def testWrongSolver(self):
'''Test incorrect mixing of variables and solvers'''
solver1 = scip.solver()
solver2 = scip.solver()
v1 = solver1.variable()
self.assertRaises(scip.ConstraintError, solver2.constraint, v1 <= 1)
self.assertRaises(scip.SolverError, solver2.maximize, objective=v1<=3)
def testWrongSolver(self):
'''Test incorrect mixing of variables and solvers'''
solver1 = scip.solver()
solver2 = scip.solver()
v1 = solver1.variable()
self.assertRaises(scip.ConstraintError, solver2.constraint, v1 <= 1)
self.assertRaises(scip.SolverError,
solver2.maximize,
objective=v1 <= 3)
def setUp(self):
self.solver = scip.solver()
self.x1 = self.solver.variable(scip.INTEGER)
self.x2 = self.solver.variable(scip.INTEGER)
self.c1 = self.solver.constraint(2*self.x1 + 2*self.x2 <= 4)
self.c2 = self.solver.constraint(2*self.x1 + 2*self.x2 <= 3)
def update_linear_program(self):
self.compute_constraints(self.aa_ori, self.model.bpt)
solver = os.getenv('SOLVER', 'cplex')
if solver == 'glpk':
import pymprog
self.lp = pymprog.model('lp_elecre_tri_weights')
self.lp.verb = verbose
self.add_variables_glpk()
self.add_constraints_glpk()
self.add_objective_glpk()
self.solve_function = self.solve_glpk
elif solver == 'scip':
from zibopt import scip
self.lp = scip.solver(quiet=not verbose)
self.add_variables_scip()
self.add_constraints_scip()
self.add_objective_scip()
self.solve_function = self.solve_scip
elif solver == 'cplex':
import cplex
solver_max_threads = int(os.getenv('SOLVER_MAX_THREADS', 0))
self.lp = cplex.Cplex()
self.lp.parameters.threads.set(solver_max_threads)
if verbose is False:
self.lp.set_log_stream(None)
self.lp.set_results_stream(None)
# self.lp.set_warning_stream(None)
# self.lp.set_error_stream(None)
self.add_variables_cplex()
self.add_constraints_cplex()
self.add_objective_cplex()
self.solve_function = self.solve_cplex
else:
raise NameError('Invalid solver selected')
def setUp(self):
self.solver = scip.solver()
self.x1 = self.solver.variable(scip.INTEGER)
self.x2 = self.solver.variable(scip.INTEGER)
self.c1 = self.solver.constraint(2 * self.x1 + 2 * self.x2 <= 4)
self.c2 = self.solver.constraint(2 * self.x1 + 2 * self.x2 <= 3)
def testDisplayInvalidSettings(self):
'''Sets invalid display priority, position, and width'''
solver = scip.solver()
for d in solver.display.values():
self.assertRaises(scip.DisplayError, setattr, d, 'position', 'foo')
self.assertRaises(scip.DisplayError, setattr, d, 'priority', 'foo')
self.assertRaises(scip.DisplayError, setattr, d, 'width', 'foo')
def update_linear_program(self):
self.compute_constraints(self.aa_ori, self.model.bpt)
solver = os.getenv('SOLVER', 'cplex')
if solver == 'glpk':
import pymprog
self.lp = pymprog.model('lp_elecre_tri_weights')
self.lp.verb = verbose
self.add_variables_glpk()
self.add_constraints_glpk()
self.add_objective_glpk()
self.solve_function = self.solve_glpk
elif solver == 'scip':
from zibopt import scip
self.lp = scip.solver(quiet=not verbose)
self.add_variables_scip()
self.add_constraints_scip()
self.add_objective_scip()
self.solve_function = self.solve_scip
elif solver == 'cplex':
import cplex
solver_max_threads = int(os.getenv('SOLVER_MAX_THREADS', 0))
self.lp = cplex.Cplex()
self.lp.parameters.threads.set(solver_max_threads)
if verbose is False:
self.lp.set_log_stream(None)
self.lp.set_results_stream(None)
# self.lp.set_warning_stream(None)
# self.lp.set_error_stream(None)
self.add_variables_cplex()
self.add_constraints_cplex()
self.add_objective_cplex()
self.solve_function = self.solve_cplex
else:
raise NameError('Invalid solver selected')
