def test_GIVEN_nx_class_and_attributes_are_bytes_WHEN_output_to_json_THEN_they_are_written_as_utf8(
file, ):
dataset_name = "test_ds"
dataset_value = 1
dataset_dtype = np.int32
dataset = file.create_dataset(dataset_name,
data=dataset_value,
dtype=dataset_dtype)
test_nx_class = b"NXpinhole"
test_string_attr = b"some_string"
dataset.attrs["NX_class"] = test_nx_class
dataset.attrs["string_attr"] = test_string_attr
converter = NexusToDictConverter()
root_dict = converter.convert(file)
ds = root_dict["children"][0]
for attribute in ds["attributes"]:
assert attribute["name"] in ["NX_class", "string_attr"]
if attribute["name"] == "NX_class":
assert attribute["values"] == test_nx_class.decode("utf8")
elif attribute["name"] == "string_attr":
assert attribute["values"] == test_string_attr.decode("utf8")
def test_GIVEN_no_attributes_WHEN_adding_attributes_THEN_root_dict_is_not_changed(
file):
root_dict = dict()
dataset = file.create_dataset("test", data=123)
assert not dataset.attrs.keys()
_add_attributes(dataset, root_dict)
assert not root_dict
def test_UI_GIVEN_array_dataset_as_magnitude_WHEN_creating_translation_THEN_ui_is_filled_correctly(
qtbot, file # noqa:F811
):
wrapper = NexusWrapper()
instrument = Instrument(wrapper, {})
component = instrument.create_component("test", "NXaperture", "")
array = np.array([1, 2, 3, 4])
x = 1
y = 0
z = 0
transform = component.add_translation(QVector3D(x, y, z), name="test")
transform.dataset = file.create_dataset("test", data=array)
view = EditTranslation(parent=None, transformation=transform, instrument=instrument)
qtbot.addWidget(view)
assert view.transformation_frame.x_spinbox.value() == x
assert view.transformation_frame.y_spinbox.value() == y
assert view.transformation_frame.z_spinbox.value() == z
assert np.allclose(view.transformation.dataset[...], array)
assert (
view.transformation_frame.magnitude_widget.field_type == FieldType.array_dataset
)
def test_GIVEN_attribute_in_blacklist_WHEN_adding_attributes_THEN_attrs_is_blank(
file):
root_dict = dict()
dataset_name = "test"
dataset = file.create_dataset(dataset_name, data=123)
attr_key = ATTR_NAME_BLACKLIST[0]
attr_value = "some_value"
dataset.attrs[attr_key] = attr_value
_add_attributes(dataset, root_dict)
assert not root_dict
def test_GIVEN_string_list_WHEN_getting_data_and_type_THEN_returns_correct_dtype(
file):
dataset_name = "ds"
dataset_value = np.string_(["s", "t", "r"])
dataset = file.create_dataset(dataset_name, data=dataset_value)
data, dtype, size = get_data_and_type(dataset)
assert data == [x.decode("ASCII") for x in list(dataset_value)]
assert size == (len(dataset_value), )
def test_GIVEN_existing_field_with_attr_which_is_in_blacklist_WHEN_editing_component_THEN_attr_is_not_filled_in(
qtbot, file, field_attributes_dialog):
attr_key = "units"
attr_val = "m"
ds = file.create_dataset(name="test", data=123)
ds.attrs[attr_key] = attr_val
field_attributes_dialog.fill_existing_attrs(ds)
assert len(field_attributes_dialog.get_attrs()) == 0
def test_GIVEN_existing_field_with_attr_WHEN_editing_component_THEN_both_field_and_attrs_are_filled_in_correctly(
qtbot, file, attr_val, field_attributes_dialog):
attr_key = "testattr"
ds = file.create_dataset(name="test", data=123)
ds.attrs[attr_key] = attr_val
field_attributes_dialog.fill_existing_attrs(ds)
assert len(field_attributes_dialog.get_attrs()) == 1
assert field_attributes_dialog.get_attrs()[attr_key] == attr_val
def test_GIVEN_attribute_value_is_byte_string_WHEN_filling_existing_values_THEN_string_is_decoded_in_lineedit(
qtbot, field_attributes_dialog, file):
attribute_value_string = "yards"
ds = file.create_dataset(name="test", data=123)
ds.attrs["testattr"] = attribute_value_string.encode("utf-8")
field_attributes_dialog.fill_existing_attrs(ds)
assert (field_attributes_dialog.list_widget.itemWidget(
field_attributes_dialog.list_widget.item(
0)).attr_value_lineedit.text() == attribute_value_string)
def test_GIVEN_transformation_with_scalar_value_that_is_not_castable_to_int_WHEN_getting_ui_value_THEN_ui_placeholder_value_is_returned_instead(
file, # noqa: F811
):
nexus_wrapper = NexusWrapper(str(uuid1()))
transform_name = "transform_1"
transform = create_transform(nexus_wrapper, transform_name)
