Merge branch 'master' into dev
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commit
f1020e8169
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@ -66,4 +66,8 @@ Basic examples that illustrate usage of the the framework are in the notebook fo
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"""
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"""
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from risk import deid
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import sys
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if sys.version_info.major == 2:
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from risk import deid
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else:
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from risk.risk import deid
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12
risk/risk.py
12
risk/risk.py
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@ -57,8 +57,10 @@ class deid :
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This function will perform experimentation by performing a random policies (combinations of attributes)
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This function will perform experimentation by performing a random policies (combinations of attributes)
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This function is intended to explore a variety of policies and evaluate their associated risk.
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This function is intended to explore a variety of policies and evaluate their associated risk.
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@param pop|sample data-frame with popublation reference
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:pop|sample data-frame with population or sample reference
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@param id key field that uniquely identifies patient/customer ...
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:field_count number of fields to randomly select
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:strict if set the field_count is exact otherwise field_count is range from 2-field_count
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:num_runs number of runs (by default 5)
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"""
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"""
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pop= args['pop'] if 'pop' in args else None
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pop= args['pop'] if 'pop' in args else None
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@ -76,7 +78,7 @@ class deid :
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sample = args['sample'] if 'sample' in args else pd.DataFrame(self._df)
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sample = args['sample'] if 'sample' in args else pd.DataFrame(self._df)
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k = sample.columns.size if 'field_count' not in args else int(args['field_count']) + 1
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k = sample.columns.size if 'field_count' not in args else int(args['field_count']) +1
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if 'id' in args :
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if 'id' in args :
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id = args['id']
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id = args['id']
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columns = list(set(sample.columns.tolist()) - set([id]))
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columns = list(set(sample.columns.tolist()) - set([id]))
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@ -85,8 +87,10 @@ class deid :
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o = pd.DataFrame()
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o = pd.DataFrame()
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for i in np.arange(RUNS):
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for i in np.arange(RUNS):
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if 'strict' not in args or ('strict' in args and args['strict'] is False):
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n = np.random.randint(2,k)
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n = np.random.randint(2,k)
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else:
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n = args['field_count']
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cols = np.random.choice(columns,n,replace=False).tolist()
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cols = np.random.choice(columns,n,replace=False).tolist()
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params = {'sample':sample,'cols':cols}
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params = {'sample':sample,'cols':cols}
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if pop is not None :
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if pop is not None :
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