def test_invalid_formulas(formula_data, exception, formula, absorb):
"""Test that an invalid formula gives rise to an exception."""
try:
formulation = Formulation(formula, absorb)
formulation._build_matrix(formula_data)
if absorb is not None:
formulation._build_ids(formula_data)
except exception:
print(traceback.format_exc())
return
raise RuntimeError(f"Successful formulation: {formulation}.")
def test_ids(
formula_data: Data, formulas: Iterable[str],
build_columns: Callable[[Mapping[str, Array]],
Sequence[Array]]) -> None:
"""Test that equivalent formulas build IDs as expected."""
# create convenience columns of tuples of categorical variables
formula_data = copy.deepcopy(formula_data)
for (key1, values1), (key2, values2), (key3, values3) in itertools.product(
formula_data.items(), repeat=3):
key12 = f'{key1}{key2}'
key123 = f'{key1}{key2}{key3}'
if key12 not in formula_data:
values12 = np.empty_like(values1, np.object_)
values12[:] = list(zip(values1, values2))
formula_data[key12] = values12
if key123 not in formula_data:
values123 = np.empty_like(values1, np.object_)
values123[:] = list(zip(values1, values2, values3))
formula_data[key123] = values123
# build and compare columns for each formula, making sure that it can be formatted
for absorb in formulas:
formulation = Formulation('x', absorb)
assert str(formulation)
ids = formulation._build_ids(formula_data)
expected_ids = np.column_stack(build_columns(formula_data))
np.testing.assert_array_equal(ids, expected_ids, err_msg=absorb)
