def test_2(self):
"""1a-2-hidden: Test create_nqueens_csp with different n."""
nQueensSolver = submission.BacktrackingSearch()
nQueensSolver.solve(submission.create_nqueens_csp(4))
# BEGIN_HIDE
# END_HIDE
nQueensSolver = submission.BacktrackingSearch()
nQueensSolver.solve(submission.create_nqueens_csp(7))
def test_1(self):
"""2b-1-hidden: Test get_sum_variable with empty list of variables."""
csp = util.CSP()
sumVar = submission.get_sum_variable(csp, 'zero', [], 15)
sumSolver = submission.BacktrackingSearch()
sumSolver.solve(csp)
# BEGIN_HIDE
# END_HIDE
csp.add_unary_factor(sumVar, lambda n: n > 0)
sumSolver = submission.BacktrackingSearch()
sumSolver.solve(csp)
def test_0(self):
"""1b-0-basic: Basic test for MCV with n-queens CSP."""
mcvSolver = submission.BacktrackingSearch()
mcvSolver.solve(submission.create_nqueens_csp(8), mcv=True)
self.assertEqual(1.0, mcvSolver.optimalWeight)
self.assertEqual(92, mcvSolver.numOptimalAssignments)
self.assertEqual(1361, mcvSolver.numOperations)
def test_0(self):
"""1a-0-basic: Basic test for create_nqueens_csp for n=8."""
nQueensSolver = submission.BacktrackingSearch()
nQueensSolver.solve(submission.create_nqueens_csp(8))
self.assertEqual(1.0, nQueensSolver.optimalWeight)
self.assertEqual(92, nQueensSolver.numOptimalAssignments)
self.assertEqual(2057, nQueensSolver.numOperations)
def test_0(self):
"""0c-0-basic: Basic test for create_chain_csp."""
solver = submission.BacktrackingSearch()
solver.solve(submission.create_chain_csp(4))
self.assertEqual(1, solver.optimalWeight)
self.assertEqual(2, solver.numOptimalAssignments)
self.assertEqual(9, solver.numOperations)
def test_0(self):
"""1c-0-basic: Basic test for AC-3 with n-queens CSP"""
acSolver = submission.BacktrackingSearch()
acSolver.solve(submission.create_nqueens_csp(8), ac3=True)
self.assertEqual(1.0, acSolver.optimalWeight)
self.assertEqual(92, acSolver.numOptimalAssignments)
self.assertEqual(769, acSolver.numOperations)
def test_2(self):
"""2b-2-hidden: Test get_sum_variable with different variables."""
csp = util.CSP()
csp.add_variable('A', [0, 1, 2])
csp.add_variable('B', [0, 1, 2])
csp.add_variable('C', [0, 1, 2])
sumVar = submission.get_sum_variable(csp, 'sum-up-to-7',
['A', 'B', 'C'], 7)
sumSolver = submission.BacktrackingSearch()
sumSolver.solve(csp)
# BEGIN_HIDE
# END_HIDE
csp.add_unary_factor(sumVar, lambda n: n == 6)
sumSolver = submission.BacktrackingSearch()
sumSolver.solve(csp)
def test_3(self):
"""3b-3-hidden: Test MVC+AC-3+all additional constraints"""
profile = util.Profile(bulletin, 'profile3b3.txt')
cspConstructor = submission.SchedulingCSPConstructor(
bulletin, copy.deepcopy(profile))
csp = cspConstructor.get_basic_csp()
cspConstructor.add_all_additional_constraints(csp)
alg = submission.BacktrackingSearch()
alg.solve(csp, mcv=True, ac3=True)
def test_2(self):
"""3b-2-hidden: Test unsatisfiable scheduling"""
profile = util.Profile(bulletin, 'profile3b2.txt')
cspConstructor = submission.SchedulingCSPConstructor(
bulletin, copy.deepcopy(profile))
csp = cspConstructor.get_basic_csp()
cspConstructor.add_all_additional_constraints(csp)
alg = submission.BacktrackingSearch()
alg.solve(csp)
def test_1(self):
"""3b-1-hidden: Test add_unit_constraints with different profiles"""
profile = util.Profile(bulletin, 'profile3b1.txt')
cspConstructor = submission.SchedulingCSPConstructor(
bulletin, copy.deepcopy(profile))
csp = cspConstructor.get_basic_csp()
cspConstructor.add_unit_constraints(csp)
alg = submission.BacktrackingSearch()
alg.solve(csp)
def test_0(self):
"""2b-0-basic: Basic test for get_sum_variable"""
csp = util.CSP()
csp.add_variable('A', [0, 1, 2, 3])
csp.add_variable('B', [0, 6, 7])
csp.add_variable('C', [0, 5])
sumVar = submission.get_sum_variable(csp, 'sum-up-to-15',
['A', 'B', 'C'], 15)
csp.add_unary_factor(sumVar, lambda n: n in [12, 13])
sumSolver = submission.BacktrackingSearch()
sumSolver.solve(csp)
self.assertEqual(4, sumSolver.numOptimalAssignments)
csp.add_unary_factor(sumVar, lambda n: n == 12)
sumSolver = submission.BacktrackingSearch()
sumSolver.solve(csp)
self.assertEqual(2, sumSolver.numOptimalAssignments)
def test_2(self):
"""3a-2-hidden: Test add_quarter_constraints with no quarter specified"""
profile = util.Profile(bulletin, 'profile3a2.txt')
cspConstructor = submission.SchedulingCSPConstructor(
bulletin, copy.deepcopy(profile))
csp = cspConstructor.get_basic_csp()
cspConstructor.add_quarter_constraints(csp)
alg = submission.BacktrackingSearch()
alg.solve(csp)
def test_0(self):
"""3b-0-basic: Basic test for add_unit_constraints"""
profile = util.Profile(bulletin, 'profile3b.txt')
cspConstructor = submission.SchedulingCSPConstructor(
bulletin, copy.deepcopy(profile))
csp = cspConstructor.get_basic_csp()
cspConstructor.add_unit_constraints(csp)
alg = submission.BacktrackingSearch()
alg.solve(csp)
