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nastasiasnk
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•
b65f10f
1
Parent(s):
e517d5e
Update app.py
Browse files
app.py
CHANGED
@@ -24,14 +24,6 @@ def test(input_json):
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threshold = inputs['input']["threshold"]
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threshold = float(threshold)
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#print("Parsed input keys:", inputs.keys())
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#print("Parsed input values:", inputs.values())
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#sum_list = sum(float(item) for item in inputs["a_list"])
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#multiplication = [-float((inputs["alpha"])) * float(item) for item in inputs["a_list"]]
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#new_df = pd.DataFrame(index=inputs["dataframe"].index, columns=inputs["dataframe"].columns)
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#multiplier_series = pd.Series(float(inputs["a_list"]), index=inputs["dataframe"].index)
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#new_df["new column"] = float(inputs["dataframe"]).mul(multiplier_series, axis=0)
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df_matrix = pd.DataFrame(matrix).T
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df_weights = pd.DataFrame(weights).T
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@@ -46,12 +38,17 @@ def test(input_json):
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subdomainsAccessibility[col] = (decay_factors * destinationWeights[col].values).sum(axis=1)
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#subdomainsAccessibility.drop(columns='commercial', inplace=True)
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return subdomainsAccessibility
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subdomainsAccessibility = computeAccessibility(df_matrix,df_weights,alpha,threshold)
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subdomainsAccessibility_dict = subdomainsAccessibility.to_dict('index')
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# Prepare the output
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output = {
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threshold = inputs['input']["threshold"]
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threshold = float(threshold)
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df_matrix = pd.DataFrame(matrix).T
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df_weights = pd.DataFrame(weights).T
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subdomainsAccessibility[col] = (decay_factors * destinationWeights[col].values).sum(axis=1)
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#subdomainsAccessibility.drop(columns='commercial', inplace=True)
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return subdomainsAccessibility
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subdomainsAccessibility = computeAccessibility(df_matrix,df_weights,alpha,threshold)
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subdomainsAccessibility_dict = subdomainsAccessibility.to_dict('index')
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for key, subdict in data['subdomainsAccessibility_dict'].items():
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ordered = OrderedDict(sorted(subdict.items(), key=lambda x: int(x[0])))
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subdomainsAccessibility_dict['subdomainsAccessibility_dict'][key] = ordered
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# Prepare the output
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output = {
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