Update imports_utils.py

imports_utils.py

@@ -307,4 +307,41 @@ def remap(value, B_min, B_max, C_min, C_max):
 
 
 
+def accessibilityToLivability (DistanceMatrix,accessibilityInputs, SubdomainAttributeDict,UniqueDomainsList):
+    livability = pd.DataFrame(index=DistanceMatrix.index, columns=accessibilityInputs.columns)
+                         
+    for domain in UniqueDomainsList:
+        livability[domain] = 0
+        
+    livability.fillna(0, inplace=True)
+    templist = []
+    # remap accessibility to livability points
+    
+    for key, values in SubdomainAttributeDict.items():
+        threshold = float(SubdomainAttributeDict[key]['thresholds'])
+        max_livability = float(SubdomainAttributeDict[key]['max_points'])
+        domains = [str(item) for item in SubdomainAttributeDict[key]['domain']]
+    
+        if key in accessibilityInputs.columns and key != 'commercial':
+            livability_score = remap(accessibilityInputs[key], 0, threshold, 0, max_livability)
+            livability.loc[accessibilityInputs[key] >= threshold, key] = max_livability
+            livability.loc[accessibilityInputs[key] < threshold, key] = livability_score          
+            if any(domains):
+                for domain in domains:
+                    if domain != 'Workplaces':
+                        livability.loc[accessibilityInputs[key] >= threshold, domain] += max_livability
+                        livability.loc[accessibilityInputs[key] < threshold, domain] += livability_score
+                                            
+        elif key == 'commercial':
+            livability_score = remap(accessibilityInputs['jobs'], 0, threshold, 0, max_livability)
+            livability.loc[accessibilityInputs['jobs'] >= threshold, domains[0]] = max_livability
+            livability.loc[accessibilityInputs['jobs'] < threshold, domains[0]] = livability_score
+
+    
+    return livability
+
+
+
+
+