def test_write(self):
results = SolverResults()
results.write(StringIO())
del results.objective
results.write(StringIO())
results.junk = 1
results.write(StringIO())
def _test_delayed_unbounded_min(comm):
solver = Solver(comm=comm)
baseline = SolverResults()
baseline.solution_status = "unbounded"
baseline.termination_condition = "no_nodes"
baseline.objective = -inf
baseline.bound = -inf
baseline.nodes = _ignore_value_
baseline.wall_time = _ignore_value_
problem = delayed_unbounded_min.DelayedUnboundedMin()
_execute_single_test(problem, baseline, solver=solver)
for queue_strategy in sorted(pybnb.QueueStrategy):
if queue_strategy == "custom":
continue
_execute_single_test(problem,
baseline,
solver=solver,
queue_strategy=queue_strategy)
def _test_root_infeasible_min(comm):
solver = Solver(comm=comm)
baseline = SolverResults()
baseline.solution_status = "infeasible"
baseline.termination_condition = "optimality"
baseline.objective = inf
baseline.bound = inf
baseline.nodes = 1
baseline.wall_time = _ignore_value_
problem = root_infeasible_min.RootInfeasibleMin()
_execute_single_test(problem, baseline, solver=solver)
for queue_strategy in sorted(pybnb.QueueStrategy):
if queue_strategy == "custom":
continue
_execute_single_test(problem,
baseline,
solver=solver,
queue_strategy=queue_strategy)
def _test_infeasible_max(comm):
solver = None
if comm is not None:
solver = Solver(comm=comm)
baseline = SolverResults()
baseline.solution_status = "infeasible"
baseline.termination_condition = "optimality"
baseline.objective = -inf
baseline.bound = -inf
baseline.nodes = 255
baseline.wall_time = _ignore_value_
problem = infeasible_max.InfeasibleMax()
if comm is None:
_execute_tests(comm, problem, baseline)
else:
_execute_single_test(problem, baseline, solver=solver)
baseline = SolverResults()
baseline.solution_status = "unknown"
baseline.termination_condition = "no_nodes"
baseline.objective = -inf
baseline.bound = -16
baseline.nodes = 31
baseline.wall_time = _ignore_value_
problem = infeasible_max.InfeasibleMax(branching_abstol=0.1)
if comm is None:
_execute_tests(comm, problem, baseline)
else:
_execute_single_test(problem, baseline, solver=solver)
baseline = SolverResults()
baseline.solution_status = "unknown"
baseline.termination_condition = "objective_limit"
baseline.objective = -inf
baseline.bound = -16
baseline.nodes = 31
baseline.wall_time = _ignore_value_
problem = infeasible_max.InfeasibleMax(branching_abstol=0.1)
if comm is None:
_execute_tests(comm, problem, baseline, bound_stop=-15)
else:
_execute_single_test(problem, baseline, solver=solver, bound_stop=-15)
baseline = SolverResults()
baseline.solution_status = "feasible"
baseline.termination_condition = "objective_limit"
baseline.objective = -20
baseline.bound = -16
baseline.absolute_gap = 4
baseline.relative_gap = 0.2
baseline.nodes = 31
baseline.wall_time = _ignore_value_
problem = infeasible_max.InfeasibleMax(branching_abstol=0.1,
fixed_objective=-20)
if comm is None:
_execute_tests(comm, problem, baseline, bound_stop=-15)
else:
_execute_single_test(problem, baseline, solver=solver, bound_stop=-15)
baseline = SolverResults()
baseline.solution_status = "unknown"
baseline.termination_condition = "node_limit"
baseline.objective = -inf
baseline.bound = -16
baseline.nodes = 31
baseline.wall_time = _ignore_value_
problem = infeasible_max.InfeasibleMax()
if comm is None:
_execute_tests(comm, problem, baseline, node_limit=31)
elif comm.size <= 2:
# skip for larger comm sizes
# as the node_limit can lead to
# a number of different outcomes
_execute_single_test(problem, baseline, solver=solver, node_limit=31)
baseline = SolverResults()
baseline.solution_status = "feasible"
baseline.termination_condition = "node_limit"
baseline.objective = -17
baseline.bound = -16
baseline.absolute_gap = 1.0
baseline.relative_gap = 1.0 / 17
baseline.nodes = 31
