Apply suggestions from code review

Co-authored-by: Chris Broz <[email protected]>

src/spyglass/behavior/core.py

@@ -44,7 +44,7 @@ def create_group(
             body parts to include in the group, by default None includes all from every set
         """
         group_key = {
-            "pose_group_name": group_name,
+            "pose_group_name": group_name
         }
         if self & group_key:
             warnings.warn(
@@ -55,16 +55,14 @@ def create_group(
             {
                 **group_key,
                 "bodyparts": bodyparts,
-            },
-            skip_duplicates=True,
+            }
         )
         for merge_id in merge_ids:
             self.Pose.insert1(
                 {
                     **group_key,
                     "pose_merge_id": merge_id,
-                },
-                skip_duplicates=True,
+                }
             )
 
     def fetch_pose_datasets(

src/spyglass/behavior/moseq.py

@@ -15,7 +15,7 @@
 
 
 @schema
-class MoseqModelParams(SpyglassMixin, dj.Manual):
+class MoseqModelParams(SpyglassMixin, dj.Lookup):
     definition = """
     model_params_name: varchar(80)
     ---
@@ -49,8 +49,7 @@ def make_training_extension_params(
         """
         model_key = (MoseqModel & model_key).fetch1("KEY")
         model_params = (self & model_key).fetch1("model_params")
-        model_params["num_epochs"] = num_epochs
-        model_params["initial_model"] = model_key
+        model_params.update({"num_epochs":num_epochs, "initial_model":model_key})
         # increment param name
         if new_name is None:
             # increment the extension number
@@ -76,6 +75,7 @@ def make_training_extension_params(
 
 @schema
 class MoseqModelSelection(SpyglassMixin, dj.Manual):
+    """Pairing of PoseGroup and moseq model params for training"""
     definition = """
     -> PoseGroup
     -> MoseqModelParams
@@ -257,8 +257,7 @@ def fetch_model(self, key: dict = None):
         if key is None:
             key = {}
         return kpms.load_checkpoint(
-            (self & key).fetch1("project_dir"),
-            (self & key).fetch1("model_name"),
+            *(self & key).fetch1("project_dir", "model_name")
         )[0]
 
     def get_training_progress_path(self, key: dict = None):
@@ -303,11 +302,12 @@ def validate_bodyparts(self, key):
         merge_key = {"merge_id": key["pose_merge_id"]}
         bodyparts_df = (PositionOutput & merge_key).fetch_pose_dataframe()
         data_bodyparts = bodyparts_df.keys().get_level_values(0).unique().values
-        for bodypart in model_bodyparts:
-            if bodypart not in data_bodyparts:
-                raise ValueError(
-                    f"Error in row {key}: " + f"Bodypart {bodypart} not in data"
-                )
+
+        missing = [bp for bp in model_bodyparts if bp not in data_bodyparts]
+        if missing:
+            raise ValueError(
+                f"PositionOutput missing bodypart(s) for {key}: {missing}"
+            )
 
 
 @schema
@@ -321,18 +321,18 @@ class MoseqSyllable(SpyglassMixin, dj.Computed):
 
     def make(self, key):
         model = MoseqModel().fetch_model(key)
-        project_dir = (MoseqModel & key).fetch1("project_dir")
+        project_dir, model_name = (MoseqModel & key).fetch1("project_dir", "model_name")
 
         merge_key = {"merge_id": key["pose_merge_id"]}
         bodyparts = (PoseGroup & key).fetch1("bodyparts")
         config = MoseqModel()._config_func(project_dir)
-        model_name = (MoseqModel & key).fetch1("model_name")
         num_iters = (MoseqSyllableSelection & key).fetch1("num_iters")
 
         # load data and format for moseq
-        video_path = (PositionOutput & merge_key).fetch_video_path()
+        merge_query = PositionOutput & merge_key
+        video_path = merge_query.fetch_video_path()
         video_name = Path(video_path).stem + ".mp4"
-        bodyparts_df = (PositionOutput & merge_key).fetch_pose_dataframe()
+        bodyparts_df = merge_query.fetch_pose_dataframe()
 
         if bodyparts is None:
             bodyparts = bodyparts_df.keys().get_level_values(0).unique().values