def run_example():
n = 10**5
bucket_size = 100
epsilon = 1
print("==========>>>>> in KRR")
krr = kRR(bucket_size=bucket_size, epsilon=epsilon)
bucket_list, true_hist = example.generate_bucket(n=n,
bucket_size=bucket_size,
distribution_name='exp')
print("this is buckets: ", bucket_list)
print("this is true hist: ", true_hist)
private_bucket_list = [krr.user_encode(item) for item in bucket_list]
estimated_hist = krr.aggregate_histogram(private_bucket_list)
print("this is estimate_hist", estimated_hist)
estimated_hist_by_matrix = krr.aggregate_histogram_by_matrix(
private_bucket_list)
print("this is estimated_hist2: ", estimated_hist_by_matrix)
index = range(bucket_size)
plt.plot(index, true_hist)
plt.plot(index, estimated_hist)
plt.legend(['true', 'krr'])
plt.show()
def run_example():
bucket_size = 5
epsilon = 1
print("==========>>>>> in RAPPOR")
rappor = RAPPOR(bucket_size=bucket_size, epsilon=epsilon)
bucket_list, true_hist = example.generate_bucket(
n=10000, bucket_size=bucket_size, distribution_name='uniform')
print("this is buckets: ", bucket_list)
print("this is true hist: ", true_hist)
private_bucket_list = [rappor.user_encode(item) for item in bucket_list]
estimate_hist = rappor.aggregate_histogram(private_bucket_list)
print("this is estimate_hist", estimate_hist)
def run_example():
bucket_size = 5
epsilon = 1
print("==========>>>>> in KRR")
krr = kRR(bucket_size=bucket_size, epsilon=epsilon)
bucket_list, true_hist = example.generate_bucket(
n=10000, bucket_size=bucket_size, distribution_name='uniform')
print("this is buckets: ", bucket_list)
print("this is true hist: ", true_hist)
private_bucket_list = [krr.encode_item(item) for item in bucket_list]
estimate_hist = krr.decode_histogram(private_bucket_list)
print("this is estimate_hist", estimate_hist)
def run_example():
bucket_size = 4
epsilon = 1
n = 1000000
# np.random.seed(10)
hr = HR(bucket_size=bucket_size, epsilon=epsilon)
bucket_list, true_hist = example.generate_bucket(
n=n, bucket_size=bucket_size, distribution_name='uniform')
print("this is buckets: ", bucket_list)
print("this is true hist: ", true_hist)
print("==========>>>>> in KRR")
private_bucket_list = [hr.encode_item(item) for item in bucket_list]
print("this is private buckets: ", private_bucket_list)
estimate_hist = hr.decode_histogram(private_bucket_list)
print("this is estimate_hist", estimate_hist)
def run_example():
epsilon = 1
n = 10 ** 6
bucket_size = 1000
m = 500000
np.random.seed(10)
bucket_list, true_hist = example.generate_bucket(n=n, bucket_size=bucket_size, distribution_name='exp')
true_distribution = true_hist / sum(true_hist)
print(true_distribution[:10])
example.draw_distribution(true_distribution)
SH = SuccinctHistogram(epsilon=epsilon, d=bucket_size, m=m)
estimated_hist = SH.PROT_FO(users_data=bucket_list)
estimated_distribution = estimated_hist / sum(estimated_hist)
example.draw_distribution(estimated_distribution)
print(estimated_distribution[:10])
def run_example():
np.set_printoptions(threshold=40, linewidth=200, edgeitems=5)
n = 10 ** 5
bucket_size = 100
epsilon = 1
print("==========>>>>> in KRR")
krr = GeneralizedRandomizedResponse(bucket_size=bucket_size, epsilon=epsilon)
bucket_list, true_hist = example.generate_bucket(n=n, bucket_size=bucket_size, distribution_name='exp')
print("this is buckets: ", bucket_list)
print("this is true hist: ", true_hist)
private_bucket_list = [krr.user_encode(item) for item in bucket_list]
estimated_hist = krr.aggregate_histogram(private_bucket_list)
print("this is estimate_hist", estimated_hist)
index = range(bucket_size)
plt.plot(index, true_hist)
plt.plot(index, estimated_hist)
plt.legend(['true', 'krr'])
plt.show()