randomized_response_bitvec.py

import numpy as np
import opendp.prelude as dp

dp.enable_features("contrib")

# Create the randomized response mechanism
m_rr = dp.m.make_randomized_response_bitvec(
    dp.bitvector_domain(max_weight=4), dp.discrete_distance(), f=0.95
)

# compute privacy loss
print(m_rr.map(1))  # -> ε = 0.8006676684558611
# formula is 2 * m * ln((2 - f) / f)
# where m = 4 (the weight) and f = .95 (the flipping probability)

# prepare a dataset to release, by encoding a bit vector as a numpy byte array
data = np.packbits(
    [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0]
)
assert np.array_equal(data, np.array([0, 8, 12], dtype=np.uint8))

# roundtrip: numpy -> bytes -> mech -> bytes -> numpy
release = np.frombuffer(m_rr(data.tobytes()), dtype=np.uint8)

# compare the two bit vectors:
print(np.unpackbits(data), np.unpackbits(release))