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UserWarning if doing predictive sampling with models containing Potentials #4419

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merged 4 commits into from
Jan 16, 2021
Merged

UserWarning if doing predictive sampling with models containing Potentials #4419

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d06eadf
Raise warning when sampling with Potentials
ricardoV94 Jan 15, 2021
a3f8d05
Add warning to fast_sample_ppc and unittests
ricardoV94 Jan 15, 2021
f98f9c7
Add release note
ricardoV94 Jan 15, 2021
51db510
Avoid sampling in unittests
ricardoV94 Jan 16, 2021
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Avoid sampling in unittests
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@ricardoV94
ricardoV94 committed Jan 16, 2021
commit 51db510f1f3a98462e72f6942b9263dadc99d5b3
18 changes: 9 additions & 9 deletions pymc3/tests/test_sampling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -726,16 +726,15 @@ def test_potentials_warning(self):
warning_msg = "The effect of Potentials on other parameters is ignored during"
with pm.Model() as m:
a = pm.Normal("a", 0, 1)
p = pm.Potential("p", a)
p = pm.Potential("p", a + 1)
obs = pm.Normal("obs", a, 1, observed=5)
trace = pm.sample()

with pytest.warns(UserWarning, match=warning_msg):
with m:
trace = az.from_dict({"a": np.random.rand(10)})
with m:
with pytest.warns(UserWarning, match=warning_msg):
pm.sample_posterior_predictive(trace, samples=5)

with pytest.warns(UserWarning, match=warning_msg):
with m:
with pytest.warns(UserWarning, match=warning_msg):
pm.fast_sample_posterior_predictive(trace, samples=5)


Expand Down Expand Up @@ -793,10 +792,10 @@ def test_potentials_warning(self):
warning_msg = "The effect of Potentials on other parameters is ignored during"
with pm.Model() as m:
a = pm.Normal("a", 0, 1)
p = pm.Potential("p", a)
p = pm.Potential("p", a + 1)
obs = pm.Normal("obs", a, 1, observed=5)
trace = pm.sample()

trace = az.from_dict({"a": np.random.rand(10)})
with pytest.warns(UserWarning, match=warning_msg):
pm.sample_posterior_predictive_w(samples=5, traces=[trace, trace], models=[m, m])

Expand Down Expand Up @@ -1043,8 +1042,9 @@ def test_potentials_warning(self):
warning_msg = "The effect of Potentials on other parameters is ignored during"
with pm.Model() as m:
a = pm.Normal("a", 0, 1)
p = pm.Potential("p", a)
p = pm.Potential("p", a + 1)

with m:
with pytest.warns(UserWarning, match=warning_msg):
pm.sample_prior_predictive(samples=5)

Expand Down