def test_sia_bipartitions():
with config.override(CUT_ONE_APPROXIMATION=False):
answer = [models.Cut((1,), (2, 3, 4)),
models.Cut((2,), (1, 3, 4)),
models.Cut((1, 2), (3, 4)),
models.Cut((3,), (1, 2, 4)),
models.Cut((1, 3), (2, 4)),
models.Cut((2, 3), (1, 4)),
models.Cut((1, 2, 3), (4,)),
models.Cut((4,), (1, 2, 3)),
models.Cut((1, 4), (2, 3)),
models.Cut((2, 4), (1, 3)),
models.Cut((1, 2, 4), (3,)),
models.Cut((3, 4), (1, 2)),
models.Cut((1, 3, 4), (2,)),
models.Cut((2, 3, 4), (1,))]
assert sia_bipartitions((1, 2, 3, 4)) == answer
with config.override(CUT_ONE_APPROXIMATION=True):
answer = [models.Cut((1,), (2, 3, 4)),
models.Cut((2,), (1, 3, 4)),
models.Cut((3,), (1, 2, 4)),
models.Cut((4,), (1, 2, 3)),
models.Cut((2, 3, 4), (1,)),
models.Cut((1, 3, 4), (2,)),
models.Cut((1, 2, 4), (3,)),
models.Cut((1, 2, 3), (4,))]
assert sia_bipartitions((1, 2, 3, 4)) == answer
def s_noised_ComputeSystemIrreducibility(s_noised):
ces = compute.ces(s_noised)
cuts = sia_bipartitions(s_noised.node_indices)
return ComputeSystemIrreducibility(cuts, s_noised, ces)
def micro_s_ComputeSystemIrreducibility(micro_s):
ces = compute.ces(micro_s)
cuts = sia_bipartitions(micro_s.node_indices)
return ComputeSystemIrreducibility(cuts, micro_s, ces)
def standard_ComputeSystemIrreducibility(s):
ces = compute.ces(s)
cuts = sia_bipartitions(s.node_indices)
return ComputeSystemIrreducibility(cuts, s, ces)
