def test_mle_jacobian():
"""Test MAP / MLE estimation for distributions with flat priors."""
truth = 10.0 # Simple normal model should give mu=10.0
start, model, _ = models.simple_normal(bounded_prior=False)
with model:
map_estimate = find_MAP(method="BFGS", model=model)
rtol = 1e-5 # this rtol should work on both floatX precisions
np.testing.assert_allclose(map_estimate["mu_i"], truth, rtol=rtol)
start, model, _ = models.simple_normal(bounded_prior=True)
with model:
map_estimate = find_MAP(method="BFGS", model=model)
np.testing.assert_allclose(map_estimate["mu_i"], truth, rtol=rtol)
def test_mle_jacobian():
"""Test MAP / MLE estimation for distributions with flat priors."""
truth = 10.0 # Simple normal model should give mu=10.0
start, model, _ = models.simple_normal(bounded_prior=False)
with model:
map_estimate = find_MAP(model=model)
rtol = 1E-5 # this rtol should work on both floatX precisions
np.testing.assert_allclose(map_estimate["mu_i"], truth, rtol=rtol)
start, model, _ = models.simple_normal(bounded_prior=True)
with model:
map_estimate = find_MAP(model=model)
np.testing.assert_allclose(map_estimate["mu_i"], truth, rtol=rtol)