Update app.py

app.py

@@ -107,14 +107,44 @@ def test(input_json):
     
     # ------------------------- Accessing input data from Grasshopper ------------------------- #
 
+    from imports_utils import getDataFromGrasshopper
+    from config import alpha as alphaDefault
+    from config import threshold as thresholdDefault
     
-
     useGrasshopperData = inputs['input']["useGrasshopperData"]    # fetch grasshoper data or not
     
+    
     if useGrasshopperData == "True": # grasshopper input
+        
+   # fetch grasshoper data or not
+
+        dfMatrix_gh, dfLanduses_gh, attributeMapperDict_gh, landuseMapperDict_gh, alpha, threshold = getDataFromGrasshopper(
+        inputNameMatrix = "matrix",
+        inputNameLanduse = "landuse_areas",
+        inputNameAttributeMapper = "attributeMapperDict",
+        inputNameLanduseMapper = "landuseMapperDict",        
+        inputNameAlpha = "alpha",
+        inputNameThreshold = "threshold"    
+        )
+
+        dfMatrix = dfMatrix_gh
+        dfLanduses = dfLanduses_gh
+
+        if alpha is None:
+            alpha = alphaDefault
+            
+        if threshold is None:
+            threshold = thresholdDefault
+        
+        if useNotionData != True:
+            attributeMapperDict = attributeMapperDict_gh
+            landuseMapperDict = landuseMapperDict_gh
+
+            
+        """
         matrix = inputs['input']["matrix"]
-        landuses = inputs['input']["landuse_areas"]    # fetch grasshoper data or not
-    
+        landuses = inputs['input']["landuse_areas"] 
+        
         dfLanduses = pd.DataFrame(landuses).T
         dfLanduses = dfLanduses.apply(pd.to_numeric, errors='coerce')
         dfLanduses = dfLanduses.replace([np.inf, -np.inf], 0).fillna(0)  # cleaning function?
@@ -124,20 +154,33 @@ def test(input_json):
         dfMatrix = dfMatrix.apply(pd.to_numeric, errors='coerce')
         dfMatrix = dfMatrix.replace([np.inf, -np.inf], 10000).fillna(0)
         dfMatrix = dfMatrix.round(0).astype(int)
-    else:
-        dfLanduses = df_lu.copy()     # fetch speckl data or not
-        dfMatrix = df_dm.copy()
-        
 
-    df_lu_filtered_dict = dfLanduses.to_dict('index')
-    dm_dictionary = dfMatrix.to_dict('index')
+        attributeMapperDict_gh = inputs['input']["attributeMapperDict"]
+        landuseMapperDict_gh = inputs['input']["landuseMapperDict"]        # if fetch notion data or not, def
 
-    attributeMapperDict_gh = inputs['input']["attributeMapperDict"]
-    landuseMapperDict_gh = inputs['input']["landuseMapperDict"]        # if fetch notion data or not, def
+        """
+        
+    else:
 
+        dfMatrix_gh, dfLanduses_gh, attributeMapperDict_gh, landuseMapperDict_gh, alpha, threshold = getDataFromGrasshopper(
+        inputNameMatrix = None,
+        inputNameLanduse = None,
+        inputNameAttributeMapper = None,
+        inputNameLanduseMapper = None,        
+        inputNameAlpha = "alpha",
+        inputNameThreshold = "threshold"    
+        )
 
-    from config import alpha as alphaDefault
-    from config import threshold as thresholdDefault
+        if alpha is None:
+            alpha = alphaDefault
+            
+        if threshold is None:
+            threshold = thresholdDefault
+        
+        dfLanduses = df_lu.copy()     # fetch speckl data or not
+        dfMatrix = df_dm.copy()
+        
+    """   
     
     if not inputs['input']["alpha"]:
         alpha = alphaDefault
@@ -150,6 +193,8 @@ def test(input_json):
     else:
         threshold = inputs['input']["threshold"]
         threshold = float(threshold)
+    """
+
 
     """
     valid_indexes = [idx for idx in mask_connected if idx in dfLanduses.index]
@@ -196,6 +241,8 @@ def test(input_json):
     subdomainsAccessibility_dictionary = subdomainsAccessibility.to_dict('index')
     LivabilitySubdomainsWeights_dictionary = LivabilitySubdomainsWeights.to_dict('index')
     
+    df_lu_filtered_dict = dfLanduses.to_dict('index')
+    dm_dictionary = dfMatrix.to_dict('index')
     """
     # Prepare the output
     output = {