def test_non_numeric_inputs():
with pytest.raises(TypeError):
params_mle(["male", "female", "male", "female"])
with pytest.raises(TypeError):
params_mle(pd.DataFrame({"var1": [1, 2, "5", "9"]}))
with pytest.raises(TypeError):
params_mle([True, False, True])
def test_output_type():
assert isinstance(params_mle(dummy), pd.DataFrame)
assert isinstance(params_mle(matrix_type), pd.DataFrame)
assert isinstance(params_mle(list_2d_type), pd.DataFrame)
assert isinstance(params_mle(series_type, pd.DataFrame))
def test_empty_inputs():
with pytest.raises(AttributeError):
params_mle(pd.DataFrame({"var1": [], "var2": []}))
with pytest.raises(AttributeError):
params_mle(list())
def test_params_mle_calc():
assert np.allclose(params_mle(dummy), expected)
assert np.allclose(params_mle(series_type), expected["var1"])
assert np.allclose(params_mle(matrix_type), expected)
assert np.allclose(params_mle(list_2d_type), expected)
def test_unequal_list_length():
assert np.allclose(
params_mle([[0, 1, 1, -1], [-1, -1, 0, 1, np.nan, np.nan]]), expected)
def test_NA_values():
na_test = params_mle([[1, 1, np.nan], [np.nan, 2, 3]])
assert na_test.isnull().values.any() == False
def test_no_column_names():
assert list(params_mle(np.array(dummy["var1"]))) == [0]
assert list(params_mle(pd.Series([0, 1, 1, -1]))) == [0]
assert list(params_mle([0, 1, 1, -1])) == [0]
def test_incorrect_input_type():
with pytest.raises(TypeError):
params_mle("hello")
with pytest.raises(TypeError):
params_mle(2.4)
