def test_sample_without_replacement():
array = np.ones(100)
node_single = DataNode()
node_single.set_private_data(name="array", data=array)
sample_size = 50
def u(x, r):
output = np.zeros(len(r))
for i in range(len(r)):
output[i] = r[i] * sum(np.greater_equal(x, r[i]))
return output
r = np.arange(0, 3.5, 0.001)
delta_u = r.max()
epsilon = 5
exponential_mechanism = ExponentialMechanism(u,
r,
delta_u,
epsilon,
size=sample_size)
access_modes = [LaplaceMechanism(1, 1)]
access_modes.append(GaussianMechanism(1, (0.5, 0.5)))
access_modes.append(RandomizedResponseBinary(0.5, 0.5, 1))
access_modes.append(RandomizedResponseCoins())
access_modes.append(exponential_mechanism)
for a in access_modes:
sampling_method = SampleWithoutReplacement(a, sample_size, array.shape)
node_single.configure_data_access("array", sampling_method)
result = node_single.query("array")
assert result.shape[0] == sample_size
def test_randomize_binary_mechanism_no_binary_coins():
data_size = 100
array = np.random.rand(data_size)
federated_array = shfl.private.federated_operation.federate_array(
array, data_size)
federated_array.configure_data_access(RandomizedResponseCoins())
with pytest.raises(ValueError):
federated_array.query()
def test_randomize_binary_mechanism_scalar_coins():
scalar = 1
node_single = DataNode()
node_single.set_private_data(name="scalar", data=scalar)
node_single.configure_data_access("scalar", RandomizedResponseCoins())
result = node_single.query(private_property="scalar")
assert np.isscalar(result)
assert result == 0 or result == 1
def test_randomize_binary_mechanism_array_almost_always_true_values_coins():
array = np.ones(1000)
node_single = DataNode()
node_single.set_private_data(name="array", data=array)
# Very low heads probability in the first attempt, mean should be near true value
data_access_definition = RandomizedResponseCoins(prob_head_first=0.01,
prob_head_second=0.9)
node_single.configure_data_access("array", data_access_definition)
result = node_single.query("array")
assert 1 - np.mean(result) < 0.05
def test_randomize_binary_mechanism_array_coins():
array = np.ones(100)
node_single = DataNode()
node_single.set_private_data(name="array", data=array)
node_single.configure_data_access("array", RandomizedResponseCoins())
result = node_single.query("array")
differences = 0
for i in range(100):
if result[i] != array[i]:
differences = differences + 1
assert not np.isscalar(result)
assert 0 < differences < 100
assert np.mean(result) < 1
def test_randomize_binary_mechanism_coins():
data_size = 100
array = np.ones(data_size)
federated_array = shfl.private.federated_operation.federate_array(
array, data_size)
federated_array.configure_data_access(RandomizedResponseCoins())
result = federated_array.query()
differences = 0
for i in range(data_size):
if result[i] != array[i]:
differences = differences + 1
assert 0 < differences < data_size
assert np.mean(result) < 1
def test_randomized_response_coins_epsilon_delta():
randomized_response_coins = RandomizedResponseCoins()
assert randomized_response_coins.epsilon_delta is not None