def test_nuts_sampling_runs():
model_ndim = 1
step = lmc.NUTS(logp_dlogp_func=logp_dlogp_func, model_ndim=model_ndim)
draws = 3
tune = 1
chains = 2
cores = 1
trace, stats = lmc.sample(logp_dlogp_func,
model_ndim,
draws,
tune,
step=step,
chains=chains,
cores=cores)
assert trace.shape == (chains, draws, model_ndim)
assert all([
stats[name].shape == (chains, draws, model_ndim)
for (name, _) in step.stats_dtypes[0].items()
])
assert all([
stats[name].dtype == expected_dtype
for (name, expected_dtype) in step.stats_dtypes[0].items()
])
def test_multiprocess_sampling_runs():
size = 1
step = lmc.NUTS(logp_dlogp_func=logp_dlogp_func, size=size)
draws = 1
tune = 1
chains = None
cores = None
trace, stats = lmc.sample(
logp_dlogp_func, size, draws, tune, step=step, chains=chains, cores=cores
)
def test_nuts_sampling_runs():
size = 1
step = lmc.NUTS(logp_dlogp_func=logp_dlogp_func, size=size)
draws = 2
tune = 1
chains = 1
cores = 1
trace, stats = lmc.sample(
logp_dlogp_func, size, draws, tune, step=step, chains=chains, cores=cores
)
assert trace.shape == (1, 2)
def test_nuts_recovers_1d_normal():
size = 1
step = lmc.NUTS(logp_dlogp_func=logp_dlogp_func, size=size)
draws = 1000
tune = 1000
chains = 1
cores = 1
trace, stats = lmc.sample(
logp_dlogp_func, size, draws, tune, step=step, chains=chains, cores=cores
)
assert np.allclose(np.mean(trace), 0, atol=1)
assert np.allclose(np.std(trace), 1, atol=1)
def test_multiprocess_sampling_runs():
model_ndim = 1
step = lmc.NUTS(logp_dlogp_func=logp_dlogp_func, model_ndim=model_ndim)
draws = 1
tune = 1
chains = 4
cores = 4
trace, stats = lmc.sample(logp_dlogp_func,
model_ndim,
draws,
tune,
step=step,
chains=chains,
cores=cores)
def test_nuts_tuning():
model_ndim = 1
draws = 5
tune = 5
step = lmc.NUTS(logp_dlogp_func=logp_dlogp_func, model_ndim=model_ndim)
chains = 1
cores = 1
trace, stats = lmc.sample(logp_dlogp_func,
model_ndim,
draws,
tune,
step=step,
chains=chains,
cores=cores)
assert not step.tune
def test_nuts_tuning():
size = 1
draws = 5
tune = 5
step = lmc.NUTS(logp_dlogp_func=logp_dlogp_func, size=size)
chains = 1
cores = 1
trace, stats = lmc.sample(logp_dlogp_func,
size,
draws,
tune,
step=step,
chains=chains,
cores=cores)
assert not step.tune
