diff --git a/src/spyglass/behavior/v1/moseq.py b/src/spyglass/behavior/v1/moseq.py
index f838976ce..e683596a5 100644
--- a/src/spyglass/behavior/v1/moseq.py
+++ b/src/spyglass/behavior/v1/moseq.py
@@ -193,19 +193,37 @@ def make(self, key):
             }
         )
 
-    def _make_model_name(self, key: dict = None):
+    def _make_model_name(self, key: dict):
         # make a unique model name based on the key
-        if key is None:
-            key = {}
         key = (MoseqModelSelection & key).fetch1("KEY")
         return dj.hash.key_hash(key)
 
     @staticmethod
     def _initialize_model(
-        data, metadata, project_dir, model_name, config, model_params
+        data: dict,
+        metadata: tuple,
+        project_dir: str,
+        model_name: str,
+        config: dict,
+        model_params: dict,
     ):
         """Method to initialize a model. Creates model and runs initional ARHMM fit
 
+        Parameters
+        ----------
+        data : dict
+            data dictionary (get from kpms.format_data)
+        metadata : tuple
+            metadata tuple (get from kpms.format_data)
+        project_dir : str
+            path to the project directory
+        model_name : str
+            name of the model
+        config : dict
+            keypoint moseq config
+        model_params : dict
+            params dictionary fetched from spyglass parameter table entry
+
         Returns
         -------
         tuple
@@ -229,20 +247,20 @@ def _initialize_model(
             model_name=model_name + "_ar",
         )
 
-    def analyze_pca(self, key: dict = None):
+    def analyze_pca(self, key: dict, explained_variace: float = 0.9):
         """Method to analyze the PCA of a model
 
         Parameters
         ----------
         key : dict
             key to a single MoseqModel table entry
+        explained_variace : float, optional
+            minimum explained variance to print, by default 0.9
         """
-        if key is None:
-            key = {}
         project_dir = (self & key).fetch1("project_dir")
         pca = kpms.load_pca(project_dir)
         config = kpms.load_config(project_dir)
-        kpms.print_dims_to_explain_variance(pca, 0.9)
+        kpms.print_dims_to_explain_variance(pca, explained_variace)
         kpms.plot_scree(pca, project_dir=project_dir)
         kpms.plot_pcs(pca, project_dir=project_dir, **config)
 
@@ -280,8 +298,9 @@ def get_training_progress_path(self, key: dict = None):
         """
         if key is None:
             key = {}
-        project_dir = (self & key).fetch1("project_dir")
-        model_name = (self & key).fetch1("model_name")
+        project_dir, model_name = (self & key).fetch1(
+            "project_dir", "model_name"
+        )
         return f"{project_dir}/{model_name}/fitting_progress.pdf"
 
 
@@ -306,7 +325,9 @@ def validate_bodyparts(self, key):
         model_bodyparts = (PoseGroup & key).fetch1("bodyparts")
         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
+        data_bodyparts = MoseqSyllable.get_bodyparts_from_dataframe(
+            bodyparts_df
+        )
 
         missing = [bp for bp in model_bodyparts if bp not in data_bodyparts]
         if missing:
@@ -338,11 +359,11 @@ def make(self, key):
         # load data and format for moseq
         merge_query = PositionOutput & merge_key
         video_path = merge_query.fetch_video_path()
-        video_name = Path(video_path).stem + ".mp4"
+        video_name = Path(video_path).name
         bodyparts_df = merge_query.fetch_pose_dataframe()
 
         if bodyparts is None:
-            bodyparts = bodyparts_df.keys().get_level_values(0).unique().values
+            bodyparts = self.get_bodyparts_from_dataframe(bodyparts_df)
         datasets = {video_name: bodyparts_df[bodyparts]}
         coordinates, confidences = format_dataset_for_moseq(datasets, bodyparts)
         data, metadata = kpms.format_data(coordinates, confidences, **config)
@@ -379,3 +400,19 @@ def fetch1_dataframe(self):
         dataframe = self.fetch_nwb()[0]["moseq"]
         dataframe.set_index("time", inplace=True)
         return dataframe
+
+    @staticmethod
+    def get_bodyparts_from_dataframe(dataframe):
+        """Method to get the list of bodyparts from a dataframe
+
+        Parameters
+        ----------
+        dataframe : pd.DataFrame
+            dataframe with bodypart data from PositionOutput
+
+        Returns
+        -------
+        List[str]
+            list of bodyparts
+        """
+        return dataframe.keys().get_level_values(0).unique().values