def check_persistence(graph, terminals, persistence_type):
"""Tests for WEAK or STRONG persistence in graph with terminals.
WEAK persistence means that values which are 1 in the LP relaxation remain 1 in
an optimal IP solution.
STRONG persistence means that values which are 0 in the LP relaxation remain 0 in
an optimal IP solution.
Args:
graph: the undirected NetworkX graph for testing persistence
terminals: the vertices in the graph which are terminals
persistence_type: "strong" or "weak"
Returns:
test_result: TRUE if persistence holds, FALSE if it does not
"""
_, unseeded_value, _ = isolation_branching(graph, terminals)
_, seeded_value, _ = isolation_branching(graph,
terminals,
persistence=persistence_type)
test_result = round(unseeded_value, 8) == round(seeded_value, 8)
return test_result
def time_test_simple(
graph, terminals, test_bb, test_bb_weak, test_bb_strong, test_ip_cbc, test_ip_gurobi
):
"""Runs a single time test of each of the algorithms (B&B, B&B-weak, B&B-strong, IP)."""
t1 = time.time()
ib_rpt = None
if test_bb:
_, _, ib_rpt = isolation_branching(graph.copy(), terminals, reporting=False, time_limit=3600)
t2 = time.time()
ib_weak_rpt = None
if test_bb_weak:
_, _, ib_weak_rpt = isolation_branching(
graph.copy(), terminals, persistence="weak"
)
t3 = time.time()
ib_strong_rpt = None
if test_bb_strong:
_, _, ib_strong_rpt = isolation_branching(
graph.copy(), terminals, persistence="strong"
)
t4 = time.time()
ip_cbc_rpt = None
if test_ip_cbc:
_, _ = ip_algorithm(graph.copy(), terminals)
t5 = time.time()
ip_gurobi_rpt = None
if test_ip_gurobi:
_, _ = ip_algorithm(
graph.copy(), terminals, solver=GUROBI(msg=False)
)
t6 = time.time()
return (
(t2 - t1, ib_rpt),
(t3 - t2, ib_weak_rpt),
(t4 - t3, ib_strong_rpt),
(t5 - t4, ip_cbc_rpt),
(t6 - t5, ip_gurobi_rpt),
)
def test_graph_5():
from ktcut.isolation_branching import isolation_branching
from ktcut.lp_algorithm import lp_algorithm
test_graphs = SmallGraphs()
test_graphs.set_test_graph(5)
graph, terminals = test_graphs.get_graph(), test_graphs.get_terminals()
_, cut_value, _ = isolation_branching(graph,
terminals,
persistence='strong')
assert cut_value == 110
cut_value = lp_algorithm(graph, terminals)
assert cut_value == 110
def test_graph_4():
from ktcut.isolation_branching import isolation_branching
from ktcut.ip_algorithm import ip_algorithm
from ktcut.lp_algorithm import lp_algorithm
from ktcut.persistence import check_persistence
test_graphs = SmallGraphs()
test_graphs.set_test_graph(4)
graph, terminals = test_graphs.get_graph(), test_graphs.get_terminals()
_, cut_value, _ = isolation_branching(graph, terminals)
assert cut_value == 27
_, cut_value = ip_algorithm(graph, terminals)
assert cut_value == 27
cut_value = lp_algorithm(graph, terminals)
assert cut_value == 26
assert check_persistence(graph, terminals, 'weak')
assert check_persistence(graph, terminals, 'strong')
def test_graph_tutte():
from networkx.generators.small import tutte_graph
from ktcut.isolation_branching import isolation_branching
graph = tutte_graph()
terminals = [1, 17, 34]
partition, cut_value, _ = isolation_branching(graph, terminals)
