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