def testPresolverSettings(self):
'''Sets presolver priority'''
solver = scip.solver()
for p in solver.presolvers.values():
x = p.priority
p.priority = x + 1
self.assertAlmostEqual(x + 1, p.priority)
def testPropagatorInvalidSettings(self):
'''Sets invalid propagator priority & frequency'''
solver = scip.solver()
for p in solver.propagators.values():
self.assertRaises(scip.PropagatorError, setattr, p, 'frequency', -2)
self.assertRaises(scip.PropagatorError, setattr, p, 'frequency', 'foo')
self.assertRaises(scip.PropagatorError, setattr, p, 'priority', 'foo')
def testConflictHandlerSettings(self):
'''Sets conflict handler priority'''
solver = scip.solver()
for c in solver.conflict.values():
x = c.priority
c.priority = x + 1
self.assertAlmostEqual(x+1, c.priority)
def testConflictHandlerSettings(self):
'''Sets conflict handler priority'''
solver = scip.solver()
for c in solver.conflict.values():
x = c.priority
c.priority = x + 1
self.assertAlmostEqual(x + 1, c.priority)
def testPresolverSettings(self):
'''Sets presolver priority'''
solver = scip.solver()
for p in solver.presolvers.values():
x = p.priority
p.priority = x + 1
self.assertAlmostEqual(x+1, p.priority)
def testDisplayInvalidSettings(self):
'''Sets invalid display priority, position, and width'''
solver = scip.solver()
for d in solver.display.values():
self.assertRaises(scip.DisplayError, setattr, d, 'position', 'foo')
self.assertRaises(scip.DisplayError, setattr, d, 'priority', 'foo')
self.assertRaises(scip.DisplayError, setattr, d, 'width', 'foo')
def testHeuristicSettings(self):
'''Sets heuristic priority, maxdepth, etc'''
solver = scip.solver()
for h in solver.heuristics.values():
for a in ('freqofs', 'frequency', 'maxdepth', 'priority'):
x = getattr(h, a)
setattr(h, a, x + 1)
self.assertAlmostEqual(x+1, getattr(h, a))
def testPropagatorSettings(self):
'''Sets propagator priority and frequency'''
solver = scip.solver()
for p in solver.propagators.values():
for a in ('frequency', 'priority'):
x = getattr(p, a)
setattr(p, a, x + 1)
self.assertAlmostEqual(x + 1, getattr(p, a))
def testNonlinearMinimize(self):
'''Tests nonlinear objective maximization'''
solver = scip.solver()
x1 = solver.variable(scip.INTEGER)
solver += 2 <= x1 <= 4
solution = solver.minimize(objective=x1**2)
self.assertAlmostEqual(solution.objective, 4.0)
self.assertAlmostEqual(solution[x1], 2.0)
def testUnbounded(self):
'''Solutions should be false when unbounded'''
solver = scip.solver()
solver.variable(coefficient=1)
solution = solver.maximize()
self.assertFalse(solution)
self.assertTrue(solution.unbounded or solution.inforunbd)
self.assertTrue(solution.objective > 0)
def testHeuristicSettings(self):
'''Sets heuristic priority, maxdepth, etc'''
solver = scip.solver()
for h in solver.heuristics.values():
for a in ('freqofs', 'frequency', 'maxdepth', 'priority'):
x = getattr(h, a)
setattr(h, a, x + 1)
self.assertAlmostEqual(x + 1, getattr(h, a))
def testBranchRuleSettings(self):
'''Sets branching priority, maxdepth, etc'''
solver = scip.solver()
for b in solver.branching.values():
for a in ('maxbounddist', 'maxdepth', 'priority'):
x = getattr(b, a)
setattr(b, a, x + 1)
self.assertAlmostEqual(x + 1, getattr(b, a))
def testDisplaySettings(self):
'''Sets display priority, position and width'''
solver = scip.solver()
for d in solver.display.values():
for a in ('position', 'priority', 'width'):
x = getattr(d, a)
setattr(d, a, x + 1)
self.assertAlmostEqual(x + 1, getattr(d, a))
def testPropagatorSettings(self):
'''Sets propagator priority and frequency'''
solver = scip.solver()
for p in solver.propagators.values():
