def test_accountant(self):
acc = BudgetAccountant(1.5, 0)
a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]]).T
histogramdd(a,
epsilon=1,
bins=3,
range=[(0, 10), (0, 10)],
density=True,
accountant=acc)
with self.assertRaises(BudgetError):
histogramdd(a,
epsilon=1,
bins=3,
range=[(0, 10), (0, 10)],
density=True,
accountant=acc)
def test_different_result(self):
global_seed(3141592653)
a = np.array([1, 2, 3, 4, 5])
hist, _ = np.histogramdd(a, bins=3, range=[(0, 10)])
dp_hist, _ = histogramdd(a, epsilon=0.1, bins=3, range=[(0, 10)])
# print("Non-private histogram: %s" % hist)
# print("Private histogram: %s" % dp_hist)
self.assertTrue((hist != dp_hist).any())
def test_density_2d(self):
global_seed(3141592653)
a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]]).T
dp_hist, _ = histogramdd(a,
epsilon=10,
bins=3,
range=[(0, 10), (0, 10)],
density=True)
# print(dp_hist.sum())
self.assertAlmostEqual(dp_hist.sum(), 1.0 * (3 / 10)**2)
def test_density_1d(self):
global_seed(3141592653)
a = np.array([1, 2, 3, 4, 5])
dp_hist, _ = histogramdd(a,
epsilon=1,
bins=3,
range=[(0, 10)],
density=True)
# print(dp_hist.sum())
self.assertAlmostEqual(dp_hist.sum(), 1.0 * 3 / 10)
def test_no_params(self):
a = np.array([1, 2, 3, 4, 5])
with self.assertWarns(PrivacyLeakWarning):
res = histogramdd(a)
self.assertIsNotNone(res)
def test_no_range(self):
a = np.array([1, 2, 3, 4, 5])
with self.assertWarns(PrivacyLeakWarning):
res = histogramdd(a, epsilon=2)
self.assertIsNotNone(res)
def test_bins_instead_of_range(self):
a = np.array([1, 2, 3, 4, 5])
res = histogramdd([a, a], epsilon=2, bins=([0, 2, 6], [0, 2, 6]))
self.assertIsNotNone(res)