nastasiasnk commited on
Commit
6eedbd5
1 Parent(s): 0fc8c61

Update app.py

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Files changed (1) hide show
  1. app.py +14 -14
app.py CHANGED
@@ -217,40 +217,40 @@ def test(input_json):
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  def accessibilityToLivability (DistanceMatrix,subdomainsAccessibility, SubdomainAttributeDict,UniqueDomainsList):
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  livability = pd.DataFrame(index=DistanceMatrix.index, columns=subdomainsAccessibility.columns)
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- livability.drop(columns='jobs', inplace=True)
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- livability["Workplaces"] = 0
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  livability.fillna(0, inplace=True)
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  for domain in UniqueDomainsList:
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  livability[domain] = 0
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-
 
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  # remap accessibility to livability points
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  for key, values in SubdomainAttributeDict.items():
 
 
 
 
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  if key == 'commercial':
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- threshold = float(SubdomainAttributeDict[key]['thresholds'])
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- max_livability = float(SubdomainAttributeDict[key]['max_points'])
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  livability_score = remap(subdomainsAccessibility['jobs'], 0, threshold, 0, max_livability)
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  livability.loc[subdomainsAccessibility['jobs'] >= threshold, 'Workplaces'] = max_livability
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  livability.loc[subdomainsAccessibility['jobs'] < threshold, 'Workplaces'] = livability_score
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- elif key in subdomainsAccessibility.columns and key != 'commercial':
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- domain = [str(item) for item in SubdomainAttributeDict[key]['domain']]
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- threshold = float(SubdomainAttributeDict[key]['thresholds'])
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- max_livability = float(SubdomainAttributeDict[key]['max_points'])
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- sqm_per_employee = SubdomainAttributeDict[key]['sqmPerEmpl']
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-
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  livability_score = remap(subdomainsAccessibility[key], 0, threshold, 0, max_livability)
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  livability.loc[subdomainsAccessibility[key] >= threshold, key] = max_livability
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  livability.loc[subdomainsAccessibility[key] < threshold, key] = livability_score
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  if any(domain):
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  for item in domain:
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- if domain != 'Workplaces':
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- livability.loc[subdomainsAccessibility[key] >= threshold, item] += max_livability
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- livability.loc[subdomainsAccessibility[key] < threshold, item] += livability_score
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  return livability
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  def accessibilityToLivability (DistanceMatrix,subdomainsAccessibility, SubdomainAttributeDict,UniqueDomainsList):
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  livability = pd.DataFrame(index=DistanceMatrix.index, columns=subdomainsAccessibility.columns)
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+ #livability.drop(columns='jobs', inplace=True)
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+ #livability["Workplaces"] = 0
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  livability.fillna(0, inplace=True)
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  for domain in UniqueDomainsList:
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  livability[domain] = 0
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+
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+ livability.drop(columns='Workplaces', inplace=True)
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  # remap accessibility to livability points
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  for key, values in SubdomainAttributeDict.items():
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+ threshold = float(SubdomainAttributeDict[key]['thresholds'])
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+ max_livability = float(SubdomainAttributeDict[key]['max_points'])
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+ domain = [str(item) for item in SubdomainAttributeDict[key]['domain']]
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+ """
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  if key == 'commercial':
 
 
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  livability_score = remap(subdomainsAccessibility['jobs'], 0, threshold, 0, max_livability)
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  livability.loc[subdomainsAccessibility['jobs'] >= threshold, 'Workplaces'] = max_livability
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  livability.loc[subdomainsAccessibility['jobs'] < threshold, 'Workplaces'] = livability_score
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+ """
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+ if key in subdomainsAccessibility.columns:
 
 
 
 
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  livability_score = remap(subdomainsAccessibility[key], 0, threshold, 0, max_livability)
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  livability.loc[subdomainsAccessibility[key] >= threshold, key] = max_livability
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  livability.loc[subdomainsAccessibility[key] < threshold, key] = livability_score
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  if any(domain):
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  for item in domain:
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+ livability.loc[subdomainsAccessibility[key] >= threshold, item] += max_livability
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+ livability.loc[subdomainsAccessibility[key] < threshold, item] += livability_score
 
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+ livability = livability.rename(columns={'jobs': 'Workplaces'})
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+
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  return livability
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