
new_agent = agent.Agent(1, 1, 0, 1)
assert new_agent.n_dimensions == 1
def test_agent_n_variables_setter():
try:
new_agent = agent.Agent(0.0, 1, 0, 1)
except:
new_agent = agent.Agent(1, 1, 0, 1)
try:
new_agent = agent.Agent(0, 4, 0, 1)
except:
new_agent = agent.Agent(1, 1, 0, 1)
assert new_agent.n_variables == 1
def test_agent_fill_with_uniform():
new_agent = agent.Agent(1, 1, 0, 1)
new_agent.fill_with_uniform()
assert new_agent.position[0] >= 0
assert new_agent.position[0] <= 1
def test_agent_lb_setter():
new_agent = agent.Agent(n_variables=5, n_dimensions=4)
try:
new_agent.lb = [1]
except:
new_agent.lb = np.array([1])
assert new_agent.lb[0] == 1
def test_agent_fit_setter():
new_agent = agent.Agent(n_variables=5, n_dimensions=4)
try:
new_agent.fit = np.array([0])
except:
new_agent.fit = 0
assert new_agent.fit == 0
def test_agent_position_setter():
new_agent = agent.Agent(n_variables=1, n_dimensions=1)
try:
new_agent.position = 10
except:
new_agent.position = np.array([10])
assert new_agent.position[0] == 10
def test_agent_fit_setter():
new_agent = agent.Agent(1, 1, 0, 1)
try:
new_agent.fit = np.array([0])
except:
new_agent.fit = 0
assert new_agent.fit == 0
def test_agent_fill_with_static():
new_agent = agent.Agent(1, 1, 0, 1)
try:
new_agent.fill_with_static([20, 20])
except:
new_agent.fill_with_static(20)
assert new_agent.position[0] == 20
def test_agent_ts_setter():
new_agent = agent.Agent(1, 1, 0, 1)
try:
new_agent.ts = np.array([0])
except:
new_agent.ts = 0
assert new_agent.ts == 0
def test_agent_position_setter():
new_agent = agent.Agent(1, 1, 0, 1)
try:
new_agent.position = 10
except:
new_agent.position = np.array([10])
assert new_agent.position[0] == 10
def test_space_best_agent_setter():
new_space = space.Space()
try:
new_space.best_agent = None
except:
new_space.best_agent = agent.Agent(1, 1, 0, 1)
assert isinstance(new_space.best_agent, agent.Agent)
def test_agent_clip_limits():
new_agent = agent.Agent(n_variables=1, n_dimensions=1)
new_agent.lb = np.array([10])
new_agent.ub = np.array([10])
new_agent.clip_limits()
assert new_agent.position[0] == 10
def test_history_dump():
new_history = history.History()
agents = [agent.Agent(n_variables=2, n_dimensions=1) for _ in range(5)]
new_history.dump(agents=agents, best_agent=agents[4], value=0)
assert len(new_history.agents) > 0
assert len(new_history.best_agent) > 0
assert new_history.value[0] == 0
def test_agent_check_limits():
new_agent = agent.Agent(n_variables=1, n_dimensions=1)
lower_bound = [10]
upper_bound = [10]
new_agent.check_limits(lower_bound, upper_bound)
assert new_agent.position[0] == 10
def test_history_save():
new_history = history.History()
agents = [agent.Agent(n_variables=2, n_dimensions=1) for _ in range(5)]
new_history.dump(agents=agents, best_agent=agents[0])
new_history.save('models/test.pkl')
assert os.path.isfile('./models/test.pkl')
def test_agent_clip_by_bound():
new_agent = agent.Agent(1, 1, 0, 1)
new_agent.lb = np.array([10])
new_agent.ub = np.array([10])
new_agent.clip_by_bound()
assert new_agent.position[0] == 10
def test_agent_check_limits():
new_agent = agent.Agent(n_variables=1, n_dimensions=1)
new_agent.lb = [10]
new_agent.ub = [10]
new_agent.check_limits()
assert new_agent.position[0] == 10
def test_history_dump():
new_history = history.History()
agents = []
for _ in range(5):
agents.append(agent.Agent(n_variables=2, n_dimensions=1))
