def test_coxreg_serialize_and_compare(self):
"""Test serialization (cereal/pickle) of Cox Regression."""
np.random.seed(123)
n_samples, n_features = 100, 5
w0 = np.random.randn(n_features)
features, times, censoring = SimuCoxReg(
w0, n_samples=n_samples, verbose=False, seed=1234).simulate()
model = ModelCoxRegPartialLik()
model.fit(features, times, censoring)
pickled = pickle.loads(pickle.dumps(model))
self.assertTrue(model._model.compare(pickled._model))
def test_set_model(self):
"""...Test set_model of saga, should only accept childs of
ModelGeneralizedLinear"""
# We try to pass a ModelCoxRegPartialLik which is not a generalized
# linear model to SAGA to check that the error is raised
msg = '^SAGA accepts only childs of `ModelGeneralizedLinear`$'
with self.assertRaisesRegex(ValueError, msg):
w = weights_sparse_gauss(n_weights=2, nnz=0)
X, T, C = SimuCoxReg(w).simulate()
model = ModelCoxRegPartialLik().fit(X, T, C)
SAGA().set_model(model)
msg = '^SAGA accepts only childs of `ModelGeneralizedLinear`$'
with self.assertRaisesRegex(RuntimeError, msg):
w = weights_sparse_gauss(n_weights=2, nnz=0)
X, T, C = SimuCoxReg(w).simulate()
model = ModelCoxRegPartialLik().fit(X, T, C)
saga = SAGA()
saga._solver.set_model(model._model)
def test_ModelCoxRegPartialLik(self):
"""...Numerical consistency check of loss and gradient for Cox Regression
"""
np.random.seed(123)
n_samples, n_features = 100, 5
w0 = np.random.randn(n_features)
features, times, censoring = SimuCoxReg(
w0, n_samples=n_samples, verbose=False, seed=1234).simulate()
model = ModelCoxRegPartialLik()
model.fit(features, times, censoring)
model_spars = ModelCoxRegPartialLik()
model_spars.fit(csr_matrix(features), times, censoring)
self.run_test_for_glm(model, model_spars)