def test_Result_get_dataset_method_error(dummy_result: Result): # noqa: F811
"""Result.get_dataset(dataset_label) error on wrong key."""
with pytest.raises(ValueError, match="Unknown dataset 'foo'"):
deprecation_warning_on_call_test_helper(
dummy_result.get_dataset, args=["foo"], raise_exception=True
)
def test_deprecation_warning_on_call_test_helper_error_reraise():
"""Raise if raise_exception and args or kwargs"""
with pytest.raises(ValueError, match="not a bool"):
deprecation_warning_on_call_test_helper(dummy_warn,
args=["foo"],
kwargs={"bar": "baz"},
raise_exception=True)
def test_Result_save_method(tmpdir: LocalPath, dummy_result: Result): # noqa: F811
"""Result.save(result_dir) creates all file"""
result_dir = tmpdir / "dummy"
result_dir.mkdir()
deprecation_warning_on_call_test_helper(
dummy_result.save, args=[str(result_dir)], raise_exception=True
)
assert (result_dir / "result.md").exists()
assert (result_dir / "optimized_parameters.csv").exists()
assert (result_dir / "dataset1.nc").exists()
assert (result_dir / "dataset2.nc").exists()
assert (result_dir / "dataset3.nc").exists()
def test_deprecation_warning_on_call_test_helper():
"""Correct result passed on"""
result = deprecation_warning_on_call_test_helper(dummy_warn,
args=["foo"],
kwargs={"bar": True})
assert result == ("foo", True)
def test_Scheme_from_yaml_file_method(tmp_path: Path):
"""Create Scheme from file."""
scheme_path = tmp_path / "scheme.yml"
model_path = tmp_path / "model.yml"
model_path.write_text(
"type: kinetic-spectrum\ndataset:\n dataset1:\n megacomplex: []")
parameter_path = tmp_path / "parameters.yml"
parameter_path.write_text("[1.0, 67.0]")
dataset_path = tmp_path / "dataset.nc"
xr.DataArray([[1, 2, 3]], coords=[
("e", [1]), ("c", [1, 2, 3])
]).to_dataset(name="data").to_netcdf(dataset_path)
scheme_path.write_text(f"""
model: {model_path}
parameters: {parameter_path}
non-negative-least-squares: True
maximum-number-function-evaluations: 42
data:
dataset1: {dataset_path}""")
result = deprecation_warning_on_call_test_helper(Scheme.from_yaml_file,
args=[str(scheme_path)],
raise_exception=True)
assert isinstance(result, Scheme)
def test_parameter_group_to_csv_no_stderr(tmp_path: Path):
"""``ParameterGroup.to_csv`` raises deprecation warning and saves file."""
parameter_path = tmp_path / "test_parameter.csv"
deprecation_warning_on_call_test_helper(PARAMETERS.to_csv,
args=[parameter_path.as_posix()],
raise_exception=True)
expected = dedent("""\
label,value,expression,minimum,maximum,non-negative,vary,standard-error
rates.species_1,0.5,None,-inf,inf,False,True,None
rates.species_2,0.3,None,-inf,inf,False,True,None
rates.species_3,0.1,None,-inf,inf,False,True,None
irf.center,0.3,None,-inf,inf,False,True,None
irf.width,0.1,None,-inf,inf,False,True,None
""")
assert parameter_path.is_file()
assert parameter_path.read_text() == expected
def test_Result_get_dataset_method(dummy_result: Result): # noqa: F811
"""Result.get_dataset(dataset_label) gives correct dataset."""
result = deprecation_warning_on_call_test_helper(
dummy_result.get_dataset, args=["dataset1"], raise_exception=True
)
assert result == dummy_result.data["dataset1"]
def test_read_parameters_from_yaml():
"""read_parameters_from_yaml raises warning"""
result = deprecation_warning_on_call_test_helper(read_parameters_from_yaml,
args=["foo:\n - 123"],
raise_exception=True)
assert isinstance(result, ParameterGroup)
assert isinstance(result["foo"], ParameterGroup)
assert result["foo"].get(1) == 123
def test_read_model_from_yaml():
"""read_model_from_yaml raises warning"""
result = deprecation_warning_on_call_test_helper(
read_model_from_yaml,
args=["type: kinetic-spectrum"],
raise_exception=True)
assert isinstance(result, Model)
assert result.model_type == "kinetic-spectrum"
def test_read_model_from_yaml_file(tmp_path: Path):
"""read_model_from_yaml_file raises warning"""
model_file = tmp_path / "model.yaml"
model_file.write_text("type: kinetic-spectrum")
result = deprecation_warning_on_call_test_helper(read_model_from_yaml_file,
args=[str(model_file)],
raise_exception=True)
assert isinstance(result, Model)
assert result.model_type == "kinetic-spectrum"
def test_read_model_from_yaml():
"""read_model_from_yaml raises warning"""
yaml = """
type: kinetic-spectrum
megacomplex: {}
"""
_, result = deprecation_warning_on_call_test_helper(read_model_from_yaml,
args=[yaml],
raise_exception=True)
assert isinstance(result, Model)
def test_read_parameters_from_yaml_file(tmp_path: Path):
"""read_parameters_from_yaml_file raises warning"""
parameters_file = tmp_path / "parameters.yaml"
parameters_file.write_text("foo:\n - 123")
result = deprecation_warning_on_call_test_helper(
read_parameters_from_yaml_file,
args=[str(parameters_file)],
raise_exception=True)
assert isinstance(result, ParameterGroup)
assert isinstance(result["foo"], ParameterGroup)
assert result["foo"].get(1) == 123
def test_read_parameters_from_csv_file(tmp_path: Path):
"""read_parameters_from_csv_file raises warning"""
parameters_file = tmp_path / "parameters.csv"
parameters_file.write_text("label,value\nfoo,123")
result = deprecation_warning_on_call_test_helper(
read_parameters_from_csv_file,
args=[str(parameters_file)],
raise_exception=True,
)
assert isinstance(result, ParameterGroup)
assert result.get("foo") == 123
def test_scheme_group(group: bool):
"""Argument ``group`` raises deprecation and maps to ``dataset_groups.default.link_clp``."""
