def test_parameter_not_modified(monkeypatch, space):
"""Tests the original dataframe is not modified"""
original = copy.deepcopy(data)
mock_train_regressor(monkeypatch)
partial_dependency(data, space, n_samples=10)
pd.testing.assert_frame_equal(data, original)
def test_n_grid_points(monkeypatch, space):
"""Test that number of points on grid is correct, including adjustment for categorical dims"""
mock_train_regressor(monkeypatch)
n_grid_points = 5
partial_dependencies = partial_dependency(data,
space,
params=["x", "z"],
n_grid_points=n_grid_points,
n_samples=10)
assert set(partial_dependencies.keys()) == {"x", ("x", "z"), "z"}
assert partial_dependencies["z"][1].shape == (3, )
assert partial_dependencies["z"][2].shape == (3, )
assert len(partial_dependencies["x"][0]["x"]) == n_grid_points
assert len(partial_dependencies[("x", "z")][0]["x"]) == n_grid_points
assert partial_dependencies[("x", "z")][0]["z"] == ["a", "b", "c"]
assert partial_dependencies["z"][0]["z"] == ["a", "b", "c"]
assert partial_dependencies["x"][1].shape == (n_grid_points, )
assert partial_dependencies["x"][2].shape == (n_grid_points, )
assert partial_dependencies["z"][1].shape == (3, )
assert partial_dependencies["z"][2].shape == (3, )
assert partial_dependencies[("x", "z")][1].shape == (3, n_grid_points)
assert partial_dependencies[("x", "z")][2].shape == (3, n_grid_points)
def test_multidim(monkeypatch, hspace):
"""Test computing for multiple params in multidim space"""
mock_train_regressor(monkeypatch)
partial_dependencies = partial_dependency(hdata,
hspace,
params=["x", "y[0]", "y[1]"],
n_samples=10)
assert set(partial_dependencies.keys()) == {
"x",
"y[0]",
"y[1]",
("x", "y[0]"),
("x", "y[1]"),
("y[0]", "y[1]"),
}
assert len(partial_dependencies["x"][0]["x"]) == 10
assert len(partial_dependencies["y[0]"][0]["y[0]"]) == 10
assert len(partial_dependencies["y[1]"][0]["y[1]"]) == 10
assert len(partial_dependencies[("x", "y[0]")][0]["x"]) == 10
assert len(partial_dependencies[("x", "y[0]")][0]["y[0]"]) == 10
assert partial_dependencies["x"][1].shape == (10, )
assert partial_dependencies["x"][2].shape == (10, )
assert partial_dependencies["y[0]"][1].shape == (10, )
assert partial_dependencies["y[0]"][2].shape == (10, )
assert partial_dependencies[("x", "y[0]")][1].shape == (10, 10)
assert partial_dependencies[("x", "y[0]")][2].shape == (10, 10)
def test_accept_empty(space):
"""Tests an empty dataframe is returned if you give an empty dataframe"""
empty_frame = pd.DataFrame()
results = partial_dependency(empty_frame,
space,
n_grid_points=3,
n_samples=5)
assert results == {}
empty_frame = pd.DataFrame(columns=["x", "y", "z", "objective"])
results = partial_dependency(empty_frame,
space,
n_grid_points=3,
n_samples=5)
assert results == {}
def test_n_samples(monkeypatch, space):
"""Test n_samples is used properly when sampling random points"""
mock_train_regressor(monkeypatch)
PARAMS = ["x", "z"]
N_SAMPLES = numpy.random.randint(20, 50)
def mock_partial_dependency_grid(space, model, params, samples, n_points):
assert samples.shape == (N_SAMPLES, len(space))
return partial_dependency_grid(space, model, params, samples, n_points)
monkeypatch.setattr(
"orion.analysis.partial_dependency_utils.partial_dependency_grid",
mock_partial_dependency_grid,
)
partial_dependency(data,
space,
params=PARAMS,
n_grid_points=5,
n_samples=N_SAMPLES)
def test_single_param(monkeypatch, space):
"""Test computing for a single param"""
mock_train_regressor(monkeypatch)
partial_dependencies = partial_dependency(data,
space,
params=["x"],
n_samples=10)
assert list(partial_dependencies.keys()) == ["x"]
assert len(partial_dependencies["x"][0]["x"]) == 10
assert partial_dependencies["x"][1].shape == (10, )
assert partial_dependencies["x"][2].shape == (10, )
def test_categorical(monkeypatch, space):
"""Test computing for categorical"""
mock_train_regressor(monkeypatch)
partial_dependencies = partial_dependency(data,
space,
params=["z"],
n_samples=10)
assert set(partial_dependencies.keys()) == {"z"}
assert partial_dependencies["z"][0]["z"] == ["a", "b", "c"]
assert partial_dependencies["z"][1].shape == (3, )
assert partial_dependencies["z"][2].shape == (3, )