def test_renyi_entropy_3(alpha):
"""
Test that negative orders raise ValueErrors.
"""
d = uniform(8)
with pytest.raises(ValueError):
renyi_entropy(d, alpha)
def test_renyi_entropy_3(alpha):
"""
Test that negative orders raise ValueErrors.
"""
d = uniform(8)
with pytest.raises(ValueError):
renyi_entropy(d, alpha)
def test_renyi_entropy_2(alpha):
"""
Test the Renyi entropy of joint distributions.
"""
d = Distribution(['00', '11', '22', '33'], [1 / 4] * 4)
assert renyi_entropy(d, alpha) == pytest.approx(2)
assert renyi_entropy(d, alpha, [0]) == pytest.approx(2)
assert renyi_entropy(d, alpha, [1]) == pytest.approx(2)
def test_renyi_entropy_2(alpha):
"""
Test the Renyi entropy of joint distributions.
"""
d = Distribution(['00', '11', '22', '33'], [1/4]*4)
assert renyi_entropy(d, alpha) == pytest.approx(2)
assert renyi_entropy(d, alpha, [0]) == pytest.approx(2)
assert renyi_entropy(d, alpha, [1]) == pytest.approx(2)
def test_renyi_entropy_2():
"""
Test the Renyi entropy of joint distributions.
"""
d = Distribution(['00', '11', '22', '33'], [1/4]*4)
for alpha in [0, 1/2, 1, 2, 5, np.inf]:
yield assert_almost_equal, renyi_entropy(d, alpha), 2
yield assert_almost_equal, renyi_entropy(d, alpha, [0]), 2
yield assert_almost_equal, renyi_entropy(d, alpha, [1]), 2
def test_renyi(alpha):
"""
Consistency test for Renyi entropy and Renyi divergence
"""
dist1 = Distribution(['0', '1', '2'], [1/4, 1/2, 1/4])
uniform = Distribution(['0', '1', '2'], [1/3, 1/3, 1/3])
h = renyi_entropy(dist1, alpha)
h_u = renyi_entropy(uniform, alpha)
div = renyi_divergence(dist1, uniform, alpha)
assert h == pytest.approx(h_u - div)
def test_renyi(alpha):
"""
Consistency test for Renyi entropy and Renyi divergence
"""
dist1 = Distribution(['0', '1', '2'], [1/4, 1/2, 1/4])
uniform = Distribution(['0', '1', '2'], [1/3, 1/3, 1/3])
h = renyi_entropy(dist1, alpha)
h_u = renyi_entropy(uniform, alpha)
div = renyi_divergence(dist1, uniform, alpha)
assert h == pytest.approx(h_u - div)
def test_renyi():
"""
Consistency test for Renyi entropy and Renyi divergence
"""
dist1 = Distribution(['0', '1', '2'], [1/4, 1/2, 1/4])
uniform = Distribution(['0', '1', '2'], [1/3, 1/3, 1/3])
alphas = [0, 1, 2, 0.5]
for alpha in alphas:
h = renyi_entropy(dist1, alpha)
h_u = renyi_entropy(uniform, alpha)
div = renyi_divergence(dist1, uniform, alpha)
assert_almost_equal(h, h_u - div)
def test_renyi():
"""
Consistency test for Renyi entropy and Renyi divergence
"""
dist1 = Distribution(['0', '1', '2'], [1 / 4, 1 / 2, 1 / 4])
uniform = Distribution(['0', '1', '2'], [1 / 3, 1 / 3, 1 / 3])
alphas = [0, 1, 2, 0.5]
for alpha in alphas:
h = renyi_entropy(dist1, alpha)
h_u = renyi_entropy(uniform, alpha)
div = renyi_divergence(dist1, uniform, alpha)
assert_almost_equal(h, h_u - div)
def test_renyi_entropy_1(alpha):
"""
Test that the Renyi entropy of a uniform distirbution is indipendent of the
order.
"""
d = uniform(8)
assert renyi_entropy(d, alpha) == pytest.approx(3)
def test_renyi_entropy_1(alpha):
"""
Test that the Renyi entropy of a uniform distirbution is indipendent of the
order.
"""
d = uniform(8)
assert renyi_entropy(d, alpha) == pytest.approx(3)
def test_renyi_entropy_1():
"""
Test that the Renyi entropy of a uniform distirbution is indipendent of the
order.
"""
d = uniform(8)
for alpha in [0, 1/2, 1, 2, 5, np.inf]:
yield assert_almost_equal, renyi_entropy(d, alpha), 3