diff --git a/emission/analysis/modelling/trip_model/mapping.py b/emission/analysis/modelling/trip_model/mapping.py
index cd2d11766..06f0614ea 100644
--- a/emission/analysis/modelling/trip_model/mapping.py
+++ b/emission/analysis/modelling/trip_model/mapping.py
@@ -6,8 +6,8 @@
 import branca.element as bre
 from scipy.spatial import ConvexHull
 
-import data_wrangling
-from clustering import add_loc_clusters, ALG_OPTIONS
+import emission.analysis.modelling.trip_model.data_wrangling as eamtd
+from emission.analysis.modelling.trip_model.clustering import add_loc_clusters, ALG_OPTIONS
 
 DENVER_COORD = [39.7392, -104.9903]
 MTV_COORD = [37.3861, -122.0839]
@@ -109,7 +109,7 @@ def find_plot_clusters(user_df,
 
     # expand the 'start_loc' and 'end_loc' column into 'start_lat',
     # 'start_lon', 'end_lat', and 'end_lon' columns
-    all_trips_df = data_wrangling.expand_coords(all_trips_df)
+    all_trips_df = eamtd.expand_coords(all_trips_df)
 
     labeled_trips_df = all_trips_df.loc[all_trips_df.user_input != {}].dropna(
         subset=['purpose_confirm'])
diff --git a/emission/analysis/modelling/trip_model/models.py b/emission/analysis/modelling/trip_model/models.py
index f3026b6b8..e5fc08b46 100644
--- a/emission/analysis/modelling/trip_model/models.py
+++ b/emission/analysis/modelling/trip_model/models.py
@@ -16,8 +16,8 @@
 from sklearn.exceptions import NotFittedError
 
 # our imports
-from clustering import get_distance_matrix, single_cluster_purity
-import data_wrangling
+from emission.analysis.modelling.trip_model.clustering import get_distance_matrix, single_cluster_purity
+import emission.analysis.modelling.trip_model.data_wrangling as eamtd
 import emission.storage.decorations.trip_queries as esdtq
 from emission.analysis.classification.inference.labels.inferrers import predict_cluster_confidence_discounting
 import emission.core.wrapper.entry as ecwe
@@ -28,7 +28,7 @@
 import emission.analysis.modelling.trip_model.run_model as eamur
 
 
-import clustering
+import emission.analysis.modelling.trip_model.clustering as eamtc
 # NOTE: tour_model_extended.similarity is on the
 # eval-private-data-compatibility branch in e-mission-server
 
@@ -82,7 +82,7 @@ def _clean_data(self, df):
 
         # expand the 'start_loc' and 'end_loc' column into 'start_lat',
         # 'start_lon', 'end_lat', and 'end_lon' columns
-        df = data_wrangling.expand_coords(df)
+        df = eamtd.expand_coords(df)
 
         # drop trips with missing coordinates
         if df.start_lat.isna().any():
@@ -334,7 +334,7 @@ def fit(self, unused,train_entry_list=None):
           
         # fit the bins
         self.sim_model= eamtg.GreedySimilarityBinning(model_config)
-        cleaned_trip_entry= clustering.cleanEntryTypeData(self.train_df,train_entry_list)
+        cleaned_trip_entry= eamtc.cleanEntryTypeData(self.train_df,train_entry_list)
         self.sim_model.fit(cleaned_trip_entry)
 
         labels = [int(l) for l in self.sim_model.tripLabels]