for a in ('frequency', 'priority'):
x = getattr(p, a)
setattr(p, a, x + 1)
self.assertAlmostEqual(x+1, getattr(p, a))
def testSeparatorSettings(self):
'''Sets separator priority'''
solver = scip.solver()
for s in solver.separators.values():
for a in ('frequency', 'maxbounddist', 'priority'):
x = getattr(s, a)
setattr(s, a, x + 1)
self.assertAlmostEqual(x + 1, getattr(s, a))
def testNodeSelectorInvalidSettings(self):
'''Sets invalid node selector priorities'''
solver = scip.solver()
for n in solver.selectors.values():
self.assertRaises(scip.SelectorError, setattr, n,
'memsavepriority', 'foo')
self.assertRaises(scip.SelectorError, setattr, n, 'stdpriority',
'foo')
def testBranchRuleSettings(self):
'''Sets branching priority, maxdepth, etc'''
solver = scip.solver()
for b in solver.branching.values():
for a in ('maxbounddist', 'maxdepth', 'priority'):
x = getattr(b, a)
setattr(b, a, x + 1)
self.assertAlmostEqual(x+1, getattr(b, a))
def testNodeSelectorSettings(self):
'''Sets node selector priorities'''
solver = scip.solver()
for n in solver.selectors.values():
for a in ('memsavepriority', 'stdpriority'):
x = getattr(n, a)
setattr(n, a, x + 1)
self.assertAlmostEqual(x + 1, getattr(n, a))
def testNodeSelectorSettings(self):
'''Sets node selector priorities'''
solver = scip.solver()
for n in solver.selectors.values():
for a in ('memsavepriority', 'stdpriority'):
x = getattr(n, a)
setattr(n, a, x + 1)
self.assertAlmostEqual(x+1, getattr(n, a))
def testSeparatorSettings(self):
'''Sets separator priority'''
solver = scip.solver()
for s in solver.separators.values():
for a in ('frequency', 'maxbounddist', 'priority'):
x = getattr(s, a)
setattr(s, a, x + 1)
self.assertAlmostEqual(x+1, getattr(s, a))
def testDisplaySettings(self):
'''Sets display priority, position and width'''
solver = scip.solver()
for d in solver.display.values():
for a in ('position', 'priority', 'width'):
x = getattr(d, a)
setattr(d, a, x + 1)
self.assertAlmostEqual(x+1, getattr(d, a))
def testUnbounded(self):
'''Solutions should be false when unbounded'''
solver = scip.solver()
solver.variable(coefficient=1)
solution = solver.maximize()
self.assertFalse(solution)
self.assertTrue(solution.unbounded or solution.inforunbd)
self.assertTrue(solution.objective > 0)
def testExpressionInfeasible(self):
'''Solutions should be false for infeasibility on expressions'''
solver = scip.solver()
x1 = solver.variable()
x2 = solver.variable()
solver += x1 + x2 <= 1
solver += x1 + x2 >= 2
solution = solver.maximize()
self.assertFalse(solution)
def testBoundedVariableObjective(self):
'''Bounds on a single variable should not matter for min/max'''
solver = scip.solver()
x = solver.variable()
y = solver.variable()
solver += y >= 3
solver += x >= y
solution = solver.minimize(objective=x)
self.assertAlmostEqual(solution.objective, 3)
def testConstantInMin(self):
'''Test a constant in minimization, like minimize(objective=x-4)'''
solver = scip.solver()
x = solver.variable(lower=-1)
solution = solver.minimize(objective=x + 4)
self.assertAlmostEqual(solution.objective, 3)
solution = solver.minimize(objective=x - 5)
self.assertAlmostEqual(solution.objective, -6)
def testExpressionInfeasible(self):
'''Solutions should be false for infeasibility on expressions'''
solver = scip.solver()
x1 = solver.variable()
x2 = solver.variable()
solver += x1 + x2 <= 1
solver += x1 + x2 >= 2
solution = solver.maximize()
self.assertFalse(solution)
def testBoundedVariableObjective(self):
'''Bounds on a single variable should not matter for min/max'''
solver = scip.solver()
x = solver.variable()
