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_matrices(
formula_data: Data, formulas: Iterable[str], build_columns: Callable[[Mapping[str, Array]], Sequence[Array]],
build_derivatives: Callable[[Mapping[str, Array]], Sequence[Array]]) -> None:
"""Test that equivalent formulas build columns and derivatives as expected. Take derivatives with respect to x."""
# construct convenience columns of ones and zeros
ones = np.ones_like(formula_data['x'])
zeros = np.zeros_like(formula_data['x'])
# build columns and derivatives for each formula, making sure that it can be formatted
for formula in formulas:
formulation = Formulation(formula)
assert str(formulation)
matrix, column_formulations, underlying_data = formulation._build_matrix(formula_data)
evaluated_matrix = np.column_stack([ones * f.evaluate(underlying_data) for f in column_formulations])
derivatives = np.column_stack([ones * f.evaluate_derivative('x', underlying_data) for f in column_formulations])
# build expected columns and derivatives
supplemented_data = {'1': ones, '0': zeros, **underlying_data}
expected_matrix = np.column_stack(build_columns(supplemented_data))
expected_derivatives = np.column_stack(build_derivatives(supplemented_data))
# compare columns and derivatives
np.testing.assert_allclose(matrix, expected_matrix, rtol=0, atol=1e-14, err_msg=formula)
np.testing.assert_allclose(matrix, evaluated_matrix, rtol=0, atol=1e-14, err_msg=formula)
np.testing.assert_allclose(derivatives, expected_derivatives, rtol=0, atol=1e-14, err_msg=formula)
