def test_const_takes_ndarray_of_rank_one() -> None:
ndarray = np.array([1, 2])
v = Const(ndarray)
assert ndarray.shape == (2, )
assert v.get_value().shape == (2, )
assert np.array_equal(v.get_value().flatten(), ndarray.flatten())
def test_const_takes_ndarray(arr: List[List[primitive_types]],
expected_java_class: str) -> None:
ndarray = np.array(arr)
v = Const(ndarray)
assert_java_class(v, expected_java_class)
assert np.array_equal(v.get_value(), ndarray)
def test_boolean_vertex_value_is_a_numpy_array() -> None:
ndarray = np.array([[True, True], [False, True]])
vertex = Const(ndarray)
value = vertex.get_value()
assert type(value) == np.ndarray
assert value.dtype == np.bool_
assert (value == ndarray).all()
def test_float_vertex_value_is_a_numpy_array() -> None:
ndarray = np.array([[1., 2.], [3., 4.]])
vertex = Const(ndarray)
value = vertex.get_value()
assert type(value) == np.ndarray
assert value.dtype == np.float64
assert (value == ndarray).all()
def test_int_vertex_value_is_a_numpy_array() -> None:
ndarray = np.array([[1, 2], [3, 4]])
vertex = Const(ndarray)
value = vertex.get_value()
assert type(value) == np.ndarray
assert value.dtype == np.int64 or value.dtype == np.int32
assert (value == ndarray).all()
def test_scalar_vertex_value_is_a_numpy_array() -> None:
scalar = 1.
vertex = Const(scalar)
value = vertex.get_value()
assert type(value) == numpy_types
assert value.shape == ()
assert value.dtype == float
assert value == scalar
def test_const_takes_panda_dataframe(data: List[List[primitive_types]],
expected_java_class: str) -> None:
dataframe = pd.DataFrame(columns=['A', 'B'], data=data)
v = Const(dataframe)
assert_java_class(v, expected_java_class)
vertex_value = v.get_value()
dataframe_value = dataframe.values
assert np.array_equal(vertex_value, dataframe_value)
def test_const_takes_panda_series(data: List[primitive_types],
expected_java_class: str) -> None:
series = pd.Series(data)
v = Const(series)
assert_java_class(v, expected_java_class)
vertex_value = v.get_value()
series_value = series.values
assert len(vertex_value) == len(series_value)
assert vertex_value.shape == (2, )
assert series_value.shape == (2, )
assert np.array_equal(vertex_value.flatten(), series_value.flatten())
def test_const_takes_num(num: Union[primitive_types, numpy_types],
expected_java_class: str) -> None:
v = Const(num)
assert_java_class(v, expected_java_class)
assert v.get_value() == num