new_history.dump(agents, agents[0])
assert len(new_history.agents) > 0
assert len(new_history.best_agent) > 0
def test_history_show():
new_history = history.History()
agents = []
for _ in range(5):
agents.append(agent.Agent(n_variables=2, n_dimensions=1))
new_history.dump(agents, agents[0])
new_history.show()
assert True == True
def test_agent_lb_setter():
new_agent = agent.Agent(1, 1, 0, 1)
try:
new_agent.lb = [1]
except:
new_agent.lb = np.array([1])
assert new_agent.lb[0] == 1
try:
new_agent.lb = np.array([1, 2])
except:
new_agent.lb = np.array([1])
assert new_agent.lb[0] == 1
def test_agent_mapping_setter():
new_agent = agent.Agent(1, 1, 0, 1)
try:
new_agent.mapping = "a"
except:
new_agent.mapping = ["x1"]
assert len(new_agent.mapping) == 1
try:
new_agent.mapping = []
except:
new_agent.mapping = ["x1"]
assert len(new_agent.mapping) == 1
def test_history_get_convergence():
new_history = history.History(save_agents=True)
agents = [
agent.Agent(n_variables=2,
n_dimensions=1,
lower_bound=[0, 0],
upper_bound=[1, 1]) for _ in range(5)
]
new_history.dump(agents=agents,
best_agent=agents[4],
local_position=agents[0].position,
value=0)
new_history.dump(agents=agents,
best_agent=agents[4],
local_position=agents[0].position,
value=0)
try:
agents_pos, agents_fit = new_history.get_convergence(key='agents',
index=5)
except:
agents_pos, agents_fit = new_history.get_convergence(key='agents',
index=0)
assert agents_pos.shape == (2, 2)
assert agents_fit.shape == (2, )
best_agent_pos, best_agent_fit = new_history.get_convergence(
key='best_agent')
assert best_agent_pos.shape == (2, 2)
assert best_agent_fit.shape == (2, )
try:
local_position = new_history.get_convergence(key='local_position',
index=5)
except:
local_position = new_history.get_convergence(key='local_position')
assert local_position.shape == (2, )
value = new_history.get_convergence(key='value')
assert value.shape == (2, )
def test_history_get():
new_history = history.History()
agents = [agent.Agent(n_variables=2, n_dimensions=1) for _ in range(5)]
new_history.dump(agents=agents, best_agent=agents[4], value=0)
try:
agents = new_history.get(key='agents', index=0)
except:
agents = new_history.get(key='agents', index=(0, 0))
try:
agents = new_history.get(key='agents', index=(0, 0, 0))
except:
agents = new_history.get(key='agents', index=(0, 0))
assert agents.shape == (2, 1)
def test_history_dump():
new_history = history.History(save_agents=True)
agents = [
agent.Agent(
n_variables=2, n_dimensions=1, lower_bound=[0, 0], upper_bound=[1, 1]
)
for _ in range(5)
]
new_history.dump(agents=agents, best_agent=agents[4], value=0)
assert len(new_history.agents) > 0
assert len(new_history.best_agent) > 0
assert new_history.value[0] == 0
new_history = history.History(save_agents=False)
new_history.dump(agents=agents)
assert hasattr(new_history, "agents") is False
def test_agent_lb():
new_agent = agent.Agent(1, 1, 0, 1)
assert len(new_agent.lb) == 1
def test_agent_n_variables():
new_agent = agent.Agent(1, 1, 0, 1)
assert new_agent.n_variables == 1
def test_agent_fit():
new_agent = agent.Agent(1, 1, 0, 1)
assert new_agent.fit == sys.float_info.max
def test_agent_position():
new_agent = agent.Agent(1, 1, 0, 1)
assert new_agent.position.shape == (1, 1)
def test_agent_n_dimensions():
new_agent = agent.Agent(1, 1, 0, 1)
assert new_agent.n_dimensions == 1