Fix coords in constant_data issue #5046

pymc/backends/arviz.py

@@ -131,9 +131,9 @@ def dict_to_dataset(
         for name, vals in data.items():
             vals = np.atleast_1d(vals)
             val_dims = dims.get(name)
-            val_dims, coords = generate_dims_coords(vals.shape, name, dims=val_dims, coords=coords)
-            coords = {key: xr.IndexVariable((key,), data=coords[key]) for key in val_dims}
-            out_data[name] = xr.DataArray(vals, dims=val_dims, coords=coords)
+            val_dims, crds = generate_dims_coords(vals.shape, name, dims=val_dims, coords=coords)
+            crds = {key: xr.IndexVariable((key,), data=crds[key]) for key in val_dims}
+            out_data[name] = xr.DataArray(vals, dims=val_dims, coords=crds)
         return xr.Dataset(data_vars=out_data, attrs=make_attrs(attrs=attrs, library=library))
 
 

pymc/tests/test_idata_conversion.py

@@ -568,6 +568,36 @@ def test_multivariate_observations(self):
         assert "direction" not in idata.log_likelihood.dims
         assert "direction" in idata.observed_data.dims
 
+    def test_constant_data_coords_issue_5046(self):
+        """This is a regression test against a bug where a local coords variable was overwritten."""
+        dims = {
+            "alpha": ["backwards"],
+            "bravo": ["letters", "yesno"],
+        }
+        coords = {
+            "backwards": np.arange(17)[::-1],
+            "letters": list("ABCDEFGHIJK"),
+            "yesno": ["yes", "no"],
+        }
+        data = {
+            name: np.random.uniform(size=[len(coords[dn]) for dn in dnames])
+            for name, dnames in dims.items()
+        }
+
+        for k in data:
+            assert len(data[k].shape) == len(dims[k])
+
+        ds = pm.backends.arviz.dict_to_dataset(
+            data=data,
+            library=pm,
+            coords=coords,
+            dims=dims,
+            default_dims=[],
+            index_origin=0,
+        )
+        for dname, cvals in coords.items():
+            np.testing.assert_array_equal(ds[dname].values, cvals)
+
 
 class TestPyMCWarmupHandling:
     @pytest.mark.parametrize("save_warmup", [False, True])