model, parameters, dataset = MODEL, PARAMETERS, DATASET
warnings, result = deprecation_warning_on_call_test_helper(
Scheme,
args=(model, parameters, {"dataset": dataset}),
kwargs={"group": group},
raise_exception=True,
)
assert isinstance(result, Scheme)
assert result.model.dataset_group_models["default"].link_clp == group
assert "<model_file>dataset_groups.default.link_clp" in warnings[0].message.args[0]
def test_scheme_group_tolerance():
"""Argument ``group_tolerance`` raises deprecation and maps to ``clp_link_tolerance``."""
model, parameters, dataset = MODEL, PARAMETERS, DATASET
warnings, result = deprecation_warning_on_call_test_helper(
Scheme,
args=(model, parameters, {"dataset": dataset}),
kwargs={"group_tolerance": 1},
raise_exception=True,
)
assert isinstance(result, Scheme)
assert result.clp_link_tolerance == 1
assert "glotaran.project.Scheme(..., clp_link_tolerance=...)" in warnings[0].message.args[0]
def test_scheme_non_negative_least_squares(non_negative_least_squares: bool, expected: str):
"""Argument ``non_negative_least_squares`` raises deprecation and maps to
``dataset_groups.default.residual_function``.
"""
model, parameters, dataset = MODEL, PARAMETERS, DATASET
warnings, result = deprecation_warning_on_call_test_helper(
Scheme,
args=(model, parameters, {"dataset": dataset}),
kwargs={"non_negative_least_squares": non_negative_least_squares},
raise_exception=True,
)
assert isinstance(result, Scheme)
assert result.model.dataset_group_models["default"].residual_function == expected
assert "<model_file>dataset_groups.default.residual_function" in warnings[0].message.args[0]
def test_scheme_spec_deprecations(
monkeypatch: MonkeyPatch,
scheme_yml_str: str,
expected_key: str,
expected_value: Any,
):
"""Warning gets emitted by load_model"""
return_dicts = []
with monkeypatch.context() as m:
m.setattr(yml_module, "fromdict",
lambda _, spec, *args, **kwargs: return_dicts.append(spec))
record, _ = deprecation_warning_on_call_test_helper(
load_scheme,
args=(scheme_yml_str, ),
kwargs={"format_name": "yml_str"})
return_dict = return_dicts[0]
assert expected_key in return_dict
assert return_dict[expected_key] == expected_value
assert len(record) == 1
def test_scheme_from_yaml_file_method(tmp_path: Path):
"""Create Scheme from file."""
scheme_path = tmp_path / "scheme.yml"
model_yml_str = """
megacomplex:
m1:
type: decay
k_matrix: []
dataset:
dataset1:
megacomplex: [m1]
"""
model_path = tmp_path / "model.yml"
model_path.write_text(model_yml_str)
parameter_path = tmp_path / "parameters.yml"
parameter_path.write_text("[1.0, 67.0]")
dataset_path = tmp_path / "dataset.nc"
xr.DataArray([[1, 2, 3]], coords=[("e", [1]), ("c", [1, 2, 3])]).to_dataset(
name="data"
).to_netcdf(dataset_path)
scheme_path.write_text(
f"""
model: {model_path}
parameters: {parameter_path}
maximum_number_function_evaluations: 42
data:
dataset1: {dataset_path}"""
)
_, result = deprecation_warning_on_call_test_helper(
Scheme.from_yaml_file, args=[str(scheme_path)], raise_exception=True
)
assert isinstance(result, Scheme)
def test_model_spec_deprecations(
monkeypatch: MonkeyPatch,
model_yml_str: str,
expected_nr_of_warnings: int,
expected_key: str,
expected_value: Any,
):
"""Warning gets emitted by load_model"""
return_dicts = []
with monkeypatch.context() as m:
m.setattr(yml_module, "sanitize_yaml",
lambda spec: return_dicts.append(spec))
record, _ = deprecation_warning_on_call_test_helper(
load_model,
args=(model_yml_str, ),
kwargs={"format_name": "yml_str"})
return_dict = return_dicts[0]
assert expected_key in return_dict
assert return_dict[expected_key] == expected_value
assert len(record) == expected_nr_of_warnings
def test_deprecation_warning_on_call_test_helper_no_warn():
"""Fail no warning"""
deprecation_warning_on_call_test_helper(dummy_no_warn,
args=["foo"],
kwargs={"bar": True})
