Update app.py

app.py

@@ -42,6 +42,62 @@ def test(input_json):
     df_landuses = df_landuses.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()
+    df_landuses_filtered = df_landuses.loc[mask_connected]
+
+    # find a set of unique domains, to which subdomains are aggregated
+    
+    temp = []
+
+    for key, values in attributeMapperDict.items():
+      domain = attributeMapperDict[key]['domain']
+      for item in domain:
+        if ',' in item:
+          domain_list = item.split(',')
+          attributeMapperDict[key]['domain'] = domain_list
+          for domain in domain_list:
+            temp.append(domain) 
+        else:
+          if item != 0: 
+              temp.append(item)  
+    
+    domainsUnique = list(set(temp))
+
+
+    # find a list of unique subdomains, to which land uses are aggregated
+
+    temp = []
+    
+    for key, values in landuseMapperDict.items():
+      subdomain = str(landuseMapperDict[key])
+      if subdomain != 0: 
+        temp.append(subdomain) 
+        
+    subdomainsUnique = list(set(temp))
+    
+
+    
+    
+    def landusesToSubdomains(DistanceMatrix, LanduseDf, LanduseToSubdomainDict, UniqueSubdomainsList):
+        df_LivabilitySubdomainsArea = pd.DataFrame(0, index=DistanceMatrix.index, columns=UniqueSubdomainsList)
+    
+        for domain in UniqueSubdomainsList:
+            for lu, lu_domain in LanduseToSubdomainDict.items():
+                if lu_domain == domain:
+                    if lu in LanduseDf.columns:
+                        df_LivabilitySubdomainsArea[domain] = df_LivabilitySubdomainsArea[domain].add(LanduseDf[lu], fill_value=0)
+                    else:
+                        print(f"Warning: Column '{lu}' not found in landuse database")
+    
+        return df_LivabilitySubdomainsArea
+
+    
+
+    LivabilitySubdomainsWeights = landusesToSubdomains(df_matrix,df_landuses_filtered,landuseMapperDict,subdomainsUnique)
+    
+
     
     def computeAccessibility (DistanceMatrix,weightsNames, destinationWeights=None,alpha = 0.0038, threshold = 600):
     
@@ -58,7 +114,7 @@ def test(input_json):
         
         return subdomainsAccessibility
     
-    subdomainsAccessibility = computeAccessibility(df_matrix,weightsNames,df_weights,alpha,threshold)
+    subdomainsAccessibility = computeAccessibility(df_matrix,subdomainsUnique,LivabilitySubdomainsWeights,alpha,threshold)
 
     # make a dictionary to output in grasshopper / etc
     subdomainsAccessibility_dictionary = subdomainsAccessibility.to_dict('index')
@@ -69,30 +125,14 @@ def test(input_json):
 
 
     
-    def accessibilityToLivability (DistanceMatrix,subdomainsAccessibility, SubdomainAttributeDict):
+    def accessibilityToLivability (DistanceMatrix,subdomainsAccessibility, SubdomainAttributeDict,UniqueDomainsList):
     
         livability = pd.DataFrame(index=DistanceMatrix.index, columns=subdomainsAccessibility.columns)
         livability.fillna(0, inplace=True)
         
-        # find a set of unique domains, to which subdomains are aggregated
-        
-        temp = []
-    
-        for key, values in SubdomainAttributeDict.items():
-          domain = SubdomainAttributeDict[key]['domain']
-          for item in domain:
-            if ',' in item:
-              domain_list = item.split(',')
-              SubdomainAttributeDict[key]['domain'] = domain_list
-              for domain in domain_list:
-                temp.append(domain) 
-            else:
-              if item != 0: 
-                  temp.append(item)  
         
-        domainsUnique = list(set(temp))
              
-        for domain in domainsUnique:
+        for domain in UniqueDomainsList:
             livability[domain] = 0
     
     
@@ -119,7 +159,7 @@ def test(input_json):
     
     
 
-    livability = accessibilityToLivability(df_matrix,subdomainsAccessibility,attributeMapperDict)
+    livability = accessibilityToLivability(df_matrix,subdomainsAccessibility,attributeMapperDict,domainsUnique)
     livability_dictionary = livability.to_dict('index')