def test_pid_ccs1():
"""
Test iccs on a generic distribution.
"""
d = bivariates['gband']
pid = PID_CCS(d, ((0,), (1,)), (2,))
assert pid[((0,), (1,))] == pytest.approx(0.81127812445913283)
assert pid[((0,),)] == pytest.approx(0.5)
assert pid[((1,),)] == pytest.approx(0.5)
assert pid[((0, 1),)] == pytest.approx(0.0)
def test_pid_ccs4():
d = bivariates['gband']
pid = PID_CCS(d)
string = """\
+--------+--------+--------+
| I_ccs | I_r | pi |
+--------+--------+--------+
| {0:1} | 1.8113 | 0.0000 |
| {0} | 1.3113 | 0.5000 |
| {1} | 1.3113 | 0.5000 |
| {0}{1} | 0.8113 | 0.8113 |
+--------+--------+--------+"""
assert str(pid) == string
def test_pid_ccs3():
"""
Test iccs on another generic distribution.
"""
d = trivariates['anddup']
pid = PID_CCS(d)
for atom in pid._lattice:
if atom == ((0,), (1,), (2,)):
assert pid[atom] == pytest.approx(0.10375937481971094)
elif atom in [((0,), (2,)), ((1,),)]:
assert pid[atom] == pytest.approx(0.20751874963942191)
elif atom in [((2,), (0, 1)), ((0,), (1, 2)), ((0, 1), (0, 2)), ((0, 1), (1, 2)), ((0, 2), (1, 2)), ((0, 1, 2),)]:
assert pid[atom] == pytest.approx(0.14624062518028902)
elif atom in [((2,),), ((0,),), ((0, 1), (0, 2), (1, 2)), ((0, 2),)]:
assert pid[atom] == pytest.approx(-0.14624062518028902)
else:
assert pid[atom] == pytest.approx(0.0)
# Compute five PIDs and print the output
print("Partial Information Decompositions")
print(" ")
print("{0}{1} is Shd, {0} is UnqB, {1} is UnqA, {0:1} is Syn")
print(" ")
rcyBROJA = PID_BROJA(dist1, [[0], [1]], [2])
print(" ")
print(" The I_broja PID is plotted in Fig. 6 ")
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(" ")