def test_low_n_ess_warning(self):
n_particles = 1000
updater = self._mk_updater(n_particles, resample_thresh=0.0)
outcomes = np.array([0], dtype=int)
expparams = np.ones((1,), dtype=self.model.expparams_dtype)
expparams['alpha'][0] = 2 / 1000 # Force the particle number to be 2.
with assert_warns(ApproximationWarning):
updater.update(outcomes, expparams)
def test_low_n_ess_warning(self):
n_particles = 1000
updater = self._mk_updater(n_particles, resample_thresh=0.0)
outcomes = np.array([0], dtype=int)
expparams = np.ones((1,), dtype=self.model.expparams_dtype)
expparams['alpha'][0] = 2 / 1000 # Force the particle number to be 2.
with assert_warns(ApproximationWarning):
updater.update(outcomes, expparams)
def test_assert_warns_nowarn(self):
with assert_warns(RuntimeWarning):
pass
def test_assert_warns_ok(self):
with assert_warns(RuntimeWarning):
warnings.warn(RuntimeWarning("Test"))
def test_assert_warns_nowarn(self):
with assert_warns(RuntimeWarning):
pass
def test_assert_warns_ok(self):
with assert_warns(RuntimeWarning):
warnings.warn(RuntimeWarning("Test"))
