def test_compose_and_get_epsilon_for_delta(self):
pld1 = privacy_loss_distribution.PrivacyLossDistribution(
{
0: 0.1,
1: 0.7,
2: 0.1
}, 0.4, 0.1)
pld2 = privacy_loss_distribution.PrivacyLossDistribution(
{
1: 0.1,
2: 0.6,
3: 0.25
}, 0.4, 0.05)
self.assertAlmostEqual(
0.29560003, pld1.get_delta_for_epsilon_for_composed_pld(pld2, 1.1))
def test_get_epsilon_for_delta(self, rounded_probability_mass_function,
value_discretization_interval,
infinity_mass, delta, expected_epsilon):
pld = privacy_loss_distribution.PrivacyLossDistribution(
rounded_probability_mass_function, value_discretization_interval,
infinity_mass)
self.assertAlmostEqual(expected_epsilon,
pld.get_epsilon_for_delta(delta))
def test_composition_with_truncation(self):
pld1 = privacy_loss_distribution.PrivacyLossDistribution(
{
0: 0.1,
1: 0.7,
2: 0.1
}, 1, 0.1)
pld2 = privacy_loss_distribution.PrivacyLossDistribution(
{
0: 0.1,
1: 0.6,
2: 0.2
}, 1, 0.1)
pld_composed = pld1.compose(pld2, tail_mass_truncation=0.021)
self.assertAlmostEqual(pld_composed.infinity_mass, 0.211)
test_util.dictionary_almost_equal(
self, {
1: 0.13,
2: 0.45,
3: 0.20,
4: 0.02,
}, pld_composed.rounded_probability_mass_function)
def test_identity(self):
pld = privacy_loss_distribution.PrivacyLossDistribution.identity()
test_util.dictionary_almost_equal(
self, pld.rounded_probability_mass_function, {0: 1})
self.assertAlmostEqual(pld.infinity_mass, 0)
pld = pld.compose(
privacy_loss_distribution.PrivacyLossDistribution({
1: 0.5,
-1: 0.5
}, 1e-4, 0))
test_util.dictionary_almost_equal(
self, pld.rounded_probability_mass_function, {
1: 0.5,
-1: 0.5
})
self.assertAlmostEqual(pld.infinity_mass, 0)