def test_duals_and_slacks(self):
for solver in yaposib.available_solvers():
prob = duals_and_slacks(solver)
yaposibTestCheck(prob, ["optimal"], sol=[4, -1, 6],
reducedcosts=[0, 12, 0], duals=[0, 1, 8],
#slacks=[2, 0, 0]
)
def test_duals_and_slacks(self):
for solver in yaposib.available_solvers():
prob = duals_and_slacks(solver)
yaposibTestCheck(
prob,
["optimal"],
sol=[4, -1, 6],
reducedcosts=[0, 12, 0],
duals=[0, 1, 8],
#slacks=[2, 0, 0]
)
def test_HotStart(self):
"""
Tests the hotstart feature.
1) solve, get a hotstart
2) wipe and resolve, knowing a hotstart now exists
3) wipe and unmark the hotstart, resolve again
"""
for solver in yaposib.available_solvers():
prob = continuous(solver)
prob.solve()
yaposibTestCheck(prob, ["optimal"], sol = [4.0, -1.0, 6.0, 0.0])
wipe_solution(prob)
prob.markHotStart()
#time = -clock()
prob.solve()
#time += clock()
yaposibTestCheck(prob, ["optimal"], sol = [4.0, -1.0, 6.0, 0.0])
wipe_solution(prob)
prob.unmarkHotStart()
prob.solve()
yaposibTestCheck(prob, ["optimal"], sol = [4.0, -1.0, 6.0, 0.0])
def test_HotStart(self):
"""
Tests the hotstart feature.
1) solve, get a hotstart
2) wipe and resolve, knowing a hotstart now exists
3) wipe and unmark the hotstart, resolve again
"""
for solver in yaposib.available_solvers():
prob = continuous(solver)
prob.solve()
yaposibTestCheck(prob, ["optimal"], sol=[4.0, -1.0, 6.0, 0.0])
wipe_solution(prob)
prob.markHotStart()
#time = -clock()
prob.solve()
#time += clock()
yaposibTestCheck(prob, ["optimal"], sol=[4.0, -1.0, 6.0, 0.0])
wipe_solution(prob)
prob.unmarkHotStart()
prob.solve()
yaposibTestCheck(prob, ["optimal"], sol=[4.0, -1.0, 6.0, 0.0])
def test_writeLp(self):
lpfile = ["\Problem name: ",
"",
"Minimize",
"OBJROW: x + 4 y + 9 z",
"Subject To",
"c1: x + y <= 5",
"c2: x + z >= 10",
"c3: - y + z = 7",
"c4: w >= 0",
"Bounds",
" 0 <= x <= 4",
" -1 <= y <= 1",
"End",]
for solver in yaposib.available_solvers():
prob = continuous(solver)
prob.writeLp("debug")
with open("debug.lp", "r") as f:
for line, ref in zip(f, lpfile):
if line.strip() != ref.strip():
error_msg = "\t%s != %s" % (line.strip(), ref.strip())
raise yaposib.YaposibError(error_msg)
def test_writeLp(self):
lpfile = [
"\Problem name: ",
"",
"Minimize",
"OBJROW: x + 4 y + 9 z",
"Subject To",
"c1: x + y <= 5",
"c2: x + z >= 10",
"c3: - y + z = 7",
"c4: w >= 0",
"Bounds",
" 0 <= x <= 4",
" -1 <= y <= 1",
"End",
]
for solver in yaposib.available_solvers():
prob = continuous(solver)
prob.writeLp("debug")
with open("debug.lp", "r") as f:
for line, ref in zip(f, lpfile):
if line.strip() != ref.strip():
error_msg = "\t%s != %s" % (line.strip(), ref.strip())
raise yaposib.YaposibError(error_msg)
def test_isProvenPrimalInfeasible(self):
for solver in yaposib.available_solvers():
prob = infeasible(solver)
yaposibTestCheck(prob, ["infeasible", "limitreached"])
if (not prob.isProvenPrimalInfeasible):
raise yaposib.YaposibError
def test_isAbandoned(self):
for solver in yaposib.available_solvers():
prob = continuous(solver)
if (not prob.isAbandoned):
raise yaposib.YaposibError
def test_isProvenOptimal(self):
for solver in yaposib.available_solvers():
prob = continuous(solver)
yaposibTestCheck(prob, ["optimal"], sol = [4.0, -1.0, 6.0, 0.0])
if (not prob.isProvenOptimal):
raise yaposib.YaposibError
def test_relaxed_mip(self):
for solver in yaposib.available_solvers():
prob = mip(solver)
prob.obj.name = "relaxed_mip"
yaposibTestCheck(prob, ["optimal"], [3.5, -1, 6.5])
def test_isDualObjectiveLimitReached(self):
for solver in yaposib.available_solvers():
prob = infeasible(solver)
yaposibTestCheck(prob, ["infeasible", "limitreached"])
