add docs

Author: OriolAbril

pymc/sampling.py

@@ -1791,6 +1791,10 @@ def sample_posterior_predictive(
         generally be the model used to generate the ``trace``, but it doesn't need to be.
     var_names : Iterable[str]
         Names of variables for which to compute the posterior predictive samples.
+    sample_dims : list of str, optional
+        Dimensions over which to loop and generate posterior predictive samples.
+        When `sample_dims` is ``None`` (default) both "chain" and "draw" are considered sample
+        dimensions. Only taken into account when `trace` is InferenceData or Dataset.
     random_seed : int, RandomState or Generator, optional
         Seed for the random number generator.
     progressbar : bool
@@ -1827,6 +1831,14 @@ def sample_posterior_predictive(
         thinned_idata = idata.sel(draw=slice(None, None, 5))
         with model:
             idata.extend(pymc.sample_posterior_predictive(thinned_idata))
+
+    Generate 5 posterior predictive samples per posterior sample.
+
+    .. code:: python
+
+        expanded_data = idata.posterior.expand_dims(pred_id=5)
+        with model:
+            idata.extend(pymc.sample_posterior_predictive(expanded_data))
     """
 
     _trace: Union[MultiTrace, PointList]

pymc/tests/test_sampling.py

@@ -1625,14 +1625,14 @@ def test_sample_dims(self, point_list_arg_bug_fixture):
             pp = pm.sample_posterior_predictive(post, var_names=["d"], sample_dims=["sample"])
             assert "sample" in pp.posterior_predictive
             assert len(pp.posterior_predictive["sample"]) == len(post["sample"])
-            post = post.expand_dims(pp_dim=5)
+            post = post.expand_dims(pred_id=5)
             pp = pm.sample_posterior_predictive(
-                post, var_names=["d"], sample_dims=["sample", "pp_dim"]
+                post, var_names=["d"], sample_dims=["sample", "pred_id"]
             )
             assert "sample" in pp.posterior_predictive
-            assert "pp_dim" in pp.posterior_predictive
+            assert "pred_id" in pp.posterior_predictive
             assert len(pp.posterior_predictive["sample"]) == len(post["sample"])
-            assert len(pp.posterior_predictive["pp_dim"]) == 5
+            assert len(pp.posterior_predictive["pred_id"]) == 5
 
 
 class TestDraw(SeededTest):