def test_distortion_score_empty_clusters(self):
"""
Ensure no ValueError is thrown when there are empty clusters #1185
"""
X = np.array([[1, 2], [3, 4], [5, 6]])
valuea = distortion_score(X, np.array([1, 3, 3]))
valueb = distortion_score(X, np.array([0, 1, 1]))
assert valuea == valueb
def test_distortion_score_pandas_input(self):
"""
Test the distortion score metric on pandas DataFrame and Series
"""
df = pd.DataFrame(self.clusters.X)
s = pd.Series(self.clusters.y)
score = distortion_score(df, s)
assert score == pytest.approx(69.10006514142941)
def test_distortion_score_pandas_input(self):
"""
Test the distortion score metric on pandas DataFrame and Series
"""
df = pd.DataFrame(X)
s = pd.Series(y)
score = distortion_score(df, s)
assert score == pytest.approx(7.6777850157143783)
def test_distortion_score_sparse_matrix_input(self, func):
"""
Test the distortion score metric on a sparse array
"""
score = distortion_score(func(self.clusters.X), self.clusters.y)
assert score == pytest.approx(69.10006514142938)
def test_distortion_score(self):
"""
Test the distortion score metric function
"""
score = distortion_score(self.clusters.X, self.clusters.y)
assert score == pytest.approx(69.10006514142941)
def test_distortion_score(self):
"""
Test the distortion score metric function
"""
score = distortion_score(X, y)
self.assertEqual(score, 7.6777850157143783)
def test_distortion_score_sparse_matrix_input(self, Xs):
"""
Test the distortion score metric on a sparse array
"""
score = distortion_score(Xs, y)
assert score == pytest.approx(7.6777850157143783)
def test_distortion_score(self):
"""
Test the distortion score metric function
"""
score = distortion_score(X, y)
assert score == 7.6777850157143783
