def test_count():
odp = opendp.OpenDP()
transformation = odp.trans.make_count(
b"<SymmetricDistance, L1Sensitivity<u32>, i32>")
arg = [1, 2, 3]
ret = odp.transformation_invoke(transformation, arg)
assert ret == 3
def main():
odp = opendp.OpenDP()
### HELLO WORLD
identity = odp.trans.make_identity(b"<HammingDistance, String>")
arg = "hello, world!"
res = odp.transformation_invoke(identity, arg)
print(res)
odp.core.transformation_free(identity)
### SUMMARY STATS
# Parse dataframe
col_names = odp.py_to_object([0, 1, 2])
split_dataframe = odp.trans.make_split_dataframe(b"<HammingDistance, i32>",
b",", col_names)
parse_column_1 = odp.trans.make_parse_column(
b"<HammingDistance, i32, i32>", opendp.i32_p(1), True)
parse_column_2 = odp.trans.make_parse_column(
b"<HammingDistance, i32, f64>", opendp.i32_p(2), True)
parse_dataframe = odp.make_chain_tt_multi(parse_column_2, parse_column_1,
split_dataframe)
# Noisy sum, col 1
select_1 = odp.trans.make_select_column(b"<HammingDistance, i32, i32>",
opendp.i32_p(1))
clamp_1 = odp.trans.make_clamp_vec(b"<HammingDistance, i32>",
opendp.i32_p(0), opendp.i32_p(10))
bounded_sum_1 = odp.trans.make_bounded_sum(
b"<HammingDistance, L1Sensitivity<i32>>", opendp.i32_p(0),
opendp.i32_p(10))
base_geometric_1 = odp.meas.make_base_simple_geometric(
b"<i32, f64>", opendp.f64_p(1.0), opendp.u32_p(0), opendp.u32_p(1000))
# base_laplace_1 = odp.meas.make_base_laplace(b"<i32>", opendp.f64_p(1.0))
noisy_sum_1 = odp.core.make_chain_mt(
base_geometric_1,
odp.make_chain_tt_multi(bounded_sum_1, clamp_1, select_1))
# Count, col 1
select_2 = odp.trans.make_select_column(b"<HammingDistance, i32, f64>",
opendp.i32_p(2))
count_2 = odp.trans.make_count(
b"<HammingDistance, L1Sensitivity<u32>, f64>")
base_geometric_2 = odp.meas.make_base_simple_geometric(
b"<u32, f64>", opendp.f64_p(1.0), opendp.u32_p(0), opendp.u32_p(1000))
noisy_count_2 = odp.core.make_chain_mt(
base_geometric_2, odp.make_chain_tt_multi(count_2, select_2))
# Compose & chain
composition = odp.core.make_composition(noisy_sum_1, noisy_count_2)
everything = odp.core.make_chain_mt(composition, parse_dataframe)
# Do it!!!
arg = "ant, 1, 1.1\nbat, 2, 2.2\ncat, 3, 3.3"
res = odp.measurement_invoke(everything, arg)
print(res)
# Clean up
odp.core.measurement_free(everything)
import os
from collections import Counter
import matplotlib.pyplot as plt
import numpy as np
import opendp
odp = opendp.OpenDP()
max_word_count_per_individual = 20
data_dir = os.path.abspath(os.path.join(__file__, '..', '..', '..', 'data'))
censored_data_dir = os.path.abspath(
os.path.join(__file__, '..', '..', '..', 'data_censored'))
def check_stability(scale, threshold, line_count, budget):
count_by = odp.trans.make_count_by(
b"<SymmetricDistance, L2Sensitivity<f64>, String, u32>", line_count)
base_stability = odp.meas.make_base_stability(
b"<L2Sensitivity<f64>, String, u32, f64>", line_count,
opendp.f64_p(scale), opendp.f64_p(threshold))
stability_mech = odp.core.make_chain_mt(base_stability, count_by)
# assuming each line is a different user, a user can influence up to max_word_count_per_individual counts
check = odp.measurement_check(stability_mech,
max_word_count_per_individual, budget)
odp.core.measurement_free(stability_mech)
return check
def privatize_vocabulary(word_count, line_count, budget):
def test_data_object_int():
odp = opendp.OpenDP()
val_in = 123
obj = odp.py_to_object(val_in)
val_out = odp.object_to_py(obj)
assert val_out == val_in
def test_identity_str():
odp = opendp.OpenDP()
transformation = odp.trans.make_identity(b"<HammingDistance, String>")
arg = "hello, world"
ret = odp.transformation_invoke(transformation, arg)
assert ret == arg
def test_identity_list():
odp = opendp.OpenDP()
transformation = odp.trans.make_identity(b"<HammingDistance, Vec<i32>>")
arg = [1, 2, 3]
ret = odp.transformation_invoke(transformation, arg)
assert ret == arg
def test_identity_float():
odp = opendp.OpenDP()
transformation = odp.trans.make_identity(b"<HammingDistance, f64>")
arg = 123.123
ret = odp.transformation_invoke(transformation, arg)
assert ret == arg
def test_data_object_tuple():
odp = opendp.OpenDP()
val_in = (1., 1e-7)
obj = odp.py_to_object(val_in)
val_out = odp.object_to_py(obj)
assert val_out == val_in
def test_data_object_list():
odp = opendp.OpenDP()
val_in = [1, 2, 3]
obj = odp.py_to_object(val_in)
val_out = odp.object_to_py(obj)
assert val_out == val_in
def test_init():
odp = opendp.OpenDP()
assert odp
def test_data_object_str():
odp = opendp.OpenDP()
val_in = "hello, world"
obj = odp.py_to_object(val_in)
val_out = odp.object_to_py(obj)
assert val_out == val_in
