def test_multiple_samplers(self, caplog):
with Model():
prob = Beta("prob", alpha=5.0, beta=3.0)
Binomial("outcome", n=1, p=prob)
caplog.clear()
sample(3, tune=2, discard_tuned_samples=False, n_init=None, chains=1)
messages = [msg.msg for msg in caplog.records]
assert all("boolean index did not" not in msg for msg in messages)
def test_multiple_samplers(self):
with Model():
prob = Beta('prob', alpha=5, beta=3)
Binomial('outcome', n=1, p=prob)
with warnings.catch_warnings(record=True) as warns:
sample(3, tune=2, discard_tuned_samples=False, n_init=None)
messages = [warn.message.args[0] for warn in warns]
assert any("contains only 3" in msg for msg in messages)
assert all('boolean index did not' not in msg for msg in messages)
def test_multiple_samplers(self):
with Model():
prob = Beta('prob', alpha=5., beta=3.)
Binomial('outcome', n=1, p=prob)
# Catching warnings through multiprocessing doesn't work,
# so we have to use single threaded sampling.
with pytest.warns(None) as warns:
sample(3, tune=2, discard_tuned_samples=False,
n_init=None, chains=1)
messages = [warn.message.args[0] for warn in warns]
assert any("contains only 3" in msg for msg in messages)
assert all('boolean index did not' not in msg for msg in messages)
