def test_J10():
""" Test a property of J from result 4 of the paper """
d = SD([1 / 2, 1 / 4, 1 / 8, 1 / 16, 1 / 16])
j = J(d)
h = H(d)
s = sum(J(p) for p in d.pmf)
assert_almost_equal(h, s - j)
def test_J10():
""" Test a property of J from result 4 of the paper """
d = SD([1/2, 1/4, 1/8, 1/16, 1/16])
j = J(d)
h = H(d)
s = sum(J(p) for p in d.pmf)
assert h == pytest.approx(s-j)
def test_J6():
""" Test a property of J from result 2 of the paper with base 10 """
for i in range(2, 10):
d = SD([1 / i] * i)
d.set_base(10)
yield assert_almost_equal, J(d), (i - 1) * (np.log10(i) -
np.log10(i - 1))
def test_J11():
""" Test a property of J from result 5 of the paper """
pmf = np.array([1 / 2, 1 / 4, 1 / 8, 1 / 16, 1 / 16])
N = len(pmf)
d = SD(pmf)
q = SD(1 / (N - 1) * (1 - pmf))
j2 = (N - 1) * (H(q) - np.log2(N - 1))
assert_almost_equal(J(d), j2)
def test_J8():
""" Test a property of J from result 1 of the paper using log bases """
for i in range(3, 10):
d = SD([1 / i] * i)
d.set_base(i)
yield assert_true, J(d) < H(d)
def test_J7():
""" Test a property of J from result 1 of the paper """
for i in range(3, 10):
d = SD([1 / i] * i)
yield assert_true, J(d) < H(d)
def test_J4():
""" Test a property of J from result 2 of the paper """
for i in range(2, 10):
d = SD([1 / i] * i)
yield assert_almost_equal, J(d), (i - 1) * (np.log2(i) -
np.log2(i - 1))
def test_J3():
""" Test a simple base case using Distribution """
d = D(['00', '11'], [1 / 2, 1 / 2])
assert_almost_equal(J(d), 1)
assert_almost_equal(J(d, [0, 1]), 1)
def test_J2():
""" Test a simple base case using ScalarDistribution """
d = SD([1 / 2] * 2)
assert_almost_equal(J(d), 1)
def test_J2():
""" Test a simple base case using ScalarDistribution """
d = SD([1/2]*2)
assert J(d) == pytest.approx(1)
def test_J8(i):
""" Test a property of J from result 1 of the paper using log bases """
d = SD([1/i]*i)
d.set_base(i)
assert J(d) < H(d)
def test_J7(i):
""" Test a property of J from result 1 of the paper """
d = SD([1/i]*i)
assert J(d) < H(d)
def test_J6(i):
""" Test a property of J from result 2 of the paper with base 10 """
d = SD([1/i]*i)
d.set_base(10)
assert J(d) == pytest.approx((i-1)*(np.log10(i)-np.log10(i-1)))
def test_J5(i):
""" Test a property of J from result 2 of the paper with a log base """
d = SD([1/i]*i)
d.set_base('e')
assert J(d) == pytest.approx((i-1)*(np.log(i)-np.log(i-1)))
def test_J4(i):
""" Test a property of J from result 2 of the paper """
d = SD([1/i]*i)
assert J(d) == pytest.approx((i-1)*(np.log2(i) - np.log2(i-1)))
def test_J3():
""" Test a simple base case using Distribution """
d = D(['00', '11'], [1/2, 1/2])
assert J(d) == pytest.approx(1)
assert J(d, [0, 1]) == pytest.approx(1)
def test_J1():
""" Test that H = J for two probabilities """
assert_almost_equal(H(0.25), J(0.25))
def test_J1():
""" Test that H = J for two probabilities """
assert H(0.25) == pytest.approx(J(0.25))