Update imports_utils.py

imports_utils.py

@@ -174,36 +174,56 @@ def fetchSubdomainMapper (livabilityAttributePages):
 
 
                 
-def fetchDistanceMatrices (stream_distance_matrices):
+def fetchDistanceMatrices (streamObj):
+
+    matrices = {}
+    isDict = False
+ 
+    try:
+        data_part = streamObj["@Data"]["@{0}"]
+        for matrix in data_part:
+            # Find the matrix name
+            matrix_name = next((attr for attr in dir(matrix) if "matrix" in attr), None)
+ 
+            if not matrix_name:
+                continue
+ 
+            matrix_data = getattr(matrix, matrix_name)
+            originUUID = matrix_data["@originUUID"]
+            destinationUUID = matrix_data["@destinationUUID"]
+ 
+            processed_rows = []
+            for chunk in matrix_data["@chunks"]:
+                for row in chunk["@rows"]:
+                    processed_rows.append(row["@row"])
+ 
+            matrix_array = np.array(processed_rows)
+            matrix_df = pd.DataFrame(matrix_array, index=originUUID, columns=destinationUUID)
+            matrices[matrix_name] = matrix_df
+    except KeyError:
+        data_part = streamObj["@Data"].__dict__
+        print(data_part.keys())
+ 
+        for k, v in data_part.items():
+            if "matrix" in k:
+                matrix_name = k
+                matrix_data = v
+                originUUID = matrix_data["@originUUID"]
+                destinationUUID = matrix_data["@destinationUUID"]
+ 
+                processed_rows = []
+                for chunk in matrix_data["@chunks"]:
+                    for row in chunk["@rows"]:
+                        processed_rows.append(row["@row"])
+ 
+                matrix_array = np.array(processed_rows)
+                matrix_df = pd.DataFrame(matrix_array, index=originUUID, columns=destinationUUID)
+                matrices[matrix_name] = matrix_df
+ 
+    return matrices
 
-    nested_list = []
-    
-    # navigate to list with speckle objects of interest
-    distance_matrices = {}
-    for distM in stream_distance_matrices["@Data"]['@{0}']:
-      for kk in distM.__dict__.keys():
-        try:
-          if kk.split("+")[1].startswith("distance_matrix"):
-            distance_matrix_dict = json.loads(distM[kk])
-            origin_ids = distance_matrix_dict["origin_uuid"]
-            destination_ids = distance_matrix_dict["destination_uuid"]
-            distance_matrix =  distance_matrix_dict["matrix"]
-            # Convert the distance matrix to a DataFrame
-            chunks =  distance_matrix_dict["chunks"]
-            for chunk in chunks:
-                for row_obj in chunk['@rows']:
-                    row = row_obj['@row']
-                    nested_list.append(row)
-            
-            df_distances = pd.DataFrame(distance_matrix, index=origin_ids, columns=destination_ids)
-    
-            # i want to add the index & colum names to dist_m_csv
-            #distance_matrices[kk]  = dist_m_csv[kk]
-            distance_matrices[kk] = df_distances
-        except:
-          pass
 
-    return distance_matrices
+    
     
 """