Include potential terms in Model.point_logps

Author: ricardoV94

pymc/model.py

@@ -1699,17 +1699,16 @@ def point_logps(self, point=None, round_vals=2):
         if point is None:
             point = self.recompute_initial_point()
 
+        factors = self.basic_RVs + self.potentials
         return Series(
             {
-                rv.name: np.round(np.asarray(logp), round_vals)
-                for rv, logp in zip(
-                    self.basic_RVs,
-                    self.fn(
-                        [at.sum(factor) for factor in self.logp_elemwiset(vars=self.basic_RVs)]
-                    )(point),
+                factor.name: np.round(np.asarray(factor_logp), round_vals)
+                for factor, factor_logp in zip(
+                    factors,
+                    self.fn([at.sum(factor) for factor in self.logp_elemwiset(factors)])(point),
                 )
             },
-            name="Log-probability of test_point",
+            name="Point log-probability",
         )
 
 

pymc/tests/test_model.py

@@ -533,6 +533,15 @@ def test_point_logps():
     assert "a" in logp_vals.keys()
 
 
+def test_point_logps_potential():
+    with pm.Model() as model:
+        x = pm.Flat("x", initval=1)
+        y = pm.Potential("y", x * 2)
+
+    logps = model.point_logps()
+    assert np.isclose(logps["y"], 2)
+
+
 class TestShapeEvaluation:
     def test_eval_rv_shapes(self):
         with pm.Model(