def test_can_pass_vertex_to_vertex(jvm_view: JVMView) -> None:
mu = Vertex(jvm_view.GaussianVertex, 0., 1.)
gaussian = Vertex(jvm_view.GaussianVertex, mu, 1.)
sample = gaussian.sample()
assert type(sample) == numpy_types
assert sample.shape == ()
assert sample.dtype == float
def test_id_str_of_downstream_vertex_is_higher_than_upstream(
jvm_view: JVMView) -> None:
hyper_params = Vertex(jvm_view.GaussianVertex, 0., 1.)
gaussian = Vertex(jvm_view.GaussianVertex, 0., hyper_params)
hyper_params_id = hyper_params.get_id()
gaussian_id = gaussian.get_id()
assert type(hyper_params_id) == tuple
assert type(gaussian_id) == tuple
assert hyper_params_id < gaussian_id
def test_get_vertex_id(jvm_view: JVMView) -> None:
gaussian = Vertex(jvm_view.GaussianVertex, 0., 1.)
java_id = gaussian.unwrap().getId().getValue()
python_id = gaussian.get_id()
assert all(value in python_id for value in java_id)
def test_cannot_pass_generic_to_vertex(jvm_view: JVMView) -> None:
class GenericExampleClass:
pass
with pytest.raises(
ValueError,
match=r"Can't parse generic argument. Was given {}".format(
GenericExampleClass)):
Vertex( # type: ignore # this is expected to fail mypy
jvm_view.GaussianVertex, "gaussian", GenericExampleClass(),
GenericExampleClass())
def test_java_collections_to_generator(jvm_view: JVMView) -> None:
gaussian = Vertex(jvm_view.GaussianVertex, 0., 1.)
java_collections = gaussian.unwrap().getConnectedGraph()
python_list = list(Vertex._to_generator(java_collections))
java_vertex_ids = [
Vertex._get_python_id(java_vertex) for java_vertex in java_collections
]
assert java_collections.size() == len(python_list)
assert all(
type(element) == Vertex and element.get_id() in java_vertex_ids
for element in python_list)
def test_can_pass_array_to_vertex(jvm_view: JVMView) -> None:
gaussian = Vertex(jvm_view.GaussianVertex, "gaussian", [3, 3], Const(0.),
Const(1.))
sample = gaussian.sample()
assert sample.shape == (3, 3)
def test_construct_vertex_with_java_vertex(jvm_view: JVMView) -> None:
java_vertex = Gaussian(0., 1.).unwrap()
python_vertex = Vertex(java_vertex)
assert tuple(java_vertex.getId().getValue()) == python_vertex.get_id()
def get_double_model_output_vertex(self, label: str) -> Vertex:
label_unwrapped = VertexLabel(label).unwrap()
result = self.unwrap().getDoubleModelOutputVertex(label_unwrapped)
return Vertex(result)
def __wrap(vertices: JavaMap) -> Dict[str, Vertex]:
return {k.getUnqualifiedName(): Vertex(v) for k, v in vertices.items()}
def test_can_pass_array_to_vertex(jvm_view: JVMView) -> None:
gaussian = Vertex(jvm_view.GaussianVertex, [3, 3], 0., 1.)
sample = gaussian.sample()
assert sample.shape == (3, 3)
def test_can_pass_pandas_series_to_vertex(jvm_view):
gaussian = Vertex(jvm_view.GaussianVertex, pd.Series(data=[0.1, 0.4]),
pd.Series(data=[0.1, 0.4]))
sample = gaussian.sample()
assert sample.shape == (2, )
def test_can_pass_pandas_dataframe_to_vertex(jvm_view: JVMView) -> None:
gaussian = Vertex(jvm_view.GaussianVertex, pd.DataFrame(data=[0.1, 0.4]),
pd.DataFrame(data=[0.1, 0.4]))
sample = gaussian.sample()
assert sample.shape == (2, 1)
def test_can_pass_ndarray_to_vertex(jvm_view: JVMView) -> None:
gaussian = Vertex(jvm_view.GaussianVertex, np.array([0.1, 0.4]),
np.array([0.4, 0.5]))
sample = gaussian.sample()
assert sample.shape == (2, )
def test_get_connected_graph(jvm_view: JVMView) -> None:
gaussian = Vertex(jvm_view.GaussianVertex, 0., 1.)
connected_graph = set(gaussian.get_connected_graph())
assert len(connected_graph) == 3