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nastasiasnk
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•
68472bb
1
Parent(s):
0fdf9da
Update app.py
Browse files
app.py
CHANGED
@@ -171,7 +171,7 @@ def test(input_json):
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# Apply the filtered mask
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df_landuses_filtered = df_landuses.loc[valid_indexes]
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# find a set of unique domains, to which subdomains are aggregated
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temp = []
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for key, values in livabilityMapperDict.items():
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@@ -188,16 +188,20 @@ def test(input_json):
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domainsUnique = list(set(temp))
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# find a list of unique subdomains, to which land uses are aggregated
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temp = []
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for key, values in landuseMapperDict.items():
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subdomain = str(landuseMapperDict[key])
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if subdomain != 0:
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temp.append(subdomain)
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subdomainsUnique = list(set(temp))
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from imports_utils import landusesToSubdomains
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from imports_utils import FindWorkplacesNumber
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@@ -216,7 +220,7 @@ def test(input_json):
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# prepare an input weights dataframe for the parameter LivabilitySubdomainsInputs
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LivabilitySubdomainsInputs =pd.concat([LivabilitySubdomainsWeights, WorkplacesNumber], axis=1)
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subdomainsAccessibility = computeAccessibility(df_dm,LivabilitySubdomainsInputs,alpha,threshold)
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artAccessibility = computeAccessibility_pointOfInterest(df_art_matrix,'ART',alpha,threshold)
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gmtAccessibility = computeAccessibility_pointOfInterest(df_gmt_matrix,'GMT+HSR',alpha,threshold)
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@@ -236,17 +240,17 @@ def test(input_json):
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artmatrix = df_art_matrix.to_dict('index')
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LivabilitySubdomainsWeights_dictionary = LivabilitySubdomainsWeights.to_dict('index')
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# Prepare the output
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output = {
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"subdomainsWeights_dictionary": LivabilitySubdomainsInputs_dictionary,
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"luDomainMapper": landuseMapperDict,
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"attributeMapper": livabilityMapperDict
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}
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# Apply the filtered mask
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df_landuses_filtered = df_landuses.loc[valid_indexes]
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"""
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# find a set of unique domains, to which subdomains are aggregated
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temp = []
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for key, values in livabilityMapperDict.items():
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domainsUnique = list(set(temp))
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# find a list of unique subdomains, to which land uses are aggregated
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temp = []
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for key, values in landuseMapperDict.items():
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subdomain = str(landuseMapperDict[key]["subdomain livability"])
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if subdomain != 0:
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temp.append(subdomain)
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subdomainsUnique = list(set(temp))
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"""
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domainsUnique = findUniqueDomains(livabilityMapperDict)
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subdomainsUnique = findUniqueSubdomains(landuseMapperDict)
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from imports_utils import landusesToSubdomains
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from imports_utils import FindWorkplacesNumber
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# prepare an input weights dataframe for the parameter LivabilitySubdomainsInputs
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LivabilitySubdomainsInputs =pd.concat([LivabilitySubdomainsWeights, WorkplacesNumber], axis=1)
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subdomainsAccessibility = computeAccessibility(df_dm,LivabilitySubdomainsInputs,alpha,threshold)
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artAccessibility = computeAccessibility_pointOfInterest(df_art_matrix,'ART',alpha,threshold)
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gmtAccessibility = computeAccessibility_pointOfInterest(df_gmt_matrix,'GMT+HSR',alpha,threshold)
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artmatrix = df_art_matrix.to_dict('index')
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LivabilitySubdomainsWeights_dictionary = LivabilitySubdomainsWeights.to_dict('index')
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# Prepare the output
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output = {
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"subdomainsAccessibility_dictionary": subdomainsAccessibility_dictionary,
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"livability_dictionary": livability_dictionary,
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"subdomainsWeights_dictionary": LivabilitySubdomainsInputs_dictionary,
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"luDomainMapper": landuseMapperDict,
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"attributeMapper": livabilityMapperDict,
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"fetchDm": dm_dictionary,
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"landuses":df_lu_filtered_dict
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}
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