y = solver.variable()
solver += y >= 3
solver += x >= y
solution = solver.minimize(objective=x)
self.assertAlmostEqual(solution.objective, 3)
def testConstantInMin(self):
'''Test a constant in minimization, like minimize(objective=x-4)'''
solver = scip.solver()
x = solver.variable(lower=-1)
solution = solver.minimize(objective=x+4)
self.assertAlmostEqual(solution.objective, 3)
solution = solver.minimize(objective=x-5)
self.assertAlmostEqual(solution.objective, -6)
def testSeparatorInvalidSettings(self):
'''Sets invalid separator priority'''
solver = scip.solver()
for s in solver.separators.values():
self.assertRaises(scip.SeparatorError, setattr, s, 'maxbounddist', -5)
self.assertRaises(scip.SeparatorError, setattr, s, 'frequency', -2)
self.assertRaises(scip.SeparatorError, setattr, s, 'maxbounddist', 'foo')
self.assertRaises(scip.SeparatorError, setattr, s, 'frequency', 'foo')
self.assertRaises(scip.SeparatorError, setattr, s, 'priority', 'foo')
def testBranchingRuleInvalidSettings(self):
'''Sets branching maxdepth, maxbounddist to values < -1'''
solver = scip.solver()
for b in solver.branching.values():
self.assertRaises(scip.BranchingError, setattr, b, 'maxbounddist', -5)
self.assertRaises(scip.BranchingError, setattr, b, 'maxdepth', -2)
self.assertRaises(scip.BranchingError, setattr, b, 'maxbounddist', 'foo')
self.assertRaises(scip.BranchingError, setattr, b, 'maxdepth', 'foo')
self.assertRaises(scip.BranchingError, setattr, b, 'priority', 'foo')
def testConstantInMax(self):
'''Test a constant in maximization, like maximize(objective=x+4)'''
solver = scip.solver()
x = solver.variable()
solver += x <= 1
solution = solver.maximize(objective=x + 4)
self.assertAlmostEqual(solution.objective, 5)
solution = solver.maximize(objective=x - 7)
self.assertAlmostEqual(solution.objective, -6)
def testHeuristicInvalidSettings(self):
'''Sets invalid heuristic priority'''
solver = scip.solver()
for h in solver.heuristics.values():
self.assertRaises(scip.HeuristicError, setattr, h, 'freqofs', -1)
self.assertRaises(scip.HeuristicError, setattr, h, 'frequency', -2)
self.assertRaises(scip.HeuristicError, setattr, h, 'maxdepth', -2)
self.assertRaises(scip.HeuristicError, setattr, h, 'freqofs', 'foo')
self.assertRaises(scip.HeuristicError, setattr, h, 'frequency', 'foo')
self.assertRaises(scip.HeuristicError, setattr, h, 'priority', 'foo')
def testConstantInMax(self):
'''Test a constant in maximization, like maximize(objective=x+4)'''
solver = scip.solver()
x = solver.variable()
solver += x <= 1
solution = solver.maximize(objective=x+4)
self.assertAlmostEqual(solution.objective, 5)
solution = solver.maximize(objective=x-7)
self.assertAlmostEqual(solution.objective, -6)
def testVariablePriority(self):
'''Sets and gets variable branching priority'''
solver = scip.solver()
x = solver.variable()
p = x.priority
x.priority = p + 1
self.assertAlmostEqual(x.priority, p + 1)
solver.maximize()
def testVariablePriority(self):
'''Sets and gets variable branching priority'''
solver = scip.solver()
x = solver.variable()
p = x.priority
x.priority = p + 1
self.assertAlmostEqual(x.priority, p + 1)
solver.maximize()
def testPropagatorInvalidSettings(self):
'''Sets invalid propagator priority & frequency'''
solver = scip.solver()
for p in solver.propagators.values():
self.assertRaises(scip.PropagatorError, setattr, p, 'frequency',
-2)
self.assertRaises(scip.PropagatorError, setattr, p, 'frequency',
'foo')
self.assertRaises(scip.PropagatorError, setattr, p, 'priority',
'foo')
def testPrimal(self):
'''Test feeding of primal solutions to the solver'''