if (not prob.isDualObjectiveLimitReached):
raise yaposib.YaposibError
def test_continuous(self):
for solver in yaposib.available_solvers():
prob = continuous(solver)
yaposibTestCheck(prob, ["optimal"], sol = [4.0, -1.0, 6.0, 0.0])
def test_unbounded(self):
for solver in yaposib.available_solvers():
prob = unbounded(solver)
yaposibTestCheck(prob, ["infeasible"])
def test_feasability_only(self):
for solver in yaposib.available_solvers():
prob = feasability_only(solver)
yaposibTestCheck(prob, ["optimal"])
def test_integer_infeasible(self):
for solver in yaposib.available_solvers():
prob = integer_infeasible(solver)
yaposibTestCheck(prob, ["infeasible", "limitreached"],
solve_as_MIP=True)
def test_mip(self):
for solver in yaposib.available_solvers():
prob = mip(solver)
yaposibTestCheck(prob, ["optimal"], [3.0, -0.5, 7.0],
solve_as_MIP=True)
def test_relaxed_mip(self):
for solver in yaposib.available_solvers():
prob = mip(solver)
prob.obj.name = "relaxed_mip"
yaposibTestCheck(prob, ["optimal"], [3.5, -1, 6.5])
def test_unbounded(self):
for solver in yaposib.available_solvers():
prob = unbounded(solver)
yaposibTestCheck(prob, ["infeasible"])
def test_continuous_maximisation(self):
for solver in yaposib.available_solvers():
prob = continuous_maximisation(solver)
yaposibTestCheck(prob, ["optimal"], sol=[4.0, 1.0, 8.0, 0.0])
def test_continuous(self):
for solver in yaposib.available_solvers():
prob = continuous(solver)
yaposibTestCheck(prob, ["optimal"], sol=[4.0, -1.0, 6.0, 0.0])
def test_isProvenDualInfeasible(self):
for solver in yaposib.available_solvers():
prob = unbounded(solver)
yaposibTestCheck(prob, ["infeasible"])
if (not prob.isProvenDualInfeasible):
raise yaposib.YaposibError
def test_integer_infeasible(self):
for solver in yaposib.available_solvers():
prob = integer_infeasible(solver)
yaposibTestCheck(prob, ["infeasible", "limitreached"], solve_as_MIP = True)
def test_isDualObjectiveLimitReached(self):
for solver in yaposib.available_solvers():
prob = infeasible(solver)
yaposibTestCheck(prob, ["infeasible", "limitreached"])
if (not prob.isDualObjectiveLimitReached):
raise yaposib.YaposibError
def test_isAbandoned(self):
for solver in yaposib.available_solvers():
prob = continuous(solver)
if (not prob.isAbandoned):
raise yaposib.YaposibError
def test_continuous_maximisation(self):
for solver in yaposib.available_solvers():
prob = continuous_maximisation(solver)
yaposibTestCheck(prob, ["optimal"], sol = [4.0, 1.0, 8.0, 0.0])
def test_isProvenPrimalInfeasible(self):
for solver in yaposib.available_solvers():
prob = infeasible(solver)
yaposibTestCheck(prob, ["infeasible", "limitreached"])
if (not prob.isProvenPrimalInfeasible):
raise yaposib.YaposibError
def test_mip(self):
for solver in yaposib.available_solvers():
prob = mip(solver)
yaposibTestCheck(prob, ["optimal"], [3.0, -0.5, 7.0],
solve_as_MIP = True)
def test_isProvenOptimal(self):
for solver in yaposib.available_solvers():
prob = continuous(solver)
yaposibTestCheck(prob, ["optimal"], sol=[4.0, -1.0, 6.0, 0.0])
if (not prob.isProvenOptimal):
raise yaposib.YaposibError
def test_feasability_only(self):
for solver in yaposib.available_solvers():
prob = feasability_only(solver)
yaposibTestCheck(prob, ["optimal"])
def test_isProvenDualInfeasible(self):
for solver in yaposib.available_solvers():
prob = unbounded(solver)
yaposibTestCheck(prob, ["infeasible"])
if (not prob.isProvenDualInfeasible):
raise yaposib.YaposibError
def test_available_solvers(self):
self.failIfEqual(yaposib.available_solvers(), [])
def test_available_solvers(self):
self.failIfEqual(yaposib.available_solvers(), [])
