with pm.Model() as model:
    a = pm.Normal("a")
    b = pm.Deterministic("b", a + 10)
    c = pm.Deterministic("c", b * 3)
    d = pm.Normal("d", c, observed=0)
with model:
    trace = pm.sample()
with pm.do(model, {"a": -100}):
    trace1 = pm.sample_posterior_predictive(trace, var_names=["c"])
# should raise an error since a is -100
np.testing.assert_allclose(trace1.posterior_predictive["c"], trace.posterior["c"])
with pm.do(model, {"a": -100}):
    trace1 = pm.sample_posterior_predictive(trace, var_names=["c", "b"])
# raises an error since a is -100
np.testing.assert_allclose(trace1.posterior_predictive["c"], trace.posterior["c"])