Update app.py

app.py

@@ -78,9 +78,11 @@ else:
     df_lu =  df_lu.set_index("ids", drop=False)
     
     df_dm = matrices[distanceMatrixActivityNodes]
-    df_dm_transport = matrices[distanceMatrixTransportStops]
+    dfMatrix = dfMatrix.round(0).astype(int)
+    
+    #df_dm_transport = matrices[distanceMatrixTransportStops]
     dm_dictionary = df_dm.to_dict('index')
-    df_dm_transport_dictionary = df_dm_transport.to_dict('index')
+    #df_dm_transport_dictionary = df_dm_transport.to_dict('index')
     
     # filter activity nodes attributes
     mask_connected = df_dm.index.tolist()
@@ -92,6 +94,8 @@ else:
     df_lu_filtered = df_lu[lu_columns].loc[mask_connected]
     df_lu_filtered.columns = [col.replace('lu+', '') for col in df_lu_filtered.columns]
     df_lu_filtered.columns = [col.replace('ASSETS+', '') for col in df_lu_filtered.columns]
+    
+    df_lu_filtered = df_lu_filtered.apply(pd.to_numeric, errors='coerce')
     df_lu_filtered = df_lu_filtered.astype(int)
     df_lu_filtered = df_lu_filtered.T.groupby(level=0).sum().T
     
@@ -118,16 +122,18 @@ def test(input_json):
         landuses = inputs['input']["landuse_areas"]    
     
         dfLanduses = pd.DataFrame(landuses).T
+        dfLanduses = dfLanduses.apply(pd.to_numeric, errors='coerce')
         dfLanduses = dfLanduses.round(0).astype(int)
 
         dfMatrix = pd.DataFrame(matrix).T
+        dfMatrix = dfMatrix.apply(pd.to_numeric, errors='coerce')
         dfMatrix = dfMatrix.round(0).astype(int)
     else:
         dfLanduses = df_lu_filtered.copy()
-        dfLanduses = dfLanduses.round(0).astype(int)
+        #dfLanduses = dfLanduses.round(0).astype(int)
         
         dfMatrix = df_dm.copy()
-        dfMatrix = dfMatrix.round(0).astype(int)
+        
     
 
     attributeMapperDict_gh = inputs['input']["attributeMapperDict"]