specific tests for the alternative dict format

Author: williambdean

pymc_marketing/prior.py

@@ -1280,7 +1280,7 @@ def from_dict(cls, data: dict[str, Any]) -> Censored:
         """Create a censored distribution from a dictionary."""
         data = data["data"]
         return cls(  # type: ignore
-            distribution=Prior.from_dict(data["dist"]),
+            distribution=deserialize(data["dist"]),
             lower=data["lower"],
             upper=data["upper"],
         )

tests/test_prior.py

@@ -1169,3 +1169,40 @@ def test_scaled_sample_prior() -> None:
 def test_prior_list_dims() -> None:
     dist = Prior("Normal", dims=["channel", "geo"])
     assert dist.dims == ("channel", "geo")
+
+
+@pytest.mark.parametrize(
+    "data, expected",
+    [
+        pytest.param(
+            {
+                "distribution": "Laplace",
+                "mu": 1,
+                "b": 2,
+                "dims": ("x", "y"),
+                "transform": "sigmoid",
+            },
+            Prior("Laplace", mu=1, b=2, dims=("x", "y"), transform="sigmoid"),
+            id="Prior",
+        ),
+        pytest.param(
+            {"distribution": "Normal", "mu": {"distribution": "Normal"}},
+            Prior("Normal", mu=Prior("Normal")),
+            id="Prior with nested distribution",
+        ),
+        pytest.param(
+            {
+                "class": "Censored",
+                "data": {
+                    "dist": {"distribution": "Normal"},
+                    "lower": 0,
+                    "upper": 10,
+                },
+            },
+            Censored(Prior("Normal"), lower=0, upper=10),
+            id="Censored with alternative",
+        ),
+    ],
+)
+def test_alternative_prior_deserialize(data, expected) -> None:
+    assert deserialize(data) == expected