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Fix error with pandas dataframes in _columns_different_distributions + add appropriate test

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Signed-off-by: abigailt <abigailt@il.ibm.com>
This commit is contained in:
abigailt 2024-02-13 10:48:56 +02:00
parent cb70ca10e6
commit 90980de234
2 changed files with 11 additions and 19 deletions
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27
apt/risk/data_assessment/attack_strategy_utils.py
View file

@ -169,26 +169,15 @@ class KNNAttackStrategyUtils(AttackStrategyUtils):
differing_columns = []
df1_samples = df1.get_samples()
df2_samples = df2.get_samples()
if df1.is_pandas:
for name, _ in df1_samples.items():
is_categorical = name in categorical_features or is_categorical_dtype(df1_samples.dtypes[name])
is_numeric = is_numeric_dtype(df1_samples.dtypes[name])
KNNAttackStrategyUtils._column_statistical_test(df1_samples[name], df2_samples[name], name,
is_categorical, is_numeric,
self.distribution_comparison_numeric_test,
self.distribution_comparison_categorical_test,
self.distribution_comparison_alpha,
differing_columns)
else:
is_numeric = np.issubdtype(df1_samples.dtype, int) or np.issubdtype(df1_samples.dtype, float)
is_numeric = np.issubdtype(df1_samples.dtype, int) or np.issubdtype(df1_samples.dtype, float)
for i, column in enumerate(df1_samples.T):
is_categorical = i in categorical_features
KNNAttackStrategyUtils._column_statistical_test(df1_samples[:, i], df2_samples[:, i], i,
is_categorical, is_numeric,
self.distribution_comparison_numeric_test,
self.distribution_comparison_categorical_test,
self.distribution_comparison_alpha, differing_columns)
for i, column in enumerate(df1_samples.T):
is_categorical = i in categorical_features
KNNAttackStrategyUtils._column_statistical_test(df1_samples[:, i], df2_samples[:, i], i,
is_categorical, is_numeric,
self.distribution_comparison_numeric_test,
self.distribution_comparison_categorical_test,
self.distribution_comparison_alpha, differing_columns)
return differing_columns
def validate_distributions(self, original_data_members: ArrayDataset, original_data_non_members: ArrayDataset,

3
tests/test_data_assessment_short_test.py
View file

@ -1,3 +1,4 @@
import pandas as pd
import pytest
from apt.anonymization import Anonymize
@ -52,6 +53,8 @@ def test_risk_anonymization(name, data, dataset_type, mgr):
categorical_features = []
elif "nursery" in name:
preprocessed_x_train, preprocessed_x_test, categorical_features = preprocess_nursery_x_data(x_train, x_test)
preprocessed_x_train = pd.DataFrame(preprocessed_x_train)
preprocessed_x_test = pd.DataFrame(preprocessed_x_test)
QI = list(range(15, 20))
anonymizer = Anonymize(ANON_K, QI, train_only_QI=True)
else: