def test_perturb_cat(self):
explore = PerturbExplore()
rng = RNGStub()
rng.randint = lambda low, high, size: [1]
rng.choice = lambda choices: choices[0]
dim = Categorical("name", ["one", "two", 3, 4.0])
assert explore.perturb_cat(rng, "whatever", dim) in dim
def test_perturb(self, space):
explore = PerturbExplore()
rng = RNGStub()
rng.randint = lambda low, high, size: [1]
rng.random = lambda: 1.0
rng.normal = lambda mean, variance: 0.0
rng.choice = lambda choices: choices[0]
params = {"x": 1.0, "y": 2, "z": 0, "f": 10}
new_params = explore(rng, space, params)
for key in space.keys():
assert new_params[key] in space[key]
def test_resample_probability(self, space):
explore = ResampleExplore(probability=0.5)
rng = RNGStub()
rng.randint = lambda low, high, size: [1]
rng.random = lambda: 0.5
params = {"x": 1.0, "y": 2, "z": 0, "f": 10}
assert explore(rng, space, params) is params
rng.random = lambda: 0.4
assert explore(rng, space, params) is not params
def test_perturb_hierarchical_params(self, hspace):
explore = PerturbExplore()
rng = RNGStub()
rng.randint = lambda low, high, size: [1]
rng.random = lambda: 1.0
rng.normal = lambda mean, variance: 0.0
rng.choice = lambda choices: choices[0]
params = {"numerical": {"x": 1.0, "y": 2, "f": 10}, "z": 0}
new_params = explore(rng, hspace, params)
assert "numerical" in new_params
assert "x" in new_params["numerical"]
for key in hspace.keys():
assert flatten(new_params)[key] in hspace[key]