DM 47944: Fix calibration summary bug in v28

python/lsst/daf/butler/registry/datasets/byDimensions/_manager.py

@@ -327,6 +327,8 @@ def register_dataset_type(self, dataset_type: DatasetType) -> bool:
                     dataset_type.dimensions, dimensions_key, dataset_type.isCalibration()
                 )
                 dynamic_tables.create(self._db, type(self._collections))
+            elif dataset_type.isCalibration() and dynamic_tables.calibs_name is None:
+                dynamic_tables.add_calibs(self._db, type(self._collections))
             row, inserted = self._db.sync(
                 self._static.dataset_type,
                 keys={"name": dataset_type.name},

python/lsst/daf/butler/registry/datasets/byDimensions/tables.py

@@ -531,6 +531,24 @@ def create(self, db: Database, collections: type[CollectionManager]) -> None:
                 makeCalibTableSpec(self._dimensions, collections, db.getTimespanRepresentation()),
             )
 
+    def add_calibs(self, db: Database, collections: type[CollectionManager]) -> None:
+        """Create a calibs table for a dataset type whose dimensions already
+        have a tags table.
+
+        Parameters
+        ----------
+        db : `Database`
+            Database interface.
+        collections : `type` [ `CollectionManager` ]
+            Manager class for collections; used to create foreign key columns
+            for collections.
+        """
+        self.calibs_name = makeCalibTableName(self.dimensions_key)
+        self._calibs_table = db.ensureTableExists(
+            self.calibs_name,
+            makeCalibTableSpec(self._dimensions, collections, db.getTimespanRepresentation()),
+        )
+
     def tags(self, db: Database, collections: type[CollectionManager]) -> sqlalchemy.Table:
         """Return the "tags" table that associates datasets with data IDs in
         TAGGED and RUN collections.

tests/test_simpleButler.py

@@ -823,6 +823,35 @@ def test_clone(self):
         self.assertCountEqual(clone5.registry.defaults.collections, ["imported_r"])
         self.assertEqual(clone5.run, "imported_r")
 
+    def test_calibration_dataset_type_registration(self) -> None:
+        # Register two dataset types that should share the same tags table,
+        # but only one is a calibration and hence needs a calibs table.
+        butler1 = self.makeButler(writeable=True)
+        a = DatasetType("a", ["instrument"], universe=butler1.dimensions, storageClass="StructuredDataDict")
+        b = DatasetType(
+            "b",
+            ["instrument"],
+            universe=butler1.dimensions,
+            storageClass="StructuredDataDict",
+            isCalibration=True,
+        )
+        butler1.registry.registerDatasetType(a)
+        butler1.registry.registerDatasetType(b)
+        self.assertEqual(butler1.get_dataset_type("a"), a)
+        self.assertEqual(butler1.get_dataset_type("b"), b)
+        butler1.registry.refresh()
+        self.assertEqual(butler1.get_dataset_type("a"), a)
+        self.assertEqual(butler1.get_dataset_type("b"), b)
+        # Register them in the opposite order in a new repo.
+        butler2 = self.makeButler(writeable=True)
+        butler2.registry.registerDatasetType(b)
+        butler2.registry.registerDatasetType(a)
+        self.assertEqual(butler2.get_dataset_type("a"), a)
+        self.assertEqual(butler2.get_dataset_type("b"), b)
+        butler2.registry.refresh()
+        self.assertEqual(butler2.get_dataset_type("a"), a)
+        self.assertEqual(butler2.get_dataset_type("b"), b)
+
 
 class DirectSimpleButlerTestCase(SimpleButlerTests, unittest.TestCase):
     """Run tests against DirectButler implementation."""