solver = scip.solver()
v1 = solver.variable(coefficient=1, vartype=scip.INTEGER, upper=2)
v2 = solver.variable(vartype=scip.BINARY)
v3 = solver.variable()
solver.constraint(v1 <= 2)
# Pass known solution to the solver
solution = solver.maximize(solution={v1:2, v2:1, v3:5.4})
self.assertAlmostEqual(solution.objective, 2)
def testLoadSettingsNames(self):
'''Loads names of branching rules, separators, etc'''
solver = scip.solver()
self.assertTrue(solver.branching_names())
self.assertTrue(solver.conflict_names())
self.assertTrue(solver.display_names())
self.assertTrue(solver.heuristic_names())
self.assertTrue(solver.presolver_names())
self.assertTrue(solver.propagator_names())
self.assertTrue(solver.selector_names())
self.assertTrue(solver.separator_names())
def testRestart(self):
'''Test solver restart'''
solver = scip.solver()
solver.variable(coefficient=1, vartype=scip.INTEGER, upper=2)
solution = solver.maximize()
self.assertAlmostEqual(solution.objective, 2)
solver.restart()
solver.variable(coefficient=1, vartype=scip.INTEGER, upper=2)
solution = solver.maximize()
self.assertAlmostEqual(solution.objective, 4)
def testPrimal(self):
'''Test feeding of primal solutions to the solver'''
solver = scip.solver()
v1 = solver.variable(coefficient=1, vartype=scip.INTEGER, upper=2)
v2 = solver.variable(vartype=scip.BINARY)
v3 = solver.variable()
solver.constraint(v1 <= 2)
# Pass known solution to the solver
solution = solver.maximize(solution={v1: 2, v2: 1, v3: 5.4})
self.assertAlmostEqual(solution.objective, 2)
def testBadBranchingRule(self):
'''Test loading a setting that doesn't exist'''
solver = scip.solver()
self.assertRaises(scip.BranchingError, _branch.branching_rule, solver, 'NOSUCHRULE')
self.assertRaises(scip.ConflictError, _conflict.conflict, solver, 'NOSUCHRULE')
self.assertRaises(scip.DisplayError, _disp.display_column, solver, 'NOSUCHRULE')
self.assertRaises(scip.HeuristicError, _heur.heuristic, solver, 'NOSUCHRULE')
self.assertRaises(scip.PresolverError, _presol.presolver, solver, 'NOSUCHRULE')
self.assertRaises(scip.PropagatorError, _prop.propagator, solver, 'NOSUCHRULE')
self.assertRaises(scip.SelectorError, _nodesel.selector, solver, 'NOSUCHRULE')
self.assertRaises(scip.SeparatorError, _sepa.separator, solver, 'NOSUCHRULE')
def testRestart(self):
'''Test solver restart'''
solver = scip.solver()
solver.variable(coefficient=1, vartype=scip.INTEGER, upper=2)
solution = solver.maximize()
self.assertAlmostEqual(solution.objective, 2)
solver.restart()
solver.variable(coefficient=1, vartype=scip.INTEGER, upper=2)
solution = solver.maximize()
self.assertAlmostEqual(solution.objective, 4)
def testLoadSettingsNames(self):
'''Loads names of branching rules, separators, etc'''
solver = scip.solver()
self.assertTrue(solver.branching_names())
self.assertTrue(solver.conflict_names())
self.assertTrue(solver.display_names())
self.assertTrue(solver.heuristic_names())
self.assertTrue(solver.presolver_names())
self.assertTrue(solver.propagator_names())
self.assertTrue(solver.selector_names())
self.assertTrue(solver.separator_names())
def testAlgebraicConstraints(self):
'''Tests algebraic format for solver.constraint(...)'''
solver = scip.solver()
x1 = solver.variable(scip.INTEGER)
x2 = solver.variable(scip.INTEGER)
c = solver.constraint(1 <= x1 + 2 * x2 <= 4)
self.assertAlmostEqual(c.lower, 1.0)
self.assertAlmostEqual(c.upper, 4.0)
self.assertAlmostEqual(c.coefficients[(x1, )], 1.0)
self.assertAlmostEqual(c.coefficients[(x2, )], 2.0)
def testAlgebraicConstraints(self):
'''Tests algebraic format for solver.constraint(...)'''
