consistent usage of propagator_class across precovery fns

precovery/main.py

@@ -23,7 +23,7 @@ def precover_many(
     allow_version_mismatch: bool = False,
     datasets: Optional[set[str]] = None,
     n_workers: int = multiprocessing.cpu_count(),
-    propagator: Optional[Type[Propagator]] = None,
+    propagator_class: Optional[Type[Propagator]] = None,
 ) -> Tuple[PrecoveryCandidates, FrameCandidates]:
     """
     Run a precovery search algorithm against many orbits at once.
@@ -38,7 +38,7 @@ def precover_many(
             window_size,
             allow_version_mismatch,
             datasets,
-            propagator,
+            propagator_class,
         )
         for o in orbits
     ]
@@ -72,14 +72,13 @@ def precover_worker(
     window_size: int = 7,
     allow_version_mismatch: bool = False,
     datasets: Optional[set[str]] = None,
-    propagator: Optional[Type[Propagator]] = None,
+    propagator_class: Optional[Type[Propagator]] = None,
 ) -> Tuple[PrecoveryCandidates, FrameCandidates]:
     """
     Wraps the precover function to return the orbit_id for mapping.
     """
 
     # initialize our propagator
-    propagator_instance = propagator() if propagator is not None else None
     precovery_candidates, frame_candidates = precover(
         orbit,
         database_directory,
@@ -89,7 +88,7 @@ def precover_worker(
         window_size,
         allow_version_mismatch,
         datasets,
-        propagator=propagator_instance,
+        propagator_class=propagator_class,
     )
 
     return (
@@ -107,7 +106,7 @@ def precover(
     window_size: int = 7,
     allow_version_mismatch: bool = False,
     datasets: Optional[set[str]] = None,
-    propagator: Optional[Type[Propagator]] = None,
+    propagator_class: Optional[Type[Propagator]] = None,
 ) -> Tuple[PrecoveryCandidates, FrameCandidates]:
     """
     Connect to database directory and run precovery for the input orbit.
@@ -138,7 +137,7 @@ def precover(
         Allows using a precovery db version that does not match the library version.
     datasets : set[str], optional
         Filter down searches to only scan selected datasets
-    propagator : Type[Propagator], optional
+    propagator_class : Type[Propagator], optional
         An adam_core.propagator.Propagator subclass to use for propagating the orbit.
 
     Returns
@@ -163,7 +162,7 @@ def precover(
         end_mjd=end_mjd,
         window_size=window_size,
         datasets=datasets,
-        propagator=propagator,
+        propagator_class=propagator_class,
     )
 
     return precovery_candidates, frame_candidates

precovery/precovery_db.py

@@ -411,7 +411,7 @@ def precover(
         end_mjd: Optional[float] = None,
         window_size: int = 7,
         datasets: Optional[set[str]] = None,
-        propagator: Optional[Type[Propagator]] = None,
+        propagator_class: Optional[Type[Propagator]] = None,
     ) -> Tuple[PrecoveryCandidates, FrameCandidates]:
         """
         Find observations which match orbit in the database. Observations are
@@ -446,10 +446,10 @@ def precover(
                         yield match
         """
 
-        if propagator is None:
+        if propagator_class is None:
             raise ValueError("A propagator must be provided to run precovery")
 
-        propagator_instance = propagator()
+        propagator_instance = propagator_class()
         orbit_id = orbit.orbit_id[0].as_py()
 
         if datasets is not None:

scripts/precovery-test.py

@@ -22,8 +22,6 @@
 
 if __name__ == "__main__":
 
-    propagator = ASSISTPropagator()
-
     parser = argparse.ArgumentParser(
         description="Run precovery using test_orbits.csv in this directory"
     )
@@ -57,7 +55,9 @@
         # Select a single orbit
         orbit = orbits[i]
 
-        candidates, frame_candidates = db.precover(orbit, tolerance=1 / 3600)
+        candidates, frame_candidates = db.precover(
+            orbit, tolerance=1 / 3600, propagator_class=ASSISTPropagator
+        )
 
         print(
             f"Found {len(candidates)} potential matches for orbit ID: {orbit.object_id[0].as_py()}"

tests/test_precovery_index.py

@@ -79,7 +79,7 @@ def test_precovery(test_db_dir):
             test_db_dir,
             tolerance=1 / 3600,
             window_size=1,
-            propagator=ASSISTPropagator(),
+            propagator_class=ASSISTPropagator,
         )
 
         object_observations = observations_df[

tests/test_precovery_search.py

@@ -29,7 +29,7 @@ def test_precover(precovery_db, sample_orbits):
     precovery_db.frames.add_frames(ds_id, frames)
 
     # Do the search. We should find the three observations we inserted.
-    matches, misses = precovery_db.precover(orbit, propagator=ASSISTPropagator())
+    matches, misses = precovery_db.precover(orbit, propagator_class=ASSISTPropagator)
     assert len(matches) == 3
     assert len(misses) == 0
 
@@ -41,7 +41,6 @@ def test_precover(precovery_db, sample_orbits):
 @requires_jpl_ephem_data
 def test_precover_dataset_filter(precovery_db, sample_orbits):
     # Make two datasets which contain something we're looking for.
-    propagator = ASSISTPropagator()
 
     orbit = sample_orbits[0]
     timestamps = [50000.0, 50001.0, 50002.0]
@@ -62,7 +61,7 @@ def test_precover_dataset_filter(precovery_db, sample_orbits):
 
     # Do the search with no dataset filters. We should find all six
     # observations we inserted.
-    matches, misses = precovery_db.precover(orbit, propagator=propagator)
+    matches, misses = precovery_db.precover(orbit, propagator_class=ASSISTPropagator)
     assert len(matches) == 6
 
     have_ids = set(matches.observation_id.to_pylist())
@@ -72,7 +71,9 @@ def test_precover_dataset_filter(precovery_db, sample_orbits):
     # Now repeat the search, but filter to just one dataset. We should
     # only find that dataset's observations.
     matches, misses = list(
-        precovery_db.precover(orbit, datasets={ds1_id}, propagator=propagator)
+        precovery_db.precover(
+            orbit, datasets={ds1_id}, propagator_class=ASSISTPropagator
+        )
     )
     assert len(matches) == 3