def test_client_interaction_NLS(self):
laplace = Laplace(self.A, self.eps_share)
ans = laplace.measure(self.X, self.prng)
non_neg_least_squares = NonNegativeLeastSquares()
x_est = non_neg_least_squares.infer(self.A, ans)
self.assertEqual(self.X.shape, x_est.shape)
def test_client_interaction_LS(self):
laplace = Laplace(self.A, self.eps_share)
ans = laplace.measure(self.X, self.prng)
least_squares = LeastSquares()
x_est = least_squares.infer(self.A, ans)
self.assertEqual(self.X.shape, x_est.shape)
def test_client_interaction_WNLS(self):
laplace = Laplace(self.A, self.eps_share)
ans = laplace.measure(self.X, self.prng)
engine = WorkloadNonNegativeLeastSquares(self.A)
x_est = engine.infer(self.A, ans)
self.assertEqual(self.X.shape, x_est.shape)
def test_client_interaction_MW(self):
laplace = Laplace(self.A, self.eps_share)
ans = laplace.measure(self.X, self.prng)
x_est_init = np.random.rand(self.n)
mult_weight = MultiplicativeWeights()
x_est = mult_weight.infer(self.A, ans, x_est_init)
self.assertEqual(self.X.shape, x_est.shape)
def test_laplace_operator(self):
laplace = Laplace(self.A, self.eps_share)
actual_meas = laplace.measure(self.X, np.random.RandomState(self.seed))
prng = np.random.RandomState(self.seed)
target_meas = self.n + prng.laplace(0.0, self.n / self.eps_share,
self.n)
np.testing.assert_array_equal(target_meas, actual_meas)
def test_client_interaction_HR(self):
laplace = Laplace(self.A, self.eps_share)
ans = laplace.measure(self.X, self.prng)
eps_par = 0.1
eta = 0.35
ratio = 0.85
AHP_threshold = AHPThresholding(eta, ratio)
x_est = AHP_threshold.infer(self.A, ans, eps_par)
self.assertEqual(self.X.shape, x_est.shape)