def test_loglike():
# Tests of invalid calls to the loglike function
endog = np.ones((10, 1))
mod = KalmanFilter(endog, k_states=1, initialization='approximate_diffuse')
mod['design', :] = 1
mod['selection', :] = 1
mod['state_cov', :] = 1
# Test that self.memory_no_likelihood = True raises an error
mod.memory_no_likelihood = True
assert_raises(RuntimeError, mod.loglikeobs)
def test_loglike():
# Tests of invalid calls to the loglike function
endog = np.ones((10, 1))
mod = KalmanFilter(endog, k_states=1, initialization="approximate_diffuse")
mod["design", :] = 1
mod["selection", :] = 1
mod["state_cov", :] = 1
# Test that self.memory_no_likelihood = True raises an error
mod.memory_no_likelihood = True
assert_raises(RuntimeError, mod.loglike)
assert_raises(RuntimeError, mod.loglikeobs)