baseline.wall_time = _ignore_value_
problem = infeasible_max.InfeasibleMax(fixed_objective=-17)
if comm is None:
_execute_tests(comm, problem, baseline, node_limit=31)
elif comm.size <= 2:
# skip for larger comm sizes
# as the node_limit can lead to
# a number of different outcomes
_execute_single_test(problem, baseline, solver=solver, node_limit=31)
baseline = SolverResults()
baseline.solution_status = "unknown"
baseline.termination_condition = "time_limit"
baseline.objective = -inf
baseline.bound = inf
baseline.nodes = 0
baseline.wall_time = _ignore_value_
problem = infeasible_max.InfeasibleMax()
if comm is None:
_execute_tests(comm, problem, baseline, time_limit=0)
else:
_execute_single_test(problem, baseline, solver=solver, time_limit=0)
if solver is None:
solver = Solver(comm=comm)
baseline = SolverResults()
baseline.solution_status = "infeasible"
baseline.termination_condition = "optimality"
baseline.objective = -inf
baseline.bound = -inf
baseline.nodes = 255
baseline.wall_time = _ignore_value_
problem = infeasible_max.InfeasibleMax()
for queue_strategy in sorted(pybnb.QueueStrategy):
if queue_strategy == "custom":
continue
_execute_single_test(problem,
baseline,
solver=solver,
queue_strategy=queue_strategy)
def _test_zero_objective_min(comm):
solver = Solver(comm=comm)
baseline = SolverResults()
baseline.solution_status = "optimal"
baseline.termination_condition = "optimality"
baseline.objective = 0.0
baseline.bound = -0.0078125
baseline.absolute_gap = 0.0078125
baseline.relative_gap = 0.0078125
baseline.nodes = 255
baseline.wall_time = _ignore_value_
problem = zero_objective_min.ZeroObjectiveMin()
_execute_single_test(problem,
baseline,
solver=solver,
relative_gap=0.01,
absolute_gap=0.01)
_execute_single_test(problem,
baseline,
solver=solver,
relative_gap=0.0,
absolute_gap=0.01)
_execute_single_test(problem,
baseline,
solver=solver,
relative_gap=0.01,
absolute_gap=0.0)
baseline = SolverResults()
baseline.solution_status = "optimal"
baseline.termination_condition = "optimality"
baseline.objective = 0.0
baseline.bound = -0.0009765625
baseline.absolute_gap = 0.0009765625
baseline.relative_gap = 0.0009765625
baseline.nodes = 2047
baseline.wall_time = _ignore_value_
problem = zero_objective_min.ZeroObjectiveMin()
_execute_single_test(problem,
baseline,
solver=solver,
relative_gap=0.001,
absolute_gap=0.001)
_execute_single_test(problem,
baseline,
solver=solver,
relative_gap=0.0,
absolute_gap=0.001)
_execute_single_test(problem,
baseline,
solver=solver,
relative_gap=0.001,
absolute_gap=0.0)
baseline = SolverResults()
baseline.solution_status = "feasible"
baseline.termination_condition = "no_nodes"
baseline.objective = 0.0
baseline.bound = -0.0009765625
baseline.absolute_gap = 0.0009765625
baseline.relative_gap = 0.0009765625
baseline.nodes = 2047
baseline.wall_time = _ignore_value_
problem = zero_objective_min.ZeroObjectiveMin()
_execute_single_test(problem,
baseline,
solver=solver,
relative_gap=0.0001,
absolute_gap=0.0001)
_execute_single_test(problem,
baseline,
solver=solver,
relative_gap=0.0,
absolute_gap=0.0001)
_execute_single_test(problem,
baseline,
solver=solver,
relative_gap=0.0001,
absolute_gap=0.0)
baseline = SolverResults()
baseline.solution_status = "optimal"
baseline.termination_condition = "optimality"
baseline.objective = 0.0
baseline.bound = -0.0078125
baseline.absolute_gap = 0.0078125
baseline.relative_gap = 0.0078125
baseline.nodes = None
baseline.wall_time = _ignore_value_
problem = zero_objective_min.ZeroObjectiveMin()
for queue_strategy in sorted(pybnb.QueueStrategy):
if queue_strategy == "custom":
continue
if queue_strategy == "depth":
baseline.nodes = 2033
elif queue_strategy == "random":
baseline.nodes = _ignore_value_
else:
baseline.nodes = 255
_execute_single_test(problem,
baseline,
solver=solver,
relative_gap=0.01,
absolute_gap=0.01,
queue_strategy=queue_strategy)