def test_pid_broja3():
"""
Test that iproj and ibroja are the same on reduced or.
"""
d = bivariates['reduced or']
pid1 = PID_BROJA(d)
pid2 = PID_Proj(d)
assert pid1 == pid2
def test_pid_proj1():
"""
Test iproj on a generic distribution.
"""
d = bivariates['diff']
pid = PID_Proj(d, ((0,), (1,)), (2,))
assert pid[((0,), (1,))] == pytest.approx(0.16503749927884365)
assert pid[((0,),)] == pytest.approx(0.1462406251802893)
assert pid[((1,),)] == pytest.approx(0.1462406251802893)
assert pid[((0, 1),)] == pytest.approx(0.04248125036057776)
def test_pid_proj3():
"""
Test iproj on another generic distribution.
"""
d = trivariates['xor shared']
pid = PID_Proj(d)
for atom in pid._lattice:
if atom == ((0,), (1, 2)):
assert pid[atom] == pytest.approx(1.0)
else:
assert pid[atom] == pytest.approx(0.0)
def test_pid_proj2():
"""
Test iproj on another generic distribution.
"""
d = trivariates['anddup']
pid = PID_Proj(d, [[0], [1], [2]], [3])
assert pid[((0, 1), (1, 2))] == pytest.approx(0.5)
assert pid[((0,), (1,), (2,))] == pytest.approx(0.31127812445913305)
for atom in pid._lattice:
if atom not in [((0, 1), (1, 2)), ((0,), (1,), (2,))]:
assert pid[atom] == pytest.approx(0.0)
print(rcyBROJA)
print(" ")
rcyCCS = PID_CCS(dist1, [[0], [1]], [2])
print(rcyCCS)
rcyDEP = PID_dep(dist1, [[0], [1]], [2])
print(rcyDEP)
rcyWB = PID_WB(dist1, [[0], [1]], [2])
print(rcyWB)
rcyPROJ = PID_Proj(dist1, [[0], [1]], [2])
print(rcyPROJ)
print(" ")
# Computation of the entropies
H_OBA = entropy(dist1)
H_B = entropy(dist1, [0])
H_A = entropy(dist1, [1])
H_O = entropy(dist1, [2])
H_OB = entropy(dist1, [[0], [2]])
H_OA = entropy(dist1, [[1], [2]])
H_BA = entropy(dist1, [[0], [1]])
p = PID_BROJA(dist1, [[0], [1]], [2])
output[i, 0:4] = [
p.get_partial(n)
for n in sorted(p._lattice, key=dit.pid.lattice.sort_key(p._lattice))
]
p = PID_WB(dist1, [[0], [1]], [2])
output[i, 4:8] = [
p.get_partial(n)
for n in sorted(p._lattice, key=dit.pid.lattice.sort_key(p._lattice))
]
p = PID_Proj(dist1, [[0], [1]], [2])
output[i, 8:12] = [
p.get_partial(n)
for n in sorted(p._lattice, key=dit.pid.lattice.sort_key(p._lattice))
]
p = PID_CCS(dist1, [[0], [1]], [2])
output[i, 12:16] = [
p.get_partial(n)
for n in sorted(p._lattice, key=dit.pid.lattice.sort_key(p._lattice))
]
p = PID_dep(dist1, [[0], [1]], [2])