str_value = "sdfji"
transform.dataset = file.create_dataset("test", data=str_value)
assert transform.ui_value != str_value
assert transform.ui_value == 0
def test_GIVEN_attribute_WHEN_adding_attributes_THEN_attrs_are_added_to_root_dict(
file):
root_dict = dict()
dataset_name = "test"
dataset = file.create_dataset(dataset_name, data=123)
attr_key = "something"
attr_value = "some_value"
dataset.attrs[attr_key] = attr_value
_add_attributes(dataset, root_dict)
assert root_dict["attributes"]
assert root_dict["attributes"][0]["name"] == attr_key
assert root_dict["attributes"][0]["values"] == attr_value
def test_GIVEN_array_WHEN_getting_data_and_dtype_THEN_function_returns_correcte_fw_json_dtype_and_values(
file, ):
expected_dtype = "float"
expected_values = [1.1, 1.2, 1.3]
dataset = file.create_dataset("test_dataset",
data=expected_values,
dtype="float32")
data, dtype, size = get_data_and_type(dataset)
assert size == (len(expected_values), )
assert np.allclose(data, expected_values)
assert dtype == expected_dtype
def test_GIVEN_float_WHEN_getting_data_and_type_THEN_returns_correct_dtype(
file):
dataset_name = "ds"
dataset_type = np.float32
dataset_value = np.float32(2.123)
dataset = file.create_dataset(dataset_name,
dtype=dataset_type,
data=dataset_value)
data, dtype, size = get_data_and_type(dataset)
assert data == dataset_value
assert dtype == "float"
assert size == 1
def test_GIVEN_single_string_WHEN_getting_data_and_dtype_THEN_function_returns_correct_fw_json_dtype(
file, ):
expected_dtype = "string"
expected_size = 1
expected_value = np.string_("udder")
dataset = file.create_dataset("test_dataset",
data=expected_value,
dtype="S5")
data, dtype, size = get_data_and_type(dataset)
assert size == expected_size
assert dtype == expected_dtype
assert bytes(data, "ASCII") == expected_value
def test_GIVEN_int64_WHEN_getting_data_and_dtype_THEN_function_returns_correct_fw_json_dtype(
file, ):
expected_dtype = "int64"
expected_size = 1
expected_value = np.int64(171_798_691_842) # bigger than max 32b int
dataset = file.create_dataset("test_dataset",
dtype="int64",
data=expected_value)
data, dtype, size = get_data_and_type(dataset)
assert size == expected_size
assert dtype == expected_dtype
assert data == expected_value
def test_GIVEN_int32_WHEN_getting_data_and_dtype_THEN_function_returns_correct_fw_json_dtype(
file, ):
expected_dtype = "int32"
expected_size = 1
expected_value = np.int32(42)
dataset = file.create_dataset("test_dataset",
dtype="int32",
data=expected_value)
data, dtype, size = get_data_and_type(dataset)
assert size == expected_size
assert dtype == expected_dtype
assert data == expected_value
def test_GIVEN_float64_WHEN_getting_data_and_dtype_THEN_function_returns_correct_fw_json_dtype(
file, ):
expected_dtype = "double"
expected_size = 1
expected_value = np.float64(324.123_231_413_515_223_412_352_135_34)
dataset = file.create_dataset("test_dataset",
dtype=np.float64,
data=expected_value)
data, dtype, size = get_data_and_type(dataset)
assert size == expected_size
assert dtype == expected_dtype
assert data == expected_value
def test_GIVEN_dataset_with_an_array_attribute_WHEN_output_to_json_THEN_attribute_is_present_in_json(
file, test_input):
dataset_name = "test_ds"
dataset_value = 1
dataset_dtype = np.int32
dataset = file.create_dataset(dataset_name,
data=dataset_value,
dtype=dataset_dtype)
test_attr_name = "test_attr"
dataset.attrs[test_attr_name] = test_input
converter = NexusToDictConverter()
root_dict = converter.convert(file)
ds = root_dict["children"][0]
assert ds["attributes"][0]["name"] == test_attr_name
assert ds["attributes"][0]["values"].tolist() == test_input
def test_GIVEN_multiple_values_WHEN_handling_dataset_THEN_size_field_does_exist_in_root_dict(
file, ):
dataset_name = "test_ds"
dataset_value = [1.1, 1.2, 1.3]
dataset_dtype = np.float
dataset = file.create_dataset(dataset_name,
data=dataset_value,
dtype=dataset_dtype)
dataset.attrs["NX_class"] = "NXpinhole"
converter = NexusToDictConverter()
root_dict = converter.convert(file)
ds = root_dict["children"][0]
assert ds["name"].lstrip("/") == dataset_name
assert ds["type"] == "dataset"
assert ds["values"] == dataset_value
assert ds["dataset"]["size"] == (len(dataset_value), )