def test_linear_regressor_score_not_fitted():
"""Test of `LinearRegressor` class with score calculation without fit."""
lr = LinearRegressor(learning_rate=0.1, iterations=1, standardize=False)
X = np.array([1])
y = np.array([1])
with pytest.raises(NotFitted):
lr.score(X, y)
def test_linear_regressor_normal():
"""Test of `normal` method of `LinearRegressor` class."""
lr = LinearRegressor(learning_rate=0.1, iterations=1, standardize=False)
X = np.array([1])
y = np.array([1])
lr.normal(X, y)
assert lr.score(X, y) == 1
def test_linear_regressor_standardized():
"""Test of `LinearRegressor` class with standardization."""
lr = LinearRegressor(learning_rate=0.1, iterations=1, standardize=True)
X = np.array([1])
y = np.array([1])
lr.fit(X, y)
assert lr.score(X, y) == 1