def test_hypergeometric_pmf_sum_up_to_one(self, test_range, n, y_j):
for x in test_range:
probs = [
prob for _, prob in info_theory._hypergeometric_pmf(n, x, y_j)
]
sum_prob = sum(probs)
self.assertNear(sum_prob, 1.0, EPSILON)
def testHypergeometricPmf_LargeN(self):
expected_results = [(0, 0.9508937), (1, 0.0482198), (2, 0.0008794),
(3, 7.1e-06), (4, 2.5e-08), (5, 0.0)]
results = list(info_theory._hypergeometric_pmf(1000, 5, 10))
for expected_result, result in zip(expected_results, results):
self.assertEqual(expected_result[0], result[0])
self.assertNear(expected_result[1], result[1], EPSILON)
def testHypergeometricPmf_SumUpToOne(self):
for x in range(1000, 10000):
probs = [
prob for _, prob in info_theory._hypergeometric_pmf(10000, x, 1000)
]
sum_prob = sum(probs)
self.assertNear(sum_prob, 1.0, EPSILON)
def testHypergeometricPmf(self):
expected_results = [(0, 0.75), (1, 0.25)]
results = list(info_theory._hypergeometric_pmf(4, 1, 1))
for expected_result, result in zip(expected_results, results):
self.assertEqual(expected_result[0], result[0])
self.assertNear(expected_result[1], result[1], EPSILON)