def test_bad_marginal():
epsilon = 0.01
pXY = BEC_joint(epsilon)
pXY.set_rv_names('XY')
pX, pYgX = pXY.condition_on('X')
pX['0'] = 0
# Now make its length disagree with the number of cdists.
pX.make_sparse()
with pytest.raises(ditException):
channel_capacity(pYgX, pX)
def test_bad_marginal():
epsilon = 0.01
pXY = BEC_joint(epsilon)
pXY.set_rv_names('XY')
pX, pYgX = pXY.condition_on('X')
pX['0'] = 0
# Now make its length disagree with the number of cdists.
pX.make_sparse()
with pytest.raises(ditException):
channel_capacity(pYgX, pX)
def test_channel_capacity_array1():
epsilon = 0.3
pXY = BEC_joint(epsilon)
pX, pYgX = pXY.condition_on([0])
cc, pXopt_pmf = channel_capacity(pYgX)
# Verify channel capacity.
assert np.allclose(cc, 1 - epsilon)
# Verify maximizing distribution.
assert np.allclose(pX.pmf, pXopt_pmf)
def test_channel_capacity_array1():
epsilon = 0.3
pXY = BEC_joint(epsilon)
pX, pYgX = pXY.condition_on([0])
cc, pXopt_pmf = channel_capacity(pYgX)
# Verify channel capacity.
assert np.allclose(cc, 1 - epsilon)
# Verify maximizing distribution.
assert np.allclose(pX.pmf, pXopt_pmf)
def test_channel_capacity_array2():
epsilon = 0.3
pXY = BEC_joint(epsilon)
pX, pYgX = pXY.condition_on([0])
pYgX = cdist_array(pYgX, base='linear', mode='dense')
cc, pXopt_pmf = channel_capacity(pYgX, atol=1e-9, rtol=1e-9)
# Verify channel capacity.
assert np.allclose(cc, 1 - epsilon)
# Verify maximizing distribution.
assert np.allclose(pX.pmf, pXopt_pmf)
def test_channel_capacity_array2():
epsilon = 0.3
pXY = BEC_joint(epsilon)
pX, pYgX = pXY.condition_on([0])
pYgX = cdist_array(pYgX, base='linear', mode='dense')
cc, pXopt_pmf = channel_capacity(pYgX, atol=1e-9, rtol=1e-9)
# Verify channel capacity.
assert np.allclose(cc, 1 - epsilon)
# Verify maximizing distribution.
assert np.allclose(pX.pmf, pXopt_pmf)
def test_channel_capacity_no_rvnames():
epsilon = 0.3
pXY = BEC_joint(epsilon)
pX, pYgX = pXY.condition_on([0])
cc, pXopt = channel_capacity(pYgX, pX)
# Verify channel capacity.
assert np.allclose(cc, 1 - epsilon)
# Verify maximizing distribution.
assert pX.is_approx_equal(pXopt)
# Verify joint distribution at channel capacity.
pXYopt = joint_from_factors(pXopt, pYgX)
assert pXY.is_approx_equal(pXYopt)
def test_channel_capacity_no_rvnames():
epsilon = 0.3
pXY = BEC_joint(epsilon)
pX, pYgX = pXY.condition_on([0])
cc, pXopt = channel_capacity(pYgX, pX)
# Verify channel capacity.
assert np.allclose(cc, 1 - epsilon)
# Verify maximizing distribution.
assert pX.is_approx_equal(pXopt)
# Verify joint distribution at channel capacity.
pXYopt = joint_from_factors(pXopt, pYgX)
assert pXY.is_approx_equal(pXYopt)