solver = scip.solver()
x1 = solver.variable(scip.INTEGER)
x2 = solver.variable(scip.INTEGER)
c = solver.constraint(1 <= x1 + 2*x2 <= 4)
self.assertAlmostEqual(c.lower, 1.0)
self.assertAlmostEqual(c.upper, 4.0)
self.assertAlmostEqual(c.coefficients[(x1,)], 1.0)
self.assertAlmostEqual(c.coefficients[(x2,)], 2.0)
def testBilinearIntegerConstraints(self):
'''Tests nonlinear integer constraints'''
solver = scip.solver()
x1 = solver.variable(scip.INTEGER, upper=2)
x2 = solver.variable(scip.INTEGER, upper=2)
solver += 0 <= x1*x2 <= 3
solution = solver.maximize(objective=5*x1+2*x2)
self.assertAlmostEqual(solution.objective, 12.0)
self.assertAlmostEqual(solution[x1], 2.0)
self.assertAlmostEqual(solution[x2], 1.0)
def testSeparatorInvalidSettings(self):
'''Sets invalid separator priority'''
solver = scip.solver()
for s in solver.separators.values():
self.assertRaises(scip.SeparatorError, setattr, s, 'maxbounddist',
-5)
self.assertRaises(scip.SeparatorError, setattr, s, 'frequency', -2)
self.assertRaises(scip.SeparatorError, setattr, s, 'maxbounddist',
'foo')
self.assertRaises(scip.SeparatorError, setattr, s, 'frequency',
'foo')
self.assertRaises(scip.SeparatorError, setattr, s, 'priority',
'foo')
def testBranchingRuleInvalidSettings(self):
'''Sets branching maxdepth, maxbounddist to values < -1'''
solver = scip.solver()
for b in solver.branching.values():
self.assertRaises(scip.BranchingError, setattr, b, 'maxbounddist',
-5)
self.assertRaises(scip.BranchingError, setattr, b, 'maxdepth', -2)
self.assertRaises(scip.BranchingError, setattr, b, 'maxbounddist',
'foo')
self.assertRaises(scip.BranchingError, setattr, b, 'maxdepth',
'foo')
self.assertRaises(scip.BranchingError, setattr, b, 'priority',
'foo')
def testHeuristicInvalidSettings(self):
'''Sets invalid heuristic priority'''
solver = scip.solver()
for h in solver.heuristics.values():
self.assertRaises(scip.HeuristicError, setattr, h, 'freqofs', -1)
self.assertRaises(scip.HeuristicError, setattr, h, 'frequency', -2)
self.assertRaises(scip.HeuristicError, setattr, h, 'maxdepth', -2)
self.assertRaises(scip.HeuristicError, setattr, h, 'freqofs',
'foo')
self.assertRaises(scip.HeuristicError, setattr, h, 'frequency',
'foo')
self.assertRaises(scip.HeuristicError, setattr, h, 'priority',
'foo')
def testMax(self):
'''Maximize an objective subject to integer constraints'''
solver = scip.solver()
x1 = solver.variable(scip.INTEGER)
x2 = solver.variable(scip.INTEGER)
x3 = solver.variable(scip.INTEGER)
solver += x1 <= 2
solver += x1 + x2 + 3*x3 <= 3
solution = solver.maximize(objective=x1+x2+2*x3)
self.assertTrue(solution)
self.assertAlmostEqual(solution.objective, 3)
self.assertAlmostEqual(solution[x3], 0)
def testExpressionBounds(self):
'''Tests that bounds are cleared by constraint construction'''
solver = scip.solver()
x = solver.variable()
c1 = solver.constraint(x >= 2)
self.assertIsNone(x.expr_upper)
c2 = solver.constraint(3 <= x <= 4)
solution = solver.maximize(objective=x)
self.assertAlmostEqual(solution.objective, 4)
solver -= c2
solution = solver.minimize(objective=x)
self.assertAlmostEqual(solution.objective, 2)
