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test_histogram.py
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/
test_histogram.py
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import numpy as np
from unittest import TestCase
from diffprivlib.tools.histograms import histogram
from diffprivlib.utils import global_seed
class TestHistogram(TestCase):
def test_no_params(self):
a = np.array([1, 2, 3, 4, 5])
with self.assertWarns(RuntimeWarning):
res = histogram(a)
self.assertIsNotNone(res)
def test_no_range(self):
a = np.array([1, 2, 3, 4, 5])
with self.assertWarns(RuntimeWarning):
res = histogram(a, epsilon=1)
self.assertIsNotNone(res)
def test_same_edges(self):
a = np.array([1, 2, 3, 4, 5])
_, edges = np.histogram(a, bins=3, range=(0, 10))
_, dp_edges = histogram(a, epsilon=1, bins=3, range=(0, 10))
self.assertTrue((edges == dp_edges).all())
def test_different_result(self):
global_seed(3141592653)
a = np.array([1, 2, 3, 4, 5])
hist, _ = np.histogram(a, bins=3, range=(0, 10))
dp_hist, _ = histogram(a, epsilon=0.1, bins=3, range=(0, 10))
# print("Non-private histogram: %s" % hist)
# print("Private histogram: %s" % dp_hist)
self.assertTrue((hist != dp_hist).any())
def test_density(self):
global_seed(3141592653)
a = np.array([1, 2, 3, 4, 5])
dp_hist, _ = histogram(a, epsilon=0.1, bins=3, range=(0, 10), density=True)
# print(dp_hist.sum())
self.assertAlmostEqual(dp_hist.sum(), 1.0 * 3 / 10)