def test_union1(self):
a = CountingFilter(n, p)
b = CountingFilter(n, p)
for i in range(1000):
a.insert(str(i))
for i in range(1000, 2000):
b.insert(str(i))
a.union(b)
# If the union Bloom Filter actually contains an element, it should always say it does
for i in range(2000):
self.assertTrue(a.contains(str(i)))
# If a Bloom Filter does not contain an element, there is a chance of false positives, which will be calculated
# by the get_false_positive_rate method
errors = 0
for i in range(-1, -1001, -1):
if a.contains(str(i)):
errors = errors + 1
print("number of errors is" ,errors)
fpr = self.get_false_positive_rate(n * 2, a.getBitSize(), a.getHashCount())
print("false positive rate is ", fpr)
self.assertTrue(errors < n * (fpr + buffer))
def test_intersection3(self):
a = CountingFilter(n, p)
b = CountingFilter(n, p)
c = CountingFilter(n, p)
for i in range(1000):
a.insert(str(i))
for i in range(500, 1000):
b.insert(str(i))
for i in range(600, 700):
c.insert(str(i))
b.intersection(c)
a.intersection(b)
fpr = self.get_false_positive_rate(100, a.getBitSize(), a.getHashCount()) # only 100 elements in intersect
# False positive errors should be expected in this range
errors = 0
for i in range(600):
if a.contains(str(i)):
errors = errors + 1
self.assertTrue(errors < n * (fpr + buffer))
# 100% accuracy is expected in this range
for i in range(600, 700):
self.assertTrue(a.contains(str(i)))
# False positive errors should be expected in this range
errors = 0
for i in range(700, 1000):
if a.contains(str(i)):
errors = errors + 1
self.assertTrue(errors < n * (fpr + buffer))
def test_insert_contains(self):
s = CountingFilter(n, p)
tempList = []
for i in range(1000):
tempList.append(i)
random.shuffle(tempList)
for i in tempList:
s.insert(str(i))
# If the Counting Filter actually contains an element, it should always say it does
for i in range(1000):
self.assertTrue(s.contains(str(i)))
# If a Counting Filter does not contain an element, there is a ~5% chance of a false positive
errors = 0
for i in range(-1, -1001, -1):
if s.contains(str(i)):
errors = errors + 1
print(errors)
self.assertTrue(errors < n * (p + buffer))
def test_intersection2(self):
a = CountingFilter(n, p)
b = CountingFilter(n, p)
for i in range(1000):
a.insert(str(i))
for i in range(500, 1000):
b.insert(str(i))
a.intersection(b)
# There are no elements from 0 - 499, so in this range the bloom filter should only contain false postives
errors = 0
for i in range(500):
if a.contains(str(i)):
errors = errors + 1
print("intersect2 errors", errors)
fpr = self.get_false_positive_rate(500, a.getBitSize(), a.getHashCount()) # only 500 elements in intersect
print("intersect2 fpr", fpr)
self.assertTrue(errors < n * (fpr + buffer))
# These elements all should be in the intersection, so they must be in the intersect bloom filter
for i in range(500, 1000, 1):
self.assertTrue(a.contains(str(i)))
def test_intersection1(self):
a = CountingFilter(n, p / 50) # we need to use a slightly smaller fpr here so we don't have too many intersects
b = CountingFilter(n, p / 50)
for i in range(1000):
a.insert(str(i))
for i in range(1000, 2000):
b.insert(str(i))
a.intersection(b)
# There are no elements in the intersection, so this bloom filter should contain nothing except for a few
# elements caused by hash collisions
errors = 0
for i in range(2000):
if a.contains(str(i)):
errors = errors + 1
print("number of intersections is", errors)
self.assertTrue(errors < n * 0.01)