Update app.py

app.py

@@ -100,7 +100,7 @@ def test(input_json):
 
 
 
-    """
+
     # List containing the substrings to check against
     tranportModes = ["DRT", "GMT", "HSR"]
     
@@ -112,13 +112,14 @@ def test(input_json):
         for mode in tranportModes:
             if mode in key:  # Check if the substring is in the dictionary key
                 result_dict[substring][key] = value
-    
-
 
     
-    df_transport_matrix = pd.DataFrame(transport_matrix).T
-    df_transport_matrix = df_transport_matrix.round(0).astype(int)    
-    """
+    art = result_dict["DRT"]
+    
+    
+    df_art_matrix = pd.DataFrame(art).T
+    df_art_matrix = df_art_matrix.round(0).astype(int)    
+
     
     # create a mask based on the matrix size and ids, crop activity nodes to the mask
     mask_connected = df_matrix.index.tolist()
@@ -211,9 +212,10 @@ def test(input_json):
     def computeAccessibility (DistanceMatrix, destinationWeights=None,alpha = 0.0038, threshold = 600):
     
         decay_factors = np.exp(-alpha * DistanceMatrix) * (DistanceMatrix <= threshold)
-        subdomainsAccessibility = pd.DataFrame(index=DistanceMatrix.index, columns=destinationWeights.columns)
+        
         # for weighted accessibility (e. g. areas)
         if not destinationWeights.empty:
+        subdomainsAccessibility = pd.DataFrame(index=DistanceMatrix.index, columns=destinationWeights.columns)
             for col in destinationWeights.columns:
                 subdomainsAccessibility[col] = (decay_factors * destinationWeights[col].values).sum(axis=1)
         # for unweighted accessibility (e. g. points of interest)