def test_tse1(i, j):
""" Test identity comparing TSE to B from Olbrich's talk """
d = n_mod_m(i, j)
indices = [[k] for k in range(i)]
tse = TSE(d)
x = 1 / 2 * sum(B(d, rv) / nCk(i, len(rv)) for rv in powerset(indices))
assert tse == pytest.approx(x)
def test_tse1():
""" Test identity comparing TSE to B from Olbrich's talk """
for i, j in zip(range(3, 6), range(2, 5)):
d = n_mod_m(i, j)
indices = [[k] for k in range(i)]
tse = TSE(d)
x = 1/2 * sum(B(d, rv)/nCk(i, len(rv)) for rv in powerset(indices))
yield assert_almost_equal, tse, x
def test_tse2(n):
""" Test TSE for giant bit distributions """
d = D(['0' * n, '1' * n], [1 / 2, 1 / 2])
tse = TSE(d)
assert tse == pytest.approx((n - 1) / 2)
def test_tse2():
""" Test TSE for giant bit distributions """
for n in range(2, 7):
d = D(['0'*n, '1'*n], [1/2, 1/2])
tse = TSE(d)
yield assert_almost_equal, tse, (n-1)/2