def test_offline_changepoint_gauss_univ(self):
"""changepoint.BayesOffline: Gauss, univariate
This is a regression test against the output of the original
implementation.
"""
f = offline.BayesOffline("const", "gauss", engine=self.engine)
prob, Q, P, Pcp = f.find_changepoints(
self.data, truncate=-20, full_output=True)
orig = np.load(os.path.join(data_path, "offline_gauss_univ.npz"))
np.testing.assert_allclose(Q, orig["Q"])
np.testing.assert_allclose(P, orig["P"])
o_pcp = np.hstack([np.full((Pcp.shape[0], 1), -np.inf), orig["Pcp"]])
np.testing.assert_allclose(Pcp, o_pcp, rtol=1e-6)
def test_engine(self):
"""changepoint.BayesOffline: set numba engine"""
f = offline.BayesOffline("const", "gauss", engine=self.engine)
assert hasattr(f.segmentation, "py_func")
def test_find_changepoints_prob_thresh(self):
"""changepoint.BayesOffline.find_changepoints: `prob_threshold`"""
f = offline.BayesOffline("const", "gauss", engine=self.engine)
cp = f.find_changepoints(self.data, truncate=-20, prob_threshold=0.2)
np.testing.assert_array_equal(cp, [30, 69])
def test_engine(self):
"""changepoint.BayesOffline: set python engine"""
f = offline.BayesOffline("const", "gauss", engine=self.engine)
self.assertIsInstance(f.segmentation, types.FunctionType)