# Verify correctness.
self.assertEqual(15, alg.numOptimalAssignments)
for assignment in alg.allAssignments:
sol = util.extract_course_scheduling_solution(profile, assignment)
self.assertTrue(verify_schedule(bulletin, profile, sol))
for idx1 in range(10, 15):
for idx2 in range(10, 15):
if idx1 != idx2:
csp.add_binary_potential(variables[idx1], variables[idx2],
lambda x, y: x != y)
for idx1 in range(15, 20):
for idx2 in range(15, 20):
if idx1 != idx2:
csp.add_binary_potential(variables[idx1], variables[idx2],
lambda x, y: x != y)
for idx1 in range(20, 25):
for idx2 in range(20, 25):
if idx1 != idx2:
csp.add_binary_potential(variables[idx1], variables[idx2],
lambda x, y: x != y)
return csp
csp = create_zebra_problem()
search = submission.BacktrackingSearch()
search.solve(csp, mcv=True, mac=True)
print(search.optimalAssignment)
houses = collections.defaultdict(list)
for var, house in search.optimalAssignment.items():
houses[house].append(var)
print(houses)
def test_2(self):
"""1b-2-hidden: Test MCV with different CSPs."""
mcvSolver = submission.BacktrackingSearch()
mcvSolver.solve(util.create_map_coloring_csp(), mcv=True)
def test_1(self):
"""1a-1-hidden: Test create_nqueens_csp with n=3."""
nQueensSolver = submission.BacktrackingSearch()
nQueensSolver.solve(submission.create_nqueens_csp(3))
def test_4(self):
"""1c-4-hidden: Test MCV+AC-3 for map coloring CSP"""
acSolver = submission.BacktrackingSearch()
acSolver.solve(util.create_map_coloring_csp(), mcv=True, ac3=True)
def test_3(self):
"""1c-3-hidden: Test MCV+AC-3 for n-queens CSP with n=7"""
acSolver = submission.BacktrackingSearch()
nqueens_csp = self.run_with_solution_if_possible(
submission, lambda sub_or_sol: sub_or_sol.create_nqueens_csp(7))
acSolver.solve(nqueens_csp, mcv=True, ac3=True)
from __future__ import print_function
import util, submission
print('Map coloring example:')
csp = util.create_map_coloring_csp()
alg = submission.BacktrackingSearch()
alg.solve(csp)
print('One of the optimal assignments:' % alg.optimalAssignment)
print('\nWeighted CSP example:')
csp = util.create_weighted_csp()
alg = submission.BacktrackingSearch()
alg.solve(csp)
print('One of the optimal assignments:' % alg.optimalAssignment)
print('\nnqueen CSP example:')
csp = submission.create_nqueens_csp(8)
alg = submission.BacktrackingSearch()
alg.solve(csp)
print('One of the optimal assignments:' % alg.optimalAssignment)
def main():
csp = submission.create_n_queens_csp()
alg = submission.BacktrackingSearch()
alg.solve(csp, mcv=False, ac3=False)
print('One of the optimal assignments:', alg.all_assignments[0])
def test_1(self):
"""1b-1-hidden: Test for MCV with n-queens CSP."""
mcvSolver = submission.BacktrackingSearch()
nqueens_csp = self.run_with_solution_if_possible(
submission, lambda sub_or_sol: sub_or_sol.create_nqueens_csp(8))
mcvSolver.solve(nqueens_csp, mcv=True)
