def test_simple_inference_can_be_run():
n_samples = 4
true_params = [0.5, 0.5] # t1, t2
for sampling_type in ["grid", "uniform", "BO"]:
params = BolfiParams(bounds=((0, 1), (0, 1)),
n_samples=n_samples,
n_initial_evidence=2,
sampling_type=sampling_type,
grid_tics=[[0.25, 0.75], [0.33, 0.66]],
seed=1,
simulator_node_name="MA2",
discrepancy_node_name="d")
model = get_model(n_obs=1000, true_params=true_params, seed_obs=1)
results = list()
bf = BolfiFactory(model, params)
exp = bf.get()
exp.do_sampling()
exp.compute_samples_and_ML()
assert len(exp.samples) == n_samples
assert exp.ML_val is not None
exp.compute_posterior()
assert exp.post is not None
exp.compute_MAP()
assert exp.MAP_val is not None
ML_sim = exp.simulate_data(exp.ML)
MAP_sim = exp.simulate_data(exp.MAP)
ML_disc = exp.compute_discrepancy_with_data(exp.ML, ML_sim)
MAP_disc = exp.compute_discrepancy_with_data(exp.MAP, MAP_sim)
def test_simple_inference_can_be_run_consistently():
for sampling_type in ["grid", "uniform", "BO"]:
params = BolfiParams(bounds=((0, 1), (0, 1)),
n_samples=4,
n_initial_evidence=2,
sampling_type=sampling_type,
grid_tics=[[0.25, 0.75], [0.33, 0.66]],
seed=1,
discrepancy_node_name="d")
model = get_model()
results = list()
bf = BolfiFactory(model, params)
for i in range(2):
post = bf.get().run()
results.append(post.ML[0])
np.testing.assert_array_almost_equal(results[0], results[1])