def test_pmf_1():
"""Test PMF with only one possible event"""
p = np.array([1.0])
rso = np.random.RandomState(29348)
dist = MultinomialDistribution(p, rso=rso)
assert dist.pmf(np.array([1])) == 1.0
assert dist.pmf(np.array([2])) == 1.0
assert dist.pmf(np.array([10])) == 1.0
def test_pmf_1():
"""Test PMF with only one possible event"""
p = np.array([1.0])
rso = np.random.RandomState(29348)
dist = MultinomialDistribution(p, rso=rso)
assert dist.pmf(np.array([1])) == 1.0
assert dist.pmf(np.array([2])) == 1.0
assert dist.pmf(np.array([10])) == 1.0
def test_pmf_3():
"""Test PMF with two possible events, both with nonzero probability"""
p = np.array([0.5, 0.5])
rso = np.random.RandomState(29348)
dist = MultinomialDistribution(p, rso=rso)
assert dist.pmf(np.array([1, 0])) == 0.5
assert dist.pmf(np.array([0, 1])) == 0.5
assert dist.pmf(np.array([2, 0])) == 0.25
assert dist.pmf(np.array([0, 2])) == 0.25
assert dist.pmf(np.array([1, 1])) == 0.5
def test_pmf_3():
"""Test PMF with two possible events, both with nonzero probability"""
p = np.array([0.5, 0.5])
rso = np.random.RandomState(29348)
dist = MultinomialDistribution(p, rso=rso)
assert dist.pmf(np.array([1, 0])) == 0.5
assert dist.pmf(np.array([0, 1])) == 0.5
assert dist.pmf(np.array([2, 0])) == 0.25
assert dist.pmf(np.array([0, 2])) == 0.25
assert dist.pmf(np.array([1, 1])) == 0.5
def test_pmf_2():
"""Test PMF with two possible events, one with zero probability"""
p = np.array([1.0, 0.0])
rso = np.random.RandomState(29348)
dist = MultinomialDistribution(p, rso=rso)
assert dist.pmf(np.array([1, 0])) == 1.0
assert dist.pmf(np.array([0, 1])) == 0.0
assert dist.pmf(np.array([2, 0])) == 1.0
assert dist.pmf(np.array([2, 2])) == 0.0
assert dist.pmf(np.array([10, 0])) == 1.0
assert dist.pmf(np.array([10, 3])) == 0.0
p = np.array([0.0, 1.0])
rso = np.random.RandomState(29348)
dist = MultinomialDistribution(p, rso=rso)
assert dist.pmf(np.array([0, 1])) == 1.0
assert dist.pmf(np.array([1, 0])) == 0.0
assert dist.pmf(np.array([0, 2])) == 1.0
assert dist.pmf(np.array([2, 2])) == 0.0
assert dist.pmf(np.array([0, 10])) == 1.0
assert dist.pmf(np.array([3, 10])) == 0.0
def test_pmf_2():
"""Test PMF with two possible events, one with zero probability"""
p = np.array([1.0, 0.0])
rso = np.random.RandomState(29348)
dist = MultinomialDistribution(p, rso=rso)
assert dist.pmf(np.array([1, 0])) == 1.0
assert dist.pmf(np.array([0, 1])) == 0.0
assert dist.pmf(np.array([2, 0])) == 1.0
assert dist.pmf(np.array([2, 2])) == 0.0
assert dist.pmf(np.array([10, 0])) == 1.0
assert dist.pmf(np.array([10, 3])) == 0.0
p = np.array([0.0, 1.0])
rso = np.random.RandomState(29348)
dist = MultinomialDistribution(p, rso=rso)
assert dist.pmf(np.array([0, 1])) == 1.0
assert dist.pmf(np.array([1, 0])) == 0.0
assert dist.pmf(np.array([0, 2])) == 1.0
assert dist.pmf(np.array([2, 2])) == 0.0
assert dist.pmf(np.array([0, 10])) == 1.0
assert dist.pmf(np.array([3, 10])) == 0.0
