def test_compare_sklearn_mod_0():
X, y = data_gen(nrows = 99)
function_scores = cross_validation(lm(), X = X, y = y, shuffle = False)
sklearn_scores = cross_val_score(lm(), X = X, y = y, cv = 3)
assert max(function_scores - sklearn_scores) < 0.000001, "results doesn't match sklearn"
def test_y_one_column():
X, y = data_gen()
y = X
with pytest.raises(TypeError):
cross_validation(lm(), X=X, y=y)
def test_X_y_Nrows():
X, y = data_gen(nrows = 2)
with pytest.raises(TypeError):
cross_validation(lm(), X=X, y=y)
def test_random_state_range():
X, y = data_gen()
with pytest.raises(TypeError):
cross_validation(lm, X=X, y=y, random_state=-10)
def test_X_y_match():
X, y = data_gen()
y = y[0:90]
with pytest.raises(TypeError):
cross_validation(lm(), X=X, y=y)
def test_model_linear_regression():
X, y = data_gen()
with pytest.raises(TypeError):
cross_validation("LINEAR MODEL", X = X, y = y, random_state = 10)
def test_k_range():
X, y = data_gen(nrows = 5)
with pytest.raises(TypeError):
cross_validation(lm(), X=X, y=y, k = 1)
with pytest.raises(TypeError):
cross_validation(lm(), X=X, y=y, k = 40)
def test_random_state_as_number():
X, y = data_gen()
with pytest.raises(TypeError):
cross_validation(lm(), X = X, y = y, random_state = '10')
def test_shuffle_as_boolean():
X, y = data_gen()
with pytest.raises(TypeError):
cross_validation(lm(), X = X, y = y, shuffle = '1')
with pytest.raises(TypeError):
cross_validation(lm(), X=X, y=y, shuffle=1.0)
def test_k_as_number():
X, y = data_gen()
with pytest.raises(TypeError):
cross_validation(lm(), X = X, y = y, k = '3')
def test_y_as_dataframe():
X, y = data_gen()
with pytest.raises(TypeError):
train_test_split(lm(), X = X, y = "y")
def test_X_as_dataframe():
X, y = data_gen()
with pytest.raises(TypeError):
cross_validation(lm(), X = "X", y = y)