def test_min_cov_det():
df = get_data()
S = risk_models.min_cov_determinant(df, random_state=8)
assert S.shape == (20, 20)
assert S.index.equals(df.columns)
assert S.index.equals(S.columns)
assert S.notnull().all().all()
S2 = risk_models.min_cov_determinant(df, frequency=2, random_state=8)
pd.testing.assert_frame_equal(S / 126, S2)
def test_min_cov_det():
df = get_data()
S = risk_models.min_cov_determinant(df, random_state=8)
assert S.shape == (20, 20)
assert S.index.equals(df.columns)
assert S.index.equals(S.columns)
assert S.notnull().all().all()
S2 = risk_models.min_cov_determinant(df, frequency=2, random_state=8)
pd.testing.assert_frame_equal(S / 126, S2)
def test_min_cov_det():
df = get_data()
S = risk_models.min_cov_determinant(df, random_state=8)
assert S.shape == (20, 20)
assert S.index.equals(df.columns)
assert S.index.equals(S.columns)
assert S.notnull().all().all()
# Min cov det is NOT positive semidefinite for this example.
# Warning has been added to docs.
# assert risk_models._is_positive_semidefinite(S)
S2 = risk_models.min_cov_determinant(df, frequency=2, random_state=8)
pd.testing.assert_frame_equal(S / 126, S2)
def test_min_cov_det():
df = get_data()
S = risk_models.min_cov_determinant(df, random_state=8)
assert S.shape == (20, 20)
assert S.index.equals(df.columns)
assert S.index.equals(S.columns)
assert S.notnull().all().all()
# assert risk_models._is_positive_semidefinite(S)
# Cover that it works on np.ndarray, with a warning
with pytest.warns(RuntimeWarning):
S2 = risk_models.min_cov_determinant(df.to_numpy(), random_state=8)
assert isinstance(S2, pd.DataFrame)
np.testing.assert_equal(S.to_numpy(), S2.to_numpy())
def test_min_cov_det():
df = get_data()
S = risk_models.min_cov_determinant(df, random_state=8)
assert S.shape == (20, 20)
assert S.index.equals(df.columns)
assert S.index.equals(S.columns)
assert S.notnull().all().all()